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Compressed Baryonic Matter Experiment<br />
Technical Status Report<br />
CBM experiment<br />
January 2005<br />
CBM collaboration
ii<br />
Sketch of the planned Compressed Baryonic Matter (CBM) experiment with the HADES spectrometer<br />
positioned in front of it. The CBM setup consists of a superconducting dipole magnet with a Silicon<br />
tracker System insi<strong>de</strong>, a Rich Imaging Cherenkov <strong>de</strong>tector (RICH) for electron i<strong>de</strong>ntification, the three<br />
Transition Radiation Detectors (TRD), the Time-Of Flight (TOF) wall which is a Resistive Plate Chamber<br />
(RPC), and the electromagnetic calorimeter (ECAL). The total length of the setup is approximately 12 m<br />
from target at the entrance of the dipole to the ECAL.
The CBM Collaboration<br />
• Bergen, Norway, Department of Physics and Technology, University of Bergen<br />
D. Röhrich, K. Ullaland<br />
• Bucharest, Romania, National Institute for Physics and Nuclear Engineering<br />
C. Aiftimiei, V. Catanescu, D. Moisa, M. Petris, A. Petrovici, M. Petrovici, A. Raduta, G. Stoicea<br />
• Budapest, Hungary, Eötvös University<br />
F. Deak, R. Izsak, A. Kiss<br />
• Budapest, Hungary, KFKI<br />
E. Denes, Z. Fodor, J. Kecskemeti, Cs. Soos, T. Kiss, G. Vesztergombi<br />
• Coimbra, Portugal, LIP<br />
P. Fonte, R. Ferreira Marques, A. Policarpo<br />
• Darmstadt, Germany, <strong>GSI</strong><br />
M. Al-Turany, A. Andronic, E. Badura, E. Ber<strong>de</strong>rmann, D. Bertini, P. Braun-Munzinger, M. Ciobanu,<br />
H. Deppe, M. Deveaux, J. Eschke, H. Essel, H. Flemming, V. Friese, T. Galatyuk, C. Garabatos,<br />
C. Höhne, R. Holzmann, E. Jimenes, M. Kalisky, A. Kiseleva, K. Koch, P. Koczon, W. König,<br />
B. Kolb, G. Kružić, Y. Leifels, S. Linev, C. Lippmann, W.F.J. Müller, W. Niebur, A. Schüttauf,<br />
K. Schwarz, P. Senger, R. Simon, F. Uhlig, I. Vassiliev<br />
• Dubna, Russia, JINR-LHE<br />
V. Chepurnov, S. Chernenko, O. Fateev, V. Golovatyuk, A. Ierusalimov, V. Ladygin, A. Malakhov,<br />
E. Matyushevsky, E. Plekhanov, V. Pozdniakov, O. Rogachevsky, Yu. Zanevsky, V. Zrjuev<br />
• Dubna, Russia, JINR-LPP<br />
Ju. Gousakov, N. Grigalashvili, G. Kekelidze, V. Lucenko, S. Mishin, D. Peshekhonov, V. Peshekhonov,<br />
O. Strekalovsky, K. Viriasov, J. Zlobin<br />
• Dubna, Russia, JINR-LIT<br />
P. Akishin, E. Akishina, S. Baginyan, Victor Ivanov, Valery Ivanov, B. Kostenko, E. Litvinenko,<br />
G. Ososkov, A. Raportirenko, A. Soloviev, P. Zrelov, V. Uzhinsky<br />
• Dubna, Russia, JINR-LTP 1<br />
D. Blaschke, V. Burov, V. Toneev<br />
• Frankfurt, Germany, Institut für Kernphysik, Universität Frankfurt<br />
H. Appelshäuser, C. Müntz, H. Ströbele, J. Stroth<br />
• Hei<strong>de</strong>lberg, Germany, 2. Physikalisches Institut, Universität Hei<strong>de</strong>lberg<br />
M.L. Benab<strong>de</strong>rahmane, E. Cordier, N. Herrmann, A. Mangiarotti<br />
• Hei<strong>de</strong>lberg, Germany, Kirchhoff-Institut für Physik, Universität Hei<strong>de</strong>lberg<br />
D. Atanasov, U. Kebschull (Universität Leipzig), I. Kisel, V. Lin<strong>de</strong>nstruth, G. Torralba, G. Tröger<br />
iii
iv<br />
• Kaiserslautern, Deutschland, Universität Kaiserslautern 1<br />
D. Muthers, R. Tielert, S. Tontisirin<br />
• Katowice, Poland, University of Silesia<br />
A. Bubak, A. Grzeszczuk, S. Kowalski, M. Krauze, E. Stephan, W. Zipper<br />
• Krakow, Poland, Jagiellonian University<br />
J. Brzychczyk, R. Karabowicz, Z. Majka, P. Staszel, P. Szostak<br />
• Kyiv, Ukraine, National University of Kyiv<br />
O. Bezshyyko, I. Ka<strong>de</strong>nko, D. Kresan, V. Plujko, V. Shevshenko<br />
• Mannheim, Germany, Inst. of Computer Engineering, Universität Mannheim<br />
K.-H. Brenner, U. Brüning, P. Fischer, J. Gläß, P. Haspel, R. Männer, D. Slogsnat, C. Steinle,<br />
D. Wohlfeld, A. Wurz<br />
• Marburg, Germany, Fachbereich Physik, Universität Marburg<br />
B. Kohlmeyer, C. Schindler<br />
• Moscow, Russia, Institute for Nuclear Research<br />
M. Golubeva, F. Guber, A. Ivashkin, O. Karavichev, T. Karavicheva, E. Karpechev, A. Kurepin,<br />
A. Maevskaia, I. Peshenichnov, V. Rasin, A. Reshetin, V. Tiflov, N. Topilskaya<br />
• Moscow, Russia, ITEP<br />
A. Akindinov, A. Arefiev, Y. Grishuk, A. Golutvin, S. Kiselev, I. Korolko, T. Kvaracheliya, V. Maiatski<br />
, S. Malyshev, A. Martemiyanov, K. Mikhailov, P. Polozov, M. Prokudin, A. Smirnitskiy,<br />
A. Stavinsky, V. Stolin, K. Voloshin, B. Zagreev<br />
Smolyankin laboratory: Y. Grishkin, A. Lebe<strong>de</strong>v, N. Rabin, V. Smolyankin, A. Zhilin<br />
• Moscow, Russia, SINP, Moscow State University<br />
N. Baranova, G. Bashindjagyan, D. Karmanov, M. Korolev, M. Merkin, A. Voronin<br />
• Moscow, Russia, Kurchatov Institute<br />
A. Kazantsev, V. Manko, I. Yushmanov<br />
• Moscow, Russia, MEPhi 1<br />
M. Alyushin, E. Atkin, Y. Bocharov, B. Bogdanovich, V. Emelianov, I. Ilyushenko, A. Krasnuk,<br />
E. Onishchenko, V. Popov, A. Silaev, A. Simakov, Y. Volkov<br />
• Münster, Germany, Institut für Kernphysik, Universität Münster<br />
D. Bucher, M. Hoppe, K. Reygers, A. Wilk, J. Wessels<br />
• Nikosia, Cyprus, Cyprus University<br />
J. Mousa, H. Tsertos<br />
• Obninsk, Russia, Obninsk State University of Atomic Energy<br />
V. Galkin, A. Golovin, D. Ossetski, D. Ryzhikov, V. Saveliev, M. Zaboudko<br />
• Prag, Czech Republic, Technical University<br />
V. Petracek, L. Skoda
• Protvino, Russia, IHEP<br />
V. Ammosov, M. Bogolyubsky, V. Dyatchenko, Yu. Kharlov, V. Khmelnikov, A. Kuznetsov, V. Leontiev,<br />
V. Obraztsov, B. Polishchuk, V. Rykalin, A. Ryazantsev, S. Sadovsky, A. Semak, V. Shelikhov,<br />
A. Soldatov, V. Sougonyaev, Y. Sviridov, V. Victorov, V. Zaets<br />
• Pusan, Korea, Pusan National University<br />
J.K. Ahn, D.-S. Kim, J.-Y. Kim, I.-K. Yoo<br />
• Rez, Czech Republic, Czech Aca<strong>de</strong>my of Sciences<br />
D. Adamova, A. Kugler, J. Novotny, P. Tlusty<br />
• Rossendorf, Germany, FZR, Institut für Kern- und Hadronenphysik<br />
F. Dohrmann, E. Grosse, K. Hei<strong>de</strong>l, B. Kämpfer, R. Kotte, L. Naumann<br />
• Santiago <strong>de</strong> la Compostela, Spain, University<br />
M. Angeles Lopez, D. Belver, J. Garzon, F. Gomez, D. Gonzalez<br />
• Seoul, Korea, Korea University<br />
B. Hong, Y.J. Kim, K.S. Sim<br />
• St. Petersburg, Russia, Khlopin Radium Institute (KRI)<br />
M. Chubarov, V. Karasev, S. Loshaev, Y. Murin, V. Plujschev, E. Seleznev<br />
• St. Petersburg, Russia, CKBM<br />
A. Bolonin, V. Dobulevich, S. Igolkin, G. Karasev, G. Petrova, A. Svischev, M. Tkachev, V. Varava,<br />
A. Vasiliev, A. Vorobeva, V. Yaritzin<br />
• St. Petersburg, Russia, PNPI<br />
V. Ivanov, A. Khanza<strong>de</strong>ev, A. Nadtochii, Y. Riabov, V. Samsonov, D. Seliverstov, M. Zhalov<br />
• St. Petersburg, Russia, St. Petersburg State Polytechnic University<br />
Y. Berdnikov, E. Kryshen, M. Ryzhinskiy, A. Tsvetkov<br />
• Strasbourg, France, IN2P3-CNRS/ULP (IRes)<br />
A. Besson, G. Gaycken, S. Heini, F. Rami, H. Souffi-Kebbati, M. Winter<br />
• Warsaw, Poland, Warsaw University, Institute of Experimental Physics<br />
M. Kirejczyk, T. Matulewicz, B. Sikora, K. Siwek-Wilczynska, L. Slusarczyk, K. Wisniewski<br />
• Wuhan, China, Institute of Particle Physics, Hua-zhong Normal University 1<br />
X. Cai, T. Wu, Z.B. Yin, D.C. Zhou<br />
• Zagreb, Croatia, Rudjer Bošković Institute<br />
Z. Basrak, R. Čaplar, M. Dželalija, I. Gašparić, M. Kiš<br />
1 membership to be confirmed by the collaboration board<br />
v
vi<br />
Persons additionally contributing to this report:<br />
E.L. Bratkovskaya, Institut für Theoretische Physik Frankfurt, Germany<br />
B. Friman, A. Martemiyanov, and P. Moritz <strong>GSI</strong> Darmstadt, Germany<br />
S. Gorbunov, DESY Zeuthen, Germany<br />
J. Marzec, K. Zaremba, Warsaw University of Technology, Poland<br />
H.K. Soltveit, Physikalisches Institut, Universität Hei<strong>de</strong>lberg, Germany<br />
V. Tikhomirov, Lebe<strong>de</strong>v Physical Inst., Moscow, Russia<br />
P. Wintz, Forschungszentrum Jülich, Germany<br />
A. Bertin, M. Bruschi, B. Giacobbe, N. Semprini-Cesari, R. Spighi, M. Villa, A. Vitale, A. Zoccoli,<br />
Instituto Nazionale di Fisica Nucleare - Sezione di Bologna, Italy<br />
Acknowledgement<br />
This work is supported by the EU Integrated Infrastructure Initiative Hadron-Physics Project un<strong>de</strong>r Contract<br />
number RII3-CT-2004-506078 and by INTAS (contract numbers 03-51-6645, 03-54-6272, 03-54-<br />
4169, 03-54-5119, and 03-54-3891).
Contents<br />
The CBM Collaboration iii<br />
Preface 1<br />
I Introduction and Overview 3<br />
1 Introduction and Overview 5<br />
1.1 Physics case and observables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5<br />
1.1.1 Low-mass vector mesons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7<br />
1.1.2 Charm production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8<br />
1.1.3 Strangeness in <strong>de</strong>nse matter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9<br />
1.1.4 Event-by-event fluctuations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10<br />
1.2 The CBM experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12<br />
1.2.1 The research program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12<br />
1.2.2 The <strong>de</strong>tector system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14<br />
1.2.3 Detector performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18<br />
1.2.4 Planning and organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21<br />
II Detector Systems 23<br />
2 The Silicon Tracking Station (STS) 25<br />
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25<br />
2.1.1 Tracking in CBM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25<br />
2.1.2 Operational environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26<br />
2.1.3 Overall geometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26<br />
2.1.4 Status of R&D and <strong>de</strong>sign optimization . . . . . . . . . . . . . . . . . . . . . . . . . 27<br />
2.2 The inner tracking station (ITS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27<br />
2.2.1 Design aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27<br />
2.2.2 Conceptional <strong>de</strong>sign . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29<br />
2.2.3 Monolithic Active Pixel Sensors (MAPS) . . . . . . . . . . . . . . . . . . . . . . . . 29<br />
2.2.4 Alternative technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39<br />
2.3 The Silicon Strip Tracker (SST) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44<br />
2.3.1 General <strong>de</strong>sign consi<strong>de</strong>rations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44<br />
vii
viii<br />
2.3.2 Geometry of the Si-strip tracker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47<br />
2.3.3 Si-strip sensors: Design and Technology . . . . . . . . . . . . . . . . . . . . . . . . 52<br />
2.3.4 Si-strip STS Readout Electronics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53<br />
2.3.5 Working packages, timelines, cost estimate . . . . . . . . . . . . . . . . . . . . . . 57<br />
3 Ring Imaging Cherenkov <strong>de</strong>tector (RICH) 59<br />
3.1 Design consi<strong>de</strong>rations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59<br />
3.2 Particle i<strong>de</strong>ntification with the RICH <strong>de</strong>tector . . . . . . . . . . . . . . . . . . . . . . . . 61<br />
3.3 RICH simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65<br />
3.3.1 Description of simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65<br />
3.3.2 Response of the RICH <strong>de</strong>tector to single particles . . . . . . . . . . . . . . . . . . . 66<br />
3.3.3 Acceptance of the RICH <strong>de</strong>tector . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68<br />
3.3.4 Response of the RICH <strong>de</strong>tector to heavy-ion collisions . . . . . . . . . . . . . . . . . 69<br />
3.4 Technical realization of the RICH <strong>de</strong>tector . . . . . . . . . . . . . . . . . . . . . . . . . 72<br />
3.4.1 Optics and mirrors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72<br />
3.4.2 Radiator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74<br />
3.4.3 UV photo<strong>de</strong>tector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76<br />
3.4.4 HV and readout electronics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80<br />
3.4.5 Support structure, gas vessel and gas supply system . . . . . . . . . . . . . . . . . . 81<br />
3.5 Working packages, timelines, costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83<br />
4 Transition Radiation <strong>de</strong>tector (TRD) 85<br />
4.1 Design consi<strong>de</strong>rations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85<br />
4.2 An MWPC-based TRD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85<br />
4.2.1 Simulations of electron/pion i<strong>de</strong>ntification . . . . . . . . . . . . . . . . . . . . . . . 86<br />
4.2.2 Tests with prototypes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91<br />
4.2.3 Gas system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98<br />
4.2.4 Readout electronics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100<br />
4.2.5 Design consi<strong>de</strong>rations, mechanics, and material budget . . . . . . . . . . . . . . . . 102<br />
4.2.6 Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103<br />
4.3 A straw-based TRD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103<br />
4.3.1 Monte Carlo simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104<br />
4.3.2 Design of a TRT for CBM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108<br />
4.3.3 Detector elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111<br />
4.3.4 Gas supply system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114<br />
4.3.5 Detector readout . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
4.3.6 Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118<br />
4.4 Detector ageing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118<br />
4.5 Infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118<br />
4.6 Working packages and timelines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120<br />
5 Resistive Plate Chambers (RPC) 121<br />
5.1 Design consi<strong>de</strong>rations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121<br />
5.2 Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122<br />
5.2.1 Input data and parameters of simulation . . . . . . . . . . . . . . . . . . . . . . . . . 122<br />
5.2.2 Matching of tracks with TOF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122<br />
5.3 RPC properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124<br />
5.3.1 Rate capability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124<br />
5.3.2 Aging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132<br />
5.4 RPC <strong>de</strong>tector layout options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136<br />
5.4.1 Single cell chambers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136<br />
5.4.2 Multipad chambers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136<br />
5.4.3 Single strip counter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141<br />
5.4.4 Multistrip counter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144<br />
5.5 RPC electronics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149<br />
5.5.1 FOPI-RPC-Electronics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149<br />
5.5.2 Preamplifier/discriminator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150<br />
5.5.3 Time Measurement and Digital Backend . . . . . . . . . . . . . . . . . . . . . . . . 152<br />
5.6 TOF <strong>de</strong>tector test facility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156<br />
5.7 Infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158<br />
5.8 Working packages and milestones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159<br />
5.9 Cost estimate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159<br />
6 Electromagnetic Calorimeter (ECAL) 161<br />
6.1 Design consi<strong>de</strong>rations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161<br />
6.2 Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162<br />
6.2.1 Acceptance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165<br />
6.2.2 e/π separation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165<br />
6.3 Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168<br />
6.4 Detector construction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170<br />
6.4.1 Module <strong>de</strong>sign . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170<br />
6.5 Photon <strong>de</strong>tectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172<br />
ix
x<br />
6.6 Readout electronics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173<br />
6.7 Radiation hardness of <strong>de</strong>tectors and electronics . . . . . . . . . . . . . . . . . . . . . . . 173<br />
6.8 Working packages, timelines, costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174<br />
7 Superconducting dipole magnet 177<br />
7.1 Dipole with parallel pole shoes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177<br />
7.2 Dipole with inclined pole shoes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178<br />
8 Diamond start <strong>de</strong>tector 183<br />
8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183<br />
8.2 Properties of CVD diamond <strong>de</strong>tectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184<br />
8.2.1 Pulse shape characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184<br />
8.2.2 Intrinsic time resolution of HI diamond <strong>de</strong>tectors at SIS energies . . . . . . . . . . . 185<br />
8.2.3 MIP timing with PC diamond <strong>de</strong>tectors . . . . . . . . . . . . . . . . . . . . . . . . . 185<br />
8.2.4 Suppression of trigger rate and background using START-VETO <strong>de</strong>vices . . . . . . . 186<br />
8.2.5 Pulse-height distributions in CVD-diamond <strong>de</strong>tectors . . . . . . . . . . . . . . . . . 187<br />
8.3 Discussion of the strip <strong>de</strong>sign with respect to the beam parameters . . . . . . . . . . . . . 188<br />
8.3.1 Beam dimensions and beam intensity load at different distance from the CBM target<br />
assuming 50 µm strip and readout pitch at a strip width of 12 µm . . . . . . . . . . . 188<br />
8.3.2 Time Zero precision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190<br />
8.4 Influence of diamond material type and thickness . . . . . . . . . . . . . . . . . . . . . . 191<br />
8.4.1 Available types of CVD-D material and their corresponding <strong>de</strong>tector properties . . . . 191<br />
8.4.2 Multiple scattering and energy straggling . . . . . . . . . . . . . . . . . . . . . . . . 192<br />
8.5 FE Electronics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192<br />
8.6 Summary, concluding remarks and outlook . . . . . . . . . . . . . . . . . . . . . . . . . 193<br />
9 Common Front-End Electronics Aspects 195<br />
9.1 General Consi<strong>de</strong>rations, Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . 195<br />
9.1.1 Consi<strong>de</strong>rations with respect to electronics . . . . . . . . . . . . . . . . . . . . . . . . 197<br />
9.1.2 Microelectronics technology choice . . . . . . . . . . . . . . . . . . . . . . . . . . . 198<br />
9.2 Existing microelectronics building blocks . . . . . . . . . . . . . . . . . . . . . . . . . . 200<br />
9.2.1 TRAP-ADC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200<br />
9.2.2 LVDS IO Cells. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201<br />
9.2.3 On-Chip Slow Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201<br />
9.2.4 Analogue multiplexer, auxiliary ADC, temperature sensor and voltage reference . . . 202<br />
9.2.5 Digital Filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202<br />
9.2.6 High-speed Tracklet Processor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203
9.2.7 32-bit RISC CPU . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203<br />
9.2.8 Network Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203<br />
9.2.9 High Performance ALU . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204<br />
9.2.10 Quad Port Memory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204<br />
9.2.11 Programmable Delay Unit & Network Fault Tolerance . . . . . . . . . . . . . . . . . 204<br />
9.2.12 SCSN Redundant High-speed Configuration Network . . . . . . . . . . . . . . . . . 204<br />
9.3 Overall Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205<br />
9.4 First Amplifier Stages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208<br />
9.5 Analog Memory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210<br />
9.6 Multi-purpose ADC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211<br />
9.6.1 General requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211<br />
9.6.2 Variant 1: Interleaving (Multiplexing) of 4 ADCs . . . . . . . . . . . . . . . . . . . . 211<br />
9.6.3 Variant 2: Pipeline-ADC with 10/12 bit . . . . . . . . . . . . . . . . . . . . . . . . . 212<br />
9.6.4 Variant 3: 9bit Pipeline-ADC with 2 different gain stages . . . . . . . . . . . . . . . 212<br />
9.7 SerDes, Clock recovery and Optical links . . . . . . . . . . . . . . . . . . . . . . . . . . 213<br />
9.7.1 High Performance Clock Recovery . . . . . . . . . . . . . . . . . . . . . . . . . . . 213<br />
9.7.2 SerDes and Optical driver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215<br />
9.7.3 Low cost electrical / optical conversion . . . . . . . . . . . . . . . . . . . . . . . . . 220<br />
9.8 FEE Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221<br />
9.8.1 Clock/Time Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221<br />
9.8.2 Generic Optical Advanced Serializer/Deserializer (OASE) . . . . . . . . . . . . . . . 222<br />
9.9 CNet – Concentrator Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225<br />
9.9.1 General Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225<br />
9.9.2 CNet System Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226<br />
9.9.3 Link Protocol Physical Layer (FELA) . . . . . . . . . . . . . . . . . . . . . . . . . . 228<br />
9.10 Miscellaneous, Infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232<br />
9.10.1 Power distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232<br />
9.10.2 FPGA Roadmap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233<br />
9.10.3 Radiation Tolerance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234<br />
10 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing 237<br />
10.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237<br />
10.2 Overall Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238<br />
10.3 Communication and Processing Architecture . . . . . . . . . . . . . . . . . . . . . . . . 241<br />
10.3.1 BNet - Build Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241<br />
10.3.2 First Level Farm Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249<br />
xi
xii<br />
10.3.3 Implementation Plan for First Level Farm . . . . . . . . . . . . . . . . . . . . . . . . 255<br />
10.4 Feature Extraction and Event Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . 258<br />
10.4.1 Filter Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 259<br />
10.4.2 Implementation Scenarios for Selected Algorithms . . . . . . . . . . . . . . . . . . . 260<br />
10.5 Controls (ECS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 264<br />
10.5.1 General Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265<br />
10.5.2 Detailed requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265<br />
10.5.3 Possible Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266<br />
10.5.4 The Detector Control System (DCS) . . . . . . . . . . . . . . . . . . . . . . . . . . 267<br />
10.5.5 Configurations and Update Management . . . . . . . . . . . . . . . . . . . . . . . . 270<br />
10.6 Computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271<br />
10.6.1 Physics requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271<br />
10.6.2 Event structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272<br />
10.6.3 High level event reconstruction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273<br />
10.6.4 Estimate of computing power and storage . . . . . . . . . . . . . . . . . . . . . . . . 274<br />
10.6.5 Offline computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275<br />
10.6.6 Cost estimate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275<br />
10.7 CBM Simulation and Analysis Framework . . . . . . . . . . . . . . . . . . . . . . . . . 275<br />
10.7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275<br />
10.7.2 Design and implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275<br />
11 Beam requirements and run time estimate 279<br />
11.1 Beam requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279<br />
11.2 Runtime estimate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279<br />
11.2.1 Nucleus-nucleus collisions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280<br />
11.2.2 Proton-nucleus and proton-proton collisions . . . . . . . . . . . . . . . . . . . . . . 282<br />
III Physics performance 285<br />
12 Experimental conditions 287<br />
12.1 Hit <strong>de</strong>nsities and rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 287<br />
12.2 Hadron multiplicities and momentum distributions from UrQMD calculations . . . . . . 295<br />
12.3 Hadron multiplicities from HSD calculations . . . . . . . . . . . . . . . . . . . . . . . . 297<br />
12.4 Hadron multiplicities: experimental results . . . . . . . . . . . . . . . . . . . . . . . . . 299<br />
12.5 Knock-On electrons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299
13 Event reconstruction 301<br />
13.1 Track finding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302<br />
13.1.1 Hough Transform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302<br />
13.1.2 Cellular Automaton method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305<br />
13.1.3 Conformal Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308<br />
13.1.4 3D track-following method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308<br />
13.2 Track fitting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311<br />
13.2.1 Kalman filter – first approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311<br />
13.2.2 Kalman filter - second approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 314<br />
13.2.3 Parabolic approximation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315<br />
13.2.4 Polynomial approximation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 318<br />
13.2.5 Orthogonal polynomial sets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 320<br />
13.3 Primary vertex fitting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323<br />
13.3.1 Minimisation of track impact parameters . . . . . . . . . . . . . . . . . . . . . . . . 323<br />
13.3.2 Geometrical fit with Kalman filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323<br />
13.4 Secondary vertex fitting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 326<br />
13.4.1 Geometrical fit with Kalman filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . 326<br />
13.4.2 Mass and topological constrained fit with Kalman filter . . . . . . . . . . . . . . . . 327<br />
13.5 RICH ring finding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330<br />
13.5.1 Track extrapolation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330<br />
13.5.2 Hough Transform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330<br />
13.5.3 Elastic Net for standalone RICH ring finding . . . . . . . . . . . . . . . . . . . . . . 333<br />
13.6 RICH ring fitting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337<br />
13.6.1 Robust ring fitter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337<br />
14 Hadron i<strong>de</strong>ntification 339<br />
14.1 Acceptance for TOF i<strong>de</strong>ntified particles . . . . . . . . . . . . . . . . . . . . . . . . . . . 339<br />
14.2 Hadron i<strong>de</strong>ntification by time-of-flight . . . . . . . . . . . . . . . . . . . . . . . . . . . 339<br />
15 Hyperons 345<br />
15.1 Λ hyperons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345<br />
15.2 Ξ − hyperons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347<br />
15.3 Ω − hyperons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 349<br />
15.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 350<br />
16 Low-mass vector mesons 353<br />
16.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353<br />
xiii
xiv<br />
16.2 Simulation tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353<br />
16.3 Background suppression - cut strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . 354<br />
16.4 Results of signal to background ratio studies . . . . . . . . . . . . . . . . . . . . . . . . 354<br />
17 Charmonium 357<br />
17.1 J/ψ <strong>de</strong>tection via e + e − <strong>de</strong>cay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357<br />
17.1.1 Signal and background simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357<br />
17.1.2 Acceptance and efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359<br />
17.1.3 Signal to background ratio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 360<br />
17.1.4 Online event selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 361<br />
17.1.5 Fast track reconstruction in the TRD . . . . . . . . . . . . . . . . . . . . . . . . . . 362<br />
17.1.6 Conclusions and next steps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365<br />
17.2 J/ψ <strong>de</strong>tection via µ + µ − <strong>de</strong>cay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365<br />
17.2.1 Signal and background simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365<br />
17.2.2 Signal to background ratio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366<br />
17.2.3 I<strong>de</strong>ntification of primary muons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 369<br />
17.2.4 Conclusions and next steps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 372<br />
18 Open charm 375<br />
18.1 Signal and background simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375<br />
18.2 Tracking and Vertexing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375<br />
18.3 Background reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376<br />
18.4 Analysis and results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 378<br />
18.5 Influence of the material budget . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 380<br />
18.6 Next steps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 380<br />
19 Event-by-event fluctuations 383<br />
IV Infrastructure and Safety 385<br />
20 Cave 387<br />
21 Radiation protection 389<br />
V Organization and Responsibilities, Planning 391<br />
22 Planning and organization 393
22.1 Cost estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393<br />
22.2 Responsibilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393<br />
22.3 Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395<br />
22.4 Schedule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 397<br />
References 401
xvi
Preface<br />
Since the submission of the Letter-of-Intent in January 2004 the CBM collaboration has concentrated on<br />
feasibility studies and <strong>de</strong>tector R&D in or<strong>de</strong>r to reach the <strong>de</strong>sign goals formulated in the Conceptional<br />
Design Report of the FAIR project. This Technical Status Report documents the progress which has been<br />
ma<strong>de</strong> particularly in the following areas:<br />
• <strong>de</strong>velopment and implementation of a common CBM simulation framework<br />
• <strong>de</strong>sign of the Ring Imaging Cherenkov <strong>de</strong>tector<br />
• <strong>de</strong>sign of Transition Radiation Detectors<br />
• study of the high-rate performance of gas <strong>de</strong>tectors and Resistive Plate Chambers,<br />
• improvement of read-out speed and radiation hardness of MAPS <strong>de</strong>tectors<br />
• layout of the Silicon strip <strong>de</strong>tectors<br />
• <strong>de</strong>velopment of track reconstruction and pattern recognition algorithms<br />
• analysis techniques for low-mass dilepton pairs, charmonium, D-mesons and hyperons<br />
• feasibility studies on event-by-event fluctuations<br />
• concept studies of event selection, FEE and DAQ<br />
• <strong>de</strong>sign of a superconducting dipole magnet<br />
In spite of this progress more effort is nee<strong>de</strong>d in or<strong>de</strong>r to reach conclusion upon a <strong>de</strong>tailed <strong>de</strong>tector<br />
concept with optimized geometry and granularity. We have to <strong>de</strong>monstrate the feasibility to measure low<br />
mass dilepton pairs and D mesons by simulations which are based on track reconstruction in the magnetic<br />
field including realistic <strong>de</strong>tector responses. Moreover, we have to prove that the <strong>de</strong>tectors fulfill the<br />
requirements on rate capability, radiation hardness, spatial resolution, efficiencies and material budget.<br />
These are serious issues, as the CBM <strong>de</strong>tector and its data acquisition system aim at unprece<strong>de</strong>nted<br />
performance in rate capabilities and radiation hardness.<br />
We still follow more than one option for the technical solution of some particular tasks, such as Silicon<br />
pixel <strong>de</strong>tectors or transition radiation <strong>de</strong>tectors. Our next goal is to prepare the <strong>de</strong>cision on <strong>de</strong>tector<br />
technologies and to <strong>de</strong>monstrate the feasibility of the envisaged measurements until end of 2006.<br />
1
Part I<br />
Introduction and Overview<br />
3
1 Introduction and Overview<br />
1.1 Physics case and observables<br />
The exploration of the phase diagram of strongly interacting matter is one of the most challenging fields<br />
of mo<strong>de</strong>rn high-energy physics [1]. Of particular interest is the transition from hadronic to partonic<br />
<strong>de</strong>grees of freedom which is expected to occur at high temperatures and/or high baryon <strong>de</strong>nsities. Both<br />
phases played an important role in the early universe and possibly exist in the core of neutron stars [2].<br />
The discovery of this phase transition would shed light on two fundamental but still puzzling aspects of<br />
Quantum Chromo Dynamics (QCD): confinement and chiral symmetry breaking. In particular, at high<br />
baryon <strong>de</strong>nsities one expects new phases of strongly interacting matter [3]. The scientific progress in this<br />
exciting field, QCD at high baryon <strong>de</strong>nsities, is driven by new experimental data.<br />
In or<strong>de</strong>r to study the dynamics of strongly interacting matter far from its ground state, laboratory experiments<br />
are performed with high-energy nucleus-nucleus collisions. The conditions insi<strong>de</strong> the transiently<br />
existing fireball are reflected in the abundances and phase-space distributions of the emitted hadrons.<br />
Important information on the early phase of the collision is provi<strong>de</strong>d by the quark flavor of the observed<br />
hadrons. In particular, hadrons containing strange or charmed quarks are regar<strong>de</strong>d as sensitive diagnostic<br />
probes of the collision dynamics. The hadrons are either observed directly or are i<strong>de</strong>ntified via their<br />
hadronic or leptonic <strong>de</strong>cay products.<br />
Lattice QCD calculations at vanishing baryochemical potential and finite temperature predict the formation<br />
of a quark-gluon plasma above energy <strong>de</strong>nsities of about 1 GeV/fm 3 [4]. Such conditions may be created<br />
in central collisions between heavy nuclei already at bombarding energies of about 10 AGeV [5,6].<br />
Recent lattice QCD calculations at finite baryon chemical potential predict a critical endpoint of <strong>de</strong>confinement<br />
phase transition at µB ≈ 400 MeV and T≈160 MeV [7, 8].<br />
Our current knowledge on the QCD phase diagram is illustrated in figure 1.1. The data points correspond<br />
to chemical freeze-out and result from a statistical analysis of particle ratios measured in Pb+Pb and<br />
Au+Au collisions at SIS, AGS, SPS and RHIC [9, 10, 11]. The solid curve along the freeze-out points<br />
represents a calculation with a constant baryon <strong>de</strong>nsity (baryons + antibaryons) of about ρB = 0.75<br />
ρ0 [11]. The phase boundary between quark-gluon matter and hadronic matter together with the location<br />
of the critical endpoint as shown in figure 1.1 is predicted by lattice QCD calculations [7, 8]. These<br />
calculations indicate that for values of µB larger than about 400 MeV the phase transition is first or<strong>de</strong>r,<br />
whereas for µB smaller than 400 MeV there is a smooth cross over from the hadronic to the partonic<br />
phase (dotted line). The search for the critical endpoint is a prime goal of high-energy nucleus-nucleus<br />
collision experiments.<br />
At ultra-relativistic beam energies provi<strong>de</strong>d by RHIC and the future LHC, partonic matter is expected<br />
to be produced at very high temperatures and at small baryon chemical potentials. Similar conditions<br />
prevailed in the early universe. The complementary situation exists in the core of a neutron star: here<br />
the baryon <strong>de</strong>nsity is very high and the temperature very low. In the laboratory, fireballs at high baryon<br />
<strong>de</strong>nsities and mo<strong>de</strong>rate temperatures are created at beam energies significantly below top SPS energies.<br />
This region of the QCD phase diagram - marked by the hatched area in figure 1.1- has not been studied<br />
in <strong>de</strong>tail so far (see next section).<br />
Trajectories of nucleus-nucleus collisions in the T - µB plane have been recently calculated with a 3-fluid<br />
hydrodynamics mo<strong>de</strong>l [12]. Figure 1.2 <strong>de</strong>picts the trajectories corresponding to different beam energies.<br />
5
6 Introduction and Overview<br />
temperature T [MeV]<br />
200<br />
175<br />
150<br />
125<br />
100<br />
75<br />
50<br />
25<br />
dilute<br />
hadronic<br />
medium<br />
critical endpoint<br />
Lattice QCD<br />
n b =0.12 fm -3<br />
quark-gluon matter<br />
P. Braun-Munzinger et al. PLB 518 (2001)<br />
F. Becattini et al. PRC 96 (2004)<br />
R. Averbeck et al. nucl-ex/9803001<br />
<strong>de</strong>nse<br />
baryonic<br />
medium<br />
0<br />
0 0.2 0.4 0.6 0.8 1<br />
baryonic chemical potential μ B [GeV]<br />
Figure 1.1: The phase diagram of<br />
strongly interacting matter plotted as<br />
a function of temperature and baryon<br />
chemical potential. Full symbols:<br />
freeze-out points obtained with a statistical<br />
mo<strong>de</strong>l analysis from particle ratios<br />
measured in heavy collisions [213, 10].<br />
The critical endpoint at µB ≈ 400 MeV<br />
is predicted by lattice QCD calculations<br />
[7, 8]. "Dilute hadronic medium":<br />
ρB=0.038 fm −3 ≈ 0.24 ρ0. "Dense<br />
baryonic medium": ρB=1.0 fm −3 ≈ 6.2<br />
ρ0.<br />
According to the calculations a beam energy of 10 AGeV is sufficient to cross the phase boundary. For a<br />
beam energy of about 30 AGeV the trajectory is predicted to pass the region of the critical endpoint of the<br />
<strong>de</strong>confinement phase transition [12]. The planned SIS 300 synchrotron at the future FAIR facility [13]<br />
covers an energy range of up to 45 AGeV for nuclei with A=2Z, and, hence, is well suited to explore the<br />
high baryon <strong>de</strong>nsity region of the QCD phase diagram. The research programme to be performed with<br />
the proposed Compressed Baryonic Matter (CBM) experiment inclu<strong>de</strong>s a comprehensive investigation<br />
of the relevant hadronic observables, and is focused on systematic measurements of diagnostic probes<br />
which have not been measured before in this energy range: the dileptonic <strong>de</strong>cay of low-mass vector<br />
mesons and hadrons containing charmed quarks.<br />
, MeV<br />
300<br />
Pb+Pb, central collision<br />
freeze-out<br />
A end-point<br />
2<br />
1<br />
1<br />
10 GeV<br />
1fm/c<br />
2<br />
200<br />
2<br />
3 3<br />
4 4 4<br />
9<br />
5 5<br />
9<br />
9<br />
6<br />
9<br />
3<br />
4<br />
3<br />
2<br />
1<br />
80 GeV<br />
158 GeV<br />
100<br />
30 GeV<br />
0<br />
0 1000 2000 3000<br />
, MeV<br />
Figure 1.2: Trajectories of heavy ion<br />
collisions in the QCD phase diagram<br />
calculated by a 3-fluid hydrodynamics<br />
mo<strong>de</strong>l [12].
1.1. Physics case and observables 7<br />
The major challenge is to find diagnostic probes which are connected to chiral symmetry restoration and<br />
to the <strong>de</strong>confinement phase transition. A signature for the onset of chiral symmetry restoration might be<br />
the observation of in-medium modifications of hadrons. In-medium effects have been found for pions<br />
in <strong>de</strong>eply bound pionic atoms [14] and for kaons and antikaons produced in heavy-ion collisions at<br />
SIS energies [16, 15, 17]. Very promising observables are also short-lived vector mesons <strong>de</strong>caying into<br />
dilepton pairs insi<strong>de</strong> the fireball. An enhanced yield of low-mass dilepton pairs has been found in central<br />
heavy-ion collisions [18, 19]. This observation has triggered an enormous theoretical activity on the inmedium<br />
modification of ρ-mesons and its relation to chiral symmetry restoration. A promising candidate<br />
for a probe of in-medium modifications is open charm produced at very high baryon <strong>de</strong>nsities [20].<br />
Enormous experimental and theoretical efforts have been and are still <strong>de</strong>voted to the search for the <strong>de</strong>confined<br />
phase of strongly interacting matter, the quark-gluon-plasma (QGP). The discovery of the QGP<br />
was announced by CERN in the year 2000 [21]. The arguments given in the press release were essentially<br />
based on experimental findings like enhanced production of strangeness, anomalous suppression<br />
of charmonium, enhanced production of low-mass dilepton pairs, and the fact that an analysis of particle<br />
multiplicities yields a chemical freeze-out temperature of about 170 MeV which is very close to the<br />
critical temperature. Several years later, new and complementary experimental results obtained at RHIC<br />
were interpreted as signatures of the QGP [22]. The observations of the RHIC experiments inclu<strong>de</strong>: large<br />
values of the elliptic flow in agreement with hydrodynamical calculations, quenching of hadron jets, and<br />
quark number scaling of flow observables.<br />
Many signals have been proposed and are still un<strong>de</strong>r discussion, although the hope for finding a "smoking<br />
gun" has not yet become true. The discovery of the critical endpoint of the <strong>de</strong>confinement phase transition<br />
would be such a direct indication for the existence of a new phase. Theoretical investigations suggest<br />
that particle <strong>de</strong>nsity fluctuations occur in the vicinity of the critical endpoint, which might be observed<br />
experimentally as nonstatistical event-by-event fluctuations of observables [23]. This phenomenon was<br />
also seen in lattice QCD calculations [8]. The fluctuation signal should show up around a certain beam<br />
energy.<br />
In this section we will briefly review the existing data which are relevant for the study of the high baryon<br />
<strong>de</strong>nsity region of the QCD phase diagram.<br />
1.1.1 Low-mass vector mesons<br />
The in-medium spectral function of short-lived vector mesons can be measured directly via their <strong>de</strong>cay<br />
into dilepton pairs. Since leptons are essentially unaffected by the passage through the high-<strong>de</strong>nsity<br />
matter, they provi<strong>de</strong>, as a penetrating probe, almost undistorted information on the conditions in the<br />
interior of the collision zone [24].<br />
However, dilepton pairs from vector meson <strong>de</strong>cays are notoriously difficult to measure due to the very<br />
small branching ratios and the large combinatorial background in heavy-ion collisions. The challenge is<br />
to i<strong>de</strong>ntify the electrons or muons unambiguously, measure their momentum better than Δp/p = 1% and to<br />
efficiently suppress the background which stems mainly from Dalitz <strong>de</strong>cays and gamma conversion. The<br />
test of theoretical predictions requires high statistics data measured with large acceptance spectrometers<br />
in many weeks of beamtime. Pioneering experiments have been performed in heavy-ion collisions at<br />
beam energies below 2 AGeV (DLS at LBL) [18] and above 40 AGeV at CERN with the CERES setup<br />
[19]. The HADES spectrometer at <strong>GSI</strong> has started to take data in nucleus-nucleus collisions at energies<br />
up to 2 AGeV.<br />
The most recent result of the CERES collaboration is presented in figure 1.3 [25]. It shows the inclusive<br />
e + e − pair mass spectra measured in Pb+Au collisions at 40 AGeV and at 158 AGeV together with the<br />
hadronic cocktail of known dilepton sources and with results of mo<strong>de</strong>l calculations based on different
8 Introduction and Overview<br />
assumptions on the in-medium properties of the ρ-meson. The error bars of the data at 40 AGeV - which<br />
contain less than 200 true dilepton pairs - are too large to rule out a particular mo<strong>de</strong>l for the in-medium<br />
properties of the ρ meson. In or<strong>de</strong>r to draw final conclusions, a <strong>de</strong>dicated high luminosity experiment is<br />
required.<br />
-1<br />
)<br />
2<br />
>(100 MeV/c<br />
ch<br />
>/35 mrad<br />
ee<br />
2.1< η
1.1. Physics case and observables 9<br />
1.1.3 Strangeness in <strong>de</strong>nse matter<br />
Figure 1.4: Dimuon invariant mass<br />
spectrum measured in In+In collisions<br />
at 158 AGeV [30].<br />
One of the early predictions for a QGP signal was the increased production of strangeness in the <strong>de</strong>confined<br />
phase resulting in an enhanced yield of strange particles after hadronization [31]. This effect was<br />
expected to be even more pronounced for multistrange hyperons. In<strong>de</strong>ed, the NA57 experiment observed<br />
that the multiplicity of Ξ and Ω hyperons per participant is higher in nucleus-nucleus collisions than in<br />
proton-proton (or proton-Beryllium) collisions [32]. Moreover, the enhancement increases according to<br />
the s-hierarchy. Again, the interpretation of these results is still un<strong>de</strong>r discussion. An intriguing finding<br />
is that the slope of the Ω kinetic energy distribution is steeper than expected. This indicates that the<br />
Ω hyperon - which consists only of strange quarks - might freeze out very early. Recently, data on the<br />
excitation function of strangeness production measured by NA49 have revived the discussion on the role<br />
of strangeness as a signature for a <strong>de</strong>confinement phase transition [33].<br />
The NA49 collaboration has studied systematically the production of strange hadrons scanning the beam<br />
energy from top SPS energy of 158 AGeV down to 20 AGeV [34]. Figure 1.5 shows the multiplicity of<br />
strange particles normalized to the pion multiplicity as function of the beam energy for central Au+Au<br />
(Pb+Pb) collisions. The data are compared to results of hadron gas mo<strong>de</strong>l calculations (blue lines)<br />
and of UrQMD transport mo<strong>de</strong>l calculations (red lines). None of the mo<strong>de</strong>l calculations <strong>de</strong>scribes the<br />
data set satisfactorily. The UrQMD mo<strong>de</strong>l clearly un<strong>de</strong>restimates the ratios. The reason for this is an<br />
overestimation of the pion yield, whereas the strange particle yield is reasonably well reproduced by<br />
transport calculations [35]. The statistical hadron gas mo<strong>de</strong>l agrees roughly with the measured Λ/π ratio<br />
(where the AGS data do not fit well to the SPS data) and with the (Ω + + Ω − )/π ratio which has large<br />
error bars.<br />
The global trend of the excitation functions shown in figure 1.5 is un<strong>de</strong>rstood as the consequence of<br />
the <strong>de</strong>creasing baryon chemical potential with increasing beam energy. In the energy range between<br />
AGS and SPS there is a transition from baryon dominated to meson dominated matter. The pronounced<br />
kink structure in the K + /π + ratio has caused speculations on a possible <strong>de</strong>confinement phase transition<br />
around 30 AGeV [36]. This interpretation seems to be supported by the observation that the slope<br />
of the K + meson spectra exhibits a constant value within the SPS energy range. The K + slopes are<br />
shown in figure 1.6 in comparison to results of transport mo<strong>de</strong>ls (UrQMD and HSD) which significantly<br />
un<strong>de</strong>restimate the data in the energy range of the kink [35]. The authors argue that the missing pressure<br />
should be generated in the early phase of the collision by nonperturbative partonic interactions because<br />
the strong hadronic interactions in the later stages - as mo<strong>de</strong>lled in their transport calculations - are not
10 Introduction and Overview<br />
〉<br />
+<br />
π<br />
〈<br />
/<br />
〉<br />
+<br />
K<br />
〈<br />
〉<br />
-<br />
π<br />
〈<br />
/<br />
〉<br />
-<br />
K<br />
〈<br />
〉<br />
π<br />
〈<br />
/<br />
〉<br />
φ<br />
〈<br />
0.2<br />
0.1<br />
0.15<br />
0.1<br />
0.05<br />
0.008<br />
0.006<br />
0.004<br />
0.002<br />
UrQMD 2.0<br />
HSD<br />
Hadron Gas A<br />
AGS<br />
NA49<br />
RHIC<br />
1 10 10<br />
(GeV)<br />
2<br />
sNN<br />
〉<br />
π<br />
〈<br />
/<br />
〉<br />
Λ<br />
〈<br />
〉<br />
π<br />
〈<br />
/<br />
〉<br />
-<br />
Ξ<br />
〈<br />
〉<br />
π<br />
/ 〈<br />
〉<br />
+<br />
Ω<br />
+<br />
-<br />
Ω<br />
〈<br />
0.06<br />
0.04<br />
0.02<br />
0.004<br />
0.003<br />
0.002<br />
0.001<br />
0.0008<br />
0.0006<br />
0.0004<br />
0.0002<br />
UrQMD 2.0<br />
HSD<br />
Hadron Gas A<br />
1 10 10<br />
(GeV)<br />
2<br />
Figure 1.5: Excitation function of strangeness production in central Au+Au and Pb+Pb collisions. The yield of<br />
strange particles is normalized to the pion yield and compared to mo<strong>de</strong>l calculations. ( [34]).<br />
sufficient to generate the flow [35].<br />
In summary, the experimental search for discontinuities in the excitation function of strange and nonstrange<br />
particles has yiel<strong>de</strong>d intriguing results in the energy range between 10 and 40 AGeV. However,<br />
the data require confirmation and more comprehensive studies with reduced statistical and systematic<br />
errors, in particular for the (multi-strange) hyperons.<br />
1.1.4 Event-by-event fluctuations<br />
In the vicinity of the <strong>de</strong>confinement phase transition, critical <strong>de</strong>nsity fluctuations have been predicted to<br />
cause non-statistical event-by-event fluctuations of experimental observables. In particular, the study of<br />
event-by-event fluctuations in the hadro-chemical composition of the particle source offers the possibility<br />
to directly observe effects of a phase transition. Depending on the nature and the or<strong>de</strong>r of the phase<br />
transition one expects anomalies in the energy <strong>de</strong>pen<strong>de</strong>nce of event-by-event fluctuations [23]. I<strong>de</strong>ally,<br />
a sud<strong>de</strong>n non-monotonous change in the dynamical fluctuations measured as function of beam energy<br />
would be a signal of the critical endpoint.<br />
The NA49 collaboration has searched for dynamical event-by-event fluctuations of the (K + +K − )/(π + +<br />
π − ) ratio in central Pb+Pb collsions. The experimental results of a beam energy scan of dynamical<br />
fluctuations are shown in figure 1.7 [37] together with the analysis of UrQMD calculations.<br />
AGS<br />
NA49<br />
RHIC<br />
sNN
1.1. Physics case and observables 11<br />
T (MeV)<br />
300<br />
200<br />
100<br />
+<br />
K<br />
1 10<br />
string hadronic mo<strong>de</strong>ls: A+A:<br />
HSD<br />
NA49<br />
HSD with Cronin effect AGS<br />
UrQMD 2.0<br />
RHIC<br />
10<br />
s (GeV)<br />
NN<br />
2<br />
Figure 1.6: Inverse slope parameters<br />
of the K + spectra as function of beam<br />
energy measured in Au+Au and Pb+Pb<br />
collisions in comparison to transport<br />
mo<strong>de</strong>l calculations (UrQMD, HSD).<br />
In or<strong>de</strong>r to claim a significant <strong>de</strong>viation of the data from the UrQMD event analysis one would need much<br />
smaller statistical and systematical errors. The errors reflect the difficulties of the measurement: (i) Due<br />
to the limited acceptance of NA49, the number of observed particles per event <strong>de</strong>creases with <strong>de</strong>creasing<br />
beam energy leading to increasing statistical fluctuations. (ii) Due to non-i<strong>de</strong>al particle i<strong>de</strong>ntification the<br />
(K + + K − )/(π + + π − ) ratio is affected by the experimental dE/dx resolution and the event-by-event<br />
fitting procedure.<br />
Dynamical Fluctuations [%]<br />
10<br />
8<br />
6<br />
4<br />
2<br />
0<br />
+<br />
(K<br />
- + -<br />
+ K )/( π + π )<br />
Data<br />
UrQMD v1.3<br />
5 10 15 20<br />
sqrt(s)<br />
Dynamical Fluctuations [%]<br />
0<br />
-2<br />
-4<br />
-6<br />
-8<br />
-10<br />
+ -<br />
(p + p)/(<br />
π + π )<br />
Data<br />
UrQMD v1.3<br />
5 10 15 20<br />
sqrt(s)<br />
Figure 1.7: Energy <strong>de</strong>pen<strong>de</strong>nce of the event-by-event fluctuation signal of the (K + + K − )/(π + + π − ) ratio (left)<br />
and of the (p + ¯p)/(π + + π − ) ratio (right) as function of beam energy for central Pb+Pb collisions. The data (full<br />
dots) are compared to UrQMD simulations (open circles). The systematic errors of the measurements are shown<br />
as grey band (from [37]).<br />
The contributions due to finite particle number fluctuations and effect of <strong>de</strong>tector resolution are estimated<br />
by the mixed event technique. This is a very tricky procedure and requires, for example, an excellent<br />
experimental event classification (i. e. <strong>de</strong>finition of collision centrality, number of participants) in or<strong>de</strong>r<br />
to avoid trivial fluctuations of the kaon-to-pion ratio.<br />
Nevertheless, the observed increase of the fluctuation signal with <strong>de</strong>creasing beam energy indicates the
12 Introduction and Overview<br />
onset of a new source of fluctuations. This effect <strong>de</strong>serves further experimental and theoretical investigations.<br />
A future second generation experiment should have a large acceptance over a wi<strong>de</strong> range of beam<br />
energies, and excellent capabilities for particle i<strong>de</strong>ntification and event classification.<br />
1.2 The CBM experiment<br />
1.2.1 The research program<br />
The FAIR accelerators will provi<strong>de</strong> heavy ion beams up to Uranium at beam energies ranging from 2 - 45<br />
AGeV (for Z/A = 0.5) and up to 35 AGeV for Z/A = 0.4. The maximum proton beam energy is 90 GeV.<br />
1.2.1.1 Experiments with proton beams<br />
Proton beams with energies up to 90 GeV offer the possibility to perform experiments on heavy quark<br />
production in p+p and p+A collisions. The production mechanisms of heavy quarks in this energy range<br />
are sensitive to the quark and gluon distributions of the nucleon. No data on open charm production exist<br />
below proton beam energies of 400 GeV, and no data on bottonium production exist below 200 GeV<br />
proton energy. The measurement of Ypsilon via its dilepton <strong>de</strong>cay might be possible at a proton energy<br />
of 90 GeV (threshold beam energy for p+p→ ϒpp is Ethr ≈ 65 GeV). The prediction of b¯b cross sections<br />
at such a low energy is a challenge for perturbative QCD calculations. Moreover, data on the production<br />
of charm, strangeness and low-mass vector mesons in p+p and p+A collisions are absolutely nee<strong>de</strong>d as<br />
a reference for the results obtained in A+A collisions. The CBM <strong>de</strong>tector will be well suited for the<br />
measurement of heavy resonances and exotica like pentaquarks produced in p+p and p+A collisions.<br />
The expected production cross sections for D mesons in proton induced reactions are shown in figure 1.8<br />
(taken from [38]).<br />
Figure 1.8: Production cross section<br />
for open charm in proton induced<br />
reactions. The calculation does not<br />
inclu<strong>de</strong> associated charm production<br />
(pp→ ΛcDp) which is dominating the<br />
cross section close to threshold (taken<br />
from [38]).<br />
A substantial fraction of the experiments performed with the CBM <strong>de</strong>tector will be <strong>de</strong>voted to proton<br />
induced reactions. The <strong>de</strong>tection of particles containing heavy quarks - both via leptonic and hadronic<br />
<strong>de</strong>cay channels - will benefit from the performance of the setup dictated by the heavy-ion experiments.
1.2. The CBM experiment 13<br />
1.2.1.2 Experiments with heavy-ion beams<br />
The nucleus-nucleus collisions research program of CBM will focus on the search for (i) in-medium<br />
modifications of hadrons in super-<strong>de</strong>nse matter as signal for the onset of chiral symmetry restoration,<br />
(ii) a <strong>de</strong>confined phase at high baryon <strong>de</strong>nsities, and (iii) the critical endpoint of the <strong>de</strong>confinement<br />
phase transition. The program aims at a comprehensive study of relevant observables by systematically<br />
scanning experimental parameters like beam energy, system size and collision centrality. The observables<br />
inclu<strong>de</strong>:<br />
• open and hid<strong>de</strong>n charm: Charm quarks are produced in the early phase of the collision and hence<br />
probe high-<strong>de</strong>nsity baryonic or partonic matter. The sensitivity of charm production to medium<br />
effects is enhanced due to the fact that the beam energy is close to the threshold. Charmonium<br />
(J/ψ mesons) will be measured via its <strong>de</strong>cay into electron-positron (and muon) pairs, whereas<br />
D-mesons will be i<strong>de</strong>ntified by the invariant mass of their hadronic <strong>de</strong>cay products. The low<br />
charm production cross sections drive the request for high beam intensities (up to 10 MHz reaction<br />
rates) and online event selection. Neither open nor hid<strong>de</strong>n charm has been measured up to now<br />
in nucleus-nucleus collisions at beam energies below 158 AGeV. A comprehensive experimental<br />
study of charm production requires a universal setup with outstanding performances in rate capability,<br />
radiation hardness, high-resolution secondary vertex <strong>de</strong>termination, electron (muon) and<br />
hadron i<strong>de</strong>ntification.<br />
• short-lived vector mesons <strong>de</strong>caying into electron-positron pairs: The ultimate goal is the measurement<br />
of the in-medium spectral function of ρ (or ω and φ) mesons in or<strong>de</strong>r to study effects of<br />
chiral symmetry restoration. This requires data with excellent statistics and low systematic errors,<br />
measured in the energy range from 2 - 45 AGeV. Such an amount of data can only be obtained at<br />
a <strong>de</strong>dicated facility. The upgra<strong>de</strong>d HADES Spectrometer will be used for these studies up to beam<br />
energies of about 8 GeV.<br />
• strange and multi-strange particles: Strangeness production plays an important role as a possible<br />
signature for a <strong>de</strong>confined phase of strongly interacting matter produced in nucleus-nucleus collisions<br />
[31]. Moreover, the properties of strange particles in <strong>de</strong>nse baryonic matter are of crucial<br />
importance for theories explaining the inner structure of neutron stars [2]. Of particular interest in<br />
this respect is the hyperon-hyperon interaction which can be measured via correlations. According<br />
to figure 1.5, the highest hyperon <strong>de</strong>nsities are expected to be created in nucleus-nucleus collisions<br />
at beam energies between 10 and 30 AGeV. Therefore, a future experiment studying high-<strong>de</strong>nsity<br />
matter should have the capability to measure efficiently (multi-) strange particles.<br />
• event-by-event fluctuations of observables like particle ratios, charge ratios, mean transverse momentum,<br />
etc.: The search for the critical endpoint of the <strong>de</strong>confinement phase transition requires<br />
large acceptance and good particle i<strong>de</strong>ntification capability over a wi<strong>de</strong> range of beam energies.<br />
Moreover, an excellent event selection is nee<strong>de</strong>d.<br />
• elliptic flow of (multi-) strange and charmed hadrons as a probe of the early fireball.<br />
• photons: Offer the possibility to <strong>de</strong>tect π 0 and η mesons, and direct photons emitted in the early<br />
and <strong>de</strong>nse phase of the collisions.<br />
• search for exotic objects like pentaquarks, short-lived multi-strange objects [39], strongly bound<br />
kaonic systems [40], and precursor effects of a color super-conducting phase at very high baryon<br />
<strong>de</strong>nsities [41].
14 Introduction and Overview<br />
1.2.2 The <strong>de</strong>tector system<br />
The experimental task is to i<strong>de</strong>ntify both hadrons and leptons and to <strong>de</strong>tect rare probes in a heavy ion<br />
environment. The apparatus has to measure yields and phase-space distributions of hyperons, light vector<br />
mesons, charmonium and open charm (including the i<strong>de</strong>ntification of protons, pions and kaons) with a<br />
large acceptance. The challenge is to select very rare probes in Au+Au (or U+U) collisions at reaction<br />
rates of up to 10 7 events per second. The charged particle multiplicity is about 1000 per central event.<br />
Therefore, the experiment has to fulfill the following requirements: fast and radiation hard <strong>de</strong>tectors,<br />
large acceptance and large granularity, electron and hadron i<strong>de</strong>ntification, high-resolution secondary<br />
vertex <strong>de</strong>termination and a high speed event-selection and data acquisition system. Figure 1.9 displays a<br />
sketch of the proposed setup.<br />
Figure 1.9: Sketch of the planned Compressed Baryonic Matter (CBM) experiment. The beam enters from<br />
the left hand si<strong>de</strong>. The setup consists of a superconducting dipole magnet with a Silicon Tracker System insi<strong>de</strong>, a<br />
Rich Imaging Cherenkov <strong>de</strong>tector (RICH) for electron i<strong>de</strong>ntification, three Transition Radiation Detectors (TRD), a<br />
Time-Of Flight (TOF) wall which is a Resistive Plate Chamber (RPC) and an electromagnetic Calorimeter (ECAL).<br />
The total length of the setup is approximately 12 m from target at the entrance of the dipole to the ECAL.<br />
In the following the <strong>de</strong>tector components of the CBM setup are briefly <strong>de</strong>scribed.<br />
1.2.2.1 Superconducting dipole magnet<br />
The dipole magnet serves for bending the charged particle trajectories and for <strong>de</strong>lta-ray <strong>de</strong>flection. A gap<br />
of 1 m is required to provi<strong>de</strong> sufficient space for the silicon tracking system. A bending power of about<br />
1 Tm has to be provi<strong>de</strong>d by the magnet in or<strong>de</strong>r to achieve a momentum resolution of about 1% using<br />
the Silicon Tracking System for trajectory <strong>de</strong>termination. However, this relatively high magnetic field<br />
<strong>de</strong>creases the efficiency towards low momentum particles. In particular, this effect reduces the probability<br />
to reconstruct Dalitz <strong>de</strong>cays of π 0 mesons which results in an increased combinatorial background for<br />
low-mass dilepton pairs.<br />
A lower magnetic field improves the track reconstruction for low momentum particles but worsens the<br />
momentum resolution obtained with the STS. However, the momentum resolution might be improved<br />
when taking into account the trajectory measurement with the TRDs. Simulations on momentum re-
1.2. The CBM experiment 15<br />
construction using full tracking are in progress. A severe and yet unsolved problem is caused by the<br />
huge count rate of <strong>de</strong>lta-electrons (emitted from the target) in the first Silicon Pixel <strong>de</strong>tector. A possible<br />
reduction of the <strong>de</strong>lta-electron flux onto the <strong>de</strong>tectors by a shielding or an additional magnetic field is<br />
un<strong>de</strong>r investigation.<br />
Presently, two magnetic field configurations are un<strong>de</strong>r investigation: a (gaussian shaped) symmetric field<br />
produced by a window-frame dipole magnet with parallel pole shoes, and an asymmetric field produced<br />
by a dipole with inclined pole shoes. Both configurations are studied in simulations with respect to<br />
their performance concerning track reconstruction, momentum resolution, acceptance, and <strong>de</strong>lta-electron<br />
<strong>de</strong>flection.<br />
1.2.2.2 Silicon Tracker System (STS)<br />
The Silicon Tracking System (STS) serves for track measurement and for <strong>de</strong>termination of primary and<br />
secondary vertices. The current STS layout consists of minimum 7 layers and is placed insi<strong>de</strong> a magnetic<br />
dipole field which provi<strong>de</strong>s the bending power required for momentum <strong>de</strong>termination with an accuracy<br />
of Δp/p = 1 %. The STS has to fulfill the following requirements: material budget below 0.3% radiation<br />
length per layer to reduce multiple scattering, hit resolution of about 10 µm to achieve a vertex resolution<br />
of about 30 µm, radiation hardness up to a dose of 50 MRad corresponding to the dose accumulated in<br />
ten years of running, and read-out times of about 25 ns to accommodate reaction rates of 10 MHz.<br />
Silicon Pixel (Vertex-) Detectors<br />
The first 2 stations (distance from the target 5 and 10 cm) will consist of pixel <strong>de</strong>tectors in or<strong>de</strong>r to<br />
reduce the occupancy to about 1% (for a central Au+Au collision at 25 AGeV). Monolithic Active Pixel<br />
Sensors (MAPS) with a pixel size of 40x40 µm 2 and a thickness of 100 µm would perfectly fulfill<br />
our requirements concerning vertex resolution which is nee<strong>de</strong>d to measure the displaced vertices of<br />
D mesons. However, the radiation hardness and the read out speed of nowadays MAPS <strong>de</strong>tectors have to<br />
be improved by 1 - 2 or<strong>de</strong>rs of magnitu<strong>de</strong> in or<strong>de</strong>r to match our requirements. This is the major goal for<br />
our R&D. Moreover, we work on track reconstruction methods to resolve the tracks and vertices of up to<br />
50 superimposed events in the MAPS <strong>de</strong>tectors.<br />
As a possible alternative to the MAPS <strong>de</strong>tectors based on CMOS technology we study prototypes of<br />
MAPS <strong>de</strong>tectors realized in Silicon on Insulator (SOI) technology. Moreover, the ongoing <strong>de</strong>velopment<br />
of low-mass hybrid pixel <strong>de</strong>tectors for future LHC experiments may lead to a substantial reduction of<br />
their material budget. These <strong>de</strong>tectors - which are fast and radiation hard - might then serve as a fall back<br />
solution for the CBM Vertex Tracker.<br />
Silicon Microstrip Detectors<br />
The third Silicon Tracking Station will consist both of pixel <strong>de</strong>tectors (inner part, small forward angles)<br />
and of Silicon microstrip <strong>de</strong>tectors (outer part, large forward angles). The last 4 Silicon layers (distance<br />
from the target 40, 60, 80, and 100 cm) will consist of Silicon microstrip <strong>de</strong>tectors. The current layout<br />
foresees a pitch of 25 µm and three different strip lengths of 20, 40 and 60 mm. The strips are arranged<br />
such that the occupancy is below 2% for a central Au+Au collision at 25 AGeV. The <strong>de</strong>tectors will be<br />
double si<strong>de</strong>d with a stereo angle between the strips which has to be optimized by simulations. The<br />
ambiguities due do double (or triple) hits having a distance smaller than the strip length result in 2 (or<br />
6) ghost hits which pose a severe problem to the track reconstruction algorithms. It might be necessary<br />
to add more Silicon layers with another orientation of the strips in or<strong>de</strong>r to minimize the ambiguities.
16 Introduction and Overview<br />
Another possibility would be to reduce the length of the strips with the consequence of increasing the<br />
number of channels. The investigation of this problem is in progress.<br />
1.2.2.3 Ring imaging Cherenkov <strong>de</strong>tectors (RICH)<br />
The RICH <strong>de</strong>tector is <strong>de</strong>signed to provi<strong>de</strong> i<strong>de</strong>ntification of electrons and suppression of pions in the<br />
momentum range of electrons from low-mass vector-meson <strong>de</strong>cays. The actual layout of the RICH<br />
<strong>de</strong>tector consists of a radiator (3 gases un<strong>de</strong>r study: N2, 40% He + 60 %CH4, and 50% N2 + 50 %CH4,<br />
length 2.2 m), a mirror (3 mm Be covered with 0.5 mm glass, radius 4.5 m), and a photon <strong>de</strong>tector<br />
composed of about 100.000 photomultiplier (PM) channels (6 mm diameter, quantum efficiency 20 %).<br />
The glass window of the PMs is covered with wave-length shifter (WLS) films in or<strong>de</strong>r to increase the<br />
absorption of Cherenkov photons. Depending on the <strong>de</strong>tection threshold at small wavelengths λmin, the<br />
number of measured photons per ring ranges from 15 (λmin = 250 nm) to 33 (λmin = 120 nm). The<br />
corresponding figures of merit are N0 = 138 and 292, respectively. The expected excellent efficiency of<br />
the PM-WLS combination for Cherenkov photons has still to be confirmed by test measurements.<br />
According to simulations based on UrQMD and GEANT, about 90 rings are produced in a central Au+Au<br />
collision at 35 AGeV. However, this number strongly <strong>de</strong>pends on the <strong>de</strong>tector geometry which still needs<br />
to be optimized. The crucial task is to match the rings to the charged particle tracks. If the track position<br />
at the mirror can be <strong>de</strong>termined with an accuracy of 200 µm, and assuming a momentum resolution of<br />
1%, the mismatch of pions to electron rings is less than 10 −3 per event. This number will be consi<strong>de</strong>rably<br />
improved when taking into account particle i<strong>de</strong>ntification by time-of-flight measurement and by the TRD.<br />
Performance studies are in progress, taking into account track reconstruction and more realistic <strong>de</strong>tector<br />
properties, in or<strong>de</strong>r to optimize the <strong>de</strong>tector layout.<br />
1.2.2.4 Transition radiation <strong>de</strong>tector(TRD)<br />
Three Transition Radiation Detector stations will serve for particle tracking and for the i<strong>de</strong>ntification of<br />
high energy electrons and positrons (γ > 2000) which are used to reconstruct J/ψ mesons. According to<br />
simulations which are based on the experience obtained with the <strong>de</strong>velopment of the TRD for ALICE<br />
and of the TRT for ATLAS, pion suppression factors of up to 200 (for momenta above 2 GeV/c) at an<br />
electron efficiency of better than 90% can be achieved. In or<strong>de</strong>r to provi<strong>de</strong> sufficiently good particle<br />
tracking the position resolution should be on the or<strong>de</strong>r of 200 µm.<br />
The major technical challenge is to <strong>de</strong>velop highly granular and fast gaseous <strong>de</strong>tectors which can stand<br />
the high-rate environment of CBM in particular for the inner part of the <strong>de</strong>tector planes covering forward<br />
emission angles. For example, at small forward angles and at a distance of 4 m from the target, we expect<br />
particle rates of more than 100 kHz/cm 2 for 10 MHz minimum bias Au+Au collisions at 25 AGeV. In a<br />
central collision, particle <strong>de</strong>nsities of about 0.05/cm 2 are reached. In or<strong>de</strong>r to keep the occupancy below<br />
5% the size of a single cell should be about 1 cm 2 .<br />
Within our R&D activities we investigate both the ALICE-TRD and the ATLAS-TRT concept. Both<br />
<strong>de</strong>tector versions have to be modified in or<strong>de</strong>r to meet the CBM requirements. In the case of the ALICE-<br />
TRD, the rate capability of the read-out chambers has to be improved. Various prototypes of fast Multi<br />
Wire Proportional Chambers (MWPC) and Gas Electron Multipliers (GEM) have been tested with proton<br />
and pion beams up to intensities of 100 kHz/cm 2 and no major <strong>de</strong>terioration of the performance has been<br />
observed. The high-rate performance is required for less than 30% of the active TRD area (which is about<br />
500 m 2 in total). A <strong>de</strong>tector concept for CBM has been studied on the basis of straw tubes (ATLAS-TRT<br />
option). Here, the challenge is to build very small straw tubes which still provi<strong>de</strong> a high efficiency in the<br />
regions of highest occupancy.
1.2. The CBM experiment 17<br />
1.2.2.5 Resistive plate chambers (RPC)<br />
An array of Resistive Plate Chambers will be used for hadron i<strong>de</strong>ntification via TOF measurements. The<br />
TOF wall is located about 10 m downstream of the target and covers an active area of about 120 m 2 . The<br />
required time resolution is about 80 ps. For 10 MHz minimum bias Au+Au collisions the innermost part<br />
of the <strong>de</strong>tector has to work at rates up to 20 kHz/cm 2 . At small <strong>de</strong>flection angles the pad size is about<br />
5 cm 2 corresponding to an occupancy of below 5% for central Au+Au collisions at 25 AGeV. With a<br />
small-size prototype a time resolution of about 90 ps has been achieved at a rate of 25 kHz/cm 2 . Future<br />
R&D concentrates on the rate capability, low resistivity material, long term stability, and realization of<br />
large arrays with overall excellent timing performance.<br />
1.2.2.6 Electromagnetic calorimeter<br />
The electromagnetic calorimeter will be used to measure direct photons, neutral mesons <strong>de</strong>caying into<br />
photons, electrons and muons. Simulations and R&D have been started based on the shashlik type of<br />
<strong>de</strong>tector modules as used in HERA-B, PHENIX and LHCb. Particular emphasis is put on a good energy<br />
resolution and a high pion suppression factor.<br />
1.2.2.7 Diamond microstrip <strong>de</strong>tector<br />
A microstrip CVD diamond <strong>de</strong>tector will be used to generate the start signal for the time-of-flight measurement.<br />
These <strong>de</strong>tectors are fast and radiation hard and can be operated at particle intensities of up to<br />
10 9 ions/s.<br />
1.2.2.8 Forward calorimeter for event characterization<br />
A very precise characterization of the event class is of crucial importance for the analysis of eventby-event<br />
observables. The experimental <strong>de</strong>termination of collision centrality requires the simultaneous<br />
measurement of the charged particle multiplicity and of the energy carried away by the spectator fragments<br />
at forward angles. The <strong>de</strong>sign of a forward calorimeter for CBM will start in the near future.<br />
1.2.2.9 The DAQ and Event Selection System<br />
The measurement of open charm is the key factor shaping the architecture of front-end electronics, data<br />
acquisition, and event processing in CBM. The D-mesons will be i<strong>de</strong>ntified via the displaced vertices<br />
of their hadronic <strong>de</strong>cays. The <strong>de</strong>cision for selecting candidate events thus requires tracking, primary<br />
vertex reconstruction, and secondary vertex finding in the STS at the full interaction rate of 10 MHz.<br />
The execution time of such complex algorithms will vary strongly <strong>de</strong>pending on the centrality of the<br />
interaction. This does not match well with the conventional system <strong>de</strong>sign using triggered front-end<br />
electronics, where the information of an event can be held for a limited time, usually only a few µs, in<br />
the front-end until a first level trigger <strong>de</strong>cision prompts the data acquisition system to collect all data of<br />
an event and transport it to further processing stages.<br />
In CBM we adopt a different approach. The front-end electronics of all <strong>de</strong>tectors will be self-triggered.<br />
Each particle hit is autonomously <strong>de</strong>tected and the measured hit parameters are stored with precise time<br />
stamps in large buffer pools. The event building, done by evaluating the time correlation of hits, and<br />
the selection of interesting events is then performed by processing resources accessing these buffers via<br />
a high speed network fabric. The essential performance factor is now computational throughput rather
18 Introduction and Overview<br />
than <strong>de</strong>cision latency, which results in a much better utilization of the processing resources especially<br />
in the case of heavy ion collisions with strongly varying multiplicities. Since there are no <strong>de</strong>dicated<br />
trigger data-paths, all <strong>de</strong>tectors can contribute to the event selection from the first <strong>de</strong>cision level on. The<br />
communication and processing resources can be configured to select relevant events for a wi<strong>de</strong> range of<br />
physics signals, ranging from D and J/ψ <strong>de</strong>tection in A-A collisions over low-mass dilepton <strong>de</strong>tection in<br />
p-A collisions to ϒ <strong>de</strong>tection in p-p collisions at up to 500 MHz interaction rate.<br />
This approach is very data intensive. In CBM the data flow from the front-ends to the processing resources<br />
will be about 1 TByte/sec, and becomes feasible at affordable cost due to continued strong<br />
progress in the communication and data processing technology. The key R&D areas for CBM are the<br />
<strong>de</strong>velopment of self-triggered front-end electronics with a<strong>de</strong>quate output bandwidth, of a data processing<br />
system which allows to combine the advantages of hardware processors build from programmable logic<br />
and software processors, and last but not least, of highly efficient feature extraction and event selection<br />
algorithms adapted to such a processing environment.<br />
1.2.2.10 The HADES Detector<br />
The HADES spectrometer will be installed in the CBM cave to measure dileptons and hadrons at beam<br />
energies up to about 8 AGeV. After the planned upgra<strong>de</strong> of the HADES TOF <strong>de</strong>tector its granularity is<br />
sufficiently large to cope with the high particle multiplicity at forward angles. These measurements can<br />
be performed before the installation of the CBM <strong>de</strong>tectors is completed.<br />
1.2.3 Detector performance<br />
The performance of the CBM <strong>de</strong>tector system is studied by Monte Carlo simulations using the event<br />
generators UrQMD and PLUTO, the transport co<strong>de</strong>s GEANT3/4 and FLUKA, and the software packages<br />
VMC and CBMroot. The <strong>de</strong>velopment of the simulation framework CBMroot was one of the major<br />
achievements in 2004. The feasibility studies concentrate on the <strong>de</strong>velopment of<br />
- track and momentum reconstruction routines,<br />
- hadron i<strong>de</strong>ntification,<br />
- electron i<strong>de</strong>ntification,<br />
- trigger studies for open and hid<strong>de</strong>n charm,<br />
- analysis of dilepton pairs from the <strong>de</strong>cay of vector mesons (ρ,ω,φ,J/ψ),<br />
- i<strong>de</strong>ntification of D mesons,<br />
- i<strong>de</strong>ntification of hyperons,<br />
- event-by-event fluctuations of hadron ratios,<br />
- digitizers for the various <strong>de</strong>tector systems.<br />
Realistic track reconstruction routines are still un<strong>de</strong>r <strong>de</strong>velopment, and have not been used up to now for<br />
simulations on particle i<strong>de</strong>ntification. The feasibility studies performed so far are based on assumptions<br />
on track reconstruction efficiency, momentum resolution, <strong>de</strong>tector efficiencies, and particle i<strong>de</strong>ntification<br />
probability. Therefore, the results of the studies on dilepton pairs, D-mesons, hyperons, and hadrons are<br />
still very preliminary.<br />
Moreover, no reconstruction of complete particle trajectories from target to ECAL has been performed<br />
up to now. This requires matching of hits in the STS, RICH, TRDs, RPC, and ECAL. Such a full tracking
1.2. The CBM experiment 19<br />
is nee<strong>de</strong>d in or<strong>de</strong>r to optimize the number and relative distance of <strong>de</strong>tector stations, and the granularity<br />
and position resolution of the <strong>de</strong>tectors. Hence, the <strong>de</strong>tector layout presented in figure 1.9 is still generic,<br />
and will very likely be modified as a result of future tracking studies.<br />
Geometrical acceptance<br />
The dimensions of the <strong>de</strong>tectors are chosen such that for central nucleus-nucleus collisions at 25 AGeV<br />
and a magnetic bending power of 1 Tm more than 60% of the emitted charged particles are accepted.<br />
The acceptance does not change much as function of beam energy.<br />
Track reconstruction<br />
The track reconstruction algorithms for the Silicon Tracking System (STS) operated in the magnetic<br />
dipole field are based on methods like conformal mapping, Kalman filter, and Hough transform. The<br />
main challenge is the high track <strong>de</strong>nsity, in particular for the first two stations which will consist of pixel<br />
<strong>de</strong>tectors. Actually, the track reconstruction efficiency is better than 90% for particle momenta above<br />
1 GeV/c, but it drops rapidly towards lower momenta. The momentum resolution is better than 1 %<br />
at momenta above 1 GeV/c. The primary (secondary) vertex resolution is about 1 (10) µm in x and<br />
y, and about 6 (60) µm in z (beam) direction. The track reconstruction efficiency might be improved<br />
by lowering the magnetic field which bends the low momentum particles out of acceptance. A lower<br />
magnetic field will reduce the momentum resolution, which, however, might be improved also by taking<br />
the TRD as tracking stations into account. The optimization of the track and momentum reconstruction<br />
routines are in progress.<br />
Moreover, the algorithms do not yet take into account a realistic granularity of the STS stations. The<br />
finite hit resolution is still mo<strong>de</strong>lled by position smearing with a variance of σ = 10 µm. This seems<br />
reasonable for the pixel stations, but is ina<strong>de</strong>quate for the four strip stations which have essentially a<br />
one-dimensional resolution only. Studies are on the way to find the optimum geometry (strip length,<br />
stereo angle) for the double-si<strong>de</strong>d Silicon strip <strong>de</strong>tectors, and the optimum number of tracking stations.<br />
Hadron i<strong>de</strong>ntification<br />
The i<strong>de</strong>ntification of hadrons is based on time-of-flight measurements with the RPC which is located<br />
10 m downstream from the target. Based on the assumption of an overall time resolution of 80 ps, pions<br />
can be separated from kaons up to momenta of about 4 GeV/c with a purity of almost 100 %. For higher<br />
momenta up to about 7 GeV/c, the separation can be performed by unfolding the mass distributions using<br />
a 2D probability <strong>de</strong>nsity function. Protons can be separated from kaons up to 7 GeV/c with almost 100%<br />
purity.<br />
Low-mass vector mesons<br />
The challenge of electron-positron pair spectroscopy at low invariant masses is the large combinatorial<br />
background caused by π 0 Dalitz <strong>de</strong>cays and gamma conversions (the gammas mainly stemming from<br />
π 0 <strong>de</strong>cays). The most efficient way to reduce this background is to reconstruct the pions and gammas<br />
and to remove the corresponding electron-positron pairs from the data sample. However, this method<br />
requires a large acceptance for soft electrons/positrons. Another source of background are pions which<br />
are misi<strong>de</strong>ntified as electrons. This background becomes important if the pion suppression factor is<br />
smaller than 10 4 . This value can be achieved with RICH and TRD.<br />
For the feasibility studies of dilepton measurements we have started to take into account STS track<br />
reconstruction and electron i<strong>de</strong>ntification. Due to the still low track reconstruction efficiency for lowmomentum<br />
electrons, the reconstruction of π 0 Dalitz <strong>de</strong>cays and gamma conversions is not yet very
20 Introduction and Overview<br />
efficient in background reduction. On the other hand, the simulations <strong>de</strong>monstrate that the signal to<br />
background ratio can be significantly improved if the tracking efficiency is enhanced for low momentum<br />
particles.<br />
The measurement of low-mass electron-positron pairs requires an optimized setup, and, therefore, will<br />
most probably not be performed simultaneously with the measurements of the hadronic observables.<br />
Possible modifications presently un<strong>de</strong>r investigation are the lowering of the magnetic field strength to<br />
improve the acceptance for low-momentum electrons, the shift of the target into a field-free region, and<br />
the optimization of the Silicon Tracker configuration to reduce multiple scattering.<br />
Hid<strong>de</strong>n charm<br />
Charmonium will be i<strong>de</strong>ntified via its dileptonic <strong>de</strong>cays. In the case of electron-positron pair measurements<br />
the combinatorial background is dominated by π 0 Dalitz <strong>de</strong>cays, gamma conversion, and misi<strong>de</strong>ntified<br />
pions. Most of the background pairs are efficiently rejected by requiring a minimum transverse<br />
momentum of 1 GeV/c for single leptons. For Au+Au collisions at 25 AGeV the signal to background<br />
ratio is found to be about 3. However, this result is still preliminary as the feasibility studies are not<br />
based on reconstructed tracks and momenta.<br />
Simulations of J/ψ i<strong>de</strong>ntification via the measurement of dimuon pairs have been started. In this case the<br />
combinatorial background is caused by muons from the <strong>de</strong>cay of charged pions and kaons. One possible<br />
option is to i<strong>de</strong>ntify the muons with the ECAL which is located about 11 m downstream of the target. At<br />
this distance about 10% of the pions and about 50% of the kaons have been <strong>de</strong>cayed, and the resulting<br />
signal to background ratio is below 0.1 for Au+Au collisions at 25 AGeV. The background can be further<br />
suppressed by i<strong>de</strong>ntifying and rejecting trajectories with a kink caused by the weak <strong>de</strong>cays. This requires<br />
a realistic track reconstruction method.<br />
Simulations are in progress to study the generation of a trigger based on electron-positron pairs with high<br />
single transverse momenta (pt above 1 GeV/c for each particle) using the TRD stations only.<br />
Open charm<br />
The feasibility studies concentrated on the i<strong>de</strong>ntification of D 0 mesons via the hadronic <strong>de</strong>cay into a pion<br />
and a kaon. The challenge is to achieve the required secondary vertex resolution in or<strong>de</strong>r to suppress efficiently<br />
the background generated from prompt mesons, but also from secondary particles like hyperons<br />
and neutral kaons. The background is simulated by transporting UrQMD events through the STS using<br />
GEANT4. The simulations inclu<strong>de</strong> track reconstruction without magnetic field (straight line approximation<br />
using Kalman filter). This method allows to study the influence of multiple scattering caused by the<br />
STS stations on the secondary vertex resolution.<br />
The combinatorial background in the invariant mass spectrum of the kaon-pion pair is reduced by requiring<br />
kinematical conditions like a minimum impact parameter of the single particle tracks in the target<br />
plane and a minimum displacement of the secondary vertex in beam direction. Particle i<strong>de</strong>ntification is<br />
required in or<strong>de</strong>r to obtain a signal to background ratio better than one.<br />
According to the simulations done so far, the kinematical cuts on the displaced vertex of pions and kaons<br />
reject most of the events which do not contain a D meson. An event rejection factor of about 1000 can<br />
be achieved, reducing the primary reaction rate of 10 MHz to a level of 10 kHz which can be archived.<br />
The next step is to perform a realistic tracking in the magnetic field. Moreover, we will study the feasibility<br />
to i<strong>de</strong>ntify charged D mesons which <strong>de</strong>cay into two pions and a kaon.
1.2. The CBM experiment 21<br />
Hyperons<br />
The reconstruction of hyperons from UrQMD events using the STS tracking stations has been studied by<br />
two approaches. In one simulation the magnetic field was neglected, and the tracks including secondary<br />
vertices were reconstructed by straight line fits. Moreover, i<strong>de</strong>al particle i<strong>de</strong>ntification was assumed.<br />
In this study Lambda, Xi and Omega hyperons were reconstructed almost without background. The<br />
acceptances <strong>de</strong>pend strongly on the requirement of proton and pion i<strong>de</strong>ntification (i.e. on the acceptance<br />
of the TOF wall). The second approach is based on the assumption of i<strong>de</strong>al track and vertex finding.<br />
Track fitting and momentum reconstruction is performed in the inhomogeneous magnetic field of the<br />
dipole. The Lambda is reconstructed without i<strong>de</strong>ntification of the <strong>de</strong>cay products with an efficiency of<br />
about 20 %. The next step is to inclu<strong>de</strong> full track and vertex reconstruction with the STS in the magnetic<br />
field.<br />
Event-by-event fluctuations and collective flow<br />
Due to the large geometrical acceptance and the good particle i<strong>de</strong>ntification capability the CBM <strong>de</strong>tector<br />
is well suited to study bulk properties of the fireball like particle abundances and collective flow<br />
of particles. Simulations have been performed to study non-thermal event-by-event fluctuations of the<br />
kaon-to-pion ratio. Taking into account geometrical acceptance and hadron i<strong>de</strong>ntification, the event-byevent<br />
K/π ratio in Au+Au collisions at 25 AGeV as given by URQMD can be accurately reproduced.<br />
This means that the experimental contributions to the width of the K/π distribution are very small and<br />
dynamical fluctuations can be measured. Simulations on this subject are in progress. As the geometrical<br />
acceptance of the setup varies only little with beam energy one can perform an accurate energy scan of<br />
fluctuation observables to search for the critical endpoint of the QCD <strong>de</strong>confinement phase transition.<br />
1.2.4 Planning and organization<br />
Schedule<br />
This Technical Status Report still inclu<strong>de</strong>s alternative possible technical solutions for the CBM subsystems.<br />
It will take another two years of intensive R&D in or<strong>de</strong>r to <strong>de</strong>ci<strong>de</strong> upon the optimum layout of the<br />
experiment, the technology of the <strong>de</strong>tectors, and on the FEE, DAQ, and online event selection. We plan<br />
to submit a Technical Proposal at the end of 2006. The <strong>de</strong>tailed <strong>de</strong>sign of the CBM subsystems including<br />
prototyping leading to the Technical Design Reports will take another 3-5 years. For the construction of<br />
the components we foresee 2-3 years. Installation of the first <strong>de</strong>tector components in the CBM cave will<br />
start in 2012. Commissioning of the experiment is planned for 2014 when the operation of SIS300 starts<br />
according to the present schedule.<br />
Responsibilities<br />
Currently, the CBM collaboration consists of 42 institutions (including applications) and of more than<br />
300 persons. The organization of the CBM collaboration actually consists of a Collaboration Board<br />
with 39 members, a Technical Board with representatives of 12 subprojects, and 10 physics performance<br />
working groups.<br />
The different tasks and subsystems of CBM are divi<strong>de</strong>d into working packages which are attached to<br />
working groups. This preliminary sharing of the responsibilities is based on the interest expressed by<br />
the institutes taking into account their expertise and ongoing R&D activities. The assignment of the<br />
responsibilities is neither complete nor final. In particular, we search for new collaborating institutes to
22 Introduction and Overview<br />
participate in the activities and to take over responsibilities.<br />
Several groups and institutions which are not (yet) member of the CBM collaboration work with us on<br />
various CBM related R&D projects within the framework of EU funds (FP6 Hadron Physics and INTAS).<br />
Cost estimates<br />
Wherever possible, the costs of the CBM <strong>de</strong>tectors have been mostly estimated on the basis of similar<br />
<strong>de</strong>tectors of LHC experiments. There are still uncertainties due to different <strong>de</strong>tector options. The approximate<br />
costs are 42 - 51 M for the <strong>de</strong>tectors and the magnet, 7-9 M for data acquisition and<br />
computing, and 5 M for the infrastructure.
Part II<br />
Detector Systems<br />
23
2 The Silicon Tracking Station (STS)<br />
2.1 Introduction<br />
The CBM spectrometer concept foresees high-resolution tracking of all charged particles directly after<br />
the target. A magnetic dipole field of Bmax = 1.5 T will provi<strong>de</strong> a momentum kick of p ≈ 0.3 GeV/c<br />
over the full extension of the tracking station. The main tasks of the tracking station can be summarized<br />
as follows:<br />
• track reconstruction for all charged particles with momentum above 0.1 GeV/c and with a momentum<br />
resolution of or<strong>de</strong>r 1% at 1 GeV/c,<br />
• primary and secondary vertex reconstruction with a resolution good enough to efficiently reconstruct<br />
open charm production,<br />
• V0 track pattern recognition throughout the tracking station for reconstruction of weak <strong>de</strong>cays and<br />
recognition of electron-positron pairs from photon conversion.<br />
A particular feature of the CBM spectrometer is its high rate capability. To reach the <strong>de</strong>sign goal of<br />
10 million reactions per second a high performance read-out system has to provi<strong>de</strong> freely streaming<br />
<strong>de</strong>tector information with time stamps for event synchronization.<br />
2.1.1 Tracking in CBM<br />
The tracking philosophy in CBM is to achieve momentum measurement before particle-id <strong>de</strong>tectors<br />
are traversed. This keeps the size of the tracking station compact and permits to use silicon <strong>de</strong>tectors<br />
throughout. The technology and high position resolution of silicon <strong>de</strong>tectors allow to constrain the<br />
tracking to insi<strong>de</strong> the magnetic field volume where bending power is provi<strong>de</strong>d. Moreover, a compact<br />
field volume is of economical interest since super conducting technology can be used to provi<strong>de</strong> a high<br />
field over a comparatively short length and with a mo<strong>de</strong>rate gap height.<br />
Besi<strong>de</strong>s a good momentum resolution also the two-track separation capability is of high importance for<br />
track reconstruction with high efficiency and purity. Due to the very high track <strong>de</strong>nsity high granularity<br />
is mandatory. Close to the beam axis and near the target, pixel <strong>de</strong>tectors are the only choice. In the other<br />
regions strip <strong>de</strong>tectors will provi<strong>de</strong> sufficient granularity. High position resolution is required for efficient<br />
track reconstruction, good momentum resolution up to 10 GeV/c and secondary vertex resolution below<br />
50 µm.<br />
The Silicon Tracking Station (STS) will not contribute dE/dx information for particle i<strong>de</strong>ntification.<br />
Particle i<strong>de</strong>ntification for hadrons will mainly be provi<strong>de</strong>d by time-of-flight measurements. For lepton<br />
i<strong>de</strong>ntification Cherenkov and transition radiation <strong>de</strong>tectors as well as an electromagnetic calorimeter<br />
are foreseen. Hence, tracks reconstructed in the STS have to be matched to hits in the PID <strong>de</strong>tectors.<br />
Additional large area tracking <strong>de</strong>tectors will improve the track reconstruction performance in this respect.<br />
The current concept of the CBM spectrometer assumes that this information is provi<strong>de</strong>d by the distributed<br />
transition radiation <strong>de</strong>tectors.<br />
25
26 The Silicon Tracking Station (STS)<br />
2.1.2 Operational environment<br />
A central heavy ion reaction of Au + Au at 25 AGeV produces 1400 charged particles and more than 600<br />
hundred energetic photons in the final state. Averaged over all impact parameters the particle multiplicity<br />
is about a factor 4 smaller than the maximum multiplicity. Strong kinematical focusing of reaction<br />
products into a narrow forward angle results in extremely high track <strong>de</strong>nsities. In addition, δ-electrons,<br />
showing a nearly exponential momentum distribution, are produced by each beam particle traversing the<br />
solid target. Although most of it are curled up by the magnetic field at the target area, a substantial yield<br />
of electrons will reach the first tracking station.<br />
2.1.3 Overall geometry<br />
Track information has to be provi<strong>de</strong>d for all charged particles which are i<strong>de</strong>ntified in the particle-id<br />
<strong>de</strong>tectors behind the large gap dipole magnet. To achieve this, the magnetic field volume is filled with<br />
a minimum of 7 tracking stations, each providing true two-dimensional tracking information. These 7<br />
stations are positioned at 5, 10, 20, 40, 60, 80 and 100 cm downstream the target around the beam axis.<br />
It has to be verified, that this geometry will provi<strong>de</strong> the redundancy required by the tracking algorithms<br />
to achieve sufficient track reconstruction efficiency. To maximize the vertex reconstruction resolution,<br />
the first three tracking stations will be placed insi<strong>de</strong> a vacuum vessel which will also contain the target<br />
assembly.<br />
The exponentially dropping transverse momentum of particles emitted from the reaction zone is reflected<br />
in a steeply falling track <strong>de</strong>nsity as the radial distance from the beam axis increases. Consequently, to<br />
cover as much of the phase space as possible, the tracking <strong>de</strong>tectors have to reach as close as possible<br />
to the beam axis. On the other hand, the inner sections of the tracking stations have to be mounted on a<br />
moveable support structure to permit removing the active areas from the beam line during beam tuning.<br />
We aim in a <strong>de</strong>sign in which the inner hole of the first three tracking stations is adjustable. This would<br />
allow to optimize the acceptance for different collision system sizes and beam energies.<br />
Plane D [cm] xmax [cm] ymax [cm] Area [cm 2 ]<br />
1 5 2.5 2.5 25<br />
2 10 5 5 100<br />
3 20 10 10 400(100)<br />
4 40 20 20 1600<br />
5 60 30 30 3600<br />
6 80 40 40 5600<br />
7 100 50 50 10000<br />
Table 2.1: Geometrical properties of the silicon tracking station. D is the distance from the target, xmax and<br />
ymax the maximum extension in vertical and horizontal direction, respectively. The value in brackets refers to the<br />
amount of pixels placed in the vacuum.<br />
In the peak field region of the magnet, the transverse momentum kick between two tracking stations is<br />
of or<strong>de</strong>r 50 MeV/c. This translates to a horizontal displacement from one to the next station of typically<br />
a few millimeter <strong>de</strong>pending on the particle momentum. In a tracking station with a material budget of<br />
6 · 10 −3 X0 (a typical number for LHC silicon tracking stations) the relative error in the measurement of<br />
the displacement due to <strong>de</strong>flection in the magnetic field is ≈ 1.5 %. Assuming a position resolution of<br />
10 µm or better, the uncertainty in momentum measurement will be dominated by multiple scattering<br />
for most of the particles of interest (see Sec. 12.2). Moreover, minimal material budget is essential to<br />
minimize the secondary particle production, a critical performance issue for the trigger capability of the
2.2. The inner tracking station (ITS) 27<br />
spectrometer. Hence, low material budget is a general request to all tracking stations.<br />
The silicon tracking station is subdivi<strong>de</strong>d into two sections. The inner tracking station is optimized<br />
for precise vertexing and will be operated in vacuum. It will comprise 3 out of the 7 stations and will<br />
essentially be composed of silicon pixel <strong>de</strong>tectors. The main tracking station will contain strip sensors<br />
with varying strip geometry to accommodate for the steeply varying local hit multiplicities. The gross<br />
geometrical properties are summarized in Tab. 2.1.<br />
2.1.4 Status of R&D and <strong>de</strong>sign optimization<br />
Silicon tracking <strong>de</strong>tectors are wi<strong>de</strong>ly used in all kind of nuclear and high energy physics experiments and<br />
also in numerous medical applications. Hundreds of man-years went into the R&D of position sensitive<br />
sensors in the past <strong>de</strong>ca<strong>de</strong>. As a matter of fact, the CBM collaboration will heavily rely on <strong>de</strong>velopments<br />
achieved to implement the upcoming LHC experiments with silicon vertex <strong>de</strong>tectors. Moreover, recent<br />
R&D efforts for future high energy physics experiments are aiming on similar performance parameters<br />
like they are dictated by the needs of the CBM experiment. In this respect, two research avenues are of<br />
great importance for the CBM experiment:<br />
• Monolithic sensor technology for pixel trackers. With this technology, highest position resolution<br />
at a minimum material budget seems in reach.<br />
• Thinning technologies to produce read-out chips and in particular also double-si<strong>de</strong>d strip sensors<br />
with optimized material budget.<br />
At the time of this report, <strong>de</strong>dicated R&D on silicon <strong>de</strong>tectors for the tracking station of the CBM experiment<br />
has not been started. Hence, in the following we report the first <strong>de</strong>sign concept which will be the<br />
basis for <strong>de</strong>tailed simulations including realistic <strong>de</strong>tector responses. An important criterium to achieve<br />
the physics goals is the material budget of in particular the inner tracking station. The efficiency for open<br />
charm reconstruction steeply rises with the secondary vertex resolution. Hence, the ITS is i<strong>de</strong>ally constructed<br />
from ultra-thin high resolution sensors like they would be provi<strong>de</strong>d by monolithic sensors which<br />
combine the sensor material and the read-out structure in the same substrate. This lead us to closely<br />
collaborate with colleagues <strong>de</strong>veloping monolithic sensors for a future linear colli<strong>de</strong>r experiment. Most<br />
of the physics performance studies reported in chapter III are based on the anticipated performance of<br />
such sensors. However, concerning radiation tolerance and read-out speed there is still a gap between the<br />
performance currently achieved and the one nee<strong>de</strong>d for the ITS. A fall-back solution are hybrid <strong>de</strong>tectors<br />
as used in many experiments today. The proposed NA48 upgra<strong>de</strong> foresees a next generation hybrid<br />
<strong>de</strong>tector (giga tracker) which is close in performance to the ITS needs.<br />
2.2 The inner tracking station (ITS)<br />
2.2.1 Design aspects<br />
The high track <strong>de</strong>nsity on the tracking station close to the target <strong>de</strong>mand <strong>de</strong>tectors with ultra-high granularity<br />
above 10.000 cells per cm 2 in this region. In particular the first station behind the target faces<br />
an additional load due to δ-electrons emerging from the target. True two-dimensional pixel <strong>de</strong>tectors<br />
are chosen for this region to avoid large contribution from ghost tracks during event reconstruction. An<br />
essential requirement for the inner tracking station is a high secondary vertex resolution to reconstruct<br />
two body <strong>de</strong>cays of D-mesons. With typical laboratory momenta of the <strong>de</strong>cay particles of a few GeV/c<br />
the material budget of the tracking <strong>de</strong>tectors is a big concern. Therefore, the technology of <strong>de</strong>sire are
28 The Silicon Tracking Station (STS)<br />
X<br />
5 cm 5 cm 10 cm<br />
Figure 2.1: Configuration of the hybrid pixel modules around the beam line composing the three tracking stations<br />
of the ITS. The outer part of station 3 is not displayed.<br />
monolithic pixel <strong>de</strong>tectors. The most promising <strong>de</strong>velopment in terms of minimal material budget and<br />
resolution are Monolithic Active Pixel Sensors as <strong>de</strong>scribed in the following section. With Pixel sizes as<br />
small as 25 × 25 µm and an anticipated sensor thicknesses of 50 µm or below, such sensors promise outstanding<br />
tracking performance. As a matter of fact, to fully exploit such a performance, the ITS section<br />
of the tracking station will have to be placed in vacuum. The geometry <strong>de</strong>scribed in the following chapter<br />
was <strong>de</strong>rived to allow a realistic simulation including digitization of the GEANT track information<br />
to mimic the <strong>de</strong>tector response. It has to be seen as a generic configuration which does not yet inclu<strong>de</strong><br />
realistic <strong>de</strong>tector infrastructure.<br />
1 cm<br />
5 cm<br />
Figure 2.2: Configuration of the two types of pixel modules to form the geometry of station 1 (left panel) and 2,<br />
and the inner part of station 3 (right panel). The line types indicate different locations in the direction of the beam<br />
to allow partial overlap (staggering).<br />
We foresee to place the first two tracking stations completely insi<strong>de</strong> the vacuum. For the third station<br />
only the inner section is placed insi<strong>de</strong>. The outer part can also be ma<strong>de</strong> from silicon strip sensors and<br />
can be be situated outsi<strong>de</strong> the vacuum vessel. Such a configuration, as it is shown in Fig.2.1, allows<br />
9 cm<br />
1
2.2. The inner tracking station (ITS) 29<br />
to keep the vacuum vessel small and consequently also to use a thinner exit window. To constrain the<br />
number of different geometries we have worked out a configuration which uses only two different module<br />
geometries (see Fig. 2.2). L-shaped modules are forming the part closest to the beam axis, a rectangular<br />
shape is used for the outer region farer away from the beam axis. Such a configuration would allow to<br />
move the tracking stations in two parts away from the beam spot during focusing. The final positioning<br />
could be tuned to the level of radiation by eventually leaving a gap between the left and the right section<br />
of the sensor planes. The large symmetry in the system also allows to replace pixel modules once they<br />
suffer from radiation damage. In the closest position, the hole kept open for the beam particles has an<br />
area of 1 cm 2 , and a minimal distance between sensor and beam axis of 5 mm.<br />
2.2.2 Conceptional <strong>de</strong>sign<br />
In total 6 pixel L-shaped modules and 12 rectangular modules are nee<strong>de</strong>d to build the first three stations<br />
of the vertex tracker located in the vacuum. As a generic monolithic pixel module we assume a chip of<br />
dimension 5×10mm 2 . The sensitive part is composed of 50176 pixels of dimension 25×25 µm arranged<br />
in 392 columns with 128 pixels each. The other area contains the read-out infrastructure to process the<br />
columns in parallel. A pixel module is produced by mounting to the front si<strong>de</strong> and back si<strong>de</strong> pixel chips<br />
in such a way, that in transverse direction the coverage with active sensors is 100%. Such a configuration<br />
is shown in Fig. 2.3. A multi-layer hybrid flexible printed circuit will be placed on either surface to read<br />
out the pixel chips. For simplicity, it is not shown in the figure. The substrate will have to be actively<br />
cooled by flushing a cooling agent.<br />
Figure 2.3: Placement of the MAPS sensors on the substrate to achieve full coverage with active pixel. In this<br />
configuration 24 MAPS chips are nee<strong>de</strong>d on each si<strong>de</strong>. The total number of pixels for a module of this geometry<br />
amounts to 2 million.<br />
2.2.3 Monolithic Active Pixel Sensors (MAPS)<br />
2.2.3.1 Introductory remarks<br />
The physics goals of the CBM experiment call for unprece<strong>de</strong>nted flavour tagging performances, out of<br />
reach of established technologies in their present shape: Charge Coupled Devices (CCD) provi<strong>de</strong> the<br />
necessary granularity and may be thinned down to the thickness wanted, but are too slow and radiation
30 The Silicon Tracking Station (STS)<br />
sensitive; Hybrid Pixel Sensors, on the contrary, are fast and radiation tolerant but suffer from mo<strong>de</strong>st<br />
granularity and significant material budget.<br />
The emergence of CMOS sensors (also called MAPS 1 ) for charged particle tracking offers new perspectives<br />
in high precision vertexing and may provi<strong>de</strong> the required performances. Their <strong>de</strong>velopment, which<br />
started a few years ago, has <strong>de</strong>monstrated that this novel technology provi<strong>de</strong>s charged particle <strong>de</strong>tection<br />
with excellent <strong>de</strong>tection efficiency and spatial resolution. More recently, the issues of fast read-out, radiation<br />
tolerance and thinning were addressed. Together with the search for optimal fabrication processes,<br />
they constitute the main R&D directions of the coming couple of years.<br />
The main features of CMOS sensors and of their <strong>de</strong>monstrated performances, based on the MIMOSA 2<br />
prototype series, are summarised hereafter, emphasizing the most recent progresses. An outlook of the<br />
R&D programme towards the coming three years is provi<strong>de</strong>d next, followed by an estimate of the budget<br />
nee<strong>de</strong>d to achieve it.<br />
2.2.3.2 Main features of the technology<br />
CMOS sensors are manufactured in standard CMOS technology, which offers low fabrication costs and<br />
fast turn-over for their <strong>de</strong>velopment. The key element of this novel technology is the use of an n-well/pepi<br />
dio<strong>de</strong> to collect, through thermal diffusion, the charge generated by the impinging particle in the thin<br />
(typically 5 - 15 µm) epitaxial layer un<strong>de</strong>rneath the read-out electronics [42]. The <strong>de</strong>tection of minimum<br />
ionising particles is illustrated on Fig. 2.4.<br />
An attractive peculiarity of the sensors is that they allow to fabricate System-on-Chips (SoC) by integrating<br />
signal processing micro-circuits (amplification, pe<strong>de</strong>stal correction, digitisation, discrimination,<br />
etc.) on the <strong>de</strong>tector substrate. Moreover, the latter may be thinned down to a few tens of microns since<br />
the active volume is less than 20 µm thick.<br />
Figure 2.4: Charged particle <strong>de</strong>tection mechanism within a CMOS sensor.<br />
2.2.3.3 Detection capabilities and spatial resolution<br />
The ability of these sensors to provi<strong>de</strong> charge particle tracking is now well established [43]: several<br />
prototypes exploring various manufacturing processes and key parameters of the charge sensing, <strong>de</strong>monstrated<br />
that a <strong>de</strong>tection efficiency of 99 % and a single point resolution of 2 µm could regularly be<br />
1 standing for Monolithic Active Pixel Sensor<br />
2 standing for Minimum Ionising MOS Active pixel sensor
2.2. The inner tracking station (ITS) 31<br />
achieved, based on a pixel pitch of about 20 µm. It was also shown that digitising the charge on a small<br />
number of ADC bits (e.g. 3 bits) would not <strong>de</strong>gra<strong>de</strong> the resolution beyond ∼ 2.5 – 3 µm. The double hit<br />
resolution was also studied, and found to be ∼ 30 µm.<br />
Most of the R&D was performed with small (few mm 2 wi<strong>de</strong>) prototypes ma<strong>de</strong> of a few thousand pixels.<br />
A reticle size (i.e. ∼ 3.5 cm 2 ) sensor, composed of ∼ 1 million pixel, was also fabricated. Called<br />
MIMOSA-5, it was manufactured in batches of 6 inch wafers ma<strong>de</strong> of 33 sensors, as shown on Fig. 2.5.<br />
Figure 2.5: Wafer of reticle size sensors (left) and zoom on individual chips (right).<br />
The results of its tests at the CERN-SPS confirmed the performances obtained with the small prototypes:<br />
a <strong>de</strong>tection efficiency exceeding 99 % and a single point resolution better than 2 µm were observed.<br />
This sensor is now being used for various purposes, ranging from thinning investigations to applications<br />
of low energy electron imaging (electronic microscopy, oncotherapy beam monitoring, etc.).<br />
2.2.3.4 The challenges of speed, radiation tolerance and material budget<br />
A) Read-out speed<br />
Fast read-out strategy and obstacles: The generation of sensors <strong>de</strong>veloped until 2002 was not foreseen<br />
to allow very fast signal processing, but rather to assess the <strong>de</strong>tection capabilities and the spatial<br />
resolution of the technology. This first generation of sensors happens however to be already well suited<br />
to applications requiring frame read-out times of 1 millisecond. It fits, for instance, the requirements<br />
of the vertex <strong>de</strong>tector upgra<strong>de</strong>s foreseen in the RHIC experiments in or<strong>de</strong>r to take advantage of the luminosity<br />
increase and beam pipe radius reduction planned in the coming couple of years. The use of CMOS<br />
sensors in the CBM experiment, on the other hand, is much more <strong>de</strong>manding and imposes to shorten the<br />
read-out time by two or<strong>de</strong>rs of magnitu<strong>de</strong>, a goal which calls for a vigorous R&D programme.<br />
The general i<strong>de</strong>a leading to fast sensors consists in splitting them in numerous sub-arrays processed in<br />
parallel. This approach translates into a tremendous data flow, close to one Tbit/s/cm 2 . The achievement<br />
of a high read-out speed therefore strongly <strong>de</strong>pends on the possibility to implement on-chip hit<br />
recognition and data sparsification.<br />
On-chip processing is complicated by the smallness of the signal amplitu<strong>de</strong> (in the range of millivolts),<br />
which is not far from natural dispersions occuring in CMOS processes. Another handicap comes from<br />
the constraint of the technology: N-wells bound to serve as charge collecting dio<strong>de</strong>s, a feature which
32 The Silicon Tracking Station (STS)<br />
hampers the use of P-MOS transistors to treat the signal charge insi<strong>de</strong> the sensor sensitive area. As a<br />
consequence, signal treatment insi<strong>de</strong> pixels is essentialy limited to functionalities achievable with N-<br />
MOS transistors, those relying on P-MOS transistors being performed at the sensor edge, where no<br />
charge collection takes place.<br />
Since the charge collection time is dictated by thermal diffusion, and amounts to a few tens of nanoseconds,<br />
the ultimate read-out time achievable lies in the range of a few microseconds. The goal of the R&D<br />
is to reach this ultimate value.<br />
Present achievements: Since 2002, three different prototypes were fabricated in or<strong>de</strong>r to explore various<br />
charge collection and signal treatment architectures integrated in sensors adapted to fast, massively<br />
parallel, read-out. These architectures are based on the concept of pe<strong>de</strong>stal subtraction insi<strong>de</strong> each pixel<br />
(via correlated double-sampling) and on grouping the pixels in short columns read out in parallel, each<br />
column being equipped with a single discriminator handling the signals coming out sequentially from all<br />
pixels of the column.<br />
The first of this series of prototypes was MIMOSA-6 [44]. Each of its pixels was equipped with charge<br />
amplification micro-circuits and allows for correlated double sampling (CDS) operation in or<strong>de</strong>r to subtract<br />
the pe<strong>de</strong>stal associated to the average leakage current integrated by each sensing <strong>de</strong>vice. The chip is<br />
organised in columns grouping 128 pixels (28 µm pitch); its read-out time is close to 25 µs. A comparator<br />
is integrated at the end of each column for discrimination purposes. Tests of the prototype showed very<br />
good noise performances at the single pixel level (i.e. ∼ 15 e − ENC during the read-out phase) as well<br />
as an acceptable dispersion of the discrimination thresholds. However, substantial additional noise was<br />
observed, suspected to originate from cross-talks between the digital and analog circuits insi<strong>de</strong> the pixels<br />
and from the dispersion of the pixel characteristics insi<strong>de</strong> each column.<br />
The next generation of fast prototypes (i.e. MIMOSA-7 and -8) were fabricated in 2003 and 2004 respectively.<br />
Both chips were tested with a 55 Fe source in 2004. Particularly encouraging results were obtained<br />
with MIMOSA-8 [45] (see Fig. 2.6). Manufactured in TSMC-0.25 µm technology, its architecture is<br />
inspired from that of MIMOSA-6: it features in-pixel amplification and CDS, and is organised in 4 subarrays<br />
of 32 columns read out in parallel. Each column contains 32 pixels (25 µm pitch) and is en<strong>de</strong>d<br />
with a discriminator. Three sub-arrays are based on a pixel architecture with DC coupling to the sensing<br />
dio<strong>de</strong> and explore various dio<strong>de</strong> sizes (from 1.2×1.2 µm 2 to 2.4×2.4 µm 2 ). The fourth sub-array exploits<br />
a more complicated pixel architecture (15 transistors instead of 8) with AC coupling to the sensing dio<strong>de</strong>,<br />
which allows larger charge-to-voltage conversion gain.<br />
Preliminary tests exhibited noise levels in the or<strong>de</strong>r of ∼ 13-18 e − ENC, <strong>de</strong>pending on the sub-array, and<br />
charge-to-voltage conversion gains of 50-70 (resp. 110) µV/e − for the different DC coupling (resp. AC<br />
coupling) architectures. Moreover, the pixel-to-pixel dispersion came out to be at an acceptable level.<br />
The chip is still being tested, and may be exposed to particle beams in Spring 2005 in or<strong>de</strong>r to assess<br />
its charged particle <strong>de</strong>tection performances. Its architecture, which looks very promissing, provi<strong>de</strong>s the<br />
path to follow in 2005 for the next R&D steps towards a fast chip. The first step will allow optimising<br />
the MIMOSA-8 architecture in terms of noise, amplification, etc. Next, an ADC circuit will be integrated<br />
at the column ends, followed by the <strong>de</strong>sign of data sparsification micro-circuits. Meanwhile, the<br />
integrated architecture allowing to store and extract the cluster information is being <strong>de</strong>velopped. The<br />
choice between different possible signal processing architectures will be gui<strong>de</strong>d by the aim of keeping<br />
the power dissipation well below 1 W/cm 2 .<br />
The optimisation of the sensor performances will also <strong>de</strong>pend on features specific to each fabrication<br />
process available (see part C) of this subsection). The fabrication process exploration will therefore be<br />
conducted in parallel and in close contact with the <strong>de</strong>velopment of the sensor architecture.
2.2. The inner tracking station (ITS) 33<br />
Figure 2.6: MIMOSA-8 sub-array with AC-coupling to the sensing dio<strong>de</strong>. schematic of the pixel architecture<br />
– principle of operation scheme representing the AC-coupling of the (auto-reverse polarised)<br />
charge sensitive element and the amplifier – sensor response to its illumination with an 55 Fe source. The<br />
peak around 180 ADC units is due to 5.9 keV X-rays impinging the sensor in the <strong>de</strong>pleted volume surrounding the<br />
sensing dio<strong>de</strong>, a case where the full X-ray signal charge (i.e. ∼ 1640 e − ) is collected by a single dio<strong>de</strong> and can<br />
therefore be used for charge-to-voltage calibration purposes.<br />
B) Radiation tolerance<br />
The radiation tolerance of the sensors is a central issue of the R&D programme as the CBM running<br />
conditions are particularly harsh. CMOS sensor studies performed for their original application, i.e.<br />
light imaging, provi<strong>de</strong> only little information or use for their application to charged particle tracking.<br />
The capability of the sensors adapted to tracking to stand high radiation levels requires therefore quite<br />
extensive investigations.<br />
Radiation tolerance studies were initiated in 2002-2003, mainly based on the first two MIMOSA prototypes,<br />
which provi<strong>de</strong>d preliminary estimates of the raw technology potential. Important steps were<br />
achieved in 2004 with more recent chips, essentially with ionising radiation, which allowed to make<br />
substantial progress both in the un<strong>de</strong>rstanding of the origin of certain damages as well as in the way to<br />
improve the sensor tolerance.<br />
Bulk damage: The effect of bulk damage [46] was first investigated a few years ago, by exposing<br />
small prototypes (MIMOSA-1 and -2) to fluences of up to 10 13 neq·cm −2 . A <strong>de</strong>crease of the <strong>de</strong>tection<br />
efficiency was observed, which started to have significant consequences on the <strong>de</strong>tection efficiency for<br />
doses of about 10 12 neq·cm −2 .<br />
Similar neutron irradiations were repeated in 2004 with more recent prototypes: the reticle size sensor<br />
MIMOSA-5 and the prototype MIMOSA-9 <strong>de</strong>signed to explore a new type of fabrication process (<strong>de</strong>scribed<br />
in part C) of this subsection). The study of the irradiation effects on these chips is still to perform;<br />
it is foreseen to start early in 2005.<br />
Ionising radiation effects: The first estimates of the sensor tolerance to ionising radiation were achieved<br />
with MIMOSA-2, showing that an integrated dose exceeding ∼ 200 kRad was likely to affect the <strong>de</strong>tection<br />
performances of this sensor.<br />
Further studies were performed in 2004, with integrated doses of up to 1 MRad [47]. They rely on<br />
tests of MIMOSA-2 and of another chip (called SUCCESSOR-1), borrowed from the SUCIMA collaboration<br />
[48] which <strong>de</strong>signed it for imaging purposes. Both sensors were manufactured with the same
34 The Silicon Tracking Station (STS)<br />
fabrication process, but featured different reset transistor <strong>de</strong>signs: while the source of this (enclosed)<br />
transistor was in its center and the drain at its periphery in each MIMOSA-2 pixel, drain and source<br />
had swapped positions in SUCCESSOR-1, a feature expected to improve the chip tolerance to ionising<br />
radiation.<br />
The effect of ionising irradiation was tested by illuminating MIMOSA-2 and SUCCESSOR-1 chips, exposed<br />
to integrated doses of 400 kRad and 1 MRad, respectively, with an 55 Fe source. The response of the<br />
irradiated chips to the 5.9 keV X-rays emitted by the source is compared to that of non-irradiated chips on<br />
Fig. 2.7. The latter displays the distribution of part of the cluster charges in ADC units. While the distributions<br />
of the irradiated and non-irradiated SUCCESSOR-1 chips almost overlap, those of MIMOSA-2<br />
do not. The shift of the large peak observed for this sensor expresses a substantial charge loss due to<br />
radiation damage, which is not at all visible for the irradiated SUCCESSOR-1 chip, <strong>de</strong>spite the 2.5 times<br />
larger dose it was exposed to. Though it is not yet fully established that the improved radiation tolerance<br />
is not due to some undocumented change in the fabrication process, there is strong support for the<br />
hypothesis that the source and drain swap is at its origin.<br />
Figure 2.7: Effect of 400 kRad exposure on MIMOSA-2 (left) and of 1 MRad exposure on SUCCESSOR-1<br />
(right). The response of non-irradiated (sha<strong>de</strong>d histogrammes) and irradiated (black line) sensors is shown, when<br />
illuminated with an 55 Fe source.<br />
The radiation hardness of SUCCESSOR-1 was observed to be limited by the raise of the sensor’s sensing<br />
dio<strong>de</strong> leakage current, translating into a hampering noise level. Cooling the sensor and shortening its<br />
integration time was found to be sufficient to dim this noise to a tolerable value for integrated doses of<br />
up to 1 MRad. These observations give a strong indication that the <strong>de</strong>sign of 1 MRad resistant CMOS<br />
sensors is un<strong>de</strong>r control. Moreover, they suggest that integrated doses well above 1 MRad may be<br />
tolerable.<br />
Since the present knowledge of the sensor radiation tolerance is still quite limited and needs to be better<br />
assessed, the coming years will largely be <strong>de</strong>voted to the necessary measurements. These encompass<br />
the estimate of the tolerance itself as well as of the electrical parameters governing the reaction of the<br />
sensors to intense radiation, e.g. I-V, C-V and, more generally, reverse engineering measurements within<br />
the limits allowed by the chip manufacturers.<br />
The sensitivity of the sensors may strongly <strong>de</strong>pend on the fabrication process. Each of them needs therefore<br />
to be carefuly evaluated in terms of tolerance to bulk damage and ionising radiation effects. Clearly,<br />
priority will be given to manufacturing processes providing a feature size ≤ 0.35 µm. Transistors may be<br />
enclosed in or<strong>de</strong>r to protect them against polarity inversion induced by ionising radiation. However, this<br />
increases their size substantially, a feature which may come into conflict with the granularity required.<br />
Studies will therefore be pursued in or<strong>de</strong>r to eventually spot those transistors most exposed and active,
2.2. The inner tracking station (ITS) 35<br />
which could then be enclosed individually.<br />
The R&D effort will also touch the issue of procedures allowing to recover (at least partially) from damages<br />
due to radiation. Various treatments will be consi<strong>de</strong>red, which are mainly based on temperature and<br />
time consi<strong>de</strong>rations. The role of temperature needs actually to be investigated carefuly, and the behaviour<br />
of the sensors will be studied as a function of operating temperature.<br />
C) Exploration of fabrication processes<br />
Motivation and major issues: The capability of <strong>de</strong>veloping radiation tolerant and fast sensors <strong>de</strong>pends<br />
on basic fabrication parameters such as the epitaxial layer, the feature size, the number of metal layers,<br />
the leakage current etc., which may vary substantially from one fabrication process to another. Finding<br />
well adapted fabrication processes, which allow both integrating the necessary signal conditionning<br />
micro-circuits in the sensor and optimising its <strong>de</strong>sign with respect to ionising radiation tolerance without<br />
<strong>de</strong>grading significantly the <strong>de</strong>tection performances, is therefore a must.<br />
Several manufacturing processes have been explored up to now:<br />
• AMS-0.6 µm<br />
• AMS-0.35 µm (with and without epitaxial layer)<br />
• MIETEC-0.35 µm (which became AMI-0.35 µm recently)<br />
• TSMC-0.25 µm<br />
• IBM-0.25 µm<br />
Except of the IBM process (which exhibited a too thin epitaxial layer, presumably 2 µm), all of those<br />
processes allowed to realise prototypes with excellent <strong>de</strong>tection performances. These very satisfactory<br />
results were obtained because the noise of the pixels could be kept to ∼ 10 e − ENC, a direct consequence<br />
of the simple pixel architecture which is free of signal treatment micro-circuits such as those necessary<br />
for fast parallel read-out. These micro-circuits are expected to increase the total noise value by a factor of<br />
2 to 3, restricting the choice of the manufacturing process to those exhibiting an epitaxial layer thickness<br />
8-10 µm.<br />
Some processes, relying on a lightly doped substrate but exhibiting no epitaxial layer, allow to circumvent<br />
this handicap, the substrate acting as an effective thick (i.e. several tens of microns) sensitive volume.<br />
This was <strong>de</strong>monstrated with two prototypes (called MIMOSA-4 and SUCCESSOR-2) studied in 2003.<br />
Their tests <strong>de</strong>monstrated an outstanding <strong>de</strong>tection efficiency of up to 99.9 %, and a single point resolution<br />
of about 2.5 µm [49]. However, the cluster size happens to be rather large, especially at low operating<br />
temperature, a feature which reduces the double hit resolution of the sensor. Moreover, the absence of<br />
si<strong>de</strong> effects when thinning the sensors to ∼ 50 µm needs to be <strong>de</strong>monstrated.<br />
Another concern is the number of metal layers, which is quite often equal to 3 or 4 only in standard<br />
processes. It <strong>de</strong>serves much attention once signal treatment micro-circuits are to be integrated in the<br />
sensor, imposing to chose processes offering at least 4 metal layers.<br />
Recent achievements: The manufacturer AMS announced a new fabrication process at the end of<br />
2003, with 0.35 µm feature size and about 20 µm epitaxial layer. This process was supposed to be
36 The Silicon Tracking Station (STS)<br />
optimised for CMOS imaging applications, meaning that special care was taken of sources of leakage<br />
current in or<strong>de</strong>r to minimise the latter. MIMOSA-9 was <strong>de</strong>signed and fabricated to explore this process.<br />
It is ma<strong>de</strong> of several sub-arrays, each exhibiting a different sensing dio<strong>de</strong> or pitch size. The dio<strong>de</strong><br />
dimensions are either 3.4×4.3, 5×5 or 6×6 µm 2 . The pitch is either 20, 30 or 40 µm in both directions.<br />
Several prototypes were exposed to a ∼ 120 GeV/c pion beam at the CERN SPS. Excellent performances<br />
were observed [50], as illustrated by Fig 2.8. The signal-to-noise most probable value ranges from ∼ 20<br />
to 30, <strong>de</strong>pending on the dio<strong>de</strong> and pitch. This rather comfortable magnitu<strong>de</strong> translates into a <strong>de</strong>tection<br />
efficiency exceeding 99.5 %, even in the case of a pitch as large as 40 µm, where charge collection may<br />
show some inefficiencies due to the sizeable path achieved by some charge carriers until the sensing<br />
dio<strong>de</strong>. The single point resolution was also found to be excellent ( ∼ 1.5 µm for a 20 µm pitch).<br />
Seed pixel noise for real track cluster<br />
2500<br />
2000<br />
1500<br />
1000<br />
500<br />
0<br />
hRTN<br />
Entries 6067<br />
Mean 8.665<br />
RMS 1.247<br />
6 8 10 12 14 16 18 20 22 24<br />
Electrons<br />
Events<br />
Signal/noise in 1 pixels<br />
180<br />
160<br />
140<br />
120<br />
100<br />
80<br />
60<br />
40<br />
20<br />
hsn1<br />
Entries 6067<br />
Mean 41.07<br />
RMS 23.57<br />
Un<strong>de</strong>rflow 0<br />
Overflow 202<br />
2<br />
χ / ndf 199.8 / 131<br />
Constant 930.5 ± 18.14<br />
MPV 26.27 ± 0.188<br />
Sigma 6.521 ± 0.1017<br />
0<br />
0 20 40 60 80 100 120 140<br />
Signal/Noise<br />
Figure 2.8: MIMOSA-9 beam tests results at 0 ◦ C for pixels of 20 µm pitch hosting a 3.4x4.3 µm 2 dio<strong>de</strong>.The<br />
distribution on the left stands for the residual noise while the pixel signal-to-noise is displayed on the right si<strong>de</strong> of<br />
the figure.<br />
Overall, these results make this fabrication process most attractive. There are however two features<br />
which weaken this statement. One of them concerns the total cluster charge, which was found to be<br />
around 900 e − ENC. This amount corresponds to an epitaxial layer of ∼ 11 µm, a thickness which was<br />
confirmed by visual check with a microscope, thus infirming the 20 µm announced by the foun<strong>de</strong>r. The<br />
second source of concern is related to the leakage current. The latter was in<strong>de</strong>ed measured to be about<br />
one or<strong>de</strong>r of magnitu<strong>de</strong> below the typical values of previous chips, but it increased by close to two or<strong>de</strong>rs<br />
of magnitu<strong>de</strong> after 20 kRad irradiation with a hard X-Ray source. This increase, which raised the noise<br />
by more than a factor 2, was however not observed for all sub-structures integrated in the chip, hinting to<br />
a possibility to contain the current increase. In conclusion, <strong>de</strong>spite the weaknesses of this new fabrication<br />
process, it can still be consi<strong>de</strong>red as providing better performances than any of the other processes with<br />
epitaxy used up to now.<br />
The R&D goals of the next years will inclu<strong>de</strong> testing fabrication processes offering a feature size below<br />
0.25 µm, representative of the trend of the CMOS industry. Processes envisaged encompass IBM-0.13<br />
µm, UMC-0.18 µm (with triple well option) and AMS-0.18 µm (with low leakage current option).<br />
D) Thinning<br />
General remarks: The question of thinning was not much addressed in the first years of the sensor<br />
R&D as it was not an issue of prime importance at that time. Ultimately, it will however become so since<br />
the single point resolution offered by the sensors sets a severe constraint on the material budget if one<br />
aims to avoid swamping the resolution with multiple scattering.<br />
The thickness ambitionned is typically 50 µm and, if possible, twice less. While thinning sensors to ∼ 50
2.2. The inner tracking station (ITS) 37<br />
µm is not expected to be particularly difficult or suspected to affect the sensor performances, a thickness<br />
of about 20 µm is consi<strong>de</strong>red as a challenge. The ability of industry to achieve it with a satisfactory<br />
yield needs to be assessed. Moreover, internal mechanical stress may occur, translating into wrinkling<br />
of the chip. The answer to this si<strong>de</strong> effect may consist in glueing the chip on a thin carbon foam or<br />
beryllium support, which would ensure the necessary rigidity. A <strong>de</strong>dicated research effort is nee<strong>de</strong>d,<br />
which oughts to encompass bonding issues, to investigate such possibilities. It may profit from similar<br />
studies performed for the RHIC upgra<strong>de</strong>s and for the Linear Colli<strong>de</strong>r project.<br />
Achieved thickness: It is now established since a few years that reticle size chips (i.e. MIMOSA-5)<br />
can be thinned down by industry to 120-130 µm, without any noticeable si<strong>de</strong> effect. This is still 2 or 3<br />
times too much for the resolution ambitioned on the track origin. Attempts were ma<strong>de</strong> in 2003 and 2004<br />
to thin MIMOSA-5 sensors down to ∼ 50 µm or even much less.<br />
The most agressive thinning trials were performed for imaging purposes by the SUCIMA collaboration<br />
(E.U. 5th Framework Programme). The substrate was totally removed with a non-standard method, leaving<br />
the epitaxial layer protected by only a few hundreds (or even tens) of nanometers of thin material.<br />
This procedure, which resulted in a ∼ 15 µm thin sensor, allowed to make it sensitive to electrons of a<br />
few keV only, as <strong>de</strong>man<strong>de</strong>d for beta-imaging purposes. These sensors were exposed to ∼ 120 GeV pion<br />
beams at the CERN-SPS in or<strong>de</strong>r to assess their minimum ionising particle <strong>de</strong>tection performances. The<br />
<strong>de</strong>tection efficiency was observed to amount only to ∼ 85 %, due to a substantial drop of the charge<br />
collected. This thinning method is thus not (yet) adapted to minimum ionising particle <strong>de</strong>tection. Improvements<br />
are however not exclu<strong>de</strong>d.<br />
Another, less agressive, thinning attempt was ma<strong>de</strong>, gui<strong>de</strong>d by the <strong>de</strong>velopment for the STAR vertex<br />
<strong>de</strong>tector upgra<strong>de</strong>. MIMOSA-5 wafers were thinned down to ∼ 55 µm via LBNL collaborators with<br />
rather conventional industrial means. The first wafer thinned in this way (Autumn 2004) exhibited cracks<br />
shortly after thinning, of which the origin is still being investigated. Meanwhile, the procedure was<br />
repeated with individual sensors after their dicing. The thinned sensors were bon<strong>de</strong>d to a mezzanine<br />
DAS board using a 50 µm thin film adhesive at LBNL. Preliminary test results show that this bonding<br />
technique is efficient and that the sensor functionalities tested are all preserved.<br />
In conclusion, the procedure allowing to thin down the sensors to ∼ 50 µm is still not fully established,<br />
but the first test results are very promissing.<br />
2.2.3.5 Plans for 2005-2007<br />
A) Fast read-out<br />
In or<strong>de</strong>r to minimize the costs of prototype fabrications, the latter will be of minimal size (typically 5 –<br />
20 mm 2 ) and manufactured within multiproject runs. However, since the functionalities to integrate on<br />
the sensor require a large number of transistors (i.e. several tens of millions) integrated on each chip, the<br />
fabrication yield will be an issue. Its assessment requires fabricating medium or reticle size sensors as<br />
well, which may cost up to 200 k.<br />
Plans of prototype fabrication in the coming three years look as follows:<br />
2005: fabrication of a small prototype (TSMC-0.25 µm multiproject run) optimising the fast architecture<br />
of MIMOSA-8 (see A) in subsection 2.2.3.4) and hosting the first ADC test structures. The<br />
expected cost is ∼ 20 k.
38 The Silicon Tracking Station (STS)<br />
2006: fabrication of a small prototype (TSMC-0.25 µmmultiproject run) extending the architecture above<br />
by including an ADC at the end of each column. The expected cost is ∼ 20 k.<br />
2007: fabrication of a macroscopic prototype (engineering run) allowing to test on full scale the fast and<br />
radiation tolerant archtitecture with pre-amplification and CDS insi<strong>de</strong> each pixel and ADC at the<br />
end fo each column. The cost may be in the range 150–200 k.<br />
B) Radiation tolerance<br />
Prototyping is mainly nee<strong>de</strong>d for improving the tolerance to ionising radiation. For the two coming years,<br />
<strong>de</strong>dicated prototypes will be fabricated for this issue. The outcome of this research phase should lead to<br />
a structure to be integrated in the fast prototype fabrication scheduled for 2007 mentioned above.<br />
The plans for 2005-2007 are thus as follows:<br />
2005: fabrication of a small prototype (AMS-0.35 µm OPTO multiproject run) exploring various structures<br />
expected to improve the tolerance to ionising radiation. The expected cost is ∼ 10 k.<br />
2006: fabrication of a small prototype (multiproject run) improving and extending the structures fabricated<br />
in 2005. The expected cost is ∼ 10 k.<br />
2007: integration of the architectures <strong>de</strong>veloped in 2005 and 2006 in the macroscopic fast chip mentioned<br />
in part A) of the present subsection.<br />
Besi<strong>de</strong>s these applications, the study of the sensor sensitivity to bulk effects will continue, based on the<br />
different chips fabricated in 2004-2007 and exposed to ∼ 1 MeV neutrons in Dubna.<br />
C) Fabrication processes<br />
Several CMOS manufacturing processes based on feature sizes smaller than 0.25 µm will be explored,<br />
typically one per year. The processes presently offered by industry and potentialy of interest, are IBM-<br />
0.13 µm, UMC-0.18 µm (triple well) and the announced AMS-0.18 µm (OPTO) process. The expected<br />
cost of each prototype is ∼ 5 k.<br />
D) Thinning<br />
A thickness of ∼ 50 µmseems within reach, based on the <strong>de</strong>velopment going on at LBNL with MIMOSA-<br />
5 chips for the STAR upgra<strong>de</strong>. In or<strong>de</strong>r to minimise the <strong>de</strong>pen<strong>de</strong>nce on a single industrial supplier, it<br />
may be worth finding one or two additional provi<strong>de</strong>rs. Trying to thin the sensors below 50 µm will be<br />
the next step. Another objective will consist in thinning sensors fabricated without epitaxial layer but<br />
featuring a low doping substrate as sensitive volume.<br />
The plans for 2005–2006 look presently as follows:<br />
2005: thinning studies currently performed with MIMOSA-5 chips for the STAR upgra<strong>de</strong> at LBNL will<br />
continue. Other thinning possibilites, relying on industrial or aca<strong>de</strong>mical possibilities in Europe,<br />
will also be tried, still relying on MIMOSA-5 sensors. The stock of the latter may however get<br />
exhausted rapidly if thinning needs to be tried on wafers rather than on individual sensors. Fabricating<br />
extra MIMOSA-5 wafers may therefore become necessary. The cost is expected to be ∼ 50<br />
k.
2.2. The inner tracking station (ITS) 39<br />
2006: trials may be ma<strong>de</strong> to thin MIMOSA-5 sensors below 50 µmand/or to thin sensors without epitaxial<br />
layers. Depending on the exact operations to be done, the cost may go up to ∼ 50 k.<br />
E) Final fabrication<br />
The fabrication cost of the final sensors will <strong>de</strong>pend on parameters which are still to be <strong>de</strong>termined via<br />
<strong>de</strong>tector performance studies (total surface to cover, pixel pitch, sensor thickness, etc.) or to come out<br />
from the sensor R&D (which is aimed at finding a fabrication process offering a satisfactory tra<strong>de</strong> off<br />
between a small feature size, a thick sensitive volume, etc. and an affordable price ).<br />
A first guess suggests that the final sensors will be fabricated via 1 or 2 engineering runs in a very<br />
<strong>de</strong>ep sub-micronic process (such as IBM-0.13 µm), each costing ∼ 200 k. This estimate is based on a<br />
fabrication yield of 40–50 %. It does not account for the (large) spare lot nee<strong>de</strong>d if one aims to replace<br />
the sensors affected by radiation effects in case of high beam intensity running conditions.<br />
2.2.3.6 Framework of the R&D<br />
CMOS sensors are being <strong>de</strong>veloped in Strasbourg since 1999 in perspective of various applications,<br />
which range from vertex <strong>de</strong>tectors for subatomic physics (e.g. STAR upgra<strong>de</strong>, Linear Colli<strong>de</strong>r experiment)<br />
to bio-medical imaging (e.g. beam monitoring for oncotherapy) and operational dosimetry (e.g.<br />
control of ambient radon and neutron radiation levels in nuclear plants).<br />
Several application domains call for SoCs providing fast read-out speed, high radiation tolerance, minimal<br />
material budget and low power dissipation. Developments for the CBM experiment will thus benefit<br />
from the synergy with the R&D aiming for other applications, in terms of fabrication process exploration,<br />
<strong>de</strong>velopment of fast signal processing architectures, radiation tolerance investigations and improvements,<br />
thinning procedures, etc. More information on the activities and achievements of the Strasbourg research<br />
team is available in [51].<br />
2.2.4 Alternative technologies<br />
Monolithic pixel sensors are certainly the <strong>de</strong>tectors of choice for the CBM ITS once the technological<br />
problems still existing today are solved. Besi<strong>de</strong>s several <strong>de</strong>sign issues which will require only mo<strong>de</strong>rate<br />
R&D, the main progress has to be ma<strong>de</strong> with respect to radiation tolerance and read-out speed. Only<br />
with this type of <strong>de</strong>tector integral material budget per active layer substantially below 0.5 % are in reach.<br />
The R&D efforts to overcome these drawbacks can not be carried out by the CBM collaboration but<br />
rather strong cooperation with groups working in <strong>de</strong>tector <strong>de</strong>velopment for future high energy physics is<br />
nee<strong>de</strong>d. As a fall back solution in case the progress in R&D will fall behind the projected time schedule<br />
for construction of the CBM experiment, we envisage to use hybrid technology. The larger material<br />
budget will have some impact on the physics performance, but not in all cases high vertex resolution<br />
is of high importance. In the following, we present a scenario assuming hybrid pixel, which is used<br />
to conduct <strong>de</strong>tailed performance study using realistic <strong>de</strong>tector geometries. An alternative technology<br />
aiming at monolithic sensors is presented in the subsequent section.<br />
2.2.4.1 Hybrid pixel <strong>de</strong>tectors<br />
Present hybrid pixel tracking <strong>de</strong>tectors fulfil most of the performance parameters required for operation<br />
in the CBM experiment. The major drawback is the high material budget and, to some extend, the minimum<br />
pixel size achievable, which itself is dictated by the area nee<strong>de</strong>d to place the electric components
40 The Silicon Tracking Station (STS)<br />
necessary to read out a pixel. Compared to the monolithic pixel <strong>de</strong>tector, the main difference here is the<br />
fact that the read-out chip is produced in standard CMOS technology and thus not limited in the <strong>de</strong>sign<br />
complexity. The MAPS read-out structures in contrast are implemented on the sensor substrate and are<br />
thus restricted to NMOS transistors [52].<br />
The pixel read-out chips <strong>de</strong>veloped for LHC experiments in general provi<strong>de</strong> fast enough read-out speed.<br />
The <strong>de</strong>vices are triggered by the bunch crossing which appear at a rate of 40 MHz. Pixels which show an<br />
integrated charge above a programmable threshold generate their address number and a number proportional<br />
to the charge on the pixel. The latter is a time-above-threshold (ATLAS) or the integrated current<br />
pulse (CMS). It was shown by the CMS collaboration that a digitization of 3 bit resolution is sufficient<br />
to reach a position resolution substantially smaller than the pixel size divi<strong>de</strong>d by √ 12.<br />
In a broad R&D effort by the RD42 collaboration it was shown that pixel sensor material can be produced<br />
with sufficient radiation hardness. The major breakthrough came from the discovery, that oxygenated<br />
silicon is radiation hard against damage caused by non-ionizing energy loss due to protons or pions [53].<br />
The read-out chips are produced in radiation hard DSM technology and show stable operation up to<br />
fluency of 10 15 neq.<br />
The material budget used for <strong>de</strong>tector infrastructure, i.e. support, cooling and connectivity, amounts<br />
to typically 50 % of the total material budget. The read-out chip are usually thinned down after being<br />
bon<strong>de</strong>d to the sensor chip. Substantial progress in optimizing this operation was achieved in recent years.<br />
The thickness of the sensor cannot be reduced beyond presently below current values without loosing<br />
to much signal. The sensor thickness also influences the <strong>de</strong>gree of charge sharing between neighboring<br />
pixels. A compilation of performance parameters of some pixel <strong>de</strong>tectors systems in high energy physics<br />
is given in Tab. 2.2.<br />
Experiment Pixel geometry Sensor Chip Infrastructure Total<br />
µm 2 µm µm X/X0 % X/X0 %<br />
ALICE SPD 50 × 400 200 150 0.44 0.81<br />
CMS 100 × 150 285 175 0.51 1.0<br />
ATLAS 50 × 400 280 150 0.16 0.7<br />
BTEV 50 × 400 250 200 0.77 1.25<br />
ITS 100 × 140 200 150 0.13 0.5<br />
Table 2.2: Parameters of pixel tracking stations to be used in upcoming high energy experiments.<br />
Conceptional <strong>de</strong>sign of a ITS with hybrid pixels.<br />
As a standard <strong>de</strong>tector module we assume a sensor geometry of 2 × 5 cm 2 which will be read-out by<br />
five read-out chips bon<strong>de</strong>d to the sensor. A read-out chip is assumed to have an active cell size of<br />
100×140 µm 2 with the cells arranged in 100 rows and 140 columns (edge effects due to inactive regions<br />
at the chip bor<strong>de</strong>rs are neglected at this stage of the simulation). A single chip would thus cover 14.000<br />
pixels. We assume a modified geometry with six read-out chips for the modules being placed close to<br />
the beam axis. The layout of the two types of modules is <strong>de</strong>picted in Fig. 2.9<br />
Each module would be installed on a support structure ma<strong>de</strong> of carbon substrate which would also<br />
provi<strong>de</strong> cooling. The assumed material budgets are extrapolated from the numbers listed in table 2.2<br />
assuming mo<strong>de</strong>rate progress in the material budget for the <strong>de</strong>tector infrastructure since lower power consumption<br />
due to 0.13 µm technology could reduce the cooling efforts. In addition we take the advantage<br />
to place the connecting bus outsi<strong>de</strong> the active area of the innermost modules.
2.2. The inner tracking station (ITS) 41<br />
Figure 2.9: Conceptional <strong>de</strong>sign of the hybrid pixel modules used for simulation.<br />
2.2.4.2 SOI sensors for the PVL<br />
The MIMOSA chip relies on bulk CMOS technologies and thermal diffusion of the charge generated<br />
in a lightly doped epitaxial layer towards the collecting N-wells. In such a solution, however, due to<br />
the small <strong>de</strong>tector active volume the charge generated by a minimum ionising particle is small (of or<strong>de</strong>r<br />
of few hundreds up to 1000 electrons) and only NMOS circuitry may be implemented in the front-end<br />
electronics. The kind of the sensors that does not suffer from these limitations is a monolithic active<br />
pixel sensor realized in Silicon on Insulator technology (SOI sensors). The concept of this <strong>de</strong>vice relies<br />
on the utilization of both silicon layers (support and <strong>de</strong>vice layers) of the SOI substrate for the realization<br />
of the pixel <strong>de</strong>tector dio<strong>de</strong>s and the readout electronics respectively. Fabrication of a monolithic active<br />
pixel <strong>de</strong>tector in the SOI substrate may potentially not only lead to good <strong>de</strong>tection efficiency and short<br />
charge collection times, but also to improved circuit immunity for single event radiation effects (SEE)<br />
and to increased <strong>de</strong>sign flexibility due to the possibility of use of transistors of both types in the readout<br />
channel.<br />
In contrast to the CMOS sensors, the manufacture of the SOI sensors requires a <strong>de</strong>dicated non-standard<br />
technology, which results in higher costs and longer production times at the early stages of the <strong>de</strong>velopment.<br />
Nevertheless, once the technology is <strong>de</strong>fined these problems can be overcome and the stability<br />
and continuity of the production is guarantied. It is also worth to point out that the growing interest of<br />
the semiconductor industry in the SOI sensors <strong>de</strong>velopment has been observed recently which may lead<br />
to the easier access to the advanced submicron technologies for the sensor manufacturing and thus to the<br />
improved performance of the future prototypes.<br />
The <strong>de</strong>velopment of the SOI sensors was started just few years ago, but <strong>de</strong>tection efficiency of such<br />
<strong>de</strong>tectors has been already <strong>de</strong>monstrated in series of tests. The radiation tolerance and the fast read-out<br />
operation must be however still investigated and will be the key issues of the future <strong>de</strong>velopment.<br />
Main features and R&D status of the SOI sensors.<br />
The operation of the SOI sensors relies on the <strong>de</strong>tection of the ionising radiation in the high resistivity<br />
support layer of the SOI wafer and the signal processing in the readout electronics created in the <strong>de</strong>vice<br />
layer of the same wafer [55]. The cross-section of such <strong>de</strong>vice is presented in figure 2.10. As it is<br />
presented, the charge sensitive part of the sensor has a conventional form of reversed biased p+-n junctions.<br />
The collecting dio<strong>de</strong>s are monolithically coupled with the read-out electronics by a connection<br />
that passes through the ultra-thin silicon film and the buried oxi<strong>de</strong> (BOX). The attractive feature of the<br />
SOI sensor is the separation of the <strong>de</strong>tector and electronics active volumes. It allows the integration of
42 The Silicon Tracking Station (STS)<br />
Figure 2.10: Integration of particle sensor and readout electronics in the SOI substrate.<br />
the advanced signal processing (amplification, pe<strong>de</strong>stal correction, filtering, discrimination, digitisation,<br />
etc.) directly in the readout cell using standard solutions of the Complementary MOS circuit theory.<br />
The key feature of the <strong>de</strong>veloped SOI sensor is the exploitation of the wafer-bon<strong>de</strong>d SOI substrates<br />
for the integration of the particle sensor and readout electronics in one entity. Such approach allows the<br />
optimisation of the resistivity of the <strong>de</strong>tector and electronics substrates. The further important advantages<br />
of the wafer-bon<strong>de</strong>d substrates in comparison with other popular SOI substrates obtained in the SIMOX<br />
process are also lower level of the structural <strong>de</strong>fects in both the <strong>de</strong>vice layer and the handle wafer, absence<br />
of silicon inclusions and islands in the buried oxi<strong>de</strong> (BOX), and lower temperature processing. All of<br />
those characteristics of the wafer-bon<strong>de</strong>d substrates are of high importance from the <strong>de</strong>tector quality<br />
point of view.<br />
The concept of the SOI sensor has been already validated by the successful production and tests of<br />
several iterations of small area test <strong>de</strong>tectors. Recently a larger, fully functional prototype of the SOI<br />
<strong>de</strong>tector, which consists of more than 16 thousands channels and covers the active area of 4 cm 2 , was<br />
also produced and is currently un<strong>de</strong>r investigation. The photo of the 4-inch wafer of SOI <strong>de</strong>tector test<br />
structures and the photo of the new large area prototype are shown in figure 2.11.<br />
Future <strong>de</strong>velopment for the CBM experiment.<br />
The <strong>de</strong>velopment of the SOI sensor for the CBM experiment requires addressing such important issues<br />
as <strong>de</strong>vice thinning, <strong>de</strong>velopment of the fast readout electronics and radiation hardness. These problems<br />
are the crucial elements of the R&D framework for the next years and will be shortly <strong>de</strong>scribed in the<br />
following.<br />
Thinning issues: In contrast to the CMOS sensors, where the amount of the charge generated by an<br />
ionising particle is <strong>de</strong>termined by the technology parameters, in the SOI sensors the charge signal is<br />
proportional to the sensor thickness. For this reason the sensor thickness should be optimised for the<br />
particular application and must be a result of the compromise between the acceptable materials budged<br />
of the tracking system and the <strong>de</strong>sired signal to noise ratio.<br />
For the SOI sensors the same thinning technologies as for the hybrid or CMOS sensors may be applied.<br />
Thinning down to 50 µm is already within the reach of existing technologies and should not be a problem.<br />
Together with the progress in the field of the thinning techniques the sensor thickness reduction below<br />
50 µm can be also consi<strong>de</strong>red. In such case however the thinning si<strong>de</strong> effects, such as mechanical stress<br />
will have to be assessed.
2.2. The inner tracking station (ITS) 43<br />
Figure 2.11: The photo of the wafer with SOI <strong>de</strong>tector test structures (left) and the photo of a first fully functional<br />
SOI sensor prototype, covering active area of 4 cm 2 and consisting of about 16.000 readout channels (right) .<br />
When the SOI sensor thinning is discussed it should be also emphasised that almost the whole SOI<br />
sensor thickness is the <strong>de</strong>tector active volume. The total thickness of the electronics and buried oxi<strong>de</strong><br />
layers does not exceed 2.2 µm (can be reduced to several hundreds of nanometres) and thus only slightly<br />
contribute to the material budged of the tracking system.<br />
Radiation tolerance studies: The radiation tolerance study of the SOI sensor is a complex problem. It<br />
has to take into consi<strong>de</strong>ration the radiation damages of several regions of the sensors: the electronics<br />
part, the <strong>de</strong>tector active volume and the buried oxi<strong>de</strong>. For each of the regions different radiation damage<br />
mechanism will be dominating and different radiation har<strong>de</strong>ning method will have to be applied. It<br />
might be expected that in case of the SOI sensor, which characterizes by the implementation of the<br />
readout electronics in relatively thin silicon film, the problem of the front-end electronics immunity<br />
to the single event effects caused by high energy particles will be of lower importance. Nevertheless<br />
the total ionisation dose effects and the total displacement effects will still have to be assessed. In the<br />
terms of sensor resistance to the <strong>de</strong>tector bulk damages it is possible that some experience gained during<br />
the <strong>de</strong>velopment of the radiation hard <strong>de</strong>tectors for the LHC experiments might be adopted in the SOI<br />
sensors. In particular the wafer bonding technique does not exclu<strong>de</strong> the usage of such <strong>de</strong>tector materials<br />
as the diffusion oxygenated float-zone silicon or the high resistivity Czochralski silicon. In the hitherto<br />
<strong>de</strong>velopment however only the classical FZ silicon substrates have been exploited. As long as the sensor<br />
sensitivity for the total ionisation dose is discussed the radiation damages of the gate, field and buried<br />
oxi<strong>de</strong>s have to be consi<strong>de</strong>red. The influence of the charge trapping in the field oxi<strong>de</strong> on the circuit<br />
performance may be probably effectively reduced by the proper <strong>de</strong>sign techniques, but the gate oxi<strong>de</strong><br />
damages even in the case of the 0.6 µm technology may still play an important role and will have to be<br />
carefully studied. Even more attention should be paid to the investigations of the results of the BOX<br />
radiation damages, since this problem is a peculiarity of the SOI sensor.<br />
The radiation tolerance of the sensor has not been addressed so far and will have to become one of the<br />
main tasks of the future <strong>de</strong>velopment. The total dose effects will be studied with the 10 keV X-ray<br />
generator in Karlsruhe or at CERN and the bulk damages will be investigated in the tests with a neutron<br />
beam. The extensive radiation hardness experiments will be accomplished by the 3-D <strong>de</strong>vice simulations<br />
performed with the ISE-TCAD package, which will allow examining the main origins of the radiation<br />
sensitivities of the SOI <strong>de</strong>tectors.
44 The Silicon Tracking Station (STS)<br />
Development of the fast readout: The simplest method of the fast readout <strong>de</strong>velopment is the segmentation<br />
of the <strong>de</strong>tector and the parallel readout. Such technique has been already implemented in the recent<br />
SOI sensor prototype where the total <strong>de</strong>tector matrix was divi<strong>de</strong>d into 4 sub-matrices with 64 by 64 readout<br />
channels each. Such method in the case of the large <strong>de</strong>tection systems leads however to the dramatic<br />
increases of the data flow. For this reason more advanced techniques, relying on the preliminary data<br />
reduction in the readout electronics will have to be applied.<br />
In case of SOI sensors the implementation of the signal pre-processing in the readout cell seems to be a<br />
simpler task than in the CMOS sensors, since the SOI approach allows the usage of both transistor types<br />
(PMOS and NMOS) in the readout cell. The integration of the advanced electronics directly in the readout<br />
channel is still restricted by the limited access to the <strong>de</strong>ep submicron technologies for the SOI sensor<br />
production and the maximum available area for a single channel of the pixel <strong>de</strong>tector. The reasonable<br />
solution may be integrating basic signal processing (correlated double sampling, discrimination, etc.) in<br />
the readout cell and exporting more complicated operations (signal digitisation and data sparsification)<br />
to the readout circuit peripheries.<br />
Framework of the R&D.<br />
The SOI sensors are being <strong>de</strong>veloped in the collaboration between Institute of Electron Technology in<br />
Warsaw and AGH-University of Science and Technology in Krakow since 2001. The work on the new<br />
sensor generation are mainly motivated by <strong>de</strong>mands of the medical applications (beam monitoring in<br />
hadrontherapy, dosimetry of radioactive source for brachytherapy) and requirements of future nuclear<br />
physics experiments. The main research goal is the <strong>de</strong>velopment of a pixel <strong>de</strong>tector that would be free of<br />
such limitation of the existing technologies, like the high material budget or low signal levels generated<br />
by the ionising particles. The R&D framework of the SOI sensor is thus in agreement with the <strong>de</strong>mands<br />
of the CBM experiments. More information about achievements of the Krakow research group may be<br />
found on the webpage of the SUCIMA project [48].<br />
2.3 The Silicon Strip Tracker (SST)<br />
2.3.1 General <strong>de</strong>sign consi<strong>de</strong>rations<br />
The challenge for the CBM Silicon Strip Tracker (SST) is to measure with high precision and efficiency<br />
the trajectories of up to 1000 charged particles per event at event rates of up to 10 MHz. The <strong>de</strong>sign of<br />
the CBM Si-Strip Tracker is <strong>de</strong>termined by the following requirements:<br />
• high granularity to keep the occupancy below a few percent<br />
• high position resolution for momentum <strong>de</strong>termination and for extrapolation of the measured tracks<br />
towards the Silicon Pixel vertex <strong>de</strong>tectors<br />
• low material budget to reduce multiple scattering<br />
• large acceptance, i.e. angular coverage from 50 to 500 mrad corresponding to the acceptance of<br />
the spectrometer<br />
• stand-alone pattern recognition<br />
• time resolution sufficient to provi<strong>de</strong> the event time stamp required for a data driven FEE and DAQ<br />
architecture
2.3. The Silicon Strip Tracker (SST) 45<br />
• operation in a harsh radiation environment.<br />
• cost effective <strong>de</strong>tector layout<br />
The HEP community has great experience in the <strong>de</strong>sign and <strong>de</strong>velopment Si-strip sensors and precision<br />
Si-strip tracking systems. For example, Si-strip vertex <strong>de</strong>tectors were successfully operated in a fixed<br />
target configuration in HERA-B at DESY [56], and are proposed for the VELO <strong>de</strong>tector [57] and<br />
the Inner Tracker [58], both part of the LHCb experiment at CERN. Similarly, the Si-strip STS for<br />
CBM exhibits a forward spectrometer configuration: The <strong>de</strong>tectors planes are mounted in subsequent<br />
layers perpendicular to the beam axis at appropriate distances to provi<strong>de</strong> optimal conditions for pattern<br />
recognition and momentum measurement in a magnetic field. The total length of the tracking system<br />
(including the Pixel vertex <strong>de</strong>tector) is about 1 m in or<strong>de</strong>r to fit into the spectrometer magnet. The<br />
general layout of the CBM Si-Strip STS is presented in figure 2.12.<br />
4 Si−STS stations<br />
cross section at x=0:<br />
X<br />
STS4<br />
0 10 20 cm<br />
STS5<br />
STS6<br />
STS7<br />
500 mrad<br />
50 mrad<br />
Figure 2.12: Arrangement of the Si-strip layers along the beam axis. The dashed lines indicate the maximum<br />
and minimum angular coverage of the Si-Strip STS<br />
The actual layout of the Si-Strip Tracker features 4 layers with a relative distance of 20 cm. The number<br />
of layers, however, as well as their positions are subject of further optimization based on simulations<br />
of track reconstruction in the inhomogeneous magnetic field. The first and the last layer are located at<br />
distances of 40 cm and 100 cm downstream from the target (z 0 cm). The minimum distance ri from<br />
the active <strong>de</strong>tector area to the beam axis is 2 cm at z 40 cm and 5 cm at z 100 cm. The positions and<br />
the inner and outer radii of the layers are listed in Table 2.3. As indicated in Fig. 2.12, all tracks with<br />
angles between 50 mrad ≤ θ ≤ 500 mrad will cross the 4 Si-strip layers. The number of measured space<br />
points will be sufficient to reconstruct the tracks in the magnetic field with the required efficiency and<br />
resolution.<br />
Z
46 The Silicon Tracking Station (STS)<br />
2.3.1.1 Low-mass double-si<strong>de</strong>d Si-strip Sensors<br />
Number Position ri ro<br />
[mm] [mm] [mm]<br />
1 40 20 200<br />
2 60 30 300<br />
3 80 40 400<br />
4 100 50 500<br />
Table 2.3: Positions of Si-strip planes along z-axis.<br />
Mo<strong>de</strong>rn Silicon technologies achieve strip pitch values as small as 25 µm resulting in a coordinate resolution<br />
of about 8 µm. In this case the precision of track reconstruction is limited mainly by multiple<br />
scattering in the material of the silicon <strong>de</strong>tectors. In or<strong>de</strong>r to benefit from the excellent intrinsic position<br />
resolution of the Si-strip <strong>de</strong>tectors we propose to use very thin (100 µm) double-si<strong>de</strong>d Si micro-strip sensors<br />
for the CBM tracking system. Such thin <strong>de</strong>tectors are highly <strong>de</strong>sirable since many relevant quantities<br />
scale favorably with <strong>de</strong>creasing thickness w [59]:<br />
• multiple scattering contribution ∝ √ w ,<br />
• leakage current ∝ w ,<br />
• full <strong>de</strong>pletion voltage ∝ w 2 , and<br />
• power dissipated in sensitive area ∝ w 3 .<br />
On the other hand, a reduction of the <strong>de</strong>tector thickness implies also a reduction of the signal-to-noise<br />
ratio (S/N) <strong>de</strong>pending on the relative contributions from series (ENCS) and parallel (ENCP) noise:<br />
rL · rC · S280 · (w/280µm)<br />
S/N = <br />
ENC2 S + ENC2 P280 · (w/280µm)<br />
where S280 <strong>de</strong>notes the most probable charge <strong>de</strong>position (23300 electrons) of a minimum ionizing particle<br />
in a 280 µm thick silicon <strong>de</strong>tector, and rL and rC account for Landau fluctuations and charge collection<br />
<strong>de</strong>ficits after exposure to high particle fluxes.<br />
Fortunately, the beneficial effects of a reduced <strong>de</strong>tector thickness scale, in general, with a higher power<br />
of w than the loss in S/N. Fig. 2.13 <strong>de</strong>picts the signal-to-noise ratio according to eq. 2.1 assuming a<br />
quite strong signal reduction (rL = 0.67 and rC = 0.9). For the indicated realistic values for series and<br />
parallel noise a sensor as thin as 150 µm is expected to yield still an acceptable signal-to-noise ratio of<br />
almost 8. Our goal is to reach a Si-sensor thickness of 100 µm. Another advantage of such a thin <strong>de</strong>tector<br />
is that the corresponding full <strong>de</strong>pletion voltage would be a factor of 2 lower as compared to a 300 µm<br />
<strong>de</strong>tector. If <strong>de</strong>tectors as thin as 100-150 µm would become available, the Si-strip STS lifetime thus could<br />
be significantly exten<strong>de</strong>d, practically without loss of performance.<br />
The choice of single or double si<strong>de</strong>d sensors for CBM is still an open issue. Clear arguments in favor of<br />
using double si<strong>de</strong>d sensors are :<br />
• savings in radiation length of up to 50 % per sensor layer,<br />
• intrinsic high precision alignment of front and back strip dio<strong>de</strong>s,<br />
(2.1)
2.3. The Silicon Strip Tracker (SST) 47<br />
Figure 2.13: Signal-to-noise ratio S/N as a function of <strong>de</strong>tector thickness for indicated equivalent noise charges<br />
of series and parallel noise ENCS/ENCP280 in electrons (see eq. 2.1). The parallel noise value ENCP280 applies<br />
to a 280 µm thick <strong>de</strong>tector.<br />
• up to 50 % reduction of heat generation from leakage current.<br />
On the other hand, unique advantages of single si<strong>de</strong>d <strong>de</strong>tectors are:<br />
• operation at partial <strong>de</strong>pletion,<br />
• non-floating readout electronics,<br />
• availability of ≤ 280 µm n-type wafer material.<br />
Obviously, the final <strong>de</strong>cision has to await further clarifications, in particular, as other criteria like final<br />
costs, yield, reliability, and, last but not least, radiation hardness have to be taken into consi<strong>de</strong>ration.<br />
Generally, double-si<strong>de</strong>d Si-strip sensors are more suitable for the CBM conditions, and we hope to<br />
benefit from the impressive <strong>de</strong>velopment of Si-strip sensor technology.<br />
2.3.1.2 Long Lad<strong>de</strong>r Si-strip Sensor Technology<br />
Further optimization of the material budget may be achieved with the mo<strong>de</strong>rn long lad<strong>de</strong>r technology for<br />
the production of Si-strip <strong>de</strong>tectors, which excee<strong>de</strong>d the maximum size of the commercially available<br />
Si wafers. This technology provi<strong>de</strong>s the possibility to significantly reduce material and elements insi<strong>de</strong><br />
the sensitive area of the Si-strip STS, in particular the front-end electronics and the number of readout<br />
electronics channels.<br />
The number of readout channels is <strong>de</strong>fined by the readout pitch of 25 µm and the <strong>de</strong>tector dimensions. In<br />
the final sensor layout the readout pitch can be slightly readjusted such that the numbers of stereo strips<br />
on a wafer are integer multiples (1/2 or 1/4), i.e. the standard number of channels integrated on a readout<br />
chip. A power consumption of a few mW is assumed per readout channel. For the output line drivers it<br />
should be consi<strong>de</strong>rable less.<br />
2.3.2 Geometry of the Si-strip tracker<br />
Simulations based on GEANT4 within the CBM virtual Monte Carlo framework were performed in<br />
or<strong>de</strong>r to optimize the layout of the Si-strip tracker. The realistic geometry of the <strong>de</strong>tector is shown in
48 The Silicon Tracking Station (STS)<br />
fig. 2.14 as it is implemented in GEANT4. In this layout, the first three (vertex tracker) planes of the STS<br />
are hid<strong>de</strong>n insi<strong>de</strong> the conical beam pipe, and the four layers of the Si-strip tracker are visible as <strong>de</strong>tector<br />
planes. For better visualization the yoke of the magnet has been removed, and only the magnet pole shoes<br />
are shown. In or<strong>de</strong>r to optimize the performance of the Si-Strip tracker for high track <strong>de</strong>nsities, central<br />
Au+Au collisions at 25 AGeV as generated by the UrQMD co<strong>de</strong> have been studied. The corresponding<br />
radial occupancies along the x axis in the central parts for the 4 planes of Si-strip tracker are presented<br />
in figure 2.15. The highest hit <strong>de</strong>nsity is expected for the inner part of the first Si-Strip tracker plane<br />
(STS4). Given the radial distributions of charged particle <strong>de</strong>nsities as shown in figure 2.15, the size of<br />
the Si-Strip sensors can be <strong>de</strong>fined:<br />
• strip pitch of 25 µm<br />
• occupancy of 2.5 %.<br />
• strip length of 2 cm in regions close to the beam<br />
Figure 2.14: The geometry of Si-Strip STS in GEANT 4 CBM Virtual MC<br />
In or<strong>de</strong>r to reconstruct the charged particle tracks efficiently and to obtain a momentum resolution in<br />
the or<strong>de</strong>r of 1%, the space resolution of the Si-strip <strong>de</strong>tector should be in the or<strong>de</strong>r of ≈50 µm in both<br />
coordinates. The two-dimensional position sensitivity will be provi<strong>de</strong>d by the double-si<strong>de</strong>d stereo angle<br />
topology of Si-strip sensors. Using this his method one has to find a compromise between the maximal<br />
possible space point resolution and the fake rate which is a feature of stereo strip topology of sensors. The<br />
performance of the different <strong>de</strong>sign options has been studied in simulations based on GEANT4 Virtual<br />
Monte Carlo, applying algorithms of hit production with strip structures close to the real <strong>de</strong>sign of double<br />
si<strong>de</strong> Si-strip sensors. A sketch of the Si-strip sensor geometry is shown in figure 2.16 together with the<br />
hit <strong>de</strong>finition. In the first step of the analysis we did not inclu<strong>de</strong> the mechanism of charge splitting<br />
between neighbored strips as illustrated in figure 2.16. The space point resolution can be estimated from<br />
the Si-strip sensor topology. The resolution given by the pitch (coordinate 1) is<br />
σ1 = ps<br />
√12<br />
(2.2)
2.3. The Silicon Strip Tracker (SST) 49<br />
/event<br />
2<br />
Hits/cm<br />
/event<br />
2<br />
Hits/cm<br />
STS 4, z = 0.4(m)<br />
6<br />
5<br />
4<br />
3<br />
2<br />
1<br />
0<br />
0 2 4 6 8 10 12 14 16 18 20<br />
x [cm]<br />
STS 6, z = 0.8(m)<br />
1.6<br />
1.4<br />
1.2<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
0<br />
0 5 10 15 20 25 30 35 40<br />
x [cm]<br />
/event<br />
2<br />
Hits/cm<br />
/event<br />
2<br />
Hits/cm<br />
STS 5, z = 0.6(m)<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
0<br />
0 5 10 15 20 25 30<br />
x [cm]<br />
STS 7, z = 1(m)<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
0<br />
0 5 10 15 20 25 30 35 40 45 50<br />
x [cm]<br />
Figure 2.15: Charged particles occupancy in the four Si-strip planes as a function of the horizontal distance (in<br />
cm) from the beam centre.<br />
with ps the pitch of the Si-strip sensors.<br />
For a Si-strip pitch size of 25 µm the resolution is σ1 = 7.2 µm. The resolution in the perpendicular<br />
coordinate 2 is given by:<br />
σ2 = 2 × (ps) × 0.8<br />
√ 12 ×tg(θ)<br />
with 0.8 the correction factor for the non uniform distribution of the cross section along the coordinate 2<br />
and θ the stereo angle. For a stereo angle of 15 ◦ and a pitch size of 25 µm the resulting resolution is σ2 =<br />
46 µm. The analysis of charge division between neighbouring strips will significantly improve the space<br />
point hits resolution.<br />
The number of fake hits is given by:<br />
with n the number of real hits in the area of overlapping stereo strips.<br />
(2.3)<br />
Nf ake = n × (n − 1) (2.4)<br />
For particle occupancies corresponding to central Au+Au collisions and a stereo angle of 15 ◦ the expected<br />
number of fake hits in the innermost parts of the Si-strip plane STS4 amounts up to 80% of all<br />
hits. This large number of fake hits is a big challenge for the track finding algorithms. In the outer<br />
parts of the <strong>de</strong>tector the number of fake hits drops dramatically and will not <strong>de</strong>teriorate the track finding<br />
procedure. Figure 2.17 illustrates the hit distributions including fake hits in the 4 Si-strip planes for one<br />
event of a central Au+Au collision at 25 AGeV.
50 The Silicon Tracking Station (STS)<br />
Strip<br />
j−1 j j+1<br />
i−1<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
S<br />
STS<br />
Figure 2.16: the Si-Strip STS sensors layout (principal i<strong>de</strong>a and hit <strong>de</strong>finition)<br />
2.3.2.1 Design of the Si-strip Planes<br />
A <strong>de</strong>tector element consisting of double-si<strong>de</strong>d sensors with a sensitive area of 60 × 60 mm 2 can be cut<br />
from a 4 inch wafer. In the future it is planned to apply the 6 inch wafers technologies. Figure 2.18<br />
displays the layout of the 4th and 6th layer of the Si-strip STS which consist of Si-strip sensor elements<br />
of different sizes. The expected particle <strong>de</strong>nsity is highest at the 4th Si-strip layer which, therefore,<br />
has to exhibit the highest granularity. The intermediate zone of the 4th layer consists of single Si-strip<br />
sensors with longer strip length according the required occupancy. The outer zone of the Si-strip plane<br />
is composed of Si-strip modules built in Long Lad<strong>de</strong>r technology. In the 4th Si-strip layer the lad<strong>de</strong>r<br />
consists only of two Si-strip sensors.
2.3. The Silicon Strip Tracker (SST) 51<br />
Figure 2.17: Hit distribution on the STS planes 4, 5 and 6 including fake hits for one event of central Au+Au<br />
collision at 25 AGev<br />
STS4<br />
STS6<br />
000000<br />
111111<br />
000000<br />
111111<br />
000000<br />
111111<br />
01<br />
00 11 000000<br />
111111<br />
01<br />
00 11 000000<br />
111111<br />
01<br />
00 11<br />
01<br />
00 11<br />
01<br />
00 11<br />
01<br />
Y<br />
000000000<br />
111111111<br />
000000000<br />
111111111<br />
000 111<br />
000000000<br />
111111111<br />
000 111<br />
000000000<br />
111111111<br />
000 111000<br />
111<br />
000000000<br />
111111111<br />
000 111000<br />
111<br />
000000000<br />
111111111<br />
000 111000<br />
111<br />
000 111<br />
111 000<br />
111 000<br />
X<br />
0 10 20 cm<br />
Figure 2.18: the Layout of the Si-Strip STS4 and STS6 Planes
52 The Silicon Tracking Station (STS)<br />
2.3.3 Si-strip sensors: Design and Technology<br />
The ultimate goal is to <strong>de</strong>velop radiation-hard n-type double-si<strong>de</strong>d capacitively coupled silicon strip<br />
<strong>de</strong>tectors with a thickness of 100 µm. The aim is also to simultaneously simplify the <strong>de</strong>sign and the<br />
production of the <strong>de</strong>tector in or<strong>de</strong>r to reduce costs [60]. The preferred <strong>de</strong>tector concept is <strong>de</strong>picted in<br />
figure 2.19 illustrating the <strong>de</strong>sign of a n-type double-si<strong>de</strong>d strip <strong>de</strong>tector [56]. Double-si<strong>de</strong>d micro strip<br />
sensors are built from 100 mm diameter wafers of n-type material with a resistivity of 5-7 kOhm cm.<br />
They have a maximal active area 60x60 mm in or<strong>de</strong>r to optimize the acceptance, and a narrow pitch down<br />
to 25 µm in or<strong>de</strong>r to keep the occupancy on the level of a few %. This layout ensures a high efficiency<br />
for track finding and double track separation.<br />
Guard Ring<br />
Structure<br />
22 X<br />
22 X<br />
p-comp<br />
+ V<br />
bias<br />
Aluminum<br />
Implant<br />
n +<br />
n si<strong>de</strong> strip direction<br />
p +<br />
n-<br />
p si<strong>de</strong> strip direction<br />
is orthogonal to the page<br />
Figure 2.19: Double si<strong>de</strong>d ac coupled n-type strip <strong>de</strong>tector with punch through biasing, guard ring structures,<br />
and large area compensation implantation at the n-si<strong>de</strong>.<br />
The strips on the two si<strong>de</strong>s of a sensor are tilted by an angle of 15 ◦ with respect to each other to obtain a<br />
stereo topology which provi<strong>de</strong>s two-dimensional space-point resolution. The AC coupling of the sensors<br />
strips is accomplished by insulating the p + - and n + -implants from the Al readout electro<strong>de</strong>s by a very<br />
thin SiO2 layer. Neighbored n-strips are insulated from each other by (over)compensating the electron<br />
accumulation layer by a large area p-implantation. Two bias rings surround the active <strong>de</strong>tector region<br />
both on the p- and the n-si<strong>de</strong>. Since strips are separated from the bias lines by the field oxi<strong>de</strong>, controlled<br />
biasing is obtained by punch through injection of free carriers. The sensors will have a guard ring<br />
structure that is optimized to avoid breakdown in the termination of the <strong>de</strong>pletion zone. Active area<br />
and guard region size may alter until the final <strong>de</strong>sign. The main efforts will be concentrated on the<br />
<strong>de</strong>velopment of technology for production of very thin, up to 100 µm Si-strip sensors. Sensors as thin as<br />
150 µm are planned to be <strong>de</strong>veloped during R&D. Studies of their radiation resistance are in progress.<br />
A summary of the Si-strip STS’s major characteristics is given in Table 2.4.
2.3. The Silicon Strip Tracker (SST) 53<br />
Feature Value / Quantity<br />
Angular coverage 50 to 500 mrad<br />
Number of superlayers 4<br />
Views in one superlayer 0 ◦ , - 15 ◦<br />
Detector modules per plane 28 - 60<br />
Double si<strong>de</strong>d sensors per plane 44-184<br />
Detector thickness ≤ 100-150 µm<br />
Sensitive <strong>de</strong>tector area 20 × 20cm 2 to 50 × 50cm 2<br />
Readout chips per module 20<br />
Analog (optical fibre) links 20/34<br />
Operational temperature ≤40 ◦ C<br />
Total active area 2 m 2<br />
Total number of readout channels 0.5 × 10 6 ,<br />
Total number of readout chips 10 4 ,<br />
Total number of <strong>de</strong>tector modules 176<br />
Total number of double si<strong>de</strong>d sensors 456<br />
2.3.4 Si-strip STS Readout Electronics<br />
2.3.4.1 General consi<strong>de</strong>rations<br />
Table 2.4: Summary of Si-strip STS<br />
The main goal of the R&D on the Si-Strip readout electronics is to achieve the new data-driven architecture,<br />
which is required by the CBM data acquisition and online event selection architecture (see<br />
section 10.1). The electronics has to operate at interaction rates of 10 MHz for A-A collisions and several<br />
100 MHz for p-p without a fixed bunch structure. As a consequence, hits have to be <strong>de</strong>tected without<br />
assistance of an external trigger system or a bunch crossing clock and tagged with a time stamp. Since<br />
all hits will be transfered to the DAQ system, efficient techniques for sparse readout and a<strong>de</strong>quate output<br />
bandwidth have to be provi<strong>de</strong>d.<br />
With a total number of about 10 6 readout channels, the efficient processing of <strong>de</strong>tector signals has to rely<br />
on custom-ma<strong>de</strong> front-end chips which will be mounted very close to the <strong>de</strong>tectors.<br />
The main features of the Si-Strip readout electronics are:<br />
• Amplitu<strong>de</strong> and time measurements,<br />
• Digitization of amplitu<strong>de</strong> and time,<br />
• Self triggering and generation of an event time stamp,<br />
• Dead time free,<br />
• Calibration (test) system,<br />
• Flexibility of control and adjustment.<br />
From the construction point of view the proposed layout is based on the intention to move as much electronics<br />
as possible from the <strong>de</strong>tector site to the electronics hut without sacrificing system performance.
54 The Silicon Tracking Station (STS)<br />
Digital readout using discriminators has been discar<strong>de</strong>d since this choice would exclu<strong>de</strong> continuous<br />
on-line monitoring of analog signals which will be valuable to <strong>de</strong>tect radiation damage effects and to<br />
counteract to them. An important point is the transmission system of the signal from <strong>de</strong>tector area to the<br />
front-end electronics.<br />
2.3.4.2 Si-strip Readout Chip<br />
The CBM <strong>de</strong>tector is <strong>de</strong>signed to run at a rate of up to 10 7 heavy-ion reactions per second without fixed<br />
bunch structure. These conditions require the <strong>de</strong>velopment of specific front-end electronics as a part of<br />
the Data Driven Architecture. The most important part of the readout chain is the readout chip, which is<br />
placed at the Si-strip STS <strong>de</strong>tector area.<br />
The major specifications for the chip performance are constrained by<br />
• Small signal - 7000 electrons per MIP for 100 µm sensor thickness;<br />
• Detector capacitance in the range 30-300 pF <strong>de</strong>pending on the thickness and length of the strip;<br />
• Signal-to-noise ratio better than 10 for MIP;<br />
• Dynamic range of a few MIPs;<br />
• Random input signal rate of several 100 kHz per channel;<br />
• AC <strong>de</strong>tector input coupling, possible DC coupling for <strong>de</strong>tector dark current control;<br />
• Low power consumption on the level of a few mW/channel;<br />
• Number of channels dictated by the tracker <strong>de</strong>sign (128,256...)<br />
• Minimal number of external components;<br />
• Radiation hardness;<br />
The front-end electronics at the silicon strip <strong>de</strong>tectors should provi<strong>de</strong> the following functionality:<br />
• Finding the <strong>de</strong>tector signals produced by the particles<br />
• Dead time free data readout from the silicon strip <strong>de</strong>tectors which allows to <strong>de</strong>fine the <strong>de</strong>tector<br />
signal amplitu<strong>de</strong> and time of an event for each channel<br />
• Digitization and digital treatment of signals, including data compression and data transmission to<br />
the concentrator<br />
• Service, control, test, signal and voltage distribution functions.<br />
The general structure of the Si-strip STS readout chip is presented in Fig. 2.20. Each FEE channel<br />
consists of three parts: analog front-end, digitization plus digital back-end.<br />
The Strip FEE <strong>de</strong>velopment is currently still in the first part of the conceptual <strong>de</strong>sign phase, where the<br />
<strong>de</strong>sign space is explored and the essential R&D issues are i<strong>de</strong>ntified. Two different options for the<br />
readout chip structure are un<strong>de</strong>r investigation: an "analog" FEE version and a "digital" version.<br />
The "analog" FEE version provi<strong>de</strong>s functions such as signal finding, amplitu<strong>de</strong> and time measurements<br />
mostly with analog signal processing. By further digitization one obtains the amplitu<strong>de</strong> and time of the
2.3. The Silicon Strip Tracker (SST) 55<br />
Silicon<br />
Detectors<br />
High<br />
Voltage<br />
Distribution<br />
Charge<br />
Sensitive<br />
Amplifiers<br />
Read Out Electronics<br />
Analog<br />
Signal<br />
Processing<br />
Control<br />
And<br />
Control<br />
Distribution<br />
Digitizing<br />
Slow<br />
Control<br />
Housekeeping<br />
Digital<br />
Signal<br />
Processing<br />
Service and Control Electronics<br />
Interface<br />
Transmission<br />
System<br />
Test<br />
And<br />
Calibration<br />
System<br />
Amplitu<strong>de</strong><br />
Figure 2.20: General structure of the readout chip of the Si-strip STS.<br />
Input<br />
protection<br />
Ccal<br />
Switch<br />
array<br />
DAC<br />
array<br />
Test<br />
data<br />
Polarity<br />
Switch<br />
Calibration (test) System<br />
CSA<br />
Feedback<br />
adjustment<br />
Soft<br />
Limiter<br />
Limitation<br />
adjustment<br />
T-Pulse Fast<br />
shaper<br />
DAC<br />
CR-RC n<br />
Shaper<br />
(n=2)<br />
Peak time<br />
adjustment<br />
Analog fin<strong>de</strong>r<br />
Threshold<br />
Scale<br />
amplifier<br />
Gain<br />
adjustment<br />
Time<br />
To ADC<br />
Figure 2.21: Analog front-end section of one channel for the "analog" option<br />
hit. The analog front-end part for "analog" option version is shown in Fig. 2.21, the digitization and<br />
digital back-end part in Fig. 2.22<br />
An input protection circuitry protects the Charge Sensitive Amplifier (CSA) against possible high voltage<br />
discharges of the silicon <strong>de</strong>tectors during bias processes. This circuitry should not increase the CSA<br />
noise. A polarity switch allows to handle signals of both polarities, so that the same read-out chip can be<br />
used for both si<strong>de</strong>s of the double-si<strong>de</strong>d sensors.<br />
The fast part of each channel provi<strong>de</strong>s hit finding and the start of the time measurement and consists<br />
of a fast shaper and a comparator. The slow part provi<strong>de</strong>s the amplitu<strong>de</strong> measurement and contains a<br />
shaper and circuitry for <strong>de</strong>termining and storing the amplitu<strong>de</strong>. The analog memory can be organized as<br />
a pipeline, allowing to implement various strategies to share ADCs between channels.<br />
The test and calibration system provi<strong>de</strong>s information on the status of the FEE and the <strong>de</strong>tectors, and<br />
produces a set of test pulses with different amplitu<strong>de</strong>s for each channel. It allows to measure the crosstalk,
56 The Silicon Tracking Station (STS)<br />
Internal<br />
pulser<br />
(phase control)<br />
ADC Pe<strong>de</strong>stal<br />
B<br />
U<br />
F<br />
Subtraction<br />
F Pe<strong>de</strong>stal<br />
E<br />
R<br />
memory<br />
External<br />
CLK<br />
Pe<strong>de</strong>stal<br />
calculator<br />
Pe<strong>de</strong>stal<br />
measurement<br />
mo<strong>de</strong><br />
Control<br />
Noise<br />
reduction<br />
Shape<br />
reconstruction<br />
Signal<br />
fin<strong>de</strong>r<br />
Zero<br />
suppression<br />
Amplitu<strong>de</strong><br />
& Time<br />
reconstruction<br />
Data<br />
reduction<br />
Interface<br />
(serial)<br />
Figure 2.22: Digitization and digital back-end section for the "analog" option<br />
and shift of the base line and other parameters.<br />
The ADC and the digital part of "analog" option version provi<strong>de</strong> (i) amplitu<strong>de</strong> and time digitization by<br />
ADC for amplitu<strong>de</strong> and time measurement, (ii) zero suppression and data reduction to minimize the data<br />
volume for transmission to the concentrator by a fast serial interface, (iii) and pe<strong>de</strong>stal subtraction.<br />
In the "digital" FEE version the <strong>de</strong>termination of amplitu<strong>de</strong> and time estimates for a hit is done after<br />
digitization. Figures 2.23 and 2.24 show the analog front-end and digitization and digital back-end part,<br />
respectively, for this variant.<br />
Input<br />
protection<br />
Ccal<br />
Switch<br />
array<br />
DAC<br />
array<br />
Test<br />
data<br />
Polarity<br />
switch<br />
Calibration (test) System<br />
CSA<br />
Feedback<br />
adjustment<br />
CR-RC n<br />
shaper<br />
(n=2)<br />
Peak time<br />
adjustment<br />
T-Pulse Fast<br />
shaper<br />
DAC<br />
Analog fin<strong>de</strong>r<br />
Threshold<br />
Peak<br />
<strong>de</strong>tector<br />
Delay<br />
(adjust.)<br />
Pipeline<br />
From<br />
pulser<br />
To ADC<br />
Figure 2.23: Analog front-end section of one channel for the "digital" option<br />
The analog front-end section may contain also in this scenario a fast shaper and discriminator. This allows<br />
for example to gate the ADC and digital signal processing stages and can thus help to reduce the power<br />
consumption (a similar approach is also discussed in section 9.3 ). The data driven approach requires<br />
that the hit <strong>de</strong>tection and sparse read-out functionality are implemented on the FEE chip. However, other<br />
digital signal processing steps, in particular the time and amplitu<strong>de</strong> estimation, can also be moved to
2.3. The Silicon Strip Tracker (SST) 57<br />
ADC<br />
Internal<br />
pulser<br />
(phase control)<br />
B<br />
U<br />
F<br />
F<br />
E<br />
R<br />
External<br />
CLK<br />
To pipeline<br />
Pe<strong>de</strong>stal<br />
subtraction<br />
Pe<strong>de</strong>stal<br />
memory<br />
Pe<strong>de</strong>stal<br />
calculator<br />
Pe<strong>de</strong>stal<br />
Measurement<br />
Mo<strong>de</strong><br />
Control<br />
Zero<br />
suppression<br />
Time<br />
measurement<br />
Data<br />
reduction<br />
Interface<br />
(serial)<br />
Figure 2.24: Digitization and digital back-end section for the "digital" option<br />
later stages of the FEE-DAQ chain. Currently, several options are studied to <strong>de</strong>termine the impact on<br />
data rates, power dissipation, chip area and <strong>de</strong>sign complexity.<br />
2.3.5 Working packages, timelines, cost estimate<br />
The future R&D efforts will be focused on the <strong>de</strong>velopment of (i) the technology of thin (up to 100 µm<br />
thickness) Si-strip sensors, and (ii) of the <strong>de</strong>dicated readout ASIC for the Si-STS based on data driven<br />
architecture. In addition, <strong>de</strong>sign studies are planned for the mechanical construction of the Si-strip STS<br />
based on lightweight carbon fiber monolithic space frame (lad<strong>de</strong>r), which provi<strong>de</strong>s an excellent ratio<br />
of rigidity vs. mass [61]. Moreover, we plan irradiation tests of the Si-strip sensors and the FEE. The<br />
<strong>de</strong>tailed R&D programme is listed in table 2.5. A cost estimate of the Si-Strip Tracker is given in table<br />
2.6.
58 The Silicon Tracking Station (STS)<br />
Activity Duration<br />
Simulation and optimization of Si-strip STS 2005-2006<br />
Final Si-strip STS <strong>de</strong>sign 2007<br />
Si-strip sensors R&D 2005-2006<br />
Si-strip sensors prototypes 2006-2007<br />
Si-strip sensors radiation hardness tests 2006-2008<br />
Si-strip sensors baseline <strong>de</strong>sign 2009<br />
Si-strip sensors production 2009-2010<br />
Long Lad<strong>de</strong>r technology study 2006-2007<br />
Long Lad<strong>de</strong>r technology support, bridges <strong>de</strong>sign 2007-2008<br />
Test of prototypes of Long Lad<strong>de</strong>r <strong>de</strong>tectors 2008-2009<br />
Production of Long Lad<strong>de</strong>r Si-strip <strong>de</strong>tectors 2009-2010<br />
Front-end readout chip evaluation 2005-2006<br />
Front-end readout chip prototyping and test 2006-2007<br />
Front-end readout board <strong>de</strong>sign 2007-2008<br />
Front-end readout production and integration 2009-2010<br />
Mechanics, support <strong>de</strong>sign 2006-2007<br />
Cooling system <strong>de</strong>sign 2006-2007<br />
Mechanics system production and integration 2008-2010<br />
Si-strip STS integration, test measurement and commissioning 2011-2012<br />
Table 2.5: Si-strip STS Time plans.<br />
Sensors fabrication 3000<br />
Long lad<strong>de</strong>r technology <strong>de</strong>tectors production 500<br />
Front-end electronics 2000<br />
Mechanics, support 500<br />
Cooling system 500<br />
Infrastructure 200<br />
Table 2.6: Si-strip STS costs (in k).
3 Ring Imaging Cherenkov <strong>de</strong>tector (RICH)<br />
3.1 Design consi<strong>de</strong>rations<br />
The Ring Imaging Cherenkov <strong>de</strong>tector (RICH) is <strong>de</strong>signed to provi<strong>de</strong> electron i<strong>de</strong>ntification in the momentum<br />
range of electrons from low-mass vector-meson <strong>de</strong>cays (see fig 3.1). The (y, pt) region of the ρ<br />
and φ meson which will be covered by a certain momentum range of i<strong>de</strong>ntified electrons is presented in<br />
fig. 3.2. Since midrapidity lies at 1.75, 2, and 2.16 for 15, 25, and 35 AGeV beam energy, respectively, a<br />
momentum range for electron i<strong>de</strong>ntification up to 10-12 GeV/c should be sufficient. These requirements<br />
<strong>de</strong>fine possible radiators for the RICH <strong>de</strong>tector: Assuming that pions can be separated from electrons up<br />
to 90% of the maximum Cherenkov opening angle θc (cosθc = 1<br />
n ), the momentum range for π i<strong>de</strong>ntifica-<br />
1<br />
tion is illustrated in fig. 3.3 in <strong>de</strong>pen<strong>de</strong>nce on the Lorentz factor γth = , where n is the refractive<br />
√ 1−1/n 2<br />
in<strong>de</strong>x of the medium. A radiator with γth > 38 would be i<strong>de</strong>al, because then the Cherenkov angle of pions<br />
is less than 90% of θc for all momenta smaller than 12 GeV/c.<br />
A second task of the RICH <strong>de</strong>tector is the π i<strong>de</strong>ntification for higher momenta in or<strong>de</strong>r to improve the<br />
K/π separation which quickly <strong>de</strong>teriorates for p > 4 GeV/c if only time-of-flight information is used (see<br />
fig. 14.3 and 14.5). For γth = 35.8 the momentum threshold for Cherenkov light production of pions lies<br />
at 5 GeV/c while kaons emit Cherenkov light only for momenta larger than 17.7 GeV/c.<br />
Combining both requirements for the RICH <strong>de</strong>tector, a radiator with a threshold γth 38 would be<br />
appropriate. For a further discussion of this topic see section 3.4.2.<br />
entries<br />
10<br />
2<br />
10<br />
1<br />
0 2 4 6 8 10 12 14 16 18 20<br />
Plab [GeV/c]<br />
Figure 3.1: Total momentum distribution in the laboratory for electrons from the <strong>de</strong>cay of ρ (black), ω (red)<br />
and φ-mesons (blue). The low-mass vector mesons were generated in Pluto with a thermal pt-distribution (T =<br />
130 MeV), transverse flow (β = 0.3c) and a gaussian rapidity distribution (σy = 0.41) in the center-of-mass frame<br />
of the collision. The total lab-momentum for the <strong>de</strong>cay electrons was calculated for Elab=25 AGeV.<br />
59
60 Ring Imaging Cherenkov <strong>de</strong>tector (RICH)<br />
p t [GeV]<br />
3<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
p e = 1 2 10 12 GeV/c<br />
0<br />
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5<br />
ρ<br />
y<br />
p t [GeV]<br />
3<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
p e = 1 2 10 12 GeV/c<br />
0<br />
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5<br />
Figure 3.2: (y, pt) region for ρ and φ mesons with lines of constant momenta for the <strong>de</strong>cay-electrons. These<br />
lines enclose the region to be covered <strong>de</strong>pending on the momentum region of i<strong>de</strong>ntified electrons. [Center-of-mass<br />
rapidities for 15, 25, and 35 AGeV beam momentum are 1.75, 2, and 2.16, respectively.]<br />
p [GeV]<br />
30<br />
25<br />
20<br />
15<br />
10<br />
5<br />
K threshold<br />
CO 2<br />
N 2<br />
Θ π 90% of Θ c<br />
π threshold<br />
0<br />
0 10 20 30 40 50 60<br />
γ th<br />
Figure 3.3: Momentum threshold for<br />
Cherenkov light production for pions and<br />
kaons in <strong>de</strong>pen<strong>de</strong>nce on γth. Also shown is the<br />
momentum at which the opening angle of pions<br />
corresponds to 90% of the opening angle<br />
of electrons. The green/grey band thus indicates<br />
the approximate region of pion i<strong>de</strong>ntification<br />
in <strong>de</strong>pen<strong>de</strong>nce on γth. γth for CO2 and<br />
N2 is indicated by the dashed lines.<br />
The overall length of the <strong>de</strong>tector is mainly constrained by the maximum distance between the last STS<br />
and the first TRD station with which the global tracking still works sufficiently precise. On the other<br />
hand, a long <strong>de</strong>tector will increase the number of Cherenkov photons generated by particles traversing<br />
the RICH since this number is proportional to its length. A 2.2 m long gas radiator is aimed at currently.<br />
The same polar angle as for the STS should be covered.<br />
In the <strong>de</strong>sign of the RICH <strong>de</strong>tector, one has to consi<strong>de</strong>r that it will be operated in a high track <strong>de</strong>nsity<br />
environment. The material budget has to be kept low in or<strong>de</strong>r to reduce secondary particle production. In<br />
particular, the probability for γ-conversion producing electron-positron pairs which is the largest source<br />
of background in the RICH <strong>de</strong>tector has to be kept small.<br />
The overall <strong>de</strong>sign of the RICH <strong>de</strong>tector is shown in fig. 3.4. The <strong>de</strong>tector will be positioned behind the<br />
φ<br />
y
3.2. Particle i<strong>de</strong>ntification with the RICH <strong>de</strong>tector 61<br />
dipole magnet about 1.5 m downstream of the target. It will consist of a 2.2 m long gas radiator with a<br />
beam pipe in the center, two arrays of spherical hexagonal Beryllium-glass mirrors, two photo<strong>de</strong>tector<br />
planes and corresponding support structures. The Be-glass mirrors are chosen to provi<strong>de</strong> excellent optics<br />
of the RICH <strong>de</strong>tector with a low material budget at the same time. Optics <strong>de</strong>gradation and radiator gas<br />
pollution due to long exposition in a radiation hard environment as given in this experiment should also<br />
be prevented by this choice of mirrors. The photo<strong>de</strong>tectors are shiel<strong>de</strong>d by the dipole magnet yoke to<br />
reduce the background from particles crossing the photo<strong>de</strong>tector plane. The main requirements for the<br />
photo<strong>de</strong>tector are high granularity, high geometrical efficiency and high <strong>de</strong>tection efficiency of photons,<br />
in particular in the near UV region, as well as a reliable operation. The readout of the RICH <strong>de</strong>tectors<br />
can be accomplished based on gaseous <strong>de</strong>tectors with a suitable converter for UV photons or with<br />
photomultipliers. In this report we concentrate on a <strong>de</strong>sign based on the latter option.<br />
Figure 3.4: Overall <strong>de</strong>sign of the RICH <strong>de</strong>tector.<br />
3.2 Particle i<strong>de</strong>ntification with the RICH <strong>de</strong>tector<br />
Particle i<strong>de</strong>ntification with the RICH <strong>de</strong>tector is performed by a measurement of the Cherenkov angle/<br />
ring radius and the momentum of the particles (see fig. 3.14). Assuming that tracks with momentum are<br />
provi<strong>de</strong>d by the tracking system, the RICH part for particle i<strong>de</strong>ntification requires the following steps:<br />
• ring finding<br />
• <strong>de</strong>termination of center and radius of ring/ Cherenkov angle<br />
• matching of rings with tracks<br />
Methods currently available for ring finding and fitting are <strong>de</strong>scribed in section 13.5 and 13.6. Here, the<br />
status of first simulations <strong>de</strong>termining electron i<strong>de</strong>ntification efficiency and pion misi<strong>de</strong>ntification will<br />
be <strong>de</strong>scribed.
62 Ring Imaging Cherenkov <strong>de</strong>tector (RICH)<br />
Purity, efficiency and momentum range of particle i<strong>de</strong>ntification with the RICH <strong>de</strong>tector is limited by:<br />
• refractive in<strong>de</strong>x of the radiator<br />
• Cherenkov angle/ ring radius resolution<br />
• momentum resolution of the tracks, position resolution of the track extrapolation to the photo<strong>de</strong>tector<br />
plane<br />
• ring-track matching<br />
The momentum range which is available for particle i<strong>de</strong>ntification has already been discussed in the<br />
previous section, see also fig. 3.3. However, the upper momentum limit for a reliable e/π separation is<br />
strongly <strong>de</strong>termined by the Cherenkov angle/ ring radius resolution. The resolution of the reconstructed<br />
Cherenkov rings/ angles has the following main contributions:<br />
• chromatic dispersion: the wavelength <strong>de</strong>pen<strong>de</strong>nce of the refractive in<strong>de</strong>x leads to a wavelength<br />
<strong>de</strong>pen<strong>de</strong>nce of the Cherenkov angle, see fig. 3.31 and 3.32. The resolution of the Cherenkov angle<br />
will thus <strong>de</strong>pend on the wavelength region <strong>de</strong>tected by the photo<strong>de</strong>tector.<br />
• pixel size: the finite granularity of the photo<strong>de</strong>tector results in a corresponding finite resolution.<br />
The granularity is to be chosen in accordance to the other contributions to the total resolution.<br />
• emission point: the particle trajectories do not pass through the center of curvature of the mirror<br />
yielding to a smearing of the projected ring in <strong>de</strong>pen<strong>de</strong>nce on their azimuthal and polar angle.<br />
• mirror surface: a <strong>de</strong>viation of the mirror surface from the i<strong>de</strong>al spherical surface yields to an<br />
enlargement of the focal spot in the focal plane.<br />
A <strong>de</strong>tailed study of the contributions from these sources has to be performed. The result will be important<br />
for <strong>de</strong>termining the optimum granularity of the photo<strong>de</strong>tector, the wavelength region i<strong>de</strong>ally to be<br />
<strong>de</strong>tected, and the maximum variation of the mirror surface from the i<strong>de</strong>al spherical surface. The impact<br />
of the total resolution on the particle i<strong>de</strong>ntification capabilities has still to be studied in <strong>de</strong>tail.<br />
The matching of rings and tracks is difficult due to the high particle multiplicities in central Au+Au<br />
collisions at 15 to 35 AGeV; see chapter 12. The resulting challenge for RICH is illustrated in figure<br />
3.5: All charged tracks being reconstructed by the tracking system are reflected at the mirror in or<strong>de</strong>r<br />
to give the center of a possible Cherenkov ring (red crosses). The number of these tracks is much<br />
larger than the number of particles really producing a ring. In or<strong>de</strong>r to combine rings and tracks each<br />
ring is matched to the track having its extrapolation closest to the calculated ring center. The distance<br />
between track extrapolation and ring center ΔR is shown in fig. 3.6 for all "true" combinations, i.e. for<br />
those for which ring and track in<strong>de</strong>ed belong to the same particle (green and black line). For i<strong>de</strong>al<br />
tracking (perfect momentum and position <strong>de</strong>termination) the width of this distribution is mainly due to<br />
the limited accuracy of the ring center <strong>de</strong>termination. Currently we use a simple procedure which still<br />
can be improved. Taking an experimental momentum resolution into account (Δp/p = 1%, azimuth<br />
angle β=1.3 mrad, <strong>de</strong>ep angle α=0.8 mrad, see section 13.2.4) and an expected position resolution of the<br />
tracks at the mirror (200 µm), this distribution wi<strong>de</strong>ns, see right part of fig. 3.6.<br />
However, as will be discussed in the next section, only about 1<br />
3 of all rings stem from primary particles,<br />
i.e. from those produced in the Au+Au collision. All other rings are mainly produced by electrons<br />
generated in secondary interactions such as γ-conversion in the material before the RICH <strong>de</strong>tector. Very<br />
often these tracks will not be reconstructed by the tracking system. Due to the high track <strong>de</strong>nsity another<br />
track extrapolated to the photo<strong>de</strong>tector will probably be close by and thus matched to the ring. These
3.2. Particle i<strong>de</strong>ntification with the RICH <strong>de</strong>tector 63<br />
y, cm<br />
250<br />
200<br />
150<br />
100<br />
50<br />
0<br />
-50<br />
-100<br />
-150<br />
-200<br />
-250<br />
-150 -100 -50 0 50 100 150<br />
x, cm<br />
Figure 3.5: Sample event with fired<br />
PMTs (blue circles) and reconstructed<br />
track projections onto the photo<strong>de</strong>tector<br />
plane (red crosses) in central Au+Au<br />
collisions at 35 AGeV. The size of<br />
the photo<strong>de</strong>tectors is indicated by the<br />
boxes. These boxes contain all rings<br />
from primary tracks, rings lying outsi<strong>de</strong><br />
stem from secondary interactions.<br />
"false" matches in <strong>de</strong>pen<strong>de</strong>nce on ΔR are shown by the red and blue line in fig. 3.6. Naturally their<br />
number increases with ΔR. Every possibility for a reduction of the material budget in front of the RICH<br />
<strong>de</strong>tector should thus be used (see section 3.3.4 for a brief discussion).<br />
The distance ΔR between ring center and track extrapolation will therefore be an important cut criterion<br />
to limit the contribution of wrong ring-track matching in the data (fig. 3.8). On the other hand, a cut on<br />
ΔR will limit the i<strong>de</strong>ntification efficiency for "true" matches (fig. 3.7).<br />
The quality of the invariant mass spectra of the low mass vector mesons is strongly correlated to the<br />
amount of pions misi<strong>de</strong>ntified as electrons (see chapter 16). The above <strong>de</strong>scribed investigations can be<br />
used for a first estimate of the π-misi<strong>de</strong>ntification expected from the RICH <strong>de</strong>tector. Consi<strong>de</strong>ring only<br />
tracks originating from the main vertex of the collision and integrating all momenta up to 12 GeV/c, the<br />
efficiency of electron i<strong>de</strong>ntification is shown in fig. 3.7 in <strong>de</strong>pen<strong>de</strong>nce on a cut in ΔR. The probability<br />
of matching a pion track to an electron ring is given in fig. 3.8 in <strong>de</strong>pen<strong>de</strong>nce on a cut in ΔR. In central<br />
Au+Au collisions at 35 AGeV about 827 pions are produced in UrQMD simulations (see section 12). A<br />
preliminary estimation of the π-misi<strong>de</strong>ntification thus yields ∼ 4 · 10 −4 for ΔR = 0.8 cm. Combining the<br />
RICH electron i<strong>de</strong>ntification with the π-suppression of the TRD stations and the particle i<strong>de</strong>ntification<br />
by TOF, the final purity of the electron i<strong>de</strong>ntification in CBM will be significantly better.
64 Ring Imaging Cherenkov <strong>de</strong>tector (RICH)<br />
# /event (RICH)<br />
5<br />
4<br />
3<br />
2<br />
1<br />
true matching - all<br />
true matching - e<br />
false matching - all<br />
false matching - π as e<br />
0<br />
0 1 2 3 4 5<br />
Δ [cm] R<br />
# /event (RICH)<br />
3<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
true matching - all<br />
true matching - e<br />
false matching - all<br />
false matching - π as e<br />
0<br />
0 1 2 3 4 5<br />
Δ [cm] R<br />
Figure 3.6: Distance ΔR between ring center and track extrapolation assuming perfect tracking (left), and a final<br />
experimental tracking resolution (right) (see text for numbers). The black and green lines shows ΔR if ring and<br />
track belong to the same particle "true matching", the red and blue lines if not "false matching". Only primary<br />
vertex tracks (production vertex of track within 1 mm of target) with p < 12 GeV/c were consi<strong>de</strong>red. The latter<br />
requirement reflects the upper momentum bor<strong>de</strong>r for particle i<strong>de</strong>ntification in the RICH <strong>de</strong>tector. The simulation<br />
was performed for central Au+Au collisions from UrQMD at 35 AGeV and 40%He+60%CH4 as a radiator.<br />
Efficiency<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
0<br />
0 1 2 3 4 5<br />
ΔRΔ[cm]<br />
[cm]<br />
Figure 3.7: Efficiency for correctly matching<br />
electron rings and tracks in <strong>de</strong>pen<strong>de</strong>nce on a cut in<br />
ΔR; calculated from the green lines in fig. 3.6 (solid<br />
line for perfect tracking, dashed line taking experimental<br />
resolution into account).<br />
R<br />
id as e/event (RICH)<br />
π<br />
#<br />
5<br />
4<br />
3<br />
2<br />
1<br />
0<br />
0 1 2 3 4 5<br />
ΔRΔ[cm]<br />
[cm]<br />
Figure 3.8: Number of electrons per event measured<br />
in the RICH <strong>de</strong>tector and wrongly matched to<br />
a pion track in <strong>de</strong>pen<strong>de</strong>nce on a cut in ΔR; calculated<br />
from the blue lines in fig. 3.6 (solid line for<br />
perfect tracking, dashed line taking experimental<br />
resolution into account).<br />
Once more we want to emphasize the preliminary status of the simulation and these estimates. In the<br />
future more realistic simulations are urgently nee<strong>de</strong>d. Also a <strong>de</strong>tailed study of the particle i<strong>de</strong>ntification<br />
capabilities for π and µ is necessary.<br />
R
3.3. RICH simulations 65<br />
3.3 RICH simulations<br />
Simulations were started to study in <strong>de</strong>tail the performance of the RICH <strong>de</strong>tector. In this section, the input<br />
parameters of the simulation are <strong>de</strong>scribed before the response of the RICH <strong>de</strong>tector to single particles<br />
as well as to UrQMD events representing typical heavy-ion collisions is discussed.<br />
3.3.1 Description of simulation<br />
The performance of the RICH <strong>de</strong>tector was studied within the Monte Carlo framework cbmroot [62]<br />
(version OCT04) using GEANT3 for the <strong>de</strong>tector simulation. The implemented mo<strong>de</strong>l of the <strong>de</strong>tector<br />
is a simplified version of fig. 3.4 and consists of a gas vessel ma<strong>de</strong> of 0.25 mm aluminum walls filled<br />
with the Cherenkov radiator gas. Two rectangular sectors of the spherical mirror are positioned in the<br />
downstream part of the gas vessel. They are ma<strong>de</strong> of 3 mm Beryllium covered by 0.5 mm of glass. The<br />
curvature radius of the mirror is 450 cm. The photo<strong>de</strong>tector consists of two rectangular planes positioned<br />
insi<strong>de</strong> the gas vessel on its upstream wall. In the center of the gas vessel a hole is left for the beam-pipe.<br />
The photo<strong>de</strong>tector was split into circle cells of 6 mm diameter corresponding to photomultiplier tubes<br />
assembled in a hexagonal close packing (corresponds to 90% geometrical acceptance). Only photons<br />
hitting the cells are consi<strong>de</strong>red as <strong>de</strong>tected taking additionally the quantum efficiency of the photo<strong>de</strong>tector<br />
into account. The RICH geometry used in the simulation is shown in fig. 3.9.<br />
Figure 3.9: RICH <strong>de</strong>tector as implemented into the CBM simulation framework.<br />
For the simulation of Cherenkov radiation, optical properties for the radiator gas and the mirror were<br />
introduced to the mo<strong>de</strong>l, as well as the quantum efficiency of the photo<strong>de</strong>tector. The radiator gas refractive<br />
indices are taken from table 3.1, the chromatic dispersion is not yet taken into account. The<br />
gas transparency is based on figs. 3.29 and 3.30. The mirror reflection follows fig. 3.10 which is taken<br />
from the HADES experiment. No diffuse reflection is simulated yet. The photo-multiplier quantum efficiency<br />
is taken from fig. 3.35 which is a very optimistic scenario. Alternatively, the quantum efficiency<br />
from the Hamamatsu flat panel multiano<strong>de</strong> PMT (H8500) [63] is used. The amplitu<strong>de</strong> response of the<br />
photomultipliers to single photo-electrons is parametrized by fig. 3.33.<br />
With these parameters Cherenkov light emission is simulated for single electrons traversing the RICH<br />
<strong>de</strong>tector. For a 2 m long nitrogen radiator the spectrum of the generated Cherenkov light is shown in<br />
fig. 3.11. Photon losses due to absorption in the gas, the final reflectivity of the mirror and the quantum<br />
efficiency of the photo<strong>de</strong>tector (PMT FEU-Hive) are also presented. Using the quantum efficiency from<br />
the H8500 PMT from Hamamatsu, the final photon yield is reduced to about 1<br />
3 .
panels<br />
setup<br />
th 45<br />
D for<br />
the<br />
was<br />
each<br />
of all<br />
and<br />
alues<br />
erage<br />
n 0.2<br />
was<br />
re in<br />
t and<br />
tion.<br />
f the<br />
SE80<br />
5–0.8<br />
VUV<br />
ples<br />
The<br />
cal a-<br />
. The<br />
of a<br />
mple.<br />
probhigh<br />
than<br />
icrothe<br />
Fig. 662. Surface scans of polished glassy carbon (Sigradur Ring Imaging Cherenkov <strong>de</strong>tector (RICH)<br />
s G)<br />
and float glass samples measured with an a-step profiler. The<br />
<strong>de</strong>fects shown in the top curve cover less than 0.1% of area.<br />
Fig. 3. Reflectivities measured for witness substrates of polished<br />
glassy carbon (Sigradurs G) and float glass covered with<br />
Al=MgF2: 6<br />
]<br />
-1<br />
The VUV reflectivity was measured in a monochromator<br />
setup with a D2 lamp and a solarblind<br />
photo tube as <strong>de</strong>scribed in Ref. [8]. The experimental<br />
curves are shown for the wavelength region<br />
of interest in Fig. 3 and exhibit constant values<br />
around R ¼ 80% down to 150 nm: The reflectivity<br />
curves show no significant difference between float<br />
glass and polished Sigradurs dN<br />
2<br />
=<br />
2πα<br />
sin θ L<br />
dλ<br />
2<br />
λ<br />
generated photons<br />
5<br />
reflected photons<br />
measured photons<br />
4 transmitted photons<br />
G and are consistent<br />
with 3the<br />
assumption of a micro roughness sC<br />
2 3 nm as <strong>de</strong>duced from the ratio of observed<br />
specular reflectance to that of an i<strong>de</strong>al smooth<br />
2<br />
surface [9].<br />
[nm<br />
λ<br />
dN/d<br />
1<br />
0<br />
100 200 300 400 500 600 700<br />
wavelength λ [nm]<br />
Figure 3.10: Reflectivity of the<br />
HADES mirror in <strong>de</strong>pen<strong>de</strong>nce on the<br />
wavelength [64]. This reflectivity was<br />
used for the simulation.<br />
Figure 3.11: Spectrum of the<br />
Cherenkov light emitted by single<br />
electrons traversing a N2 radiator. As<br />
black curve the spectrum of generated<br />
photons is shown, the red line shows<br />
those which are transmitted by the<br />
nitrogen. In green the reflected photons<br />
are illustrated and in blue those<br />
being <strong>de</strong>tected by the photomultipliers<br />
taking a quantum efficiency as shown<br />
in fig. 3.35. An integration of this<br />
spectrum yields the number of photons<br />
finally <strong>de</strong>tected in the PMTs.<br />
Fig. 3.12 shows the focussed Cherenkov rings from electrons in one quarter of the photo<strong>de</strong>tector plane.<br />
For this simulation no magnetic field was applied and no multiple scattering was allowed. Hits from all<br />
photons are shown not taking into account the granularity and quantum efficiency of the photomultiplier.<br />
In the center of the photo<strong>de</strong>tector the rings are well focussed while they are not in the outer regions.<br />
In future, the tilting of the mirrors and photo<strong>de</strong>tector planes has to be changed to optimize the imaging<br />
properties of the mirror. Also, the acceptance has to be better matched to the one of the STS. For a brief<br />
discussion of the Cherenkov angle/ ring radius resolution and its implication on the <strong>de</strong>tector <strong>de</strong>sign see<br />
section 3.2.<br />
3.3.2 Response of the RICH <strong>de</strong>tector to single particles<br />
To study the RICH response to single particles crossing the <strong>de</strong>tector, single electrons, muons and pions<br />
were simulated. They were emitted from the center of the target with a uniformly distributed trans-
3.3. RICH simulations 67<br />
one quarter of mirror/ photo<strong>de</strong>tector:<br />
φ = 80 o 60 o 40 o<br />
20 o<br />
θ = 5 o 10 o 15 o 20 o 25 o 30 o 35 o<br />
Figure 3.12: Imaging<br />
property of the RICH <strong>de</strong>tector<br />
as it is currently implemented<br />
into the simulation.<br />
Tracks are emitted from the<br />
target, θ is their polar, φ their<br />
azimuth angle.<br />
verse momentum 0 < pT < 5 GeV/c, and a uniformly distributed azimuth and polar angle, the latter<br />
being in the range of 2◦ < θ < 30◦ . The number of fired photo-multipliers versus the particle momentum<br />
for electrons, muons and pions were simulated for three radiator gases, 40%He+60%CH4, N2 and<br />
50%N2+50%CH4 (fig. 3.13). The average number of photomultipliers per electron giving a signal is 26,<br />
30 and 33, respectively, assuming the quantum efficiency for the PMT-FEU Hive as shown in fig. 3.35.<br />
For the Hamamatsu H8500 PMT these numbers are reduced to about 1<br />
3 . Since the Cherenkov threshold<br />
for muons and pions is at p = 4 − 6 GeV/c <strong>de</strong>pending on the gas, their Cherenkov angles are momentum<br />
<strong>de</strong>pen<strong>de</strong>nt resulting in a momentum <strong>de</strong>pen<strong>de</strong>nt number of PMTs giving a signal.<br />
NPMT<br />
50<br />
e±<br />
45<br />
40<br />
π ±<br />
±<br />
μ<br />
35<br />
30<br />
25<br />
20<br />
15<br />
10<br />
5<br />
2 4 6 8 10 12 14<br />
p, GeV/c<br />
NPMT<br />
50<br />
e±<br />
45<br />
40<br />
π ±<br />
±<br />
μ<br />
35<br />
30<br />
25<br />
20<br />
15<br />
10<br />
5<br />
2 4 6 8 10 12 14<br />
p, GeV/c<br />
NPMT<br />
50<br />
e±<br />
45<br />
40<br />
π ±<br />
±<br />
μ<br />
35<br />
30<br />
25<br />
20<br />
15<br />
10<br />
5<br />
2 4 6 8 10 12 14<br />
p, GeV/c<br />
Figure 3.13: Number of PMTs giving a signal versus the track momentum assuming a quantum efficiency<br />
of the PMTs as shown in fig. 3.35. e ± are shown in red, µ ± in blue, and π ± in green for three radiator gases<br />
40%He+60%CH4, N2, and 50%N2+50%CH4.<br />
The photomultipliers fired by the focussed Cherenkov light of one particle were fitted by a circle equation.<br />
The radius distribution for electrons, muons and pions is shown in Fig. 3.14 in <strong>de</strong>pen<strong>de</strong>nce on the<br />
particle momentum. The electron ring radius is about 5.5 cm in<strong>de</strong>pen<strong>de</strong>nt on the particle momentum and<br />
slightly <strong>de</strong>pending on the chosen radiator gas. Starting from about 10-12 GeV/c the radius distribution of<br />
muons and pions overlaps with the distribution of electrons limiting the electron i<strong>de</strong>ntification capability<br />
of the RICH <strong>de</strong>tector. A <strong>de</strong>tailed investigation of the particle i<strong>de</strong>ntification capabilities in <strong>de</strong>pen<strong>de</strong>nce on<br />
the momentum has still to be performed, preliminary results have been discussed in section 3.2.
68 Ring Imaging Cherenkov <strong>de</strong>tector (RICH)<br />
R, cm<br />
7 e±<br />
π ±<br />
±<br />
6<br />
μ<br />
5<br />
4<br />
3<br />
2<br />
1<br />
2 4 6 8 10 12 14<br />
p, GeV/c<br />
R, cm<br />
7 e±<br />
π ±<br />
±<br />
6<br />
μ<br />
5<br />
4<br />
3<br />
2<br />
1<br />
2 4 6 8 10 12 14<br />
p, GeV/c<br />
R, cm<br />
7 e±<br />
π ±<br />
±<br />
6<br />
μ<br />
5<br />
4<br />
3<br />
2<br />
1<br />
2 4 6 8 10 12 14<br />
p, GeV/c<br />
Figure 3.14: Ring radius distribution versus the track momentum for e ± (red), µ ± (blue) and π ± (green) for the<br />
three radiator gases 40%He+60%CH4, N2, and 50%N2+50%CH4.<br />
P<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
0<br />
0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5<br />
Np.e.<br />
Figure 3.15: Number of <strong>de</strong>tected photons per<br />
photo<strong>de</strong>tector including the quantum efficiency of<br />
the PMT-FEU Hive; only those photo<strong>de</strong>tectors<br />
are consi<strong>de</strong>red which were hit by at least one<br />
Cherenkov photon from an electron crossing the<br />
RICH <strong>de</strong>tector.<br />
In fig. 3.15 the number of <strong>de</strong>tected photons per photo<strong>de</strong>tector including the quantum efficiency of the<br />
PMT-FEU Hive is shown. For this figure only those PMTs were consi<strong>de</strong>red which were hit by at least<br />
one Cherenkov photon from single electrons crossing the RICH <strong>de</strong>tector. Approximately 15% of all<br />
PMTs <strong>de</strong>tect two photons.<br />
3.3.3 Acceptance of the RICH <strong>de</strong>tector<br />
For acceptance studies of the RICH <strong>de</strong>tector single particles were generated with a uniformly distributed<br />
transverse momentum, azimuthal angle and rapidity. The particle is accepted in the RICH <strong>de</strong>tector if at<br />
least 3 photo-multipliers <strong>de</strong>tected Cherenkov photons from this particle. Since for particle i<strong>de</strong>ntification<br />
the momentum is also nee<strong>de</strong>d, at least 4 hits are required in the tracking system STS. In the final layout<br />
the RICH acceptance will be matched to the STS acceptance.<br />
The acceptance of electrons and π − in <strong>de</strong>pen<strong>de</strong>nce on transverse momentum pT and rapidity y is shown<br />
in figs. 3.16 and 3.17, respectively. The acceptance of the light vector mesons ρ,ω, and φ <strong>de</strong>caying<br />
into e + e − pairs is shown in figs. 3.18, 3.19, and 3.20. For each of the <strong>de</strong>cay products the single particle<br />
acceptance criteria as <strong>de</strong>scribed above are used. For all particles a wi<strong>de</strong> range in y and pT will be covered.
3.3. RICH simulations 69<br />
[GeV/c]<br />
T<br />
p<br />
4<br />
3.5<br />
3<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
0<br />
0 1 2 3 4 5 6<br />
y y<br />
Figure 3.16: RICH+STS acceptance for e − in <strong>de</strong>pen<strong>de</strong>nce<br />
on pT and y.<br />
[GeV/c]<br />
T<br />
p<br />
4<br />
3.5<br />
3<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
0<br />
0 1 2 3 4 5 6<br />
y y<br />
Figure 3.18: RICH+STS acceptance<br />
for ρ → e + e − in <strong>de</strong>pen<strong>de</strong>nce<br />
on pT and y.<br />
1<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
0<br />
[GeV/c]<br />
T<br />
p<br />
4<br />
3.5<br />
3<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
1<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
0<br />
[GeV/c]<br />
T<br />
p<br />
4<br />
3.5<br />
3<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
0<br />
0 1 2 3 4 5 6<br />
y y<br />
Figure 3.19: RICH+STS acceptance<br />
for ω → e + e − in <strong>de</strong>pen<strong>de</strong>nce<br />
on pT and y.<br />
3.3.4 Response of the RICH <strong>de</strong>tector to heavy-ion collisions<br />
0<br />
0 1 2 3 4 5 6<br />
y y<br />
Figure 3.17: RICH+STS acceptance for π ± in <strong>de</strong>pen<strong>de</strong>nce<br />
on pT and y.<br />
1<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
0<br />
[GeV/c]<br />
T<br />
p<br />
4<br />
3.5<br />
3<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
0<br />
0 1 2 3 4 5 6<br />
y y<br />
1<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
0<br />
1<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
Figure 3.20: RICH+STS acceptance<br />
for φ → e + e − in <strong>de</strong>pen<strong>de</strong>nce<br />
on pT and y.<br />
The performance of the RICH <strong>de</strong>tector has been studied for central Au+Au collisions at 35 AGeV. Events<br />
were generated by the UrQMD event generator and then tracked through the mo<strong>de</strong>lled CBM setup by<br />
the CBM simulation package cbmroot with GEANT3. Fig. 3.5 shows the signals of the PMTs in the<br />
photo<strong>de</strong>tector plane for a sample event.<br />
The left plot of fig. 3.21 shows the distribution of the number of <strong>de</strong>tected tracks in the photo<strong>de</strong>tector<br />
plane for three radiator gases. On average about 80, 90, and 95 tracks are measured in the RICH <strong>de</strong>tector<br />
for the radiator gases 40%He+60%CH4, N2, and 50%N2+50%CH4, respectively. Only about 1<br />
3 of these<br />
particles are primary particles generated by UrQMD in the nuclear collision (right plot of fig. 3.21). It<br />
should be noted that these numbers <strong>de</strong>pend strongly on the size of the inner hole of the mirrors which is<br />
left for the fast particles. The size of this hole has still to be optimized with respect to acceptance and<br />
ring multiplicity. In particular, since in the inner region particles with high momenta are accepted and<br />
the particle i<strong>de</strong>ntification capability of the RICH <strong>de</strong>tector <strong>de</strong>teriorates above 12 GeV/c.<br />
A large fraction of the particles <strong>de</strong>tected in RICH thus stem from secondary sources. In or<strong>de</strong>r to allow<br />
for a good i<strong>de</strong>ntification of the light vector mesons the overwhelming combinatorial background has to<br />
be reduced (see section 16.1). One major background source are electrons from γ-conversion. In or<strong>de</strong>r to<br />
0
70 Ring Imaging Cherenkov <strong>de</strong>tector (RICH)<br />
a.u.<br />
0.22 2<br />
0.2<br />
0.18<br />
N<br />
50%N +50%CH<br />
2<br />
4<br />
40%He+60%CH4<br />
0.16<br />
0.14<br />
0.12<br />
0.1<br />
0.08<br />
0.06<br />
0.04<br />
0.02<br />
0<br />
0 20 40 60 80 100 120 140 160 180<br />
N<br />
rings<br />
a.u.<br />
0<br />
0 5 10 15 20 25 30 35 40 45 50<br />
Figure 3.21: Total multiplicity of particles <strong>de</strong>tected in RICH for central Au+Au collisions at 35 AGeV (left).<br />
Multiplicity of primary particles (generated by UrQMD) measured in the RICH <strong>de</strong>tector for N2 as a radiator<br />
(right).<br />
reduce this background source, the position/ material in which the conversion took place has to be known.<br />
The z-position of the production vertex of all tracks measured in the RICH <strong>de</strong>tector is shown in fig.3.22.<br />
Peaks on this distribution are due to tracks produced in the target (z = 0 cm, non-segmented), at the 7<br />
STS stations (z = 5,10,20,40,60,80, and 100 cm), and at the RICH front wall (z = 170 cm). The wi<strong>de</strong><br />
maximum between z = 20 cm and z = 80 cm stems mainly from e + e − pairs generated by γ-conversion<br />
in the beam pipe: Since in the current setup the first three STS stations are located in the vacuum insi<strong>de</strong><br />
the beam pipe, the size of the beam pipe is reduced after the 3rd STS station. Therefore all particles<br />
cross the beam pipe. In addition, the opening angle of the reduced beam pipe directly points back to the<br />
vertex, therefore γ rays with a certain polar angle are all converted in the beam pipe. The following wi<strong>de</strong><br />
maximum between z = 110 cm and z = 140 cm stems from e + e − pairs generated by γ-conversion in the<br />
magnet yoke. In future simulations the position of the magnet yoke relative to the RICH <strong>de</strong>tector will<br />
be changed which should yield less electrons from γ-conversion. The continuous un<strong>de</strong>rlying distribution<br />
comes from secondary particles produced in the gas. The different radiation length of the studied three<br />
radiator gases results in a different production rate of secondaries. However, it becomes clear that for all<br />
gases the contribution of background tracks can be neglected compared to the sources discussed before.<br />
This above discussion also ma<strong>de</strong> clear that the material budget in front of the RICH <strong>de</strong>tector has still to<br />
be optimized which will result in less secondaries in the RICH <strong>de</strong>tector.<br />
The occupancy of the RICH photo<strong>de</strong>tector can be represented by the number of fired photomultipliers.<br />
Fig. 3.23 shows the number of photomultipliers giving a signal in one central Au+Au collision at<br />
35 AGeV. Three RICH radiator gases, 40%He+60%CH4, N2, and 50%N2+50%CH4 are shown on this<br />
plot by different colors. The momentum distribution of tracks measured in the RICH <strong>de</strong>tector is shown in<br />
fig. 3.24. For the current geometry 58 electrons, 25 pions, 0.4 muons and 6·10 −3 kaons are measured on<br />
average per central Au+Au event at 35 AGeV. We would like to emphasize once more that these numbers<br />
will change with an optimized <strong>de</strong>tector geometry and material budget in front of the RICH <strong>de</strong>tector.<br />
700<br />
600<br />
500<br />
400<br />
300<br />
200<br />
100<br />
N<br />
prim
3.3. RICH simulations 71<br />
per event<br />
vertex<br />
N<br />
a.u.<br />
0.14<br />
0.12<br />
0.1<br />
0.08<br />
0.06<br />
0.04<br />
0.02<br />
-1<br />
10<br />
-2<br />
10<br />
-3<br />
10<br />
-4<br />
10<br />
N2<br />
50%N +50%CH<br />
2<br />
4<br />
40%He+60%CH<br />
0 50 100 150 200 250 300 350 400<br />
z [cm]<br />
N2<br />
50%N +50%CH<br />
2<br />
4<br />
40%He+60%CH<br />
0<br />
0 500 1000 1500 2000 2500 3000<br />
4<br />
NPMT<br />
Figure 3.23: Number of photomultipliers registering<br />
a photon for central Au+Au collisions at<br />
35 AGeV. Also here the quantum efficiency of the<br />
PMT-FEU Hive is used.<br />
4<br />
N per event<br />
10<br />
1<br />
-1<br />
10<br />
-2<br />
10<br />
-3<br />
10<br />
-4<br />
10<br />
Figure 3.22: z-coordinates of<br />
the track vertices for all tracks<br />
measured in the RICH <strong>de</strong>tector.<br />
± e : 58.066 per event<br />
π±<br />
: 25.387 per event<br />
± μ : 0.412 per event<br />
± K : 0.0057 per event<br />
0 5 10 15 20 25 30<br />
p , GeV/c<br />
lab<br />
Figure 3.24: (Momentum distribution of all tracks<br />
measured in the RICH <strong>de</strong>tector using N2 as radiator:<br />
e ± (red), µ ± (blue), π ± (green), and K ± (pink)<br />
are shown.
72 Ring Imaging Cherenkov <strong>de</strong>tector (RICH)<br />
3.4 Technical realization of the RICH <strong>de</strong>tector<br />
3.4.1 Optics and mirrors<br />
The actual layout of the RICH <strong>de</strong>tector in the vertical and horizontal plane is shown in fig. 3.25. The<br />
RICH <strong>de</strong>tector consists of two i<strong>de</strong>ntical spherical mirror walls. The radius of the mirror curvature is<br />
450 cm. Each spherical mirror has the overall dimensions 4.5x1.75 m 2 . The Cherenkov light produced<br />
by charged particles is focused on two photo<strong>de</strong>tector planes, positioned at 25 cm just after the dipole<br />
magnet and in about 2.2 m distance from the mirrors. In the center of the mirror system is a whole for<br />
the beam pipe.<br />
The RICH mirrors will be ma<strong>de</strong> mainly of spherical hexagonal 3 mm thick Beryllium plates covered<br />
with 0.5 mm glass which forms an optically perfect mirror surface. The diameter (maximum size) of the<br />
hexagons is 60 cm. The diameter of a light point source in the focal plane containing more than 95%<br />
Figure 3.25: Layout of the RICH <strong>de</strong>tector, left vertical plane, right horizontal plane.<br />
Figure 3.26: Be mirror prototype without glass and Al cover.
3.4. Technical realization of the RICH <strong>de</strong>tector 73<br />
of the light is less than 0.45 mm. The total radiation length of the mirror (Be+glass) is 1.25% of X0.<br />
The weight of one hexagonal plate is about 1.3 kg. The technology of such a mirror production exists<br />
in Russia and has been chosen for RICH1 of the LHCb experiment; see fig. 3.26 for a prototype of the<br />
Be plate. The measured optical surface roughness after glass polishing, Al covering and SiO2 coating is<br />
σh = 1.6 nm. This roughness <strong>de</strong>termines the diffuse reflection which is the total reflectivity R0 minus the<br />
specular reflectivity Rsp. The ratio Rsp/R0 can be calculated from σh in <strong>de</strong>pen<strong>de</strong>nce on the wavelength:<br />
Rsp/R0 = exp(−4πσh/λ). (3.1)<br />
The specular reflectivity is shown in fig. 3.27 as function of the wavelength for a surface roughness of<br />
σh = 1.6 nm. The diffuse reflectivity increases in the UV region but is still only about 12% of R0 at<br />
λ = 150 nm. The total reflectivity R0 of Al mirrors is 92% within a wi<strong>de</strong> wavelength range for photons.<br />
However, the coating to seal the Al has still to be chosen and matched to the wavelength <strong>de</strong>pen<strong>de</strong>nce of<br />
the sensitivity of the photo<strong>de</strong>tector. On average less than 92% reflectivity will thus be achieved for the<br />
final mirror.<br />
Specular reflectivity, %<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
Be-glass mirror, specular reflectivity<br />
100 200 300 400 500 600 700<br />
Wave length, nm<br />
Figure 3.27: Fraction of specular reflectivity<br />
for the Be-glass mirrors calculated according<br />
to equation 3.1.<br />
The structure of one mirror wall consisting out of the Be-glass hexagons is shown in Fig. 3.28. Each<br />
hexagon will be supported separately by the common support structure of the RICH <strong>de</strong>tector. Each<br />
segment will be moveable in or<strong>de</strong>r to allow for individual tuning to provi<strong>de</strong> excellent optics of the mirror<br />
assembly as a whole. A laser monitoring during operation of the <strong>de</strong>tector will allow for continuous<br />
quality control and readjustment if necessary.<br />
Figure 3.28: Illustration of the assembly of the Be-glass hexagons for one of the mirror walls.
74 Ring Imaging Cherenkov <strong>de</strong>tector (RICH)<br />
3.4.2 Radiator<br />
In section 3.1, the Lorentz factor γth as the main requirement on the radiator was discussed. Possible<br />
gas radiators with γth 38 are listed in table 3.1; mixtures of these gases are possible as well. Besi<strong>de</strong>s<br />
γth, the radiation length is an important factor to be consi<strong>de</strong>red because it <strong>de</strong>termines the production of<br />
secondary electrons which are an important background source in the RICH <strong>de</strong>tector. It is also a matter<br />
of concern for the multiple scattering which strongly affects the track matching between STS and TRD.<br />
Since the number of Cherenkov photons produced by charged particles consi<strong>de</strong>rably increases in the UV<br />
region (see fig. 3.11), the UV region is important for the final photon yield per particle. However, the<br />
transmittance of photons in the UV range is limited by absorption in the gas, the threshold wavelength is<br />
given in the second last column in table 3.1. Fig. 3.29 and 3.30 show the wavelength <strong>de</strong>pen<strong>de</strong>nce of the<br />
transmittance for two of the radiators as example. If no window between the photo<strong>de</strong>tector and the gas<br />
radiator will be used, possible radiator gases have also to be checked whether they are compatible with<br />
this requirement.<br />
An important characteristic of the radiators eventually limiting the resolution of the rings in the photo<strong>de</strong>tector<br />
plane is the dispersion of the refractive in<strong>de</strong>x n(λ). The chromatic dispersion is rather weak<br />
in a wi<strong>de</strong> wavelength range, however, it changes fast in the UV region. In the Landolt-Boernstein Series<br />
[65] parameterizations and data can be found for the radiator gases of interest (see fig. 3.31). For a<br />
Radiator gas n-1 γth θc λthresh Radiation<br />
[10 −4 ] [nm] length [m]<br />
He 0.35 119.5 0.48 ◦ 50 5300<br />
N2 2.98 41.0 1.4 ◦
3.4. Technical realization of the RICH <strong>de</strong>tector 75<br />
(n-1)10 4<br />
6<br />
5.5<br />
5<br />
4.5<br />
4<br />
3.5<br />
3<br />
2.5<br />
CO 2<br />
CH 4<br />
N 2<br />
2<br />
100 200 300 400 500 600 700 800<br />
λ[nm]<br />
Figure 3.31: Chromatic dispersion for various<br />
gases; data and parametrization (dotted lines) are<br />
taken from [65]. The solid line corresponds to an<br />
own fit according to formula 3.2. The dashed horizontal<br />
lines indicate the fixed refraction in<strong>de</strong>x used<br />
for simulation.<br />
temperature of 0 ◦ C and a pressure of 1 atmosphere, n(λ) can be calculated as<br />
Θ e [<strong>de</strong>grees]<br />
3<br />
2.8<br />
2.6<br />
2.4<br />
2.2<br />
2<br />
1.8<br />
1.6<br />
1.4<br />
1.2<br />
(n(λ) − 1) · 10 6 = C<br />
ν2 · 106<br />
0 − ν2<br />
= C′<br />
1<br />
λ 2 0<br />
CO 2<br />
CH 4<br />
N 2<br />
1<br />
100 200 300 400 500 600 700 800<br />
λ[nm]<br />
Figure 3.32: Wavelength <strong>de</strong>pen<strong>de</strong>nce of the<br />
Cherenkov opening angle due to the chromatic dispersion<br />
in the various gases. The opening angle is<br />
calculated from the fit with the solid line in fig. 3.31.<br />
with the parameters C and ν 2 0 or C′ and λ0 as given in table 3.2. With n(λ) the Cherenkov angle which is<br />
proportional to the ring radius can be extracted, see fig. 3.32. Taking nitrogen as example, the Cherenkov<br />
opening angle changes by ∼0.1 ◦ between λ = 600 nm and λ = 200 nm. The wavelength region which<br />
to <strong>de</strong>tect in the photo<strong>de</strong>tector has thus to be chosen keeping in mind the <strong>de</strong>sired final Cherenkov angle<br />
resolution (see discussion in section 3.3). The lower limit of the UV region can be regulated by either<br />
choosing a photo<strong>de</strong>tector working in the required wavelength region or by adding gases to the radiator<br />
with adsorption below the chosen limit.<br />
− 1<br />
λ 2<br />
Radiator gas C ν 2 0 C ′ λ0<br />
[10 27 cm −2 ] [10 27 cm −2 ] [nm −2 ] [nm]<br />
He 1.21238 34991.7<br />
N2 5.0345 17095 0.05432 73.63<br />
CH4 5.02763 11689.3 0.05412 89.13<br />
CO2 6.2144 14097 0.073191 77.73<br />
Table 3.2: Parameters for calculating the chromatic dispersion at 0 ◦ C and 1 atmosphere according to formula<br />
3.2. C and ν 2 0 are taken from [65], C′ and λ0 are from an own fit, see fig.3.31.<br />
Pure N2 as a radiator fulfills all requirements for the RICH <strong>de</strong>tector. In addition it is non inflammable and<br />
a chemically passive gas. It satisfies security requirements as well, and the RICH gas system would be<br />
rather cheap in this case. Thus, we have chosen a N2 radiator as the base option for the RICH <strong>de</strong>tector.<br />
,<br />
(3.2)
76 Ring Imaging Cherenkov <strong>de</strong>tector (RICH)<br />
The radiation length of a 2.2 m long N2 radiator is equal to 0.75% of X0. A disadvantage of the N2<br />
radiator is that N2 is a weak fluorescent gas in the UV region [72]. However, fluorescent light is diffuse<br />
and the Omega RICH <strong>de</strong>tector was successfully operated with a 5 m long nitrogen radiator for the WA69,<br />
WA82, and WA89 experiments at CERN [73]. Still, the performance of a N2 radiator in a high rate and<br />
high track <strong>de</strong>nsity experiment like at CBM should be carefully studied. It was shown that an admixture<br />
of methane but also CO2 can suppress the fluorescent light from N2 [74]. An admixture of 40% methane<br />
(or CO2) could thus also be an option for a RICH gas radiator. In addition, it would limit the transparency<br />
to wavelengths above 145 nm (or 175 nm) thus eliminating much of the region in which the refractive<br />
in<strong>de</strong>x of N2 changes fast, see fig. 3.31. The radiation length of a 2.2 m long radiator would be 0.57% of<br />
X0 for 60% N2+40% CH4. However, due to the fact that methane is highly inflammable, the gas system<br />
would be more expensive and the safety regulations would be much more <strong>de</strong>manding than in the case of a<br />
pure N2 radiator. In addition, the production of slow protons due to interactions of thermal neutrons with<br />
Hydrogen might be a problem when using methane and needs to be studied in <strong>de</strong>tail, see [260, 261, 77].<br />
Studies for a N2/CO2 mixture have still to be performed.<br />
CO2 has a slightly lower γth and a 2.2 m long radiator would correspond to 1.2% of X0, but it might<br />
still be an option if the pion i<strong>de</strong>ntification capabilities need to be increased for momenta starting from<br />
4.65 GeV/c instead of 5.6 GeV/c which is the threshold for N2. The most promising radiator gas in terms<br />
of radiation length (and the most expensive for service) is the 40% He+60% CH4 gas mixture. A 2.2<br />
m long radiator would be equal to only 0.22% of X0 in this case. In addition to the safety requirements<br />
discussed above, the He admixture would lead to hard hermetic requirements of the RICH gas system<br />
due to the high He leakage, resulting in an increased price of the gas system. He leakage would also be<br />
a matter of concern for vacuum <strong>de</strong>vices used for the photo<strong>de</strong>tector.<br />
Three gas mixtures, pure N2, 60% N2+40% CH4 and 40% He+60% CH4, were studied when simulating<br />
the RICH performance. Further studies, also with a RICH prototype, have still to be performed.<br />
3.4.3 UV photo<strong>de</strong>tector<br />
The RICH <strong>de</strong>tector has two photo<strong>de</strong>tector planes each covering an area of about 2.8x1.4 m 2 . The diameter<br />
of the focussed electron rings is approximately 11 cm (see fig. 3.14). Requiring at least 10 pads<br />
per diameter, the maximum padsize should be 1 cm×1 cm. Assuming a possible range of padsizes from<br />
0.5 cm×0.5 cm to 1 cm×1 cm, about 3 · 10 5 to 10 5 channels would be nee<strong>de</strong>d. As has been shortly discussed<br />
in the previous chapter, the sensitivity of the photo<strong>de</strong>tectors should cover as much of the visible<br />
wavelength as possible down to λ ≈ 200 nm. Moreover, due to the high interaction rates the <strong>de</strong>tectors<br />
should be fast.<br />
3.4.3.1 Small diameter photomultipliers<br />
These requirements are fulfilled by using photomultipliers as basic elements of the photo<strong>de</strong>tector. The<br />
IHEP Protvino has <strong>de</strong>signed the so called PMT FEU-Hive in cooperation with the Moscow Electrolamp<br />
Company (MELZ). This is a special small diameter photomultiplier tube on the basis of a resistive<br />
distributed dyno<strong>de</strong> system with electrostatic focusing, bialkali photocatho<strong>de</strong> and plain glass window. The<br />
external diameter of the PMT FEU-Hive is equal to 6 mm, the tube length is 60 mm, more parameters<br />
are given in table 3.3. The electrostatic optics, construction <strong>de</strong>tails and PMT parameters have been<br />
optimized by using a computer mo<strong>de</strong>l of the PMT. In particular by means of the optics and dyno<strong>de</strong><br />
system optimization one achieves an effective operation of the PMT in the one-photo-electron regime.<br />
This is an important feature for its possible application in RICH <strong>de</strong>tectors. In fig. 3.33 the simulated<br />
one-photo-electron spectrum is shown for this PMT FEU-Hive. The PMT pulse jitter is on the or<strong>de</strong>r of<br />
1 ns.
3.4. Technical realization of the RICH <strong>de</strong>tector 77<br />
Parameter Description Unit<br />
External sizes D 6x60 mm<br />
Window material C-95 glass<br />
Window thickness 0.5 mm<br />
Photocatho<strong>de</strong> Material Bialkali (K2CsSb)<br />
Spectral Response 300 to 650 nm<br />
Peak Wavelength 400-420 nm<br />
Max. Quantum Efficiency (at 400-420 nm) 25 %<br />
Dyno<strong>de</strong> structure Resistive distributive<br />
Dyno<strong>de</strong> number 13 (on average)<br />
Capacitance 10-15 pF<br />
Gain 10 6<br />
Charge 0.16 pC<br />
Power dissipation 40 mW<br />
Ano<strong>de</strong> Dark Current per Channel 0.5 nA<br />
Rise Time 1 ns<br />
Transit Time 10 ns<br />
Transit Time Spread (FWHM) 1 ns<br />
Supply (Ano<strong>de</strong> to Catho<strong>de</strong>) Voltage -2000 V<br />
Average Ano<strong>de</strong> Output Current 2 µA<br />
Weight 5 g<br />
Table 3.3: Main parameters of the PMT FEU-Hive.<br />
The photocatho<strong>de</strong> sensitivity of the PMT FEU-Hive is typical for bialkali photocatho<strong>de</strong>s, see fig. 3.34.<br />
However, a higher sensitivity in the UV range would be <strong>de</strong>sirable. To increase the sensitivity of the photo<strong>de</strong>tector<br />
in the UV region, one may use UV transparent photocatho<strong>de</strong> windows ma<strong>de</strong> of quartz, MgF2<br />
or UV glasses. This is a standard, but unfortunately rather expensive solution. An alternative solution<br />
would be to cover the glass of the photocatho<strong>de</strong> window with a transparent WLS film from evaporated<br />
layers of tetraphenil butadiene or a transparent p-terphenyl film using the technology <strong>de</strong>veloped and used<br />
at IHEP [78, 79]. According to simulations, the quantum efficiency of such an optimized photo<strong>de</strong>tector<br />
could become flat at the 22% level in the UV range starting from 100 nm, see Fig. 3.35. The plateau can<br />
be un<strong>de</strong>rstood from the flat character of the tetraphenyl butadiene or p-terphenyl WLS spectral response<br />
in the range from 100-350 nm [80]. Since dN/dλ ∝ λ −2 holds for the Cherenkov spectrum, the use of<br />
WLS films should result in an increase of <strong>de</strong>tected Cherenkov photons up to a factor of 3.5, even if a<br />
less transparent gas is used or evaporated tetraphenil butadiene WLS of a diffuse type [81]. The use of<br />
WLS films thus should consi<strong>de</strong>rably improve the performance of the RICH <strong>de</strong>tector compared with the<br />
standard solution of a usual bialkali photocatho<strong>de</strong>. Depending on the required wavelength to be <strong>de</strong>tected,<br />
the WLS film can also be chosen to extend the sensitivity to a smaller UV region.<br />
The PMTs would be assembled in two photo<strong>de</strong>tector planes using special honeycomb structures ma<strong>de</strong><br />
of carbon fibers. A schematic fragment of this structure is shown in fig. 3.36. The wall thickness<br />
of the honeycomb structure is equal to 0.5 mm. Together with the thickness of the PMT wall itself<br />
(0.5 mm of glass) this leads to an overall geometrical coverage of the photocatho<strong>de</strong>s of less than 54%<br />
only. Although the geometrical efficiency is so low, a fraction of almost 90% of the total area of the<br />
photo<strong>de</strong>tector plane can be ma<strong>de</strong> active in the RICH <strong>de</strong>tector using special cone-shaped reflectors from<br />
aluminized plastics which collect the Cherenkov light to the active part of the photocatho<strong>de</strong> window of<br />
each PMT. For estimating the overall <strong>de</strong>tection efficiency of Cherenkov photons, the quantum efficiency<br />
shown in fig. 3.35 has to be scaled with the geometrical efficiency yielding about 18% of all photons for
78 Ring Imaging Cherenkov <strong>de</strong>tector (RICH)<br />
Nevent<br />
200<br />
175<br />
150<br />
125<br />
100<br />
75<br />
50<br />
25<br />
0<br />
λ < 350 nm.<br />
0 2 4 6 8 10<br />
Amplitu<strong>de</strong> (Arbitr.units)<br />
3.4.3.2 Alternative photo<strong>de</strong>tectors<br />
Figure 3.33: One-photo-electron spectrum<br />
as simulated for the PMT FEU-Hive.<br />
As an alternative, multiano<strong>de</strong> <strong>de</strong>vices such as multiano<strong>de</strong> PMTs or HPDs are very promising, because<br />
they would reduce the number of electronic <strong>de</strong>vices consi<strong>de</strong>rably. Hamamatsu, e.g., offers a new flat<br />
panel multianao<strong>de</strong> PMT (H8500) with a 8×8 matrix, a high geometrical coverage of 89%, a pixel size<br />
of 5.8mm×5.8mm, and a bialkali photocatho<strong>de</strong> [63]. Main parameters of this flat panel MAPMT are<br />
given in table 3.4. Unfortunately an increase of the sensitivity towards the UV region cannot easily be<br />
done with WLS films. Since the light radiation of the WLS film has an isotropic angular distribution, a<br />
significant part of the shifted light will propagate along the photocatho<strong>de</strong> window resulting in a <strong>de</strong>creased<br />
position resolution for the hit position of the Cherenkov photon. In addition, the <strong>de</strong>tection efficiency will<br />
be reduced due to internal light reflection in the glass window. Intensive R&D work on this topic would<br />
be nee<strong>de</strong>d.<br />
The LHCb experiment at CERN <strong>de</strong>ci<strong>de</strong>d to use pixel-HPDs as photo<strong>de</strong>tector with a pixel size of<br />
2.5 mm×2.5 mm on the HPD photocatho<strong>de</strong>. The HPD has a 7 mm thick, spherical quartz entrance<br />
Radiant sensitivity, (mA/W)<br />
90<br />
80<br />
70<br />
60<br />
50<br />
40<br />
30<br />
20<br />
10<br />
0<br />
200 250 300 350 400 450 500 550 600 650 700<br />
Wave length, nm<br />
Figure 3.34: Sensitivity of the bialkaliphotocatho<strong>de</strong><br />
of the PMT FEU-Hive as function of<br />
the photon wavelength.<br />
Quantum efficiency, %<br />
25<br />
20<br />
15<br />
10<br />
5<br />
0<br />
100 200 300 400 500 600 700<br />
Wave length, nm<br />
Figure 3.35: Simulation of the FEU-Hive quantum<br />
efficiency with an optimized WLS window.
3.4. Technical realization of the RICH <strong>de</strong>tector 79<br />
Figure 3.36: Fragment of the honeycomb structure in which the PMTs could be assembled.<br />
Parameter Description Unit<br />
Dimensional Outline (WxHxD) 52x52x28 mm 3<br />
Effective Area 49x49 mm 2<br />
Pixel Size/Pitch at Center 5.8x5.8/6.08 mm<br />
Number of Ano<strong>de</strong> Pixels 64 (8x8 matrix)<br />
Window material Borosilicate glass<br />
Window thickness 2.0 mm<br />
Photocatho<strong>de</strong> Material Bialkali<br />
Spectral Response 300 to 650 nm<br />
Peak Wavelength 420 nm<br />
Quantum Efficiency at 420 nm 19 %<br />
Dyno<strong>de</strong> structure Metal channel dyno<strong>de</strong><br />
Dyno<strong>de</strong> number 12<br />
Gain 10 6<br />
Ano<strong>de</strong> Dark Current per Channel 0.5 nA<br />
Rise Time 0.8 ns<br />
Transit Time 6 ns<br />
Transit Time Spread (FWHM) 0.4 ns<br />
Supply (Ano<strong>de</strong> to Catho<strong>de</strong>) Voltage -1100 V<br />
Average Ano<strong>de</strong> Output Current in Total 100 µA<br />
Weight 145 g<br />
Operating Ambient Temperature 0 to +50 ◦ C<br />
Uniformity 1:3<br />
Cross-talk 3 %<br />
Table 3.4: Main parameters of the flat panel multianao<strong>de</strong> PMT H8500 [63].
80 Ring Imaging Cherenkov <strong>de</strong>tector (RICH)<br />
window with an S20 (multialkali) photocatho<strong>de</strong> <strong>de</strong>posited on its inner surface. The effective area of a<br />
hexagonal close packing of these HPDs is 67%; for more information also on the quantum efficiency<br />
see [82].<br />
Gaseous UV <strong>de</strong>tector<br />
An alternative solution to <strong>de</strong>tect the Cherenkov photons is the use of a thin gaseous <strong>de</strong>tector with a CsI<br />
photocatho<strong>de</strong>. This approach is convenient for its low cost and large geometrical coverage. However, in<br />
or<strong>de</strong>r to limit the chromatic dispersion (see fig. 3.32), the use of a window in front of the <strong>de</strong>tector would<br />
be <strong>de</strong>sirable. Quartz [83] (cut-off at approximately 170 nm) or the more expensive CaF2 [84] (cut-off at<br />
150 nm approximately) are candidate materials for this window. In this scenario, one can <strong>de</strong>couple the<br />
radiator gas from the counting gas. CsI photocatho<strong>de</strong>s are nowadays [83,85] produced with a QE of 30%<br />
at 160 nm (fig. 3.30) with an almost linear <strong>de</strong>crease to 0% at 208 nm. This range is a<strong>de</strong>quate to achieve<br />
good spatial resolution in the ring reconstruction. The gaseous <strong>de</strong>tector itself should be a few mm thin<br />
in or<strong>de</strong>r to cope with the event rate foreseen in the experiment, and to limit the energy loss of charged<br />
particles that might cross the <strong>de</strong>tector. An ano<strong>de</strong> to catho<strong>de</strong> distance of 2-3 mm is enough. The counting<br />
gas must be transparent to VUV photons and limit the scattering of the photoelectrons. The ALICE<br />
HMPID uses CH4, although mixtures of this hydrocarbon with He are conceivable. The operating gain<br />
should be ≦ 10 5 in or<strong>de</strong>r to achieve > 90% photoelectron <strong>de</strong>tection efficiency. Precisions of or<strong>de</strong>r 100<br />
µm are thus nee<strong>de</strong>d in the positioning of the electro<strong>de</strong>s for a stable operation of the chamber. Assuming a<br />
grid of 70 µm diameter catho<strong>de</strong> wires at 4 mm pitch positioned just behind the window, the geometrical<br />
acceptance would be larger than 98%. The readout electronics must combine short shaping time with<br />
good signal to noise. In this respect one can benefit from the <strong>de</strong>velopments foreseen for other <strong>de</strong>tectors<br />
of the experiment, like the TRD (see chapter 4).<br />
These different photo<strong>de</strong>tector types which could be used for the RICH <strong>de</strong>tector have to be studied in<br />
<strong>de</strong>tail. As for all the other elements of the RICH <strong>de</strong>tector, a stable operation is a major issue. The<br />
<strong>de</strong>tector simulations which have been started in or<strong>de</strong>r to give precise answers on the granularity nee<strong>de</strong>d<br />
for a sufficient Cherenkov angle resolution and the wavelength region which should i<strong>de</strong>ally be covered<br />
by the measurement.<br />
3.4.4 HV and readout electronics<br />
For the FEU-Hive photomultiplier a HV control <strong>de</strong>vice and readout electronics have been <strong>de</strong>veloped.<br />
The HV control <strong>de</strong>vice is <strong>de</strong>signed on the basis of the classical scheme, i.e. a ballast resistor Rb in<br />
connection with the PMT high voltage divi<strong>de</strong>r, see fig. 3.37. The resistor Rb, being ma<strong>de</strong> of a set of<br />
consecutive resistors Rn with values 2 n R, can be tuned to change the high voltage applied to the PMT<br />
by means of switching transistors, controlled by optopairs according to the co<strong>de</strong> in a status register, see<br />
fig. 3.38. The voltage drop on the control resistor Rb should be about 400 V (maximum 500 V). Using<br />
a 6-bit commutator for changing the value of the control resistor, the PMT high voltage can be tuned in<br />
steps of 7 V. The requirements on the FEE of the RICH <strong>de</strong>tector are <strong>de</strong>termined by the main features<br />
of the output signals from the PMTs, i.e. the dynamical range of the total charge, noise current, signal<br />
time and output chain capacitance. For the PMT FEU-Hive the dynamical range of the signal charge is<br />
Q = (0.25 − 25) · 10 6 e − = 0.04–4 pC, the average signal time is about 1 ns; other parameter values can<br />
be found in table 3.3. An additional amplification of the output signal of the PMT is nee<strong>de</strong>d. The shaping<br />
time of the amplifier is <strong>de</strong>termined by the chosen sampling frequency fsampl in the ADC. If the minimal<br />
signal sampling is set to 3, the amplifier shaping time should be on the or<strong>de</strong>r of τshaper = 3/ fsampl = 50 ns<br />
at fsampl = 60 MHz.<br />
Concerning the ADC bit number the RICH requirements are sufficiently weak. Due to the strong over-
3.4. Technical realization of the RICH <strong>de</strong>tector 81<br />
HV<br />
R<br />
b<br />
R<br />
PM<br />
Control<br />
Figure 3.37: High voltage control scheme.<br />
HV<br />
R<br />
2R 4R 8R 16R 32R<br />
R PM<br />
A B C D E F<br />
Status Register<br />
BUS<br />
Control<br />
Figure 3.38: Control resistor and commutator<br />
scheme of the PMT HV regulation.<br />
lapping one-photo-electron and two-photo-electron signal spectra in the PMT FEU-Hive, the digitization<br />
of the output signals is important only for an individual tuning of the threshold in all RICH channels. A<br />
signal digitization with an 8-bit ADC is therefore sufficient.<br />
The HV supply and readout electronics of the other possible photo<strong>de</strong>tectors discussed in the last section<br />
would still have to be <strong>de</strong>veloped. Since other new big-scale experiments like LHCb and BTeV will start<br />
before the final <strong>de</strong>sign of the CBM RICH <strong>de</strong>tector has to be available, a lot of knowledge gained in those<br />
experiments could be used for CBM.<br />
3.4.5 Support structure, gas vessel and gas supply system<br />
In general, the support structure of the RICH <strong>de</strong>tector consists of two main parts: a support system for<br />
the two photo<strong>de</strong>tector planes and a support system for the two Be-hexagon walls. For both a rectangular<br />
frame would be used in or<strong>de</strong>r to position all structural components outsi<strong>de</strong> of the spectrometer<br />
acceptance. Each mirror hexagon will be supported separately from the back and can be rotated in two<br />
dimensions for tuning the optical system.<br />
In the center of the RICH <strong>de</strong>tector a vacuum beam pipe will be installed in or<strong>de</strong>r to prevent the interaction<br />
of beam particles with the radiator gas. The overall support structure of the RICH <strong>de</strong>tector including the<br />
front part of the photo<strong>de</strong>tector planes as well as the mirror walls with mechanics are placed in one gas<br />
vessel. The approximate vessel size can be extracted from figure 3.25, it will be about (4 − 6) × 4.5 ×<br />
2.9 m 3 with a volume of ∼60 m 3 .<br />
The layout and requirements of the gas system for the RICH <strong>de</strong>tector will <strong>de</strong>pend strongly on the chosen<br />
radiator. In any case, the radiator will be operated at atmospheric pressure. Special care has to be taken to<br />
keep the radiator clean in particular from dust because of the sensitive mirror and photocatho<strong>de</strong> surfaces,<br />
and water and oxygen contamination because of their strong absorption of photons with wavelengths<br />
λ < 190 nm (see fig. 3.39). If the radiator will not be nitrogen, a nitrogen atmosphere would still be<br />
used during <strong>de</strong>tector shutdown and whenever the working gas mixture is not nee<strong>de</strong>d. The working gas<br />
would come into the vessel through filtering cartridges and cleaning <strong>de</strong>vices. The vessel gas filling rate<br />
would be about 5-7 m 3 /hour. This high value of the gas flow will be in operation until the concentration<br />
of oxygen molecules gets to a level where UV photon absorption is sufficiently low. During operation of<br />
the <strong>de</strong>tector, the gas flow will be <strong>de</strong>creased to about 2.5 m 3 /hour (corresponds to one total gas exchange<br />
per day) to constantly renew the gas mixture. These parameters will be monitored carefully by the gas<br />
control system supplied with <strong>de</strong>vices such as a commercial hydrometer, oxygen-meter and a binary gas<br />
analyzer. A possible general scheme of the gas system is shown in Fig. 3.40.
82 Ring Imaging Cherenkov <strong>de</strong>tector (RICH)<br />
He<br />
CH 4<br />
N 2<br />
Figure 3.39: Absorption spectra for water, oxygen and CO2 [71].<br />
valves Flowmeters Filter<br />
Mixer<br />
Principal scheme of the RICH1 gas system elements.<br />
gas quality control<br />
RICH1<br />
vessel<br />
to the gas<br />
collection<br />
system<br />
to atmosphere<br />
Figure 3.40: Scheme of the gas supply system for the RICH <strong>de</strong>tector in the case of operation with a<br />
40%He+60%CH4 gas mixture.
3.5. Working packages, timelines, costs 83<br />
3.5 Working packages, timelines, costs<br />
An outline of the future plans for the <strong>de</strong>velopment of the RICH <strong>de</strong>tector is presented in table 3.5.<br />
activity time period<br />
simulations of the RICH performance 2005 − 2009<br />
R&D on gas radiator 2005 − 2006<br />
R&D on WLS film 2005 − 2006<br />
R&D on photo<strong>de</strong>tectors 2005 − 2009<br />
R&D on Be-mirror and coating 2005 − 2009<br />
<strong>de</strong>tector prototype <strong>de</strong>velopment/ beam test 2006/ 2007<br />
technical proposal end 2006<br />
<strong>de</strong>sign of the gas system 2007 − 2009<br />
<strong>de</strong>sign of HV supply, cooling system 2007 − 2009<br />
<strong>de</strong>sign of readout electronics, data preprocessing 2007 − 2009<br />
final <strong>de</strong>tector layout and technology choice 2008 − 2009<br />
mechanical <strong>de</strong>sign 2009<br />
technical <strong>de</strong>sign report 2010<br />
production, installation, tests 2011 − 2012<br />
Table 3.5: RICH future planning<br />
Since at the present stage only a conceptual <strong>de</strong>sign for the RICH <strong>de</strong>tector has been <strong>de</strong>veloped, a cost<br />
estimate can only be done with respect to other similar RICH <strong>de</strong>tectors being currently build or planned.<br />
As a reference point we have taken the RICH2 <strong>de</strong>tector of the LHCb experiment [82], because this<br />
<strong>de</strong>tector will in several aspects be similar to the RICH <strong>de</strong>tector of CBM. Since for most subsystems of<br />
the RICH <strong>de</strong>tector several options are still un<strong>de</strong>r discussion, only ranges of expected costs can be given.<br />
Cost for <strong>de</strong>tector R&D are only partially inclu<strong>de</strong>d in the estimate, thus extra costs should be foreseen.<br />
Item Cost(M)<br />
mechanics 0.5 − 1<br />
Be-glass mirrors 1 − 1.5<br />
photo<strong>de</strong>tector 2.5 − 4.5<br />
electronics 0.5 − 1<br />
gas system 0.5− 1<br />
services ∼ 0.5<br />
extra R&D ∼ 0.5<br />
total 6 − 10<br />
Table 3.6: Cost estimate of the RICH <strong>de</strong>tector.
84 Ring Imaging Cherenkov <strong>de</strong>tector (RICH)
4 Transition Radiation <strong>de</strong>tector (TRD)<br />
4.1 Design consi<strong>de</strong>rations<br />
The TRD will provi<strong>de</strong> electron i<strong>de</strong>ntification and tracking of all charged particles. It has to provi<strong>de</strong>, in<br />
conjunction with the RICH <strong>de</strong>tector and the electromagnetic calorimeter, sufficient electron i<strong>de</strong>ntification<br />
capability for the measurements of charmonium and of low-mass vector mesons. The required pion<br />
suppression is a factor of about 100 and the required position resolution is of the or<strong>de</strong>r of 200-300 µm.<br />
In or<strong>de</strong>r to fulfill these tasks, in the context of the high rates and high particle multiplicities in CBM, a<br />
careful optimisation of the <strong>de</strong>tector is required.<br />
Currently, the whole <strong>de</strong>tector is envisaged to be divi<strong>de</strong>d into 3 stations, positioned at distances of 4, 6<br />
and 8 m from the target. A <strong>de</strong>tailed study of the tracking performance in combination with all the CBM<br />
sub<strong>de</strong>tectors is nee<strong>de</strong>d for a final <strong>de</strong>cision on such a segmentation, as well as for the final requirements<br />
on position resolution within each of the planes. The total thickness of the <strong>de</strong>tector in terms of radiation<br />
length has to be kept as small as possible to minimise multiple scattering and conversions. The gas<br />
mixture of the readout <strong>de</strong>tectors has to be based on Xe, to maximize the absorption of transition radiation<br />
(TR) produced by the radiator. Because of the high rate environment expected in the CBM experiment,<br />
a fast readout <strong>de</strong>tector has to be used. To ensure the speed and also to minimize possible space charge<br />
effects expected at high rates, it is clear that the <strong>de</strong>tector has to have a thickness smaller than 1 cm.<br />
Two solutions exist for such a <strong>de</strong>tector: a multiwire proportional chamber (MWPC) with pad readout<br />
or a straw tube. Both will be investigated in <strong>de</strong>tail in the following sections as alternative <strong>de</strong>signs. A<br />
combination of the two is feasible and is a possible solution.<br />
For the radiator there are two principal possibilities: regular and irregular. The regular radiator, composed<br />
of foils (polypropylene) and gaps of equal size, is obviously the choice which provi<strong>de</strong>s the highest TR<br />
yield. However, the costs are rather high due to a complicated construction procedure. The irregular<br />
radiator, composed of fibres and/or foams has a reduced TR yield compared to a regular radiator of<br />
the same material budget, but the advantage is ease of manufacturing. In addition, such a radiator can<br />
accommodate the stiff support structure for keeping the required flatness of the MWPC gas window, as<br />
in the ALICE TRD [86]. The TR performance of various irregular materials (foams and fibres) have<br />
been evaluated during the prototype tests for ALICE TRD [87]. The final choice of the radiator type in<br />
CBM TRD will be established after the completion of prototypes tests.<br />
4.2 An MWPC-based TRD<br />
The small readout cell required to cope with the high multiplicities for small forward angles in CBM can<br />
be easily realized with pad readout MWPCs as <strong>de</strong>tector element in TRD. Good performance concerning<br />
both electron/pion i<strong>de</strong>ntification [88] and position resolution [89] are established features of such chambers.<br />
In addition, they are rather easy to manufacture, allow for <strong>de</strong>sign flexibility and are very stable over<br />
a wi<strong>de</strong> range of gas compositions and of gas gain values.<br />
85
86 Transition Radiation <strong>de</strong>tector (TRD)<br />
4.2.1 Simulations of electron/pion i<strong>de</strong>ntification<br />
A standalone Monte Carlo C++ based simulation co<strong>de</strong> was <strong>de</strong>veloped to perform the simulations. The<br />
main goal is to scan over a reasonable region of the basic parameters of the <strong>de</strong>tector: gas <strong>de</strong>tector thickness,<br />
radiator thickness, number of <strong>de</strong>tectors and basic properties of the radiator (gap and foil thickness)<br />
and their influence on the electron/pion separation capability of the TRD. The radiator material<br />
(polypropylene and air) is kept unchanged for this study. In the simulations, one layer of the TRD consists<br />
of a radiator, composed of polypropylene foils with air gaps, and a readout chamber filled with<br />
a Xe/CO2 (85/15) mixture. A mylar foil of 25 µm thickness acts as <strong>de</strong>tector gas barrier. A simulated<br />
"event" corresponds to either one electron or one pion crossing the <strong>de</strong>tector.<br />
The following processes are consi<strong>de</strong>red in the simulations: i) energy loss of electrons and pions in the<br />
gas <strong>de</strong>tector, done following the procedure <strong>de</strong>scribed in [90]. Primary electrons with energies above 10<br />
keV are treated as <strong>de</strong>lta electrons whose trajectory is collinear with the one of the primary particle; ii)<br />
for electrons, production and absorption of TR in the radiator, absorption of TR in the mylar foil and<br />
absorption of TR in the active gas volume. The baseline <strong>de</strong>tector gas thickness is consi<strong>de</strong>red here to be<br />
6 mm. Most of the results shown are for a momentum of 2 GeV/c.<br />
counts<br />
N. of produced TR photons per electron per TRD Mean 0.8218 TR spectra<br />
Mean 8.816<br />
counts<br />
4<br />
10<br />
3<br />
10<br />
2<br />
10<br />
10<br />
1<br />
RMS 0.904<br />
0 1 2 3 4 5 6 7 8 9<br />
N. of photons<br />
counts<br />
0.12<br />
0.1<br />
0.08<br />
0.06<br />
0.04<br />
0.02<br />
0<br />
RMS 6.526<br />
5 10 15 20 25 30 35 40 45 50<br />
Energy [keV]<br />
TR spectra escaped from the <strong>de</strong>tector Mean 12.47 TR spectra absorbed in the <strong>de</strong>tector<br />
Mean 6.379<br />
0.045<br />
0.04<br />
0.035<br />
0.03<br />
0.025<br />
0.02<br />
0.015<br />
0.01<br />
0.005<br />
0<br />
RMS 8.338<br />
5 10 15 20 25 30 35 40 45 50<br />
Energy [keV]<br />
counts<br />
0.1<br />
0.08<br />
0.06<br />
0.04<br />
0.02<br />
0<br />
RMS 3.128<br />
5 10 15 20 25 30 35 40 45 50<br />
Energy [keV]<br />
Figure 4.1: The distribution of the number of TR photons per electron (upper left panel) and the spectra of TR:<br />
produced in the radiator (upper right), absorbed in the active <strong>de</strong>tector gas (lower right) and behind the <strong>de</strong>tector<br />
(lower left).<br />
Computation of the transition radiation spectra in the radiator is done with a simplified formula [91]:<br />
dW<br />
dω =<br />
4α<br />
σ(κ + 1) (1 − exp(−Nf σ)) × <br />
n<br />
Θn<br />
1<br />
ρ1 + Θn<br />
−<br />
1<br />
ρ2 + Θn<br />
2<br />
[1 − cos(ρ1 + Θn)] (4.1)
4.2. An MWPC-based TRD 87<br />
where:<br />
ρi = ωd1<br />
2c<br />
−2 2<br />
γ + ξi , κ = d2/d1, Θn = 2πn − (ρ1 + κρ2)<br />
> 0, ξ = ωplasma/ω. (4.2)<br />
1 + κ<br />
d1, d2 are the foil thickness and gap width, respectively, and Nf is the number of foils. ωplasma is the<br />
plasma frequency of the material, ω is the frequency of the emitted photon, σ is the absorption coefficient<br />
of the radiation in one (foil + gap) layer of the radiator. The X-ray mass attenuation coefficients for<br />
the radiator, mylar foil and <strong>de</strong>tector gas mixture are taken from [92]. Unless otherwise specified, the<br />
radiator parameters used for the present simulations are: d1=10 µm, d2=90 µm, Nf =100. The basic TR<br />
properties for these parameters are shown in Fig. 4.1. It is important to mention that the parameters<br />
of this equivalent regular radiator were tuned to reproduce the properties of an inhomogeneous radiator<br />
(polypropylene fiber mats and Rohacell foam) used in the ALICE TRD [88, 93]. The number of foils<br />
Nf =100 correspond, for the inhomogeneous radiator, to a thickness of about 2 cm. For the study on the<br />
effect of varying d1 and d2, the results are valid only for a regular radiator.<br />
[keV]<br />
12<br />
11<br />
10<br />
9<br />
8<br />
7<br />
6<br />
5<br />
produced photons<br />
absorbed photons<br />
10 12 14 16 18 20<br />
foil thickness [ μ m]<br />
<br />
1.1<br />
1<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
produced photons<br />
absorbed photons<br />
10 12 14 16 18 20<br />
foil thickness [ μ m]<br />
Figure 4.2: Depen<strong>de</strong>nce of the TR yield on the foil thickness for produced and <strong>de</strong>tected average energy per TR<br />
photon (left panel) and average number of TR photons (right panel), for a gap width of 90 µm.<br />
In Fig. 4.2 and 4.3 we illustrate the <strong>de</strong>pen<strong>de</strong>nce of the TR yield, produced and <strong>de</strong>tected, on the thickness<br />
of the foil and of the gap, respectively. The TR yield is quantified by the average energy per TR photon<br />
and by the average number of the TR photons. Plotted are the yield produced (at the end of the radiator)<br />
and as <strong>de</strong>tected. With increasing foil thickness, both the average energy of produced TR and the number<br />
of produced photons increase. However, due to a har<strong>de</strong>r TR spectrum for thicker foils, the number<br />
of <strong>de</strong>tected photons starts to <strong>de</strong>crease for a foil thickness larger than 14 µm. Although this effect is<br />
compensated by the larger TR energy, beyond a foil thickness of about 16 µm the overall gain in TR<br />
yield is marginal. The <strong>de</strong>pen<strong>de</strong>nce of TR on the gap width, Fig. 4.3, is somewhat different: while the<br />
average energy of the TR is almost constant, the number of the TR photons, both produced and <strong>de</strong>tected,<br />
is increasing, with a saturation expected for a gap width beyond 300 µm. All of these effects are arising<br />
due to the formation zone character of TR [94].<br />
The calculated spectra of energy <strong>de</strong>posited in one <strong>de</strong>tector layer are shown in Fig. 4.4 for pions and<br />
electrons. These spectra are taken as probability distributions to produce a signal with a given energy,<br />
p(Eπ i ) and p(Ee i ), respectively. The likelihood (to be an electron) for N layers is then computed as
88 Transition Radiation <strong>de</strong>tector (TRD)<br />
[keV]<br />
counts<br />
9<br />
8.5<br />
8<br />
7.5<br />
7<br />
6.5<br />
5<br />
10<br />
4<br />
10<br />
3<br />
10<br />
2<br />
10<br />
produced photons<br />
absorbed photons<br />
6<br />
80 100 120 140 160 180 200 220 240<br />
gap width [ μ m]<br />
10<br />
<br />
1.2<br />
1.1<br />
1<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
produced photons<br />
absorbed photons<br />
0.4<br />
80 100 120 140 160 180 200 220 240<br />
gap width [ μ m]<br />
Figure 4.3: Same as Fig. 4.2, but for the gap width, for a foil thickness of 10 µm.<br />
el. with TR<br />
el. without TR<br />
pion<br />
0 5 10 15 20 25 30 35 40 45 50<br />
Energy [keV]<br />
Figure 4.4: Deposited energy spectra for electrons<br />
(with and without TR) and pions of 2 GeV/c.<br />
follows:<br />
Likelihood = Pe<br />
, Pe =<br />
Pe + Pπ<br />
counts<br />
10<br />
6<br />
5<br />
10<br />
4<br />
10<br />
3<br />
10<br />
pions<br />
electrons<br />
90 %<br />
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1<br />
likelihood<br />
Figure 4.5: Likelihood distributions for electrons and<br />
pions. The limit for 90% electron efficiency is indicated.<br />
N<br />
p(E e N<br />
i ), Pπ = p(E π i ) (4.3)<br />
The likelihood distributions are shown in Fig. 4.5. The pion efficiency (misi<strong>de</strong>ntification probability) is<br />
the relative number of counts in the region corresponding to a certain electron efficiency (90% in our<br />
case). In the following the term "pion efficiency" is used to quantify the electron/pion i<strong>de</strong>ntification. The<br />
inverse of the pion efficiency is the pion suppression factor. For example, a pion efficiency of 1% (pion<br />
suppression of 100) means that 1% of the pions are misi<strong>de</strong>ntified as electrons. In the simulations, we<br />
require the pion suppression to be 200 or better, to have a safety margin, as in the real experiment high<br />
rates and high occupancy may lead to a <strong>de</strong>terioration of the <strong>de</strong>tector performance. The pion rejection<br />
factor will be slightly improved when taking into account TR propagation and absorption in subsequent<br />
layers, an effect not consi<strong>de</strong>red in the present simulations.<br />
i=1<br />
i=1
4.2. An MWPC-based TRD 89<br />
pion eff. [%]<br />
0.65<br />
0.6<br />
0.55<br />
0.5<br />
0.45<br />
0.4<br />
0.35<br />
9 TRDs (180 foils)<br />
12 TRDs (100 foils)<br />
10 11 12 13 14 15 16<br />
foil thickness [ μ m]<br />
Figure 4.6: Pion efficiency as a function of the foil<br />
thickness for 9 and 12 TRD layers (d2=90 µm).<br />
pion eff. [%]<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
9 TRDs (180 foils)<br />
12 TRDs (100 foils)<br />
80 100 120 140 160 180 200 220<br />
gap thickness [ μ m]<br />
Figure 4.7: Pion efficiency as a function of the gap<br />
thickness for 9 and 12 TRD layers (d1=10 µm).<br />
The <strong>de</strong>pen<strong>de</strong>nce of the pion efficiency on the foil thickness and on the gap width is shown in Fig. 4.6<br />
and Fig. 4.7, respectively. The results for a TRD configuration with 9 and 12 layers are shown. In the<br />
case of a 9 layer TRD, the number of foils has to be increased to Nf =180 in or<strong>de</strong>r to obtain the same<br />
pion rejection as for 12 layers with Nf =100. Fig. 4.6 shows that increasing the thickness of the foils<br />
from 10 to 16 µm improves the pion rejection by a factor of 2. The increase of the material budget due<br />
to the increase of the foil thickness will obviously have a negative impact on the tracking capability of<br />
the TRD. This needs to be evaluated in separate studies. Fig. 4.7 shows that an increase of the gap width<br />
from 90 to 210 µm leads to an improvement of the pion rejection by a factor of 6. As increasing the gap<br />
does not imply any negative impact on the material budget, it is clear that a regular radiator with a large<br />
foil gap would lead to a significantly better electron/pion i<strong>de</strong>ntification than an irregular radiator (which<br />
corresponds to small gap values) of the same material budget.<br />
In Fig. 4.8, left panel, the pion efficiency as a function of number of layers is shown for different radiator<br />
thicknesses (number of foils). Also shown is the pion efficiency computed without radiator (only from<br />
dE/dx in case of electrons). The right panel of Fig. 4.8 shows a similar <strong>de</strong>pen<strong>de</strong>nce of the pion efficiency<br />
on the thickness of the gas readout chamber. The required pion efficiency can be reached with different<br />
<strong>de</strong>tector configurations. A lighter radiator (which is more favorable for tracking) implies more layers (at<br />
higher costs for the extra electronics channels). A thicker readout chamber implies the benefit of fewer<br />
layers, but needs to be tested with prototypes concerning the rate capability and the position resolution<br />
performance. The <strong>de</strong>cision on the final configuration has to await the final assessments on the required<br />
position resolution performance.<br />
In Fig. 4.9 we present the <strong>de</strong>pen<strong>de</strong>nce of the pion efficiency on the CO2 concentration in the <strong>de</strong>tector<br />
mixture, for two radiator configurations and a 9 layer TRD. As expected, the pion rejection shows a<br />
strong <strong>de</strong>pen<strong>de</strong>nce on the CO2 content, arising from the efficiency of TR absorption in the active <strong>de</strong>tector<br />
gas. For instance, about a factor of 2 better rejection is achieved for 10% CO2 compared to 30% CO2.<br />
The amount of CO2 is dictated by <strong>de</strong>tector consi<strong>de</strong>ration (stability, gas gain) and we expect to be able<br />
to operate our <strong>de</strong>tectors at a CO2 content of 10-15%. Another point to emphasize from Fig. 4.9 is the<br />
importance to have a regular radiator, for which one can choose the parameters more easily than for an<br />
irregular one. This is in particular the case for the gap width, which does bring a nice improvement of the<br />
pion rejection, essentially without any penalty. For the two configurations (d1/d2/Nf ) that we investigate,<br />
a factor of 2 better rejection is achieved with the large gap width variant (d2=210 µm) compared to the
90 Transition Radiation <strong>de</strong>tector (TRD)<br />
pion efficiency [%]<br />
10<br />
1<br />
-1<br />
10<br />
NO radiator<br />
80 foils<br />
100 foils<br />
120 foils<br />
140 foils<br />
160 foils<br />
180 foils<br />
200 foils<br />
8 9 10 11 12<br />
No. of TRD<br />
pion efficiency [%]<br />
10<br />
1<br />
-1<br />
10<br />
3 mm<br />
4 mm<br />
5 mm<br />
6 mm<br />
7 mm<br />
8 mm<br />
9 mm<br />
10 mm<br />
8 9 10 11 12<br />
No. of TRD<br />
Figure 4.8: Left panel: Pion efficiency as a function of number of the TRD layers for different number of foils.<br />
The pion efficiency based only on dEdx (no TR inclu<strong>de</strong>d) is also shown. The <strong>de</strong>tector thickness is 6 mm. Right<br />
panel: pion efficiency as a function of number of the TRD layers for different <strong>de</strong>tector gas thicknesses, for Nf =100.<br />
pion efficiency [%]<br />
1.2 9 TRD - 10/90/180<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
9 TRD - 15/210/100<br />
0.1 0.15 0.2 0.25 0.3 0.35<br />
CO2 content [%]<br />
Figure 4.9: Pion efficiency as a function CO2 concentration in the <strong>de</strong>tector mixture for two radiator configurations<br />
(d1/d2/Nf ), for a 9 layer TRD.<br />
case of small gap width (d2=90 µm), even at a smaller material budget. Note that the case of small gap<br />
width does correspond to an irregular radiator that would have anyway more material that its equivalent<br />
regular radiator parametrization.<br />
In summary, the results of our simulations <strong>de</strong>monstrate that a TRD with 9 to 12 layers can fulfill the<br />
required electron/pion i<strong>de</strong>ntification performance in CBM. From the multi-dimensional parameter space<br />
of the <strong>de</strong>tector which we have explored, a configuration will be chosen based on further studies with<br />
simulations and <strong>de</strong>tector prototypes.
4.2. An MWPC-based TRD 91<br />
4.2.2 Tests with prototypes<br />
Four prototype MWPCs have been tested with sources ( 55 Fe) and beams. In addition, one GEM-readout<br />
chamber was studied in the beam measurements for reference. The two different layouts used for the<br />
MWPCs are sketched in Fig. 4.10. Three different prototypes were realized for the <strong>de</strong>sign presented in<br />
the left panel of Fig. 4.10, differing in ano<strong>de</strong> pitch: 2 and 4 mm were used for the two chambers built<br />
at <strong>GSI</strong> (labelled <strong>GSI</strong>1 and <strong>GSI</strong>2 in the following plots), while 2.5 mm was used for the chamber built in<br />
Bucharest. The ano<strong>de</strong>-catho<strong>de</strong> gap for these three chambers is 3 mm. The entrance window of 25 µm<br />
aluminized kapton simultaneously serves as gas barrier and catho<strong>de</strong> plane. The pad planes consist of a<br />
segmented catho<strong>de</strong> with 8 pads with an area of 6 cm 2 each. The width of one pad is 7.5 mm, the length<br />
80 mm.<br />
z<br />
x<br />
3 mm<br />
3 mm<br />
ano<strong>de</strong><br />
wires<br />
catho<strong>de</strong> pads<br />
Radiator<br />
particle<br />
amplification<br />
region<br />
entrance<br />
window<br />
Figure 4.10: Layout of the MWPC prototypes. Left panel: chambers built at <strong>GSI</strong> and in Bucharest, right panel:<br />
chamber built in Dubna.<br />
Another chamber, built in Dubna, has a different <strong>de</strong>sign, with a drift region of 8 mm and an amplification<br />
region of 4 mm, as seen in the right panel of Fig. 4.10. The ano<strong>de</strong> wire pitch is in this case 2 mm, while<br />
the catho<strong>de</strong> wires are spaced by 0.5 mm. The size of the readout pads is 3×4 mm 2 . For all chambers,<br />
the ano<strong>de</strong> wires are ma<strong>de</strong> of gold-plated tungsten and have a diameter of 20 µm.<br />
In Fig. 4.11 the layout of the GEM chamber from the Dubna group is shown. The <strong>de</strong>tector has a drift<br />
gap of 3 mm and 3 amplification stages. The size of the readout pads is 10 x 20 mm 2 .<br />
A charge-sensitive preamplifier/shaper (PASA), built with discrete components for the tests of ALICE<br />
TRD prototypes was used for the Bucharest prototype. It has a gain of 2 mV/fC and noise of 1800<br />
electrons r.m.s. For both MWPCs from <strong>GSI</strong>, ASIC PASAs, also from ALICE TRD [86], with a gain of 6<br />
mV/fC and a noise of 1000 electrons r.m.s were used. The FWHM of the output pulse is, for both PASA<br />
types, about 100 ns for an input step function. An octal channel PASA was <strong>de</strong>signed for the Dubna<br />
MWPC and GEM, based on the KATOD-1 ASIC [95]. A low-noise preamplifier ASIC PU-1/2 [96] was<br />
used as a first stage. The total gain is 10 mV/fC, with fully differential output. The level of noise was<br />
about 1500 e (FWHM). Two different shaping time values were used for GEM and MWPC, 400 ns and<br />
700ns, respectively. For the readout of the chambers we used an 8-bit nonlinear Flash ADC (FADC)<br />
system with 33 MHz sampling frequency, 0.6 V voltage swing and an adjustable baseline.<br />
The prototypes have been tested with the Ar- and Xe-based gas mixtures (with 15% and 30% CO2 as<br />
quencher) using a 55 Fe X-ray source of 5.9 keV and beams. Tests with X-rays at high-rate are un<strong>de</strong>r way.
92 Transition Radiation <strong>de</strong>tector (TRD)<br />
4.2.2.1 Tests with 55 Fe source<br />
Figure 4.11: Geometry of the GEM <strong>de</strong>tector.<br />
In Fig. 4.12 <strong>de</strong>tector signals for two gas mixtures are shown, which were obtained with the 55 Fe source<br />
for chamber <strong>GSI</strong>2. The ano<strong>de</strong> voltage was 1.35 kV for the Ar-based gas mixture and 1.55 kV for the<br />
Xe-based gas mixture. These signals are from the pad on which the collimated source was centered. The<br />
shape of the signals is a convolution of the <strong>de</strong>tector signal and the PASA response. The longer tails in<br />
case of the Xe-based mixture is the result of the slower ion motion. Note that the mobility of the Xe ions<br />
is almost 3 times lower than that of Ar ions [97].<br />
Figure 4.12: Time <strong>de</strong>velopment of the signals for the <strong>GSI</strong> chamber with 4 mm ano<strong>de</strong> pitch measured with a 55 Fe<br />
source. On the left si<strong>de</strong> for measurements with an Ar based gas mixture, on the right si<strong>de</strong> for a Xe based mixture.<br />
In both cases the fraction of CO2 was 15%.
4.2. An MWPC-based TRD 93<br />
The energy spectrum of the 55 Fe source is obtained by integrating the signals of the main pad and one<br />
neighbouring pad on each si<strong>de</strong>. This is done to account for the charge sharing between adjacent pads. In<br />
Fig. 4.13 we present the energy spectra of 55 Fe measured for the Ar- and Xe-based gas mixtures with a<br />
CO2 fraction of 15 %. The ano<strong>de</strong> voltage was 1.35 kV (Ar,CO2) and 1.55 kV (Xe,CO2). Besi<strong>de</strong> the main<br />
peak corresponding to the full energy <strong>de</strong>posit of 5.9 keV, the escape peak corresponding to the partial<br />
energy <strong>de</strong>posit of 2.9 keV in the Ar-based and around 1.2 keV in the Xe-based gas mixture is clearly<br />
visible for both cases.<br />
Figure 4.13: The spectra of 55 Fe measured with Ar,CO2(15%) (left panel) and Xe,CO2(15%) (right panel )for<br />
the <strong>GSI</strong> chamber with 4 mm ano<strong>de</strong> pitch. The curves are the results of gaussian fits to the main peak.<br />
The curves are the results of gaussian fits to the main peak, to extract the mean value and the width of the<br />
energy spectrum. The achieved resolutions are 10-11% for the Xe-based and 11-14% for the Ar-based<br />
gas mixture.<br />
In Fig. 4.14 the energy spectrum of 55 Fe measured for Ar/CO2(85/15), obtained with the MWPC built in<br />
Bucharest is shown. The energy resolution is 8.6%.<br />
The gain as a function of the ano<strong>de</strong> voltage Ua is measured using a 55 Fe source placed in front of the<br />
entrance window of the chamber. Information about gas gain curves are important inputs for programs<br />
simulating the <strong>de</strong>tector behaviour un<strong>de</strong>r high rate conditions, when space charge effects lead to an <strong>de</strong>crease<br />
of the <strong>de</strong>tector signal. The gain was measured for both <strong>GSI</strong> chambers as a function of the ano<strong>de</strong><br />
voltage Ua for different gas mixtures. The results of the measurements for the Xe,CO2(15%) mixture<br />
are shown in figure 4.15. The lines in this figure are results from calculations [98] with the program<br />
Magboltz [99]. These calculations are reproducing the measurements very well, giving confi<strong>de</strong>nce for<br />
future simulations which will be employed for <strong>de</strong>tector <strong>de</strong>sign.<br />
4.2.2.2 Beam tests<br />
The aim of the measurements performed at the secondary beam at SIS/<strong>GSI</strong> was to test the general <strong>de</strong>tector<br />
performance of the different readout chambers un<strong>de</strong>r high rate conditions. The bulk of the measurements<br />
were performed with a mixed proton and pion beam at 2 GeV/c for two Xe-based gas mixtures:<br />
Xe,CO2(15%) and Xe,CO2(30%).<br />
The setup used for the beam tests, sketched in Fig. 4.16, is composed of the following <strong>de</strong>tectors:<br />
• two scintillator counters (S0, S1), used for beam <strong>de</strong>finition and trigger, with area 5×5 cm 2 .
94 Transition Radiation <strong>de</strong>tector (TRD)<br />
Figure 4.14: Energy spectra of 55 Fe measured with the<br />
MWPC built in Bucharest.<br />
S0<br />
Si1 Si2<br />
<strong>GSI</strong>1 <strong>GSI</strong>2<br />
Gain<br />
10 4<br />
10 3<br />
Bukarest GEM MWPC<br />
4 mm<br />
2 mm<br />
Xe,CO 2 (15%)<br />
lines: simulations, NIM A523 (2004) 302<br />
1.4 1.5 1.6 1.7 1.8 1.9 2<br />
Ua (kV)<br />
Figure 4.15: Gain <strong>de</strong>pen<strong>de</strong>nce as a function on the<br />
ano<strong>de</strong> voltage for the two <strong>GSI</strong> chambers (2 and 4 mm<br />
ano<strong>de</strong> pitch), for the Xe,CO2(15%) mixture. The lines<br />
are results of calculations with the program Magboltz<br />
[99].<br />
Figure 4.16: Sketch of the setup used for the beam tests (not to scale). The different components are explained<br />
in the text.<br />
• two MWPCs built at <strong>GSI</strong> (<strong>GSI</strong>1, <strong>GSI</strong>2)<br />
• a MWPC built by the Bucharest group<br />
• a MWPC readout chamber built by the Dubna group<br />
• a GEM with pad readout, also built in Dubna<br />
• two silicon strip <strong>de</strong>tectors (Si1, Si2) with active area of 32 x 32 mm 2 . Each have strips of 50 µm<br />
pitch in both x and y direction.<br />
• a Pb-glass calorimeter (Pb) with dimensions of 6×10 cm 2 and a <strong>de</strong>pth of 25 cm (equivalent to<br />
10 X0) for electron i<strong>de</strong>ntification. This <strong>de</strong>tector was only insi<strong>de</strong> the experimental setup for a run<br />
<strong>de</strong>dicated to electron i<strong>de</strong>ntification.<br />
The data acquisition (DAQ) was based on a VME event buil<strong>de</strong>r and <strong>de</strong>veloped at <strong>GSI</strong> Darmstadt [100].<br />
The beam trigger was <strong>de</strong>fined by a coinci<strong>de</strong>nce of the two scintillator counters. The size of the beam<br />
was about 10 cm 2 FWHM for all measurements. The measurements have been carried out with positive<br />
secondaries of 1 and 2 GeV/c momentum. The composition of the beam varies as function of momentum,<br />
which can be seen in the time-of-flight (ToF) spectra shown in Fig. 4.17, measured with the two<br />
S1<br />
Pb<br />
Beam
4.2. An MWPC-based TRD 95<br />
10 4<br />
10 3<br />
10 2<br />
10<br />
1<br />
p=1 GeV/c<br />
750 1000 1250 1500 1750<br />
10 4<br />
10 3<br />
10 2<br />
10<br />
1<br />
p=2 GeV/c<br />
750 1000 1250 1500 1750<br />
ToF (a.u.)<br />
Figure 4.17: Time-of-flight spectra for 1 and 2 GeV/c beam momentum.<br />
scintillators. At 1 GeV/c, the mixture of pions and protons makes the study of the separation between<br />
these two species using dE/dx a suitable substitute for the electron/pion case, for which the rates were<br />
not high enough. However, the beam intensities at 1 GeV/c were also not sufficiently high to study the<br />
relative rate performance of pions and protons. We have resorted to the 2 GeV/c beam, for which the<br />
beam almost entirely consists of protons, but enabled us to do basic exploratory measurements of <strong>de</strong>tector<br />
performance as a function of rate. The rate was chosen by varying the extraction time of the primary<br />
beam from 2 to 0.2 seconds.<br />
The time <strong>de</strong>pen<strong>de</strong>nce of the average pulse height is shown in Fig. 4.18 for the gas mixture<br />
Xe,CO2(70%/30%). From left to right the spill length is <strong>de</strong>creasing (increasing rate). From top to<br />
bottom the data for the different readout chambers are shown. The time zero has been shifted arbitrarily<br />
by about 0.2 µs to have a measurement of the baseline. One can notice that the absolute magnitu<strong>de</strong> of<br />
the peak is changing very little with increasing rate. However, the tails of the signals are larger with<br />
increasing beam rate, probably due to pile-up.<br />
The signals illustrated in Fig. 4.18 are summed over adjacent pads and integrated around the peak values<br />
to produce the energy <strong>de</strong>posit spectra. The resulting spectra are shown in Fig. 4.19 for all five chambers.<br />
The lines represent Landau fits to the distributions. The distributions are characterised by the most<br />
probable value (MPV) and the widths.<br />
In Fig. 4.20 we present the results for the Dubna <strong>de</strong>tectors. Both the MWPC and the GEM chambers<br />
show no <strong>de</strong>gradation of the signal amplitu<strong>de</strong>s for high rates. The results for the relative <strong>de</strong>tector gain<br />
(<strong>de</strong>rived from signal amplitu<strong>de</strong>s) as a function of the rate for the <strong>GSI</strong> <strong>de</strong>tectors are shown in Fig. 4.21.<br />
These results correspond to the gas mixture Xe,CO2(15%) with ano<strong>de</strong> voltages of Ua=2.0 kV and 1.55<br />
kV for <strong>GSI</strong>1 and <strong>GSI</strong>2, respectively. The gain values at low rate for these settings are 11300 for <strong>GSI</strong>1<br />
and 7500 for <strong>GSI</strong>2 (see Fig. 4.15). The lines are simulations taking into account the geometry of the<br />
MWPC [101, 99] and the increasing space charge with increasing rate [102]. Again, the measurements<br />
show no <strong>de</strong>crease of the gain with increasing rate, while the simulations indicate a gain drop of a few<br />
percent, <strong>de</strong>pending on the ano<strong>de</strong> wire pitch.<br />
The <strong>de</strong>pen<strong>de</strong>nce of the width of the charge distributions on rate for the gas mixture Xe,CO2(15%) is
96 Transition Radiation <strong>de</strong>tector (TRD)<br />
(mV/0.74)<br />
50<br />
2<br />
S1:260000, S2:150000 /spill; Xe,CO 2 (30%)<br />
50<br />
1<br />
0<br />
0<br />
0<br />
0<br />
0 0.5 1 1.5 0 0.5 1 1.5 0 0.5 1 1.5 0 0.5 1 1.5<br />
50<br />
50<br />
50<br />
50<br />
0<br />
0 0.5 1 1.5 0<br />
0 0.5 1 1.5 0<br />
0 0.5 1 1.5 0<br />
0 0.5 1 1.5<br />
50<br />
50<br />
50<br />
0<br />
0 0.5 1 1.5 0<br />
0 0.5 1 1.5 0<br />
0 0.5 1 1.5 0<br />
0 0.5 1 1.5<br />
10<br />
0<br />
0 0.5 1 1.5 0<br />
0 0.5 1 1.5 0<br />
0 0.5 1 1.5 0<br />
0 0.5 1 1.5<br />
20<br />
10<br />
10<br />
20<br />
10<br />
20<br />
0<br />
0 0.5 1 1.5 0<br />
0 0.5 1 1.5 0<br />
0 0.5 1 1.5 0<br />
0 0.5 1 1.5<br />
0.5<br />
50<br />
50<br />
50<br />
25<br />
10<br />
20<br />
0.2<br />
Drift time (μs)<br />
Figure 4.18: Average pulse height as a function of time for the different readout chambers (rows) and for<br />
different spill lengths (columns, from left to right corresponding to 2, 1, 0.5 and 0.2 s extraction time).<br />
shown in Fig. 4.22. One can see a rate effect: with increasing rate the width is increasing. It is not<br />
easy to quantify to which extent this broa<strong>de</strong>ning is an effect of rate (due to build up of space charge)<br />
or of pile-up. It is clear that a broa<strong>de</strong>ning of the charge distribution would lead to a <strong>de</strong>gradation in<br />
electron/pion i<strong>de</strong>ntification performance. After this broa<strong>de</strong>ning is thoroughly established, its influence<br />
on the i<strong>de</strong>ntification power can be quantitatively assessed via simulations. This work is un<strong>de</strong>r way.<br />
The effects of constant or slight increasing average signal and of the broa<strong>de</strong>ning charge distributions<br />
with increasing rate seen in the data are probably effects of event pile-up. This effect can be reduced<br />
with tighter cuts for the event selection and is also foreseen to be improved in future measurements by<br />
changes at the trigger level. Also, a preamplifier/shaper with a shorter shaping time will be used in the<br />
future.<br />
Another important aspect is the rate <strong>de</strong>pen<strong>de</strong>nce of the position resolution. The position is reconstructed<br />
in our chambers via charge sharing among adjacent pads. The pad response function (PRF) is a measure<br />
of charge sharing. The PRF measured in the beam is presented in Fig. 4.23 for 2 and 4 mm ano<strong>de</strong> wire<br />
pitch. Shown is the ratio of the charge (integrated over a gate of 0.6 µs around the signal maximum)<br />
on the central pad to the sum of the charges on the central pad and the adjacent pads as function of the<br />
position of the hit. This position was <strong>de</strong>termined with the Si-strip <strong>de</strong>tectors.<br />
The rate <strong>de</strong>pen<strong>de</strong>nce of position resolution performance is presented in Fig. 4.24, <strong>de</strong>rived from the two<br />
<strong>GSI</strong>1<br />
<strong>GSI</strong>2<br />
Buc<br />
Dub<br />
GEM
4.2. An MWPC-based TRD 97<br />
6 tb Integral<br />
300<br />
250<br />
200<br />
150<br />
100<br />
50<br />
6 tb Integral<br />
Ch1<br />
Entries 40110<br />
Mean 762.6<br />
RMS<br />
2<br />
χ / ndf<br />
Constant<br />
816.7<br />
1156 / 1077<br />
1680 ± 13.3<br />
MPV 329.6 ± 1.4<br />
Sigma 118.7 ± 0.8<br />
0<br />
0 1000 2000 3000 4000 5000<br />
300<br />
250<br />
200<br />
150<br />
100<br />
50<br />
6 tb Integral<br />
Ch2<br />
Entries 41963<br />
Mean 846.1<br />
RMS 852.6<br />
2<br />
χ / ndf<br />
1189 / 1100<br />
Constant 1564 ± 11.9<br />
MPV 384.6 ± 1.5<br />
Sigma 133.5 ± 0.8<br />
0<br />
0 1000 2000 3000 4000 5000<br />
400<br />
350<br />
300<br />
250<br />
200<br />
150<br />
100<br />
50<br />
Ch3<br />
Entries 42759<br />
Mean 657<br />
RMS<br />
2<br />
χ / ndf<br />
791<br />
1020 / 1074<br />
Constant 2117 ± 16.4<br />
MPV 256.4 ± 1.2<br />
Sigma 101.7 ± 0.7<br />
0<br />
0 1000 2000 3000 4000 5000<br />
Figure 4.19: Total energy <strong>de</strong>posited in the chambers. Left panels, top to bottom: <strong>GSI</strong>1, <strong>GSI</strong>2, and Bucharest<br />
chambers. Right panels: MWPC and GEM chambers from Dubna. The lines are Landau fits.<br />
Figure 4.20: Rate <strong>de</strong>pen<strong>de</strong>nce of the average signal for the MWPC (left panel) and GEM (right panel) <strong>de</strong>tectors<br />
built in Dubna.<br />
<strong>GSI</strong> chambers data (assuming that both have the same resolution). Resolutions of 300 µm are achieved<br />
at low rates, although the geometry of the present <strong>de</strong>tector was not optimized for position resolution.<br />
A steady <strong>de</strong>gradation of the resolution is observed for higher rates, amounting to about 30 µm at 100<br />
kHz/cm 2 , which is rather tolerable.<br />
In summary, the first exploratory beam measurements at high rates indicate that the required performance<br />
for the CBM TRD can be achieved with MWPCs with pad readout. More quantitative statements will be<br />
<strong>de</strong>rived from further analysis of the existing data, as well as from new measurements, which we foresee
98 Transition Radiation <strong>de</strong>tector (TRD)<br />
0<br />
G/G<br />
1.04<br />
1.02<br />
1<br />
0.98<br />
0.96<br />
0.94<br />
0.92<br />
0.9<br />
0.88<br />
Data:<br />
MPV extracted<br />
from landau fits<br />
G (2000V) = 11300<br />
0<br />
G (1550V) = 7470<br />
0<br />
Data, <strong>GSI</strong> 1, 2mm pitch<br />
Data, <strong>GSI</strong> 2, 4mm pitch<br />
Simulation, 2mm pitch<br />
Simulation, 4mm pitch<br />
10 4<br />
10 5<br />
10<br />
2<br />
6<br />
rate [Hz/cm ]<br />
Figure 4.21: Most probable value of total <strong>de</strong>posited<br />
energy as a function of rate for the two <strong>GSI</strong> chambers.<br />
The lines are simulations.<br />
Charge ratio<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
σ = 3.51 mm<br />
exp<br />
2 mm pitch<br />
−8 −6 −4 −2 0 2 4 6 8<br />
Position (mm)<br />
Charge ratio<br />
Width, σ (%)<br />
150<br />
140<br />
130<br />
120<br />
110<br />
100<br />
90<br />
80<br />
70<br />
10 4<br />
<strong>GSI</strong>1<br />
<strong>GSI</strong>2<br />
Bucharest<br />
10 5<br />
Rate (Hz/cm 2 )<br />
Figure 4.22: Width of the total <strong>de</strong>posited energy spectrum<br />
as a function of rate.<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
σ = 3.66 mm<br />
exp<br />
4 mm pitch<br />
−8 −6 −4 −2 0 2 4 6 8<br />
Position (mm)<br />
Figure 4.23: Pad response function for the <strong>GSI</strong> chambers with 2 and 4 mm ano<strong>de</strong> pitch.<br />
to realize in the course of the next years, both with beams and with x-ray generators. Nevertheless, we<br />
can conclu<strong>de</strong> at this moment that the <strong>de</strong>tector configurations which we have investigated are suited for<br />
usage in the CBM TRD.<br />
4.2.3 Gas system<br />
The TRD uses xenon as the main counting gas. Excluding organic quenchers due to their flammability<br />
and CF4 due to its potential aging risk, the quencher has to be carbon dioxy<strong>de</strong>. The CO2 concentration
4.2. An MWPC-based TRD 99<br />
Resolution (μm)<br />
450<br />
400<br />
350<br />
300<br />
250<br />
10 4<br />
10 5<br />
Rate (Hz/cm 2 )<br />
Figure 4.24: Position resolution as a function of rate for the <strong>GSI</strong> chambers.<br />
may be chosen over a range between 10 % and 30 %, <strong>de</strong>pending on performance issues. The choice of<br />
a high price (5 /l) and high <strong>de</strong>nsity (5.58 kg/m 3 ) noble gas <strong>de</strong>termines the <strong>de</strong>sign of the gas circulation<br />
system, in particular for use with large size and thin multi-wire proportional chambers (MWPC). Assuming<br />
a segmentation of each <strong>de</strong>tector plane into four quadrants, the largest chambers would be 2.3 m<br />
long. The total <strong>de</strong>tector volume adds up to 3 m 3 . The main implications of these numbers are that: i)<br />
The full system must be as gas-tight as possible, in or<strong>de</strong>r to limit the cost of gas lost through leaks. A<br />
reasonable leak rate during operation is 10 % of the total <strong>de</strong>tector volume per year. ii) The pressure at<br />
the <strong>de</strong>tectors must be accurately regulated at a value only slightly above the ambient pressure, in or<strong>de</strong>r to<br />
limit the <strong>de</strong>formation of the chamber enclosing catho<strong>de</strong>s and thus keeping the gas thickness and gas gain<br />
as uniform as possible over the entire active area. With nowadays instruments, overpressures of 1 mbar,<br />
with an accuracy better than 0.1 mbar, are routinely achieved.<br />
The proposed gas system for a 3-station MWPC-based TRD is schematically shown in Fig. 4.25. It is<br />
a closed-loop circulation system. Initially, the <strong>de</strong>tectors are flushed with CO2 from the gas supply until<br />
all air is vented away. At this point, xenon injection starts, and the returning gas is passed through a<br />
membrane separator which keeps the xenon in the loop but lets the CO2 diffuse through its walls. In<br />
this way, the amount of xenon lost for the filling of the <strong>de</strong>tector is limited to the small loss through the<br />
membrane. Once the <strong>de</strong>sired gas composition is reached, the system is switched to run mo<strong>de</strong>. In or<strong>de</strong>r<br />
to save gas, fresh gas injection could be activated only to compensate for the gas lost through leaks. This<br />
is automatically done by measuring the pressure at the high pressure buffer, after the compressor, since<br />
the amount of gas in the rest of the system is kept constant.<br />
The <strong>de</strong>tector pressure regulation is done in two steps: a pressure sensor located at the outlet of each<br />
station -or height level- ensures that the <strong>de</strong>tector overpressure is kept at the <strong>de</strong>sired value by regulating<br />
the flow through the chambers. A second pressure sensor located at the compressor module regulates<br />
the total flow through the compressor. The gas is continuously filtered through a copper catalyst which<br />
removes O2 and H2O, and the gas quality is monitored with appropriate analysis instruments. The filters
100 Transition Radiation <strong>de</strong>tector (TRD)<br />
Gas Room Near Cave Cave<br />
Exhaust<br />
(N )<br />
2<br />
Xe recovery<br />
Exhaust<br />
(CO )<br />
2<br />
Gas<br />
Supply<br />
Cryogenic<br />
Xe Plant<br />
Membrane<br />
Separator<br />
Filling/Purging<br />
Purifier<br />
Mixer<br />
Run<br />
Circu<br />
lation<br />
Buffer<br />
Distribution<br />
Module<br />
Analysis<br />
Compressor<br />
Module<br />
Figure 4.25: Layout of the gas system.<br />
Detectors<br />
themselves need eventually to be regenerated with a flammable (Ar-H2) mixture at 200 ◦ C. This module<br />
is therefore installed in the gas room. In this approach, N2, not removed by any filter, slowly builds up in<br />
the mixture during each running period. It has been shown, however, that concentrations of or<strong>de</strong>r 10%<br />
of N2 in a Xe-CO2 mixture are tolerable, since the impact on the gas gain is small [98].<br />
The precious xenon may eventually be recovered at the end of each run. To do so, CO2-free gas is dumped<br />
into a cryogenic plant where the xenon is frozen and the remaining gaseous N2 is evacuated. The clean<br />
noble gas is thereafter pumped into the primary supply vessels, ready to be used the next running period.<br />
The system is PLC-controlled. A user interface provi<strong>de</strong>s access to monitoring information and activation<br />
of operating mo<strong>de</strong>s. A suitable package enables the interfacing to the general Detector Control System<br />
of the experiment. A set of alarms and interlocks can stop the gas system, and other systems such as high<br />
voltage, in case unsafe pressure or gas conditions are <strong>de</strong>tected.<br />
4.2.4 Readout electronics<br />
The <strong>de</strong>tector signals of the MWPC-based TRD are amplified by a preamplifier/shaper (PASA). The total<br />
number of channels is above half a million, <strong>de</strong>pending on the number of layers consi<strong>de</strong>red. It is obvious<br />
that, for such a high number of channels, reasonable costs for front-end electronics (FEE) can be achieved<br />
only through custom ASIC <strong>de</strong>velopments. Research and <strong>de</strong>velopment for the PASA of the TRD has two<br />
challenges: i) low noise with short shaping time and high pulse rate. ii) low power consumption and small<br />
chip size. The two issues are <strong>de</strong>coupled. First, one can check with a prototype that the requirements can<br />
be fulfilled using standard technology (0.35 µm) and that tests with prototype chambers give the expected<br />
physics performance. In a second step one needs to <strong>de</strong>velop a completely new prototype in state-of-theart<br />
technology with close to final specifications (for example 0.18 or 0.13 µm). The basic requirements<br />
for a PASA chip suitable for the CBM TRD are given in Table 4.1.<br />
In or<strong>de</strong>r to achieve an overall noise of less than 1000 electrons per channel for a typical input capacitance<br />
of 15-35 pF, the use of a low-noise circuit is required. A well proven topology to fulfill such a requirement<br />
is shown in Fig. 4.26.<br />
Each channel consists of a low noise charge-sensitive amplifier and an active CR-RC pulse shaper and<br />
a source follower buffer that can handle both polarities. The main noise contributor in this scheme is<br />
the input transistor of the preamplifier that is based on a fol<strong>de</strong>d casco<strong>de</strong> topology. The casco<strong>de</strong> consists<br />
P<br />
P<br />
P
4.2. An MWPC-based TRD 101<br />
Parameter specification simulated<br />
Noise rms (Cinp=35 pF) 1000e 850 e<br />
Shaping time 70 ns 75 ns<br />
Gain 10mV/fC 40 mV/fC<br />
Table 4.1: The requirements for the preamplifier/shaper chip for the TRD.<br />
Adaptiv−bias<br />
From Detector<br />
Cd<br />
MF<br />
Preamplifier<br />
MPZ<br />
Cf Vref<br />
C2<br />
CPZ<br />
Preamplifier Vref1<br />
R<br />
R1 R2<br />
Amplifier<br />
Non−Inverting stage<br />
Figure 4.26: Schematics of the fast PASA done in 0.35µm technology<br />
of a common-source stage followed by a common-gate stage. It combines two transistors (a wi<strong>de</strong> input<br />
transistor and a narrower casco<strong>de</strong> transistor) to obtain: i) high transconductance and low noise of a<br />
wi<strong>de</strong> transistor, ii) high output resistance and low output capacitance of a narrow transistor, and iii)<br />
reduced capacitance between output and input. In addition, a pole-zero network is inclu<strong>de</strong>d to avoid the<br />
un<strong>de</strong>rshoot which strongly limits the counting rate behavior. In case of a second pulse arriving during<br />
the period of un<strong>de</strong>rshoot, it will be superimposed on the un<strong>de</strong>rshoot and an error will be introduced in<br />
the pulse amplitu<strong>de</strong>. In the <strong>de</strong>sign, a MOS transistor (MF) is used with a feedback capacitor C f that<br />
is continously discharged with a <strong>de</strong>cay time td = D f *Rds(MF). This continuously sensitive <strong>de</strong>sign is<br />
particularly suitable for a <strong>de</strong>tector with high occupancy and high counting rate. In or<strong>de</strong>r to increase<br />
the gain and shape of the signal a shaper is built around a Miller OTA (Operational Transconductance<br />
Amplifier). By means of the external reference voltage Vre f , this part has in addition the capability of<br />
maximizing the dynamic range for a given polarity. The reference voltage is set closer to the positive<br />
rail such that the output swings towards the negative rail for positive input charges. For negative input<br />
charges the reference voltage is set closer to the negative rail such that its output swings toward the<br />
positive rail.<br />
A first prototype using this <strong>de</strong>sign was submitted in October 2004 and has just been received back from<br />
the foundry. First tests have already been un<strong>de</strong>rtaken. Since the <strong>de</strong>sign was targeted for a slightly<br />
different type of <strong>de</strong>tector the conversion gain is slightly higher (40mV/fC) in this prototype version<br />
compared to the requirements for the TRD. This can easily be lowered by adding a resistor of suitable<br />
size in series to the external reference voltage Vre f .<br />
In this first prototype the peaking time is 30 ns (t0/100), and the FWHM is about 75 ns. It returns to<br />
the baseline after 270 ns. In terms of noise this circuit fulfills the requirement with the ENC being less<br />
than 850 electrons for an input capacitance of 35 pF. In terms of power consumption the circuit uses<br />
8.5 mW/channel. The chip is fabricated in 0.35 µm standard CMOS technology, and has a pad pitch of<br />
50 µm.<br />
The next step in the analog front-end electronics <strong>de</strong>velopment will be to migrate from 0.35 µm technology<br />
to a smaller technology. This should yield a reduction in power consumption. A prototype <strong>de</strong>velopment<br />
of a new circuit in 0.13 µm IBM technology is already un<strong>de</strong>r way. The proposed schematic layout is<br />
Vout
102 Transition Radiation <strong>de</strong>tector (TRD)<br />
shown in Fig. 4.27.<br />
Adaptiv−bias<br />
From Detector<br />
Selectable gain<br />
Preamplifier<br />
Select Select<br />
Select<br />
Select<br />
Pole−Zero<br />
Network<br />
Adaptiv−bias<br />
Selectable shaping<br />
and gain stage<br />
n−th−Or<strong>de</strong>r filter<br />
Amplifier<br />
Figure 4.27: Schematics of the fast PASA un<strong>de</strong>r <strong>de</strong>velopment in 0.13µm technology.<br />
This circuit consists of a low-noise selectable-gain preamplifier circuit that can handle both polarities.<br />
The choice of a gain range in the preamplifier is ma<strong>de</strong> by switching the relevant range capacitors. The<br />
reason of choosing a selectable gain preamplifier is to provi<strong>de</strong> a versatile preamplifier potentially suitable<br />
for several of the proposed CBM <strong>de</strong>tectors (RICH, ECAL and TRD). The core preamplifier is again based<br />
on the same topology as used in ALICE-TPC/TRD. The change in <strong>de</strong>cay time (due to changes in the gain<br />
range) also influences the pole-zero network, which has to change to preserve the same relation to avoid<br />
un<strong>de</strong>rshoot. The shaper/gain circuit is also ma<strong>de</strong> selectable. The purpose of the selectable shaper/gain<br />
circuit is to amplify the input signal to match the full scale voltage of the ADC ensuring that maximum<br />
signal resolution is achieved. Several programmable shaper/gain topologies are un<strong>de</strong>r investigation to<br />
i<strong>de</strong>ntify the best candidate for the proposed <strong>de</strong>tectors.<br />
4.2.5 Design consi<strong>de</strong>rations, mechanics, and material budget<br />
Our simulations have <strong>de</strong>monstrated that the required pion rejection factor of 100 can be achieved with a<br />
TRD of 9 to 12 layers, <strong>de</strong>pending on the radiator thickness, for a <strong>de</strong>tector thickness of 6 mm. The final<br />
configuration concerning the radiator thickness, number of layers and their spatial separation, will be<br />
chosen according to the required position resolution, which will be <strong>de</strong>rived from simulations, based on<br />
tracking/matching performance. The choice to use either a regular or an irregular radiator (a combination<br />
of the two is also conceivable) is left open for the moment. Another important parameter contributing to<br />
electron i<strong>de</strong>ntification is obviously the active <strong>de</strong>tector gas thickness. Constraints on this will be <strong>de</strong>rived<br />
from high rate studies as well as from measurements on position resolution performance.<br />
Element Material X/X0[%]<br />
radiator foils(fibres)/gas 0.20-0.50<br />
entrance foil/stiffener alluminized kapton 0.06<br />
drift chamber gas Xe/CO2 0.04<br />
pad plane G10/Cu 0.15<br />
readout motherboards G10/Cu 0.90<br />
1 TRD layer 1.35-1.65<br />
Table 4.2: Material budget of one TRD module. Only components contributing within the <strong>de</strong>tector’s active area<br />
are listed.<br />
In Table 4.2 we summarize the radiation length of all components in the active area of the <strong>de</strong>tector for<br />
Vout
4.3. A straw-based TRD 103<br />
one layer. Given the above arguments, for the radiator we have <strong>de</strong>fined a range of values. Note that,<br />
for the entrance foil, the reinforcement required to keep it flat is inclu<strong>de</strong>d in its material budget. For<br />
the readout chamber gas, Xe,CO2 with a total thickness of 6 mm has been consi<strong>de</strong>red. The pad plane is<br />
inclu<strong>de</strong>d in the calculation with a thickness of 250 µm and a copper coating of 5 µm. We have consi<strong>de</strong>red<br />
a readout motherboard of 800 µm thickness and with 6 layers of copper of 17 µm thickness, with Cu<br />
coverage of 50% per layer. For the whole TRD, the total radiation length in the active area will be of<br />
the or<strong>de</strong>r of 15%. The material budget of the <strong>de</strong>tector frames (which can amount up to about 10% of the<br />
active area) and its effect on the production of secondary particles has not been estimated yet. It is clear<br />
that, in or<strong>de</strong>r to minimize the background due to secondaries, the chamber frames have to be positioned<br />
in a projective geometry.<br />
Concerning the sizes of the individual chambers, it is too early to make final statements. We know from<br />
experience with the ALICE TRD production that chambers with sizes up to 1.2×1.6 m 2 can be built with<br />
the uniformity of the wire-catho<strong>de</strong> distance better than 100 µm. In fact, all the infrastructure to build such<br />
chambers can be inherited from the four production sites of the ALICE TRD. At this stage we can also<br />
not <strong>de</strong>ci<strong>de</strong> whether the <strong>de</strong>tector modules within a layer will be positioned in a vertical plane or will have<br />
angles to favor normal inci<strong>de</strong>nce of the tracks. Position resolution studies will be performed in or<strong>de</strong>r to<br />
answer this question.<br />
Also relying on position resolution performance, in particular on tracking through the TRD, is the question<br />
of stereo angles for the pad direction in successive layers. Since the readout pads will have to be<br />
rather long, good position resolution is obtained within one layer only in one coordinate (wire direction).<br />
Optimizations on the stereo angle will be performed to ensure the best tracking performance of the TRD.<br />
4.2.6 Costs<br />
The cost estimate can only be done at this stage using a scaling procedure with respect to other similar<br />
<strong>de</strong>tectors. A case in point is the ALICE TRD [86], which we have used to estimate the costs of the<br />
TRD in CBM. However, due to unknown choice of implementation (both for radiator and <strong>de</strong>tectors,<br />
for example), as well as due to not obvious extrapolations for the FEE costs, we are giving ranges of<br />
expected costs, see Table 4.3. Part of the uncertainty on the number of layers nee<strong>de</strong>d is inclu<strong>de</strong>d in the<br />
given cost ranges. If nee<strong>de</strong>d, we keep the option to compromise on occupancy and build more layers<br />
within the same budget. The values in Table 4.3 inclu<strong>de</strong> the costs of R&D activities.<br />
Item Cost (k)<br />
Radiator 200-700<br />
Readout chambers 2000-2600<br />
FEE 3100-3600<br />
Services (HV/LV, cooling) 1200-1500<br />
Gas system 400-500<br />
Support frames 800-1000<br />
Total 7900-9900<br />
4.3 A straw-based TRD<br />
Table 4.3: The costs of the main components of the MWPC-based TRD.<br />
A possible alternative to the MWPC-based TRD is a TRD based on straw tubes. Such a Transition<br />
Radiation Tracker (TRT) was proposed many years ago for colli<strong>de</strong>r experiments [103] and is now built
104 Transition Radiation <strong>de</strong>tector (TRD)<br />
for the ATLAS experiment at LHC [104]. Straws were chosen as a <strong>de</strong>tecting element as they provi<strong>de</strong><br />
a high modularity for the <strong>de</strong>tector in areas with different irradiations levels. Due to the fixed target<br />
geometry the angular distribution of particles is peaked at small angles, hence the segmentation with<br />
very different readout chamber sizes is required. For example, at a distance of 4 m from the target, we<br />
expect particle rates of about 100 kHz/cm 2 at small angles for 10 MHz minimum bias Au+Au collisions<br />
at 25 AGeV. The technical task is to <strong>de</strong>velop for such rates a <strong>de</strong>tector for track reconstruction with a<br />
resolution better than 200 µm, and efficient pion rejection by more than two or<strong>de</strong>rs of magnitu<strong>de</strong>.<br />
4.3.1 Monte Carlo simulation<br />
A stand-alone Monte Carlo simulation program has been used to estimate the rejection power of the<br />
proposed TRT <strong>de</strong>tector and to optimize the <strong>de</strong>tector parameters. The program was primarily <strong>de</strong>veloped<br />
for the ATLAS TRT and is based on Transition Radiation (TR) simulation in the so called field transport<br />
approach [105], on dE/dx energy loss simulation using PAI [106] mo<strong>de</strong>l, and on GEANT3 [107] for<br />
geometry <strong>de</strong>scription and transport of particles. The mo<strong>de</strong>l has been carefully checked by comparison to<br />
ATLAS test beam data, and has shown an agreement within a few percent accuracy for different particles,<br />
energies, <strong>de</strong>tector parameters and working conditions [108]. Even such a tiny effect as the TR production<br />
on the straw walls can be <strong>de</strong>scribed by the mo<strong>de</strong>l.<br />
For simulations it is supposed that a TRT module (Fig. 4.28) consists of six i<strong>de</strong>ntical layers with radiator<br />
foils and adjacent straw tubes. Straws are shifted from layer to layer by the straw radius to minimize the<br />
fluctuations in the particle path in the straw gas at different impact points. A single straw is <strong>de</strong>scribed in<br />
this mo<strong>de</strong>l as a cylindrical volume of a Kapton tube filled with gas and a tungsten wire along the cylin<strong>de</strong>r<br />
axis. The radiator is <strong>de</strong>scribed as a set of regularly spaced polypropylene films.<br />
Radiators<br />
Straws<br />
Particle<br />
Figure 4.28: Schematic view of one TRT module.<br />
The whole TRT <strong>de</strong>tector consists of three modules. A primary single particle crosses all the 18 layers<br />
at normal inci<strong>de</strong>nt direction and with spread of position across the straw radius. The following <strong>de</strong>tector<br />
parameters have been fixed in the simulation:<br />
• straw wall: Kapton, thickness: 60 µm<br />
• ano<strong>de</strong> wire: tungsten, 30 µm in diameter<br />
• gas mixture: 70% Xe, 20% CF4 and 10% CO2 at atmospheric pressure<br />
• radiator: polypropylen<br />
The straw diameter, the total thickness of one radiator, the thickness of the radiator foil, and the distance<br />
between two foils were the subjects to optimization. Fig. 4.29 shows the energy loss spectra for pions and
4.3. A straw-based TRD 105<br />
electrons in a single straw. The energy <strong>de</strong>position of electrons clearly exhibits an additional contribution<br />
due to the absorbed TR photons. The pion spectra are i<strong>de</strong>ntical for all straws. The electron spectra<br />
are slightly varying in different layers due to the TR accumulation along the particle path: TR photons,<br />
generated in the first radiator, not obligatory to be absorbed in a straw of the first layer, but can pass<br />
through and be absorbed in the second straw layer or even later. For the consi<strong>de</strong>red <strong>de</strong>tector configuration<br />
the mean energy loss in a single straw is ≈2.2 keV for pions and 5.3-6.9 keV for electrons.<br />
3500<br />
3000<br />
2500<br />
2000<br />
1500<br />
1000<br />
500<br />
0<br />
0 10 20 30<br />
Energy loss in straw (keV)<br />
700<br />
600<br />
500<br />
400<br />
300<br />
200<br />
100<br />
0<br />
Pion and electron spectra<br />
Pion, first layer<br />
Electron, first layer<br />
0 10 20 30<br />
Energy loss in straw (keV)<br />
3500<br />
3000<br />
2500<br />
2000<br />
1500<br />
1000<br />
500<br />
Pion, sixth layer<br />
0<br />
0 10 20 30<br />
Energy loss in straw (keV)<br />
600<br />
500<br />
400<br />
300<br />
200<br />
100<br />
Electron, sixth layer<br />
0<br />
0 10 20 30<br />
Energy loss in straw (keV)<br />
Figure 4.29: Differential spectra of energy <strong>de</strong>position in a single straw for pions (top) and electrons (bottom).<br />
The histograms on the left si<strong>de</strong> correspond to the first straw layer, on the right – to the sixth layer. The result is<br />
obtained for 20 GeV primary particles, 4 mm straws, 2.6 cm radiator with 15 µm foils and 200 µm gap.<br />
The corresponding integrated spectra are shown in Fig. 4.30 for pions and electrons. One can see that<br />
the probability to exceed the threshold energy at 6-7 keV for electrons is approximately one or<strong>de</strong>r of<br />
magnitu<strong>de</strong> higher than for pions due to generated and absorbed TR photons along the electron track.<br />
The difference in energy loss provi<strong>de</strong>s the basis for pion/electron separation. For the proposed TRT <strong>de</strong>tector<br />
the cluster counting method is supposed to be used. Complementary methods such as likelihood<br />
and time-over-threshold [109] can also be consi<strong>de</strong>red. For optimization of TRT <strong>de</strong>tector parameters, the<br />
simulations have been done for many different combinations of straw diameter and radiator parameters.<br />
Fig. 4.31 shows the <strong>de</strong>pen<strong>de</strong>nce of pion efficiency on cluster energy threshold for 4 and 6 mm straws,<br />
2.6 cm radiator stack thickness, 15 µm foils and different gaps between foils. One can see that the rejection<br />
power (the inverse value of the pion efficiency) amounts to 1.4·10 3 for a single particle. The rejection<br />
power is practically in<strong>de</strong>pen<strong>de</strong>nt on spacing gap of 150-250 µm between radiator foils and slightly worse<br />
for 400 µm gap. Our calculations show that radiators with thicker foils provi<strong>de</strong> a slightly worse rejection<br />
capability compared to 15 µm. A better rejection performance can be achieved for thicker radiator stacks<br />
(i.e. larger number of foils), but at the cost of increasing <strong>de</strong>tector size and additional material. The<br />
amount of material in the TRT <strong>de</strong>tector should be kept as small as possible. The radiator configuration<br />
of 15 µm foils and 200-250 µm gaps seems to be in our case the preferable option. The thickness of one<br />
layer amounts to 2.5-3 cm. The optimal cluster energy threshold for 4 mm straws is around 6 keV.<br />
The expected rejection is better for 6 mm straws compared to 4 mm straws due to more efficient absorption<br />
of TR photons in the thicker straws. Due to the same reason the optimal cluster threshold for 6 mm<br />
straw is shifted to 8 keV compared to 6 keV for 4 mm straws. The pion efficiency does not <strong>de</strong>pend on<br />
radiator parameters, but the electron efficiency does: the 90% efficiency threshold is shifted. The elec-
106 Transition Radiation <strong>de</strong>tector (TRD)<br />
Probability to exceed energy<br />
1<br />
10 -1<br />
10 -2<br />
Pion and electron integral spectra<br />
0 2.5 5 7.5 10 12.5 15 17.5 20<br />
π<br />
electron<br />
Energy loss in straw (keV)<br />
Figure 4.30: Probability to exceed the threshold energy as a function of energy <strong>de</strong>position in a single straw for<br />
pions and electrons. Different lines for elctrons correspond to straws in different layers: the lower line – to the first<br />
layer, the upper one – to the sixth layer.<br />
Pion efficiency at 0.9 of electron<br />
10 -2<br />
10 -3<br />
5 GeV, 4 mm straw, 2.6 cm radiator, 15 µm foil<br />
3 4 5 6 7 8 9 10<br />
Threshold (keV)<br />
Pion efficiency at 0.9 of electron<br />
10 -2<br />
10 -3<br />
5 GeV, 6 mm straw, 2.6 cm radiator, 15µm foil<br />
10 -4<br />
3 4 5 6 7 8 9 10<br />
High threshold (keV)<br />
Figure 4.31: Depen<strong>de</strong>nce of pion efficiency at 0.9 of electron efficiency as a function of cluster threshold for<br />
different spacing gap between radiator foils for 4 mm (left panel) and 6 mm (right panel) straws.<br />
tron threshold <strong>de</strong>pends on the TR spectra which <strong>de</strong>pend on radiator parameters (radiator foil thickness,<br />
gap size, total radiator thickness and <strong>de</strong>tector thickness) in a very complex way. The choice of these<br />
parameters is subject to further optimization.<br />
The results above were obtained for 5 GeV primary particles. The <strong>de</strong>pen<strong>de</strong>nce of pion efficiency on<br />
primary particle energy is shown in Fig. 4.32. The best rejection factor is expected at 2-5 GeV – the<br />
energy of most of secondaries in nucleus-nucleus interaction. The <strong>de</strong>terioration in rejection at very low<br />
energy is expected due to small TR yield, and at higher energy – due to relativistic rise of dE/dx energy<br />
loss in the straw gas for pions.
4.3. A straw-based TRD 107<br />
Pion efficiency at 0.9 of electron<br />
10 -3<br />
Depen<strong>de</strong>nce on particle energy<br />
1 10<br />
Primary particle energy (GeV)<br />
Figure 4.32: Depen<strong>de</strong>nce of pion efficiency at 0.9 of electron efficiency as a function of primary particle energy.<br />
4 mm straws, 2.6 cm radiator with 15 µm foils and 200 µm gap.<br />
Fig. 4.33 shows how the TRT rejection <strong>de</strong>pends on <strong>de</strong>tector efficiency or, in other words, on the number<br />
of operational straws on the particle track. The <strong>de</strong>sirable rejection level can be achieved if straws are<br />
operational at least in 15-16 among 18 layers, i.e. the fraction of operational channels should be larger<br />
than 83-89%.<br />
Pion efficiency at 0.9 of electron<br />
10 -2<br />
Depen<strong>de</strong>nce on number of straws on track<br />
10 -3<br />
11 12 13 14 15 16 17 18 19<br />
Number of operational straws on track<br />
Figure 4.33: Depen<strong>de</strong>nce of pion efficiency at 0.9 of electron efficiency as a function of number of straws on the<br />
primary particle track. 20 GeV particle energy, 4 mm straws, 2.6 cm radiator with 15 µm foils and 200 µm gap.<br />
The main challenge for the TRT in the CBM both from the point of view of track reconstruction and<br />
of pion/electron separation is arising from multiparticle environment in real nucleus-nucleus interaction.<br />
Two pions crossing the same straw produce a twofold signal compared to a single pion and emulate a<br />
high energy cluster above the chosen threshold of 6-8 keV. Fig. 4.34 shows the rejection <strong>de</strong>pen<strong>de</strong>nce
108 Transition Radiation <strong>de</strong>tector (TRD)<br />
on the number of double hits on the particle track. The pion rejection <strong>de</strong>crease with increasing number<br />
of double hit straws. One possible solution to improve the particle i<strong>de</strong>ntification ability in the presence<br />
of close particle tracks (double pions and conversion) is to use additional intermediate threshold around<br />
2-3 keV [110]. Such a technique is un<strong>de</strong>r way. Hit ambiguities can also be reduced by the arrangement<br />
of straw layers un<strong>de</strong>r stereo angles.<br />
Pion efficiency at 0.9 of electron<br />
1<br />
10 -1<br />
10 -2<br />
10 -3<br />
Rejection for double hits<br />
0 2 4 6 8 10 12 14 16 18<br />
Number of straws with double hit<br />
Figure 4.34: Depen<strong>de</strong>nce of pion efficiency at 0.9 of electron efficiency as a function of number of straws with<br />
double hit. 20 GeV particle energy, 4 mm straws, 2.6 cm radiator with 15 µm foils and 200 µm gap.<br />
4.3.2 Design of a TRT for CBM<br />
The proposed Transition Radiation Tracker has the following hierarchical structure: <strong>de</strong>tector, module,<br />
submodule, chamber, straw layer, radiator layer. In or<strong>de</strong>r to achieve the necessary tracking performance<br />
it is currently anticipated to build three TRT modules. A module is a stack of three submodules. In the<br />
submodules the straws are arranged vertically and inclined un<strong>de</strong>r the stereo angles (0 ◦ ,+20 ◦ and -20 ◦ ).<br />
The submodules have the same active area as the <strong>de</strong>dicated module and they are segmented in the XYplane<br />
into several in<strong>de</strong>pen<strong>de</strong>nt chambers. The segmentation <strong>de</strong>pends on the distance to the beam axis<br />
and to the target. The size of each chamber is adapted to achieve a reasonable occupancy. The chambers<br />
are different in lateral size, but i<strong>de</strong>ntical in the <strong>de</strong>pth profile, which contains two sensitive straw planes<br />
and multi-layer radiator stacks in front of the tubes. The straws in the two layers of a chamber are shifted<br />
according to the each other perpendicular to the ano<strong>de</strong> wire by the radius of the straw (see Fig. 4.28). The<br />
modules are ranged at distances of 4 m, 6 m and 8 m behind the target. The thickness of an assembled<br />
submodule amounts to 20 cm and of the full assembled TRT module 60 cm. The horizontal (X) and<br />
vertical (Y) sensitive sizes amount to (5.8×3.9) m 2 , (8.7×5.8) m 2 and (11.6×7.7) m 2 , for 1-st, 2-nd and<br />
3-th module. The total number of straws and readout channels are given in the Table 4.4.<br />
In the center of each module are physical holes. The sizes of the holes and the beam pipe have to be<br />
chosen accordingly to <strong>de</strong>tect the charged particles with emission angles θ ≥50 mrad. The first module<br />
is located 4 m downstream from the target and should have maximal granularity. Each submodule of<br />
module-I consists of 20 chambers of five different types. The straws with 4 mm in diameter will be used<br />
for this chambers. The sensitive area of <strong>de</strong>tecting elements vary from 4 cm 2 to ≈32 cm 2 . To reduce the<br />
occupancy, glass joints will be integrated to interrupt the galvanic contact of the ano<strong>de</strong> wires in different<br />
chambers. Preliminary parameters of the straw chambers for the first module are given in Table 4.5 and
4.3. A straw-based TRD 109<br />
module straws <strong>de</strong>tecting total sensitive<br />
∅=4 mm ∅=6 mm channels area, m 2<br />
I 45 696 — 82 944 6×23<br />
II 24 288 21 504 91 584 6×50<br />
III — 67 968 113 280 6×90<br />
TRT-<strong>de</strong>tector ≈160 000 ≈300 000 ≈ 1000<br />
Table 4.4: Number of straws, channels and the common sensitive size of the TRT-modules.<br />
the arrangement of the chambers on the XY-plane is shown in Fig. 4.35. To accept particles emitted at<br />
θ ≥50 mrad the beam pipe diameter should not exceed 20 cm. Assuming an interaction rate of 10 MHz<br />
for minimum bias Au+Au collisions at 25 AGeV, the rate amounts to about 100 kHz cm −2 near the<br />
minimal opening angle, whereas the hit <strong>de</strong>nsity for central events is about 0.045/cm 2 .<br />
Figure 4.35: The arrangement of five different chambers in a submodule of TRT module-I. The dots show the<br />
location of the glass joints.<br />
chamber number of chamber size straws per channels per<br />
type chambers X, cm Y, cm module module<br />
I-1 12 162 25 9600 19200<br />
I-2 12 162/143 20/10 9600 19200<br />
I-3 12 162 130 9600 19200<br />
I-4 12 143 130 8448 16896<br />
I-5 12 143 60 8448 8448<br />
Table 4.5: Parameters of the five types of chambers of module-I.<br />
The second module is located 6 m downstream from the target. Each submodule consists of 7 chambers<br />
of four different types. Straws with 4 mm and 6 mm in diameter will be used. Preliminary parameters<br />
of the straw chambers for module-II are given in Table 4.6 and the arrangement of the chambers on the<br />
XY-plane is shown in Fig. 4.36. For θ ≥50 mrad the beam pipe diameter should not exceed 40 cm. In
110 Transition Radiation <strong>de</strong>tector (TRD)<br />
central Au+Au collisions at 25 AGeV the maximum hit <strong>de</strong>nsity seen by the second TRT module at small<br />
forward angles is 0.022/cm 2 .<br />
Figure 4.36: The arrangement of the four types of straw chambers in a submodule of module-II.<br />
chamber number of straws chamber size straws per channels per<br />
type chambers ∅, mm X, cm Y, cm module module<br />
II-1a 12 4 165 95 8880 17760<br />
II-1b 12 4 165/150 45/22 8880 17760<br />
II-2 12 6 165 150 6528 13056<br />
II-3 48 6 136 150 21504 43008<br />
Table 4.6: Parameters of the four straw chamber types of module-II.<br />
The third module is located 8 m downstream from the target. Each submodule consists of 15 chambers of<br />
five different types. Only straws with 6 mm in diameter will be used. The preliminary parameters of the<br />
straw chambers for module-III are given in Table 4.7 and the allocation of the chambers on the XY-plane<br />
is shown in Fig. 4.37. In module-III the chambers 1,2 and 3 are arranged symmetric to the vertical axis<br />
normal to the beam line. The beam pipe diameter should not exceed 60 cm. In central Au+Au collisions<br />
at 25 AGeV the maximum hit <strong>de</strong>nsity seen by the third TRT module at small forward angles is 0.014/cm 2 .<br />
Figure 4.37: The arrangement of the five chamber types in submodule of module-III.
4.3. A straw-based TRD 111<br />
4.3.3 Detector elements<br />
4.3.3.1 Straws<br />
chamber number of chamber size straws per channels per<br />
type chambers X, cm Y, cm module module<br />
III-1 6 58 117 1152 2304<br />
III-2 6 58 150 1152 2304<br />
III-3 6 58 75 1152 1152<br />
III-4 96 136 150 43008 86016<br />
III-5 48 136 75 21504 21504<br />
Table 4.7: Parameters of the five types of chambers of TRT module-III.<br />
The straw tubes are ma<strong>de</strong> of two layers of polyimi<strong>de</strong> film. The Kapton film 160XC with graphite loading<br />
is used for the inner layer and the Kapton film 100VN is used for the outer skin of the straw tube.<br />
The inner surface of the 100VN film is aluminized with a thin layer of about 0.2 µm thickness. The<br />
summarized specifications is given in Table 4.8.<br />
<strong>de</strong>scription specifications<br />
Kapton film polyimi<strong>de</strong> type 100VN polyimi<strong>de</strong> type 160XC / 275XC /other<br />
<strong>de</strong>nsity 1.42 g/cm 3 1.41 g/cm 3<br />
aluminium layer (0.20±0.08) µm —<br />
film layer (25±2) µm (25±2) µm<br />
film resistivity
112 Transition Radiation <strong>de</strong>tector (TRD)<br />
4.3.3.2 Straw internal elements<br />
The gold-plated tungsten wire type 861 (Luma) – 30 µm in diameter – will be used for the ano<strong>de</strong>s. The<br />
tension of the wire is 0.7 N. Polycarbonate end-plugs ma<strong>de</strong> by the method of pressure moulding are used<br />
to fix the wires at the straw ends. These elements are inserted into the straw against their stop. This exclu<strong>de</strong>s<br />
their displacement later on. There are grooves on the outsi<strong>de</strong> surface of the end-plugs to connect<br />
the internal straw volume to that common to all the straws; this gas manifold is used for their blow-down.<br />
There is also a gutter to install a contact spring which allows one to connect the catho<strong>de</strong> to the common<br />
ground of the chamber. The wire goes through Cu pins inserted in the end-plugs. The inner diameter of<br />
the tube is 100 µm and the outer one is 700 µm. The top pin is then crimped, the wire is tensioned and the<br />
bottom pin is finally crimped. To increase the straw rate capability, the ano<strong>de</strong> of a straw can be divi<strong>de</strong>d<br />
into two in<strong>de</strong>pen<strong>de</strong>nt <strong>de</strong>tecting elements. Glass capillary tubes with parameters given in Table 4.10 will<br />
be used for the glass-joints as shown in Fig. 4.38.<br />
parameter specification<br />
outer diameter 0.25 mm<br />
inner diameter 0.1 mm<br />
weight 0.19 mg/pc<br />
length 4, 5 or 6 mm<br />
Table 4.10: The main parameters of the glass-joints.<br />
Figure 4.38: Schematic view of a glass-joint. The glass-joint holds and insulate two ends of an interrupted ano<strong>de</strong><br />
wire.<br />
To compensate the sagitta of the wires, one spacer per 80 cm length of the ano<strong>de</strong> wire will be used.<br />
These spacers with a central hole of 100 µm in diameter also ma<strong>de</strong> of polycarbonate by the method of<br />
pressure moulding. The dimensions and mass of the spacers are minimized, e.g. a prototype for straws<br />
of ∅=6.00 mm has a diameter of 5.97(+0 -0.018) mm and the mass of one spacer amounts to 15 mg. The<br />
spacers are pasted on the ano<strong>de</strong> wires with epoxy glue before mounting the wires in the straws.<br />
4.3.3.3 Radiators<br />
Each radiator layer is a stack of 140 polypropylene foils of 15 µm thickness. The foils are regularly<br />
spaced with gaps of 200 µm. The support mesh is placed between neighbouring films. The size of the<br />
mesh cells is about 7×7 mm 2 . Total radiator layer thickness is ≈3 cm. The radiator layer is suspen<strong>de</strong>d<br />
on springs in front of the straw layer and fixed to the inner wall of the frame. The radiation length of a<br />
radiator layer (140 foils×15 µm) amounts to X/X0=0.443%.<br />
4.3.3.4 Support frame and subframes<br />
To provi<strong>de</strong> an external protection and to make a monolithic double layer submodule, the chambers are<br />
mounted into a carbon structure support. A subframe is a part of a chamber. It contains two – orthogonal<br />
to the straws – carbon fiber bars and two – parallel to the straws – thin aluminium bars. The temperature<br />
changes leads either to the appearance of an effort, stretching the straws additionally, or to their curvature.
4.3. A straw-based TRD 113<br />
Aluminium bars minimize this effect because the expansion coefficients for Al and Kapton are quite close<br />
to each other (23.2·10 6 K −1 and 18·10 6 K −1 , respectively). Carbon bars have no temperature expansion<br />
and provi<strong>de</strong> a high long time stability of the chamber position in the frame structure. The accuracy of<br />
the chamber installation in the frame structure will be 50 µm. Each subframe contains gas manifolds and<br />
provi<strong>de</strong>s the fixation of the radiators, electronic boards etc.<br />
4.3.3.5 Material budget<br />
The TRT <strong>de</strong>tector should consists of low-Z materials. Lightweight construction will be used for the<br />
support frames. The use of metallic components should be minimized. The main materials and elements<br />
of the <strong>de</strong>tector are listed below in Table 4.11:<br />
element material size rad. length, %<br />
wire W(Au) ∅30µm 0.007<br />
joint glass ∅0.25 mm×5 mm 0.115<br />
straw tube Kapton 68µm 0.005<br />
glue — 0.003<br />
spacer — ∅6 mmx6 mm; 15 mg 0.1<br />
gas Xe(75%)/CO2(25%) ∅6 mm 0.046<br />
∅4 mm .032<br />
end-plug lexan ∅6 mm×10 mm; 250 mg 1.003<br />
∅4 mm×10 mm; 150 mg 0.903<br />
radiator polypropylen 140x15µm 0.875<br />
crimping tube Cu ∅.7 mm×7 mm<br />
Table 4.11: Size and radiation length of some elements of the straw chambers.<br />
The radiation length of the whole <strong>de</strong>tector amounts to X/X0≤15% if we assume one module with 4 mm<br />
straws and two modules with 6 mm straws. The frame contains additionally motherboards for ∅=4 mm<br />
straws – 0.52 cm 3 /channel and for ∅=6 mm straws – 0.78 cm 3 /channel. Table 4.12 shows the common<br />
length of the horizontal and vertical bars in the XY–plane. The construction is more complex in the<br />
horizontal direction as in the vertical one. The choice of bar material for the Y direction will be done after<br />
the <strong>de</strong>sign of the frame. The temperature coefficient, the radiation length and cost for both construction<br />
materials – Al and the carbon fiber – will be taken in account. Table 4.12 shows the amount of carbon<br />
fibers nee<strong>de</strong>d for the all TRT frames. Preliminary calculation of the carbon fiber amounts to 0.6 kg/m in<br />
X and 0.3 kg/m in Y-direction.<br />
module X Y<br />
length, m mass, kg length, m mass, kg<br />
I 384 65.9 197 39<br />
II 514 86.5 416 82.3<br />
III 880 151.2 864 171.1<br />
total 1778 303.6 1477 292.4<br />
Table 4.12: Amount of carbon fiber for the straw chamber frames in all three modules.
114 Transition Radiation <strong>de</strong>tector (TRD)<br />
4.3.4 Gas supply system<br />
The gas system is <strong>de</strong>signed to provi<strong>de</strong> the operation of all three TRT modules consisting of ≈160 000<br />
straws with total volume of ≈ 4.7 m 3 . The gas volumes in the different modules are shown in Table 4.13:<br />
module straw length, m gas volume<br />
∅=4 mm ∅=6 mm m 3<br />
I 37 422 — 0.5<br />
II 14 208 44 651 1.5<br />
III — 91 377 2.7<br />
total 51 630 136 028 ≈4.7<br />
Table 4.13: The gas volume of all straws.<br />
The operating conditions expected at the CBM experiment, and the specific characteristics of transition<br />
radiation <strong>de</strong>tectors for acceptable electron to pion separation of ≈10 −2 require the following gas<br />
properties:<br />
• The gas must be a Xe based mixture providing efficient X-ray absorption.<br />
• The gas must be as fast as possible to minimize pile-up effect.<br />
• The gas must guarantee stable operation of the straws in a sufficient high-voltage range and for<br />
very high fluxes of particles crossing the straws.<br />
Taking into account the experience of ATLAS TRT [111] which showed an essential ageing of straws in<br />
gas mixture (Xe/CO2/CF4) we propose to use gas mixture Xe(75%) + CO2(25%), which shows stable<br />
operation of the straws at high counting rates up to 18 MHz. The variation of percentage rates of gas<br />
components within 1% is acceptable. Each chamber contains two straw layers and consequently two<br />
in<strong>de</strong>pen<strong>de</strong>nd gas units. The total number of gas units for TRT <strong>de</strong>tector amounts to 612 with a volume<br />
of 4.7 m 3 . The gas leakage level is less than 1 mbar/min/bar. Assuming an overpressure of 20 mbar the<br />
gas leak for the whole TRT <strong>de</strong>tector amounts to ≈0.2 m 3 /day. The minimal gas flux (similar required at<br />
LHC) is 0.058 m 3 /min or 83 m 3 /day for all three modules. The gas flow through module-I is 12.2 m 3 /day.<br />
In all cases the large volume of expensive Xe gas is required for long time of the operation. Therefore the<br />
proposed gas system should provi<strong>de</strong> recirculation of gas mixture and its purity. The primary purpose of<br />
the CBM TRD gas system (Fig. 4.39) is to provi<strong>de</strong> the gas mixture to the <strong>de</strong>tector segments at the correct<br />
pressure. Refer to Table 4.14 for a list of gas system parameters. The system operates nominally as a<br />
closed circuit gas system with the majority of mixture recirculating through the three modules connected<br />
in parallel [112]. During normal operation a small amount of fresh mixture is ad<strong>de</strong>d and an equivalent<br />
quantity of the existing mixture is vented to the buffer. The gas system can be operated in an open<br />
configuration for purging. The mixture circulation rate through the compressor is 150 l/min at 250 mbar.<br />
The gas system contains two compressors (Com1, Com2), one active and one spare. The mixture from<br />
the compressor goes to the supply line through the check valves (CV4 or CV5). The 250 mbar output<br />
pressure from the compressor is reduced to 50 mbar by the pressure regulator (PCV1) and supported with<br />
the back pressure control valve (BPCV1). Then 50 mbar pressure is reduced to 20 mbar supply pressure<br />
by the pressure regulator (PCV2). The return gas manifold is maintained at 2 mbar above atmospheric<br />
pressure by a differential pressure transmitter (PT1) and pneumatic PID controller (PIDC) that operates<br />
a bypass valve (BV1). The bypass shunts flow from the compressor discharge line directly back to<br />
the compressor’s inlet to support the return manifold pressure stable. A second bypass valve (MV3) is<br />
manually adjusted to enable the automatic control loop to be used within its optimum range.
4.3. A straw-based TRD 115<br />
Figure 4.39: General layout of circulation gas loop.<br />
The flow indicating transmitter FIT2 will measure the recirculating flow. The measurements of the fresh<br />
mixture (FM1, FM2 and FM3) and flow through the flow indicating transmitter (FIT1) give a possibility<br />
to estimate the <strong>de</strong>tector leakage. The purity and composition of recirculating mixture is monitored using<br />
oxygen, carbon dioxi<strong>de</strong> and humidity analyzers. A fraction of the recirculating mixture can be passed<br />
through a dryer to remove the moisture. Mixture coming out through the BPCV1 is collected with the<br />
buffer and then compressed by the high pressure compressor (HPC) to one of the cylin<strong>de</strong>rs (C1 or C2).<br />
The compressed mixture can be used as the part of make up mixture or for recovery of Xenon gas. A<br />
computer driven data acquisition and control systems monitor all of the process variables including the<br />
barometric pressure. The computer system flags quantities which fall outsi<strong>de</strong> of pre<strong>de</strong>fined limits and<br />
initiates corrective action. However, where the safety of equipment or personnel are affected, a relay<br />
based system connected to redundant set of sensors control the pressure levels of all key based controls<br />
fail. The vent lines, associated valves and bubbler are sized to allow rapid venting of the TRD segments<br />
mixture to prevent a high internal pressure in the case of the fast barometric pressure fall.<br />
mixture Xe(75%) + CO2(25%)<br />
compressors output pressure 250 mbar<br />
mixture supply pressure 20 mbar<br />
mixture return pressure 2 ± 0.05 mbar<br />
recirculation flow 80 - 150 l/min<br />
make-up mixture flow 0.2 - 5 l/min<br />
water content < 80 ppm<br />
gas leakage < 0.2 m 3 /day<br />
Table 4.14: Performance of the gas system.
116 Transition Radiation <strong>de</strong>tector (TRD)<br />
4.3.5 Detector readout<br />
Two types of the track position readout were consi<strong>de</strong>red: the ano<strong>de</strong> readout (based on the drift time<br />
registration) and the catho<strong>de</strong> readout (based on the amplitu<strong>de</strong>s of the pulses induced in the pads). Both<br />
of them have certain advantages and shortcomings. We have recognized the ano<strong>de</strong> readout as more<br />
advisable due to possibility of application of faster electronics (important for the high-rate properties of<br />
the system) and lower distortion of the position resolution due to angular effects.<br />
4.3.5.1 Behavior of the <strong>de</strong>tectors un<strong>de</strong>r high-rate conditions<br />
For minimum bias Au+Au collisions particle flux ranges from 0.25 kHz cm −2 (at the edge of module-III)<br />
to 100 kHz cm −2 (at the central part of module-I). For central Au+Au collisions, the hit <strong>de</strong>nsity amounts<br />
to 0.045 cm −2 for the inner part of the first TRT module.<br />
The drift cell size is <strong>de</strong>fined by the intersection of straws with different orientations (0 ◦ ,+20 ◦ and -20 ◦ ).<br />
The cross section area <strong>de</strong>fined by three straw tubes with 6 mm in diameter amounts to 0.4 cm 2 . Taking<br />
into account the shift of parallel straws by a half straw diameter and 4 mm tubes, than the size of a<br />
drift cell will be reduced by one or<strong>de</strong>r of magnitu<strong>de</strong> and amounts to ≈0.04 cm 2 ). Let us assume that<br />
the straws are 6 mm thick and the <strong>de</strong>tector is filled with the Xe/CO2 mixture. Maximum ano<strong>de</strong> current<br />
pulse duration (cluster charge collecting time) may be estimated as 70-80 ns. Then the duration of the<br />
pulse from the straw tube ano<strong>de</strong> (in the case of aggressive base line restoration) is about 100 ns (as in the<br />
ATLAS TRT). For central collisions the occupancy will increase to 4%. The stereo angle arrangement<br />
of the tubes gives the possibility to disentangle multihits in straws. According to table 4.5 the shortest<br />
ano<strong>de</strong> wires will have a length of 10 cm, corresponding to a single straw occupancy of 18% for the most<br />
forward angles. The performance of the TRT at high rates and for high multiplicities, in particular the<br />
pion suppression capability, is subject of further investigations.<br />
4.3.5.2 Spatial resolution<br />
The use of fast front-end electronics should provi<strong>de</strong> the necessary spatial resolution. There is no doubt<br />
that the assumed requirement of the 200 µm spatial resolution may be fulfilled by the straw drift tubes.<br />
An ano<strong>de</strong> signal provi<strong>de</strong>s the start of the time measurement. The stop is <strong>de</strong>duced from an external <strong>de</strong>tector,<br />
e.g. the <strong>de</strong>layed signal of a scintillator telescope or a RPC. The resulting arrival time of the drift<br />
electrons, after offset subtraction and calibration is converted into a distance from the sense wire. The<br />
drift-time measurement was performed with a TDC with bin width around 1 ns. Assuming a drift velocity<br />
smaller than 60µm/ns in the straws the coordinates can be obtained with an accuracy of better than<br />
200µm. Fig. 4.40 shows the results of the observed spatial resolution for a straw of 50 cm length and<br />
4 mm in diameter for a low rate (top) and for a high rate up to 18 MHz (bottom) [104] [113]. The particle<br />
track has been measured with an accuracy of 5µm using a Si-microstrip telescope as a master <strong>de</strong>tector.<br />
4.3.5.3 Front end electronics<br />
In the straw drift chambers the signal is being received from the <strong>de</strong>tector edges, not from the whole surface.<br />
Therefore there is no problem with the signal transmission from the ano<strong>de</strong> to the amplifier input.<br />
According to our experience from the <strong>de</strong>sign of the large area straw tracker for the COMPASS experiment,<br />
it is hard to achieve the satisfactorily low electromagnetic interference level when the analog and<br />
digital part of the electronics are placed on a common board. Therefore we would suggest to divi<strong>de</strong>
4.3. A straw-based TRD 117<br />
500<br />
400<br />
300<br />
200<br />
100<br />
0<br />
250<br />
200<br />
150<br />
100<br />
50<br />
0<br />
0 MHz<br />
σ = 128 μm<br />
ε = 86 %<br />
-1 -0.5 0 0.5 1<br />
Residual (mm)<br />
18 MHz<br />
σ = 183 μm<br />
ε = 54 %<br />
-1 -0.5 0 0.5 1<br />
Residual (mm)<br />
Figure 4.40: Spatial resolution obtained with straws by low (top) and high (bottom) particle flux [104] [113].<br />
the front end electronics into two separated parts: the first one would contain the Amplifier-Shaper-<br />
Discriminator circuits and it would be placed close to the straw tube endplugs and second one, contains<br />
TDCs, would be mounted on the frame. The signal transmission between the analog and digital part<br />
could be realized using twisted pair cables or optical fibers, <strong>de</strong>pending on the ground connections, power<br />
consumption, time jitter etc. This needs more thorough analysis. The analog part may be realized using<br />
the ASD-BLR integrated circuits, <strong>de</strong>signed for the ATLAS TRT. However, taking into account that<br />
the ASD circuit was <strong>de</strong>signed several years ago, we consi<strong>de</strong>r a <strong>de</strong>sign of the new integrated circuits as<br />
advisable. We are ready to un<strong>de</strong>rtake this task and <strong>de</strong>sign the chip having better parameters and based<br />
on mo<strong>de</strong>rn technologies (e.g. AMS 0.35 µm SiGe HBT). The <strong>de</strong>sign would be based on the project of<br />
the Amplifier-Shaper-Discriminator chip, which was prepared by the team from the Institute of Radioelectronics<br />
and specialists from the Institute of Microelectronics and Optoelectronics from the Warsaw<br />
University of Technology. The new chip was foreseen mainly as an up-to-date, improved replacement<br />
of the ASD family chips in the updated COMPASS experiment and other future high energy experiments.<br />
The project was suspen<strong>de</strong>d because of the lack of the financial support. However, the functional<br />
and electrical <strong>de</strong>sign of the chip was done, as well as simulations of the chip layout based on the AMS<br />
0.8 µm Bi-CMOS technology, which, unfortunately, becomes to be obsolete nowadays. In or<strong>de</strong>r to apply<br />
this <strong>de</strong>sign for the CBM TRT slight changes of the electrical scheme would be necessary, as well as a<br />
migration to newer technology, like AMS 0.35 µm SiGe HBT. For the digital part it would be necessary<br />
to <strong>de</strong>sign chips containing TDC and interface to the link, which connects the FEE with the higher levels<br />
of the data acquisition system.
118 Transition Radiation <strong>de</strong>tector (TRD)<br />
4.3.6 Costs<br />
Table 4.15 contain information about the costs for straw based TRT modules, gas supply and front-end<br />
electronics. The costs are preliminary and will be worked out in more <strong>de</strong>tail during the next steps of<br />
research and <strong>de</strong>velopment.<br />
4.4 Detector ageing<br />
item costs (k)<br />
straw tube <strong>de</strong>tectors 2000<br />
radiators 300<br />
support frames 1000<br />
gas system 300<br />
services(HV, LV, cooling) 2000<br />
FEE 3000<br />
total 8600<br />
Table 4.15: Preliminary cost of the main <strong>de</strong>tector components.<br />
To estimate the dose per year of operation for the TRD <strong>de</strong>tectors we use the multiplicities of charged<br />
particles calculated with the UrQMD mo<strong>de</strong>l [114, 115] for Au+Au events at 25 AGeV beam energy. We<br />
assume a reaction rate of 10 7 /s and an equivalent beam on target period of two months per year (5×10 6<br />
seconds).<br />
The rates, fluxes and doses for different polar emission angles are given in Table 4.16 for the three TRD<br />
stations. In the regions closer to the beam the integrated particle flux amounts to 5 × 10 11 charged<br />
particles per cm 2 per year of operation. For 6 mm thick <strong>de</strong>tectors filled with a Xe-CO2 gas mixture<br />
and operating at a gas gain of 10 4 , this translates into 26 or 53 mC per cm of wire per year for a 2 or<br />
4 mm ano<strong>de</strong> pitch, respectively. This integrated charge is consi<strong>de</strong>rable, so that ageing phenomena need<br />
to be consi<strong>de</strong>red. While the gas mixture itself is non-polymerising, the materials in contact with the<br />
gas may outgas pollutants that can produce severe ageing. Therefore, a careful selection of the chamber<br />
assembly insulators and epoxies, as well as of the components of the gas system, must be carried out.<br />
Specific ageing tests will therefore be part of the <strong>de</strong>tector <strong>de</strong>velopment program. The expected current<br />
in the most loa<strong>de</strong>d regions of the TRD is 26 nA/cm 2 . Several years of CBM could be accumulated in<br />
days or weeks in accelerated ageing tests at current <strong>de</strong>nsities several times higher that this. However, the<br />
behaviour of the ageing processes as a function of the current <strong>de</strong>nsity should be taken into account, since<br />
the rate of ageing is often lower the more accelerated the test is. On the other hand, many materials have<br />
already been tested and validated at other experiments (LHC, HERA) [116] for similar or higher lifetime<br />
requirements, thus making the task easier.<br />
4.5 Infrastructure<br />
The common infrastructure required for the TRD system comprises: electrical power (total estimate<br />
power consumption can be up to 40 kW), cooling water, crane for mounting of individual <strong>de</strong>tectors.<br />
Note that, the gas system, being a <strong>de</strong>dicated part of the TRD system, is factorized into <strong>de</strong>tector costs.
4.5. Infrastructure 119<br />
Polar emission angle Rate Flux Dose<br />
[mrad] [kHz/cm 2 ] [yr −1 cm −2 ] [krad/yr]<br />
station 1<br />
50 - 100 100 5.0×10 11 16.0<br />
100 - 150 53 2.7×10 11 8.5<br />
150 - 200 26 1.3×10 11 4.2<br />
200 - 250 17 8.5×10 10 2.7<br />
250 - 300 9.6 4.8×10 10 1.5<br />
300 - 350 7.1 3.6×10 10 1.1<br />
350 - 400 4.4 2.2×10 10 0.7<br />
400 - 450 2.0 1.0×10 10 0.3<br />
450 - 500 0.9 4.5×10 9 0.14<br />
station 2<br />
50 - 100 50 2.5×10 11 8.0<br />
100 - 150 25 1.3×10 11 4.0<br />
150 - 200 13 6.5×10 10 2.1<br />
200 - 250 7.5 3.8×10 10 1.2<br />
250 - 300 5 2.5×10 10 0.8<br />
300 - 350 3.3 1.7×10 10 0.5<br />
350 - 400 2.1 1.1×10 10 0.3<br />
400 - 450 1.0 5.0×10 9 0.16<br />
450 - 500 0.4 2.0×10 9 0.06<br />
station 3<br />
50 - 100 32 1.6×10 11 5.1<br />
100 - 150 15 7.5×10 10 2.4<br />
150 - 200 7.9 4.0×10 10 1.3<br />
200 - 250 4.8 2.4×10 10 0.8<br />
250 - 300 2.7 1.4×10 10 0.4<br />
300 - 350 2.0 1.0×10 10 0.3<br />
350 - 400 1.3 6.5×10 9 0.2<br />
400 - 450 0.6 3.0×10 9 0.1<br />
450 - 500 0.3 1.5×10 9 0.05<br />
Table 4.16: Rate, flux and dose in the three TRD stations for different polar emission angles.
120 Transition Radiation <strong>de</strong>tector (TRD)<br />
4.6 Working packages and timelines<br />
Activity Period<br />
performance simulations of <strong>de</strong>tector variants 2005<br />
global tracking 2005-2006<br />
S/B optimization of <strong>de</strong>tector layout 2005-2006<br />
<strong>de</strong>tector prototypes <strong>de</strong>velopment/tests 2005-2006<br />
<strong>de</strong>sign and tests of preamplifier/shaper prototypes 2005-2006<br />
matching data/simulations 2005-2006<br />
performance simulations of high-rate and high-occupancy 2006<br />
technical proposal end 2006<br />
<strong>de</strong>sign of preamplifier/shaper 2007-2008<br />
<strong>de</strong>sign of digital readout 2008-2009<br />
data preprocessing/trigger 2008-2009<br />
<strong>de</strong>tector prototypes and FEE tests 2007-2009<br />
final <strong>de</strong>tector layout and technology choice 2008-2009<br />
mechanical <strong>de</strong>sign 2008-2009<br />
technical <strong>de</strong>sign report 2010<br />
production, installation, tests 2011-2012<br />
Table 4.17: Outline of the future TRD activities and timelines.
5 Resistive Plate Chambers (RPC)<br />
5.1 Design consi<strong>de</strong>rations<br />
The main task of the TOF sub<strong>de</strong>tector system is the i<strong>de</strong>ntification of hadrons. The anticipated performance<br />
and acceptance is presented in chapter 14. It is obvious that the performance of the CBM<br />
experiments improves with an improved time resolution of the TOF subsystem. A better resolution does<br />
not only improve the particle - i<strong>de</strong>ntification capability of the <strong>de</strong>tector system, it also would allow for<br />
shorter distances, over which the time-of-flight is measured and thus for a more compact <strong>de</strong>sign. Provi<strong>de</strong>d<br />
that the counters are able to sustain the anticipated high rates as presented in section 12.1 a better<br />
time resolution would also allow for a substantial reduction of cost.<br />
One of the key tasks of the TOF system is the separation of pions and kaons. In or<strong>de</strong>r to achieve a<br />
two to three sigma separation with time resolutions in the or<strong>de</strong>r of 80 ps, flight pathes of the or<strong>de</strong>r of<br />
10 m are necessary. Therefore the full coverage of the same solid angle as the STS system requires<br />
an area of the TOF system in the or<strong>de</strong>r of 150 m 2 . Such an area cannot be equipped with traditional<br />
scintillator/ photomultiplier counters at an affordable cost. The only choice and the one adopted by the<br />
CBM collaboration is to <strong>de</strong>velop a high resolution and high rate version of multigap timing RPCs.<br />
RPCs (Resistive Plate Chambers) is a 23 years old technology [117], but only 4 years ago it was shown<br />
that it is possible to use RPCs for precise time of flight measurements at normal conditions of pressure<br />
and temperature with inexpensive materials [118]. There are already several experiments foreseeing<br />
or working with timing RPCs like ALICE [119, 120], FOPI [121], HADES [122], HARP [123] or<br />
STAR [124].<br />
A system of similar size as nee<strong>de</strong>d for the CBM <strong>de</strong>tector is currently being installed in the ALICE<br />
experiment [119]. The requirements imposed by the running conditions of CBM are, however, very<br />
different from the situation within ALICE at LHC. For CBM a system time resolution of at least 80 ps<br />
is necessary, which has to be obtained over the full acceptance and thus un<strong>de</strong>r different count rate loads<br />
ranging from 20 kHz near the beam axis to about 1 kHz at 28 o . Due to the fixed target geometry of the<br />
CBM experiment also the hit <strong>de</strong>nsity changes significantly from 10 −2 cm −2 (2.5 o ) to 6 · 10 −4 cm −2 (27 o ).<br />
Based on those consi<strong>de</strong>rations the directions for R&D for the CBM TOF wall are:<br />
• Explore the rate capability of the RPC <strong>de</strong>tector concept.<br />
Towards this goal materials different from float glass with a bulk resistivity of Ω=10 11 Ωcm have<br />
to be investigated. Also environmental parameters like the temperature could help to improve<br />
the rate capability and have to be studied. New materials and operation conditions have to be<br />
complemented by aging studies.<br />
• Explore the time resolution limit of various RPC readout concepts for large area coverage.<br />
The uniformity of the response over the full <strong>de</strong>tector surface is a key element for the physics<br />
performance. Due to the large differences in hit <strong>de</strong>nsity and rate various readout scenarios at<br />
different polar angles could present the optimum solution. Therefore the limitations of a pad or a<br />
strip based readout need to be evaluated.<br />
• Develop fast front-end electronics and digitisation system.<br />
Due to the fast rise time of the <strong>de</strong>tector signals, signal propagation over large distances and pro-<br />
121
122 Resistive Plate Chambers (RPC)<br />
cessing in highly integrated electronics represents a serious problem. Learning from existing solutions<br />
[119, 121], the optimal strategy needs to be <strong>de</strong>velopped.<br />
• Perform <strong>de</strong>tailed simulations for RPCs embed<strong>de</strong>d into the CBM system.<br />
Besi<strong>de</strong>s time resolution the requirements posed onto the RPC system <strong>de</strong>pend to some extend on the<br />
way the TOF subsystem is integrated into the full experiment. The TOF - Hits need to be matched<br />
with the tracks found in the TRD stations. There resolution and geometry <strong>de</strong>fines the necessary<br />
position resolution / granularity that the TOF <strong>de</strong>tector has to <strong>de</strong>liver. The TOF system layout needs<br />
to be optimized with respect to those needs.<br />
These R&D items are currently actively pursued. Since the <strong>de</strong>velopment of timing RPCs started only in<br />
the year 2000 [118] its final potential is not known today. Therefore a <strong>de</strong>sign proposal for the CBM TOF<br />
wall does not exist yet. However, the assumptions ma<strong>de</strong> in chapter 14 of a time resolution in the or<strong>de</strong>r<br />
of 80 ps seem to be reachable. Further improvements are not exclu<strong>de</strong>d and would result in a significant<br />
improvement of the PID capability of the experiment. At this moment of time, it is not justified to base<br />
the overall layout of the concept on such possible improvements. Therefore in the following a baseline<br />
of an overall uniform time resolution of σt=80 ps is used.<br />
In the following the progress and the status in the various research areas are <strong>de</strong>scribed.<br />
5.2 Simulations<br />
5.2.1 Input data and parameters of simulation<br />
The generic CBM simulation is <strong>de</strong>scribed in chapter 14. The simulation presented here <strong>de</strong>als with the<br />
specific aspects of the TOF wall and also uses common CBM software framework CbmRoot, which is<br />
based on the ROOT and Geant3 packages. The TOF <strong>de</strong>tector a 10 × 10 m 2 plane with a 0.8 × 0.8 m 2<br />
hole in the middle is placed 10 m away from the target. It contains the following material layers: Al-Gas-<br />
Glass-Gas-Al with corresponding widths of 0.2 − 0.12 − 0.54 − 0.12 − 0.2 cm. The <strong>de</strong>sign and material<br />
budget were assumed similar to those of the ALICE-TOF <strong>de</strong>tector. The other CBM sub-<strong>de</strong>tectors were<br />
taken by <strong>de</strong>fault from the CbmRoot package. 100 UrQMD Au+Au central events at E/A=25 GeV were<br />
used as input particles. Momentum and angular distributions of primary pions, kaons and protons are<br />
shown in chapter 14.<br />
Occupancy appears to be one of the most important parameters influencing the TOF <strong>de</strong>tector performance.<br />
The <strong>de</strong>nsity of charged tracks in the TOF plane is shown in Fig. 12.4. It is found that close<br />
to the beam pipe the maximum occupancy is about 0.6 primary tracks/dm 2 , and about 0.5 secondary<br />
tracks/dm 2 . For 10 cm 2 TOF cells, the maximum occupancy is about 11%. The contribution of secondaries<br />
therefore is significant.<br />
In total 1080 tracks per event cross the TOF plane of which 440 (40%) are primaries and 650 (60%) are<br />
secondaries. The composition of the secondaries is: 54% e ± , 19% p, 14% π ± and 13% µ ± . The origins<br />
of secondaries are: 6% ECAL, 12% TOF, 18% TRD3, 13% TRD2, 10% TRD1, 4% RICH and 16%<br />
STS.<br />
5.2.2 Matching of tracks with TOF<br />
Track matching is an important task for the TOF <strong>de</strong>tector. Let us consi<strong>de</strong>r a single track in the last TRD<br />
station positioned 8 m away from the vertex. Extrapolating this track to the TOF plane, we <strong>de</strong>fine ΔR to<br />
be the <strong>de</strong>viation of the track from the corresponding TOF hit and Rmin to be the minimum distance from
5.2. Simulations 123<br />
the given hit to the others. ΔR is <strong>de</strong>termined by the multiple scattering between the last TRD station and<br />
the TOF plane (see Fig. 5.1 for its distribution). The average <strong>de</strong>viation is ∼ 0.4 cm but there is a long<br />
tail to larger values. Rmin <strong>de</strong>pends on the hit <strong>de</strong>nsity in the TOF plane and its distribution is shown on the<br />
right si<strong>de</strong> panel of Fig. 5.1.<br />
number of tracks per event (1/bin)<br />
90<br />
80<br />
70<br />
60<br />
50<br />
40<br />
30<br />
20<br />
10<br />
<strong>de</strong>viation of the track from the hit<br />
hPrimTOF<strong>de</strong>ltaRho<br />
Entries 41536<br />
Mean 0.4311<br />
RMS 0.492<br />
0<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
ΔR<br />
(cm)<br />
number of tracks per event (1/bin)<br />
25<br />
20<br />
15<br />
10<br />
5<br />
distance to the closest hit<br />
hPrimTOFminRho<br />
Entries 44457<br />
Mean 12.52<br />
RMS 8.689<br />
0 5 10 15 20 25 30 35 40<br />
Rmin<br />
(cm)<br />
Figure 5.1: ΔR distribution (left) and Rmin distribution (right) obtained for central UrQMD collisions of Au + Au<br />
at Ebeam=25 AGeV.<br />
Clearly there is a correlation of the minimal distance to the closest hit with the distance to the beam pipe<br />
ρ (Fig. 5.2). The granularity of the <strong>de</strong>tector setup can be optimized with respect to the anticipated hit<br />
<strong>de</strong>nsity.<br />
(cm)<br />
Rmin<br />
40<br />
35<br />
30<br />
25<br />
20<br />
15<br />
10<br />
5<br />
0<br />
0 50 100 150 200 250 300 350 400<br />
ρ (cm)<br />
Figure 5.2: RPC Hit distribution as function of the minimal distance to the closest next hit Rmin and the distance<br />
to the beam pipe ρ.<br />
For ΔR > Rmin it is difficult to find a track corresponding to the particular hit, and such a track may be<br />
consi<strong>de</strong>red as mismatched. This gives us an estimate of the mismatching fraction. Comparing ΔR and<br />
Rmin distribution (Fig. 5.1) we can find only a small number of tracks with ΔR > Rmin. The simulation<br />
confirms this conclusion: the fraction of the mismatched tracks is about 1.53%. These results may be<br />
nevertheless improved by moving the TRD station closer to the TOF plane. Such improvement of track<br />
position accuracy could also benefit the overall TOF performance. Our plan is to continue the simulation<br />
with the real TOF structure to find an optimal <strong>de</strong>sign and to <strong>de</strong>velop matching and particle i<strong>de</strong>ntification<br />
algorithms using the experience gained by the ALICE-TOF group [120, 125].<br />
1.6<br />
1.4<br />
1.2<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
0
124 Resistive Plate Chambers (RPC)<br />
5.3 RPC properties<br />
5.3.1 Rate capability<br />
Currently the <strong>de</strong>tection of MIPs over large areas with RPCs can be ma<strong>de</strong> at rates close to 3 kHz/cm 2 [126,<br />
127], while at medium gas gains, around 10 5 , and small active areas, counting rates over 10 7 Hz/cm 2 [128,<br />
129] have been <strong>de</strong>monstrated. For timing RPCs [118] the current maximum counting rate capability is<br />
close to 2 kHz/cm 2 [130]. However, these counters operate at rather extreme conditions (enormous gas<br />
gain over 10 12 and avalanche <strong>de</strong>velopment in a <strong>de</strong>eply space-charge saturated mo<strong>de</strong> [131]), which may<br />
ren<strong>de</strong>r difficult the operation at high counting rates due to instabilities arising from the catho<strong>de</strong>s [128].<br />
In practice, the counting rate capability of RPCs is also strongly conditioned by the availability of suitable<br />
electro<strong>de</strong> materials with medium resistivity and good mechanical characteristics. Bulk resistive<br />
materials used so far inclu<strong>de</strong> bakelite and glass (the most common RPC materials), doped ABS plastic<br />
[132], silicon or gallium arseni<strong>de</strong> [129] and other ad hoc materials [133]. Layers of germanium [134]<br />
or SiC [135] <strong>de</strong>posited on insulating substrates have been also consi<strong>de</strong>red. Difficulties may also arise<br />
from the possible appearance of permanent discharges at medium electro<strong>de</strong> resistivities (roughly 10 4 to<br />
10 8 Ω·cm [129]), while at lower resistivity values the sparks progressively become more powerful.<br />
As the extension of the current counting rate capabilities of RPCs up to 50kHz/cm 2 will be an important<br />
part of the requirements for the inner part of the CBM TOF Wall, we tried to i<strong>de</strong>ntify suitable electro<strong>de</strong><br />
materials. Our efforts, so far, concerned the semiconducting glasses and the doped polymers, being the<br />
results <strong>de</strong>veloped below. We consi<strong>de</strong>red also an alternative approach that, although it will probably not<br />
meet the rate requirements over the full TOF area, may help to extend the area covered by RPCs ma<strong>de</strong><br />
of ordinary flat glass. This approach involves a mo<strong>de</strong>rate warming of the <strong>de</strong>tectors, exploiting the very<br />
strong <strong>de</strong>pen<strong>de</strong>nce of the glass resistivity with temperature.<br />
5.3.1.1 Rate capability improvement using polymeric materials<br />
In this section we <strong>de</strong>scribe the main results obtained with the so called antistatic plastics, which are<br />
available with catalogue resistivities ranging from 10 8 to 10 12 Ωcm.<br />
The <strong>de</strong>tectors, with an active area of 9 cm 2 , were ma<strong>de</strong> by a stainless steel catho<strong>de</strong> and an ENSITAL R○<br />
SD [136] plastic ano<strong>de</strong>, <strong>de</strong>fining a single 0.3 mm wi<strong>de</strong> gas gap (Fig. 5.3). More <strong>de</strong>tails are available<br />
in [137].<br />
Currents and counting rate<br />
Figure 5.3: Schematic view of the <strong>de</strong>tector structure.<br />
The chamber current and counting rate per unit area as a function of the applied voltage is shown in<br />
Fig. 5.4.
5.3. RPC properties 125<br />
For currents below 70 nA/cm 2 , corresponding to a saturation counting rate of 27 kHz/cm 2 , the chamber<br />
follows a linear current growth law. Although gas counters should in principle follow an exponential law,<br />
it is well known that RPCs follow a linear law at high gains due to the space-charge effect.<br />
Using the method suggested in [138] it was estimated that during the measurements shown in Fig. 5.5<br />
the resistive electro<strong>de</strong> presented a resistivity around 20 GΩcm.<br />
Figure 5.4: Current and counting rate per unit area as a function of the applied voltage. The chamber <strong>de</strong>viates<br />
from the linear current growth close to 70 nA/cm 2 , corresponding to a saturation counting rate of 27 kHz/cm 2 .<br />
Time resolution<br />
As shown in Fig. 5.5, the time resolution remained essentially unchanged, at a level around 90 ps σ, from<br />
2 kHz/cm 2 to 27 kHz/cm 2 .<br />
It should be noted that previous experience with timing RPCs in particle beams and with annihilation<br />
photons has shown that while single-gap counters may reach a time resolution of 60 ps σ in particle<br />
beams [139], similar counters irradiated with 511 keV photon pairs reach only about 90 ps σ. This<br />
fact may be attributed to the larger statistical variance of the primary currents arising from the latter<br />
irradiation method (see [140]).<br />
Brief characterization of the resistive material<br />
External tests to the resistive material were performed for obtaining some information about its longterm<br />
dynamic behavior. A second conductive electro<strong>de</strong> ma<strong>de</strong> with silverloa<strong>de</strong>d epoxy was formed over<br />
the ENSITAL plate and the sample placed in a temperature-controlled enclosure (the resistivity sharply<br />
<strong>de</strong>creases with temperature) un<strong>de</strong>r a steady flow of tetrafluorethane. A fixed voltage was applied across<br />
the sample and the current continuously monitored. After some time, the voltage was set to zero, except<br />
for a few brief moments to allow a fast resistivity measurement.<br />
The results can be seen in Fig. 5.6. Initially the resistivity rises exponentially with the transferred charge,<br />
but later seems to progressively approach a stable value. This value <strong>de</strong>pends on the applied voltage but,<br />
remarkably, the final currents are similar for different applied voltages. When the voltage is removed the<br />
resistivity recovers slowly in time, eventually retrieving its initial value.
126 Resistive Plate Chambers (RPC)<br />
Figure 5.5: Time resolution as a function of the counting rate, essentially unchanged from 2 kHz/cm 2 to 27<br />
kHz/cm 2 at a level around 90 ps σ. The vertical spread of the points is mainly due to statistical fluctuations and the<br />
horizontal spread due to the different working voltages at which the points have been taken.<br />
Although such measurements may not rigorously represent the behavior of the material, when used as<br />
an electro<strong>de</strong> (namely given the different current injection method), it seems that a qualitative agreement<br />
can be perceived. For instance, at the highest counting rates the chamber current was up to 15% higher<br />
at the beginning of each run and then <strong>de</strong>cayed rapidly to its equilibrium value. The runs lasted typically<br />
for 20 minutes, followed by a low current period of about 10 minutes. For such intermittent use a<br />
kind of equilibrium may be reached between resistivity increase due to current flow and its recovery<br />
by resting, allowing a reasonable agreement between the indirect resistivity measurements mentioned<br />
before (dashed line in Fig. 5.6) and the external ones.<br />
Figure 5.6: Externally measured resistivity of the ENSITAL plastic as a function of the transferred charge. Tests<br />
were done with applied voltages of 100V and 600V and the electro<strong>de</strong>s allowed to rest for 170 hours between<br />
measurements. The horizontal dashed line marks the indirect measurement mentioned in section 5.3.1.1.<br />
Conclusions<br />
The present result establishes the basic feasibility of timing measurements with RPCs at rates of tens of<br />
kHz/cm 2 while keeping a time resolution below 100 ps σ. This represents an improvement of over one<br />
or<strong>de</strong>r of magnitu<strong>de</strong> in counting rate as compared to the highest rates reported so far. For this particular<br />
study we used a commercially available plastic material, showing that small area timing RPCs can be<br />
ma<strong>de</strong> with plastic ano<strong>de</strong> electro<strong>de</strong>s. A severe, but reversible, increase of the plastic resistivity with the
5.3. RPC properties 127<br />
transferred charge was observed. While this characteristic may not be of much importance if the counters<br />
are to be used in a low duty cycle situation, the material may not be suitable for application in CBM.<br />
5.3.1.2 Rate capability improvement using semiconductor glasses<br />
Semiconductive glass is one of the best candidate for RPCs electro<strong>de</strong> material with its low electron<br />
conductivity and its relatively small resistivity of 10 8 - 10 11 Ωcm. One of the main disadvantages of<br />
semiconductive glasses is the absence of mass production, and, as a consequence, high prices of the<br />
prototype samples. Semiconductive glasses have been <strong>de</strong>veloped in Russia since the 60’s of last century.<br />
There are 3 known types of semiconductive glasses <strong>de</strong>pending on the base material selected for their<br />
production: phosphate, silicate and borosilicate glasses. These glasses are characterized by electron<br />
conductivity and contain the oxi<strong>de</strong>s of transition elements. They have black color and are opaque for<br />
the visible light. The technology of semiconductive glass fabrication is more complicated than for usual<br />
window glass, and before starting a semi-industrial production of the glass a few problems should be<br />
solved:<br />
• the best chemical composition should be found to get glasses with electron conductivity and the<br />
required resistivity;<br />
• because the color of the glasses influence the heat transfer properties, the <strong>de</strong>velopment of special<br />
production technology and equipment different from that of usual window glass is nee<strong>de</strong>d;<br />
• a method for removing the internal glass stresses, which arise during its cooling, has to be <strong>de</strong>vised.<br />
The control of the glass fritting is not possible by the technique routinely adopted for window<br />
glass, in particular, by polarimeters, due to the opacity of the proposed glasses. Another method<br />
to control the <strong>de</strong>gree of fritting should be <strong>de</strong>veloped;<br />
• the problem of glass crystallization should also be solved to get an homogeneous <strong>de</strong>nsity of the<br />
glass.<br />
To solve these problems, production and tests of a variety of samples with different compositions, produced<br />
by different technologies, is nee<strong>de</strong>d to choose the ones closer to the requirements of the CBM<br />
experiment. Moreover, prototypes of RPCs should be constructed using the different types of glasses<br />
and tested in the beam to check the real performances of the <strong>de</strong>tectors.<br />
INR started this R&D program about one year ago. During this period of time a lot of samples from<br />
phosphate and silicate glasses with different chemical composition and properties have been produced<br />
in the form of moulding with sizes 30 × 30 mm 2 and 100 × 110 mm 2 and with thickness about few mm.<br />
After that the samples have been grin<strong>de</strong>r and polished. Then the glass resistivity has been measured.<br />
The resistivity of one of the sample (phosphate glass) is shown in Fig. 5.7 as function of the applied high<br />
voltage (upper curve) and as a function of time, with applied HV = 1 kV, (lower curve). The resistivity<br />
is about 10 10 Ωcm at applied voltages of about several hundred volts.<br />
An RPC prototype has been constructed using phosphate glass. Beam tests of a chamber of the single<br />
cell type with 4 gaps 0.3 mm wi<strong>de</strong> (<strong>de</strong>scribed in section 5.4.1) have been performed at ITEP PS with<br />
protons of 1.8 GeV/c momentum and an intensity of up to 0.5 · 10 6 particles per spill. The spill duration<br />
was ≈ 300 ms. The employed gas mixture was 85% C2H2F4 + 5% iso-C4H10 + 10% SF6. Results of the<br />
efficiency and time resolution measurements are shown in Fig. 5.8.<br />
Despite the <strong>de</strong>gradation in the time resolution from 90 ps at counting rates of about 1 kHz/cm 2 to 120<br />
ps at 18 kHz/cm 2 , this result is a significant step-forward in the <strong>de</strong>tector improvement. Fig. 5.9 gives a<br />
<strong>de</strong>tailed information about the <strong>de</strong>pen<strong>de</strong>nce of the shape of the time spectra on the rate.
128 Resistive Plate Chambers (RPC)<br />
Figure 5.7: Resistivity of the sample of the phosphate glass as function of applied voltage (upper curve) and as<br />
function of time (lower curve) measured at an applied voltage of 1 kV.<br />
Figure 5.8: Time resolution and efficiency of an RPC prototype ma<strong>de</strong> with phosphate glass, as a function of the<br />
beam rate.<br />
In addition to a rather slow <strong>de</strong>gradation of the TOF resolution (rising from 90 ps up to 120 ps), one can<br />
see an increasing admixture of tails in the timing distributions. This is a serious obstacle preventing the<br />
usage of RPC for precise particle i<strong>de</strong>ntification. The way out of this problem still has to be found.<br />
Preliminary results of the glass production show that the technology should be simpler for silicate glasses.<br />
The resistivity of the first samples 30 × 30 mm 2 of the silicate glasses doped by Fe, Ti and Ge are<br />
presented on Fig. 5.10. At present few samples of silicate glasses have been produced to construct other<br />
RPC prototypes, but beam tests have not been performed yet. Production of the first plate with dimension<br />
about 1000 × 200 × 2 mm 3 is foreseen for end of 2004 still un<strong>de</strong>r laboratory conditions.
5.3. RPC properties 129<br />
Figure 5.9: Timing properties of the same RPC prototype used for the data of Fig. 5.8 at different rates.<br />
Figure 5.10: Resistivity of the sample of the silicate glass as function of applied voltage (upper curve) and as<br />
function of time (lower curve) measured at an applied voltage of 1 kV.<br />
5.3.1.3 Rate capability extension through temperature increase<br />
Here we <strong>de</strong>scribe an experimental <strong>de</strong>monstration of a consi<strong>de</strong>rable improvement on the counting rate<br />
capability of glass timing RPCs by means of a mo<strong>de</strong>rate warming of the <strong>de</strong>tector.
130 Resistive Plate Chambers (RPC)<br />
It is known that the resistivity of many ionic conductors follows an Arrhenius law<br />
ln(ρ) = a + b<br />
T ,<br />
which for narrow temperature intervals may be conveniently represented as<br />
ρ ρT0 10(T0−T )/ΔT , (5.1)<br />
where ΔT is the temperature increase required for a resistivity <strong>de</strong>crease by one or<strong>de</strong>r of magnitu<strong>de</strong> and<br />
the resistivity at the reference temperature.<br />
ρT0<br />
A measurement of several flat-glass types from common brands, has shown a relatively uniform rate<br />
of <strong>de</strong>crease of the resistivity with the temperature by about one or<strong>de</strong>r of magnitu<strong>de</strong> per ∼25 o C of<br />
temperature increase. Further <strong>de</strong>tails may be found in [141].<br />
Naturally, as already shown experimentally by [142] for wi<strong>de</strong>-gap RPCs, it is to be expected that the<br />
counting rate characteristics of RPCs, ma<strong>de</strong> from such glasses, will improve when the glass temperature<br />
is increased. Therefore, it is interesting to consi<strong>de</strong>r the use of warmed-up <strong>de</strong>tectors for extending the<br />
counting rate capability of timing RPCs while keeping the practical advantages of using industrial flat<br />
glass for its construction.<br />
The tests were performed on one of the 2×60 cm 2 four-gap shiel<strong>de</strong>d timing RPCs <strong>de</strong>scribed in [122],<br />
which were equipped with several internal thermometers and inserted in an external heating sleeve comman<strong>de</strong>d<br />
by a temperature control system. An illustration of the test setup is shown in Fig. 5.11.<br />
The internal temperature differences were generally less than one <strong>de</strong>gree measured over the RPCs aluminum<br />
shield, assuring that, un<strong>de</strong>r static conditions, the temperature of the enclosed RPCs would stay<br />
within the boundary temperatures. Further <strong>de</strong>tails may be found in [141].<br />
Figure 5.11: Schematic representation of the test setup. Irradiations were ma<strong>de</strong> with radioactive sources of 22 Na<br />
and 60 Co. The 22 Na positron annihilation source allows performing timing measurements in coinci<strong>de</strong>nce with a<br />
scintillator.<br />
Timing accuracy<br />
Timing measurements were performed by coinci<strong>de</strong>nt measurement of the photon pairs from the 22 Na<br />
source between the RPC and a plastic scintillator. The time resolution of the scintillator for photons was<br />
estimated by performing the same measurement between two i<strong>de</strong>ntical scintillators, yielding a resolution<br />
of 110 ps σ.
5.3. RPC properties 131<br />
A series of measurements were performed as a function of the source intensity, of the applied voltage<br />
and of the temperature. The applied voltage was rescaled to an effective value<br />
V ∗ 0 = V0<br />
T<br />
Tre f<br />
where Tre f and Pre f are a common reference temperature and pressure. The results for the timing resolution,<br />
together with a sample time spectrum, are shown in Fig. 5.12. Surprisingly, none of these variables<br />
exerts any effect on the timing accuracy for gamma photons. The observed resolution around 90 ps σ<br />
agrees well with previous investigations.<br />
Figure 5.12: Timing accuracy (ps σ) as a function of the source intensity, effective applied voltage (see text) and<br />
temperature. Surprisingly, none of these variables exerts any effect on the timing accuracy for gamma photons.<br />
For reference, some measurements were done with cosmic rays, yielding a resolution of 76 ps σ, also in<br />
qualitative agreement with previous results obtained with this <strong>de</strong>tector [122].<br />
Efficiency<br />
The measured charge spectra for an RPC irradiated with gamma photons is very well <strong>de</strong>scribed by an<br />
exponential [141]. So in this particular case, the efficiency of timing RPCs should be very sensitive to<br />
variations in the operating parameters. Therefore, this quantity may be more promising than the timing<br />
resolution, as an assessment of the effects of temperature on the counter. However, the extraction of the<br />
relevant physical parameters from the data requires the <strong>de</strong>velopment of a minimally realistic mo<strong>de</strong>l of the<br />
<strong>de</strong>tector efficiency. This mo<strong>de</strong>l, <strong>de</strong>scribed in [141], contains four fixed parameters plus one parameter<br />
for each temperature, in total 10 parameters in the present study. These parameters can be robustly<br />
<strong>de</strong>termined by a global least squares fit to the data (a total of 84 individual curves), being an example<br />
show in Fig. 5.13.<br />
After fitting the mo<strong>de</strong>l to the experimental data one can extract the relative improvement of the rate<br />
capability due to temperature [141] and compare it with what is expected from the direct measurement<br />
of the glass resistivity. These quantities are represented in Fig. 5.14.<br />
Based on these results, one may extrapolate measurements ma<strong>de</strong> with the same counter on particle<br />
beams [122], suggesting that operation at resolutions below 100 ps σ and efficiency of close to 90%<br />
may be feasible at 6 kHz/cm 2 when the <strong>de</strong>tector is warmed up at 50 o C (10-fold increase in rate capability<br />
[122]).<br />
Pre f<br />
P
132 Resistive Plate Chambers (RPC)<br />
Figure 5.13: Least squares fit of the mo<strong>de</strong>l (lines), <strong>de</strong>scribed in [141], to the observed counting rates (points)<br />
as a function of the avalanche position in the central ±20 cm of the RPC. Each panel corresponds to one of the<br />
used sources. Within a panel, each graph refers to the temperature indicated in <strong>de</strong>grees in the inset. It is evi<strong>de</strong>nt a<br />
sharp increase on the visible counting rate with increasing temperature for the strongest sources. The thicker line<br />
corresponds to the visible rate at zero current.<br />
Figure 5.14: Relative increase of the rate capability with the <strong>de</strong>tector temperature, as estimated by measurements<br />
of <strong>de</strong>tector behavior and by direct measurements of the glass resistivity. It is evi<strong>de</strong>nt the good agreement, indicating<br />
a rate improvement by a factor 10 when the temperature is increased by ∼25 o C.<br />
5.3.2 Aging<br />
Severe aging of glass RPCs operating in streamer mo<strong>de</strong> has been reported [143, 142] and related to the<br />
presence of water vapor traces in the gas mixture. An uni<strong>de</strong>ntified <strong>de</strong>posit was found over the glass<br />
surface, severely increasing the dark count rates and reducing the counter efficiency.<br />
Naturally it is of consi<strong>de</strong>rable practical importance to investigate such effects in timing RPCs, often ma<strong>de</strong><br />
with glass electro<strong>de</strong>s and working in somewhat similar gaseous mixtures.
5.3. RPC properties 133<br />
The test setup comprised six 9 cm 2 single-gap counters, each ma<strong>de</strong> with one glass (SCHOTT ATHERMAL R○<br />
tainted glass) and one aluminum electro<strong>de</strong>. Three counters had a glass catho<strong>de</strong> and three had an aluminum<br />
catho<strong>de</strong>. Further <strong>de</strong>tails are available in [144].<br />
Dark current<br />
As an increase in dark current was the main experimental indication of aging reported in [143], we use<br />
this parameter as indicative of an eventual aging effect.<br />
Fig. 5.15 shows the dark current for each of the six chambers averaged over the second of the two daily<br />
rest hours. There is no evi<strong>de</strong>nce of any systematic long term increase with time, suggesting that the<br />
aging effect mentioned above is less severe in timing RPCs than in streamer mo<strong>de</strong> RPCs. The short term<br />
fluctuations are well correlated for the three chambers of the same type and are of environmental origin<br />
(mostly temperature).<br />
When the catho<strong>de</strong> is ma<strong>de</strong> from aluminum, the new chambers apparently need to work for a longer time<br />
until the dark current stabilizes. A possible explanation may be related to the different surface porosity<br />
of aluminum and glass, the former easily trapping microscopic dust particles that generate dark currents.<br />
Nevertheless there is a general ten<strong>de</strong>ncy for the initial dark currents to <strong>de</strong>crease with time.<br />
Figure 5.15: Dark current as a function of operation time. No systematic increase in dark current is apparent.<br />
(Positive current: glass catho<strong>de</strong>; negative current: glass ano<strong>de</strong>). After 280 days two counters (1), one of each<br />
configuration, were removed for surface analysis, and replaced by two new chambers (2).<br />
Integrated charge<br />
Fig. 5.16 shows the charge accumulated in each chamber after 480 days of operation. Two chambers were<br />
removed for surface analysis at day 280. The replacement chambers had the tainted glass substituted by<br />
ordinary sheet glass.<br />
Consi<strong>de</strong>ring an average avalanche charge of 10 pC, the accumulated charge of 800 mC corresponds to<br />
about 80 × 10 9 avalanches in each chamber. As the effectively illuminated area in each chamber is about<br />
1 cm 2 , one estimates that the chambers un<strong>de</strong>r test operate at a counting rate of about 2.5 kHz/cm 2 . The<br />
charge accumulated so far corresponds to 2.5 years and 1 month of operation at a counting rate of 1 and<br />
20 kHz/cm 2 , respectively.<br />
Surface composition analysis by Electron Probe Microanalysis<br />
After 280 days of operation two chambers were opened for analysis. A visual inspection of the electro<strong>de</strong>s
134 Resistive Plate Chambers (RPC)<br />
Figure 5.16: Integrated charge as a function of operation time. Two chambers (1) were substituted after 280 days<br />
by new ones (2). The remaining four chambers accumulated an integrated charge of about 800 mC.<br />
revealed a multicolored dry <strong>de</strong>posit over the glass electro<strong>de</strong>s. The colors appeared to be merely due to<br />
light interference and not intrinsic to the material.<br />
When the glass was operated as a catho<strong>de</strong>, the <strong>de</strong>posit was well localized over an area of approximately<br />
1 cm 2 close to the UV-light entrance slit, presumably corresponding to the effectively illuminated region.<br />
When the glass was operated as an ano<strong>de</strong> the <strong>de</strong>posit was distributed over most of the electro<strong>de</strong> area.<br />
The aluminum electro<strong>de</strong> facing the glass catho<strong>de</strong> appeared covered with a localized matter layer that coinci<strong>de</strong>d<br />
with the <strong>de</strong>posit on the glass. The aluminum electro<strong>de</strong> facing the glass ano<strong>de</strong> seemed completely<br />
clean.<br />
The results of a qualitative Electron Probe Microanalysis (EPMA) of the most abundant elements found<br />
on the surfaces of the glass electro<strong>de</strong>s (ano<strong>de</strong> and catho<strong>de</strong>) and, for comparison, on both surfaces of<br />
a new glass are presented in Table 5.1. Only the relative concentrations within the same element are<br />
meaningful and no comparisons should be ma<strong>de</strong> along the table columns.<br />
The surfaces in contact with the gas show a significant enrichment in fluor, oxygen and sulphur contents<br />
after irradiation, presumably by <strong>de</strong>position from the gas (oxygen may be also extracted from the glass).<br />
These elements may eventually be associated with lighter ones, but the method could not <strong>de</strong>tect elements<br />
lighter than oxygen.<br />
There is also some surface enrichment in elements that are not present in the gas. For certain elements<br />
the enrichment is observed both on glass ano<strong>de</strong>s and catho<strong>de</strong>s (Si, Al, Ca, Mg) or only on one electro<strong>de</strong><br />
polarity (Cl, Na, Fe). Naturally aluminum could have been etched from the opposing electro<strong>de</strong> and<br />
transported by the avalanches across the gap. The enrichment observed for the remaining elements could<br />
be a consequence of the ion flow in the glass due to the electric current. However this process does<br />
not explain why the enrichment appears both in the ano<strong>de</strong> and catho<strong>de</strong> surfaces or why there is not a<br />
corresponding <strong>de</strong>pletion on the back surfaces.<br />
A similar analysis of the aluminum electro<strong>de</strong>s is also shown in Table 5.1. There is a corresponding<br />
enrichment in fluor for both electro<strong>de</strong> polarities. However the aluminum catho<strong>de</strong> seems to have been<br />
somewhat cleaned of initial traces of oxygen and silicon, while the ano<strong>de</strong> appeared enriched not only in<br />
oxygen but also in potassium and sodium.<br />
Clearly a full un<strong>de</strong>rstanding of the ion flows in aluminum-glass RPCs is not available at this moment.
5.3. RPC properties 135<br />
GLASS<br />
new new catho<strong>de</strong> ano<strong>de</strong><br />
Element glass glass back catho<strong>de</strong> back ano<strong>de</strong><br />
face 1 face 2 face face<br />
F 0 0 81 669 0 228<br />
O 438 360 505 1002 627 890<br />
Cl 0 0 0 0 0 84<br />
S 0 0 0 7 0 5<br />
Si 29 53 84 536 170 1052<br />
Al 4 7 7 55 11 44<br />
Mg 4 5 7 29 11 17<br />
Na 8 13 44 55 11 344<br />
Fe 84 60 78 184 96 91<br />
Ca 0 0 0 40 0 66<br />
ALUMINUM<br />
Element new catho<strong>de</strong> ano<strong>de</strong><br />
F 0 125 302<br />
O 99 50 133<br />
Si 27 9 26<br />
K 0 0 12<br />
Na 0 0 14<br />
Al 5827 6094 5274<br />
Table 5.1: Qualitative Electron Probe Microanalysis of the most abundant elements found in the surfaces of two<br />
glass electro<strong>de</strong>s and, for comparison, in both surfaces of a new, never used, glass. Elements lighter than oxygen<br />
were not <strong>de</strong>tected. Units are arbitrary. Only the relative concentrations within the same element are meaningful and<br />
no comparisons should be ma<strong>de</strong> along the table columns. Similar analyses were also performed on the aluminum<br />
electro<strong>de</strong>s.<br />
Conclusions<br />
Aging studies were performed on six 0.3 mm gap timing RPCs ma<strong>de</strong> with glass and aluminum electro<strong>de</strong>s<br />
and operating in a mixture of tetrafluorethane with 10% sulphur hexafluori<strong>de</strong>, 5% isobutane and water at<br />
10% relative humidity. After a charge transfer of about 800 mC, equivalent to 2.5 years of operation at<br />
1 kHz/cm 2 , no systematic increase of dark current was <strong>de</strong>tected, suggesting that no severe aging process<br />
is at work.<br />
However some thin <strong>de</strong>posits were found over the electro<strong>de</strong>s. An EPMA qualitative analysis suggested<br />
that the glass surfaces contained mainly fluor and oxygen, with enrichment in several trace metals and in<br />
chlorine. However a full un<strong>de</strong>rstanding of all the perceived ion flows is not available at this moment.<br />
The tests are still un<strong>de</strong>r way to reach even higher integrated charges and probe conditions similar to the<br />
inner part of the CBM TOF wall.
136 Resistive Plate Chambers (RPC)<br />
5.4 RPC <strong>de</strong>tector layout options<br />
Timing Resistive Plate Counters (RPCs) consist of a stack of planar electro<strong>de</strong> plates of high resistivity<br />
which are kept by spacers at fixed distances between 0.2 and 0.35 mm typically. Normally an ano<strong>de</strong><br />
is placed in the center of the stack, 2 catho<strong>de</strong>s enclose it at its outer surfaces. Operated in the right gas<br />
mixture un<strong>de</strong>r a uniform electric field of about 10 kV/mm between the electro<strong>de</strong>s the counters <strong>de</strong>liver fast<br />
avalanche signals which can be <strong>de</strong>rived as single pulses from the ano<strong>de</strong> or in differential mo<strong>de</strong> between<br />
ano<strong>de</strong> and the catho<strong>de</strong>s.<br />
How this working principle which can be inferred from Fig. 5.17 is realized technically <strong>de</strong>pends on the<br />
various <strong>de</strong>mands set by the experiment. With the very different rates the CBM TOF wall has to cope<br />
with certainly various polar angle ranges have to be equipped with different <strong>de</strong>tector types. The possible<br />
options un<strong>de</strong>r consi<strong>de</strong>ration and the present status of their performance are <strong>de</strong>scribed in the following.<br />
5.4.1 Single cell chambers<br />
A typical single-cell RPC <strong>de</strong>sign is sketched in Fig. 5.17; it actually <strong>de</strong>scribes a test counter (electro<strong>de</strong><br />
size 50 x 50 mm 2 ) used to study the rate performance of semi-conductive glasses (resistivity 10 10 Ωcm)<br />
<strong>de</strong>scribed in section 5.3.1.2.<br />
Figure 5.17: Schematic cut through a single-cell RPC.<br />
Single-cell counters with 4 or more gaps and surfaces of typically 10 cm 2 <strong>de</strong>liver easily time resolutions<br />
down to 40 ps at efficiencies above 99%. Adopted in size and shape to the nee<strong>de</strong>d granularity they are<br />
also shiel<strong>de</strong>d perfectly hence featuring minimum cross talk to neighbours. They are one of the choices<br />
for the innermost angular region of the planned TOF wall, provi<strong>de</strong>d suitable electro<strong>de</strong> material can be<br />
found which allows for the envisaged time resolutions in the high-rate environment.<br />
5.4.2 Multipad chambers<br />
A somewhat more economical realisation are multipad chambers: The surface of the electro<strong>de</strong> stack is<br />
much larger, the ano<strong>de</strong> is subdivi<strong>de</strong>d into single pads which are read out separately. This allows for an<br />
easier coverage of larger areas; it is paid by enhanced cross talk between the pads.<br />
A multi-pad based RPC TOF system [120] is being constructed for the ALICE <strong>de</strong>tector at CERN [145]
5.4. RPC <strong>de</strong>tector layout options 137<br />
at present; a similar system could be envisaged for the larger polar regions of the CBM TOF wall. In<br />
ALICE the RPC shell will provi<strong>de</strong> particle i<strong>de</strong>ntification for the bulk of charged particles produced in<br />
the central rapidity region (|y| ≤ 1) at intermediate momenta (up to a few GeV/c) at particle rates below<br />
1 kHz/cm 2 .<br />
The basic <strong>de</strong>sign features of an ALICE multigap resistive plate chamber (MRPC) [146] are <strong>de</strong>picted in<br />
Fig. 5.18.<br />
Figure 5.18: Cross-section view of an MRPC strip used in the ALICE TOF system.<br />
Each module (called strip) is 10 cm wi<strong>de</strong> and 120 cm long, carrying 96 rectangular ano<strong>de</strong> pads of 2.5 x.<br />
3.5 cm 2 area (cf. the photo in Fig. 5.19).<br />
They are placed in the middle of the stack, the two catho<strong>de</strong>s on the external surfaces; a differential high<br />
voltage is applied. For the readout a differential signal is <strong>de</strong>rived from ano<strong>de</strong> and catho<strong>de</strong> pickup pads.<br />
The stack on each si<strong>de</strong> has 5 gaps (10 gaps in total), each gap being 250 µm wi<strong>de</strong>. The electro<strong>de</strong> plates<br />
are ma<strong>de</strong> of commercial soda-lime glass, 400 µm thick for the internal plates and 550 µm thick for the<br />
external ones. The spacers are ma<strong>de</strong> of nylon fishing line.<br />
Fig. 5.20 shows the efficiency, time resolution and streamer probability as a function of the high voltage.<br />
The efficiency reaches 99.9% at a time resolution of 40 ps and has a plateau for streamer free operation<br />
that is more than 1.5 kV wi<strong>de</strong>.<br />
Fig. 5.21 shows typical time distributions before (σ = 91 ps) and after (σ = 48 ps) slewing corrections.<br />
Ten such strips with the final <strong>de</strong>sign characteristics have been tested and the results are shown in Fig. 5.22.<br />
All strips can be operated at 12 kV with a time resolution between 40 and 50 ps. The main disadvantages
138 Resistive Plate Chambers (RPC)<br />
Figure 5.19: MRPC strips layout.<br />
Figure 5.20: Efficiency, time resolution and streamer probability of MRPC as a function of the high voltage.<br />
of MRPC is the cross-talk between neighboring pads and the <strong>de</strong>gradation of the time resolution near pad<br />
bor<strong>de</strong>rs. Fig. 5.23 illustrates the charge induced between neighboring pads. The cross-talk probability<br />
and time resolution close to the pad bor<strong>de</strong>r are shown in Fig. 5.24.<br />
The use of MRPC is also limited due to the high glass resistivity [120]. Fig. 5.25 shows their rate capability,<br />
<strong>de</strong>monstrating that RPCs of this type can be used if the count rates are not exceeding 1 kHz/cm 2 .
5.4. RPC <strong>de</strong>tector layout options 139<br />
Figure 5.21: Time distribution of MRPC before (above) and after (below) slewing corrections.<br />
Figure 5.22: Efficiency and time resolution versus applied high voltage for 10 MRPC strips.<br />
Figure 5.23: Charge induction between neighboring cells of MRPC strips.
140 Resistive Plate Chambers (RPC)<br />
Figure 5.24: Longitudinal scan along the MRPC strip between two pads (◦ - left pad, △ - right pad) at 12.5 kV:<br />
(a) efficiency; (b) time resolution; (c) OR probability; and (d) AND probability. The distance is relative to the<br />
bor<strong>de</strong>r between the two pads.<br />
Figure 5.25: TOF efficiency as a function of beam rate for two versions of MRPC strips.
5.4. RPC <strong>de</strong>tector layout options 141<br />
5.4.3 Single strip counter<br />
A major challenge for timing RPC operation at high fractional occupancy concerns the inter-channel<br />
crosstalk that arises from the coupling of the GHz-bandwidth RPC pulses to the neighbouring <strong>de</strong>tector<br />
channels. To address this issue we studied a prototype for time of flight measurements over large areas<br />
and at high occupancies. The <strong>de</strong>tector was constituted by three in<strong>de</strong>pen<strong>de</strong>nt cells placed into groun<strong>de</strong>d<br />
aluminum boxes. Each 2 × 2 × 60 cm 3 box contained a 4-gap glass-aluminum RPC.<br />
Measurements were performed at the <strong>GSI</strong> (Darmstadt) SIS accelerator using fragments generated by<br />
primary collisions of C at 1 GeV/u.<br />
At 200 Hz/cm 2 the counters have shown a time resolution of 60 ps < σt < 80 ps with 3σ-tails below 8%.<br />
An inefficiency of 13%, compatible with the <strong>de</strong>tector geometry, was observed, calling for a two-layer<br />
<strong>de</strong>sign. High mechanical robustness and homogeneity of the physical properties along the longitudinal<br />
direction of the <strong>de</strong>tector were also observed. A measured cross-talk level of only 0.4% has shown no<br />
influence at all on the timing resolution.<br />
A procedure for the stand-alone calibration of the <strong>de</strong>tector using redundant information is proposed,<br />
taking advantage of the very good spatial uniformity observed.<br />
Further <strong>de</strong>tails about these results may be found in [147, 122]. Efforts supported by the 6th European<br />
Framework Program are un<strong>de</strong>rway for a large scale test of this <strong>de</strong>tector concept, in close cooperation<br />
with the upgra<strong>de</strong> program of the TOF Wall of the HADES experiment at <strong>GSI</strong>.<br />
5.4.3.1 Cross-talk in high occupancy environments<br />
Economic consi<strong>de</strong>rations on the <strong>de</strong>sign of this type of <strong>de</strong>tector generally suggest that the occupancy per<br />
individual readout cell Pocc should be at the level of 20% in the most unfavourable scenario. Roughly<br />
speaking, once there is a hit in a given cell, the probability of having a hit in at least one of the neighbours<br />
is Nneighbours × Pocc. If these ’neighbour hits’ interfere with the ’interesting’ hit (cross - talk) the<br />
performance of the <strong>de</strong>tector may be <strong>de</strong>teriorated for a large fraction of the hits, potentially introducing<br />
complex systematic effects on the measurements.<br />
5.4.3.2 Shiel<strong>de</strong>d RPCs<br />
To avoid potentially troublesome cross-talk, we <strong>de</strong>signed and tested the shiel<strong>de</strong>d RPC layout shown in<br />
Fig. 5.26, resembling the original i<strong>de</strong>a suggested in [148]. The chambers are constituted by 2x60 cm 2 ,<br />
2 mm thick, aluminum and glass electro<strong>de</strong>s, the later being left electrically floating [149] for easier<br />
construction. Each RPC cell is shiel<strong>de</strong>d in groun<strong>de</strong>d aluminum boxes (for <strong>de</strong>tails see [147]).<br />
Figure 5.26: Schematic representation of the shiel<strong>de</strong>d RPC prototype.
142 Resistive Plate Chambers (RPC)<br />
5.4.3.3 Physical environment<br />
Measurements were performed at the <strong>GSI</strong> (Darmstadt) SIS accelerator using fragments generated by<br />
primary collisions of C at 1GeV/u. For the reference time we used a scintillator system of resolution<br />
equal to 35 ps σ, which allowed to precisely measure the intrinsic resolution of the RPC and also the<br />
γβ distribution of the incoming particles, yielding the energy <strong>de</strong>position distribution (Fig. 5.27). It<br />
could be estimated that at least 5% of the particles <strong>de</strong>posited at least a factor 2 more energy than the<br />
minimum ionizing ones [147]. However, no significant difference was observed when studying slow and<br />
fast particles separately.<br />
Events<br />
600<br />
500<br />
400<br />
300<br />
200<br />
100<br />
GEANT+URQMD (CC 1GeV/u)<br />
MEASURED<br />
0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2<br />
β<br />
/hfill<br />
Events<br />
120<br />
100<br />
80<br />
60<br />
40<br />
20<br />
10 -1<br />
dE<br />
(a.u.)<br />
dx<br />
1 10<br />
Figure 5.27: Distributions of β and γβ measured with the trigger scintillators, compared with the ones obtained<br />
from the HADES simulation toolkit [150]. Also shown superimposed the Bethe-Bloch curve for fluorine in arbitrary<br />
units.<br />
5.4.3.4 Cross-talk<br />
Despite previous experience of cross-talk levels around 85% between neighbouring strips in long <strong>de</strong>tectors<br />
[151], we observed an excess of events of only 0.4%/neighbour due to the a<strong>de</strong>quate shielding.<br />
Expectedly, the probability that a signal induces cross-talk is higher for the larger signals (mostly from<br />
streamer discharges) (Fig. 5.28).<br />
However the <strong>de</strong>finitive test is to measure the possible <strong>de</strong>gradation of the time resolution performance in<br />
the case where there are two almost simultaneous hits in neighbouring cells. Due to the low multiplicity<br />
of carbon collisions the probability of having ’neighbouring hits’ was only 1.2%/neighbour. However, a<br />
sample of around 1300 of such events was collected, being the corresponding, unaffected, time distribution<br />
shown in Fig. 5.29. It is also shown that there is no correlation between the time difference between<br />
both hits and the time measured in the ’interesting’ channel.<br />
5.4.3.5 Behaviour with rate<br />
The behaviour of the most relevant quantities is shown in Fig. 5.30: the <strong>de</strong>pen<strong>de</strong>nce with the local<br />
rate R[Hz/cm2 ] is found to be linear and yields for the efficiency: ε = 87 − 1.5·R<br />
100Hz/cm2 [%], for the time<br />
resolution σt = 67+ 4.7·R<br />
100Hz/cm2 [ps] and for the tails 3σ-tails = 6.7+ 0.6·R<br />
100Hz/cm2 [%] (3σ-tails stands for the<br />
fraction of events out of 3 σ from the maximum).<br />
RPCs similar to the ones used are known to yield efficiencies up to 99.5% [152], suggesting that the<br />
measured efficiency was dominated by geometric losses. The observed intrinsic inefficiency, 13%, is<br />
compatible with the 15% expected for perpendicular particle inci<strong>de</strong>nce (1 − ε=<strong>de</strong>ad zone/active zone <br />
3 mm/20 mm 15%). This intrinsic inefficiency can be compensated by a 2-layer scheme of the <strong>de</strong>tector<br />
γ β
5.4. RPC <strong>de</strong>tector layout options 143<br />
Figure 5.28: Fraction of cross-talk and coinci<strong>de</strong>nt hits in neighbour cell (right axis) as a function of the fast<br />
charge in main RPC (left axis). The double hit probability does not show any significant <strong>de</strong>pen<strong>de</strong>nce with charge,<br />
as expected, whereas the probability of cross-talk is much higher for streamers.<br />
Figure 5.29: a) Time distribution in one RPC in presence of an almost simultaneous hit in a neighbouring cell<br />
(between parentheses the resolution after subtracting the intrinsic resolution of the scintillators). b) No correlation<br />
between the time measured in the main counter and the time lag between both hits is observed. c) Distribution of<br />
the position of hits in the neighbour cell whenever the main cell has been fired, showing a clear peak at trigger<br />
position (0 cm) that can be attributed to local production of particles. Subtracting these events, the sample is<br />
dominated by coinci<strong>de</strong>nt pairs coming from the target.<br />
layout. It might be advantageous, providing as a benefit easier mechanical construction and redundant<br />
information, useful for calibration purposes.<br />
5.4.3.6 Homogeneity and calibration<br />
The <strong>de</strong>tector has shown good homogeneity along the longitudinal dimension (Fig. 5.31). The position<br />
resolution was measured to be below 6 mm σ, with systematic shifts of the distribution kept below 2.5<br />
mm. These facts <strong>de</strong>monstrate the mechanical robustness of the <strong>de</strong>sign and the negligible effect of the<br />
nylon monofilaments used as spacers [147].<br />
In timing RPCs the measured time must be corrected for the time-charge correlation that is always present<br />
[151]. Additionally, in a system, the isocronicity of all time signals must be guaranteed by a<strong>de</strong>quate<br />
inter-comparisons. The ensemble of all these procedures we call calibration. In practice this operation<br />
must be performed with some periodicity, since the <strong>de</strong>tector-related time lags are likely <strong>de</strong>pen<strong>de</strong>nt on
144 Resistive Plate Chambers (RPC)<br />
Figure 5.30: Plot showing the global behaviour with rate of the efficiency (right axis), time resolution (left axis)<br />
and 3-sigma tails (right axis). The 13% inefficiency at low count rates is of geometric origin, calling for a two-layer<br />
approach<br />
environmental conditions.<br />
In the present case it was found that:<br />
1. The time-charge correlation is well <strong>de</strong>scribed by a simple two-segment linear fit in time vs. log(Q)<br />
representation. This can be particularly interesting for on-line purposes.<br />
2. The parameters of the fit can be obtained from any single position along the <strong>de</strong>tector and used<br />
elsewhere.<br />
3. The time measured with two in<strong>de</strong>pen<strong>de</strong>nt RPCs can be used to <strong>de</strong>termine the parameters of the fit<br />
without the help of any auxiliary <strong>de</strong>tector; we call this concept self-calibration and <strong>de</strong>scribe it in<br />
section 5.4.3.7.<br />
5.4.3.7 Self-calibration<br />
The time difference between two in<strong>de</strong>pen<strong>de</strong>nt RPCs placed close to each other and measuring the same<br />
particles is a function of both RPC charges only (Fig. 5.32). To <strong>de</strong>rive the time-charge calibration for<br />
RPC1, for instance, we keep only a narrow range of Q2 close to the charge distribution maximum and fit<br />
the points Δt(Q1,Q2) by a mosaic of two planar surfaces, yielding the required linear correction segments<br />
for RPC1.<br />
For the data shown in Fig. 5.31 the second RPC was simulated by data taken from an in<strong>de</strong>pen<strong>de</strong>nt run at<br />
a single location chosen arbitrarily.<br />
5.4.4 Multistrip counter<br />
In analogy to the transition from a single-cell to a multi-pad counter one can also replace the single ano<strong>de</strong><br />
strip by a multistrip ano<strong>de</strong> [153]. Such an ano<strong>de</strong> (see Fig. 5.33) has a segmented strip/gap configuration;<br />
by reading out both ends of each strip, the ToF is <strong>de</strong>termined by the mean timing, the position along
5.4. RPC <strong>de</strong>tector layout options 145<br />
Figure 5.31: Comparison between different calibration methods in several points along the <strong>de</strong>tector. Standard:<br />
run-by-run fit in 15 linear segments. 2 piece linear: run-by-run fit in 2 linear segments. Self-calibrated: 2 piece<br />
linear fit <strong>de</strong>rived by self-calibration (see 5.4.3.7) from a point chosen arbitrarily.<br />
t1−t2 (ps)<br />
log(Q2)<br />
2000<br />
1500<br />
1000<br />
500<br />
0<br />
−500<br />
−1000<br />
−1500<br />
2.5<br />
2<br />
1.5<br />
0 0.5 1 1.5<br />
log(Q1)<br />
2 2.5 3 3.5<br />
Figure 5.32: Example of a self-calibration fit in two planar surfaces. The reference chamber corresponds to Q2<br />
and the fit parameters are calculated for chamber 1 (see 5.4.3.7).<br />
the strip is <strong>de</strong>livered by the time difference. The advantage of such a <strong>de</strong>sign in comparison to a pad<br />
like structure is the reduction of electronic channels and a potentially better spatial resolution. Of course<br />
the limit for this <strong>de</strong>tector type is the number of hits which can be <strong>de</strong>tected within an event (Multihitperformance).<br />
Equipped with normal floating glass electro<strong>de</strong>s such <strong>de</strong>tectors offer an i<strong>de</strong>al solution for<br />
the outer 75 % of the total TOF wall where the rates stay below 1 kHz/cm 2 .<br />
As single-strip <strong>de</strong>tectors such multistrip <strong>de</strong>tectors need to be arranged in a staggered configuration in or<strong>de</strong>r<br />
to guarantee a full geometrical efficiency. The number of strips and the pitch are of course <strong>de</strong>pending<br />
on the required spatial resolution and the multihit capability. Detectors of this type are presently being<br />
<strong>de</strong>veloped for the FOPI-ToF upgra<strong>de</strong> project; they are part of an R&D program which is supported by<br />
the European Union (JRA 12). In Fig. 5.34 a full size supermodule of the FOPI-system is shown. Five<br />
RPCs (each 90 cm long, 4.6 cm wi<strong>de</strong>) with 8 gaps of 250 µm are placed insi<strong>de</strong> a common gas and high
146 Resistive Plate Chambers (RPC)<br />
Glass<br />
z<br />
HV<br />
Multistrip ano<strong>de</strong>s<br />
HV catho<strong>de</strong><br />
¤£¤£¤£¤£¤£¤£¤£¤£¤£¤£¤£¤£¤£¤£¤<br />
¢£¢£¢£¢£¢£¢£¢£¢£¢£¢£¢£¢£¢£¢£¢<br />
y<br />
¡<br />
Spacers<br />
Figure 5.33: Structure of Multistrip - Multigap RPC<br />
voltage box. They are staggered with an overlap of 3 strips between the front and back layer RPCs thus<br />
giving full geometrical coverage. A 16 strip ano<strong>de</strong> with a strip to gap ratio of 1.6/0.94 mm has been used<br />
to optimize the cluster width and impedance adaption. The <strong>de</strong>tector is read out via a multipin connection<br />
system [154], the sockets of which are sol<strong>de</strong>red directly on the ano<strong>de</strong> board and the input card of<br />
the Front-End-Electronic (FEE). The connection is ma<strong>de</strong> by a flexible and low pitch (0.8 mm) 50 Ohm<br />
multi-coaxial cable. The electronics is placed directly behind the <strong>de</strong>tector box; it comprises the FEE part<br />
with the preamplifier and discriminator and a TAC-based readout card (TAQUILA) which digitizes and<br />
acquires the data of 16 channels of one si<strong>de</strong> of a <strong>de</strong>tector (i.e. 10 of these systems are placed behind the<br />
box). 30 of such supermodules with in total 150 MRPCs and 4800 electronic channels will be used in<br />
the FOPI project.<br />
In-beam tests the <strong>de</strong>tectors have <strong>de</strong>monstrated time resolutions of σt ≤ 100 at rates up to 1 kHz/cm 2 , cf.<br />
Fig. 5.35; the non-gaussian component of the time distribution is below 2 %.<br />
The <strong>de</strong>pen<strong>de</strong>nce of the resolution on the applied high voltage is shown in Fig.5.36. The efficiency rises<br />
within a few kV to 99 %; at the same time the resolution improves constantly, levelling off at about 60<br />
ps. In addition the rate <strong>de</strong>pen<strong>de</strong>nce has been studied: Whereas no influence on the efficiency has been<br />
seen between 100 Hz/cm 2 and 1000 Hz/cm 2 , a <strong>de</strong>gradation of the time resolution from σt ≤ 60 to 90 ps<br />
is visible in the plot. Nevertheless one can conclu<strong>de</strong> that a multistrip counter can safely be operated at<br />
rates up to ∼ 1kHz/cm 2 with time resolutions below 100 ps.<br />
The second important issue of such a <strong>de</strong>tector is the multihit capability. For this purpose the shown<br />
module was placed in the final experimental position in FOPI in or<strong>de</strong>r to test its timing and efficiency<br />
performance in a realistic experimental multihit environment. As can be seen in Fig. 5.37 the efficiency<br />
drops form 99% to 85%, which simply reflects the fact that an active strip can not count a second hit<br />
within the same event. On the other hand the time resolution <strong>de</strong>teriorates from 80 to 100 ps for the<br />
second hit.<br />
As mentioned, the multistrip-multigap RPC is comparable to single cell or pad read-out <strong>de</strong>vices in terms<br />
of time resolution and counting rate performance. However, it has the further advantage of <strong>de</strong>livering<br />
position information (∼15 mm along the strips and ∼ 200-300 µm across the strips). This feature recommends<br />
such a type for large-area TOF systems where the particle <strong>de</strong>nsity leads to a negligible multihit
5.4. RPC <strong>de</strong>tector layout options 147<br />
Figure 5.34: Photograph of prototype counters. Five counters share the same gas volume box.<br />
Figure 5.35: Time resolution measured with multistrip prototype<br />
probability within the cluster. On the other hand the position resolution could be of interest for tracking<br />
also in the high rate enviroment.<br />
In further investigations it is planned to replace the present float glass electro<strong>de</strong>s (10 12 - 10 13 Ωcm) by<br />
float glass of lower resistivity in or<strong>de</strong>r to conserve the present perfomance also in a high counting rate<br />
environment. Such glasses would combine a low resistivity with the surface and evenness properties of
148 Resistive Plate Chambers (RPC)<br />
Efficiency (%)<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
100 ps →<br />
75 ps →<br />
60 ps →<br />
New wiggle<br />
Efficiency<br />
← 100 %<br />
← 95 %<br />
σ t - σ ts 0.8 ∼ 1 kHz / cm 2<br />
σ t - σ ts ∼ 0.1 kHz / cm 2<br />
σ t - σ ts ∼ 0.1 kHz / cm 2<br />
10 10.5 11 11.5<br />
Voltage (kV)<br />
12 12.5 13<br />
Figure 5.36: Time resolution and efficiency as function of applied voltage for a 8-gap counter<br />
Efficiency (%)<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
150 160 170 180 190 200 210 220 230 240 250 0<br />
HTYP<br />
Full-RPC<br />
Mini+RPC<br />
Figure 5.37: Double hit time resolution<br />
the standard window glass - at a higher prize of course. A possible solution is Glaverbel float glass [155]<br />
with a resistivity of the or<strong>de</strong>r of ∼10 10 Ωcm. Prototypes equipped with such glass electro<strong>de</strong>s have been<br />
built already; except for the glass they are i<strong>de</strong>ntical in size and structure to the standard counters, which<br />
should allow for a meaningful comparison of their features.<br />
Eff.<br />
σt-σts Eff.<br />
σt-σts 200<br />
180<br />
160<br />
140<br />
120<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
175<br />
150<br />
125<br />
100<br />
75<br />
50<br />
25<br />
σ t (ps)<br />
σ t (ps)
5.5. RPC electronics 149<br />
5.5 RPC electronics<br />
The time of flight measurement poses completely different <strong>de</strong>mands on the readout system than the other<br />
sub<strong>de</strong>tectors. The signal amplitu<strong>de</strong> is only of interest for time correction issues, so the <strong>de</strong>mands on the<br />
amplitu<strong>de</strong> resolution are relatively mo<strong>de</strong>st. The <strong>de</strong>mands on the time resolution however are extremely<br />
high. To get a sufficient kaon i<strong>de</strong>ntification efficiency, a time resolution better than 80 ps for the complete<br />
system is required. The event-rate per channel will be in the region of 100 kHz.<br />
To reach these timing requirements with the foreseen RPC <strong>de</strong>tector, a highly optimized time measurement<br />
electronic has to be <strong>de</strong>veloped. The experience with an existing readout system for a RPC <strong>de</strong>tector at<br />
<strong>GSI</strong> which is <strong>de</strong>scribed in section 5.5.1 could be a good starting point for this <strong>de</strong>velopment.<br />
5.5.1 FOPI-RPC-Electronics<br />
The major issue of the FOPI readout electronics is a ToF-resolution of σt ≤ 100 ps for the complete<br />
RPC-barrel consisting of 5000 channels. For this purpose a 16 channel Front-End-Electronic card (FEE)<br />
with a gain of α ∼ 200 at a bandwidth of δ f ∼ 1000 MHz was <strong>de</strong>veloped. This card has a single en<strong>de</strong>d<br />
50 Ω input stage and two differential (PECL) outputs per channel for timing and charge.<br />
The analog amplification is realized in three stages with a maximum gain factor of 10 per stage. Discrimination<br />
of the timing signal is also done on this FEE-card. With the mentioned gain of 200 at a low<br />
preamplifier noise (≤ 40 mV) we are able to measure primary RPC signals above 0.4 mV.<br />
The FEE-card is directly connected to the digitization part which contains a 16 channel common stop<br />
TAC-system followed by the readout part of the Data Acquisition (DAQ) [156]. This so called TAQUILAcard<br />
uses a single channel TAC-ASIC, <strong>de</strong>signed at <strong>GSI</strong>, which is based on a 0.8 µm CMOS-technology<br />
and <strong>de</strong>scribed in section 5.5.3.1. A typical time resolution between two channels on one TAQUILA<br />
board without a FEE card is about 10 ps. After correction of nonlinearities 7 ps RMS are reachable. The<br />
clock distribution over a distance of more than 10 m and up to three stages shows a RMS jitter of about<br />
5 ps.<br />
From pulser tests we <strong>de</strong>termined the system resolutions as follows [121]:<br />
System σt (ps)<br />
1 TAQUILA 12±2<br />
1 FEE + 1 TAQUILA 26±3<br />
2 FEE + 2 TAQUILA 33±4<br />
Subsystem Resolution (ps)<br />
FEE σFEE ≤ 18 ± 3<br />
TAC σTAC ≤ 12 ± 2<br />
Clock shift σCLK ≤ 15 ± 3<br />
Card variations σCARD ≤ 20 ± 3<br />
Sum σtotal ≤ 33 ± 4<br />
The results of this test showed that our new <strong>de</strong>veloped electronics has a multi-card resolution of σtotal ≤<br />
33±4 ps. From this we can conclu<strong>de</strong> that the electronics will not limit the timing measurement of the<br />
RPCs. One can <strong>de</strong>duce further that the clock cascading system, which was used for the first time in this<br />
test, has a minor effect on the total resolution (σCLK ≤ 15±3 ps).
150 Resistive Plate Chambers (RPC)<br />
5.5.2 Preamplifier/discriminator<br />
The Resistive Plate Chamber (RPC) is a gaseous <strong>de</strong>tector which can <strong>de</strong>liver very fast pulses when an<br />
ionization particle passes through. Typical characteristics of <strong>de</strong>tector signals for 50 Ohms impedance of<br />
the <strong>de</strong>tecting strip are presented in Table 5.2. The amplitu<strong>de</strong> pulse height spectrum is continuous with a<br />
peak value in the range of 2-5 mV.<br />
Parameter Value<br />
Rise Time 0.3 ns<br />
FWHM 1-2 ns<br />
Fall Time 0.3 ns<br />
Amplitu<strong>de</strong> (maximum) 30 mV<br />
Table 5.2: Typical characteristics of RPC signals for 50 Ohms impedance.<br />
REFE. SIGNAL<br />
START<br />
PARTICLE STOP DELTA T INFORMATION<br />
OUT<br />
DETECTOR AMPLIFIER DISCRIMINATOR TIME DIGITTZER<br />
Figure 5.38: A typical time measurement channel.<br />
Due to its fast response, the RPC Detector can be used for Time of Flight (ToF) measurements, and in<br />
this case, the associated electronics must process these fast and low amplitu<strong>de</strong> pulses with the minimum<br />
amount of supplementary time errors. A typical time measurement channel is shown in Fig. 5.38.<br />
The amplified and leading edge discriminated signal starts the time digitizer and the reference signal<br />
stops it. The output signal contains the useful information Δt, the time difference between Start and Stop<br />
signals. In our concept, the amplifier and discriminator blocks are inclu<strong>de</strong>d in the FEE ToF preamplifier<br />
unit.<br />
Fig. 5.39 shows the main error sources in time measurements:<br />
1. ‘WALK’ is the error due to amplitu<strong>de</strong> variation of the input signal. If the rise time is constant,<br />
the time nee<strong>de</strong>d to reach the threshold value level <strong>de</strong>pends of the input amplitu<strong>de</strong>; this error is<br />
systematical and can be corrected if the information regarding the amplitu<strong>de</strong> of the input pulses is<br />
known or if the discriminated signal has a width <strong>de</strong>pen<strong>de</strong>nt to Time over Threshold.<br />
2. ‘JITTER’ is a random error due to noise of amplifier. The peak-peak noise signal projected on<br />
time scale by the slope of signal give the jitter peak-peak value. To reduce the jitter, the ratio noise<br />
to slope must be as small as possible.<br />
The parasitic signals coupled from outsi<strong>de</strong> to measurement channel increase the jitter. To <strong>de</strong>crease this
5.5. RPC electronics 151<br />
UIN D<br />
VTHR<br />
UOUT D<br />
TSTOP<br />
"WALK"<br />
t<br />
t<br />
UIN D<br />
VTHR<br />
6SIGMA A<br />
UOUT D<br />
TSTOP<br />
6SIGMA T<br />
CLEAN SIGNAL APPLIED TO DISCRIMINATOR NOISY SIGNAL APPLIED TO DISCRIMINATOR<br />
Figure 5.39: A schematic illustration of walk and jitter errors.<br />
influence, the CBM FEE should be oriented to differential coupling to the <strong>de</strong>tector. A low cost solution<br />
can use twisted pair cable giving a mo<strong>de</strong>rate rejection of parasitic pick-up.<br />
The time over threshold walk correction can be favorable in the high integration case because it needs<br />
two time values instead of time and amplitu<strong>de</strong> information.<br />
We have some experience in FEE ToF from FOPI experiment, and in this moment we consi<strong>de</strong>r that the<br />
main initial technical parameters for CBM FEE ToF preamplifier are:<br />
• Input impedance: Differential with 50 Ohms to ground of each line<br />
• Gain: >100<br />
• Bandwidth: >1 GHz<br />
• Noise, related to input:
152 Resistive Plate Chambers (RPC)<br />
SIGMA [ps]<br />
100<br />
10<br />
1<br />
THR=100mV<br />
THR=12mV<br />
TIME RESOLUTION<br />
FEE1 Ch3<br />
1 10 100<br />
UINP [mV]<br />
Figure 5.40: ToF resolution as a function of signal amplitu<strong>de</strong>.<br />
5.5.3 Time Measurement and Digital Backend<br />
In the existing RPC readout system mentioned in section 5.5 a time to amplitu<strong>de</strong> converter (TAC) is the<br />
central element for the time measurement. It provi<strong>de</strong>s a time resolution of 7 ps between two channels<br />
on the same 16 channel readout PCB and about 20 ps between two channels on different PCBs. This<br />
time resolution would also be sufficient for CBM. An amplitu<strong>de</strong> correlated value, which is nee<strong>de</strong>d for<br />
walk correction of the measured time information, could be received from a simple time over threshold<br />
measurement.<br />
As a second variant, a Delay Locked Loop (DLL) based time measurement system will also be evaluated.<br />
5.5.3.1 Time Measurement by Using a Time to Amplitu<strong>de</strong> Converter<br />
Figure 5.41 shows the block diagram of a TAC based readout system for the CBM time of flight measurement.<br />
A TAC core is used to measure the time interval between a signal coming from the <strong>de</strong>tector<br />
and the next rising edge of a reference clock. Therefore the start input of the TAC is connected to the<br />
signal input and the stop input is connected to the reference clock.<br />
While the input signal is active, a time over threshold measurement is done by a simple integrator. The<br />
output signals of the time to amplitu<strong>de</strong> converter and of the time over threshold integrator are converted<br />
into digital values by two ADCs.<br />
For the self triggered DAQ, which is supposed to be used in the CBM experiment, a time stamp for every<br />
local event is nee<strong>de</strong>d. This time stamp is latched from a time stamp counter with the incoming <strong>de</strong>tector<br />
signal. All these values are stored in an event fifo memory. The DAQ-Interface reads the data from this<br />
fifo and arranges it in event messages that are sent to the DAQ network by a serial interface.<br />
The time to amplitu<strong>de</strong> converter core, which is shown in figure 5.42, is based on a distributed RC network<br />
which is fed via tristate drivers by a digital <strong>de</strong>lay chain. The <strong>de</strong>lay chain consists of a linear arrangement<br />
of <strong>de</strong>lay cells, which contains two inverting stages as shown in the dashed box on the right si<strong>de</strong>. For the<br />
first inverting stage a nand gate is used to provi<strong>de</strong> a common reset input.<br />
A start signal is latched in a d-flipflop and then traveling through the <strong>de</strong>lay chain and connecting one
5.5. RPC electronics 153<br />
Reset<br />
Start<br />
Stop<br />
Running<br />
In<br />
Clk<br />
High<br />
D<br />
D<br />
R<br />
5ns<br />
R<br />
Q<br />
Q<br />
Q<br />
Q<br />
Reset<br />
In<br />
Reset<br />
Start<br />
Stop<br />
Time over<br />
Threshold<br />
Running<br />
Latch<br />
Clock Epoche<br />
Reset Set<br />
Timestamp Counter<br />
Out<br />
Time to<br />
Amplitu<strong>de</strong> Out<br />
A<br />
D<br />
C<br />
A<br />
D<br />
C<br />
Event<br />
FIFO<br />
Write Read<br />
Controller<br />
Figure 5.41: block diagram of a TAC based readout system<br />
...<br />
D D D D D<br />
R R R R R<br />
C<br />
Out<br />
Delay cell<br />
Figure 5.42: principle diagram of the time to amplitu<strong>de</strong> converter core<br />
Reset<br />
tri state<br />
Out<br />
D<br />
A<br />
Q<br />
-<br />
I<br />
n<br />
t<br />
e<br />
r<br />
f<br />
a<br />
c<br />
e<br />
In Out<br />
resistor of the RC network after the other to supply voltage. So, while the signal is traveling through the<br />
<strong>de</strong>lay chain, the charge in the capacitor is increasing linearly with time.<br />
After a <strong>de</strong>lay of 5 ns, which prevents the TAC stopping directly after starting, a clock latch d-flipflop is<br />
enabled, so the next rising edge of the clock signal is stoping the conversion by setting all tri-state drivers<br />
to high ohmic state, so the RC network is disconnected from ground and supply voltage and the capacity<br />
will keep the current charge. With a second RC network which is complementary fed to the shown one<br />
a differential output could be provi<strong>de</strong>d to double the signal swing.<br />
The <strong>GSI</strong> TAC ASIC in the existing RPC readout is carried out in a 0.8µm CMOS process. To investigate<br />
the properties of a <strong>de</strong>lay chain in a later technology some simulations based on the AMS 0.35µm<br />
CMOS process have been done with a <strong>de</strong>lay cell that was optimized for minimum propagation <strong>de</strong>lay.<br />
To consi<strong>de</strong>r parasitic capacities also a layout for this cell was done (shown in figure 5.43) and extracted<br />
for the simulations. The simulations show that one could expect a <strong>de</strong>lay of 95 ps per <strong>de</strong>lay cell with a<br />
temperature coefficient of 0.18 %/K.<br />
For the clock frequency a value of 51.2 MHz leading to 512 (= 2 9 ) clock cycles in a 10µs period seems<br />
to be reasonable. In this case the <strong>de</strong>lay chain would have to cover the 19.5 ns clock time period, the 5 ns
154 Resistive Plate Chambers (RPC)<br />
Q<br />
MN6<br />
R RN In RNMP0<br />
R<br />
MN1<br />
MN0<br />
MN2<br />
Out<br />
MP1<br />
MP2<br />
Figure 5.43: layout of the simulated <strong>de</strong>lay cell<br />
MP3<br />
<strong>de</strong>lay and some safety margin, so at least a 25 ns coverage would be nee<strong>de</strong>d. This would lead to a <strong>de</strong>lay<br />
chain of 270 <strong>de</strong>lay cells.<br />
From the experience with the existing time to amplitu<strong>de</strong> converter and these first simulations it is obvious<br />
that also for the CBM RPC <strong>de</strong>tector a high precision TAC based time measurement is feasible, but there<br />
are still open questions which need some investigation in the next time.<br />
During operation of the TAC the current in the RC network reaches for some nano seconds up to 16 mA.<br />
This causes a voltage drop of several mV of the supply voltage on the chip. If more than one channel<br />
is implemented on the same die much care on <strong>de</strong>coupling the power supplies has to be taken to avoid<br />
interferences between the channels. However, the best way to do this is not clear yet.<br />
Noise, induced by the components of the digital backend on the chip, could also influence the performance<br />
of the time measurement. Due to the fact that this is correlated noise the choice of an optimized<br />
phase shift between TAC clock and digital clock could help keeping this influence small, but this has to<br />
be investigated.<br />
A very challenging part of the readout chip is the ADC. At a TAC time coverage of 25 ns for a sufficient<br />
time quantization a 12 bit ADC is nee<strong>de</strong>d. The <strong>de</strong>man<strong>de</strong>d conversion time is given by the typical event<br />
rate per channel. A conversion time of 1µs seems to provi<strong>de</strong> enough safety margin for a 100 kHz event<br />
rate.<br />
The next step should be the <strong>de</strong>sign of a test structure that should contain the following blocks:<br />
• At least two time to amplitu<strong>de</strong> converter cores to investigate crosstalk and power supply <strong>de</strong>coupling<br />
• A clock distribution network for clock skew and jitter measurement<br />
• A digital logic block with a programable clock phase shift for noise measurements<br />
• The first iteration of a 1µs 12 bit ADC<br />
Mo<strong>de</strong>rn <strong>de</strong>ep sub micron technologies provi<strong>de</strong> for complex digital logic several benefits like lower power<br />
consumption, higher speed, higher number of metal layers, etc. On the other hand process technologies<br />
with larger feature sizes are much cheaper and work with a higher core voltage which is very helpful for<br />
analog <strong>de</strong>signs like the time to amplitu<strong>de</strong> converter and the ADC. For this reason at the moment a medium<br />
scale technology like 0.35µm CMOS seems to be the most reasonable for the TAC implementation.
5.5. RPC electronics 155<br />
5.5.3.2 Time Measurement using a Delay Locked Loop based TDC<br />
A second <strong>de</strong>sign solution for ToF could be a time measurement based on a DLL (or PLL). The principle<br />
is shown in figure 5.44. The core of a DLL circuit is a <strong>de</strong>lay chain ma<strong>de</strong> up of N i<strong>de</strong>ntical <strong>de</strong>lay elements<br />
with adjustable <strong>de</strong>lay. A reference clock signal is injected into the <strong>de</strong>lay chain. The <strong>de</strong>lays are adjusted<br />
by a regulation loop such that the output signal exactly coinci<strong>de</strong>s with the reference clock. Each <strong>de</strong>lay<br />
element is guaranteed in this way to have a <strong>de</strong>lay of 1/Nth of the reference clock period. A PLL uses<br />
a ring oscillator ma<strong>de</strong> up of N i<strong>de</strong>ntical <strong>de</strong>lay elements with adjustable <strong>de</strong>lay. One element must be<br />
inverting so that an oscillation with a period of 2N is maintained. The frequency of this oscillation (or a<br />
down-scales signal with lower frequency) is locked to a reference clock. Both systems offer the advantage<br />
of an absolute calibration of the time steps in all channels w.r. to the reference clock. Upon arrival of a<br />
hit, the status of the <strong>de</strong>lay elements is latched and <strong>de</strong>co<strong>de</strong>d. By implementing a suited buffering scheme,<br />
the circuit is immediately ready to process a new hit. A second advantage of this approach is therefore<br />
the very small <strong>de</strong>ad time after a hit.<br />
Figure 5.44: Block diagram of a Delay Lock Loop<br />
In general the achievable resolution for a DLL is limited by the minimum gate <strong>de</strong>lay which is given by<br />
the used technology. The resolution for a simple N element DLL scheme is <strong>de</strong>termine by the intrinsic<br />
<strong>de</strong>lay of a basic cell, consisting of 2 inverter stages, with Tn = T<br />
N , were T is the system clock period and<br />
N the number of basic cells. A rough estimation concerning this intrinsic <strong>de</strong>lay for the UMC 0.18µm<br />
process yields about 70ps for one <strong>de</strong>lay element. Due to the extremely high receivables for the time<br />
resolution of the RPC <strong>de</strong>tector different DLL based schemes are possible.<br />
Several <strong>de</strong>sign variants have been proposed to optimize among the parameters speed, tuning range, linearity,<br />
power consumption, layout area etc. Some <strong>de</strong>sign aspects are:<br />
• Use single en<strong>de</strong>d or differential <strong>de</strong>lay elements. Single en<strong>de</strong>d implementations often use currentstarved<br />
inverters. To keep the <strong>de</strong>lay of rising and falling edges exactly equal, units of two such<br />
inverters form one <strong>de</strong>lay element. This increases the minimal <strong>de</strong>lay and <strong>de</strong>gra<strong>de</strong>s the time resolution.<br />
Differential logic is very popular for these circuits, because the inverse of the signal is<br />
readily available so that only one differential circuit per <strong>de</strong>lay stage is required. As an example,<br />
we have measured a <strong>de</strong>lay of < 150ps per stage at a power consumption of ≈ 100µW in a 0.35µm<br />
technology. Constant current logic produces much less spikes in the supply lines than CMOS so<br />
that a better performance my be achieved.<br />
• An improved time resolution can be obtained by running an array of DLLs [157] with controlled<br />
phase shifts (see Fig. 5.45). Here the time resolution is <strong>de</strong>termined by the number of <strong>de</strong>lay elements
156 Resistive Plate Chambers (RPC)<br />
N and the counts of M DLL’s with Tm = T<br />
N ˙M .<br />
¢¡¤£¤¡¤¥¤¡¤¦¤§¤¡<br />
§¤ ¨¤©¤<br />
¤¤¤¤¤¦ ¤©<br />
©¤¤¢© ¡¢¡¤¦¤¤<br />
¤¡ ©¤¤¢© ¡¢¡¤¦¤¤<br />
¤¡<br />
¢¤¦¤<br />
¢¡¤¤¤¤¤¡¤¥<br />
Figure 5.45: An array of Delay Locked Loops<br />
¤ £ ¢¥¤¥<br />
¤¤¢<br />
• The <strong>de</strong>lay line taps or the input signal can be <strong>de</strong>layed by small time steps to get a sub-unit-<strong>de</strong>lay<br />
resolution (Fig. 5.46). By <strong>de</strong>termining in which sample the rising edge of the system clock appears<br />
on a <strong>de</strong>lay cell output one can calculate the arrival time of the event with the resolution of the<br />
sample interval.<br />
• Analog methods could be used to interpolate between successive transitions.<br />
Several advantages of the DLL based TDC should be pointed out: At first the structure allows for self calibration<br />
to compensate temperature and process variations. A second point is a <strong>de</strong>ad time free operation<br />
that allows to cope high event rates.<br />
The basic building blocks required for the realization of this concept (controllable <strong>de</strong>lays, interpolation,<br />
frequency division, phase comparison, charge pump for regulation, latches, r/o logic) will be evaluated<br />
in a first step. Feasible implementations to achieve the required specifications will then be <strong>de</strong>signed.<br />
5.6 TOF <strong>de</strong>tector test facility<br />
Detectors tests need minimum ionizing particles (MIPs) in most cases, either protons or secondary beams<br />
(e.g. pions) which are focussed directly on the <strong>de</strong>tectors; as an alternative ejectiles from nuclear reactions<br />
can be used. Usually the intrinsic time resolution of the beam is quite broad. Hence in most beam tests<br />
reference counters are nee<strong>de</strong>d; i<strong>de</strong>ally they should have time resolutions comparable or better than that<br />
of the investigated counter itself. The measured time has then to be corrected for the resolutions of<br />
electronics and reference counters; moreover the electronic walk has to be corrected for. The latter is<br />
even more critical in case the reference counters exhibit an electronic walk, too.
5.6. TOF <strong>de</strong>tector test facility 157<br />
¢¡¤£¤¡¤¥¤¡¤¦¤§¤¡<br />
§¤ ¨¤©¤<br />
¤¤¤¤¤¦¤ ©<br />
<br />
<br />
<br />
<br />
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<br />
<br />
¢¡¤¤¤¤¤¡¤¥<br />
<br />
¢¡¤¤¤¤¤¡¤¥<br />
<br />
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<br />
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<br />
Figure 5.46: Time interpolation circuit [158]<br />
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¢¤¤¡¤¤¡¤¤¡¤§¤ ¥<br />
If, however, the test beam itself has a very good time structure, one may avoid in an elegant way many of<br />
the mentioned problems by referencing the test <strong>de</strong>tector against the beam signal itself. This is the case<br />
at the Rossendorf electron accelerator ELBE which provi<strong>de</strong>s electrons up to 40 MeV in beam packets<br />
with a time spread of better than 10 ps. Moreover, electrons with energies of a few 10 MeV have specific<br />
energy losses very similar to MIPs, thus being suited to test the counter behaviour in terms of pulse<br />
height, time resolution and <strong>de</strong>tection efficiency.<br />
coinci<strong>de</strong>nce rate (Hz)<br />
100<br />
90<br />
80<br />
70<br />
60<br />
50<br />
40<br />
30<br />
20<br />
10<br />
0<br />
15 MeV e - on Al (18μm), I=22nA<br />
-20 0 20 40 60 80<br />
angle relative to 45 <strong>de</strong>g<br />
Figure 5.47: Background distribution relative to 45 <strong>de</strong>grees
158 Resistive Plate Chambers (RPC)<br />
The challenge of this elegant method is to provi<strong>de</strong> electron beams of intensities down to ∼ 1 kHz/cm 2 .<br />
Currently, beam diagnostics at ELBE requires a minimum beam intensity of ∼ 1µA or ∼ 1 × 10 10<br />
Hz/cm 2 . In tests intensities down to ∼ 1 nA have been reached, but this rate is still too high for inbeam<br />
<strong>de</strong>tector tests. While it is conceivable that even lower intensities might be available in the future,<br />
the present solution is to reduce the intensities by scattering from a target. In this way one can reduce<br />
the intensity to any <strong>de</strong>sired value; at the same time one can also vary the size of the irradiated spot on the<br />
<strong>de</strong>tector.<br />
First parasitic beam tests were performed in the <strong>de</strong>dicated radiation cave at ELBE. A 17 MeV electron<br />
beam was scattered off a thin Al foil. Electrons were <strong>de</strong>tected un<strong>de</strong>r 45 <strong>de</strong>grees scattering angle. The<br />
background distribution was scanned with respect to the main scattering direction, as shown in Fig. 5.47.<br />
A second test will use scintillators with very good time resolution as they have been used in RPC tests in<br />
other laboratories.<br />
The experimental environment has been prepared as a general setup for in- and external users (hardware,<br />
gas supply/mixing systems in the cave and adjacent laboratories, cable connections, etc.). A second<br />
irradiation station for <strong>de</strong>tector tests is in preparation in another cave.<br />
5.7 Infrastructure<br />
The infrastructural requirements are largely <strong>de</strong>fined by the power needs of the fast electronics operated<br />
on the <strong>de</strong>tector. A conservative estimates is 1 W/channel of thermal power generation, e.g. 80kW of<br />
power have to be cooled by a common system. The gas system is consi<strong>de</strong>red an integral part of the<br />
<strong>de</strong>tector.<br />
Mounting tools (crane) have to be installed to facilitate mounting and servicing of <strong>de</strong>tector modules at a<br />
height of 11 m above ground.
5.8. Working packages and milestones 159<br />
5.8 Working packages and milestones<br />
The main working packages and the anticipated time periods are listed in Table 5.3. The main milestone<br />
are the Technical proposal in 2006 and the Technical Design Report for the RPC subsystem that should<br />
be doable by end 2009.<br />
activity time period<br />
Material tests with single cell RPCs 2005 - 2006<br />
Optimisation of operation parameters (temperature, gas mixture,<br />
HV, ... )<br />
2005 - 2006<br />
Test of Pad/Multipad/Strip/Multistrip Layouts 2005 - 2006<br />
Design and test of FEE prototypes 2005 - 2006<br />
Design and test of TDC prototypes 2005 - 2006<br />
Performance simulations with global tracking 2005<br />
MC simulation for optimisation of wall layout 2006<br />
technical proposal end 2006<br />
<strong>de</strong>sign and test of <strong>de</strong>tector modules 2007 - 2009<br />
<strong>de</strong>sign of support structure 2008 - 2009<br />
<strong>de</strong>sign and test of discriminator 2007 - 2009<br />
<strong>de</strong>sign and test of digital readout 2007 - 2009<br />
final choice of ASIC technology 2009<br />
technical <strong>de</strong>sign report end 2009<br />
production, installation, tests 2010 - 2012<br />
5.9 Cost estimate<br />
Table 5.3: RPC future planning<br />
At this time the cost estimate for the RPC subsystem can only be based on scaling arguments from<br />
existing RPC system <strong>de</strong>signs [120,121]. Due to unknown choices of material and electronics technology,<br />
large uncertainties exist. Therefore in Table 5.4 ranges for the various cost items are given for the final<br />
<strong>de</strong>tector components.<br />
Item Cost (kEuro)<br />
Glass plates 250 - 1000<br />
Cables 250 - 400<br />
Detector modules 500 - 700<br />
Mechanical support 200 - 300<br />
FEE electronics 1000 - 1500<br />
Digitizer and clock 2000 - 2600<br />
Gas system 150 - 200<br />
Services (LV/HV/cooling) 600 - 700<br />
Total 5000 - 7400<br />
Table 5.4: RPC cost estimate
160 Resistive Plate Chambers (RPC)
6 Electromagnetic Calorimeter (ECAL)<br />
6.1 Design consi<strong>de</strong>rations<br />
The calorimeter system of CBM will be used for the i<strong>de</strong>ntification of electrons and photons and the<br />
precise measurement of their momenta. Been used together with RICH and TRD, the electromagnetic<br />
calorimeter (ECAL) will significantly contribute to the particle i<strong>de</strong>ntification due to its high capability to<br />
discriminate photons, electrons and hadrons.<br />
The ECAL will also allow a reconstruction of neutral mesons <strong>de</strong>caying in their photonic <strong>de</strong>cay channels.<br />
The precise measurement of mass and width of short-living mesons (ω(782), η ′ , f2(1270), etc) will shed<br />
light on the chiral symmetry restoration which is expected to occur in <strong>de</strong>nse nuclear matter. A measurement<br />
of the π 0 spectrum is important to study the <strong>de</strong>pen<strong>de</strong>nce of the particle yield on thermodynamical<br />
parameters of nuclear matter. The measurement of direct photons provi<strong>de</strong>s a signal from the early fireball.<br />
Elliptic and directed flow of π 0 measured by the ECAL will be used for collision geometry and<br />
collective phenomena studies.<br />
The fast calorimeter signal could also provi<strong>de</strong> an online selection of rare events, where electrons or<br />
photons are produced with a high transverse momentum. The physics program requires a very effective<br />
particle i<strong>de</strong>ntification, high energy and spatial resolution for the reconstruction of short lived heavy<br />
particles (J/ψ, D, ρ mesons) via their <strong>de</strong>cay products, and very fast response to operate at a maximum<br />
ion-ion interaction rate of about 10 MHz.<br />
The physics program imposes the following requirements on the ECAL:<br />
• large acceptance (θ < 26 ◦ ) and phase space coverage leading to a large sensitive surface of the<br />
<strong>de</strong>tector;<br />
• good energy resolution of ∼ 5%/ √ E (GeV) and a few mm spatial resolution in a wi<strong>de</strong> energy<br />
range up to 40 GeV are essential to ensure effective reconstruction of photons and π 0 s;<br />
• high radiation resistance.<br />
The large angular acceptance of the CBM experiment and the distance nee<strong>de</strong>d for precise time-of-flight<br />
<strong>de</strong>tector results in a large area calorimeter system located immediately after the wall of RPC <strong>de</strong>tector.<br />
Optimizing the cost-to-performance ratio we propose to employ the “shashlik” technology of sampling<br />
scintillator-lead structure readout by plastic wavelength shifting fibers. This technology has been<br />
successfully <strong>de</strong>veloped by the PHENIX collaboration at BNL [159], the HERA-B collaboration [160]<br />
at DESY, RD36 [161] and LHCb [162] collaborations at CERN. Recently, an extremely good energy<br />
resolution of ∼ 3%/ √ E (GeV) has been <strong>de</strong>monstrated for “shashlik” modules with 300 sampling layers<br />
[163] [164]. Adopting “shashlik” technology for CBM environment certainly requires consi<strong>de</strong>rable<br />
modifications and extensive R&D studies.<br />
The energy resolution of the calorimeter will directly affect the sensitivity of our experiment to prompt<br />
photons and π 0 s. Taking into account that the energy range of particles produced in ion-ion collisions at<br />
CBM is rather soft, we have to <strong>de</strong>crease the thickness of lead plates, thus minimizing the sampling term<br />
in the energy resolution. At the same time the very high multiplicity of about 1200 charged and neutral<br />
particles per heavy ion (Au+Au) central collision at 25 AGeV has to be taken into account (see also<br />
Fig. 6.1). Overlapping showers from neighbour tracks consi<strong>de</strong>rably dilute the intrinsic energy resolution<br />
and i<strong>de</strong>ntification power of a calorimeter with poor transversal segmentation (or large Moliere radius).<br />
There are only two possibilities to minimize this effect: <strong>de</strong>creasing the Moliere radius via <strong>de</strong>creasing of<br />
161
162 Electromagnetic Calorimeter (ECAL)<br />
Hits / cm 2<br />
Hits / cm 2<br />
10 -1<br />
10 -2<br />
10 -3<br />
10 -4<br />
10 -5<br />
10 -1<br />
10 -2<br />
10 -3<br />
10 -4<br />
10 -5<br />
10 2<br />
10 2<br />
Hadrons<br />
Photons<br />
Electrons<br />
Hadrons<br />
Photons<br />
Electrons<br />
A<br />
B<br />
X, cm<br />
X, cm<br />
Figure 6.1: The number of particles<br />
entering the calorimeter per cm 2<br />
per ion-ion collision along x axis; (A)<br />
for Minimum Bias events and (B) for<br />
central events (b < 3 fm). Electrons<br />
and photons have energies above 1 MeV,<br />
hadrons have energies above 10 MeV.<br />
the scintillator plates thickness or moving the calorimeter further away from the target, which certainly<br />
would increase the overall <strong>de</strong>tector dimensions, complexity and cost.<br />
Discrimination between electrons (positrons) and hadrons in electromagnetic calorimeter is conveniently<br />
achieved by comparison of <strong>de</strong>posited energy with the measured track momentum. In CBM this method<br />
suffers from very high <strong>de</strong>nsity of incoming particles. Further discrimination power could be obtained<br />
by using shower-shape information. Therefore we have studied the possibility to put a thin (1.5 X0)<br />
preshower <strong>de</strong>tector in front of the calorimeter. Time information from ECAL could provi<strong>de</strong> additional<br />
suppression of heavy hadrons.<br />
Longitudinal segmentation could also be useful for µ i<strong>de</strong>ntification. The discrimination of π mesons<br />
is based on the fact that muon energy <strong>de</strong>position is directly proportional to the width of calorimeter<br />
segments while the pion energy <strong>de</strong>position fluctuates significantly. A possibility of µ/π separation using<br />
the combined information from the ECAL and a hadron catcher is being studied [165]. In this document<br />
we present the results of performance studies for a system consisting of preshower and electromagnetic<br />
calorimeter.<br />
6.2 Simulations<br />
The main aim of this chapter is to <strong>de</strong>monstrate the e/π separation achievable with the CBM calorimeter<br />
system. Feasibility studies of the photon reconstruction and muon i<strong>de</strong>ntification are in progress.<br />
The <strong>de</strong>nsities of incoming particles at the front face of the calorimeter system are shown in Fig. 6.1 as a<br />
function of the distance from the beam pipe. The hit <strong>de</strong>nsity varies over the calorimeter surface by two
6.2. Simulations 163<br />
ECAL<br />
region Inner Middle Outer<br />
Cell size 3x3 cm 2 6x6 cm 2 12x12 cm 2<br />
No. of channels 11712 6448 5592<br />
Dynamic range 0 - 40 GeV 0 - 30 GeV 0 - 20 GeV<br />
Average e energy (from J/ψ) 11 GeV 8 GeV 5 GeV<br />
ADC 12 bits 12 bits 12 bits<br />
Table 6.1: Parameters of the CBM electromagnetic calorimeter.<br />
or<strong>de</strong>rs of magnitu<strong>de</strong>. To minimize the number of readout channels, the calorimeter should have a variable<br />
granularity. It is composed of inner, middle and outer regions with transverse segmentation adjusted<br />
to ensure an average 10 % occupancy per calorimeter cell for central Au-Au collisions at 25 AGeV. The<br />
overall layout of the ECAL regions is shown in Fig. 6.2. In the outer region a calorimeter module is<br />
read out by a single photo-<strong>de</strong>tector. Modules in the middle region are divi<strong>de</strong>d in 4 light isolated cells<br />
(6x6 cm 2 ). In the innermost region modules are divi<strong>de</strong>d in 16 light isolated cells (3x3 cm 2 ) which corresponds<br />
to the 3 cm Moliere radius in the lead-plastic structure with 1:1 volume ratio. The calorimeter<br />
covers 12 × 9.6m 2 area and weights about 200 tons. Table 6.1 summarizes the parameters of the three<br />
calorimeter regions.<br />
400<br />
300<br />
200<br />
100<br />
0<br />
-100<br />
-200<br />
-300<br />
-400<br />
-600 -400 -200 0 200 400 600<br />
Figure 6.2: Lateral segmentation of the CBM ECAL (Numbers in cm). One block stands for 12x12 cm 2 module.<br />
The overall number of channels is 23752.<br />
The working conditions of the CBM calorimeter are illustrated in Fig. 6.3. The 2D maps of all three<br />
ECAL sections show the probability to find a fired cell (i.e. cell with energy <strong>de</strong>position above the certain<br />
threshold) per one central Au-Au collision. Assuming in<strong>de</strong>pen<strong>de</strong>nt energy <strong>de</strong>positions in neighbour cells,<br />
thresholds are chosen to insure less than 5%/ √ E (GeV)/ √ #cells contribution to the average energy of<br />
electrons (positrons) from J/ψ <strong>de</strong>cays (50 MeV for outer section, 60 MeV for middle section and 80 MeV
164 Electromagnetic Calorimeter (ECAL)<br />
row number<br />
row number<br />
row number<br />
80<br />
60<br />
40<br />
20<br />
0<br />
100<br />
75<br />
50<br />
25<br />
0<br />
100<br />
75<br />
50<br />
25<br />
0<br />
Central Au-Au collisions at 25 AGeV<br />
0 20 40 60 80 100<br />
column number<br />
Outer section<br />
0 20 40 60 80 100<br />
column number<br />
Middle section<br />
0 20 40 60 80 100 120<br />
column number<br />
Inner section<br />
0.5<br />
0.45<br />
0.4<br />
0.35<br />
0.3<br />
0.25<br />
0.2<br />
0.15<br />
0.1<br />
0.05<br />
0<br />
0.5<br />
0.45<br />
0.4<br />
0.35<br />
0.3<br />
0.25<br />
0.2<br />
0.15<br />
0.1<br />
0.05<br />
0<br />
0.5<br />
0.45<br />
0.4<br />
0.35<br />
0.3<br />
0.25<br />
0.2<br />
0.15<br />
0.1<br />
0.05<br />
0<br />
Figure 6.3: Probability to find a fired cell in all ECAL sections for central Au-Au collisions.
6.2. Simulations 165<br />
for inner section). In spite of the relatively large number of channels, the occupancies in the innermost<br />
region of all calorimeter sections are rather high.<br />
6.2.1 Acceptance<br />
The acceptance of the ECAL for <strong>de</strong>tection of two particles, J/ψ → e + e − and ω(782) → π 0 γ, as a function<br />
of transverse momentum pT and rapidity y is shown in Fig.6.4. The mesons J/ψ and ω(782) are assumed<br />
, GeV/c<br />
T<br />
p<br />
5<br />
4.5<br />
4<br />
3.5<br />
3<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
0<br />
0 1 2 3 4 5 6<br />
y<br />
1<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
0<br />
, GeV/c<br />
T<br />
p<br />
0<br />
0 1 2 3 4 5 6<br />
y<br />
Figure 6.4: Geometrical acceptance for J/ψ → e + e − (left) and ω(782) → π 0 γ (right) as a function of pT and y.<br />
as <strong>de</strong>tected if all their <strong>de</strong>cay products hit the ECAL surface.<br />
The ECAL geometry can be optimized for a particular reaction. Acceptance of the ECAL for J/ψ → e + e −<br />
<strong>de</strong>cay as a function of the CBM calorimeter area is presented in Fig. 6.5. The ECAL has a rectangular<br />
shape with the X dimension 20 % larger than the Y dimension to account for a bending of charged particles<br />
in the vertical magnetic field. Following the J/ψ reconstruction procedure, the transverse momentum<br />
of electrons (positrons) is required to be higher than 1 GeV/c.<br />
6.2.2 e/π separation<br />
Our studies on e/π separation are based on the attempt to use only the information of the electromagnetic<br />
calorimeter. The method used in the simulation is the following:<br />
• Use the track information to predict the impact point of a particle into the calorimeter. Construct<br />
the 3×3 cluster of the calorimeter cells closest to the found impact point, checking that the central<br />
cell has a maximal energy <strong>de</strong>position.<br />
• Choose the 2 × 2 matrix with the maximal energy within the found cluster.<br />
• Require the energy of the maximal 2 × 2 matrix to be larger than a certain fraction of track momentum.<br />
Tune this cut to ensure the same electron i<strong>de</strong>ntification efficiency (95 %) for different<br />
momentum intervals.<br />
• Check the cluster shape, requiring the contribution of the maximal 2 × 2 matrix to the total cluster<br />
energy to be greater than a certain fraction. Tune this cut to ensure the same electron i<strong>de</strong>ntification<br />
efficiency (90 %) for different momentum intervals.<br />
5<br />
4.5<br />
4<br />
3.5<br />
3<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
1<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
0
166 Electromagnetic Calorimeter (ECAL)<br />
acceptance<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
Acceptance of the CBM ECAL<br />
40 50 60 70 80 90 100 110 120<br />
ECAL area, m 2<br />
Figure 6.5: Geometrical acceptance<br />
for J/ψ → e + e − as a function of ECAL<br />
area.<br />
Fig. 6.6 shows the ratio of ECAL energy in a 2 × 2 matrix to track momentum for 4 GeV/c electrons<br />
and pions entering the middle section of the calorimeter. The tail above unity is explained by energy<br />
contributions leaking in from neighbor tracks. This is the main factor limiting the e/π separation power<br />
of the CBM ECAL.<br />
Table 6.2 summarizes the results on e/π discrimination in the three sections of the CBM calorimeter<br />
for central Au-Au collisions. The π meson suppression, which is the ratio of accepted pions to pions<br />
misi<strong>de</strong>ntified as electrons, is shown for different momentum intervals for central events and single particles.<br />
The very high particle <strong>de</strong>nsity <strong>de</strong>creases the i<strong>de</strong>ntification power of the calorimeter, in particular<br />
for low momentum particles.<br />
ECAL<br />
region Inner Middle Outer<br />
65 (< 8 GeV) 27 (< 5 GeV) 13 (< 5 GeV)<br />
Central 141 (8-13 GeV) 69 (5-8 GeV) 35 (> 5 GeV)<br />
events 153 (>13 GeV) 250 (> 8 GeV)<br />
single >250 (3-8 GeV) >200 (3-5 GeV) 150 (< 5 GeV)<br />
particles >500 (>8 GeV) >300 (>5 GeV) >300 (> 5 GeV)<br />
Table 6.2: π meson suppression for three regions of the CBM ECAL obtained using ECAL information only.<br />
The corresponding energy range is given in brackets.
6.2. Simulations 167<br />
arbitrary units<br />
arbitrary units<br />
120<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
0 0.2 0.4 0.6 0.8 1 1.2 1.4<br />
electrons<br />
E calorimeter / P tracker<br />
500<br />
400<br />
300<br />
200<br />
100<br />
0<br />
0 0.2 0.4 0.6 0.8 1 1.2 1.4<br />
pions<br />
E calorimeter / P tracker<br />
Figure 6.6: Ratio of ECAL cluster<br />
energy to track momentum for 4 GeV/c<br />
electrons (upper panel) and π mesons<br />
(lower panel).<br />
Calorimeter clusters consisting of 9 cells with almost 50 % probability have energy contributions from<br />
more than one particle (for central events). A preshower <strong>de</strong>tector, located in front of the electromagnetic<br />
calorimeter, could significantly improve the suppression of π mesons. We studied a preshower <strong>de</strong>tector<br />
consisting of a 1.5 X0 lead absorber and 10 mm thick plastic tiles with a transverse granularity following<br />
the one chosen for ECAL. Typical signals observed in the preshower <strong>de</strong>tector for electrons and pions in<br />
central Au-Au collisions are shown in Fig. 6.7. Most of the electrons are arriving at the entrance of the<br />
calorimeter system together with radiative photons emitted in the material of TRD and RPC. Interacting<br />
in the preshower absorber, these particles produce large (10-15 MIP) signal in plastic tiles. Pions are<br />
mostly registered as MIP particles. The preshower cell is chosen by propagating the reconstructed track<br />
to the calorimeter system entrance. The preshower signal is required to be larger than a certain threshold<br />
which <strong>de</strong>pends on the track momentum to guarantee the same electron i<strong>de</strong>ntification efficiency (85 %)<br />
for different momentum intervals. Table 6.3 summarizes our final results on e/π discrimination in three<br />
sections of the CBM calorimeter system for central Au-Au collisions.<br />
ECAL<br />
region Inner Middle Outer<br />
117 (< 8 GeV) 48 (< 5 GeV) 41 (< 5 GeV)<br />
Central 311 ( 8-13 GeV) 203 (5-8 GeV) 163 (> 5 GeV)<br />
events 600 (>13 GeV) 580 (> 8 GeV)<br />
Table 6.3: π meson suppression for three regions of the CBM calorimeter system using combined ECAL and<br />
preshower information. The corresponding energy range is given in brackets.
168 Electromagnetic Calorimeter (ECAL)<br />
arbitrary units<br />
arbitrary units<br />
300<br />
250<br />
200<br />
150<br />
100<br />
50<br />
4500<br />
4000<br />
3500<br />
3000<br />
2500<br />
2000<br />
1500<br />
1000<br />
0<br />
0 5 10 15 20 25 30 35 40 45 50<br />
electron signal in preshower<br />
MIPs<br />
500<br />
0<br />
0 5 10 15 20 25 30 35 40 45 50<br />
pion signal in preshower<br />
MIPs<br />
6.3 Technology<br />
Figure 6.7: Preshower signals for<br />
electrons and pions.<br />
The <strong>de</strong>sign proposed for the CBM ECAL is based on the technology <strong>de</strong>veloped for other electromagnetic<br />
calorimeters built in 1986–2004 for the experiments PHENIX, HERA-B, LHCb and KOPIO. The<br />
calorimeter will be of the sampling type, i.e. will be ma<strong>de</strong> of layers of metallic and scintillator tiles. The<br />
scintillator is ma<strong>de</strong> of polystyrene doped by 1.5% pTP and 0.04% POPOP. Typical physical properties<br />
of the scintillator of 1.5 mm thickness produced in the Institute for High Energy Physics [164, 166] are<br />
shown in Table 6.4.<br />
Light output Attenuation length Light yield of MIP, Main <strong>de</strong>cay λmax<br />
(%) Anthracene cm p.e. per tile time (ns) (nm)<br />
54 ± 6 6.8 ± 0.5 7.1 ± 0.3 2 420<br />
Table 6.4: Typical physical properties of the scintillator for ECAL modules.<br />
The requirement to have a smaller Moliere radius with the same energy resolution leads to the need of<br />
thinner scintillator tiles. Available facilities at IHEP and Vladimir allow to produce tiles with variable<br />
thickness (see examples in Fig. 6.8 and Fig. 6.9) from 10 mm to 0.5 mm. A test “shashlik” module has<br />
been constructed from 280 alternative layers of 0.5 mm thick scintillator and 0.5 mm thick lead tiles. This<br />
module has been extensively studied at a 100 GeV/c muon beam in or<strong>de</strong>r to measure the light yield and<br />
uniformity of light collection. The light yield was measured to be ∼ 5000 photons per GeV. The maximal<br />
variation of response as a function of entry point coordinate is better than 40 % as shown in Fig. 6.10.<br />
This variation is caused by fiber to fiber nonuniformity of light collection efficiency. A substancial
6.3. Technology 169<br />
improvement is expected for showering electrons and inclined tracks. Nevertheless we plan a <strong>de</strong>dicated<br />
R&D to further improve uniformity of response for very thin plastic plates.<br />
Figure 6.8: Sample of scintillator tiles produced in<br />
IHEP.<br />
Figure 6.9: Set of different plastic and lead tiles produced<br />
in Vladimir.<br />
Scintillator tiles are produced with injected mold technology. The machine for the automatic processing<br />
using this technology installed in IHEP is shown in Fig. 6.11. A smaller Moliere radius can also be<br />
achieved by using an absorber with a smaller radiation length. As an alternative to conventionally used<br />
lead, tungsten and uranium absorbers can be consi<strong>de</strong>red for the CBM calorimeter. These materials have<br />
1.7-times better radiation length than lead. Tungsten is much har<strong>de</strong>r in mechanical processing than lead<br />
or uranium, and research is nee<strong>de</strong>d to <strong>de</strong>velop a relatively cheap technology to treat it.<br />
ADC counts<br />
140<br />
130<br />
120<br />
110<br />
100<br />
90<br />
left bor<strong>de</strong>r<br />
-25 -20 -15 -10 -5 0 5 10 15 20 25<br />
right bor<strong>de</strong>r<br />
local X(mm)<br />
Figure 6.10: Energy response of the<br />
test module for 100 GeV/c muons as a<br />
function of the impact point position<br />
along a 1 mm slice passing through the<br />
row of fibers.
170 Electromagnetic Calorimeter (ECAL)<br />
6.4 Detector construction<br />
Figure 6.11: Injected mold machine<br />
for the automatic processing of the scintillator<br />
tiles.<br />
The geometry of the calorimeter system implemented into the Monte Carlo simulation package (see<br />
section 6.2), represents the wall of the calorimeter modules. As an example, Fig. 6.12 shows the LHCb<br />
electromagnetic calorimeter. The advantage of this geometry is an inherent simplicity of construction<br />
and good homogeneity of the sensitive surface which results in the minimum of <strong>de</strong>ad zones between the<br />
calorimeter modules. The wall consists of three zones with different transverse cell size as <strong>de</strong>scribed in<br />
section 6.2.<br />
Possible modifications of the above <strong>de</strong>scribed solution, including the choice of the module granularity,<br />
dimensions, number of ECAL zones as well as a use of a quasi-projective geometry for the sub-parts of<br />
ECAL wall, is subject of further optimization.<br />
The preshower <strong>de</strong>tector could be either constructed as a separate wall, with a granularity corresponding<br />
to the ECAL, or integrated into the ECAL module. The latter option is our baseline solution. The<br />
whole calorimeter system can be put onto a separate movable platform to ease installation and access for<br />
maintenance.<br />
6.4.1 Module <strong>de</strong>sign<br />
Each calorimeter module combines a preshower and ECAL parts, readout from the forward and rear si<strong>de</strong>s<br />
respectively, all physically integrated into a single module box. The preshower elements are 8.4 mm thick<br />
lead (1.5 X0) and scintillator pads. A groove in the scintillator pad houses the helical WLS fiber which<br />
collect the light. The light from both WLS fiber ends is sent to SiPM located at the front surface of the<br />
calorimeter module. A light yield of about 20 p.h.e. in response to minimum ionizing particles has been<br />
<strong>de</strong>monstrated with a 5 mm thick scintillator pad [167].<br />
The ECAL part of the module has a periodical structure along z-axis of metal absorber and scintillator<br />
tiles. Absorbers can be ma<strong>de</strong> of lead or other heavy metals (tungsten, uranium), and the actual choice<br />
of the absorber will <strong>de</strong>pend on the physics requirements. Scintillator tiles are wrapped by 60µm-thick<br />
tyvek from both si<strong>de</strong>s for better diffusive light reflection. Scintillating light is collected by optic fibers<br />
KURARAY KY11(200)M-DC doped by the wave-length shifter (WLS). This type of the fibers has one<br />
of the best light attenuation length and elasticity. The fibers penetrate all the layers with the surface<br />
<strong>de</strong>nsity about 0.9 fibers/cm 2 which provi<strong>de</strong>s a good homogeneity of the light collection. WLS-fibers are
6.4. Detector construction 171<br />
Figure 6.12: LHCb electromagnetic<br />
calorimeter 3D-view<br />
from behind of ECAL towards<br />
the interaction region. One of<br />
two ECAL platforms is partially<br />
moved out.<br />
looped at the front of the cell and the ends of all the fibers are collected into one bundle at the end of<br />
the cell to gui<strong>de</strong> the light to a photo-<strong>de</strong>tector. The tower of lead-tyvek-scintillator layers is compressed<br />
together and held by steel strings in four corners of the cell. As an example, the LHCb modules of the<br />
inner, middle and outer sections, are shown in Fig. 6.13<br />
The actual transverse size of the module, thickness and number of sampling layers are <strong>de</strong>fined by the<br />
physical requirements, namely by the <strong>de</strong>sired Moliere radius, total effective radiation and nuclear absorption<br />
lengths and the energy resolution. These values <strong>de</strong>pend on the sampling and can be expressed in<br />
terms of the relative length of the lead layers with respect to the total cell length w = hPb/htot as <strong>de</strong>monstrated<br />
in Fig. 6.14. Markers on the curves show some particular sampling cases with different lead and<br />
scintillator thicknesses which are available now in the IHEP scintillator facility [166] and in the Russian<br />
heavy metal industry.<br />
As an example, modules with a Moliere radius of 4 cm and a good energy resolution could consist of the<br />
lead and scintillator layers of the thicknesses 0.275 and 0.8 mm respectively. The total radiation length of<br />
20X0 could be realized with 390 layers and a total cell length of 466 mm. Modules with a Moliere radius<br />
of 6 cm could be assembled from the lead layers of 0.275 mm and scintillator layers of 1.5 mm. The total<br />
number of sampling layers required to provi<strong>de</strong> the same radiation length of 20X0 is 360 resulting in the<br />
cell length of 680 mm.
172 Electromagnetic Calorimeter (ECAL)<br />
, mm<br />
0<br />
X<br />
70<br />
60<br />
50<br />
40<br />
30<br />
20<br />
10<br />
h =0.275 mm, h =1.5 mm<br />
Pb<br />
Sci<br />
h =0.275 mm, h =0.8 mm<br />
Pb<br />
Sci<br />
h =0.350 mm, h =0.8 mm<br />
Pb<br />
Sci<br />
0<br />
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1<br />
w=h /h Pb tot<br />
, mm<br />
I<br />
λ<br />
800<br />
700<br />
600<br />
500<br />
400<br />
300<br />
200<br />
Figure 6.13: LHCb modules.<br />
h =0.275 mm, h =1.5 mm<br />
Pb<br />
Sci<br />
h =0.275 mm, h =0.8 mm<br />
Pb<br />
Sci<br />
h =0.350 mm, h =0.8 mm<br />
Pb<br />
Sci<br />
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1<br />
w=h /h Pb tot<br />
, mm<br />
M<br />
R<br />
90<br />
80<br />
70<br />
60<br />
50<br />
40<br />
30<br />
20<br />
10<br />
h =0.275 mm, h =1.5 mm<br />
Pb<br />
Sci<br />
h =0.275 mm, h =0.8 mm<br />
Pb<br />
Sci<br />
h =0.350 mm, h =0.8 mm<br />
Pb<br />
Sci<br />
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1<br />
w=h /(h ) Pm tot<br />
Figure 6.14: Effective radiation length, nuclear absorption length and effective Moliere radius of the calorimeter<br />
vs the length fraction of lead w = hPb/htot.<br />
6.5 Photon <strong>de</strong>tectors<br />
Custom photomultipliers have <strong>de</strong>monstrated perfect performance with “shashlik” calorimeters during the<br />
last 15 years. However, their relatively high price seriously limits the granularity of the system, which is<br />
particularly important for CBM. Therefore it would be very interesting to consi<strong>de</strong>r the new technologies<br />
(APDs, multiano<strong>de</strong> PMTs, SiPMs) especially for the preshower and hadron catcher where requirements<br />
for energy resolution, dynamic range and linearity are not very stringent.
6.6. Readout electronics 173<br />
To provi<strong>de</strong> high accuracy of the energy measurement and long-term stability in the high-frequency load<br />
environment, the photon <strong>de</strong>tectors should have a low rate effect and a linear amplification in the whole<br />
energy range. PMTs with the required low rate effect are characterized by a stability of better than 1 %<br />
at a current of 20µA. The linearity should be better than 1 % in the range of pulse currents up to 50 mA.<br />
6.6 Readout electronics<br />
The electromagnetic calorimeter of the CBM experiment must handle in its hottest regions a counting<br />
rate compatible with the expected beam average rate of 10 MHz for A-A collisions and up to several<br />
100 MHz for p-p and p-A collisions. In this kind of experimental situation we need to implement a fast<br />
shaping of the PMT signals and a processing capable of signal <strong>de</strong>convolution in case of events pile-up.<br />
The PMT signal processing could be essentially based on a Gaussian-like continuous shaping of the type<br />
(CR−RC) n (where for the following <strong>de</strong>scription n=4 should be a reasonable starting point). The shaping<br />
time constant is a compromise between noise reduction optimization, pile-up extent, and ADC sampling<br />
frequency. The latter requirement is because the cost per channel will <strong>de</strong>pend in relevant extent on the<br />
number of Mega Samples chosen for the 12 bit ADC. Nowadays 100 MSPS 12 bit ADC can be found for<br />
∼20 $ and we will base our initial <strong>de</strong>sign on these characteristics.<br />
As a consequence, a (CR − RC) 4 shaping on the photomultiplier signals with 50 ns time constant looks a<br />
reasonable starting point for the <strong>de</strong>sign of the ECAL FEE, since typically 5 samples per hit at 100 MSPS<br />
should be sufficient, once properly processed, to reconstruct the signal amplitu<strong>de</strong> after a proper baseline<br />
subtraction, also in the case some pile-up occurred. The digitally converted 12 bit information should<br />
then been fed into a processing unit that should perform the following main operations:<br />
• provi<strong>de</strong> a self trigger based either on the single readout channel information or, better, by a clustering<br />
algorithm on neighbouring channels;<br />
• provi<strong>de</strong> possibly a data size reduction by means of zero suppression;<br />
• append to each sampled amplitu<strong>de</strong> its time stamp and spatial coordinate.<br />
These processing units could be implemented in FPGAs (containing DSP units) each one handling a<br />
group of calorimeter channels. At the actual status of the system <strong>de</strong>sign it is very difficult to go <strong>de</strong>eper in<br />
the <strong>de</strong>tails of the logic to be implemented in the FPGA and therefore is hard to <strong>de</strong>fine how many readout<br />
channels a FPGA will serve. Nevertheless the flexibility and the performances of the already existing<br />
FPGA <strong>de</strong>vices (see, for instance, the ALTERA stratix II series) make us confi<strong>de</strong>nt that a good level of<br />
channel integration could be achieved also with the implementation of complex logic and processing<br />
schemes keeping the cost per channels still reasonably low.<br />
6.7 Radiation hardness of <strong>de</strong>tectors and electronics<br />
The radiation doses are obtained by summing energy <strong>de</strong>positions calculated with the CBM GEANT<br />
based simulation program. The expected annual radiation dose at the shower maximum for the CBM<br />
calorimeter modules closest to the beam pipe is 0.2 Mrad, assuming 10 7 ion-ion collisions per second<br />
and 5 × 10 6 seconds per nominal year. As it can be seen from Fig. 6.15, the dose is a steep function of<br />
the distance from the beam pipe, and varies over the inner calorimeter region by an or<strong>de</strong>r of magnitu<strong>de</strong>.<br />
The middle and outer section modules do not suffer from radiation.<br />
The radiation can affect the quality of the optical components ma<strong>de</strong> of plastic materials, namely the<br />
scintillating tiles and the WLS fibers. Both, light yield and transmission through the tiles and fibers may<br />
<strong>de</strong>crease with increasing dose. The <strong>de</strong>tailed studies performed for the LHCb electromagnetic calorimeter
174 Electromagnetic Calorimeter (ECAL)<br />
[162] has shown the mo<strong>de</strong>st <strong>de</strong>gradation of constant term in energy resolution of “shashlik” modules after<br />
5 Mrad accumulated dose. For the CBM calorimeter such a <strong>de</strong>gradation is much less important.<br />
Dose, rad/year<br />
10 5<br />
60 80 100 120 140 160 180 200<br />
distance from the ECAL center, cm<br />
6.8 Working packages, timelines, costs<br />
Figure 6.15: The expected annual radiation<br />
dose distribution along the xaxis<br />
at y=0<br />
Activity Time line<br />
Simulation package <strong>de</strong>velopment, optimization of calorimeter geometry and module<br />
parameters, reconstruction and particle i<strong>de</strong>ntification algorithms implementation<br />
2004–2006<br />
Manufacturing and characterization of pilot samples of thin scintillator (0.5–1.0<br />
mm)<br />
2004-2006<br />
Production of prototypes with different sampling and transverse cell sizes and their<br />
tests at IHEP, ITEP and <strong>GSI</strong> beams<br />
2005–2006<br />
Construction of a large-scale matrix of pre-production modules and studies of the<br />
energy and spatial resolutions, and PID issues at the beams<br />
2006–2008<br />
R&D of monitoring system 2006-2007<br />
R&D on photon <strong>de</strong>tector: tests with the prototype of different PMT, SiPM and APD 2005–2007<br />
Module mechanical <strong>de</strong>sign 2006–2007<br />
Calorimeter mechanical structure <strong>de</strong>sign 2007–2008<br />
Definition of the FEE project and <strong>de</strong>sign 2004–2006<br />
R&D on the shaping filter 2007–2008<br />
Implementation of the readout board logic 2007–2008<br />
Prototype and tests 2008–2009<br />
FEE mass production 2010–2011<br />
FEE installation and commissioning 2011–2012<br />
Mass production of the modules 2008–2012<br />
Calorimeter assembling and commissioning in <strong>GSI</strong> 2011–2012
6.8. Working packages, timelines, costs 175<br />
The cost estimate is extrapolated from the known costs of other calorimeters of the similar type and<br />
shown in Table 6.5<br />
Element price per unit, quantity cost, M<br />
Inner modules 2000 732 1.5<br />
Middle modules 1000 1612 1.6<br />
Outer modules 600 5592 3.4<br />
Mechanical structure 0.2 1 0.2<br />
PMT 90 23752 2.2<br />
SiPM 10 23752 0.2<br />
High voltage system 50 23752 1.2<br />
FEE ECAL channel 50 23752 1.2<br />
FEE PRS channel 30 23752 0.7<br />
Total 12.2<br />
Table 6.5: Cost estimate for ECAL.
176 Electromagnetic Calorimeter (ECAL)
7 Superconducting dipole magnet<br />
The requirements for the CBM dipole magnet are: aperture of 1 x 1 m 2 , a bending power of about 1 Tm,<br />
and negligible stray field within the volume of the RICH radiator. Moreover, the magnetic field is nee<strong>de</strong>d<br />
to <strong>de</strong>flect the δ-electrons being produced abundantly in the target by the intense heavy-ion beam.<br />
We have <strong>de</strong>signed two versions of dipole magnets which differ in their field configuration. Track reconstruction<br />
simulations are un<strong>de</strong>r way to <strong>de</strong>ci<strong>de</strong> upon the two magnetic field versions.<br />
7.1 Dipole with parallel pole shoes<br />
The first magnet concept is shown in figure 7.1. The magnetic field is calculated using the TOSCA co<strong>de</strong><br />
and has been implemented in the GEANT simulation co<strong>de</strong>. Figure 7.2 shows the y component of the<br />
field along the beam axis at x = 0 and various vertical distances from the midplane. A possible technical<br />
realization of the magnet is illustrated in figure 7.3.<br />
Figure 7.1: Mo<strong>de</strong>l of the dipole magnet used for TOSCA calculations<br />
177
178 Superconducting dipole magnet<br />
Figure 7.2: Magnetic field component in vertical direction as calculated with TOSCA<br />
Figure 7.3: Possible realization of the superconducting dipole magnet<br />
7.2 Dipole with inclined pole shoes<br />
The second magnet version is illustrated in figure 7.4. Details of the construction of the iron yoke, the<br />
pole shoes and the coils are presented in figure 7.6.<br />
The yoke of the magnet consists of the top and bottom gir<strong>de</strong>rs, the si<strong>de</strong> struts and the poles. The magnet<br />
pole has a trapezoidal shape with the corners roun<strong>de</strong>d with the radius 61 mm. The poles are fastened<br />
on the gir<strong>de</strong>rs and make angles 30 ◦ with the median plane. The top and bottom gir<strong>de</strong>rs consist of three<br />
separate parts each. The racks of the magnet have the shape of a trapezoid. The weight of any structural<br />
element does not exceed 10 tons. Therefore, the crane available in the cave will be sufficient for the<br />
assembly of the magnet. All parts of the magnet yoke are manufactured of steel with low carbon content<br />
(Steel 10). The gir<strong>de</strong>rs and racks are assembled in one structure and are fastened with the help of bolted
7.2. Dipole with inclined pole shoes 179<br />
Figure 7.4: Mo<strong>de</strong>l of the dipole magnet with inclined pole shoes as used for TOSCA calculations<br />
Figure 7.5: Field configuration of magnet with inclined pole shoes<br />
connections. The structural elements are fastened together with the help of pins and inserts. The magnet<br />
poles are fastened on the top and bottom gir<strong>de</strong>rs with the help of special bolted connections. The field<br />
insi<strong>de</strong> the gap of the magnet is formed by the poles of a trapezoidal shape. The cryostats of the winding<br />
are fastened on the poles. The load from pon<strong>de</strong>romotive forces originating in the winding excited by
180 Superconducting dipole magnet<br />
Figure 7.6: Construction of the dipole magnet with inclined pole shoes<br />
electric current is transmitted to the poles. The excitation winding is ma<strong>de</strong> from a superconducting cable<br />
with the cross-section 7*4.5 mm. The wires of the cable are manufactured of superconducting Ni-Ti<br />
threads (niobium and titanium alloy). The superconducting threads are in a copper matrix and are placed<br />
in a common aluminum shell. The ratio of the superconductor cross section area to the cross section<br />
area of copper is 1/3. The ratio of the SC cross section area to the aluminum shell cross section area<br />
is 1/12. The cable is insulated by two layers of a 20-micron thick polyami<strong>de</strong> film and two layers of a<br />
fiberglass ribbon of the thickness 0.1 mm and width 20 mm with half-width overlapping. While winding<br />
the excitation coil slots 10 mm wi<strong>de</strong> and 0.2 mm <strong>de</strong>ep occur between adjacent layers of the winding.<br />
The slots provi<strong>de</strong> penetration of liquid helium to the cable and improve heat dissipation. The winding<br />
consists of two coils (a pancake-like <strong>de</strong>sign), each of them in a separate helium vessel of the cryostat.<br />
The cryostat of the excitation winding consists of a helium vessel, a nitrogen shield and a vacuum shell.<br />
The nitrogen shield and the vacuum shell transmit load from pon<strong>de</strong>romotive forces originating in the<br />
winding to the magnet pole. The windings are insulated from the walls of the helium vessel by frame<br />
insulation of 2 mm thick fiberglass with vertical grooves 1 mm <strong>de</strong>ep and 7.5 mm wi<strong>de</strong>. The grooves serve<br />
as channels for liquid and gaseous helium flow. The wel<strong>de</strong>d helium vessel serves as a helium reservoir.<br />
The external surface of the vessel is polished. The radiation heat flux from the nitrogen shield to the<br />
helium vessel is 0.25 W. The helium vessel is fastened to the nitrogen shield by supports with maximum<br />
heat resistance. Heat flux to the helium vessel due to heat conduction of the supports does not exceed<br />
2.0 W. The nitrogen shield is manufactured of copper. Copper tubes for pumping of liquid nitrogen are<br />
sol<strong>de</strong>red to the shield. The nitrogen shield is hanged in the vacuum shell with the help of special supports.<br />
The supports are fabricated of a material with maximum heat resistance. The walls of the nitrogen shield<br />
are polished and covered with five layers of vacuum insulation. It takes away approximately 40% of<br />
the radiation heat flux to the nitrogen shield from the vacuum shell. The vacuum shell is manufactured<br />
of stainless steel. The covers and hatches in the shell provi<strong>de</strong> access insi<strong>de</strong> for mounting equipment.<br />
The internal wall of the shell leans on the magnet pole and is fastened to it. The selected thickness of<br />
the vacuum shell walls is 4 mm. The wall thickness was selected from the conditions of stability and<br />
maximum permissible sagging 0.2 mm. The shell is supplied with nipples for attachment of vacuum
7.2. Dipole with inclined pole shoes 181<br />
Figure 7.7: Construction of the superconducting coils<br />
pumps and pressure sensors. The internal surface of the vacuum shell is polished. The top and bottom<br />
cryostats are connected with each other by two cryo-vacuum subs. The joints of all communication lines<br />
are placed insi<strong>de</strong> the subs. They are the cryostat monitoring systems, helium and nitrogen joints, current<br />
joints of the top and bottom coil windings. The upper cryostat is supplied with a filler neck. Two <strong>de</strong>vices<br />
for current input, 4 leads each, liquid helium and liquid nitrogen inputs, control and sealing <strong>de</strong>vices,<br />
indicators of operating liquid levels in the cryostat, outputs of sensors of transition to the normal phase<br />
and temperature sensors, etc. are placed on the neck. The pipelines and the communication joints in the<br />
filler neck yield heat flux to the helium vessel 3.75 W. The main specifications of the magnet are given<br />
in Table 7.1.<br />
Parameter Quantity Dimension<br />
Weight of yoke 37 ton<br />
Coil windings 270<br />
Distance between poles maximal 845 mm<br />
Distance between poles minimal 368 mm<br />
Ampere turns 600000<br />
Field length 1200 mm<br />
Maximum field 1.7 T<br />
Time to cool down 48 hours<br />
Time to ramp-up field 45 minutes<br />
Thermal stream to Helium vessel 6 W<br />
Thermal stream to Nitrogen screen 30 W<br />
Table 7.1: Main specifications of the magnet
182 Superconducting dipole magnet
8 Diamond start <strong>de</strong>tector<br />
8.1 Introduction<br />
CVD Diamond Detectors (CVD-DD) are radiation-hard and fast particle sensors suitable for operation<br />
in primary Heavy-Ion (HI) beams of beam intensities up to 10 9 ions/s [168]. We intent to apply CVD-D<br />
micro-strip <strong>de</strong>tector(s) of a thickness 100 µm ≤ dD ≤ 300µm as START (T0) <strong>de</strong>tector(s) for the ToF<br />
measurements. The <strong>de</strong>tectors will be optimized with respect to an intrinsic time resolution in the or<strong>de</strong>r of<br />
50 ps and a count rate capability of ≥ 5 · 10 6 ions/s per strip. Presently, a <strong>de</strong>tector of a strip and readout<br />
pitch of 50 µm at a strip width of 25 µm is discussed.<br />
Polycrystalline CVD Diamond (PC-CVD-D) strip <strong>de</strong>tectors of such a layout (Fig. 8.1)) have been reliably<br />
produced and extensively tested in the past from the RD42 Collaboration striving for minimum<br />
ionizing particles (MIP) tracking near the interaction region in high-energy experiments at high luminosity<br />
colli<strong>de</strong>rs [169]. Using muon beams and VA2 electronics, a spatial resolution of 10 µm to 20 µm and<br />
a hit efficiency of 86.7% have been achieved.<br />
Figure 8.1: A CVD Diamond Beam Telescope<br />
(The RD42 Collaboration). Two hybrids<br />
carrying PC-CVD diamond strip <strong>de</strong>tectors<br />
and readout chips. The 2×2 cm 2 big sensors<br />
of a strip- and readout pitch of 50 µm are<br />
centered over a hole in the aluminum frame.<br />
However, <strong>de</strong>pending on diamond quality and thickness (section 8.4) the charge collection efficiency<br />
(CCE) of PC-CVD-DD is reduced to 20% - 50%. The main charge loss is due to the grain boundaries<br />
within the polycrystalline texture of the material. Since operation with heavy projectiles and light ions<br />
down to protons is foreseen for CBM Single-Crystal (SC) CVD-DD of almost 100% CCE [170] must<br />
be consi<strong>de</strong>red as well. In section 8.2 relevant data obtained so far from dot- respectively pad-<strong>de</strong>tectors<br />
of these two types of diamond is presented. The suitability of the above <strong>de</strong>scribed layout is discussed<br />
in section 8.3, 8.4 and 8.5 with respect to the initial beam parameters published in reference [171]. The<br />
parameters have been scaled for 197 Au ions and protons of lowest and highest kinetic energy. Special<br />
care is spent to consequences of the small beam focus size required in CBM, which affects both, the<br />
specifications of FE electronics (section 8.5) and the choice of the diamond <strong>de</strong>tector thickness and quality<br />
(section 8.4). The goal is to minimize avoidable background and time-zero jitter, maintaining a good<br />
Signal-to-Noise (S/N) ratio at an acceptable ion rate per <strong>de</strong>tector channel.<br />
183
184 Diamond start <strong>de</strong>tector<br />
8.2 Properties of CVD diamond <strong>de</strong>tectors<br />
8.2.1 Pulse shape characteristics<br />
The high mobility of electrons (2400 cm 2 V −1 s −1 ) and holes (1600 cm 2 V −1 s −1 ) in diamond predicts<br />
the suitability of DD for timing applications. <strong>GSI</strong> has a long experience with the operation of fast HI<br />
diamond <strong>de</strong>tectors placed in the primary beam and with <strong>de</strong>velopment of suitable single-channel Diamond<br />
Broadband Amplifiers (DBA [172], 2 GHz) and low threshold discriminators (LTD [173]).<br />
The left plots in figures 8.2 and 8.3 show 241 Am-α-signals of Eα = 5.5 MeV, which are obtained from PC<br />
(Fig. 8.2) respectively SC (Fig.8.3) material using such current amplifiers. The signals are recor<strong>de</strong>d with<br />
fast Digital Storage Oscilloscopes of a bandwidth of 1.5 GHz and a single-shot resolution of 10 GS/s.<br />
Due to the short range of 12 µm of α-particles in diamond the drift of electrons and holes can be studied<br />
separately. The measurement of the uniform and fast rise time of the signals (trise
8.2. Properties of CVD diamond <strong>de</strong>tectors 185<br />
Figure 8.3: Hole drift in SC-CVDD (The NoRHDia Collaboration) [174]. Signals from an 241 Am source measured<br />
with a single-crystal diamond dot <strong>de</strong>tector of 300 µm thickness and a capacitance of 0.5 pF.<br />
time distribution shown on the right plot of the figure is given by the <strong>de</strong>tector thickness whereas the<br />
narrow width of it predicts both a good time and energy resolution.<br />
Obviously, this type of <strong>de</strong>tector in conjunction with DBA-type FEE operates as a fast diamond drift<br />
chamber of 100% CCE and an expected count-rate capability at operation field of about 10 8 ions/s per<br />
<strong>de</strong>tector channel.<br />
8.2.2 Intrinsic time resolution of HI diamond <strong>de</strong>tectors at SIS energies<br />
Using various heavy projectiles the intrinsic time resolution of PC-CVD-DD has been measured frequently<br />
to be well below 50 ps [168]. Recently, in a FOPI beam test with 181 Ta ions of 1 AGeV a<br />
σintr = 22 ps has been achieved using 500 µm thick samples and the DBA based RPC FEE of FOPI (Figure<br />
8.4). A similar value (σintr = 29 ps) has been obtained earlier by the HADES Collaboration using<br />
52 Cr ions of 650 AMeV and two diamond <strong>de</strong>tectors of a thickness of 100 µm.<br />
Based on the observation of fast and uniform rise times of SC-DD signals (Figure 8.3) and of a better<br />
S/N ratio we expect an intrinsic time resolution for this type of DD at least as good as in the PC case.<br />
8.2.3 MIP timing with PC diamond <strong>de</strong>tectors<br />
First encouraging results [175] have been obtained using 90 Sr electrons (E β max = 2.4 MeV) and two diamond<br />
samples of a thickness of 500 µm and of a CCE of 42%. The PC-DDs were mounted in a stack<br />
in front of a plastic scintillator used as trigger <strong>de</strong>tector. Figure 8.5 shows on the left plot (arb. units) the<br />
) signal after walk correction and on the right plot<br />
pulse-height <strong>de</strong>pen<strong>de</strong>nce of the time difference (Tlin D<br />
the Tlin D distribution for amplitu<strong>de</strong>s in the indicated range of 750 < ET < 1000. Fitting the spectrum with<br />
a Gaussian a time resolution of σintr = 95 ps is estimated assuming equal contribution of both <strong>de</strong>tectors<br />
to the width.<br />
However, due to a mean value of the collected charge per 90 Sr electron of 7560 e − corresponding to an<br />
amplifier noise signal of 13000 e − the <strong>de</strong>tection efficiency is only about 3%. New generation diamond<br />
timing amplifiers are nee<strong>de</strong>d for this application. A CMOS based charge-sensitive but fast amplifier
186 Diamond start <strong>de</strong>tector<br />
Figure 8.4: Preliminary data obtained with 181 Ta ions of 1 AGeV (The FOPI Collaboration). The time spectrum<br />
measured with two PC diamond <strong>de</strong>tectors of a thickness of 500 µm mounted perpendicular to the primary beam<br />
(left) is compared to the time spectrum measured with one of the diamonds against the time given by the currently<br />
used FOPI start <strong>de</strong>tector (plastic scintillator <strong>de</strong>tector).<br />
Figure 8.5: The walk corrected time difference is plotted versus the pulse height of one of the diamond samples<br />
(left). The one dimensional time spectrum (right) fitted with a Gaussian shows an intrinsic resolution of σintr =<br />
95 ps for an amplitu<strong>de</strong> range 750 < ET < 1000. The tails of the distribution are exclu<strong>de</strong>d in the fit.<br />
prototype (rise time ≈ 1 ns) is currently un<strong>de</strong>r <strong>de</strong>velopment at <strong>GSI</strong> (The NoRHDia Collaboration). It will<br />
be used in conjunction with a fast filter amplifier (5 - 10 ns Gaussian shaping time) allowing to improve<br />
significantly the S/N ratio. The experience from these <strong>de</strong>velopments will be exploited for diamond strip<br />
<strong>de</strong>tector FEE. First reliable results are expected in spring 2005.<br />
8.2.4 Suppression of trigger rate and background using START-VETO <strong>de</strong>vices<br />
The HADES experiment is <strong>de</strong>signed for beam rates of up to 10 8 HI/spill. Due to the short intrinsic <strong>de</strong>ad<br />
time (1 -2 ns) of diamond <strong>de</strong>tectors the required beam intensity can be accepted. Two i<strong>de</strong>ntical diamond<br />
strip <strong>de</strong>tectors (START-VETO <strong>de</strong>vice) of 100 µm thickness located 75 cm upstream and downstream of
8.2. Properties of CVD diamond <strong>de</strong>tectors 187<br />
the target are used to generate a start signal for the time-of-flight measurements. The start signal rate is<br />
reduced by two or<strong>de</strong>rs of magnitu<strong>de</strong> by rejecting beam particles not reacting in the target.<br />
In or<strong>de</strong>r to distinguish and suppress pions with almost light velocity from leptons a good time-of-flight<br />
resolution is required. In Figure 8.6 ToF spectra measured in a commissioning run with 52 Cr ions on<br />
27 Al are shown. The distance between START and ToF is 2.1 m.<br />
Figure 8.6: ToF spectrum of all particles <strong>de</strong>tected (left). ToF spectrum of electron candidates, as selected by<br />
means of position correlation between RICH and ToF hits. The data was obtained without magnetic field.<br />
Data taken from all 384 ToF segments is inclu<strong>de</strong>d in both spectra. In the left plot the time-of-flight<br />
spectrum of all particles arriving within 20 ns at ToF is shown. The lepton candidates are selected by<br />
position correlations of hits in the RICH and the segmented plastic scintillator wall (ToF <strong>de</strong>tector). The<br />
time-of-flight spectrum of those candidates is shown in the right plot. The intrinsic time resolution of the<br />
START-VETO <strong>de</strong>vice amounts to σintr = 29 ps. The measured time-of-flight of σ = 233 ps is <strong>de</strong>fined by<br />
the ToF <strong>de</strong>tector and is affected in this spectrum in addition by calibration uncertainties of ToF segments.<br />
8.2.5 Pulse-height distributions in CVD-diamond <strong>de</strong>tectors<br />
Broad pulse-height distributions are obtained with PC-CVD-DD from all kinds of mono-energetic charged<br />
particles from MIP up to highly ionizing heavy ions. In opposite to this, an excellent alpha resolution<br />
has been measured recently with SC-DD of 300 µm thickness (NoRHDia).<br />
In Figure 8.7 two representative spectra are plotted. On the left si<strong>de</strong> the collected charge spectrum of<br />
84 Kr ions of 650 AMeV measured with a 100 µm thick PC-DD is shown revealing an amplitu<strong>de</strong> dynamic<br />
range of 3 and a pulse-height resolution ΔQ/Q ≈ 1. On the right plot the energy spectrum of a mixed<br />
nucli<strong>de</strong> α-source ( 239 Pu, 241 Am, 244 Cm) is presented. All satellite lines are resolved. A preliminary<br />
calibration gives an energy resolution ΔE of about 20 keV.<br />
Of course, charge-sensitive spectroscopic measurements have been performed in or<strong>de</strong>r to obtain such<br />
spectra. Nevertheless, the shape of the pulse-height distributions must be consi<strong>de</strong>red differently for each<br />
type of diamond timing <strong>de</strong>tector with respect to the <strong>de</strong>sign of FEE electronics including discriminator<br />
thresholds and possibly nee<strong>de</strong>d time walk corrections.
188 Diamond start <strong>de</strong>tector<br />
Figure 8.7: Typical collected charge distributions of mono-energetic particles in CVD-D <strong>de</strong>tectors. Spectrum of<br />
84 Kr ions of 650 AMeV measured with a 100 µm thick PC-DD (left plot); Spectrum of a mixed nucli<strong>de</strong>-α-source<br />
( 239 Pu, 241 Am, 244 Cm) measured with a SC-DD of 300 µm thickness (right plot).<br />
8.3 Discussion of the strip <strong>de</strong>sign with respect to the beam parameters<br />
Beam parameters are given in Reference [171] for 238 U 92+ ions of highest possible kinetic energy,<br />
i.e. 34 AGeV. Table 8.1 shows corresponding horizontal (h) and vertical (v) parameters for 197 Au 79+<br />
ions and protons of different kinetic energies. The uranium values have been scaled according to the<br />
relations ε ∝ 1<br />
Bρ<br />
∼ 1<br />
βγ .<br />
Beam parameters 197Au, 34 AGeV 197Au, 10 AGeV p, 30 GeV p, 90 GeV<br />
Time structure D.C. during spill<br />
N (50% duty cycle)<br />
/ions s−1 1 · 109 Transverse<br />
ε/mm mrad<br />
emittance 0.6 (h) × 0.3 (v) 2 (h) × 1 (v) 1.7 (h) × 0.9 (v) 0.6 (h) × 0.3 (v)<br />
Momentum spread ±1 · 10−4 Beam spot radius /mm 0.5 (h) × 0.5 (v)<br />
beam angles /mrad 1.2 (h), 0.6 (v) 4 (h), 2 (v) 3.4 (h), 1.8 (v) 1.2 (h), 0.6 (v)<br />
Table 8.1: Beam parameters for 197 Au 79+ ions and protons of two different beam energies.<br />
8.3.1 Beam dimensions and beam intensity load at different distance from the CBM target<br />
assuming 50 µm strip and readout pitch at a strip width of 12 µm<br />
Figure 8.8 shows preliminary beam dynamic feasibility studies [176]. Both possible target positions are<br />
indicated: the HADES target at a distance of 2 m and the CBM target at a distance of 12 m downstream<br />
the last quadrupole. Assuming the <strong>de</strong>signed beam focus of 0.5(v) × 0.5(h) mm 2 at the CBM target<br />
position and transverse emittance of 0.6 (h) × 0.3 (v) mm mrad, beam dimensions at different distances<br />
from the target are plotted in Figure 8.9. The elliptic beam spots become almost circular at a distance of<br />
10 cm from target.<br />
The beam intensity profile is presently not available. In or<strong>de</strong>r to estimate roughly the beam load at the<br />
innermost strips the following assumptions have been ma<strong>de</strong>:
8.3. Discussion of the strip <strong>de</strong>sign with respect to the beam parameters 189<br />
Figure 8.8: Beam dynamic calculations (feasibility studies) for the HADES-CBM beam line.<br />
• The requested ion rate of 10 9 /s is within the 4σ-width of a Gaussian intensity distribution.<br />
• The beam intensity is distributed over the total number of strips.<br />
• About 65% of the beam is hitting homogeneously the inner strips placed at the 2σ-width of the<br />
intensity distribution.<br />
The rates per inner <strong>de</strong>tector strip are plotted in the blue plot of Figure 8.9. The numbers indicate the<br />
corresponding total number of <strong>de</strong>tector channels at each distance away from target.<br />
Figure 8.9: Calculated beam dimension (full-size) in horizontal (red dots) and vertical (black dots) direction for<br />
different distance from the CBM target. The ion rate on the innermost strips (blue dots) has been estimated for<br />
65% of the beam intensity distributed on 2/4 of the strips around the beam axis. The total number of <strong>de</strong>tector strips<br />
nee<strong>de</strong>d is given in blue numbers.
190 Diamond start <strong>de</strong>tector<br />
8.3.2 Time Zero precision<br />
Influence of momentum spread<br />
At relativistic motion the relative time jitter is proportional to the momentum spread according Δt/t =<br />
−γ −2 · Δp/p. Due to a Δp/p = 10 −4 the uncertainty of the time zero (ΔT0) is negligible. In Figure 8.10<br />
the calculated values for 197 Au ions of 34 AGeV respectively 10 AGeV as well as for protons of 30 GeV<br />
respectively 90 GeV are plotted versus the distance between START <strong>de</strong>tector and CBM target.<br />
Figure 8.10: Calculated total T0 variation for different distances between START <strong>de</strong>tector and CBM target.<br />
Influence of <strong>de</strong>tector layout and strip readout<br />
If a larger distance from the target must be chosen in or<strong>de</strong>r to relax the count rates of the inner strips,<br />
the signal propagation time within each strip is not negligible because it leads to a position <strong>de</strong>pen<strong>de</strong>nce<br />
of T0. Assuming light velocity, a 15 mm length of a strip contributes with 50 ps. One can think to<br />
readout the strips on both si<strong>de</strong>s and to correct time with position, if possible, or to separate them into<br />
two in<strong>de</strong>pen<strong>de</strong>nt <strong>de</strong>tector channels of half the length gaining such a way in addition a factor of two lower<br />
rates per <strong>de</strong>tector channel.<br />
On the other hand, a <strong>de</strong>tector placed 0.5 m upstream of the CBM target can be much smaller, containing<br />
only 24 strips. The ion rates per inner strip increase to about 5 x 10 7 /s (Figure 8.9) and the use of a<br />
START-VETO <strong>de</strong>vice (section 8.2.4) is strongly recommen<strong>de</strong>d. A trigger-rate reduction of two or<strong>de</strong>rs of<br />
magnitu<strong>de</strong> can be achieved. However, it could be useful to discuss single-channel amplifiers combined<br />
with fast logic <strong>de</strong>vices able to process rates up to 10 GHz. Such <strong>de</strong>vices are implemented for instance in<br />
fast clock distribution systems.
8.4. Influence of diamond material type and thickness 191<br />
8.4 Influence of diamond material type and thickness<br />
A radiation length of 18.8 cm is given in data tables for carbon (compare silicon: 9.4 cm). However,<br />
the total reaction probability of 197 Au ions in 100 µm diamond is estimated to be ∼ 0.56%. The energy<br />
nee<strong>de</strong>d to create an e-h pair in diamond is 13.4 eV, which is about 4 times higher than for silicon. A<br />
MIP produces only 36 e − per micrometer. Therefore, the <strong>de</strong>tector thickness becomes a crucial parameter<br />
especially in the case of minimum ionizing protons and very light ions.<br />
8.4.1 Available types of CVD-D material and their corresponding <strong>de</strong>tector properties<br />
Free-standing Electronic Gra<strong>de</strong> (EG) CVD-D material, being the only available quality suitable for<br />
charged particle <strong>de</strong>tection, is classified according to its crystal texture to PC- or SC-type diamond and<br />
according to its finishing and surface preparation to polished Detector Gra<strong>de</strong> (DG)- or As Grown (AG)<br />
material. An overview of material parameters and the corresponding <strong>de</strong>tector properties at operation bias<br />
is given in Table 8.2. Values marked with asterisk are presently not measured but expected.<br />
Material parameters PC-AG-CVDD PC-DG-CVDD SC-CVDD<br />
Radiation hardness for p, π, e and fast n (1MeV) ∼ 1015 cm−2 ∼ 1015 cm−2 ∗<br />
Largest possible area [mm] ∅ 100 ∅ 100 6 × 6 mm2 Free-standing thickness [µm ] 80 - 2000 250 - 600 250 - 450<br />
CCE [%] 25 60 100<br />
MIP signal [e− ]/300 µm 2700 6480 10800<br />
197Au, 34 AGeV signal [e− ]/300 µm 1.7 · 107 4.0 · 107 6.7 · 107 ∗<br />
Signal rise time [ps] < 500 ps < 500 ps < 500 ps<br />
Signal drift time [ps]/300 µm
192 Diamond start <strong>de</strong>tector<br />
(rise time ∼ 1 ns) low-noise amplifier for this purpose with an enhanced S/N ratio is un<strong>de</strong>r <strong>de</strong>velopment<br />
at <strong>GSI</strong> within the frame work of the NoRHDia Collaboration.<br />
8.4.2 Multiple scattering and energy straggling<br />
The energy straggling ΔE/E is negligible with respect to the time-zero <strong>de</strong>finition. For 197 Au ions of<br />
10 AGeV kinetic energy it amounts to 6.8·10 −5 and for 34 AGeV to 5.3·10 −5 , respectively. Although the<br />
proton values are slightly higher (∼ 1.8 · 10 −4 for both consi<strong>de</strong>red energies) the same can be conclu<strong>de</strong>d<br />
also for this case.<br />
Assuming <strong>de</strong>tector thicknesses as proposed in section 8.4.1 the multiple scattering (σ) of 197 Au ions and<br />
protons in 100 µm respectively 300 µm diamond is given in Table 8.3.<br />
dD ΔΘx(σ) ΔΘx(σ) ΔΘx(σ) ΔΘx(σ)<br />
(µm) ( 197 Au, 10 AGeV) ( 197 Au, 34 AGeV) (p, 30 GeV) (p, 90 GeV)<br />
100 0.008 0.002<br />
300 0.013 0.004<br />
[mrad] [mrad] [mrad] [mrad]<br />
Table 8.3: Multiple scattering of 197 Au ions and protons in 100 µm respectively 300 µm diamond.<br />
The increased beam spot dimensions on CBM target produced from <strong>de</strong>tectors of such thickness are plotted<br />
in Figure 8.11 versus possible START <strong>de</strong>tector positions towards the last quadrupole. Full straggling<br />
has been consi<strong>de</strong>red in the plot.<br />
Figure 8.11: Resulting beam spot diameters<br />
at target position due to 197 Au-straggling in a<br />
100 µm thick PC-AG-DD, respectively proton<br />
straggling in a 300 µm SC-DD placed at different<br />
distances between CBM target and last<br />
quadrupole.<br />
This result leads possibly to a serious problem. It must be simulated how this focus enhancement affects<br />
the required energy <strong>de</strong>nsity on target.<br />
8.5 FE Electronics<br />
The <strong>de</strong>velopment of FEE for diamond micro-strip ToF <strong>de</strong>tectors is challenging. The signal processing<br />
will require multi (16-64) channel FE chips that perform several tasks: charge <strong>de</strong>tection, hit discrimination,<br />
time stamping, hit <strong>de</strong>-randomization and serialization.
8.6. Summary, concluding remarks and outlook 193<br />
Charge <strong>de</strong>tection<br />
This task is simplified in the heavy-ion scenario thanks to the huge charge of 2 pC produced for instance<br />
per 197 Au ion in a 100 µm sensor. An amplifier operated in a fairly small gain will be sufficient so that a<br />
high bandwidth can be reached rather easily. The proton case with charges in the fC range is much more<br />
challenging and more power will be required in the preamplifier to achieve a sufficient speed. The worst<br />
case pulse repetition rate of 5 · 10 6 requires shaping times in the range of 10 ns which is still compatible<br />
with the planned 0.18 µm chip technology.<br />
Hit discrimination<br />
The threshold for a hit can be set individually in every channel to cope with possible variations in the signal<br />
amplitu<strong>de</strong>. A coarse pulse height information may be required to correct for time walk, in particular<br />
in the proton case. A simple method is the measurement of the time over threshold by time stamping also<br />
the falling edge of the discriminator output signal. This solution does not require additional fast analog<br />
circuitry.<br />
Time stamping<br />
The continuous time stamping every 200 ns on average in the most populated strips can be performed by<br />
latching the state of a continuously running time stamp generator. This generator can, for instance, be<br />
implemented as a self-running ring oscillator locked to a reference clock. The required timing precision<br />
of below 50 ps probably calls for advanced circuit solutions like multiple with shifted phases or analog<br />
interpolation. Several solutions are presently being investigated. A significant problem at this required<br />
precision are cell-to-cell <strong>de</strong>lay variations which must be reduced as much as possible by appropriated<br />
circuit techniques and calibration.<br />
Hit <strong>de</strong>-randomization and serialization<br />
The raw hit information must be <strong>de</strong>co<strong>de</strong>d as soon as possible to reduce the data volume. It is queued for<br />
serialization to free the time stamping latches for a new hit so that no <strong>de</strong>ad time is introduced. This can<br />
be guaranteed by appropriate FIFO-type structures. The maximum data volume for a 32 channel chip<br />
amounts to 32 strips × 5 · 10 6 hits/sec/strip × 16 bits/hit = 2.5 Gbit/s. This can still be handled by the<br />
serial links which are <strong>de</strong>veloped in a 0.18 µm technology as a general purpose optical interconnect for<br />
CBM. The serializer block will be inclu<strong>de</strong>d on the FE chip.<br />
8.6 Summary, concluding remarks and outlook<br />
Suitability of the discussed <strong>de</strong>tector setup(s) and strip <strong>de</strong>sign<br />
Large area polycrystalline diamond <strong>de</strong>tectors are discussed as START <strong>de</strong>tectors for CBM experiments<br />
using heavy projectiles and single-crystal polished samples of limited area as START <strong>de</strong>tectors for protons.<br />
In both cases a strip- and readout pitch of 50 µm at a strip width of 25 µm is consi<strong>de</strong>red. Assuming<br />
a beam intensity of 10 9 ions/s, about 256 strips are nee<strong>de</strong>d in or<strong>de</strong>r to achieve a comfortable rate of<br />
5 · 10 6 ions/s/ inner strip. A distance of 5 m from the target leading to a <strong>de</strong>tector size of about 15 ×<br />
9 mm 2 must be chosen in this case. For a distance of 2 m 160 strips are nee<strong>de</strong>d and the FE chips must
194 Diamond start <strong>de</strong>tector<br />
cope in this case with about 8 · 10 6 /s/ inner strip. A factor of two lower rate is gained if the strips are<br />
separated in two parts reducing in addition the signal propagation time within each strip.<br />
Consi<strong>de</strong>ring the size of the <strong>de</strong>tector(s), distances closer to the target are advantageous. However, the<br />
beam load on the inner strips becomes then a serious problem. The only possible solution discussed<br />
presently is the use of a START-VETO <strong>de</strong>vice reducing the trigger rate by two or<strong>de</strong>rs of magnitu<strong>de</strong><br />
as <strong>de</strong>monstrated by HADES. The VETO <strong>de</strong>tector can be mounted in a place not affecting the silicon<br />
trackers.<br />
Heavy-ion START <strong>de</strong>tectors<br />
PC-AG-CVDD of a thickness in the or<strong>de</strong>r of 100 µm is the best choice for this case. <strong>GSI</strong> has a long<br />
time successful experience with this type of material and application. Any <strong>de</strong>sirable total size and shape<br />
is available. The START <strong>de</strong>tectors can be placed in any distance from target acceptable from FEE and<br />
data acquisition. If a reduction of trigger rate and background is nee<strong>de</strong>d a VETO <strong>de</strong>tector must also be<br />
used in this case. The price of PC-AG-CVD-D is 250 US$/cm 2 and the <strong>de</strong>livery usually 6 weeks from<br />
or<strong>de</strong>r. The estimated costs for the manufacture of the electro<strong>de</strong>s are about 5000 . In case of new mask<br />
production this amount can be slightly higher.<br />
Proton START <strong>de</strong>tectors<br />
SC-CVD-D samples of at least 300 µm thickness must be used in this case. The expected total reaction<br />
probability is 0.14% and multiple scattering of the beam is not negligible.<br />
The SC material is rather new and not yet easily available. Our diamond suppliers [177] consi<strong>de</strong>r it still<br />
as an R&D object, however, with very promising test results. Larger samples up to 10 × 10 mm 2 are<br />
expected in the next 2-3 years. In a long-term, wafers as large as 1 inch in diameter are also expected.<br />
Presently however, since active areas larger than 5 × 5 mm 2 are nee<strong>de</strong>d in or<strong>de</strong>r to reduce the ion<br />
rates/channel, mosaic <strong>de</strong>tector techniques and assembly prototypes must be <strong>de</strong>veloped. The price of<br />
SC-CVD-D is about 800 US$ for 3.5 × 3.5 mm 2 and the <strong>de</strong>livery about 8 - 10 weeks from or<strong>de</strong>r.<br />
FE Electronics<br />
Novel broadband FE chips of high sensitivity and speed are nee<strong>de</strong>d. It appears useful to discuss in a first<br />
round the same <strong>de</strong>sign as for the RPC <strong>de</strong>tectors. Nevertheless, single-channel amplifiers for small size<br />
<strong>de</strong>tectors must be consi<strong>de</strong>red as well<br />
Simulations<br />
All estimations discussed above must be simulated in realistic CBM experiment scenarios. Particularly,<br />
background production and beam spot wi<strong>de</strong>ning due to START <strong>de</strong>tectors must be compared to the advantage<br />
which can be taken by the implementation of diamond START-VETO <strong>de</strong>vices.
9 Common Front-End Electronics Aspects<br />
This section discusses all aspects of a common front-end electronics architecture. The first two sections<br />
discuss the general aspects and the over all requirements as <strong>de</strong>fined at this point in time, together with<br />
microelectronics boundary conditions and available building blocks. The resulting architecture is then<br />
outlined in section 9.3. The required advanced building blocks are <strong>de</strong>tailed in the following sections, discussing<br />
analog memories, multi-purpose ADCs, clock recovery, data communication and miscellaneous<br />
issues.<br />
9.1 General Consi<strong>de</strong>rations, Requirements<br />
The CBM experiment foresees a variety of sub-<strong>de</strong>tectors, including a silicon tracker, RICH, TRD, ToF<br />
and ECAL. Their architectures are outlined in appropriate sections. Their requirements with respect to<br />
front-end electronics and readout are not yet finalized. However, with respect to the front-end electronics<br />
three groups of <strong>de</strong>tectors and appropriate electronics can be <strong>de</strong>fined.<br />
• The silicon tracker is, unlike the other <strong>de</strong>tectors, mounted close to the reaction zone and is therefore<br />
exposed to very high radiation levels [178, 179]. Correspondingly the electronics has to be<br />
radiation hard in or<strong>de</strong>r to survive the projected 10 years of operation in the experiment. Radiation<br />
hard <strong>de</strong>signs differ from commercial gra<strong>de</strong> implementations by the shape of the transistors and<br />
other <strong>de</strong>sign techniques, generally resulting in a four fold higher space requirement and cost per<br />
transistor or logic cell and an appropriate higher power and lower speed rating in the same technology<br />
[178,179]. Given such high penalties for radiation hardness it is not advisable to use radiation<br />
hard techniques where they are not required. Therefore it is expected that the electronics, mounted<br />
on the silicon tracker, will be <strong>de</strong>veloped mostly in<strong>de</strong>pen<strong>de</strong>ntly of the other <strong>de</strong>tector systems.<br />
• The Time of Flight system has very high requirements with respect to the timing of the electronics<br />
in or<strong>de</strong>r to achieve the target 25 ps resolution. In or<strong>de</strong>r for the electronics not to significantly<br />
contribute to the ToF timing resolution the clock distribution and signal amplification has to operate<br />
with less than 10ps peak to peak jitter. The corresponding requirements of the remaining <strong>de</strong>tectors<br />
in CBM are more than an or<strong>de</strong>r of magnitu<strong>de</strong> relaxed. At this point in time it is not <strong>de</strong>finitely<br />
possible to judge whether or not such requirements can be met without extra effort and cost by<br />
standard electronics (see also the discussion in section 9.7.1).<br />
• The remaining <strong>de</strong>tector systems TRD, RICH and ECAL do not require radiation hard electronics<br />
or very high-speed electronics, like RAD in case of the ToF. For the radiation levels of the named<br />
<strong>de</strong>tectors refer to chapter 21. Using mo<strong>de</strong>rn <strong>de</strong>ep submicron electronics, these radiation levels,<br />
applied over the lifetime of the experiment do not produce significant total dose effects, allowing<br />
the use of commercial gra<strong>de</strong> <strong>de</strong>sign techniques and silicon libraries. Single event upsets can be<br />
<strong>de</strong>tected and corrected by appropriate fault tolerant <strong>de</strong>sign techniques. The TRD requires at least<br />
600k channels with 1. . . 10 cm 2 size, the RICH 120k channels with 0.4 cm 2 size and the ECAL<br />
requires about 23k with 10 cm 2 to 140 cm 2 sized channels. The digitization requirements range<br />
from 10 to 12 bits at up to 50 MSPS. The quoted channel <strong>de</strong>nsities require the use of highly<br />
integrated electronics, in or<strong>de</strong>r to fit into the space requirements. The large channel count of the<br />
TRD and RICH <strong>de</strong>tector also favors microelectronics for cost reasons.<br />
195
196 Common Front-End Electronics Aspects<br />
Figure 9.1 sketches the typical building blocks found in mo<strong>de</strong>rn <strong>de</strong>tector readout electronics. The first<br />
element, the preamplifier, forms the interface to the sensor or <strong>de</strong>tector and amplifies the typically weak<br />
signals to <strong>de</strong>fined internal working signal levels. It is followed by a first analogue filter, which implements<br />
the required anti aliasing filter to match the following time discrete stages. It may also inclu<strong>de</strong><br />
some first signal shaping, for instance converting the step function, as measured by gas <strong>de</strong>tectors, into<br />
a pulse with proportional amplitu<strong>de</strong>. These prepared analog signals, which are implemented best in a<br />
differential manner, are then digitized and processed further by appropriate digital filters. It is a general<br />
trend to digitize as early as possible and to implement the signal processing in digital filters. Digital logic<br />
presents a variety of advantages, given enough bits, such as error free signal processing, no additional<br />
introduction of electronic noise, possibility relatively good technology in<strong>de</strong>pen<strong>de</strong>nce, by using standard<br />
cells, just to name a few. The processed analogue signals are then zero suppressed in the next processing<br />
stage, implementing typically multi threshold hit fin<strong>de</strong>r algorithms. Depending on the architecture of the<br />
readout and trigger system the data is stored intermediately and finally shipped off the <strong>de</strong>tector, using<br />
some back-end drivers, which often inclu<strong>de</strong> high-speed serializer and electrical-optical signal converters.<br />
Si Si Strip Strip<br />
Pad Pad<br />
GEM's<br />
GEM's<br />
PMT PMT<br />
APD's<br />
APD's<br />
PreAmp PreAmp<br />
Anti- Anti-<br />
Aliasing Aliasing<br />
Filter Filter<br />
pre pre<br />
Filter ADC<br />
Filter ADC<br />
Sample Sample rate: rate:<br />
10-100 10-100 MHz MHz<br />
Dyn. Dyn. range: range:<br />
8...>12 8...>12 bit bit<br />
digital digital<br />
Filter Filter<br />
'Shaping' 'Shaping'<br />
1/t 1/t Tail Tail<br />
cancellation cancellation<br />
Baseline Baseline<br />
restorer restorer<br />
Hit Hit<br />
Fin<strong>de</strong>r Fin<strong>de</strong>r<br />
Hit Hit<br />
parameter parameter<br />
estimators: estimators:<br />
Amplitu<strong>de</strong> Amplitu<strong>de</strong><br />
Time Time<br />
Backend Backend<br />
& Driver Driver<br />
Clustering Clustering<br />
Buffering Buffering<br />
Link Link protocol protocol<br />
Detector specific generic<br />
Figure 9.1: Typical generic electronics chain<br />
The implementation of digital filters and digital hit selection has the draw-back that the ADCs have to<br />
be operating at constant walk, with the consequence of the ADC digitizing baseline signals most of its<br />
operation time, <strong>de</strong>pending on the occupancy of the <strong>de</strong>tector.<br />
The building blocks shown Fig. 9.1 are lesser <strong>de</strong>tector specific, the later they are located in the processing<br />
chain, where the first unit, the preamplifier is highly <strong>de</strong>tector specific and is typically co-<strong>de</strong>veloped<br />
with the <strong>de</strong>tector architecture and geometry, while the back-end serializer and drivers are typically very<br />
generic and not <strong>de</strong>tector specific at all. This observation leads to the goal to build as much as possible<br />
generic building blocks, with the appropriate customization options, in or<strong>de</strong>r to allow moving the bor<strong>de</strong>r<br />
between generic and <strong>de</strong>tector specific <strong>de</strong>velopment as far as possible to the front of the electronics chain.<br />
One option could be the <strong>de</strong>finition of a generic multi-purpose ADC with a <strong>de</strong>fined analog input, to which<br />
all <strong>de</strong>tector specific preamplifiers are <strong>de</strong>signed. Another even more ambitious approach could be the<br />
<strong>de</strong>sign of a customizable multi-purpose preamplifier, suitable for multiple <strong>de</strong>tectors.<br />
Another important aspect of the CBM experiment is the elimination of the canonical trigger hierarchy.<br />
In CBM all front-end systems implement appropriate hit <strong>de</strong>tection circuitry, which selects relevant information<br />
and ships it together with appropriate time stamps off the <strong>de</strong>tector in<strong>de</strong>pen<strong>de</strong>ntly of all other<br />
systems. Consequently there is no maximum latency requirement, except for the selection of the readout<br />
of neighboring channels around a given hit. This architecture opens a large <strong>de</strong>gree of freedom because it<br />
may be pipelined to a high level.
9.1. General Consi<strong>de</strong>rations, Requirements 197<br />
9.1.1 Consi<strong>de</strong>rations with respect to electronics<br />
The requirements for the front-end electronics, sketched above, necessitate the application of microelectronics,<br />
for the first signal processing and readout stages, in particular due to the channel <strong>de</strong>nsity and in<br />
part due to the channel count. One aspect to be consi<strong>de</strong>red in this context is cost. On one hand the mask<br />
cost for mo<strong>de</strong>rn <strong>de</strong>ep submicron processes is around $300k for a 180 nm process and approaches $1M<br />
for a 130 nm process. Multi project wafer (MPW) runs allow to mitigate this high cost by synchronizing<br />
multiple R&D chips and merging them onto one reticle, therefore allowing to share the mask cost. Such<br />
MPW runs typically yield 50 to 100 chips with the option to buy 1. . . 2 times that quantity in addition<br />
for testing. To dates prices range in 180 nm technology between about $10k for a 9 mm 2 chip and about<br />
$35k for a 25 mm 2 chip. The appropriate cost for the 130 nm technology exceeds a factor 2 of these<br />
numbers.<br />
Assuming the lower cost 180 nm process and a minimum of one prototyping run, generates non recurring<br />
engineering NRE cost of $335k per run. Applying these numbers to the CBM TRD <strong>de</strong>tector and<br />
assuming a grouping of 16 channels per chip, results in about $9 per chip. Note the ALICE TRD Tracklet<br />
Processor chip (TRAP) [180] has a per die cost of about $6, assuming a yield of 80%. This chip implements<br />
22 ADCs for 18 active channels, 21 multi stage digital filters, event buffers, four 32-Bit RISC<br />
processors and a simplified 4-port 2.5 GBit network switch on one chip. When comparing these numbers<br />
the NRE cost here exceeds the chip cost by 50% or a factor 45 in case of the ECAL sub-<strong>de</strong>tector,<br />
assuming chips of similar size.<br />
Figure 9.2: Number of ASIC prototyping<br />
cycles in comparison with<br />
required chips for the LHC project.<br />
Each histogram bar corresponds to<br />
one particular chip project. Note<br />
that there is no correlation between<br />
the number of required chips and the<br />
number of prototyping cycles<br />
Another related issue is the number of MPW runs required before the production run is launched. Given<br />
the already very high ratio between NRE and production cost, it is likely to have a larger number of<br />
MPW runs prior to the production run, in or<strong>de</strong>r to minimize the risk. Fig. 9.2 shows a compilation of all<br />
chip <strong>de</strong>velopments for the LHC project at CERN [181]. The number of MPW runs, which were required<br />
for each given chip, are compared with the number of chips required for each given type. There are more<br />
than 75 different chip <strong>de</strong>velopments, requiring between 1 and 14 prototyping cycles. Note the number of<br />
prototyping cycles is not related to the number of chips required in production. Most chips are <strong>de</strong>veloped<br />
with two or three prototyping cycles. However these prototyping cycles will add about $100k per chip<br />
project in NRE. Note further that the number of chips required for any <strong>de</strong>tector at CBM, for instance<br />
about 10k for the TRD assuming a 16 channel chip, is at the low end of the spectrum in Fig. 9.2.<br />
Taking the above observations into account the consequence is to minimize the number of different<br />
silicon processes as far as possible with the goal to use one foundry as baseline for all microelectronics<br />
<strong>de</strong>velopment. This plan has a variety of advantages. First it is possible to build a library of digital and<br />
analog building blocks, to be used in the different chips. Further it is beneficial to implement more<br />
functionality into the chips, allowing them to serve multiple purposes, selected by configuration. The<br />
typically imposed area penalty will only increase the production cost of the chip by a small amount.
198 Common Front-End Electronics Aspects<br />
Further it is possible to share MPW runs for different <strong>de</strong>velopments, as often the minimum MPW silicon<br />
buy is larger than the area required for the given test chip. The disadvantage of this approach is the<br />
complication in schedule for the different <strong>de</strong>tector projects. Finally it is even possible to share the<br />
production run between different possible chip projects, therefore also sharing the very large production<br />
cost.<br />
Such an approach was successfully taken by the ASIC-CC community in the context of the ALICE TRD<br />
TRAP chip. There were many different <strong>de</strong>velopments, which were executed in parallel, sharing the<br />
few MPW runs (here 4). For instance there is the entire digital processing and readout back-end, the<br />
<strong>de</strong>velopment of a 10 MSPS, 10-Bit ADC, a 2.5 GBit ser<strong>de</strong>s, a temperature sensor, instrument amplifier,<br />
specialized low-power LVDS cells, reference voltage generators, and the like. The final production reticle<br />
inclu<strong>de</strong>s 15 TRAP chips, 1 ATOLL chip (high-speed PCI-X network chip for the ALICE HLT) of same<br />
size and four OASE chips (2.5 GBit ser<strong>de</strong>s with digital front-end). The ratio of TRAP and ATOLL was<br />
chosen to match roughly the number of required chips. The TRAP chip itself can be operated as three<br />
different chips with different configurations, <strong>de</strong>pending on where it is mounted insi<strong>de</strong> the <strong>de</strong>tector.<br />
It should be noted here that one important candidate to be consi<strong>de</strong>red in the area of the front-end electronics<br />
is the FPGA. FPGAs utilize the most mo<strong>de</strong>rn silicon technologies, due to the same reasons as<br />
DRAMs do. They have a large number of regular building blocks and allow therefore a much quicker<br />
adoption to new silicon processes than for instance microprocessors do. We may safely assume that the<br />
per gate cost in FPGAs will continue to <strong>de</strong>crease and the internal clock rates will increase. Therefore<br />
it is likely that purely digital <strong>de</strong>signs may be better integrated in FPGAs, possibly using their gate array<br />
option for cost reduction, unless some features are required, which are not available or are unlikely<br />
to become available in the context of FPGAs. The technological <strong>de</strong>velopment of FPGAs will have to<br />
be monitored very carefully during the course of the <strong>de</strong>velopment of the CBM <strong>de</strong>tector (refer also to<br />
section 9.10.2).<br />
9.1.2 Microelectronics technology choice<br />
Several Application Specific Integrated Circuits (ASICs) will be <strong>de</strong>veloped for the particular requirements<br />
of CBM. In or<strong>de</strong>r to share expertise and building blocks (’IP cells’) among the various <strong>de</strong>signers<br />
involved it is the goal of CBM to use the same technology for the majority of the <strong>de</strong>signs (see also<br />
figure 9.2, section 9.1.1).<br />
Most groups involved so far in the <strong>de</strong>velopment of integrated front end and readout electronics are<br />
presently using the 0.18 µm technology from UMC. This technology is therefore the most obvious candidate<br />
for a baseline. Moving to another technology requires strong arguments. Going ’back’ to feature<br />
sizes of 0.25 µm or more does not seem to be reasonable and feasible, as certain <strong>de</strong>signs (serial links,<br />
high resolution TDC, ADC) require the speed of a 0.18 µm technology. Moving to technologies smaller<br />
than 0.13 µm does not seem to be required. These very mo<strong>de</strong>rn technologies are difficult to access and<br />
are probably not affordable at this time. The following three options for a baseline are therefore possible:<br />
1. stay with UMC 0.18 µm;<br />
2. switch to a 0.18 µm technology from an other vendor;<br />
3. move to 0.13 µm.<br />
The first option is favored by CBM at this point in time for the following reasons:<br />
• Existing expertise. As mentioned above, the groups involved have a running <strong>de</strong>sign flow for this<br />
option. The typical initial problems when installing a new <strong>de</strong>sign kit have been solved.
9.1. General Consi<strong>de</strong>rations, Requirements 199<br />
• Existing IP cells. Several existing building blocks can immediately be used. Examples are given<br />
in the next section.<br />
• Technology characterization. The technology is already well characterized through measurements<br />
on test structures.<br />
• Cost. For the same functionality, the cost (UMC trough Europractice) of 0.13 µm increases by<br />
roughly 50%. Extra overhead is introduced by the more or less fixed size of bonding pads, so that<br />
pad limited <strong>de</strong>signs become significantly more expensive.<br />
• Analog Design Possibilities. Analog circuit <strong>de</strong>sign becomes more difficult in some respects as<br />
feature sizes shrink due to reduced dynamic range and increased leakage current.<br />
• Run schedule. Slightly more runs are scheduled for 0.18 µm (6 vs. 4 per year) so that prototyping<br />
<strong>de</strong>signs can be submitted easily. There are also slightly more Mini-Asic runs (3 vs. 2 per year).<br />
• Radiation hardness. Although the exact doses expected at CBM are not yet well known, we<br />
believe that the radiation hardness of <strong>de</strong>signs in a 0.18 µm technology even without any special<br />
precautions is sufficient.<br />
• Layout <strong>de</strong>nsity is roughly doubled for standard cells when moving from 0.18 µm to 0.13 µm. We<br />
do not see this as an advantage by itself. However, pad limited <strong>de</strong>signs do not benefit from the die<br />
shrink because bond pad size remains constant for packaging reasons. Further analog <strong>de</strong>signs also<br />
may not fully utilize the full area saving. On the other hand at this point in time the cost for MPW<br />
runs is twice the cost of a comparable 0.18 µm process.<br />
• Routing Layers. More advanced technologies also offer more routing layers (8 vs. 6 for UMC).<br />
We believe, however, that the six layers available in the 0.18 µm technology are enough for the<br />
<strong>de</strong>signs we envisage.<br />
• Power consumption. The power consumption at a given circuit <strong>de</strong>creases for smaller feature size<br />
due to shrinking capacitances. We do not, however, expect power consumption to be a major<br />
problem in this fixed target application.<br />
• Speed. Designs become faster with shrinking feature sizes. In this context also copper processes<br />
have to be consi<strong>de</strong>red, due to its higher conductivity it allows faster interconnect routing. Copper<br />
starts becoming important at feature sizes of about 0.18 µm. However, we are confi<strong>de</strong>nt, that our<br />
<strong>de</strong>sign goals can be met with the present technology. An exception may be a TDC with a resolution<br />
of a few ps only.<br />
It should be noted that CERN has chosen a 0.13 µm technology as the baseline for future <strong>de</strong>velopments<br />
thereby replacing a 0.25 µm process. With the <strong>de</strong>cision to drop a technology which is consi<strong>de</strong>red to<br />
be not sufficient anymore, CERN goes a significant step (of a factor of roughly four with respect to<br />
the 0.25 µm process) further. The situation in CBM is different, because the technology step would be<br />
relatively small. Note also that LHC++ will start later than FAIR so that a longer term perspective is<br />
reasonable.<br />
CBM retains the option to transition to a more advanced technology, if really required, after 3-4 years<br />
of R&D when the experiment’s requirements are well un<strong>de</strong>rstood and most of the critical electronics<br />
building blocks have been <strong>de</strong>signed. An appropriate die shrink step can be implemented in a timely<br />
manner.
200 Common Front-End Electronics Aspects<br />
9.2 Existing microelectronics building blocks<br />
The <strong>de</strong>velopment of microelectronic circuits has a significant overhead with respect to the maintenance<br />
of the software and <strong>de</strong>sign libraries as well as the requirement to study and test certain process features,<br />
which may not be well represented in the appropriate libraries of the foundry. In the context of the<br />
ALICE TRD project a group of four institutes has joined forces in the ASIC Competence Center (ASIC-<br />
CC) and has <strong>de</strong>veloped a variety of modular ASIC building blocks, which may be reused in the context<br />
of the CBM project or serve as starting point for improvements and customizations. An appropriate list<br />
of available building blocks is compiled below with a brief <strong>de</strong>scription of the <strong>de</strong>vices. All listed building<br />
blocks have been built and tested. The <strong>de</strong>velopments have centered around the UMC 0.18 µm process,<br />
where some are in 0.13 µm for further reference.<br />
9.2.1 TRAP-ADC<br />
The TRAP-Chip of the ALICE Transition Radiation Detector required a 10 bit 10 MS/s-ADC with the<br />
shortest possible conversion latency, to be integrated in a multichannel array together with the complex<br />
digital electronics of this signal processor.<br />
Figure 9.3: Photograph of a single TRAP-ADC. Dimensions:<br />
200 µm × 550 µm<br />
The stringent requirements in terms of power and chip area were met with a cyclic ADC-architecture,<br />
which turned out as optimal solution for this application. At 10 MS/s the power consumption of a single<br />
TRAP-ADC is 12 mW, a value close to that of other state of the art ADCs published.<br />
Figure 9.4: Effective number of bits (ENOB)<br />
and signal-to-noise ratio (SNR) versus input frequency<br />
of the TRAP-ADC<br />
Figure 9.5: Output spectrum of the low-power<br />
version @ 100kHz signal frequency. The signal<br />
frequency was limited by the test setup.<br />
Cyclic ADCs use the same conversion principle like pipeline ADCs, but consist of only one stage which<br />
performs the quantization in a sequential manner. As recent pipeline ADCs in 0.18 µm CMOS reach<br />
100 MS/s, the maximum achievable throughput at 10 bit resolution is in the or<strong>de</strong>r of 10 MS/s, while the<br />
converter area is greatly reduced compared to a pipeline implementation. The photograph of a single<br />
TRAP-ADC, which occupies only 0.11 mm 2 of silicon, is <strong>de</strong>picted in Fig. 9.3.
9.2. Existing microelectronics building blocks 201<br />
Parameter TRAP-ADC Low-Power version<br />
Resolution 10 bit 10 bit<br />
Conversion rate 10 MS/s 10 MS/s<br />
Active area 0.11 mm 2 0.11 mm 2<br />
Power consumption 12 mW @ 10.4 MS/s 7 mW @ 10.4 MS/s<br />
Input range ±1 V – ±1.4 V ±1 V<br />
DNL –0.4/+0.6 LSB not analyzed yet<br />
INL –0.8/+0.7 LSB not analyzed yet<br />
ENOB 9.5 @ 1 MHz input 9.1 @ 100 kHz<br />
SNR 59.2 dB @1 MHz input 56.4 dB @ 100 kHz<br />
SFDR 73.0 dB @ 1 MHz input 63.0 dB @ 100 kHz<br />
THD -69.5 dB @ 1 MHz input -74.2 dB @ 100 kHz<br />
Table 9.1: Listed data of the TRAP-ADC and its low-power version<br />
Various advanced <strong>de</strong>sign techniques like a second set of sampling capacitors to enlarge the sample interval,<br />
conversion cycles of different lengths or a pseudodifferential implementation to save power were<br />
exploited to obtain this ADC [182].<br />
In Fig. 9.4 the effective number of bits (ENOB) and the signal-to-noise ratio (SNR) versus input signal<br />
frequency are shown. The ENOB stays well above 9 bit over the whole Nyquist frequency range.<br />
Due to the tight project schedule of the TRAP-<strong>de</strong>velopment the TRAP-ADC was in many points rather<br />
conservatively <strong>de</strong>signed in or<strong>de</strong>r to ensure a reliably working circuit. The knowledge gained during<br />
<strong>de</strong>signing and testing the TRAP-ADC allowed to implement a more improved version with lowered<br />
power consumption. Though it has not been completely tested yet, its first performance data in Fig. 9.5<br />
and table 9.1, right column, are promising. The power consumption is 7 mW @ 10 MS/s. This ADC<br />
shows the possible power efficiency of similar converters in the future.<br />
Table 9.1 summarizes the performance data of the TRAP-ADC and its low-power version.<br />
9.2.2 LVDS IO Cells.<br />
These cells are layout compatible to the digital standard IO cells. They can operate at up to 500 MHz<br />
at a power consumption of 7.4 mW for the transmitter and 0.5 mW for the receiver. Both transmitter<br />
and receiver can be disabled, putting them into a low power mo<strong>de</strong>. An enabled receiver, being driven<br />
by a disabled transceiver will generate a <strong>de</strong>fined ZERO at its internal outputs, therefore allowing the<br />
dynamic enabling and disabling of the LVDS transmitters without generating any si<strong>de</strong> effects at the<br />
receiver end, provi<strong>de</strong>d the <strong>de</strong>fault signal state is <strong>de</strong>fined as ZERO. There is a second set of LVDS standard<br />
I/O cells, which incorporate the complete boundary scan logic, drastically simplifying the boundary scan<br />
placement and routing.<br />
9.2.3 On-Chip Slow Control<br />
For mo<strong>de</strong>rn high complex integrated read out electronics it is very helpful to have access to several<br />
system parameters as core voltages and temperature.<br />
For this reason an analog multiplexer and switched capacitor attenuator was <strong>de</strong>signed for the TRAP chip,<br />
which is available as standard cell in the UMC 0.18 µm-CMOS technology. The cell provi<strong>de</strong>s eight fully<br />
differential analog inputs that could be attenuated by factors of 1, 3/4, 2/3, 1/2, 1/3 and 1/4.
202 Common Front-End Electronics Aspects<br />
Using the switched capacitor technology in the attenuator provi<strong>de</strong>s minimum power consumption during<br />
operation and even zero power in stand by mo<strong>de</strong>.<br />
9.2.4 Analogue multiplexer, auxiliary ADC, temperature sensor and voltage reference<br />
For monitoring on-chip supply voltages, temperature and reference voltage, an auxiliary ADC was combined<br />
with an analogue multiplexer. This IP-cell can be placed manually and routed to several test points<br />
of the system on chip. The auxiliary ADC runs at reduced clock frequency and power as required. The<br />
multiplexer offers several attenuation factors corresponding to capacitor ratios, which can be selected by<br />
the slow control unit. The IP-cell was verified and successfully tested on the TRAP chip.<br />
The on chip temperature sensor relies on the change of a pn-junction voltage at constant current. The<br />
signal is amplified relative to a band-gap reference voltage, using a continuous time instrumentation<br />
amplifier. The measurements have shown a useful temperature range from -30 to +120 <strong>de</strong>gree Celsius.<br />
Scale is fairly linear; the resolution obtained using the multiplexer/ADC-cell is approx. 0.2 <strong>de</strong>gree.<br />
The offset of the scale has sufficient reproducibility for monitoring purposes, although no provisions<br />
for trimming have been inclu<strong>de</strong>d. The application could perform global numerical trimming in or<strong>de</strong>r<br />
to compensate for manufacturing tolerances (i.e. offsets, mobility, implant). Fig. 9.6 shows a typical<br />
measurement of the temperature sensor taken on the TRAP chip.<br />
Voltage [mV]<br />
600<br />
400<br />
200<br />
−40 −20 0<br />
20 40 60<br />
−200<br />
Temperature [<strong>de</strong>g.C]<br />
−400<br />
−60<br />
−800<br />
−1000<br />
T=(Co<strong>de</strong>−287)x(40/241)<br />
Figure 9.6: Measurement of the temperaturesensor<br />
output<br />
VBandgap[V]<br />
1,38<br />
1,36<br />
1,34<br />
1,32<br />
1,3<br />
1,28<br />
1,26<br />
1,24<br />
1,22<br />
−40,000 −20,000<br />
1,2<br />
0,000 20,000 40,000 60,000 80,000 100,000 120,000<br />
Tem p[Celcius]<br />
Figure 9.7: Measured bandgap voltage versus<br />
temperature<br />
The on-chip reference voltage generator is a classical bootstrap band-gap voltage source, using multiples<br />
of pn-junctions in an n-well as reference <strong>de</strong>vices. The output voltage is optionally filtered by the low-pass<br />
formed by the 100k Ohm output resistance and an external capacitor which is connected between output<br />
pin and <strong>de</strong>dicated ground return pin. Thermal noise can thus be largely suppressed. No provisions for<br />
trimming are implemented, still the variation of the nominal 1.26 V output voltage measured on a series<br />
of chips was less than one percent. The measurement over temperature, <strong>de</strong>picted in Fig. 9.7, was ma<strong>de</strong><br />
with the latest TRAP chip.<br />
9.2.5 Digital Filters<br />
The digital filter within the TRAP chip is separated into five functional parts. Within the filter two<br />
additional <strong>de</strong>cimal places for number representation are used to reduce numerical errors.<br />
A nonlinearity correction filter performs a look-up table based common correction of the ADC signal.<br />
The signal is moved to a configurable baseline by a pe<strong>de</strong>stal correction filter. Therefore the individual<br />
baseline level of each channel is <strong>de</strong>termined by a first or<strong>de</strong>r low band pass filter with various time constants<br />
of 0.8 ms to 0.8 s. A gain correction filter scales the signal in each channel by an individually
9.2. Existing microelectronics building blocks 203<br />
choosable factor. These factors have to be <strong>de</strong>termined by the on-chip CPUs performing basic spectral<br />
analysis based on histogramming counters which are inclu<strong>de</strong>d into the data chain. Tail cancellation is <strong>de</strong>signed<br />
as a second or<strong>de</strong>r recursive IIR filter with variable parameters. Crosstalk suppression is available<br />
as a fourth or<strong>de</strong>r FIR filter.<br />
9.2.6 High-speed Tracklet Processor<br />
In this block of the TRAP chip the signal is parameterized by a set of track segments (tracklets). Therefore<br />
a maximum of four clusters per time step can be <strong>de</strong>tected and inclu<strong>de</strong>d into the associated tracklet.<br />
The two coordinates of a cluster are drift time and pad position which is calculated by using charge<br />
sharing between adjacent channels. Tracklets are built channel-wise by accumulating the parameters of<br />
a straight line fit and charge in various sections of the drift time.<br />
9.2.7 32-bit RISC CPU<br />
The CPU-core is 32-bit RISC processor, impelementing a two stage pipeline and some special components<br />
(Fig. 9.8). The Fit Register File (FRF) is the interface to the Preprocessor. The Global Register File<br />
(GRF) is the fastest way to exchange information between the 4 CPU cores and to synchronize them. The<br />
fixed and programmable Constants can be used like registers. The Arbiter gives access to the IO <strong>de</strong>vices,<br />
shared by the 4 CPUs and the SCSN interface (section 9.2.12). The instruction memory is private 4k x 24<br />
+ hamming bits. The data memory is quad ported, 1k x 32 + hamming.<br />
5<br />
5<br />
4<br />
4<br />
3<br />
D D<br />
IMEM<br />
DECODER<br />
PIPE1 PIPE2<br />
WE<br />
WA<br />
WD<br />
RA<br />
GRF<br />
RD<br />
PRF<br />
WDAT<br />
C C<br />
ADDR RDAT<br />
WE<br />
WA<br />
PRF15<br />
WD<br />
<strong>de</strong>vices<br />
RA_A RD_A<br />
RA_B RD_B<br />
MEM read<br />
FIT<br />
RA_A RD_A<br />
RA_B RD_B<br />
B B<br />
r/w<br />
PC<br />
IMM<br />
IMM<br />
PRF_A<br />
PC+1<br />
ShadowPC<br />
RA<br />
CON<br />
RD<br />
PRF_A<br />
GRF<br />
PRF_B<br />
PRF15<br />
IMM<br />
PRF_B<br />
GRF<br />
r/w<br />
A A<br />
3<br />
IO write data<br />
ALU<br />
r<br />
w<br />
2<br />
IO read<br />
MEM address<br />
PRF_A<br />
IO address<br />
2<br />
Counter/<br />
timer<br />
IRQ<br />
contr<br />
Arbiter<br />
other<br />
QPDMEM<br />
ADDR RDAT<br />
WDAT<br />
Figure 9.8: Block diagram of the CPU core<br />
9.2.8 Network Interface<br />
1<br />
1<br />
local I/O 0<br />
local I/O 1<br />
local I/O 2<br />
local I/O 3<br />
global I/O<br />
A0<br />
Di0<br />
Do0<br />
A1<br />
Di1<br />
Do1<br />
A2<br />
Di2<br />
Do2<br />
A3<br />
Di3<br />
Do3<br />
AG<br />
Di4<br />
DoG<br />
Network<br />
Interface<br />
I/O 0<br />
I/O 1<br />
I/O 2<br />
I/O 3<br />
I/O G<br />
16<br />
16<br />
16<br />
16<br />
port 3 port 2 port 1 port 0<br />
16<br />
FiFo<br />
128x16<br />
10 10 10 10<br />
16 16 16 16<br />
16<br />
FiFo<br />
128x16<br />
16<br />
FiFo<br />
128x16<br />
16 16 16 16<br />
16<br />
FiFo<br />
128x16<br />
endsig endsig endsig endsig<br />
16 16 16 16<br />
16<br />
port 4<br />
Figure 9.9: Network Interface block diagram<br />
Given the large <strong>de</strong>tector surface area and number of 65000 MCMs to be readout, the best architecture<br />
is to implement a multi-level readout tree. The resulting 4-to-1 readout trees, which collect the data<br />
of 64 MCMs each, are build up by a Network Interface (NI), which is a part of the tracklet processor<br />
chip. The NI consists of four 10 Bit wi<strong>de</strong> input ports, one output port, FIFOs, interfaces to the processor,<br />
and control logic (Fig. 9.9). The data transfer is performed with 120 MHz DDR, therefore running at<br />
2.5 GBit/s. In or<strong>de</strong>r to save power the NI is capable of operating stand-alone and dynamically switching<br />
off unused LVDS ports.<br />
10
204 Common Front-End Electronics Aspects<br />
9.2.9 High Performance ALU<br />
The ALU applies arithmetic and logic operations on two 32-bit integer operands. It implements binary<br />
logic (and, or, xor) and the standard set of typical integer arithmetic operations. In addition, bit shifts of<br />
variable distance can be applied. The implementation allows for high clock rates, while still performing<br />
most arithmetic operations in a single clock cycle using a non-pipelined architecture. The selected<br />
implementation for the divi<strong>de</strong>r is a high-performance CSA-based radix-4 divi<strong>de</strong>r.<br />
9.2.10 Quad Port Memory<br />
The quad port memory is the data memory for the four RISC CPUs of the Trap Chip. It allows four<br />
concurrent accesses simultaneously. Each port can be used in<strong>de</strong>pen<strong>de</strong>ntly for read or write access. Data<br />
written via one port is also available via all other ports. This memory is an i<strong>de</strong>al place for mutual data<br />
exchange between the four CPUs on the TRAP die. It fills an area of 1.36 mm 2 and offers a capacity of<br />
1024 words. Each word has 32 bits plus 7 hamming bits for error correction.<br />
9.2.11 Programmable Delay Unit & Network Fault Tolerance<br />
All output signals can be shifted in multiples of ∼1 ns (Fig. 9.10) with respect to the reference clock.<br />
This Programmable Delay Unit is <strong>de</strong>signed to equalize skew caused by different trace lengths on die,<br />
PCB or interconnect. Its dynamic range covers a full clock period of 120 Mhz.<br />
Propagation <strong>de</strong>lay (ps) after Delay Unit<br />
9000<br />
8000<br />
7000<br />
6000<br />
5000<br />
4000<br />
3000<br />
2000<br />
D<br />
LH bit3 single<br />
HL bit3 single<br />
LH bit3<br />
HL bit3<br />
SERIAL<br />
S0out S1in<br />
D<br />
1000<br />
SLAVE<br />
S0in S1out<br />
1 5<br />
0<br />
0 1 2 3 4 B5 6 7<br />
ring 0<br />
ring 0<br />
B<br />
<strong>de</strong>lay selected in Delay Unit<br />
Figure 9.10: Measured results of one <strong>de</strong>lay<br />
channel for different transitions of the channel<br />
itself and its direct neighbors.<br />
5<br />
5<br />
4<br />
ring 1<br />
4<br />
3<br />
C C<br />
3 3<br />
S0out S1in<br />
MASTER<br />
SLAVE<br />
5 1<br />
SLAVE<br />
4 2<br />
SLAVE<br />
SLAVE<br />
2 4<br />
A A<br />
3<br />
S0in S1out<br />
BRIDGED<br />
2<br />
2<br />
MASTER<br />
Figure 9.11: SCSN architecture, implementing<br />
two anticyclic rings (left). Bridge operation,<br />
eliminating single points of failure<br />
Dedicated test patterns allow to optimize the eye pattern for each link. Normally the link consists of<br />
8 Bit data, 1 Bit parity and 1 Bit spare. The position of the spare bit can be configured within the 10 Bit<br />
port. In addition the parity bit can be exclu<strong>de</strong>d to get two redundant bits. However, in this case no error<br />
<strong>de</strong>tection can be performed.<br />
9.2.12 SCSN Redundant High-speed Configuration Network<br />
The Slow Control Serial Network (SCSN) transmits data packets at 24 <strong>MB</strong>it/s speed. It is organized as<br />
two antizyclic rings, allowing to address up to 126 slaves in one ring. If some connection is broken,<br />
the second ring can be used. If a no<strong>de</strong> fails full connectivity to the remaining no<strong>de</strong>s can be obtained<br />
by configuring the operational neighboring no<strong>de</strong>s to perform a loop back operation, therefore breaking<br />
up the two redundant large rings into two in<strong>de</strong>pen<strong>de</strong>nt small rings (refer also to Fig. 9.11). The SCSN<br />
ring 1<br />
1<br />
1
9.3. Overall Architecture 205<br />
protocol implements fixed length packets with a payload of 32 bit data, 16 bit address, CRC check. It implements<br />
remote shared memory commands, including special network commands, such as ping, bridge,<br />
broadcast. The broadcast commands are reliable, and are used to initialize common data structures, such<br />
as the instruction memories of the front-end TRAP chips.<br />
9.3 Overall Architecture<br />
The sections above outlined the requirement for a mostly generalized front-end electronics. It is pointed<br />
out again that the majority of the cost will be in the non recurring engineering and not in the chip cost<br />
itself. Further should be noted that the experience, gained in the ALICE TRD project, where the channel<br />
count exceeds the CBM TRD <strong>de</strong>tector by a factor two, also suggests to consi<strong>de</strong>r tra<strong>de</strong>-offs between the<br />
chip size and the integration cost. For instance if the bonding PAD pitch is chosen too small then the<br />
cost for the chip package or carrier will increase dramatically, while a slightly larger chip may already<br />
support the use of low-cost PCB material, using a feature size of 110 µm, as carrier (CoB). In such<br />
cases it will be very cost effective to <strong>de</strong>sign somewhat larger chips in favor of the reduced integration<br />
cost. For instance in the ALICE TRD project the integration cost of the TRAP chip (bonding, glob-top,<br />
BGA sol<strong>de</strong>ring) amounts to about 8.9 (26% NRE, 15% consumables, 59% manpower) while the chip<br />
cost itself is at about $6. Note the largest integration cost components are man power and NRE, which<br />
typically increase as the production unit count <strong>de</strong>creases. Note further that the cost per silicon real estate<br />
is about 10 Cents without yield correction.<br />
Given these consi<strong>de</strong>rations it is attractive to aim for one or a few mostly generic chips, that can serve<br />
an as large as possible set of purposes within the CBM <strong>de</strong>tector. Such generic chips will inclu<strong>de</strong> functionality<br />
of several in<strong>de</strong>pen<strong>de</strong>nt functions which may never all be enabled simultaneously, resulting in<br />
any configuration having disabled areas on the chip. This, however, is not consi<strong>de</strong>red a disadvantage as<br />
the arguments above drive towards larger chips anyway and such configuration options may use silicon<br />
real estate, which would otherwise be used for filler structures. A <strong>de</strong>tailed analysis of these tra<strong>de</strong>-offs<br />
remains until the <strong>de</strong>tailed <strong>de</strong>tector requirements are finalized.<br />
The CBM <strong>de</strong>tectors do not operate a classical trigger/readout architecture. Instead all <strong>de</strong>tector channels<br />
implement some hit selection functionality, generating a data stream of time stamped hits, which are then<br />
coalesced within the higher layers of the readout system. In this context it has to be noted that on one<br />
hand this coalescing will have to merge several events into one container, for instance since there are<br />
slow <strong>de</strong>tectors (e.g. MAPS), which cannot resolve hits at resolutions down to nanoseconds and since in<br />
or<strong>de</strong>r to avoid granularity losses the hits with time information close to a time granularity bor<strong>de</strong>r have to<br />
be replicated. In addition this trigger less architecture requires a very precise time stamping information<br />
for all fast <strong>de</strong>tectors in or<strong>de</strong>r to minimize the combinatorial background when putting together hits to<br />
events.<br />
Further all front-end modules have to have precision time information, in or<strong>de</strong>r to allow proper hit matching.<br />
Given the average event rate of 10 MHz a hit time resolution of 1 ns appears a<strong>de</strong>quate for the hit<br />
i<strong>de</strong>ntification. The hit time should be adjusted for the various <strong>de</strong>tector channels, such that particles at<br />
c = 1 have the same time stamp.<br />
The front-end hit selection has to implement some next neighbor functionality in or<strong>de</strong>r to allow the<br />
readout of next neighboring channels below the threshold in or<strong>de</strong>r to digitize the entire hit cluster. Depending<br />
on the cluster size one approach could be to implement preamplifiers with multiple outputs per<br />
channel, which would be routed such to different digitization chips, that un<strong>de</strong>r all circumstances at least<br />
one digitization chip has a complete cluster available. This approach was chosen for the ALICE TRD. It<br />
heavily relies on the number of next neighbors being very low and the corresponding cluster size being<br />
small. One consequence is power and cost overhead for the additional digitizer channels. In case of the
206 Common Front-End Electronics Aspects<br />
ALICE TRD this overhead is 17%. However, this architecture cannot be a general solution. Therefore<br />
it is required to exchange the information of a given hit to the appropriate chips, processing neighboring<br />
channels. In general there are two principally different approaches. One is to just exchange some<br />
kind of hit signals between the next neighbors, which trigger the readout in<strong>de</strong>pen<strong>de</strong>nt of its hit status<br />
if a neighbor has a signal i<strong>de</strong>ntified as hit. The second option uses the CNet readout infrastructure to<br />
distribute the hit information to the next neighbors, using some kind of low latency multi cast. Latency<br />
is very important here as all hits have to be stored for that amount of time. Assuming a canonical <strong>de</strong>tector<br />
readout system, results in readout link lengths of several tens of meters, resulting in latencies of<br />
hundreds of nanoseconds. High-speed switches have propagation latencies of hundreds of ns, ranging<br />
up into the µs range, while assuming zero load. At a digitization rate of 50 MHz this corresponds to<br />
50 time bins. However, in the example discussed we may not assume the appropriate switch to be idle,<br />
as it may happen that a large number of neighboring <strong>de</strong>tector channels are hit simultaneously. Un<strong>de</strong>r<br />
all normal circumstances there will be a load <strong>de</strong>pen<strong>de</strong>nt <strong>de</strong>lay in the appropriate switches, requiring an<br />
appropriately large input buffer (refer also to section 9.9).<br />
It should be noted also, that in any case some buffering of the analog signals is required in or<strong>de</strong>r to access<br />
the leading edge of a <strong>de</strong>tector signal, when a hit is <strong>de</strong>tected, for instance by some peak sensing logic.<br />
However, it is often not possible to combine physically adjacent <strong>de</strong>tector channels on the same readout<br />
board, making it difficult to exchange the hit information in this scenario. Given the arguments presented,<br />
the next neighbor hit selection is implemented wherever possible by generating hit messages and<br />
directly distributing them to the appropriate next neighbor chips, which resi<strong>de</strong> on the same or adjacent<br />
readout boards. Neighboring channels, which cannot be handled in this manner receive their neighbor<br />
hit information via higher levels of CNet, which will only see a small fraction of the resulting message<br />
transfer, as most of it is done on the readout boards. This message transfer puts very high absolute latency<br />
requirements on the CNet architecture. Note that this latency requirement may be reduced at the<br />
cost of power consumption by lowering the digitization threshold very close to the baseline, resulting<br />
in many low level readout triggers, resulting in the appropriate data being stored in the front-end digital<br />
buffers, allowing a loss less storage of this information for a longer period of time. For a hit trigger<br />
to be communicated to neighboring channels, however, an appropriate second threshold will have to be<br />
met. The baseline data is readout only if a matching hit trigger is received. It will be discar<strong>de</strong>d after<br />
the maximum hit trigger time-out has been reached. Appropriate discrete event simulations remain to be<br />
done in or<strong>de</strong>r to mo<strong>de</strong>l this system.<br />
Every <strong>de</strong>tected hit has to be time stamped with a time resolution of about 1 ns. This resolution is not<br />
good enough or inten<strong>de</strong>d for any time-of-flight measurements but only used to disentangle the various<br />
hits insi<strong>de</strong> the <strong>de</strong>tectors. A time measurement with this resolution is very feasible to be implemented<br />
purely using digital standard cells and therefore does not present a particular technological challenge.<br />
Another si<strong>de</strong> effect of the elimination of the trigger signal is the increased requirement for noise reduction.<br />
While in triggered systems effort may be implemented for the trigger <strong>de</strong>tectors in or<strong>de</strong>r to not fire<br />
in case of noise hits and therefore suppressing any noise in any other <strong>de</strong>tector outsi<strong>de</strong> the trigger window,<br />
the given architecture will readout any noise hit. Two strategies will have to be <strong>de</strong>ployed. First the hit<br />
<strong>de</strong>tection on the <strong>de</strong>tector within the front-end electronics will already have to implement somewhat more<br />
advanced hit <strong>de</strong>tection as usual. Further the hit merging functionality at the higher levels of the readout<br />
chain will have to i<strong>de</strong>ntify isolated hits, likely to be noise, and discard them.<br />
Fig. 9.12 sketches the building blocks required for the CBM front-end electronics. The first stage is the<br />
preamplifier. By <strong>de</strong>fining appropriate electrical and physical interfaces it is possible to have multiple<br />
preamplifier standard cells, which may be tuned for the specific <strong>de</strong>tector and inserted into reserved areas<br />
on the chip during the tape-out phase. In or<strong>de</strong>r to gain maximum in<strong>de</strong>pen<strong>de</strong>nce between the sensitive<br />
analog preamplifiers and the higher stages of the electronics chain on the chip all signals are planned to be<br />
done differentially. These adaptive filter blocks are optimized to fit the following ADC stage. The second
9.3. Overall Architecture 207<br />
Ain<br />
1..N<br />
N Pre-<br />
Amplifier<br />
Blocks<br />
.<br />
.<br />
.<br />
Hit Detector<br />
• Leading Edge<br />
• peak<br />
• …<br />
DAC<br />
Analog<br />
Filter<br />
to/from next<br />
neighbor hit<br />
<strong>de</strong>tection<br />
to/from next<br />
neighbor hit<br />
<strong>de</strong>tection<br />
Programmable<br />
Finite State<br />
Machine<br />
TIMER<br />
CLOCK<br />
WE RE<br />
ANALOG<br />
FIFO<br />
start<br />
Hit TDC<br />
stop<br />
sample<br />
ADC<br />
different combinations<br />
• sampling rate<br />
• resoluion<br />
• power<br />
Digital<br />
Pipeline<br />
Digital<br />
Filters<br />
Figure 9.12: Overview of the required FEE building blocks<br />
send<br />
Fast<br />
Readout<br />
we<br />
Event<br />
Buffers<br />
DATA-out<br />
stage are analog filters, implementing necessary analog functionality, including an anti aliasing filter. The<br />
analog signals are subjected also to an analog hit <strong>de</strong>tector, which is sketched in a most simple form as<br />
single, programmable threshold leading edge discriminator. Depending on the <strong>de</strong>tector requirements it<br />
may become required to implement more advanced hit <strong>de</strong>tectors, such as peak <strong>de</strong>tectors and the like.<br />
The hit <strong>de</strong>tectors generate a hit signal, which may be distributed to the next neighbors. The hit signal is<br />
also ORed with the appropriate hit <strong>de</strong>tection signal of the neighboring FEE chips, triggering the readout<br />
of the channel.<br />
In or<strong>de</strong>r to allow the readout of the pre-history, the analog signal has to be sampled at all times. Since the<br />
analog sampling requires less power and infrastructure than the constant walk digitization and storage<br />
in cyclic buffer memories, an analog switched capacitor array is the best solution here. Refer to section<br />
9.5 for a discussion of the various options here. In case of a hit the ADC is enabled, recalling it from<br />
its low-power stand-by mo<strong>de</strong>. It then digitizes the pulse, starting at time bin thit −tprehist in or<strong>de</strong>r to also<br />
capture the prehistory. A similar technique is <strong>de</strong>ployed in all neighboring chips.<br />
The time of the hit is measured by a TDC with respect to the next clock edge. In or<strong>de</strong>r to save power the<br />
TDC is implemented as common stop TDC, leaving all channels without hit in stand-by mo<strong>de</strong>. The hit<br />
time is associated with the hit and subsequently transmitted with the digitized analog information.<br />
The analog-digital conversion is performed by a highly configurable ADC (refer to section 9.6). It is<br />
followed by appropriate digital filters. Unlike in case of triggered <strong>de</strong>tectors where the ADCs have to be<br />
operated at constant walk in or<strong>de</strong>r to ensure correct operation of the digital filters, since some hits may<br />
otherwise be exclu<strong>de</strong>d from the digitization, since they were outsi<strong>de</strong> the trigger window, all relevant hits<br />
are being digitized in this context. Therefore it may be possible to operate digital filter with digitization<br />
duty cycles ≤100%. It should be noted that the fall back position to operate the ADCS in constant walk<br />
remains a configuration option. A particular baseline restoration filter will have to be <strong>de</strong>veloped in or<strong>de</strong>r<br />
to cope with the architecture presented here.<br />
The hit information, which is not required for the digital filters has to be <strong>de</strong>layed with an appropriate<br />
pipeline to match the propagation <strong>de</strong>lay of the digitized analogue data in the digital filters. At the filter
208 Common Front-End Electronics Aspects<br />
output the hit/time data is queued in a <strong>de</strong>randomizing buffer for subsequent readout off the <strong>de</strong>tector using<br />
some high-speed signal transmission system (refer to section 9.8.2). The size of the <strong>de</strong>randomizing<br />
buffers remains to be simulated in <strong>de</strong>tail, <strong>de</strong>pending on the <strong>de</strong>tector granularity and corresponding statistical<br />
hit and data rate fluctuations. However, a buffer size of 8. . . 16 average events with the capability<br />
to store at least one black event, appears to be sufficient.<br />
The building blocks outlined above will be <strong>de</strong>veloped as in<strong>de</strong>pen<strong>de</strong>nt units with well <strong>de</strong>fined interfaces.<br />
However, the goal on the long run is their integration on one larger multi function, multi purpose chip.<br />
However, even if this goal is not achieved, the existence of generic building blocks, which are ready to be<br />
used in different chips, with customized preamplifiers, still serves the purpose of reduced <strong>de</strong>velopment<br />
cost, time and risk.<br />
9.4 First Amplifier Stages<br />
The first amplifier stage, the preamplifier/shaper (PASA), resembles the most <strong>de</strong>tector <strong>de</strong>pen<strong>de</strong>nt component<br />
in the entire electronics chain. Often it has to be co<strong>de</strong>veloped together with the <strong>de</strong>tector architecture.<br />
Different scenarios are conceivable, ranging from entirely in<strong>de</strong>pen<strong>de</strong>nt preamplifier chips, possibly even<br />
being integrated in a different technology, up to the integration of the entire electronics on one die. In<br />
any case a well <strong>de</strong>fined interface <strong>de</strong>fining the analog output of the preamplifier, is required.<br />
The conventional approach is based on separate ICs for the preamplifier and the digital electronics,<br />
including the ADCs. This approach was chosen in case of the ALIC TPC and TRD electronics, there<br />
for the first time the ADCs and the digital back-end were integrated on one die. In this scenario the<br />
preamplifiers have single en<strong>de</strong>d inputs, connected to the <strong>de</strong>tector electro<strong>de</strong>s. This is a practical solution,<br />
providing the required flexibility with respect to different <strong>de</strong>tectors. Disadvantageous is, however, the<br />
large space for board connections, large load capacitance and cross talk at the outputs of the PASA.<br />
Spurious noise at the inputs of the PASA can result from the single en<strong>de</strong>d connections to the chamber.<br />
Interference of signal and power ground is difficult to suppress. This requires a very careful board <strong>de</strong>sign.<br />
In any case differential coupling to the ADCs is used to cancel common mo<strong>de</strong> noise.<br />
The proposed approach is based on a single chip solution. This implies the necessity of differential<br />
inputs, in or<strong>de</strong>r to provi<strong>de</strong> sufficient isolation of signal ground and power ground. Further goal is an<br />
exten<strong>de</strong>d sampling rate of the ADC, which should be variable as an option. This implies a variable antialias<br />
filter in the preamplifier. Assuming a maximum specified sampling rate of 40 MHz and a 12 bit<br />
dynamic range, the <strong>de</strong>sign of the low power analogue amplifiers and buffers is a real challenge with<br />
respect to signal to noise ratio, bandwidth, linearity and dynamic range. More relaxed specifications will<br />
result if we assume a dual-range solution of PASA and ADC. This will be referred to as a recommen<strong>de</strong>d<br />
solution in the ADC section of this document. A draft schematic of an integrated PASA/ADC section of<br />
the proposed system is given below (Fig. 9.13). It is based on a modular <strong>de</strong>sign, which offers sufficient<br />
flexibility for the different <strong>de</strong>tector applications.<br />
The preamplifier is a generic module that takes specific requirements of the <strong>de</strong>tectors into account. The<br />
<strong>de</strong>picted example of this module is typical of a drift chamber <strong>de</strong>tector, with positive impulses of displacement<br />
currents at the input. The feedback capacitor has to be chosen with respect to pad-to-plasma<br />
capacitance, dynamic range and noise figure. Obviously the loop gain of this stage must be very high, in<br />
or<strong>de</strong>r to provi<strong>de</strong> an input impedance as low as possible (virtual ground). This is not easy to achieve, as<br />
the envisaged bandwidth of the system is in opposition to the transit frequency/power limitations of the<br />
CMOS circuits. The <strong>de</strong>sign task is therefore closely related to the chamber specifications and requires<br />
individual optimization. However, we can allow for some general constraints, like <strong>de</strong>fined cell pitch and<br />
<strong>de</strong>fined load capacitance drive at the (single en<strong>de</strong>d) output. The use of a differential configuration for the<br />
1 st stage is a also general requirement, which allows to connect the signal return of the inputs directly to
9.4. First Amplifier Stages 209<br />
Detektor<br />
pad<br />
Signal<br />
ground<br />
Detektor<br />
shield<br />
Preamp<br />
Power<br />
ground<br />
Comparator<br />
Anti−Aliasing<br />
and Zero<br />
g −C m<br />
Filter<br />
{<br />
t gr<br />
D/A<br />
x1<br />
High range<br />
x8<br />
Range<br />
Low range<br />
clk<br />
9bit<br />
ADC<br />
Range<br />
bit<br />
9<br />
Data<br />
out<br />
4<br />
Digital control<br />
of corner<br />
frequency<br />
clk<br />
Figure 9.13: Proposed<br />
Preamplifier-Shaper and<br />
ADC<br />
the chamber ground without the interference of supply currents of the electronics. Dedicated preamplifiers<br />
that meet these requirements will fit into the system. Detector related inversion of signal polarity<br />
will be accounted for in the following filter and buffer stage.<br />
The filter stage contains typically a first or<strong>de</strong>r high pass and a higher or<strong>de</strong>r low pass filter. As an option<br />
it is aligned with the sampling frequency of the ADC. Over-sampling at high frequencies is not feasible,<br />
thus we have to use a continuous time filter. Classical RC active filters are limited in performance at the<br />
envisaged high frequencies, and they suffer severely from the large RC product tolerances on the chip.<br />
Their trimming to variable cut off frequencies is very difficult to achieve. A more attractive candidate<br />
is the class of casca<strong>de</strong>d differential gm-C filters. It has less bandwidth limitations and it can be simply<br />
trimmed by the variable gm-stages, e.g. digitally by using a DAC-stage.<br />
Vin<br />
3rd−or<strong>de</strong>r gm−C low−pass filter:<br />
gm gm C1<br />
Rin L<br />
Passive representation:<br />
Rin/2<br />
Vin C1<br />
Rin/2<br />
gm<br />
gm<br />
L/2<br />
L/2<br />
CL gm<br />
gm<br />
C2<br />
C2<br />
Rout<br />
Rout<br />
gm<br />
Vout<br />
Vout<br />
Figure 9.14: Casca<strong>de</strong>d<br />
differential gm-C-filter and<br />
equivalent RLC-filter<br />
Fig. 9.14 illustrates the principle of a possible realization of a 3 rd -or<strong>de</strong>r lad<strong>de</strong>r filter in comparison with<br />
its passive LC-counterpart. Lad<strong>de</strong>r filters are relatively insensitive to component tolerances. However,<br />
a critical <strong>de</strong>sign issue of gm-C filters is their limited linearity of approx. 60 dB THD, corresponding<br />
to 10 effective bits. Fortunately, in a dual range approach this will be acceptable, since we can reduce<br />
the dynamic range of the filter stages to 9 bit. The required exten<strong>de</strong>d resolution at low signal levels<br />
is provi<strong>de</strong>d by the gain of the following linear (×8)-amplifier before the ADCs sampling gate. The<br />
sampling of both ranges is done simultaneously on individual sampling gates.<br />
The low/high- range bit, which signals an overflow of the (×8)-amplifier, can already be generated at the<br />
input of the filter using a comparator which is triggered by the ADC clock. As the analogue signal is<br />
<strong>de</strong>layed by the group <strong>de</strong>lay time of the filter (some 10 ns), the ADC receives the range bit right before the<br />
clock cycle of the first conversion. Scales mismatch, which is an issue of concern in a dual range system,
210 Common Front-End Electronics Aspects<br />
can be corrected during the measurements. As explained in the ADC-chapter 9.6, a special mo<strong>de</strong> of the<br />
ADC can provi<strong>de</strong> redundant conversion of low range events on both sampling gates, one after the other.<br />
This will allow the repeated correction of the scales by a digital data processor. Drift or aging can thus<br />
be accounted for.<br />
Individual preamplifier cells should adopt to the special requirements of the different <strong>de</strong>tectors (like TRD,<br />
RICH and ECAL). Design engineers and <strong>de</strong>tector specialist have to cooperate in providing the optimized<br />
cells. There is a common geometrical requirement of those cells, as they have to be interchangeable and<br />
must fit in the cell pitch. Area can be varied in one direction as nee<strong>de</strong>d. A differential input stage, where<br />
the signal ground of several channels can be combined in one pad, is highly recommen<strong>de</strong>d. This helps<br />
to avoid interference of the signal return path and the noisy supply current path. The rest of the front<br />
end electronics can be common to many variants of <strong>de</strong>tectors, since the required adjustments of polarity,<br />
sampling rate, filter cut-off frequency, and resolution will be built in.<br />
9.5 Analog Memory<br />
An analog memory between the preamplifier and the ADC offers the possibility to to turn off the ADC<br />
completely when no event has been <strong>de</strong>tected and thus save power. During such periods the signal of the<br />
preamplifier is sampled in a field of analog storage cells, a memory. Only when a comparator <strong>de</strong>tects<br />
a relevant signal level, the ADC is turned on and converts the samples of interest. The analog memory<br />
bridges the time gap until the ADC runs properly, at least one sample cycle. Furthermore, it allows to<br />
digitize samples taken before the event had been <strong>de</strong>tected.<br />
Data lifetime<br />
[number of sampling intervals]<br />
100000<br />
10000<br />
1000<br />
100<br />
10<br />
0 20 40 60 80 100 120<br />
Temperature [<strong>de</strong>g C]<br />
Figure 9.15: Architecture of a switched capacitor<br />
analog memory cell consisting of MIMcapacitors<br />
(top); Expected storage time in an<br />
analog memory cell versus temperature (bottom)<br />
Figure 9.16: Analog Memory cells using a<br />
switched-current technique<br />
Fig. 9.15 shows a Sample&Hold-circuit, known as “flip-around S&H”, where an amplifier is used to<br />
sample (write) signals in several analog memory cells. The same amplifier can later in the hold mo<strong>de</strong>
9.6. Multi-purpose ADC 211<br />
(Read) buffer the sampled signals to be converted by the ADC. With two amplifiers writing and reading<br />
in different cells could happen at the same time.<br />
Due to its simplicity the approach of Fig. 9.15 is i<strong>de</strong>ally suited for a smaller number of storage cells,<br />
below 20 cells. For larger arrays the area of the capacitors (UMC 0.18 µm: 1 fF/µm 2 ) gets relatively<br />
large, also the stray capacitances of the wiring, which cost power and can limit performance.<br />
For larger arrays switched current cells like in Fig. 9.16 can be a better solution. Here signal currents are<br />
stored as corresponding gate charges in transistors. This solution offers much smaller storage cells. On<br />
the other hand, achieving accuracies of 10 bit or more at the here required samplerates is more difficult<br />
in switched current technique. The main obstacle is charge injection from the switches, which cannot<br />
be suppressed so effectively like in switched capacitor circuits, leading to higher harmonic distortion.<br />
The differential approach of Fig. 9.16 is a first step to overcome this limitation, but still research is<br />
necessary [199].<br />
Fig. 9.15 plots the possible data lifetime in number of sample intervals over temperature. The leakage<br />
current of the switches <strong>de</strong>gra<strong>de</strong>s the stored signals. Here a <strong>de</strong>gradation of 0.1% was assumed. Faster<br />
S&H-circuits need larger switches with more leakage current, so the quotient of possible storage time<br />
and length of the sampling interval is in<strong>de</strong>pen<strong>de</strong>nt of the actual size of the switches. The study of<br />
Fig. 9.15 was carried out for a switched capacitor circuit, however, for switched current circuits very<br />
similar results are obtainable. The main result is that at the expected temperatures leakage currents do<br />
not limit the performance of the proposed analog memory cells.<br />
9.6 Multi-purpose ADC<br />
In this section several possible <strong>de</strong>signs of ADCs with resolutions of 10–12 bits and sampling rates of<br />
40 MS/s are presented.<br />
9.6.1 General requirements<br />
In or<strong>de</strong>r to achieve the full resolution the maximum jitter of the ADC reference clock is limited by the<br />
input frequency and digitization resolution. Therefore very low jitter clocks are required in or<strong>de</strong>r to<br />
achieve the high resolution at the given digitization rate. For instance, at 12 bit resolution and 40 MS/s, a<br />
corresponding 20 MHz input signal frequency, an RMS clock jitter of 2.5 ps leads to an RMS digitization<br />
error as large as the quantization error (≈0.3 LSB). Higher jitter can easily become the dominant source<br />
of error for such measurements.<br />
9.6.2 Variant 1: Interleaving (Multiplexing) of 4 ADCs<br />
The most simple solution to achieve samplerates of 40 MS/s would be the usage of 4 existing 10 MS/s<br />
TRAP-ADC (Section 9.2.1), sampling in an interleaved configuration. The cost for the simplicity of this<br />
approach is a reduced accuracy compared to a single TRAP-ADC, because the individual offsets and<br />
conversion gains of each ADC lower the overall precision when combining the digitized values from<br />
different converters by roughly 0.5–1 bit. So the maximum possible accuracy would be clearly lower<br />
than the target of 12 bits.
212 Common Front-End Electronics Aspects<br />
9.6.3 Variant 2: Pipeline-ADC with 10/12 bit<br />
Pipeline ADCs are simple and robust architectures consisting of similar building blocks like the cyclic<br />
TRAP-ADC. 12 bits of resolution and samplerates around 100 MS/s are state of the art. Fig. 9.17<br />
shows the first stages of a Pipeline converter in two clock cycles using a technique called “Amplifier<br />
sharing” [183]. It reduces the number of amplifiers and thus power and maximum throughput by a factor<br />
of two, therefore the maximum samplerate would be around 50 MS/s here.<br />
Figure 9.17: Pipeline ADC with amplifier<br />
sharing<br />
Figure 9.18: Pipeline ADC in 10 bit mo<strong>de</strong><br />
The power consumption of a 12 bit Pipeline ADC @ 40MS/s would be ≈40 mW. A Pipeline Implementation<br />
can be adopted to a lowered resolution of 10 bits by bypassing the first two stages, responsible for<br />
the 12th and 11th bit. Fig. 9.18 shows this i<strong>de</strong>a.<br />
Due to their high precision the first stages consume a reasonable part of the overall current, so turning<br />
them off would lead to ≈25 mW for 10 bits of resolution @ 40 MS/s. This value corresponds to the<br />
power efficiency of the low-power version of the TRAP-ADC in Section 9.2.1. Adapting the power<br />
consumption to a wi<strong>de</strong> range of lower sample frequencies is possible by changing the analog circuitry’s<br />
currents in a proportional way. Switched capacitor implementations naturally offer this possibility. The<br />
amplifiers insi<strong>de</strong> the ADC can be <strong>de</strong>signed for a wi<strong>de</strong> range of supply currents.<br />
• Pro: Flexible in terms of resolution and samplerate (at constant Power/Samplerate)<br />
• Contra: Pipeline latency of 10/12 clock cycles<br />
Note that the CBM experiment does not implement the canonical trigger architecture, typically requiring<br />
a maximum trigger latency due to the finite input event buffers, and therefore requiring short conversion<br />
latencies. For the CBM experiment the conversion latency is not an important factor.<br />
9.6.4 Variant 3: 9bit Pipeline-ADC with 2 different gain stages<br />
An other option would be exploiting the fact that high resolution of the input range is only required in<br />
a fraction of amplitu<strong>de</strong>s, where the baseline and small pulses are located. Using an ADC of lowered<br />
resolution, e.g. 9bit, and two preamplifier output stages with different gains allows to digitize fractions<br />
of the input range with different resolution.<br />
Fig. 9.19 illustrates this i<strong>de</strong>a. The ADC needs two S&H-inputs to sample always the outputs of both<br />
gain buffers. A comparator <strong>de</strong>ci<strong>de</strong>s, if the signal is located in the low amplitu<strong>de</strong> area where the output
9.7. SerDes, Clock recovery and Optical links 213<br />
from Shaper<br />
Comparator<br />
Anti−<br />
Alias<br />
x1<br />
low gain buffer<br />
high gain buffer<br />
x8<br />
S&H<br />
S&H<br />
low<br />
gain<br />
high<br />
gain<br />
9bit Pipeline<br />
high/low<br />
9<br />
Figure 9.19: 9 bit Pipeline with<br />
two buffers of different gains<br />
of the high-gain buffer is to be used to obtain high resolution or if a large signal was sampled, so the<br />
sampled value of the low-gain buffer has to be digitized. For a high-gain factor of 8 the resolution would<br />
be increased by 3 bit.<br />
To overcome inaccuracies in the gains and offsets of the two different gain buffers, a simple digital<br />
calibration will be nee<strong>de</strong>d. In calibration mo<strong>de</strong> the outputs of both buffers are sampled and then digitized<br />
one after the other. Performing this measurement at different points of the overlap range allows to obtain<br />
calibration values for the gains and offsets of the two buffers. These calibration cycles can be well<br />
executed in situ, using the typically implemented electronic test pulser functionality of the preamplifier<br />
stages. During the digital postprocessing of the data the calibration values are nee<strong>de</strong>d for the weighting<br />
to the corresponding data. The estimated power consumption for this possibility would be ≈25 mW.<br />
Table 9.2 shows an overview over power and resolution of the different proposed variants of ADCs.<br />
Variant Power @ 40MS/s Resolution<br />
Interleaving 48 mW
214 Common Front-End Electronics Aspects<br />
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GDWD<br />
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VHULDO<br />
GDWD<br />
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FORFN<br />
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Figure GHWHFWRU 9.20: Simplified block diagram 'HVHULDOL]HU of serializer RVFLOODWRU (left) and <strong>de</strong>serializer (right)<br />
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ORRS<br />
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RVFLOODWRU<br />
YROWDJH<br />
FRQWUROOHG<br />
RVFLOODWRU<br />
ELW V\QFKURQL]HG<br />
GDWD<br />
ELW V\QFKURQL]HG<br />
FORFN<br />
PXOWLSOLHG<br />
FORFN<br />
PXOWLSOLHG<br />
FORFN<br />
UHFRYHUHG<br />
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FORFN<br />
'HVHULDOL]HU<br />
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GDWD<br />
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VHULDO GDWD LQ<br />
Figure 9.21: Simplified<br />
block diagrams of Clock<br />
Multiplier Unit (top) and<br />
Clock Recovery Circuit<br />
(bottom)<br />
than the reference clock. 3// TheEDVHG clock &ORFNrecovery 5HFRYHU\ &LUFXLW circuit tracks frequency and phase of the serial data stream<br />
to generate the bit-synchronized clock. Using an a<strong>de</strong>quate phase frequency <strong>de</strong>tector type, recovered<br />
clock edges are aligned to the center of the data eye opening in lock condition.<br />
One has to optimize the loop filters jitter transfer function by tra<strong>de</strong>-offs between the different jitter<br />
sources. Fig. 9.22 presents plots of jitter transfer functions in PLL systems from input and VCO. The<br />
transfer function of the input has a low-pass filter property. Therefore the output jitter, caused by input<br />
jitter, can be reduced by minimizing the loop bandwidth. The jitter transfer function of the VCO has<br />
a high-pass filter nature, hence the suppressed band has to be exten<strong>de</strong>d to reduce the jitter contribution<br />
by the VCO. That means the loop bandwidth has to be maximized, but it is always limited by the loop<br />
stability. From above discussion, output jitter optimization is a compromise between the jitter from the<br />
VCO and the input of the PLL system, which is the reference clock in case of the CMU and serial the<br />
data stream in case of CDR. For instance a clock multiplier unit using a ring-oscillator based VCO needs<br />
a low jitter reference clock and its loop bandwidth should be wi<strong>de</strong>, in or<strong>de</strong>r to reduce the jitter of the ring<br />
oscillator. Wi<strong>de</strong> loop bandwidth means the multiplied clock can track the quality of that reference clock.<br />
On the opposite, if a VCO can generate the low-jitter clock, such as an LC oscillator, loop bandwidth has<br />
to be as low as possible in or<strong>de</strong>r to filter the jitter from the reference clock. In this case the quality of the<br />
reference clock can be relaxed.<br />
Figure 9.22: Plots of Jitter<br />
Transfer Functions in a PLL System<br />
[184]<br />
The availability of passive RF components such as inductors in CMOS technology improves the performance<br />
of a ser/<strong>de</strong>s system. Fig. 9.23 shows examples of on-chip inductors. There are many approaches<br />
utilizing LC-oscillators which can reach 2.5 Gbps or 10 Gbps [185, 186, 187]. Some attempts without<br />
on-chip inductor have <strong>de</strong>monstrated multi gigabit data systems, but a high quality local reference clock<br />
was always required [188, 189].
9.7. SerDes, Clock recovery and Optical links 215<br />
Figure 9.23: Different implementations<br />
of on-chip inductors<br />
[190]<br />
In the clock distribution system, one approach to generate high quality local clocks is using a QPLL. It<br />
uses a PLL-based clock synthesis with a quartz VCO (VCXO) [191]. Another approach is to distribute<br />
the clock through a serial data link. Howerver, without a low jitter reference clock, a high quality clock,<br />
for instance from a LC-VCO is necessary. Design of low-noise VCOs and high performance clock<br />
recovery circuits in CMOS technology are an ongoing challenge for research. The next R&D phase will<br />
<strong>de</strong>termine what clock recovery performance is achievable in a real system environment, what architecture<br />
is used best (VXCO, LC-VCO) and whether or not it is good enoug as timing reference for the time of<br />
flight <strong>de</strong>tector.<br />
9.7.2 SerDes and Optical driver<br />
Up to now a high speed optical transmission system consists of many different components, which are<br />
assembled in a multi-chip-module (MCM) or on a printed circuit board (PCB). At the moment two components<br />
must be optimized for their function and therefore cannot be inclu<strong>de</strong>d in the standard CMOS<br />
process. They perform the electrical/optical conversion, and are typically implemented as the light emitting<br />
<strong>de</strong>vice (VCSEL dio<strong>de</strong>) and the light receiver (PIN dio<strong>de</strong>).<br />
The goal is the integration of all other circuit parts of the optical communication system into the standard<br />
CMOS 0.18 µm technology. If the <strong>de</strong>signs are modularized it will be useful as IP cells in many different<br />
configurations or as complete high-speed serial communication <strong>de</strong>vice (refer to section 9.8.2).<br />
parallel<br />
interface<br />
input<br />
parallel<br />
interface<br />
output<br />
8B/10B<br />
enco<strong>de</strong>r<br />
control &<br />
<strong>de</strong>bug<br />
interface<br />
8B/10B<br />
<strong>de</strong>co<strong>de</strong>r<br />
serilaizer<br />
control &<br />
status<br />
registers<br />
<strong>de</strong>serilaizer<br />
preequalization<br />
clock & data<br />
recovery<br />
laser driver<br />
with PhDet<br />
laser driver<br />
CML<br />
Output<br />
CML<br />
input<br />
transimpedance<br />
Amplifier &<br />
limiting amplifier<br />
to VCSEL<br />
on-chip<br />
to VCSEL<br />
off-chip<br />
to optical<br />
transceiver<br />
from optical<br />
transceiver<br />
from PIN<br />
dio<strong>de</strong><br />
Figure 9.24: Simplified functional<br />
blocks of a high-speed serial<br />
communication system<br />
The functions of the optical communication system as it is implemented in the OASE chip is shown in<br />
Fig. 9.24. Sha<strong>de</strong>d blocks are assembled by layout synthesizer tools. The rest of the cells are full custom<br />
<strong>de</strong>sign cells.<br />
9.7.2.1 Modules<br />
A first high-speed serializer/<strong>de</strong>-serializer (ser/<strong>de</strong>s) chip (OASE) was <strong>de</strong>veloped in the UMC 0.18 µm<br />
process. In this chip, the ser/<strong>de</strong>s, high data rate transceiver (CML input/output) and optical front-end<br />
circuit (laser driver and trans-impedance amplifier) are combined in one large full custom macro cell.<br />
Design flexibility will be gained by seperating this macro cell into smaller modules. The serializer
216 Common Front-End Electronics Aspects<br />
and <strong>de</strong>-serializer are core modules with a low data rate interface. Fig. 9.25 <strong>de</strong>picts three options of<br />
combining the serializer with a current mo<strong>de</strong> logic (CML) output driver, a VCSEL driver with off-chip<br />
photo <strong>de</strong>tector, and a VCSEL driver with on-chip photo dio<strong>de</strong>. The <strong>de</strong>-serializer can be combined with<br />
a CML input buffer for interfacing to an external transimpedance amplifier and a photo dio<strong>de</strong>, as shown<br />
in figure 9.26.<br />
Serializer Options<br />
1. Serializer with<br />
CML Output<br />
2. Serializer with<br />
VCSEL Driver and<br />
Off-chip PhDet<br />
3. Serializer with<br />
VCSEL Driver and<br />
on-chip PhDet<br />
10<br />
n<br />
10<br />
n<br />
16<br />
10<br />
10<br />
n<br />
16<br />
10<br />
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Serializer<br />
Serializer<br />
ADC<br />
2<br />
CML<br />
Tx.<br />
2<br />
2 2<br />
LD<br />
Driver<br />
ADC<br />
2 2<br />
LD<br />
Driver<br />
+<br />
Onchip<br />
PhDet<br />
Figure 9.25: Examples of serializer configurations<br />
Deserializer Options<br />
1. Deserializer with<br />
CML Input<br />
2. Deserializer with<br />
Pre-Amplifier and<br />
Limiting Amplifier<br />
10<br />
n<br />
10<br />
n<br />
10<br />
Deserializer<br />
Deserializer<br />
ADC<br />
2<br />
CML<br />
Rx.<br />
2<br />
2 2<br />
Pre-Amp<br />
+<br />
Limiting<br />
Amp.<br />
Figure 9.26: Examples of <strong>de</strong>serializer configurations<br />
Reasonable integration of the high data rate cells cannot be done by automatic placing/routing tools.<br />
Connections between them are critical with respect to performance. Therefore an interactive method is<br />
required, i.e. the high data rate IP cells have to be placed manually in or<strong>de</strong>r to get short connections. The<br />
low data rate interface ports of the cells can still be connected by layout synthesizer tools. Examples are<br />
given in Fig. 9.27 and Fig. 9.28.<br />
Serial Out Serial Out<br />
Vdd/Gnd<br />
Layout of Serializer<br />
Layout of Serializer<br />
Ctrl. Signal<br />
Vdd/Gnd<br />
Layout of<br />
CML Tx.<br />
Serial Out VCSEL<br />
Drive Out<br />
Vdd/Gnd<br />
Vdd/Gnd<br />
Layout of<br />
VCSEL Driver<br />
Ctrl. Signal<br />
Figure 9.27: Examples of “construction by<br />
placing”: layout of serializer with 2 different<br />
output options, implementing a CML and a VC-<br />
SEL driver<br />
Layout of Serializer<br />
Ctrl. Signal<br />
Serial Out Serial Out<br />
Vdd/Gnd<br />
Layout of Deserializer<br />
Vdd/Gnd<br />
Serial in<br />
CML on-chip Driver<br />
Vdd/Gnd<br />
Layout of<br />
CML Tx.<br />
Layout of<br />
CML Rx.<br />
Vdd/Gnd<br />
Serial In<br />
CML Data Selector<br />
Filled Cell<br />
For loop-back options<br />
Figure 9.28: Examples of “construction by<br />
placing”: layout of a ser/<strong>de</strong>s with a CML Rx/Tx<br />
and loop-back functionality<br />
Every IP cell requires specified positions of connection ports, for instance the serializer data output port<br />
directly connects to serial data input port of the CML output driver. Optional IP cells such as VCSEL<br />
output driver have the serial data input port at the same position. I/O cells, like CML output driver, have<br />
to bypass the power and ground connections to the inner cells. An example of a ser/<strong>de</strong>s with optional<br />
loop-back functionality is shown in Fig. 9.28. Filler cells are required here to connect the internal loop<br />
back signals. There are also filler cells with on-chip CML drivers required for the additional loads of<br />
on-chip connections. CML data selectors will be used in the filler cell of the <strong>de</strong>serializer.
9.7. SerDes, Clock recovery and Optical links 217<br />
9.7.2.2 SerDes Circuit and System Design Consi<strong>de</strong>ration<br />
An important factor in SerDes <strong>de</strong>sign is the quality of the synthesized high frequency clock. The choice<br />
of the MUX structure in the serializer is <strong>de</strong>pending on the available quality of the high frequency clock.<br />
If on-chip inductors are available, LC-VCO based oscillators can be used and the CMOS serializers can<br />
run at full data rate as shown in Fig. 9.29. A clock multiplier unit (CMU) based on a multi-phase ring<br />
oscillator needs another approach, like the one-forth data-rate multi-phase MUX, <strong>de</strong>picted in Fig. 9.30.<br />
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FORFN<br />
/DWFK<br />
/DWFK<br />
&RUH<br />
08;<br />
VHO D<br />
08; 2XW<br />
Figure 9.29: Full-rate clock<br />
multiplexer with tree structure<br />
Another possible solution for a ring-oscillator-based VCO is a dual-loop system as shown in Fig. 9.31 (top).<br />
The first loop is for filtering jitter of the reference clock. Loop bandwidth affecting the jitter transfer function<br />
has to be low. The improved quality clock is utilized as reference clock for the second loop, that<br />
generates the multiplied clock. Bandwidth of the second loop has to be as high as possible to track the<br />
improved reference clock. In conclusion, the dual-loop structure utilizes the first loop as jitter filter and<br />
the second loop as frequency multiplier. Fig. 9.31 (bottom) <strong>de</strong>picts a multi-phase PLL combined with<br />
multi-phase MUX.<br />
G<br />
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FON<br />
FON<br />
FON<br />
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FON<br />
FON<br />
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FON<br />
FON<br />
FON<br />
&ON<br />
&ON<br />
&ON<br />
&ON<br />
6HULDO 'DWD<br />
Figure 9.30: One-forth-rate clock multiplexer<br />
[188]<br />
9.7.2.3 Clock Multiplier Unit (CMU)<br />
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5HI FORFN<br />
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E 0XOWL SKDVH 3// FRPELQHG ZLWK PXOWL SKDVH 08;<br />
6HULDO 'DWD 2XW<br />
+LJK IUHT<br />
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Figure 9.31: Dual loop PLL (top) and multiphase<br />
serializer system (bottom)<br />
A PLL-based clock multiplier unit was implemented. It has a fully differential structure to reduce the<br />
sensitivity to power and ground noise. Measurement results are <strong>de</strong>picted in Fig. 9.32. Supply voltage<br />
in measurements is 1.8 V. The CMU can generate a 5-times clock output and has a jitter of 7 ps (RMS)
218 Common Front-End Electronics Aspects<br />
at 1.25 GHz. It is used for multiplexing parallel data to 2.5 Gbps serial. The CMU module consumes<br />
16 mA and its size is 0.47 × 0.43 mm 2 .<br />
Figure 9.32: CMU measurement result: output clock, jitter histogram at 1.25 GHz (left); output clock in time<br />
domain (right)<br />
9.7.2.4 Multiplexer (MUX)<br />
The multiplexer is based on a half-rate CML tree structure at the front-end and CMOS MUX at slow data<br />
rate. It has been implemented together with the CMU as a complete serializer. Fig. 9.33 (left) shows a<br />
die photograph of the complete serializer including VCSEL driver.<br />
Figure 9.33: Die photograph of the complete serializer including VCSEL driver (left) and the layout of the entire<br />
high-speed ser/<strong>de</strong>s chip OASE3 (right)<br />
The serializer was tested successfully up to 1.5 Gbps, as shown in Fig. 9.34. Area is 0.35 × 0.45 mm 2<br />
and current consumption 20 mA. Supply voltage in measurements is 1.8 V.<br />
In or<strong>de</strong>r to reach the 2.5 Gbps specification, the circuitry was revised and improved in the latest version of<br />
the chip (OASE3). The loop bandwidth of the CMU was reduced to filter jitter from the reference clock.<br />
The voltage swing of the CML components was increased to improve matching properties. All clock<br />
buffers were re<strong>de</strong>signed to guarantee rise/fall times. The power consumption is optimized by reducing<br />
CML front-end parts. The IC is still in manufacturing by UMC, expecting first silicon early 2005. The<br />
layout of the entire chip is shown in Fig. 9.33 (right).<br />
9.7.2.5 VCSEL Driver<br />
Front-end circuits for driving VCSEL have been <strong>de</strong>signed and implemented. Design features are a current<br />
balance concept to reduce power and ground noise, pre-emphasis to compensate high frequency losses.<br />
The VCSEL driver has been measured with an equivalent VCSEL load as shown in Fig. 9.35. The<br />
driver is suited for 2.5 Gbps. The output eye-diagram shows 28 ps (p-p) jitter without pre-emphasis<br />
(Fig. 9.35 (left)). The jitter reduces to 20 ps (p-p) with pre-emphasis (Fig. 9.35 (right)). The VCSEL
9.7. SerDes, Clock recovery and Optical links 219<br />
Figure 9.34: Serializer output at 1.5 Gbps, constant pattern (left); eye-diagram of serializer output, random<br />
pattern (right)<br />
Figure 9.35: VCSEL driver output: Eye-diagram at 2.5 Gbps without pre-emphasis (left); Eye-diagram at<br />
2.5 Gbps with pre-emphasis (right)<br />
driver consumes 2.8 to 4.1 mA of the 3.3 V supply voltage and 6.6 to 7.6 mA of the 1.8 V supply voltage.<br />
The area of the module is 0.29 × 0.23 mm 2 .<br />
9.7.2.6 Transimpedance Amplifier (TIA) and Limiting Amplifier (LA)<br />
The <strong>de</strong>sign contains as first stage single-en<strong>de</strong>d transimpedance amplifier, then a single-en<strong>de</strong>d to differential<br />
converter and finally a CML-based limiting amplifier. All modules are implemented and measured<br />
with an equivalent photodio<strong>de</strong> load. TIA and LA consume 7 mA and can operate at 1 Gbps. The die area<br />
is 0.10 × 0.15 mm 2 . The output signal is connected through CML buffers and long on-chip connections<br />
accross the testchip. CML buffers were re<strong>de</strong>signed and on-chip connections are optimized in the latest<br />
chip generation.<br />
9.7.2.7 DLL-based Clock Data Recovery (CDR)<br />
The DLL-based CDR has two loops in the system. The first loop is a PLL loop that generates four-phase<br />
half-rate clocks from the local reference clock. In the second loop, implemented as DLL, the phase of<br />
the serial input data is adjusted for optimal position of the half-rate clock. Fig. 9.36 shows measurement<br />
results of the DLL-based CDR. The supply current is 42 mA, the die area is 0.65 × 0.66 mm 2 . Supply<br />
voltage in measurements is 1.8 V.<br />
The DLL-based CDR can be applied to systems that have a clock distribution. A more universal alternative,<br />
the frequency-phase-locked CDR was implemented in the latest OASE chip.
220 Common Front-End Electronics Aspects<br />
9.7.3 Low cost electrical / optical conversion<br />
Figure 9.36: Clock at 625 MHz for<br />
1.25 Gbps (top left); serial data input<br />
at 1.25 Gbps, DLL-loop disable<br />
(top right); serial data input, DLLloop<br />
enable (bottom left); final phase<br />
position of Serial data input (bottom<br />
right)<br />
In the future a key technology for high speed interconnects will be the optical transmission. In or<strong>de</strong>r to<br />
keep cost low an optimized system will be <strong>de</strong>signed and tested which can cover distances from centimeters<br />
up to 100 m.<br />
The OASE project of the ASIC-CC in cooperation with the Optoelectronics Group of the University<br />
of Mannheim provi<strong>de</strong>s the basics for such a low cost interconnect technique. The optical interconnect<br />
between the VCSEL and the fiber is realized by a new self-aligning fiber attachment structure which<br />
contains also a 45 <strong>de</strong>gree mirror prism to fed the laser light into the fiber.<br />
fibre/mirror<br />
glas substrate<br />
GaAs-VCSEL<br />
chip substrate<br />
Figure 9.37: Principle of optical interconnects using 45 ◦ mirrors<br />
9.7.3.1 Development of 45 ◦ microprism in SU-8 photoresist for optical interconnects<br />
Exchanging data off-chip at high speed is becoming a bottleneck in high performance electronic processing<br />
systems. As data rates increase, electrical interconnects are limited by power, distortion, cross-talk<br />
and pin-out capacity. On PCB’s, the dielectric losses and the losses due to skin effect significantly rise<br />
above 1 GHz. Optical interconnects do not show these limitation and therefore electrical interconnects<br />
will be likely replaced in the near future. VCSELs (vertical surface emitting laser) reach more than<br />
10 Gbits/s and with this new <strong>de</strong>veloped system, directly coupling the emitted light into a fibre, interconnects<br />
may become possible at very low cost. The i<strong>de</strong>a is to combine a VCSEL array with an microprism<br />
array in one alignment step for a whole wafer (Fig. 9.37).<br />
SU-8 microprisms accomplish two tasks in one. They act as a mirror, reflecting the light by 90 ◦ and<br />
reduce the complexity to align a fibre to the VCSEL. For this reason, a process was <strong>de</strong>veloped to create<br />
alignment and <strong>de</strong>flection SU-8 structures with UV-illumination. The challenges for producing non<br />
vertical SU-8 structures are:<br />
• Limitation of exposure angle due to refraction;
9.8. FEE Communication 221<br />
• Minimize reflections from in<strong>de</strong>x boundaries;<br />
• Optimization of process parameters such as exposure time;<br />
• Increasing the quality of structures.<br />
Figure 9.38: Examples of small outline low-cost optical<br />
connectors, suitable for the required optical connectivity of<br />
the OASE architecture. It allows in particular to connect to<br />
the pig-tail type fiber connections of the OASE module.<br />
250µm<br />
Figure 9.39: Microprismarray in SU-8, top view (left), 3 Laser light coupled into a fibre and reflected at the<br />
microprism (right)<br />
By in<strong>de</strong>x matching with water between every critical layer, and “planar-fitting” the mask it was possible<br />
to produce microprisms in SU-8 (Fig. 9.39). Mass production with injection casting in the future can<br />
significantly reduce the cost for each structure.<br />
9.8 FEE Communication<br />
The existence of some 10k front-end chips or modules on the <strong>de</strong>tectors pose the requirement for the<br />
distribution of synchronized clocks, global time or reset as well as the readout of these modules at the<br />
<strong>de</strong>fined rate. Finally there is a corresponding requirement for initialization and configuration of these<br />
distributed modules. All those requirements share the necessity of peer to peer communication as well<br />
as the precision recovery of clock signals. This section is <strong>de</strong>dicated to the appropriate issues.<br />
9.8.1 Clock/Time Distribution<br />
There are several thousand front-end <strong>de</strong>vices in the experiment, which all require to have the same time<br />
at the granularity of about 1 ns and have to have a synchronized clock with a maximum jitter of 100 ps,<br />
if the time of flight system is exclu<strong>de</strong>d in this context. If the ToF system is inclu<strong>de</strong>d the maximum<br />
clock jitter is limited to 10 ps. The LHC experiments use a passive optical fan-out of a reference clock<br />
master [192].<br />
It should be noted that there are going to be a large number of high-speed multi gigabit links, used<br />
for the readout of the front-end digitizers. Each multi gigabit receiver has to implement a PLL for the
222 Common Front-End Electronics Aspects<br />
Data<br />
clk<br />
Ctl<br />
clr<br />
n<br />
Serializer<br />
t 0gen<br />
2<br />
∆t = const ±δ ≤0.8ns<br />
2<br />
Deserializer<br />
t 0<strong>de</strong>c<br />
n<br />
Data<br />
clk<br />
Ctl<br />
clr<br />
Figure 9.40: Building blocks<br />
for clock and time synchronization<br />
and distribution<br />
clock recovery with a maximum jitter, being much better than the bit width, and which is synchronized<br />
to the appropriate PLL of the corresponding transmitter (refer also to section 9.7.1). For instance a<br />
canonical 2.5 GBit link has 400 ps per bit, basically requiring a receiver clock stability, which matches<br />
the requirements, stated above, excluding ToF. Note further that the clock stability requirements of a<br />
12-Bit, 40 MSPS ADC (refer to section 9.6) is compatiple with the requirements of the ToF system.<br />
Most electrical/optical converters, as well as serializer/<strong>de</strong>serializer chips are built in full duplex. Therefore<br />
the implementation of an appropriate uplink does not result in significant extra cost. This link could<br />
be used also for the distribution of configuration and maintenance data (DCS). Using such multi gigabit<br />
uplink the front-end receiver PLL is synchronized with the backend TX clock, while providing an<br />
acceptable clock jitter. This observation drives a new concept, where the clock distribution and synchronization<br />
between the front-end and the back end is performed by just using the available multi gigabit<br />
transceivers. The uplink clock fan-out can be done both electrically or also using some passive optical<br />
splitters. In case of an electrical fan-out some redundancy has to be implemented in or<strong>de</strong>r to avoid single<br />
points of failure. One area of required research is the number of PLL hierarchies, which can be achieved<br />
with the given clock jitter requirements, which <strong>de</strong>pends on the quality of the receiver PLL. Appropriate<br />
test chips are planned to be <strong>de</strong>signed and qualified in this context (refer also to section 9.7.1). Note that<br />
an electrical fan-out of 4, which is easily achieved, and a hierarchy of 5 layers results in a fan-out of<br />
1:1000. The <strong>GSI</strong> accelerator is currently <strong>de</strong>veloping a so-called bunchphase timing system [193] which<br />
will <strong>de</strong>liver a highly stable clock anywhere on the campus with a maximum jitter and long term drift of<br />
100 ps. This infrastructure forms an i<strong>de</strong>al distributed root of the discussed trigger/clock fan-out.<br />
Another requirement is the distribution of a global time, which reduces to the counting of the synchronized<br />
clocks and the distribution of a synchronized clear signal to all counters. Such clear signal has<br />
to be distributed with a maximum jitter, less than the time clock period (1 ns). This can be also easily<br />
implemented in the appropriate serializer/<strong>de</strong>serializer as special purpose packet, which is forwar<strong>de</strong>d at<br />
high priority without any queuing <strong>de</strong>lays.<br />
Fig. 9.40 sketches an appropriate configuration. The serializer/<strong>de</strong>serializer has a parallel data input with<br />
appropriate clock and enable or control inputs. In addition a clear input/output signal is provi<strong>de</strong>d, which<br />
triggers the transmission of an appropriate control message with minimal distribution jitter. Note the<br />
transmission latency is entirely irrelevant here since this is a calibration parameter.<br />
9.8.2 Generic Optical Advanced Serializer/Deserializer (OASE)<br />
In the context of high speed data transmission, clock recovery and coherent time distribution a few additional<br />
features are usefull to add to the functionality of the OASE (optical advanced serializer/<strong>de</strong>serializer).<br />
It is planned to <strong>de</strong>velop this <strong>de</strong>vice as generic chip and as appropriate <strong>de</strong>signware building blocks, allowing<br />
their integration on specific front-end chips, implementing clock/time synchronization and data<br />
readout. The overall OASE building blocks are sketched in Fig. 9.41 and discussed below. In general this<br />
<strong>de</strong>vice implements all required functionality to form a multi gigabit serializer/<strong>de</strong>serializer like a copper<br />
substitute on one hand but also allowing to use fractional bandwidths for house keeping functionality,<br />
such as DCS. In addition it implements a rich set of functionality, typically required in the context of<br />
front-end DCS, therefore minimizing the amount of glue logic at the front-end level.
9.8. FEE Communication 223<br />
IO<br />
JTAG<br />
I2CM<br />
I2CS<br />
Vout<br />
Ain_A<br />
Ain_B<br />
Temp.<br />
Sens.<br />
SPI,<br />
PIO<br />
250 <strong>MB</strong>ps<br />
Ser_in_S<br />
REF_clk_in<br />
clear_in<br />
2.5 GBps<br />
Ser_in_A<br />
Ser_in_B<br />
OPTICAL<br />
CML_A<br />
CML_B<br />
CML_C<br />
CML_D<br />
CML_E<br />
PGA<br />
MUX<br />
Slow<br />
ADC<br />
DAC<br />
JTAG<br />
master<br />
Activity check<br />
auto select<br />
Deserializer<br />
CDR<br />
Serializer<br />
Separate drivers<br />
with progr.<br />
enable<br />
DMEM<br />
+ HM<br />
I2C<br />
master<br />
FIFO buf rec<br />
clear<br />
REF clk<br />
CPU core<br />
out<br />
A<br />
B<br />
A/B<br />
M2<br />
A<br />
B<br />
A/B<br />
M5<br />
out<br />
out<br />
IMEM<br />
+ HM<br />
M1<br />
requests to the arbiter<br />
ROM<br />
State machine<br />
send -<br />
receive<br />
A/B<br />
A<br />
B<br />
BYPASS\<br />
BYPASS\<br />
M3<br />
A<br />
B<br />
A/B<br />
out<br />
M4<br />
out<br />
I2C<br />
slave<br />
A/B<br />
A<br />
B<br />
FIFO<br />
send<br />
IO Bus<br />
ARBITER<br />
FIFO buf send<br />
clear<br />
REF clk<br />
SDR<br />
16 bit<br />
125 MHz<br />
Masters on the internal bus,<br />
connected to the Arbiter<br />
(like in trap chip)<br />
The 8-th link is redundant<br />
uplink, to be connected<br />
to Ser_in_S, REF_clk_in,<br />
clear_in of the neighbour<br />
chip<br />
Clock and clear<br />
fanout<br />
SDR<br />
16 bit<br />
125 MHz<br />
Slaves on the internal bus,<br />
all outputs ORed together<br />
(like in trap chip)<br />
PDLY<br />
PDLY<br />
DDR<br />
8 bit<br />
clear[8..0]<br />
REF_clk[8..0]<br />
OUT[8..0]<br />
LVDS<br />
DDR<br />
PDLY 8 bit<br />
IN[7..0]<br />
Figure 9.41: Architecture block diagram of a generic multi purpose optical advanced serializer, <strong>de</strong>serializer<br />
(OASE)<br />
9.8.2.1 Fan-Out, Fault Tolerance<br />
The output of the serializer implements an appropriate CML driver for the optical conversion. It is<br />
planned to implement several (for instance four) in<strong>de</strong>pen<strong>de</strong>nt CML drivers, all sharing the same input,<br />
therefore implementing a passive, electrical fan-out. Each CML output can be enabled individually,<br />
therefore not wasting power for outputs, which are not required.<br />
The OASE chip is to implement two <strong>de</strong>serializer inputs, allowing to receive clock and serial data via<br />
redundant paths. A simple arbiter checks after RESET which channel to use as active input channel<br />
and reference clock source. Therefore any error in the signal transmission will avoid the loss of the rest<br />
of the fanned-out tree, avoiding single points of failure. This redundancy can be implemented, at all<br />
hierarchy levels, for instance, implementing some kind of daisy chain. Each receiver is to implement an<br />
appropriate programmable <strong>de</strong>lay unit, allowing to adjust the individual phase of the received clock and<br />
data appropriately.<br />
In case of the OASE operating in fan-out mo<strong>de</strong> the TX clock is <strong>de</strong>rived from the RX clock. It will be<br />
enabled only after successful synchronization of the RX PLL. In or<strong>de</strong>r to allow injection of the synchronous<br />
reference clock and time pulses the OASE chips may also be used like physical interface chips<br />
in the back-end, where the receiver logic is most likely implemented in FPGAs.<br />
9.8.2.2 DCS Link, Bandwidth Segmentation<br />
The original motivation for the high-speed transmitter is the downstream data readout and the motivation<br />
for the uplink is the clock and time distribution. However given the availability of these high-speed<br />
links it is also possible to absorb the entire DCS network functionality here. But it should be noted that<br />
the readout and DCS paths have to be absolutely in<strong>de</strong>pen<strong>de</strong>nt, in or<strong>de</strong>r to guarantee that no data flow<br />
scenario may affect any DCS message transfer. The logical in<strong>de</strong>pen<strong>de</strong>nce of data readout and the DCS<br />
CTRL<br />
CTRL
224 Common Front-End Electronics Aspects<br />
messaging is an essential requirement. The fact that the same physical media is consi<strong>de</strong>red for the use of<br />
both data paths is no contradiction, provi<strong>de</strong>d that the appropriate guarantee of service on the network is<br />
given and the two functionalities readout and DCS are implemented entirely in<strong>de</strong>pen<strong>de</strong>nt.<br />
The requirements stated above are easily provi<strong>de</strong>d, for instance by reserving a certain fraction of the<br />
bandwidth of the serial link for DCS, using some fixed time multiplexing, thereby also guaranteeing a<br />
<strong>de</strong>fined latency. For instance 1% of the bandwidth of a 2.5 GBit link corresponds to 25 <strong>MB</strong>its of an<br />
individual DCS path, far exceeding all known field buses and certainly being more than a<strong>de</strong>quate.<br />
The uplinks are fanned out in a passive fashion, thereby logically implementing a broadcast architecture.<br />
However, a fan-out of 1:100 will provi<strong>de</strong> the same individual bandwidth like above. The receivers have<br />
to implement appropriate logic to intercept only packets, <strong>de</strong>stined to the appropriate no<strong>de</strong>. It is also<br />
easily possible to implement reliable broadcasts here. A similar broadcast scheme was used in case of<br />
the LHC TTC system [192].<br />
Another important aspect to be consi<strong>de</strong>red here is the segmentation of the available bandwidth onto several<br />
front-end chips. This feature is useful because the required readout speed of one front-end chip will<br />
be much lower than 2.5 GBits and also there may be several front-end chips on one readout board. In<br />
that case it is favorable to run the serial output of the front-end chips at lower bit rates, running at appropriately<br />
reduced power, and merging them by one OASE per readout board, which is also responsible<br />
for the generation of the clock and timing signals. The same functionality may be used to merge the<br />
fractional DCS downstream links in the back-end systems.<br />
The inputs and outputs of the OASE chip operate at 120 MHz DDR, using LVDS as physical transport.<br />
These transfer rates have proven to work well over distances of up to a few meters, including connectors,<br />
even in less than perfect environments, where the impedance and damping can only be controlled within<br />
limits, such as low-cost PCBs. The parallel inputs and outputs can be interpreted as in<strong>de</strong>pen<strong>de</strong>nt serial<br />
links, running at 240 <strong>MB</strong>its/sec, with respect to the synchronous reference clock, therefore allowing<br />
each front-end chip to use fractional bandwidth in multiples of 10% of the OASE link bandwidth by<br />
implementing an appropriate number of LVDS cells. This architecture generates a power requirement of<br />
about 15 mW per 240 <strong>MB</strong>it/s link.<br />
The OASE chip can also be configured to interpret its LVDS inputs and outputs as a DDR word stream,<br />
allowing its application as generic, full duplex electrical/optical network physical converter.<br />
9.8.2.3 DCS functionality<br />
Given the availability of a full duplex DCS link into the OASE chip it is a natural consequence to implement<br />
also the functionality, typically required here. Again the silicon real estate will not become a<br />
<strong>de</strong>termining cost factor. A variety of functions are integrated into the DCS functional subblock of the<br />
OASE chip. It has to be stressed again here that this block is to be <strong>de</strong>signed entirely in<strong>de</strong>pen<strong>de</strong>nt of<br />
the rest of the chip, operating on the <strong>de</strong>fined fractional, guaranteed bandwidth of the high-speed links.<br />
In or<strong>de</strong>r to keep this functionality as flexible as possible it is to implement a generic microprocessor<br />
with built-in instruction and data memory. The instruction memory can boot from either a local serial<br />
FLASH or via the optical link. The microprocessor is to perform all required in<strong>de</strong>pen<strong>de</strong>nt house keeping<br />
functionality.<br />
The DCS functional block can also inclu<strong>de</strong> a programmable instrumentation amplifier/attenuator with a<br />
10-Bit sampling ADC, temperature sensor, reference voltage generator core and I/O voltage sensors and<br />
the like. Such an analog building block was also integrated into the ALICE TRD TRAP chip (refer also<br />
to sections 9.2.3, 9.2.4).<br />
It also implements the necessary interfaces to the front-end, such as JTAG, I2C, SCSN, SPI and the like.
9.9. CNet – Concentrator Network 225<br />
Since it is unlikely that all of them are used simultaneously some pin sharing may be implemented here.<br />
In addition some parallel input/output signals will be useful. All the discussed interfaces can be ma<strong>de</strong><br />
available to the built-in microprocessor or directly to the DCS network for direct remote access.<br />
This functionality allows to fully and autonomously initialize and control all other chips on the readout<br />
board by the OASE. It can even do so without appropriate up-link by providing a quartz oscillator, which<br />
may be used in case of no operational uplink. The configuration data can be stored in the external serial<br />
FLASH, which can be reprogrammed in situ via JTAG and control of the DCS network.<br />
This DCS functionality eliminates most of the typically required hardware on the front-end modules,<br />
which is related to house keeping and safety monitoring. A group of such front-end modules is expected<br />
to be then monitored by an embed<strong>de</strong>d DCS front-end computer, such as [194].<br />
9.8.2.4 FPGA reconfiguration<br />
SRAM based FPGAs have the problem of possible radiation induced loss of configuration during the normal<br />
experiment operation. This problem can be mitigated by implementing in-situ reconfiguration and<br />
verification of the FPGAs configuration. Such functionality is currently being implemented in ALICE<br />
and was successfully <strong>de</strong>monstrated in various test beam experiments. It is implemented best, using some<br />
configuration master, which itself is radiation tolerant, such as the OASE chip. Since it is an ASIC it is<br />
possible to implement all necessary functionality to <strong>de</strong>tect and correct for single event upsets.<br />
The built-in microprocessor is available to operate the required reconfiguration and verification functionality,<br />
using a <strong>de</strong>fined interface, such as the XILINX ICAP. The configuration can be taken from the<br />
external FLASH or the optical link, should specific parts of the <strong>de</strong>sign be monitored. It can also be used<br />
for health and sanity monitoring of the FPGA operating in situ. However, typical FPGA configuration<br />
data sets can reach the size of megabytes, being segmented into individual blocks. In or<strong>de</strong>r to avoid on<br />
one hand long verification times by reading the configuration from a serial FLASH and on the other hand<br />
the need for a high speed parallel FLASH interface, requiring a large number of I/O signals, a checksum<br />
of the individual FPGA configuration blocks can be computed and stored in the small internal OASE<br />
data memory. Then only in case of a configuration error the appropriate FPGA configuration block is<br />
reread from the external serial Flash and programmed into the FPGA automatically.<br />
9.9 CNet – Concentrator Network<br />
9.9.1 General Requirements<br />
There is no global trigger for the read-out of data, which means that the <strong>de</strong>tectors are free running data<br />
acquisition systems. Each channel has local trigger units which i<strong>de</strong>ntify individual hits locally. The<br />
local threshold values should be as near as possible to the noise level to capture any significant pulse.<br />
In addition it is typically required to readout pre- and post history and also geographically neighboring<br />
channels, possibly being below their individual hit <strong>de</strong>tection threshold, in or<strong>de</strong>r to capture the entire hit<br />
cluster (refer also to section 9.3). Therefore it is necessary for each channel to be able to communicate<br />
to its geographically neighboring channels, that they are to reaout a certain group of time bins in<strong>de</strong>pen<strong>de</strong>nt<br />
of their individual hit <strong>de</strong>tection status. Since most geographically neighboring channels are also<br />
located on the same readout modules this can be done by direct signalling between the appropriate frontend<br />
chips. However, there are always boundaries and areas where such next neighbor signalling is not<br />
possible. For those cases the bidirectional CNET functionality can be used. However, this also puts a<br />
relatively high <strong>de</strong>mand onto the maximum tolerable message passing latency on CNet, since the readout<br />
message has to be received within the number of available time samples stored in the short input analog
226 Common Front-End Electronics Aspects<br />
memories (refer to section 9.5).<br />
Another general requirement is the implementation of the coalescing of the data stream and the associated<br />
hit clusters to event clusters, using the available time information. This feature allows to increase the data<br />
payload of the readout system downstream.<br />
The bidirectional CNet system supports also the distribution of clock and time information by using the<br />
otherwise idle uplinks. DCS messaging is implemented using a reserved fraction of the available full<br />
duplex bandwidth.<br />
9.9.2 CNet System Level<br />
The main function of the CNet is the data read-out from the FEE units, coalescing of hits, belonging to<br />
the same event or time interval and finally the transport of the data to the BNet interface. Thus the nature<br />
of the CNet itself is unidirectional. However, given the arguments outlined above, additionally the global<br />
clock and time information (TNet) and the DCS function are mapped to the CNet. Advantages from this<br />
are reduced costs and higher flexibility. Therefore the CNet links are bidirectional<br />
Given the availability of a very low-cost electrical/optical conversion (refer to section 9.8.2), only onboard<br />
and very local connectivity is expected to be implemented in copper. The remaining connectivity<br />
shall use multi gigabit glas connections. Additional advantages of optical interconnects are: scalable data<br />
rates, medium distances can be bridged up to 100 m (compared to very short electrical distances, less<br />
than 1 m). More benefits of optical interconnects are the electrical isolation of components, no electrical<br />
interference and low material budget.<br />
The CNet system level architecture is sketched in figure 9.42. The front-end (left) is typically implemented<br />
on some readout boards, implementing several front-end digitization and hit <strong>de</strong>tection chips<br />
(FEE). In a typical case the required down stream bandwidth is signifficant below a GBit, if <strong>de</strong>randomized<br />
appropriately by implementing appropriate small buffers. A group of front-end chips is connected<br />
to an OASE serializer, which also generates all required low jitter reference clocks and fans out the appropriate<br />
DCS messages. 120 MHz DDR LVDS links are foreseen here. The output of the OASE can<br />
be implemented redundant by using two of the CML output drivers. Groups of individual OASE chips<br />
in the front-end are also connected in form of a daisy chain, in or<strong>de</strong>r to have a redundant input for the<br />
reference clock and maintenance information.<br />
Note that the number of FEE chips per front-end module is not only <strong>de</strong>termined by bandwidth requirements.<br />
The availability of very low-cost optical converter modules, such as OASE, may drive the size of<br />
these front-end modules to become rather fine grain with a small number of front-end chips per OASE<br />
module, while un<strong>de</strong>rutilizing the available link bandwidth. Some advantages of this fine grain approach<br />
are economy of scale due to higher volume of simpler modules, such as reduced cost per module and increased<br />
yield. The CNet functionality of the OASE concentrators avoids the direct interconnects between<br />
FEE chips by implementing the required readout trigger switching.<br />
A large number of CNet readout down stream links will be required by the experiment. The physical<br />
layer and protocol will be <strong>de</strong>signed such, that they can also interface to generic ser/<strong>de</strong>s chips, in particular<br />
including FGPAs. To date there are appropriate FPGAs available implementing up to 24 multi gigabit full<br />
duplex links. All switching and coalescing or data compression functionality can be implemented very<br />
flexible here. Given a fan-in of 24, 50 CNet reciever modules are required, implementing one merger<br />
FPGA each, in or<strong>de</strong>r to serve 1000 CNet optical links. This number of units is easily implemented in two<br />
6U crates. A similar architecture was chosen for the ALICE GTU, implementing 1080 2.5 GBit links.<br />
The merger FPGA also implements connectivity to its next neighbors in or<strong>de</strong>r to allow the next neighbor<br />
distribution of hit information to trigger the readout of other front-end chips.
9.9. CNet – Concentrator Network 227<br />
Analog<br />
inputs<br />
Analog<br />
inputs<br />
Analog<br />
inputs<br />
Analog<br />
inputs<br />
FEE<br />
. . .<br />
FEE<br />
FEE<br />
. . .<br />
FEE<br />
Clock, T0,<br />
RTrgX, DCS<br />
DATA,<br />
RTrgX, DCS<br />
. . .<br />
. . .<br />
Copper<br />
250 Mbps<br />
OASE<br />
OASE<br />
Optical<br />
2.5 Gbps<br />
redundant downstream link<br />
downstream link<br />
(DATA, RTrgX, DCS)<br />
Upstream link<br />
(Clock, T0, RTrgX, DCS)<br />
optical<br />
SO - SOASE<br />
OASE<br />
OASE<br />
OASE<br />
OASE<br />
OASE<br />
Merger FPGA<br />
DATA<br />
RTrgX<br />
CNET RTrgX next neighbors<br />
OASE<br />
DCS frames<br />
DCS<br />
SBC<br />
BNet<br />
readout data<br />
Ref. clk / t0<br />
Ethernet 100<strong>MB</strong>ps<br />
configuration data<br />
Figure 9.42: Architectural building blocks of the CNet front-end (left) and its back-end, interfacing to the BNet<br />
infrastructure<br />
Figure 9.42 (left) sketches the appropriate architecture. The high-speed down-stream links feed directly<br />
into one large FPGA module. The upstream signalling does not require a high individual bandwidth<br />
and therefore is implemented as passive or active broad cast network. The figure sketches an electrical<br />
fan-out.<br />
Slow control messaging is orchestrated by a DCS single board computer. It is expected to implement<br />
a low cost single board computer, running Linux here. The back-end network is Ethernet here (refer<br />
also to section 10.5.4.5. DCS messages generated in the front-end are stripped by the merger FPGA and<br />
forwar<strong>de</strong>d directly to the DCS single board computer for further processing. DCS messages to be sent<br />
to the front-end are generated on the DCS single board computer and are forwar<strong>de</strong>d to the OASE root<br />
module for further fanning out. Given a DCS messaging band width of 25 Mb and assuming a link bandwidth<br />
of 2.5 Gb/s a fan-out of 25 will result in a 25% utilization of the available link bandwidth, allowing<br />
enough available bandwidth for the up-stream distribution of geographic neighbor readout commands to<br />
the appropriate front-end chips. The messages are stripped by the appropriate OASE modules via their<br />
individual geographic ID, which is <strong>de</strong>fined by the location of the reaodut-board. The appropriate OASE<br />
root module also receives a reference clock and t0 signal for clearing all time counters. These signals are<br />
expected to be <strong>de</strong>rived from the <strong>GSI</strong> BuTis system [193].<br />
The CNet readout, control and clock synchronization network is implemented as cost-effective, hierarchical,<br />
redundant, optical interconnect structure. Since the time and clock distribution functionality<br />
(TNet) is also inclu<strong>de</strong>d in the CNet functionality, no clock recovery is the required in the FEE chips. The<br />
result is a synchronous FEE/CNet Subsystem (refer also to figure 9.42 (left)). Additionally, effort may<br />
be put into the <strong>de</strong>velopment of an extremely low-jitter PLL element, in o<strong>de</strong>r to reach the strict timing<br />
requirements for the Time-of-Flight <strong>de</strong>tector.<br />
The CNet over all tasks are summarized in the following list:<br />
1. Transport of data from FEE units on the <strong>de</strong>tector via the CNet to the BNet interface in the counting<br />
room.<br />
2. Combining of correlated hits to hit clusters, based on the hit time information wherever possible<br />
in or<strong>de</strong>r to reduce the messaging rate and overhead.
228 Common Front-End Electronics Aspects<br />
3. In<strong>de</strong>pen<strong>de</strong>nt use of fractional bandwidth for bidirectional communication of DCS control- and<br />
status messages.<br />
4. In<strong>de</strong>pen<strong>de</strong>nt upstream time distribution with time stamps and epoch markers.<br />
5. In<strong>de</strong>pen<strong>de</strong>nt upstream synchronous clock distribution.<br />
6. Nearest neighbor very low latency hit communication to geographically adjacent <strong>de</strong>tector channels<br />
for readout of geographical hit tails.<br />
7. Redundancy and avoidance of single points of failure, in particular in the area of clock distribution<br />
and DCS networking.<br />
8. Radiation tolerance of all network components.<br />
The distribution of data within BNet will require some flow control and traffic shaping to be implemented<br />
in or<strong>de</strong>r to avoid overutilizing target resources [195].<br />
9.9.3 Link Protocol Physical Layer (FELA)<br />
Given all consi<strong>de</strong>rations outlined in the sections above, the CNet physical layer has to support five different<br />
functionalities. They are supported by a set of different special purpose messages, which are<br />
summarized in table 9.3 and will be discussed in <strong>de</strong>tail in the following. The overall principle is based<br />
on the minimization of the overhead for message hea<strong>de</strong>rs on one hand and to keep the messages as<br />
short as possible in or<strong>de</strong>r to achieve a very low latency for the transmission of some of the hit trigger<br />
messages. Both serial and 8-bit double data rate physical transmission paths have to be supported. The<br />
required logic for message processing has to work in FPGAs as well, limiting the internal clock rate.<br />
Therefore a 16 bit data path was assumed for all chip or FPGA internal processing requiring a word<br />
clock of 120 MHz for the 2.5 GBit transmission lines. Therefore all CNet messages have a granularity<br />
of 16 bits.<br />
Acronym Prio. Length Function <strong>de</strong>scription<br />
DATA 5 32...272 data readout downstream payload data format <strong>de</strong>tector specific<br />
DCS 3 32...272 DCS DCS Payload, stripped by merger FPGA<br />
RdTrgV 4 32...64 hit trigger next neighbor readout trigger command<br />
RdTrgC 4 16 hit trigger downstream next neighbor readout trigger command<br />
RdTrgB 4 16 hit trigger upstream next neighbor readout trigger broadcast command<br />
T0 2 16 TNet upstream time counter reset<br />
RESET 1 16 DCS RESET command<br />
IDLE x 16 CNet idle message<br />
StdBy N/A 16 CNet link powered down message<br />
Table 9.3: The various CNet frame types and their functions. The frame length inclu<strong>de</strong>s the 16-bit hea<strong>de</strong>r/trailor.<br />
9.9.3.1 Data readout<br />
The readout of all data, acquired by the various front-end modules, is the primary CNet function. It<br />
produces more than 95% of the downstream data traffic. The data readout is a unidirectional data path<br />
flowing downstream from the front-end towards the back-end. In or<strong>de</strong>r to keep the maximum latency
9.9. CNet – Concentrator Network 229<br />
small, the maximum frame size is limited. A payload of 32 bytes, constituting an overhead of 6.25%<br />
for the CNet hea<strong>de</strong>rs, corresponds to a frame length of 136 ns for a 2.5 Gbit link, well below the stated<br />
maximum CNet latency. The payload format is <strong>de</strong>tector <strong>de</strong>pen<strong>de</strong>nt and entirely transparent to the CNet<br />
switching functionality. The DATA packets are transparently passed through. They have the lowest<br />
priority, compared to all other CNet messages. Data messages are variable length with the frame length<br />
being enco<strong>de</strong>d in the CNet 16-bit hea<strong>de</strong>r.<br />
9.9.3.2 DCS<br />
The available full duplex connectivity provi<strong>de</strong>d by CNet can be used also to implement DCS message<br />
passing. It is emphasized here, that this functionality is entirely in<strong>de</strong>pen<strong>de</strong>nt of all other CNet messages.<br />
The DCS and other packets only share the same physical transport as many other networks impelement<br />
several in<strong>de</strong>pen<strong>de</strong>nt data paths, while guaranteeing appropriate quality of service levels. This functionality<br />
is implemented in the CNet physical interfaces, guaranteeing a minimum bandwidth and maximum<br />
latency to the DCS data paths, which is quite small given the limited frame sizes. DCS has the highest<br />
network priority, except for the T0 and RESET functionality, which is executed un<strong>de</strong>r DCS control and<br />
in a way can be consi<strong>de</strong>red as DCS subfunctionality. Like data readout DCS frames are variable length<br />
with a maximum payload of 32 bytes. DCS frames are distributed both downstream and upstream. In<br />
the first case they share the bandwidth with the data readout, with a minimum bandwidth guaranteed to<br />
DCS. Given the CNet topology, upstream DCS messages are broadcast to all front-end modules, therefore<br />
requiring proper <strong>de</strong>coding. Therefore the DCS payload has to inclu<strong>de</strong> a front-end target ID. All<br />
other messages are discar<strong>de</strong>d like in any other broad cast type network. This <strong>de</strong>coding and corresponding<br />
encoding of the responses can be easily implemented by the integrated microcontroller of the OASE<br />
chips (refer to section 9.8.2).<br />
9.9.3.3 Readout Trigger<br />
In or<strong>de</strong>r to inform FEE modules about neighboring hits and to trigger the readout of geometric neighbors<br />
the information of a hit has to be distributed. This information has to inclu<strong>de</strong> the time of hit, and an<br />
appropriate channel i<strong>de</strong>ntifier, which can be <strong>de</strong>fined as FEE channel number, FEE ID and the <strong>de</strong>tector<br />
ID. Not all those bits are required at all levels to be present as they may be <strong>de</strong>fined implicitly. Table 9.4<br />
gives an outline of the number of bits required for an appropriate encoding. The hit information has to be<br />
distributed with minimum latency to the appropriate front-end chips, which then readout a preconfigured<br />
number of time bins and channels around the hit time and coordinate.<br />
Object Bits <strong>de</strong>scription<br />
Channel 5 assuming a maximum of 32 channels per front-end chip<br />
FEE ID 17 assuming less than 127k front-end chips per <strong>de</strong>tector<br />
Detector ID 4 CBM <strong>de</strong>fines 5 major <strong>de</strong>tector systems<br />
Hit Time 11 at a granularity of 1 ns 2 µs maximum CNet latency<br />
Table 9.4: Required number of bits to enco<strong>de</strong> a hit message<br />
There are two formats of readout trigger frames <strong>de</strong>fined. A long frame, containing the entire hit information,<br />
requiring 64 bits or 32 ns to transmit at 2.5 Gbits/sec. It has to be transmitted and routed by<br />
CNet to the appropriate front-end modules within less than 2 µs. This frame can be used downstream<br />
and upstream.<br />
In case of multiple front-end chips feeding one high-speed link (OASE), a reduced frame length can be
230 Common Front-End Electronics Aspects<br />
used to communicate the hit information upstream (OASE→ FEE chips), in or<strong>de</strong>r to save latency since<br />
these links operate at reduced bit rates (for instance 4 ns/bit). For the downstream (FEE→ OASE chips)<br />
communication the third hit trigger frame can be used (RdTrgC). It does not require any payload, except<br />
for the FEE channel ID. For FEE modules with more than 16 channels, two or more channels may have to<br />
be grouped together for the purpose of transmitting readout triggers or a longer format has to be <strong>de</strong>fined<br />
(RdTrgV). The time and FEE ID is ad<strong>de</strong>d by the OASE chip, implementing a configurable preloa<strong>de</strong>d<br />
frame, which is sent with the appropriate channel ID every time a (RdTrgC) frame is received. It is<br />
therefore required for this particulare frame, that there is a fixed latency between the hit time and its<br />
transmission.<br />
In or<strong>de</strong>r to support synchronized readout of a group of front-end channels in<strong>de</strong>pen<strong>de</strong>nt of their hit information,<br />
for instance for calibration, base-line readout, etc, the readout trigger broadcast frame (RdTrgB)<br />
is <strong>de</strong>fined. It has only one parameter, <strong>de</strong>fining the time for the readout window. The pre and post history<br />
to be used are preconfigured parameters in all FEE modules. This command can be used to stimulate<br />
software or external hardware readout triggers for an entire region of a <strong>de</strong>tector, by feeding it into the<br />
upstream broadcast network. A good candidate for the insertion of these frames are the DCS single board<br />
computers.<br />
9.9.3.4 Time, TNet<br />
In or<strong>de</strong>r to produce coherent time in all front-end modules, they implement appropriate counters with a<br />
1 ns granularity. They need to be reset synchronously for proper time synchronization. This funcionality<br />
is expected to be executed when a run is started, when a synchronization error is <strong>de</strong>tected or at a low<br />
periodic rate. T0 frames are distributed upstream only. They are single word 16-bit messages, which are<br />
forwar<strong>de</strong>d by any agent immediately without any time jitter. Therefore they have the highest priority in<br />
the network.<br />
The second TNet functionality is the distribution of a synchronized clock to all front-end modules. This<br />
functionality is provi<strong>de</strong>d automatically by the PLLs in the multi gigabit receivers, since they by nature<br />
have to synchronize to the incoming bit stream with a clock jitter much smaller than the stated <strong>de</strong>tector<br />
requirement.<br />
9.9.3.5 Miscellaneous Frames<br />
There are a few additional single word 16-bit messages, which are in part un<strong>de</strong>r the over all DCS control<br />
and are processed at CNet data link layer, in<strong>de</strong>pen<strong>de</strong>nt of the state of the appropriate receiver.<br />
RESET frames allows to issue a physical reset to the target <strong>de</strong>vice. The second nibble allows to <strong>de</strong>fine<br />
certain RESET or clear types (ClrTyp). The <strong>de</strong>coding of this frame is implemented directly at the data<br />
link layer and interfaces directly to the on-chip reset and clear logic, in<strong>de</strong>pen<strong>de</strong>nt of the state of the chip.<br />
This message allows to RESET a peer module, provi<strong>de</strong>d the minimum connectivity is still available.<br />
IDLE frames are transmitted as keep alive messages to maintan link synchronization. They are not<br />
required for DC LVDS signalling, which is DC coupled or even powered down. However the reference<br />
clock has to be distributed then via other means. The unused length bits of the IDLE frame may be used<br />
to distribute generic system states, etc.<br />
StdBy frames are <strong>de</strong>fined only for completeness. The LVDS transmitters in the front-end can be disabled<br />
in or<strong>de</strong>r to save power during system idle times. In that case the appropriate receiver will read<br />
zeros. Therefore the StdBy frame has all bits <strong>de</strong>fined as zero, including the CRC, which is incorrect in<br />
this case.
9.9. CNet – Concentrator Network 231<br />
9.9.3.6 Physical Format<br />
The hea<strong>de</strong>r is composed of four nibbles. The first nibble <strong>de</strong>fines the message type. At this point 9 of<br />
the 16 possible combinations are <strong>de</strong>fined, leaving enough spare room. The second nibble <strong>de</strong>fines the<br />
number of 16 bit payload blocks. In or<strong>de</strong>r to support a payload of up to 32 bytes, the payload count is<br />
enco<strong>de</strong>d as N-1. The third nibble implements a 4-bit CRC on the entire packet, including the hea<strong>de</strong>r.<br />
It forms the CNet trailer. It should be noted that CRC checking normally requires the implementation<br />
of a store-forward architecture, since only in that case it is possible to ensure that only packets with a<br />
correct CRC are being transmitted. However, in or<strong>de</strong>r to minimize the message passing latency another<br />
aproach is implemented. Any message is forwar<strong>de</strong>d as quickly as possible, implementing cut-through<br />
routing. Should a message be received with a bad CRC the transmitted CRC is being stomped [196].<br />
This stomped CRC is <strong>de</strong>fined as the correctly recomputed CRC, being XORed with a stomp value. This<br />
stomp co<strong>de</strong> to use here will have to be evaluated. This technique allows to i<strong>de</strong>ntify the first location of the<br />
error and allows isolate potential hardware problems and does not escalate one error accross the network<br />
but it also allows cut-through routing of the messages. The final receiver of a corrupted message will<br />
<strong>de</strong>stroy it as it may not even know whether or not it is the correct receiver, as also address information<br />
possibly contained in the packet may have been altered.<br />
(A)<br />
(B)<br />
(C)<br />
SOF XX<br />
SOF XX<br />
SOF XX<br />
SOF XX<br />
SOF XX<br />
SOF XX<br />
0 4 0 15 8 11<br />
Type Len16-1 Payload Block 1<br />
…<br />
CRC4 RTrgV 0010 48 bits (FEE ID 17 – Channel 5 – Hit time 12 – spare 14 ) CRC 4<br />
SOF XX RTrgC Chnl ID CRC4 EOF XX<br />
SOF XX RTrgB Tim ID CRC4 EOF XX<br />
RESET ClrTyp CRC 4<br />
IDLE 0000 CRC 4<br />
T0 0000 CRC 4<br />
StdBy=0 0000 CRC 4 =0<br />
EOF XX<br />
EOF XX<br />
EOF XX<br />
EOF XX<br />
EOF XX<br />
SOF XX DATA NNNN Data hea<strong>de</strong>r + Data payload<br />
…<br />
CRC4 EOF XX<br />
SOF XX DCS NNNN DCS hea<strong>de</strong>r + DCS payload<br />
…<br />
CRC4 EOF XX<br />
SOF XX RTrgV 0000 16 bits (Channel5 – Hit time11 ) CRC4 EOF XX<br />
EOF XX<br />
Figure 9.43: Outline of the most<br />
important CNet physical frames, including<br />
the generic overall format<br />
(A), frames with data payload (B)<br />
and command frames without payload<br />
(C).<br />
Figure 9.43 shows a physical layout of the various CNet packets. Asi<strong>de</strong> from the three nibbles type,<br />
length and CRC there are four bits, being used for start of frame (SOF) and end of frame (EOF). The<br />
particular choice of SOF and EOF coding is a tra<strong>de</strong>-off between latency and power. For instance the<br />
choice of SOF=001 and EOF=0 gives two leading zeroes before the canonical start bit. Note the LVDS<br />
receivers will <strong>de</strong>co<strong>de</strong> a disabled peer transmitter reliably as zero and the time required to safely power<br />
up an LVDS transmitter is less than 4 ns (refer to section 9.2.2). Two leading zeros in the SOF guarantee<br />
the start bit 1 to be safely <strong>de</strong>co<strong>de</strong>d even if the transmitter is enabled only at the moment the SOF is being<br />
transmitted. Therefore this encoding scheme allows to operate the LVDS links in an on <strong>de</strong>mand fashion,<br />
requiring less than 7% of the on-line power in stand-by for the LVDS receiver. Note the frame lengths<br />
sketched in figure 9.43 are not to scale. For completeness a corresponding stand-by packet is <strong>de</strong>fined<br />
with all bits being zero.
232 Common Front-End Electronics Aspects<br />
9.10 Miscellaneous, Infrastructure<br />
9.10.1 Power distribution<br />
Basically all mo<strong>de</strong>rn front-end chips require supply voltages below 5 V. For instance the UMC 180 nm<br />
process operates at a core voltage of 1.8 V and an I/O voltage of 3.3 V. The typical candidates for supply<br />
voltages to date are 1.8 V, 2.5 V, 3.3 V and 5 V. On the time scale of the CBM experiment it is expected<br />
not to see 5 V any more and there may be requirements for supply voltages below 1 V. For instance<br />
FPGAs are candidates here.<br />
It should be noted also that there are two principal choices, where the first one is distributing some<br />
higher supply voltage and implementing step down regulators close to the front-end, and the second is<br />
the generation of the low voltage outsi<strong>de</strong> the <strong>de</strong>tector and the distribution of the low voltage into the frontend.<br />
So far the first approach was typically rejected since the requirements on the step down regulators<br />
are complex. They have to operate in magnetic fields and their fringe fields, have to be radiation tolerant<br />
and finally there is always a concern of electronic switching noise and heat dissipation close to the<br />
<strong>de</strong>tectors. For those reasons also the ALICE TRD and TPC <strong>de</strong>tectors, for instance, chose the second<br />
mo<strong>de</strong>l. However, it has to be stressed that in case of ALICE the length of these low voltage distribution<br />
lines is about 40 m. Further the current requirements add up here exceeding 10 kA distributed over the<br />
supply voltages 1.8 V and 3.3 V. The voltage drop in the supply lines lies at 1V with an additional 0.3 V<br />
for the local analog voltage regulation. The ad<strong>de</strong>d complexity and material budget to distribute tens of<br />
kiloampere is significant.<br />
The supply lines in CBM may be shorter as this is not a colli<strong>de</strong>r experiment with a solenoidal magnet.<br />
But also here the length of the low voltage supply lines will easily reach the 10 m level. In or<strong>de</strong>r to have a<br />
more elegant low voltage generation CBM plans to <strong>de</strong>velop a step down regulator with the requirements<br />
to operate insi<strong>de</strong> the experiment. In this respect CBM follows a standard industry trend. For instance<br />
the core voltage of the processor in any mo<strong>de</strong>rn PC is also generated with step down regulators, closely<br />
located to the current sink.<br />
The general requirements of the step down regulator to be <strong>de</strong>veloped are summarized in the following:<br />
• use of a low-cost primary power supply outsi<strong>de</strong> the <strong>de</strong>tector, for instance generating 48 V DC,<br />
mo<strong>de</strong>rately regulated in or<strong>de</strong>r to avoid particular safety and 50 or 600 Hz noise issues of the low<br />
voltage distribution<br />
• <strong>de</strong>sign the electronics to be radiation tolerant up to 1 MRAD.<br />
• <strong>de</strong>sign of proper inductive transformer to operate in the <strong>de</strong>fined static magnetic fields and fringe<br />
fields<br />
• operate step down regulator at as high as possible frequencies (>10 MHz) in or<strong>de</strong>r to stay far away<br />
from typical frequency domains of the preamplifiers.<br />
• implementation of DCS functionality, allowing to measure voltage and currents <strong>de</strong>livered by the<br />
regulator, its core operating temperature and supporting remote control and possibly adjustment of<br />
the <strong>de</strong>livered output voltages.<br />
The regulator is planned to be <strong>de</strong>veloped as one integrated control chip, implementing all necessary components<br />
with a minimum of external <strong>de</strong>vices, such as the transformer, capacities and power components.
9.10. Miscellaneous, Infrastructure 233<br />
Year Mo<strong>de</strong>l Complexity<br />
1990 XC3042 288 LUTs + flip-flops<br />
1994 XC4005 512 LUTs + flip-flops<br />
1994 XC40013XL 1,152 LUTs + flip-flops<br />
2000 XCV300 6,144 LUTs + flip-flops<br />
2002 XC2V1000 10,240 LUTs + flip-flops<br />
2004 XC2VP30 27,382 LUTs + flip-flops<br />
2005 XC4V60-LX 53,248 LUTs + flip-flops<br />
Table 9.5: Growing of resources for middle-of-the-road FPGAs with same price, equivalent to one day’s engineering<br />
salary (from [197])<br />
9.10.2 FPGA Roadmap<br />
The complexity of FPGAs and the amount and diversity of ASIC blocks which are integrated together<br />
with the FPGA matrix is going to increase. Therefore the boandary for what is best implemented in an<br />
ASIC and what is better implemented in an FPGA is hard to predict at this point in time. At the least there<br />
has to be a working mo<strong>de</strong>l as to what is to be expected with respect to FPGA functionality, complexity,<br />
performance, radiation tolerance and the like. These parameters will have to be monitored during the<br />
<strong>de</strong>velopment of the CBM <strong>de</strong>tectors in or<strong>de</strong>r to ensure a good choice of FPGA and ASIC combination.<br />
This section gives a first outlook of FPGA road maps.<br />
The open question addressed in this section is: How will FPGAs look like in 2010, and what will these<br />
<strong>de</strong>vices cost? To answer this question two types of FPGAs need to be distinguished: Low-Cost FPGAs<br />
(e.g. Xilinx Spartan Series, Altera Cyclone Series) and High-End FPGAs (e.g. Xilinx Virtex Series,<br />
Altera Stratix Series).<br />
Currently we see improvements into two directions: low-cost FPGAs having the same gate count become<br />
dramatically cheaper, or we see an enormous gain in terms of logic cells on a chip for the same price.<br />
High-End FPGAs on the other hand migrate from pure glue logic to configurable system platforms based<br />
on multiple processing elements, on-chip memory and high speed connection links (LVDS and multi<br />
gigabit serial transceivers).<br />
One reason for this trend is that FPGA technology gains the maximum benefit from the <strong>de</strong>velopment in<br />
the chip industry. Because of their very regular internal structure FPGAs are, besi<strong>de</strong>s RAMs, the first<br />
chips that can be built in new technologies. General purpose processors are typically following later due<br />
to their higher complexity.<br />
In case of low cost Xilinx Spartan FPGAs the cost for 400k gates went from 100$ (1998) to 40$ (2000)<br />
to 6.5$ (2004). This implies a cost reduction of factor 2.5 every two years. If we extrapolate this curve<br />
to 2010, we will be able to buy a 400k gate low cost FPGA for a little more than 40 cent.<br />
One of the major drawbacks of using FPGAs in current applications is the high power consumption per<br />
gate, compared to standard CMOS ASICs. However, since there is a lot of research going on at the<br />
moment, we expect a reduction of the power per gate of at least 65% by 2010. Therefore, in eight years<br />
from now, FPGAs may be used in many cases, where cooling and total power consumption is an issue.<br />
Watching high-end FPGAs (e.g. Xilinx Virtex), we see a similar <strong>de</strong>velopment curve. The <strong>de</strong>velopment<br />
of the costs in the past show a dramatic <strong>de</strong>crease, in 1990 one FPGA logic cell costs about 1, in 2003<br />
this is only 0.002. The resources of middle-of-the road FPGAs with constant price doubles every few<br />
years, see table 9.5. It can be expected that FPGAs with a capacity well above 100k logic cells and clock<br />
rates in excess of 500 MHz will become available at commodity prices towards the end of the time frame.
234 Common Front-End Electronics Aspects<br />
This will allow implementing many complex algorithms in FPGAs.<br />
Also the maximum clock frequency increases by a factor of 2 every 5 years [197]. Currently the clock<br />
frequency has reached 500 MHz for FPGA logic. If we extrapolate this <strong>de</strong>velopment to 2010, we will<br />
reach 1 GHz as a maximum clock frequency for the FPGA internal logic. Taking into account, that<br />
FPGAs will contain many (e.g. more than 1000) hard multiply-add cores, FPGA <strong>de</strong>vices become a perfect<br />
solution for computing intensive DSP applications.<br />
Additionally to the logical resources, mo<strong>de</strong>rn FPGAs also offer up to 20 10 Gbit/s serial I/O (SERDES)<br />
in silicon, together with embed<strong>de</strong>d processors for monitoring, test and control. 10 Gbit/s links over<br />
optical or copper interconnects as well as the associated switching hardware are expected at affordable<br />
prices in the next few years.<br />
It is not sure whether all FPGA system level features, like glitch-free partial reconfiguration, on-chip<br />
multi-gigabit transceivers, hard processor cores etc. will be available in low-cost FPGAs. However,<br />
there is a clear indication that at least processor cores will be inclu<strong>de</strong>d to the Xilinx Spartan series very<br />
soon.<br />
The above mentioned <strong>de</strong>velopment is only valid for coarse grain FPGAs like the ones from Xilinx,<br />
Altera and Actel. However, there are numerous other approaches having more complex programming<br />
elements as the basic computing elements like the XPP from PACT. The XPP architecture is heavily<br />
used for implementing communication applications. Further research needs to be done comparing these<br />
<strong>de</strong>vices with fine grain FPGAs in terms of power effectiveness, compute latency, programming tools and<br />
radiation hardness.<br />
As summary FPGAs should be used instead of custom ASICs where ever possible and cost effective.<br />
The flexibility is an important advantage since <strong>de</strong>sign errors may be corrected by simply downloading a<br />
new configuration file. New algorithms may be <strong>de</strong>ployed in the same manner giving the user a possibility<br />
to adapt algorithms in a much more convenient way. Many drawbacks like power consumption, slower<br />
clock frequency and the higher prices for medium and high volumes will mitigate within the following<br />
6 years. This observation is true in particular, taking into account that the ASIC <strong>de</strong>velopment cycles are<br />
much slower, therefore resulting in an ol<strong>de</strong>r technology being used for ASICs as compared to FPGAs<br />
(refer also to section 9.1.2).<br />
9.10.3 Radiation Tolerance<br />
The rapid <strong>de</strong>velopment of SRAM-based FPGAs is expected to continue in the coming years. Today’s<br />
<strong>de</strong>vices are already candidates for time-critical, compute intensive operations at all levels of the readout<br />
chain. Due to their flexibility, complexity, integrated resources (e.g. DSPs, microprocessors, large<br />
distributed memory blocks, fast communication cores), computational potential and price, SRAM-based<br />
FPGAs can outperform general purpose CPUs by or<strong>de</strong>rs of magnitu<strong>de</strong>. Although FPGAs are also available<br />
in flash or anti-fuse technology, the latter are a lot more expensive, much smaller and simpler and<br />
therefore not an alternative to SRAM-based FPGAs.<br />
SRAM-based FPGAs have one drawback: they are sensitive to radiation. If they are operated in radiation<br />
fields, fast hadrons (neutrons, protons, pions, kaons and heavier nuclei with kinetic energies larger than<br />
20 MeV) traverse the sensitive volume and react with the silicon nuclei. Although the energy loss of<br />
the projectile in silicon is not sufficient to change the state of a SRAM cell (in today’s technology), the<br />
spallation products (the recoil nucleus and heavy fragments) <strong>de</strong>posit larger amounts of energy in the<br />
sensitive volume.<br />
Sequential and combinatorial logic, registers and memory blocks can be protected against errors due to<br />
such bit-flips by classical redundancy methods – data: hamming coding, functionality: triple module
9.10. Miscellaneous, Infrastructure 235<br />
redundancy and voting scheme. But radiation induced bit-flips – Single Event Upsets (SEUs) – in the<br />
configuration SRAM are severe. If not corrected, they can cause SEFIs (Single Event Functional Interrupts)<br />
in the application. Since applications use between 2% and 10% of the routing resources, typically<br />
only 10% of the SEUs result in SEFIs. SEUs can by monitored by reading back the configuration bit<br />
stream. Most FPGA <strong>de</strong>vices offer a fast readback for verification and localization of a SEU in the configuration<br />
SRAM. Once <strong>de</strong>tected and localized, the SEU can be repaired by reconfiguration. Currently<br />
only Xilinx allows an active error correction via “Active Partial Reconfiguration”. Because most primary<br />
SEUs are not even visible as SEFIs – and if corrected in a timely manner – secondary effects (SEFIs as<br />
a combined result of two or more primary SEUs) can be prevented. Almost all errors can be corrected<br />
this way, maybe resulting in transient upsets (“data noise”), but basically keeping the <strong>de</strong>vice alive and<br />
the application running.<br />
The applicability of such a correction scheme <strong>de</strong>pends on the rate of SEUs, given as the product of the<br />
particle flux and the SEU cross section. The cross section per bit in its turn <strong>de</strong>pends on the structure size<br />
of the technology, e.g. 10 −14 cm 2 for the 90 nm technology. The particle flux has to be <strong>de</strong>termined by<br />
FLUKA simulations, and the application <strong>de</strong>fines the amount of resources (= number of configuration<br />
bits). The upper limit of applicability is given by the radiation damage due to cumulative effects, but<br />
such fluences will not be accumulated due to the limiting flux given by the SEU rate.<br />
Since the <strong>de</strong>pen<strong>de</strong>nce of the SEU cross section on the technology is a priori unknown and cannot be<br />
sufficiently simulated (at least not today), it has to be measured by an accelerated method. FPGAs are<br />
usually irradiated in neutron and proton beams at different energies with fluxes much larger than the expected<br />
flux in the experiment. Such data for the ALTERA APEX20K400 and the XILINX XC2VP7 have<br />
been collected at the Oslo cyclotrone laboratory and the cyclotrone at TSL in Uppsala [198]. First results<br />
on the active partial reconfiguration of the XILINX FPGAs un<strong>de</strong>r irradiation are promising. However,<br />
although the use of SRAM FPGAs in radiation fields seems manageable, cross section measurements of<br />
the selected technology and the verification of the reconfiguration scheme un<strong>de</strong>r irradiation are mandatory.
236 Common Front-End Electronics Aspects
10 Data Acquisition, Event Selection, Controls,<br />
On-line/Off-line Computing<br />
10.1 Introduction<br />
Many of the signatures pursued with the CBM experiment are based on rare processes. To achieve an<br />
a<strong>de</strong>quate sensitivity, the <strong>de</strong>tector systems are <strong>de</strong>signed to operate at interaction rates of up to 10 MHz<br />
for A-A collisions and up to several 100 MHz for p-p and p-A collisions. It is the task of the data<br />
acquisition and event selection system to i<strong>de</strong>ntify the candidate events for the physics signals un<strong>de</strong>r<br />
study and send them to archival storage. The most challenging aspect is here the measurement of open<br />
and hid<strong>de</strong>n charm production in heavy ion collisions down to very low cross sections. The D mesons<br />
will be i<strong>de</strong>ntified via the displaced vertices of their hadronic <strong>de</strong>cays, the <strong>de</strong>cision for selecting candidate<br />
events thus requires tracking, primary vertex reconstruction, and secondary vertex finding in the STS. In<br />
addition, the system has to be configurable to handle a wi<strong>de</strong> range of physics signals, ranging from D<br />
and J/ψ in A-A collisions over low-mass dileptons in p-A collisions to ϒ in p-p collisions.<br />
The conventional system <strong>de</strong>sign with triggered front-end electronics allows to keep the event information<br />
for a limited time, usually a few µs, in the front-end electronics while a fast first level trigger <strong>de</strong>cision<br />
is <strong>de</strong>termined from a subset of the data. Upon a positive trigger <strong>de</strong>cision, the data acquisition system<br />
transports the selected event to higher level trigger processing or archival storage. A system with such<br />
a fixed trigger latency constraint is not well matched to the complex algorithms nee<strong>de</strong>d for a D trigger,<br />
especially in the case of heavy ion interactions, where the multiplicities and thus the numerical effort<br />
nee<strong>de</strong>d for a <strong>de</strong>cision varies strongly from event to event.<br />
The concept adopted for CBM will use self-triggered front-end electronics, where each particle hit is<br />
autonomously <strong>de</strong>tected and the measured hit parameters are stored with precise timestamps in large<br />
buffer pools. The event building, done by evaluating the time correlation of hits, and the selection of<br />
interesting events is then performed by processing resources accessing these buffers via a high speed<br />
network fabric. The large size of the buffer pool ensures that the essential performance factor is the total<br />
computational throughput rather than <strong>de</strong>cision latency. Since we avoid <strong>de</strong>dicated trigger data-paths, all<br />
<strong>de</strong>tectors can contribute to event selection <strong>de</strong>cisions at all levels, yielding the required flexibility to cope<br />
with different operation mo<strong>de</strong>s.<br />
In this approach we have no physical trigger signal, which prompts a data acquisition system to read a<br />
selected event and transport it to further processing or storage. We thus avoid the term ’trigger’ in this<br />
chapter. The role of the data acquisition system is to transport data from the front-end to processing<br />
resources and finally to archival storage. The event selection is done in several layers of processing<br />
resources, reminiscent of the trigger level hierarchy in conventional systems.<br />
One consequence of using self-triggered front-end electronics is a much higher data flow coming from<br />
the front-ends on the <strong>de</strong>tector. For CBM a data rate of about 1 TByte/sec is expected. However, communication<br />
cost is currently improving faster over time than processing cost, an observation sometimes<br />
termed Gil<strong>de</strong>r’s law, making such a concept not only feasible but also cost effective.<br />
237
238 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
10.2 Overall Architecture<br />
The communication and processing nee<strong>de</strong>d between the front-end electronics, generating digitized <strong>de</strong>tector<br />
information, and the archival storage, where the complete context of selected candidate events<br />
is recor<strong>de</strong>d, can be structured and organized in several ways. The solution <strong>de</strong>scribed in this chapter is<br />
gui<strong>de</strong>d by two principles: processing is done after event building and it is done in a structured processor<br />
farm. It is well adapted to the type of processing nee<strong>de</strong>d in the CBM experiment and leads to a<br />
straightforward and modular architecture.<br />
FEE<br />
CNet<br />
BNet<br />
PNet<br />
HNet<br />
Detector 1 Detector 2 Detector N<br />
to high level computing<br />
September 9, 2004 CBM FEE/DAQ/Trigger - System and Network Architecture, Walter F.J. Müller, <strong>GSI</strong> 1<br />
Figure 10.1: CBM overall data processing architecture<br />
A logical data flow diagram is shown in Fig. 10.1, indicating the data sources and processing elements<br />
as boxes and every form of interconnection networks as ovals. The main components are:<br />
• Front-end electronics (FEE): The front-end <strong>de</strong>tects autonomously every particle hit and sends<br />
the hit parameters together with a precise timestamp and channel address information over the<br />
concentrator network (CNet) to a buffer pool, a more <strong>de</strong>tailed <strong>de</strong>scription was already given in<br />
sections 9.1 and 9.3.<br />
A rough estimate for the data volume generated by a <strong>de</strong>tector channel can be <strong>de</strong>duced from typical<br />
CBM operation and <strong>de</strong>tector parameters: 10 MHz interaction rate, 10 % occupancy for central<br />
collisions, a ratio of 1/4 for minimum bias to central multiplicity, and a typical cluster size of<br />
3 fired electronics channels per physical particle hit gives a channel count rate of about 750 kHz.<br />
Assuming 8 byte per hit yields a data flow of about 6 <strong>MB</strong>/sec and channel. For a typical FEE unit<br />
with 16 channels this results in a data rate of 100 <strong>MB</strong>/sec which can be transported over a single<br />
GBit serial link.<br />
• Clock and time distribution (TNet): The timestamps of each hit are used to associate hits with<br />
events but also in drift and flight time measurements. Thus not only a time scale, in practice a<br />
frequency, but also information about the absolute time has to be communicated to all front-end<br />
TNet
10.2. Overall Architecture 239<br />
units. The most stringent requirements come from the START and RPC <strong>de</strong>tectors, where the<br />
contribution from the clock jitter should be below 25 ps sigma.<br />
The most straightforward approach is to distribute a common clock frequency and to provi<strong>de</strong> a<br />
mechanism for broadcasting information with clock cycle precise latency to all units. The minimal<br />
required functionality is a global clock reset at the begin of the measurement, or alternatively,<br />
distribution of tick marks every second as provi<strong>de</strong>d by the planned campus-wi<strong>de</strong> frequency and<br />
time normal.<br />
The TNet is thus a <strong>de</strong>dicated broadcast network, connecting a central controller logically with<br />
all front-end units. The last hop to the front-end units may be implemented with the part of the<br />
CNet infrastructure, as indicated by the connection of TNet to CNet in Fig. 10.1 and discussed in<br />
sections 9.8.1 and 9.9.3.4.<br />
• Concentrator Network (CNet): The role of the concentrator network is to collect the data from<br />
the individual front-end units and aggregate the traffic on a set of high speed links which connect<br />
the <strong>de</strong>tector with the area where the data buffers and the data processing is located. A rough<br />
estimate for the total data rate is 1 TB/sec which could be finally transported off the <strong>de</strong>tector with<br />
about 1000 links with 10 Gbps each.<br />
The simplest implementation of the CNet is a collection of in<strong>de</strong>pen<strong>de</strong>nt concentrator trees, one<br />
for each high speed link. However, a better load balancing or an appropriate <strong>de</strong>gree of failure<br />
tolerance is likely to call for a more connected topology.<br />
In addition to the hit data transport from front-end to buffering, other communication tasks like<br />
control traffic or time distribution can be handled by the CNet infrastructure. Such an integrated<br />
approach is especially useful in conjunction with low-cost optical links (see section 9.7.3 and 9.8)<br />
and discussed in <strong>de</strong>tail in section 9.9.<br />
• Active Buffers: The next stage in the data flow is a large buffer pool. The units are indicated as<br />
magenta boxes in Fig. 10.1. They are dubbed ’active buffers’ because the data is not only stored<br />
but potentially also reformatted and reorganized. They are also hand-over points between different<br />
types of networks, thus logically separating them and allowing to use different technologies in<br />
CNet, BNet, and PNet.<br />
• Build Network (BNet): The data arrives from the <strong>de</strong>tector in about 10 3 parallel streams, each<br />
reflecting a small section of a <strong>de</strong>tector sub-system. For the event selection processing, the information<br />
of an event has to be assembled in a farm no<strong>de</strong>. This data reorganization is performed by<br />
the build network and the active buffers.<br />
In a conventional system, a trigger already <strong>de</strong>fines the context of an event, so all further data<br />
processing and transport can be organized in terms of events starting at the FEE. In our case, the<br />
FEE sends a stream of time-stamped hits, and it is one of the tasks of the data processing, to first<br />
i<strong>de</strong>ntify at what times interactions occur, and in a second step, to associate the hits with those<br />
events.<br />
This event tagging processing can be done before or after data traverses the BNet. In the first<br />
case, event tagging is handled in the active buffers, and the entities being assembled in the BNet<br />
transfers are in<strong>de</strong>ed events. In the second case, only the timestamp information is available, and it<br />
is thus natural to assemble all the data of a time interval.<br />
A strict event-by-event approach would lead at the nominal Au+Au interaction rate of 10 MHz to<br />
a message rate of 10 10 messages per second with an average message size of 100 Bytes. However,<br />
because the transfer latency is uncritical, it is possible to choose a bigger dispatching unit, either<br />
an interval of events, or in the simplest case, a time interval containing a significant number of<br />
events. This aggregation reduces the message rate, increases message size, and because event
240 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
size fluctuations average out, also yields a more uniform message size distribution. A reasonable<br />
choice is an event interval of about 100 events or equivalently a time interval in the or<strong>de</strong>r of 10 µs,<br />
which also matches well with the anticipated frame times of a MAPS <strong>de</strong>tector system.<br />
The simplest solution is a time interval based build logic with a shaping and traffic scheduling<br />
setup similar to the one <strong>de</strong>veloped for the LHCb first level trigger [195]. A more involved solution,<br />
which supports building event intervals and the suppression of event incoherent backgrounds, is<br />
<strong>de</strong>scribed in section 10.3.1.<br />
Fig. 10.1 indicates that source as well as <strong>de</strong>stination of a BNet transfer is an active buffer. They<br />
implement the protocol used on the BNet and are responsible for organization of the data flow, in<br />
particular for traffic shaping and appropriate scheduling of transfers. Because the actual traffic seen<br />
by the BNet can be controlled to a large <strong>de</strong>gree and adapted to a given networking technology, it is<br />
assumed that the BNet can be based on a commercial off-the-shelf (COTS) technology. Plausible<br />
candidates are Ethernet, Infiniband, or ASI.<br />
Fig. 10.1 only indicates the logical data flow, not a concrete network topology. For one, it is<br />
possible to factorize the network in several ways, which allows to build the BNet with a set<br />
of medium-sized switches and thus to exploit the usually significantly better price/port ratio of<br />
smaller switches. Also, it is possible to merge the functionality of the two active buffer layers, one<br />
interfacing CNet to Bnet and one interfacing BNet to PNet, into a single entity, leading to a system<br />
with half as many BNet ports and bidirectional traffic on all BNet links. Last but not least, the star<br />
topology with centralized switches can be replaced with other structures, like a 2D- or 3D-torus<br />
topology with distributed switches.<br />
• Processing Resources: The first level of event selection processing has to handle the full event<br />
rate, and <strong>de</strong>pending how many <strong>de</strong>tector sub-systems are involved in the <strong>de</strong>cision, a substantial fraction<br />
of the total data volume. A very rough estimate shows, that processing a data flow on the scale<br />
of a TByte/sec is likely to require a computational bandwidth on the scale of 10 15 operations/sec.<br />
With todays technology, the most promising approach is a hybrid system using a combination of<br />
hardware processors, implemented with programmable logic components like FPGA’s, and software<br />
processors, implemented with commodity PC’s. The kernels of algorithms which allow<br />
highly parallel execution are done in hardware processors, the rest in software processors. The aim<br />
is to execute most of the operations on hardware processors, which offer the best price/performance<br />
ratio for computational bandwidth, but to keep most of the co<strong>de</strong> volume on software processors,<br />
which offer much easier program <strong>de</strong>velopment and maintenance.<br />
Since programmable logic <strong>de</strong>vices are essentially arrays of simple structures, it is expected that<br />
they scale well and thus <strong>de</strong>nsity and speed will improve as the un<strong>de</strong>rlying silicon technology<br />
evolves (see also section 9.10.2). The <strong>de</strong>velopment for software processors over the relevant time<br />
scale till the <strong>de</strong>sign freeze of the CBM data processing is likely to be more complex. The evolution<br />
of single processor speed has reached apparent limits of complexity and power dissipation, calling<br />
for changes in concepts and architectures. This trend is already apparent in recent <strong>de</strong>velopments<br />
like the compute ASIC for IBM’s Blue Gene system or the STI cell processor.<br />
It is also expected, that conventional fixed instruction set processor and programmable logic concepts<br />
will be coupled, resulting new forms of configurable computing, like processors with dynamically<br />
adaptable instruction sets. A first product in this emerging segment are for example the<br />
Stretch S5000 series CPUs [200].<br />
Nevertheless, the rest of this chapter is formulated in terms of physically separated hardware and<br />
software processors because these are the mainstream products available today and the near future.<br />
The overall architecture is, however, easily adaptable to more integrated forms of configurable<br />
computing.
10.3. Communication and Processing Architecture 241<br />
• Processing Network (PNet): The processing resources are grouped in farm no<strong>de</strong>s. Each farm<br />
no<strong>de</strong> is organized around a local processing network which provi<strong>de</strong>s the communication between<br />
the associated processing resources and active buffers, which act as central data repository and as<br />
gateway to the BNet. The PNet is thus structured into many local networks.<br />
The number of hardware and software processors aggregated to one farm no<strong>de</strong> is <strong>de</strong>termined by the<br />
amount of resources nee<strong>de</strong>d to efficiently handle all the algorithms nee<strong>de</strong>d for an event selection<br />
<strong>de</strong>cision. Each hardware processor will have a <strong>de</strong>dicated configuration to execute a particular<br />
algorithm, a total about a dozen different configurations may be nee<strong>de</strong>d. A rough estimate gives,<br />
that an about equal number of software processors is nee<strong>de</strong>d for a balanced load of the whole<br />
system.<br />
It is expected that the resources of a farm are concentrated in a crate or are at least in close proximity.<br />
The PNet can therefore use technologies <strong>de</strong>signed for short distance interconnects, plausible<br />
candidates are from todays perspective PCIexpress or ASI. As stated already for the BNet,<br />
Fig. 10.1 only indicates the logical data flow, not a concrete network topology. The PNet can be a<br />
homogeneous, single technology, switch based star network as suggested by the figure, but many<br />
other topologies are possible, some are discussed in section 10.3.2.<br />
• High-level Network (HNet): The task of the event selection processing <strong>de</strong>scribed up to now is<br />
to perform a first reduction, similar to the ’level 1 trigger’ in conventional systems. A further<br />
reduction will be nee<strong>de</strong>d to reduce the data volume to a level suitable for archival storage. This<br />
will be handled by a more conventional processing farm (see section 10.6). The HNet provi<strong>de</strong>s the<br />
connection to this high-level computing.<br />
10.3 Communication and Processing Architecture<br />
10.3.1 BNet - Build Strategies<br />
The concentrator modules store the hit data in active buffer modules with functionality data dispatcher.<br />
These modules are then the sen<strong>de</strong>rs into the BNet. At the other si<strong>de</strong> of the BNet are active buffer modules<br />
with functionality event dispatcher. The task of the BNet is logically simple: the data of one event<br />
distributed over all data dispatchers, must be assembled in one event dispatcher for further processing<br />
(see Fig. 10.2). Nearly all experiments of the CBM class have solved this task. The special situation<br />
at CBM is that in the data dispatchers there is no event information yet. One possible method to get<br />
this information is to analyze the multiplicity over time of the silicon trackers. This means that the<br />
multiplicities of the ca. 50 STS concentrator modules (one or two layers of the STS system) must be<br />
summed up per time interval (about 2 ns) in subsequent bins of a multiplicity histogram. The time<br />
interval of an event can then be recognized by multiplicity signatures in this histogram. Each event gets a<br />
unique tag number. The association between event time intervals and tag numbers is called event tagging.<br />
Event tagging is used in the event building mechanism.<br />
It is assumed that a peer to peer connection in a conventional hierarchically switched network can transport<br />
1 Gbyte/s. It has been proven that currently available 10 GE switches are capable to switch full data<br />
rates even with 64 byte packets without loss.<br />
To avoid confusion in the following we mention here that there are two time systems: the intrinsic time<br />
is <strong>de</strong>fined by the time stamps insi<strong>de</strong> the data streams as <strong>de</strong>livered by the TNet. The scheduler time (local<br />
time of the active buffers) specifies when the data dispatchers have to send data to an event dispatcher.<br />
Time intervals in the data stream like epochs refer to the intrinsic time. These intervals can be recognized<br />
in each data channel in<strong>de</strong>pen<strong>de</strong>ntly by the time stamps, i.e. epoch markers. Each data dispatcher can<br />
<strong>de</strong>termine the amount of data belonging to an intrinsic time interval. Intrinsic time intervals are time
242 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
FEE: front end electronics<br />
DD: data dispatcher<br />
HC: histogram collector<br />
BC: BNet controller<br />
ED: event dispatcher<br />
FEE CNet<br />
50000<br />
10<br />
HC BC<br />
1<br />
logical<br />
physical<br />
active buffer active buffer<br />
DD ED<br />
BNet<br />
1000<br />
Figure 10.2: BNet: logical overview.<br />
frames and time slices (sequential set of time frames). The schedule time <strong>de</strong>termines when the data of a<br />
time slice has to be sent (data transfer buffer). The time interval to send this data is called time slot.<br />
10.3.1.1 Two approaches: time frame or event dispatching<br />
The event tagging can be done at two places: behind the BNet (frame switching) or before the BNet<br />
(event switching). In the first case the <strong>de</strong>termination of the data transfer buffers to be distributed through<br />
the network is based on fixed time frames (intrinsic time). A time frame can be recognized by epoch<br />
time stamps in each data stream (variable data size!). Several time frames may be bundled into a time<br />
slice (data transfer buffer) by the BNet-controller (see Fig. 10.3). Because of data duplication at the time<br />
frame boundaries the time slices should be at least some 10 µs (hundreds of events). The full data rate has<br />
to be sent through BNet. However, no communication is nee<strong>de</strong>d for histogramming. The event tagging<br />
and hits association is then done locally in the event dispatchers. The second case - tagging the event<br />
Detector data buffer memory<br />
align<br />
time frame<br />
epoch or tagged events<br />
~ 10 µs<br />
1000<br />
5 frames = 1 time slice<br />
i [Kbytes] sent to one ED<br />
~ 50 µs : 50 Kbyte<br />
Figure 10.3: BNet: data dispatcher: <strong>de</strong>tector data buffer structure.<br />
before switching - opens the chance to reduce the BNet throughput by suppressing background and by<br />
selecting events of a special multiplicity signature. Some of the data dispatchers get the additional task<br />
to generate and summarise the multiplicity histograms. The BNet-controller must <strong>de</strong>termine the event<br />
tags before calculating the schedule.<br />
However, the traffic scheduling is similar in both cases. A <strong>de</strong>cision between frame switching and event<br />
switching cannot be ma<strong>de</strong> in the current phase. Instead, both are investigated in the simulation setups.<br />
From experiment requirements it might turn out that both approaches are nee<strong>de</strong>d for different event<br />
signatures.<br />
PNet
10.3. Communication and Processing Architecture 243<br />
10.3.1.2 Data flow due to event tagging<br />
Let us consi<strong>de</strong>r all kinds of data traffic, which is required to perform event tagging and event building.<br />
Our main approach is to keep all kind of traffic insi<strong>de</strong> BNet. Therefore in the following we give some<br />
calculations about the net load produced by different traffic sources.<br />
The entry point to BNet are data dispatchers, which keep the input stream of (intrinsic) time stamped<br />
hit data coming from the associated concentrator module in <strong>de</strong>tector data buffers. The data dispatchers<br />
corresponding to STS must generate local multiplicity histograms, which should be then summed up to<br />
<strong>de</strong>tect events. One data dispatcher producing histograms with a bin size of 2 ns and 1 byte/bin generates<br />
a data rate of 500 <strong>MB</strong>ytes/s. One can not afford to transport such noncompressed data over the BNet.<br />
But such local multiplicity histogram will have a lot of empty bins. Therefore, such histogram can be<br />
efficiently compressed down to an outgoing data flow of 100 <strong>MB</strong>ytes/s per data dispatcher.<br />
It is not plausible to send all compressed histograms from 50 data dispatchers to one single end point.<br />
Therefore additional histogram collectors should be used to combine intermediate sum histograms from<br />
5-8 data dispatchers. About 7-10 histogram collectors will be required. Histograms from each histogram<br />
collector should be <strong>de</strong>livered to one end point, called tag generator. These histograms may not be compressed<br />
so efficiently as individual ones. Therefore another compression approach can be consi<strong>de</strong>red. In<br />
such intermediate sum histograms one expects more clear peaks, corresponding to single events. Therefore<br />
a histogram collector can locate these peaks and transfer them to the BNet-controller. One expects<br />
not more than 1.5 peaks per event or about 60 Mbyte/s data rate (supposing 4 bytes/peak in average).<br />
The tag generator should get peak information from all 7-10 histogram collectors and produce event tags.<br />
Each event will be <strong>de</strong>fined by short time interval of several ns, where the STS multiplicity is above some<br />
threshold. Time shifts between subsystems must be taken into account. Each event gets its individual<br />
tag, which will be used in event building scheme.<br />
The event tagging approach implies that not individual event fragments, but rather groups of subsequent<br />
event fragments (event groups) should be dispatched in the BNet during data transfer. Based on event<br />
multiplicities the BNet-controller can balance the size of <strong>de</strong>fined event groups. Such grouping should<br />
reduce the size variation of the data transfer buffers dispatched in the BNet.<br />
Once events are tagged and event groups are <strong>de</strong>fined, the corresponding information should be distributed<br />
to all data dispatchers. Each event requires about 2 bytes for coding which results in about 20-30<br />
<strong>MB</strong>ytes/s from the BNet-controller broadcast into the BNet. That results in about 30 GByte/s traffic at<br />
the end no<strong>de</strong>s (data dispatchers).<br />
When the data dispatcher has received the event tagging information it selects by the time stamps appropriate<br />
data pieces from the input buffer. At that moment most of noise hits and non interesting events can<br />
be thrown away and only sorted data (which is smaller in size) is kept in the <strong>de</strong>tector data buffers.<br />
10.3.1.3 Data flow due to scheduling<br />
The main task of the BNet-controller is to balance the data transfer of the network and utilize full bandwidth<br />
of peer to peer connections. The BNet-controller should know the exact sizes of data packets to be<br />
transferred from data dispatchers to event dispatchers. Therefore, after data dispatchers produced sorted<br />
data for event groups, data sizes for each group of events should be send to BNet-controller. One expects<br />
about 10 5 groups/s producing 200 KBytes/s of information traffic sent by each data dispatcher and about<br />
200 <strong>MB</strong>ytes/s received by the BNet-controller.<br />
Based on the received information about the event group sizes, the BNet-controller produces a schedule,<br />
which prevents conjunction, blocking, or data loss in the BNet. The schedule inclu<strong>de</strong>s the exact sequence<br />
of transactions for each data dispatcher, synchronized by time slots (scheduler time). The schedule will
244 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
be <strong>de</strong>scribed in the following in more <strong>de</strong>tail. Once the schedule is produced, it must be distributed to all<br />
data dispatchers. This is done in two phases. In the first phase the individual schedule is transferred to<br />
each data dispatcher producing about 200 KBytes/s resulting in a total of 200 <strong>MB</strong>ytes/s outgoing from<br />
the BNet-controller.<br />
In the second phase the schedule timing information (scheduler time, about 200 KByte/s) is broadcast to<br />
all data dispatchers. This portion inclu<strong>de</strong>s timing, when each transaction in schedule should be started.<br />
This schedule timing information is distributed right before the schedule can be executed.<br />
10.3.1.4 Data flow summary<br />
During schedule execution each data dispatcher according to its individual schedule sequence sends<br />
data packets to an event dispatcher, compressed histograms (if required) to a histogram collector, or data<br />
packets information to the BNet-controller. At the same time a data dispatcher may receive event tagging<br />
data and schedule for the next transactions. Table 10.1 shows a short summary of all traffic in the system.<br />
Traffic type Sen<strong>de</strong>r Receiver Sen<strong>de</strong>r Receiver Total<br />
Single histograms data dispatcher histogram collector 0.1 0.7 5.0<br />
Peak data histogram collector tag generator 0.1 0.8 0.8<br />
Tagging brdcst BNet-controller data dispatcher 0.03 0.03 30.0<br />
Size information data dispatcher BNet-controller 0.0002 0.2 0.2<br />
Sched. <strong>de</strong>stinations BNet-controller data dispatcher 0.2 0.0002 0.2<br />
Sched.timing brdcst BNet-controller data dispatcher 0.0002 0.0002 0.2<br />
Data transfer data dispatcher event dispatcher 0.9 0.9 900<br />
Table 10.1: List of traffic types in the system and data rates (in GBytes/s).<br />
It can be seen, that the sum of all meta data traffic is only a few percent of the main data traffic. Therefore<br />
it seems to be promising to <strong>de</strong>velop a mechanism to mix all kind of traffic in one common network. The<br />
intention is to keep all traffic types insi<strong>de</strong> BNet to reduce construction cost.<br />
10.3.1.5 Time frame switching<br />
This mo<strong>de</strong> will be required, when event tagging via multiplicity histograms is not possible, i.e. when<br />
events have a very low multiplicity, or when the event rate is too high. In that case not a group of events,<br />
but intrinsic time frames will compose a time slice to be dispatched into the BNet. This mo<strong>de</strong> can be<br />
supported with very slight modifications of the scheme proposed so far.<br />
First of all, histogramming can be kept as it is, but the histogram bins can be increased from 2 ns to 100-<br />
200 ns scaling down the size. The histogram is not used for peak <strong>de</strong>tection but rather to get a guess about<br />
the data size of the time slice. The tag generator obtains a histogram over 50 STS channels which shows<br />
the average hit <strong>de</strong>nsity over a certain time interval. From that histogram the tag generator can produce<br />
variable time slices to balance the average data size of the slices. By the same method, as event tags,<br />
time slice <strong>de</strong>finitions can be distributed to the data dispatchers. There the correspon<strong>de</strong>nt data packets can<br />
be produced. From that point on the remaining schedule sequence, which inclu<strong>de</strong>s info traffic, schedule<br />
distribution and schedule execution algorithms is the same. Instead of an event group i<strong>de</strong>ntifier a time<br />
slice i<strong>de</strong>ntifier is in the schedule. Finally, the event dispatcher modules should execute in this mo<strong>de</strong> an<br />
additional algorithm to tag events (if it will be possible). Most probably, such modified scheme can run<br />
on the same hardware. Only another version of software, running on data dispatcher and event dispatcher,
10.3. Communication and Processing Architecture 245<br />
should be used.<br />
10.3.1.6 Network topology<br />
The BNet should provi<strong>de</strong> full connectivity between 1000 data dispatchers and 1000 event dispatchers.<br />
For the implementation of a logical 1000x1000 switch several approaches are possible. We intend to<br />
use the network bidirectional to reduce the number of components and final cost. For that one has to<br />
combine the data dispatchers (mainly source of data traffic) and the event dispatchers (consumer of data<br />
traffic) on the same <strong>de</strong>vice (active buffer) marked as DD/ED in Fig. 10.4. Then they can share one I/O<br />
port, connected to BNet.<br />
The logical 1000x1000 switch should be factorized. As one possibility the principle of a star topology<br />
is shown in Fig. 10.4. The n ’outer’ ports of the switches are connected to active buffer modules<br />
(DD/ED). The ’inner’ n-1 ports connect the switch with the other n-1 switches. As a result n*(n-1)/2<br />
interconnections between switches are required.<br />
For example: n=8 means that 64 data channels can be implemented and 28 interconnection are required.<br />
For n=32, 1024 channels can be implemented and 496 interconnection are required. One 32x32 switch<br />
could again be split into 12 6x6 switches for cost reasons, resulting in 384 switches. This case, however,<br />
introduces more layers in the hierarchy and needs further investigation.<br />
CNet<br />
n -1 ports<br />
HC/DD<br />
n * (n -1) / 2 bidirectional connections<br />
TG/BC<br />
BNet controller<br />
n<br />
switch n × n •• • • switch n × n<br />
n -1 ports<br />
•• • •• • • n<br />
n -1 H: histogrammer<br />
TG: event tagger<br />
DD/ED<br />
HC: histogram collector<br />
CNet<br />
H<br />
PNet<br />
BC: scheduler<br />
DD: data dispatcher<br />
ED: event dispatcher<br />
Figure 10.4: BNet: logical star topology.<br />
10.3.1.7 The data dispatcher / event dispatcher module<br />
DD/ED<br />
active buffer<br />
CNet PNet<br />
The combination of data dispatcher and event dispatcher in one active buffer module allows to fully utilize<br />
the I/O channel connected to the BNet. The active buffer has one input channel from the concentrator<br />
module and one output channel to the event processing net (PNet). The main functions of such active<br />
buffers are: buffering of input data, resorting data to event groups (data transfer buffers), sending data<br />
and info packets according provi<strong>de</strong>d schedule, and receiving and combining data for event groups.<br />
The active buffer also should inclu<strong>de</strong> a functional block to accumulate the local histogram (letter H in<br />
Fig. 10.4) when the data dispatcher is assigned to an STS data channel. For other modules this part can<br />
be <strong>de</strong>activated.
246 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
The proposed scheme of event tagging requires another function block, the histogram collector. One<br />
possible approach is to build it as in<strong>de</strong>pen<strong>de</strong>nt <strong>de</strong>vice. Another approach is to implement the functionality<br />
of a histogram collector on the event dispatcher part of our combined module. It means, that several (up<br />
to 8) active buffers in the system will not perform event building, but will combine histograms over<br />
several STS data channels. Therefore such DD/HC modules will not be event dispatchers.<br />
10.3.1.8 BNet-controller module<br />
As it is shown on the network scheme in Fig. 10.4, this module will have two connections to BNet. One<br />
of these connections will be used to receive data from the histogram collectors, the other will be used to<br />
receive information data from DD/ED modules and distribute scheduling packets back.<br />
The BNet-controller contains two functional parts, which are mostly in<strong>de</strong>pen<strong>de</strong>nt: event tagging and<br />
schedule production. The first task is relatively simple and only requires, that peak data is <strong>de</strong>livered<br />
continuously from the histogram collectors. The major and most <strong>de</strong>manding task is to produce the<br />
schedule, which guarantees a smooth transfer not only of event data, but also of all other meta data<br />
distributed over the system.<br />
The scheduler knows a priori how many data has to be transferred from every source in the system.<br />
Therefore it can assign the appropriate time for the transfer to avoid collisions in the network switches<br />
and overruns of pipelines. The scheduler also assigns some time slots (holes) in the main data traffic,<br />
which are used for different kinds of metadata transfer.<br />
10.3.1.9 Traffic shaping and schedule<br />
Let us consi<strong>de</strong>r one particular setup and discuss different aspects of the schedule. When events are<br />
tagged, they are combined into groups. Most probably a single group of events will inclu<strong>de</strong> about 500<br />
events, covering about 50 µs of intrinsic time, which we call time slice as shown in Fig. 10.3. One<br />
expects about 50 KBytes of data, which can be assigned in each data dispatcher to that group. Data at<br />
the group boundaries may be assigned to the two subsequent groups. All this data (50 KByte over 1000<br />
data dispatchers results in 50 <strong>MB</strong>ytes) should be finally collected in one single event dispatcher, where<br />
full events can be build.<br />
At any (scheduler) time all data dispatchers should send data but only one data dispatcher should <strong>de</strong>liver<br />
data to one event dispatcher, where the events of the specific group are built. Therefore one needs at<br />
least the data of 1000 (intrinsic) time slices to start the <strong>de</strong>livery of data from all 1000 data dispatchers<br />
simultaneously.<br />
The time to <strong>de</strong>liver all data of a single schedule is called super cycle. One super cycle which in our<br />
case is about 50 ms intrinsic time (from 1000 time slices or event groups of about 50 µs) covers the full<br />
schedule for all data dispatchers to <strong>de</strong>liver data to all event dispatchers. The scheduler time interval to<br />
send the data of one intrinsic time slice is called time slot.<br />
At each time slot the scheduler assigns a reciever for each data dispatcher in such way, that the produced<br />
traffic will not overlap in the network. For example, if a data dispatcher connected to switch number 1 is<br />
sending data to an event dispatcher connected to switch number 2 no other data dispatcher connected to<br />
switch 1 will be scheduled to send data to any event dispatcher connected to switch 2. This condition is<br />
a result of the single connection line between switch number 1 and switch number 2. The schedule must<br />
always fulfill that condition.<br />
In such approach all data dispatchers should finish their data transfer during one time slot before the next<br />
time slot can be started. Therefore, if packets sizes vary, most of data dispatchers sending smaller data
10.3. Communication and Processing Architecture 247<br />
packets will be silent while the biggest data packet is injected in the net. In the extreme situation, when<br />
the packet sizes vary by about 50 %, the data throughput will slow down by factor of 2 or even more as<br />
can be seen in Fig. 10.5. For that case an optimized sorted schedule can be generated. It tries to transfer<br />
data of approximately the same size at the same time slot. Intensive calculations are required to produce<br />
such a schedule, but it allows to keep the utilization of the network above 90 % even if the variation of<br />
packet sizes exceeds 50 %.<br />
Network utilization [%]<br />
100<br />
90<br />
80<br />
70<br />
60<br />
50<br />
40<br />
Network utilization by different schedule methods<br />
sorted<br />
not sorted<br />
0 10 20 30 40 50<br />
Buffer size variation [% of data size]<br />
Figure 10.5: BNet: Optimization of data dispatching.<br />
The data transfer in each time slot is divi<strong>de</strong>d into small transfer units of fixed size to produce a payload<br />
equilibrium in the network. The transfer unit size could be about 1.5K, which is an upper limit for current<br />
standard for Ethernet. In our case one time slot is divi<strong>de</strong>d into about 30 transfer units, which should be<br />
<strong>de</strong>livered to one <strong>de</strong>stination.<br />
Of course, such schedule requires, that the data transfers should be very well synchronized across the<br />
BNet. All data dispatchers must have a good synchronisation of a system clock. At least a precision<br />
of µs should be achieved. Such a system clock could be <strong>de</strong>rived from the concentrator’s data channel,<br />
because the concentrators will be connected to the time distribution system with a time presison of some<br />
ns. Another possibility is to provi<strong>de</strong> a <strong>de</strong>dicated time distribution system connecting all data dispatchers.<br />
A precision of one or even several µs should be good enough. For this overlapping time the data must<br />
be stored insi<strong>de</strong> the switch. Current 10 GE switches with a latency of about 20 µs at 1KByte packet size<br />
can <strong>de</strong>liver the full data rate. This means that they can buffer a significant number of packets in internal<br />
memory before the packets are <strong>de</strong>livered to the output. Therefore an uncertainty in sending time between<br />
data dispatchers can be smoothed by the internal switch buffers. An overlap of 1 µs results in one more<br />
packet of 1 KByte size to be additionally buffered in the switch, while the switch already keeps at least<br />
20 packets of the same size because of latency constraints.<br />
During a time slot of 50 µs a maximum of 33 packets of 1.5 KByte can be sent. Normally all these<br />
packets should be used to send data from data dispatcher to event dispatcher. But in certain situations the<br />
scheduler marks some of these packets not to be used (assigned as holes) allowing to transfer meta data in<br />
different directions synchronized with the main traffic. Depending on the kind of traffic (histogramming,<br />
information, scheduling) different algorithms how such holes should be distributed are used. For a single<br />
data dispatcher in every time slot not more than 15 % of holes are nee<strong>de</strong>d. In the overall system only
248 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
about 1-2 % of holes are required to distribute the meta data.<br />
Let us consi<strong>de</strong>r the situation of histogramming traffic. One needs to <strong>de</strong>liver about 100 <strong>MB</strong>ytes/s from<br />
a data dispatcher building a local histogram to a certain histogram collector. While these <strong>de</strong>vices are<br />
connected to the same switch, the data dispatcher can send the compressed histogram to the histogram<br />
collector at the time, when a hole in the main data traffic is scheduled. The only task of the scheduler is<br />
to distribute holes in such way, that the histogramming traffic is not crossing at the receiver (histogram<br />
collector) si<strong>de</strong>.<br />
A different approach is used, when information data should be <strong>de</strong>livered from a data dispatcher over the<br />
whole BNet to the BNet-controller. In that case the scheduler assigns a hole in the data traffic of those<br />
data dispatchers which are sending data into an event dispatcher connected to the same switch, where<br />
the BNet-controller port is connected. Then this hole will be used for information data. All packets (data<br />
and meta data) from that data dispatcher will travel over the BNet together up to the last switch, where<br />
they will be split by address selection (data to event dispatcher, meta data to BNet-controller).<br />
10.3.1.10 Simulation of event buidling<br />
Using the SystemC simulation package (http://<strong>www</strong>.systemc.org) several mo<strong>de</strong>ls have been set up to simulate<br />
and investigate the performance of the <strong>de</strong>scribed setup. The simulation inclu<strong>de</strong>s function mo<strong>de</strong>ls<br />
for components like data dispatcher, histogram collector, tag generator, BNet-controller, and event dispatcher.<br />
Connectivity between the modules is mo<strong>de</strong>led with a special interface module (simulates piece<br />
of wire), which inclu<strong>de</strong>s propagation speed and data transfer rate. Mo<strong>de</strong>ls for network switches with<br />
limited buffer capacity were also introduced. A full algorithm for schedule building was implemented.<br />
A setup with 100 end no<strong>de</strong>s (DD/ED modules) was tested. Histogramming for event tagging was done<br />
over 16 channels. A time slot of 3 µs was used. The super cycle size was about 300 µs. A simulation for<br />
10 ms, which inclu<strong>de</strong>s about 30 super cycles, takes about 25 minutes on an Athlon 1800+ XP computer.<br />
Each time slot was divi<strong>de</strong>d on 7 packets of about 450 bytes. The event generator provi<strong>de</strong>s a mixture<br />
of events and uncorrelated noise. A sustained bandwidth utilization of 79% (netto) for data traffic was<br />
achieved. At the same time the overall occupancy of the network connections between the switches was<br />
greater than 90%.<br />
Our simulation shows that the latency of event tagging (the time between event hit <strong>de</strong>tection and event<br />
tag production in the tag generator) is negligibly small. In the tested setup it was only about 15 µs. The<br />
latency of event building (the time between event hit <strong>de</strong>tection and event combination in event dispatcher)<br />
was about 1 ms, which is roughly the duration of 3 supercycles. For that time period event data must be<br />
kept in the <strong>de</strong>tector data buffer of data dispatchers. In a realistic setup with a supercycle size of 50 ms a<br />
buffer <strong>de</strong>pth of 150 <strong>MB</strong>ytes per data dispatcher will be required.<br />
10.3.1.11 MAPS problematic for event buidling<br />
The MAPS is read out continuously with a cycle of about 10 µs (see 2.2.3). That means that up to 200<br />
events are distributed in two subsequent MAPS frames, i.e. the event data is not in time or<strong>de</strong>r. Therefore<br />
tagged event fragments of the other channels have to be combined for event building with event fragments<br />
of at least two MAPS frames. When event fragments are dispatched to an event dispatcher the full MAPS<br />
frames must <strong>de</strong> sent to this event dispatcher too, i.e. the MAPS frames must be copied and sent to several<br />
event dispatchers. For small event groups, which cover about 10 µs, one has to duplicate at least 3 MAPS<br />
frames. This will populate MAPS traffic by factor of 3 and overall data traffic by 20%. But for realistic<br />
setup, when a group covers 50 µs, only two boundary MAPS frames will be duplicated and overall traffic<br />
increase will be only about 5%.
10.3. Communication and Processing Architecture 249<br />
10.3.1.12 Broadcast problematic in BNet<br />
The main problem of broadcast is the generation of traffic simultaneously on a big number of receiving<br />
no<strong>de</strong>s, exploding traffic over the net. If there is any other traffic distributed at the same time the broadcast<br />
immediately causes collisions and loss of packets. However, in BNet all traffic is controlled by the BNetcontroller.<br />
By proper schedule timing the BNet-controller can provi<strong>de</strong> <strong>de</strong>lays between transactions, in<br />
which none of the no<strong>de</strong>s in the system will send any data. During such <strong>de</strong>lays broadcast packets can<br />
be injected in the BNet. As long as there are no other transactions in the net, broadcast packets can<br />
be smoothly <strong>de</strong>livered to all end no<strong>de</strong>s. The total sum of broadcast traffic, going out of the BNetcontroller<br />
should not exceed 30 <strong>MB</strong>ytes/s or 3% of the avaliable bandwidth. Therefore one needs only a<br />
few <strong>de</strong>lays in every schedule, which sum up to about 3% of a supercycle.<br />
It has to be proven that the network technology used to construct the BNet will provi<strong>de</strong> a reliable multicast<br />
(broadcast) mechanism at least when no other kind of traffic is going on. If this cannot be achieved,<br />
a two stage peer to peer connection should be used to implement broadcast. A single source can populate<br />
traffic only between about 30 endno<strong>de</strong>s. One would need one additional module per 32 data dispatchers<br />
to distribute such "broadcast" data. This module can be connected to one spare port, left in each switch.<br />
All these 32 distribution modules should have a separate connection to the BNet-controller to get data,<br />
which should be broadcast. Such approach requires additional hardware, but exclu<strong>de</strong>s any broadcast in<br />
the BNet.<br />
10.3.1.13 Flow control and error <strong>de</strong>tection<br />
All previous estimations were done with the assumption that the un<strong>de</strong>rlaying network protocols guarantee<br />
<strong>de</strong>livery of packets sent over the BNet. But one can also impose error <strong>de</strong>tection for several kinds of traffic.<br />
Most of the network bandwidth will be used for data transfer. Therefore most probably data packets can<br />
be lost. For that case an easy, but efficient error <strong>de</strong>tection can be proposed. In the same manner, as each<br />
data dispatcher gets its schedule about the data to be sent, each event dispatcher can get a schedule about<br />
data to be <strong>de</strong>livered to it. The event dispatcher can time out after several µs when the announced packets<br />
did not arrive. Error <strong>de</strong>tection information can be <strong>de</strong>livered with other info traffic to the BNet-controller.<br />
Later lost packets can be rescheduled again.<br />
A similar approach can be applied for the traffic going to/from the BNet-controller. It knows exactly<br />
which module should send data to it and when. Thereforfe it can <strong>de</strong>tect lost packets.<br />
Generally, error <strong>de</strong>tection can be implemented for all kind of traffic, but this may increase complexity of<br />
the system. Therefore, further investigations of transaction error probability and required error correction<br />
mechanisms should be done.<br />
10.3.2 First Level Farm Strategies<br />
In this section we give a motivation for the size of the first level farm system together with a <strong>de</strong>scription<br />
of one processor sub-farm. We show the principle function and the implementation of the components<br />
of a sub-farm.<br />
The <strong>de</strong>tector outputs about 1 Tbyte/s of data via about 1,000 10 Gbit/s links. These data is stored, sorted<br />
according to epoches during their transfer through the building network, and stored again. Finally it is<br />
processed event by event. The storing and the processing is the main part of the function of the first<br />
level farm. A reasonable time for one epoch is a multiple of the MAPS readout time, that is in the<br />
or<strong>de</strong>r of 10 µs. To get all the readout frames of the MAPS <strong>de</strong>tector that belong to one certain time it is<br />
necessary to merge data from two epochs. That’s why each sub-farm should contain the storage capacity
250 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
and processing power for several epochs, to minimize the additional data traffic. A reasonable number<br />
of sub-farms is between 64 and 128. Each sub-farm has to store and process data from 8 to 16 input<br />
links, what corresponds to 8 to 16 epochs, respectively. So only every eighth to sixteenth epoch has to be<br />
copied in two sub-farms. Of course these numbers are only typical values to show the feasibility of a later<br />
realization. In particular it is a special feature of this architecture that it is very flexible and adaptable to<br />
many different requirements.<br />
The size of the sub-farms needs not to be the same, it does not require the same type and amount of<br />
processors nor the same composite of them in the different sub-farms. This has many advantages, e.g.<br />
during commissioning, maintenance, update and running of the experiment. During start-up and commissioning<br />
sub-farms with general purpose processors, later on called software processors (L1/CPU),<br />
and other COTS components are used. Of course the processing power is reduced, but it offers a maximum<br />
of flexibility by testing and <strong>de</strong>bugging all <strong>de</strong>tector and front end problems by software. In a second<br />
step these sub-farms are expan<strong>de</strong>d by special purpose hardware processor units (L1/FPGA) to speedup<br />
the processing. For maintenance during the running experiment or for an upgra<strong>de</strong> of parts of the system,<br />
individual sub-farms or parts of them can be switched off and replaced by loosing only one to two percent<br />
of processing power. Of course the L1/CPUs and networks are most probable COTS components, where<br />
the bulk is bought at the latest date. So the L1/CPUs of the sub-farms installed first may be different<br />
from the ones used finally. For the L1/FPGAs proprietary <strong>de</strong>velopment is necessary.<br />
HLT physical analysis C++, Framework, GEANT<br />
L1/CPU physical analysis, C++, Framework, GEANT<br />
event selection<br />
L1/FPGA event selection C++, Verilog, VHDL<br />
Figure 10.6: Levels of software generations.<br />
Different levels of event selection will implement different algorithms according to required data reduction<br />
and hardware implementation (Fig. 10.6). Nevertheless all levels must be algorithmically compatible.<br />
The algorithms have to run within the framework being mutually replaceable 1 to make possible<br />
implementation of the same well tested and efficient algorithm in all levels, or to <strong>de</strong>velop and monitor an<br />
algorithm which can be applicable only for a specific level of data selection.<br />
The time nee<strong>de</strong>d for processing algorithms for event selection using general purpose processors in GHz<br />
PCs, as usual today, is in the or<strong>de</strong>r of several hundreds milliseconds to several seconds, <strong>de</strong>pending on<br />
the complexity of the algorithm and track multiplicity of an event. Due to increases in processing and<br />
integration technology a speedup of 50 to 100 is expected within the next 8 to 10 years. The processing<br />
time will shrink to a few milliseconds up to some tenth of milliseconds per event. But still an event rate<br />
of 10 MHz would require a total of 10,000 to 100,000 processors per algorithm. Even when divi<strong>de</strong>d into<br />
sub-farms, a realistic and reasonable size of a computer farm is about a factor 100 smaller.<br />
One solution to speedup algorithms is the coprocessing in FPGAs (field programmable gate arrays).<br />
According to Amdahls law about 99% of the algorithm has to be accelerated by hardware maximally to<br />
get a speedup factor of 100. This means that only one percent stays in software, that is most probable<br />
just the controlling of the algorithm.<br />
The task is to implement the required computing power and communication bandwidth at affordable cost.<br />
In or<strong>de</strong>r to meet this challenge one has to optimize the analysis algorithms and to execute them according<br />
to their computational and data access characteristics on the most effective compute architecture. Both<br />
the relevant computing and communication technology showed an extraordinary <strong>de</strong>velopment during the<br />
last years which is expected to continue over the time-scale of the project.<br />
1 This must be valid at least for their C++ versions.
10.3. Communication and Processing Architecture 251<br />
The most reasonable technology for the implementation of L1/FPGAs are reconfigurable logic <strong>de</strong>vices<br />
like FPGAs. The FPGA technology gains the maximum benefit from the <strong>de</strong>velopment in the chip industry.<br />
Because of their very regular internal structure FPGAs are, besi<strong>de</strong>s RAMs, the first chips that can be<br />
built in new technologies. General purpose processors are following later due to their higher complexity.<br />
It can be expected that FPGAs with a capacity well above 100k logic cells and clock rates in excess of<br />
500 MHz will become available at commodity prices towards the end of the time frame. This will allow<br />
to implement the complex algorithms nee<strong>de</strong>d for event selection in FPGAs.<br />
Additionally to the logical resources mo<strong>de</strong>rn FPGAs also offer up to 20 10 Gbit/s serial I/O (SERDES) in<br />
silicon, together with embed<strong>de</strong>d processors for monitoring, test and control. 10 Gbit/s links over optical<br />
or copper interconnects as well as the associated switching hardware are expected at affordable prices in<br />
the next few years.<br />
Scheduler<br />
Scheduler<br />
-Farm Farm<br />
L1/FPGA<br />
L1/CPU<br />
L1/FPGA<br />
L1/CPU<br />
L1/FPGA<br />
Detector<br />
L1/CPU<br />
AB<br />
PNet<br />
L1/CPU<br />
BNet<br />
Sub-Farm Sub Farm<br />
A sub-farm (Fig. 10.7) consists of different units.<br />
L1/FPGA<br />
L1/FPGA<br />
L1/CPU<br />
L1/FPGA<br />
L1/CPU<br />
L1/FPGA<br />
Detector<br />
L1/CPU<br />
AB<br />
L1/CPU<br />
BNet<br />
Sub-Farm Sub Farm<br />
L1/FPGA<br />
L1/FPGA<br />
L1/CPU<br />
L1/FPGA<br />
L1/CPU<br />
L1/FPGA<br />
L1/CPU<br />
AB<br />
PNet PNet<br />
Figure 10.7: General structure of a sub-farm<br />
Detector<br />
L1/CPU<br />
BNet<br />
Sub-Farm Sub Farm<br />
L1/FPGA<br />
L1/FPGA<br />
L1/CPU<br />
Farm<br />
Control System<br />
1. Active Buffer (AB): An AB is the interface between the <strong>de</strong>tector link, the Built network (BNet)<br />
and the processor sub-farm network (PNet). Additional to the input/output of data from different<br />
networks, it has to store the data, and to process the event building. An AB can be split into three<br />
functions. First, it has to store the data coming from the 50 m to 100 m <strong>de</strong>tector link and to output<br />
to the BNet. Second, it has to receive the sorted data according to epoches from the BNet and to<br />
store and output them event by event to the processors of the sub-farm. Before or after this second<br />
step it calculates a histogram of the timestamps of the data for the event building. Peaks in this<br />
histogram give the time of an event. The <strong>de</strong>tectors with the best time resolution <strong>de</strong>termine the<br />
exact time. Finally, it sends the sub-<strong>de</strong>tector data from one event to the processing units. In this<br />
sense the AB also controls the processing resources of a sub-farm.<br />
The ABs are implemented using FPGAs for the processing of the data transfer protocols, the<br />
histogramming, and the control of an external memory for the data storage.<br />
2. Hardware Processors (L1/FPGA): In these units the algorithms nee<strong>de</strong>d for the first level event<br />
filtering are processed. To keep pace with the high <strong>de</strong>tector event rate of 10 MHz these algorithms<br />
are implemented directly in hardware. As <strong>de</strong>scribed earlier FPGAs are the obvious choice for<br />
this task. FPGAs combine the advantage of the flexibility of programming with the processing<br />
of an algorithm directly in a parallel hardware processor. The complexity of the FPGAs and the<br />
L1/FPGA<br />
L1/CPU
252 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
resulting system will be chosen in a way, that it is possible to process an input data stream from<br />
the network (e.g. 10 Gbit/s) in real time and implement an enclosed part or the entire algorithm in<br />
one L1/FPGA. On the other si<strong>de</strong> the system has to be modular to connect the different algorithms<br />
to one event filter. Of course, the system has to be flexible enough to implement different types of<br />
algorithms according to the physical program of the experiment.<br />
3. Software Processors (L1/CPU): These units consist of general purpose processors like PCs or<br />
system-on-a-chip processors (SoC), possibly using L1/FPGAs as coprocessors. Most probable<br />
these processors will be COTS components.<br />
The L1/CPUs are used to process data from sub-<strong>de</strong>tectors for a more accurate analysis at the end<br />
of the first and in the second filtering level. Additionally it is used to process global algorithms for<br />
high level filtering. The L1/CPUs integrated in the first level farm are the interface to the higher<br />
level and off-line farm and to the data archive.<br />
4. Processor Farm Network (PNet). The PNet connects the ABs, the L1/FPGAs and the L1/CPUs of<br />
one sub-farm. It has to be freely programmable although for a fixed algorithm only fixed pointto-point<br />
connections are necessary. The connections are only insi<strong>de</strong> of one sub-farm, e.g. chip-tochip<br />
and board-to-board links with short distances (< 1 m). Especially, there is no dynamically fast<br />
switching all-to-all network nee<strong>de</strong>d, like the BNet. The bandwidth of a link should be in the or<strong>de</strong>r<br />
of 10 Gbit/s, because this is the planned on-line processing rate for the L1/FPGAs. Best choice<br />
for PNet is to use the build-in serial links in FPGAs and processor systems and connect them with<br />
COTS switches. PCIe-AS is a plausible candidate for a commonly used serial interconnect and<br />
thus for PNet.<br />
5. Network to high level and off-line farm: Most probable this network will be what is called Ethernet<br />
in 10 years. An expected data output rate is about 1 GByte/s per subfarm.<br />
10.3.2.1 System architecture<br />
The 10 MHz event rate is nee<strong>de</strong>d for the <strong>de</strong>sired physical performance of D and J/ψ measurements. For<br />
the research concerning low-mass di-leptons and multi-strange baryons a minimum bias readout of 20k<br />
events per second, that is equivalent with an 1 GByte/s output rate of the first level farm, gives sufficient<br />
sensitivity. So the processing of D and J/ψ <strong>de</strong>termines the system architecture of the first level farm.<br />
M1<br />
M2<br />
S1<br />
S2<br />
S3<br />
S4<br />
S5<br />
RICH<br />
D<br />
J/ψ J/<br />
TRD, ECAL<br />
Figure 10.8: Filtering<br />
strategy for two different<br />
event types
10.3. Communication and Processing Architecture 253<br />
For the processing of <strong>de</strong>cays of D-mesons tracks have to be reconstructed from the STS <strong>de</strong>tector data<br />
in or<strong>de</strong>r to <strong>de</strong>termine the primary vertex. Then all candidates for secondary tracks have to be combined<br />
to <strong>de</strong>termine the invariant mass with an assumed particle i<strong>de</strong>ntity. As the primary event rate is 10 MHz<br />
the necessary tracking, fitting and vertexing has to be processed in real time using <strong>de</strong>dicated hardware<br />
processors (L1/FPGAs). This first filter step is expected to reduce the event rate by a factor of 100. So<br />
the following second filter step can be calculated using general-purpose software processors (L1/CPUs).<br />
In a high level filter step this L1/CPUs can be used to perform a global tracking and filtering strategy.<br />
For the J/ψ processing the situation is a little different, e.g. the data from the TRD <strong>de</strong>tector is used for<br />
tracking. Using PT cuts, the electron candidates are <strong>de</strong>termined and the invariant mass is calculated.<br />
No special vertexing is necessary. Additionally or alternatively the ECAL data can be used for a proper<br />
particle i<strong>de</strong>ntification and energy measurement.<br />
The first level system consists of hardware units (ABs and L1/FPGAs) and of general-purpose processors<br />
(L1/CPUs) connected by a network (PNet), as <strong>de</strong>picted in Fig. 10.9.<br />
from <strong>de</strong>tector to/from Bnet from <strong>de</strong>tector<br />
Tracking<br />
AB AB AB AB AB AB AB AB<br />
to<br />
L1/CPUs<br />
...<br />
...<br />
L1/FPGA<br />
Event selection<br />
L1/FPGA<br />
Secondary vertex<br />
L1/FPGA<br />
L1/FPGA<br />
Primary vertex<br />
Pnet<br />
L1/FPGA<br />
L1/FPGA<br />
MAPS (layer1)<br />
L1/FPGA<br />
MAPS (layer 2)<br />
L1/FPGA<br />
Fitting<br />
L1/FPGA<br />
L1/FPGA<br />
L1/FPGA<br />
L1/FPGA<br />
TRD processing<br />
L1/FPGA<br />
L1/FPGA<br />
L1/FPGA<br />
L1/FPGA<br />
ECAL processing<br />
Figure 10.9: Block diagram<br />
of L1/FPGAs and their<br />
connection in one half of a<br />
sub-farm<br />
The number of ABs nee<strong>de</strong>d can be <strong>de</strong>rived from the <strong>de</strong>tector output data rate. Each AB unit is capable<br />
to store and process a 10 Gbit/s data stream. Assuming about 1,000 <strong>de</strong>tector data links, this results in<br />
about 1,000 ABs nee<strong>de</strong>d for storage and processing. For each of the approximate 64 sub-farms therefore<br />
16 ABs are nee<strong>de</strong>d. During one epoch ca. 1,000 <strong>de</strong>tector links output data with 10 Gbit/s. This data is<br />
stored in the <strong>de</strong>tector data buffer memory of the ABs and later output to the BNet in a way, that BNet is<br />
capable to sort data according to epochs. The BNet outputs the sorted data again to the ABs, where it is<br />
stored in the epoch data storage. This takes 1000 × epoch time with one 10 Gbit/s link.<br />
The STS <strong>de</strong>tector generates about 1/5 of all data. That means it also takes about 1/5 of the input time<br />
of the data to the AB, to output the STS data. Therefore four ABs can share one STS tracking unit.<br />
The STS tracking unit outputs the track parameters of found tracks. The number of tracks is about 1/5<br />
of the number of hits plus additional information, because it takes more bits to co<strong>de</strong> a track than one<br />
hit. But still two STS tracking units can share one track fitting and vertexing pipeline. The track fitting
254 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
and vertexing is divi<strong>de</strong>d into several steps, according to several L1/FPGAs. The processing time for the<br />
fitting and vertexing is proportional to the number of tracks.<br />
With a mean event rate of about 10 MHz every 100 ns a new event occurs. Using 256 STS tracking units,<br />
25 µs per event are available. Assuming real time processing with a processing time proportional to the<br />
number of hits, and a typical min bias event size of 1,500 hits, this results in a available time of 15 ns/hit.<br />
So a pipelined <strong>de</strong>sign with a frequency of several 100 MHz, that seems to be realistic and realizable, even<br />
several clock cycles are available for processing a hit.<br />
For a further processing of a track, found by the tracking, a unit for the fitting of the track is nee<strong>de</strong>d to<br />
<strong>de</strong>termine a more accurate momentum. Two other units are nee<strong>de</strong>d to process the track following through<br />
two layers of MAPS <strong>de</strong>tectors. Another two units are used to calculate the primary and the secondary<br />
vertex. Finally one unit calculates the invariant mass and stores the resulting data for a later usage of the<br />
L1/CPUs for the second filter level. Summarizing this, per eight ABs, two STS tracking units, one fitting<br />
unit, two MAPS track following units, two vertexing units and one event selection unit are nee<strong>de</strong>d, see<br />
figure 10.9.<br />
The amount of data coming from the TRD <strong>de</strong>tector is about the same as from the STS, therefore about<br />
the same amount of L1/FPGAs are nee<strong>de</strong>d for the tracking. Additionally to each tracking unit one unit<br />
is nee<strong>de</strong>d to calculate the momentum vector of the found tracks.<br />
The processing of the ECAL data is comparable simple, because mainly cluster finding is nee<strong>de</strong>d. From<br />
the ECAL output data rate it can be estimated that one L1/FPGA is nee<strong>de</strong>d per four ABs. A second<br />
L1/FPGA might be nee<strong>de</strong>d to combine the ECAL data with the processed TRD data.<br />
In total per eight ABs, eight L1/FPGAs are nee<strong>de</strong>d for the processing of STS data, four L1/FPGAs for<br />
TRD and four L1/FPGAs for ECAL.<br />
Each of this L1/FPGA units need about the same hardware resources, that’s how the algorithms, <strong>de</strong>scribed<br />
in the next section, are <strong>de</strong>veloped. This leads to a modular system, where each hardware unit<br />
can be used for every part of the algorithm. Even the hardware nee<strong>de</strong>d for the ABs is about the same,<br />
except larger memory and different network interfaces are nee<strong>de</strong>d. That’s why most of the <strong>de</strong>velopment<br />
nee<strong>de</strong>d to built the hardware for the ABs and L1/FPGAs is about the same, and most of the R&D and<br />
pre-prototypes are the same for both units. Also i<strong>de</strong>ntical is the part to initialize and control the FP-<br />
GAs and memories of the AB and L1/FPGA units. To provi<strong>de</strong> an easy to use interface for the user an<br />
additional microcontroller with Ethernet running Linux is foreseen.<br />
After a significant event reduction (factor 100 expected), the data will continue to proceed by the second<br />
level algorithms running in L1/CPU (Fig. 10.10). Being compatible with the first level reconstruction<br />
algorithms there is no need to rerun them, but only to improve quality of tracking and vertexing with<br />
higher precision of L1/CPU and in addition using data from other sub-<strong>de</strong>tectors. Thus the first level<br />
L1/FPGA processors will play the role of coprocessors of the second level L1/CPU processors solving<br />
all time consuming combinatorial problems, such as track and ring finding.<br />
After another event reduction the selected events will continue to process at the high level farm where<br />
the algorithms will use data from all sub-<strong>de</strong>tectors to achieve maximum efficiency of event analysis.<br />
To end up with a manageable system and board size of the hardware units, the proposal is to combine<br />
four hardware units on one board. An advantage of a larger board is that the infrastructure for power<br />
supply and controlling is nee<strong>de</strong>d only once per board. So on one AB board there are four AB units, and<br />
on one L1/FPGA board there are four L1/FPGA units. Assuming 64 sub-farms, there are 4 AB boards<br />
and 8 L1/FPGA boards nee<strong>de</strong>d per sub-farm.<br />
The reduction of the first filtering level is expected to be about 100. The input event rate for L1/CPUs<br />
therefore is about 100 kHz, or 10 µs per event.
10.3. Communication and Processing Architecture 255<br />
Figure 10.10: Algorithms for the level-1, level-2 and high level selections as presented from top to bottom. Every<br />
next level of selection will improve results of the previous one using more data and having more time available.<br />
From processing time today, e.g. track finding in STS takes 200 ms, one can extrapolate the processing<br />
time nee<strong>de</strong>d for the processing in 8 to 10 years. According to Moores law there will be a speedup of 50 to<br />
100 concerning general purpose processors in the next 8 to 10 years. So the time nee<strong>de</strong>d for processing<br />
will be in the or<strong>de</strong>r of 10 ms. The amount of data coming from the TRD <strong>de</strong>tector is about the same<br />
as from the STS, therefore about the same amount of L1/CPUs are nee<strong>de</strong>d for the tracking. A total of<br />
2,000 PCs can approximately solve the problem, that means that in each of the 64 sub-farms there are<br />
32 PCs.<br />
System-on-a-chip CPUs like BlueGene etc. may have a better performance concerning GFlops/ or<br />
GFlops/Watt than PCs, that’s why a solution using one or two 128 SoC processor boards per sub-farm<br />
may also be worthwhile.<br />
10.3.3 Implementation Plan for First Level Farm<br />
The implementation plan is based on the assumption that most of the CBM installation is done by end<br />
2013 and that 2014 is used for test and commissioning. For the first level farm hardware this means that<br />
the readout should be available by end of 2013, but the processing capacity is not nee<strong>de</strong>d 100%. This<br />
has the advantage that the components can be bought at the latest date in or<strong>de</strong>r to save money.<br />
Proprietary <strong>de</strong>velopments clearly are more critical than COTS components. To build, test and install
256 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
Activity Time period<br />
Adapt algorithms to <strong>de</strong>tector changes<br />
C/C++ simulations 2005 - 2008<br />
VHDL/Verilog coding 2005 - 2008<br />
Implement algorithm in pre-prototype 2008 - 2009<br />
Adapt algorithms to real <strong>de</strong>tector and commissioning 2010 - 2014<br />
R&D prototypes 2005 - 2007<br />
Pre-prototypes 2008 - 2009<br />
Fix architecture (type of FPGA, RAM, network) 2010<br />
Decision of COTS components 2011<br />
AB prototypes (8) 2010<br />
AB small series (32) 2011<br />
AB production 1 (96) 2012<br />
AB production 2 (180) 2013<br />
AB installation 2012 - 2013<br />
L1/FPGA prototypes (8) 2010 - 2011<br />
L1/FPGA small series (32) 2011 - 2012<br />
L1/FPGA production 1 (96) 2012 - 2013<br />
L1/FPGA production 2 (192) 2013 - 2014<br />
L1/FPGA production 3 (224) 2014 - 2015<br />
L1/FPGA installation 2012 - 2015<br />
Table 10.2: Timetable of software and hardware nee<strong>de</strong>d for AB and L1/FPGA realization<br />
huge hardware units like the AB and L1/FPGA boards approximately one week is nee<strong>de</strong>d per three to<br />
six boards. The first quarter of the number of boards to build, of course takes more time than the second<br />
quarter, and the second half less than the first.<br />
To built 256 AB boards about two years are nee<strong>de</strong>d for production, test and commissioning. Before this<br />
one year for the production of a small series is nee<strong>de</strong>d and another year for prototypes.<br />
The technique of the L1/FPGA boards is very similar to the ABs, both consists of FPGAs, external<br />
memories and connections to the networks. In<strong>de</strong>ed less than half of the L1/FPGA processing resources<br />
need to be available at end 2013, but more L1/FPGAs are nee<strong>de</strong>d. The timetable for the L1/FPGA boards<br />
therefore is shifted by half a year. Because the number of L1/FPGAs is about double the number of ABs<br />
the production takes one additional year. L1/FPGA prototypes are produced at the same time with AB<br />
small series, and L1/FPGA small series is produced in parallel to AB production, and so on. In this way<br />
the L1/FPGA production can gain from the AB <strong>de</strong>velopment. AB and L1/FPGA work packages can be<br />
done in parallel by adding manpower. On the other si<strong>de</strong> the time for <strong>de</strong>velopment and realization of one<br />
unit can not be accelerated by dividing the work packages to different teams, this would even have a<br />
worse effect because more communication between these teams would be nee<strong>de</strong>d.<br />
The R&D steps towards these prototypes are the following. In 2005 a hardware <strong>de</strong>velopment is planned to<br />
test the physical layer of the multi gigabit communication. The emphasis of this boards are impedances,<br />
board layout, connectors, and the different multi gigabit connections via optics, copper or backplane,<br />
from 2.5 Gbit/s to 10 Gbit/s per link. In 2006 these tests of communication are enlarged to protocols<br />
and their implementation. In parallel to these communication issues the algorithms to be implemented<br />
in hardware have to be tested.
10.3. Communication and Processing Architecture 257<br />
Another two board <strong>de</strong>velopments are scheduled for end 2006 and 2007 where the features of new <strong>de</strong>vices<br />
and new FPGA families have to be evaluated. This boards are nee<strong>de</strong>d to fix the requirements and size of<br />
FPGAs and external memory as well as communication issues on the way to standard protocols and real<br />
implementation of algorithms.<br />
For these tests several small R&D prototypes with different numbers and sizes of FPGAs and external<br />
memory are nee<strong>de</strong>d. Beginning of 2005 two small systems with cost-efficient state-of-the art FPGAs<br />
are scheduled. At begin 2006 an update of this systems with components adapted to the requirements<br />
of the algorithms are planned, e.g. more FPGA resources and large memories. End 2006 and 2007 new<br />
R&D prototypes are build that use the up-to-date technology, that is more adapted to the needs of the<br />
final hardware processing units. The used FPGAs will be high-end <strong>de</strong>vices and therefore look expensive<br />
during R&D, but they are expected to be middle-of-the-road FPGAs at 2012 to 2014.<br />
In 2008 first pre-prototypes of the hardware units are built to test the real algorithms and communication<br />
protocols. These units have already the size of the boards used later in the experiment and also the final<br />
control infrastructure. The <strong>de</strong>velopment and test of these infrastructure is of course part of the R&D<br />
prototypes.<br />
The years 2008 and 2009 are the most critical in this timetable, because here the final <strong>de</strong>cisions for the<br />
system have to be <strong>de</strong>rived. The first version of the hardware programming software has to be ready at<br />
end 2009 and the hardware architecture, concerning the type of FPGA, external memory, network and<br />
protocol has to be done. At end of 2010 also the <strong>de</strong>cision of the COTS components has to be fixed, this<br />
is t0 minus 3 years, what is a typical latest date for this <strong>de</strong>cision.<br />
In 2011 already first prototype processing farms are available using the prototypes <strong>de</strong>veloped for the ABs<br />
and the pre-prototypes used for L1/FPGAs. The prototype COTS processors are also part of this farms,<br />
with an even higher percentage than in the later system.<br />
In 2012 already one sub-<strong>de</strong>tector can be read-out and processed by about 8 sub-farms having about 1.5%<br />
of the final processing power. One year later about half of the <strong>de</strong>tector can be readout and 12.5% of the<br />
compute resources are available. End of 2013 the full <strong>de</strong>tector can be readout and 43% of the compute<br />
resources are available. This can be translated to a CBM event rate up to 4 MHz. The full processing<br />
power will be installed during 2014/15.<br />
System cost<br />
The following cost estimate is based on our experience in building complex real-time processing systems<br />
in hardware. Our assumption is, that a hardware unit that is able to process a 10 Gbit/s input data stream<br />
in real time will cost about 1 k, incl. board, power, crate, backplane, network and control.<br />
L1/FPGA, AB<br />
1024 × AB a 1k 1 M<br />
2048 × L1/FPGA a 1k 2 M<br />
Cost of R&D prototypes, prototypes 500 k<br />
and small series (spare for system)<br />
L1/CPU<br />
2048 × PC a 1k 2 M<br />
or 20000 × SoCs a 100 <br />
Table 10.3: Estimation of system cost<br />
The total cost for 1024 ABs and the 2048 L1/FPGAs therefore is 3 M. The cost of the R&D prototypes,<br />
the prototypes and the small series of the hardware boards sums up to additionally 500 k.
258 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
The hardware cost of one of the 64 sub-farms is: 16 k for AB, 32 k for L1/FPGA, 32 k for L1/CPU.<br />
Gives a total of 80 k per sub-farm.<br />
10.4 Feature Extraction and Event Selection<br />
Typical central Au-Au collision in the CBM experiment will produce up to 1000 tracks in the inner<br />
tracker. Large track multiplicities together with the presence of a non-homogeneous magnetic field make<br />
the reconstruction of events complicated. Therefore the collaboration performs an extensive analysis of<br />
different methods of event reconstruction in or<strong>de</strong>r to better un<strong>de</strong>rstand the geometry of the <strong>de</strong>tector and<br />
to investigate specific features of accepted events:<br />
1. Hough Transform for track finding in STS;<br />
2. Cellular Automaton for track finding in STS and TRD;<br />
3. Kalman Filter for track fitting;<br />
4. Kalman Filter for geometrical and mass-constrained vertex fit;<br />
5. Elastic Net for standalone RICH ring recognition.<br />
Status and results of testing of the algorithms are presented in Chapter 13.<br />
The most <strong>de</strong>manding task concerning processing is filtering events with open-charm in the first level.<br />
D mesons are <strong>de</strong>tected via their weak <strong>de</strong>cay into charged pions and kaons. The difficulty of this measurement<br />
lies in the very low multiplicity of D mesons (about 10 −3 per central event) within an environment<br />
of about 1000 charged hadrons produced in such a collision. Evi<strong>de</strong>ntly, the combinatorial background<br />
stemming from directly produced particles has to be suppressed by many or<strong>de</strong>rs of magnitu<strong>de</strong>. The mean<br />
lifetime of the D 0 mesons is cτ = 124µm. The secondary vertex resolution <strong>de</strong>pends on the material in<br />
the first <strong>de</strong>tector stations, causing multiple scattering, and the intrinsic single-hit position resolution of<br />
the tracking <strong>de</strong>tectors.<br />
The vertex resolution required for open-charm <strong>de</strong>tection is about 50 µm. To achieve this, the resolution<br />
of the very first <strong>de</strong>tector layers after the target (5 cm and 10 cm distance) must have a position resolution<br />
below 10 µm and a very low material budget. The MAPS technology is aimed to fulfill this requirements<br />
but has the disadvantage of the very slow readout speed of about 10 µs resulting in the accumulation of<br />
about 100 minimum bias events.<br />
To measure the momentum of a particle the bulk area of the tracking stations will be covered by silicon<br />
strip <strong>de</strong>tectors with matched strip geometry. Detector layers will be at distances of 20 cm, 40 cm, 60 cm,<br />
80 cm and 100 cm.<br />
The transition radiation <strong>de</strong>tectors (TRDs) are aimed to track and i<strong>de</strong>ntify high energy electrons and<br />
positrons (γ > 2000). These particles are then used to reconstruct J/ψ mesons. Tracking will be done<br />
either standalone only, or merging TRD tracks with tracks found in STS to improve track parameters at<br />
the target region.<br />
In combination with ECAL and ToF measurements TRD tracks can be used also for particle i<strong>de</strong>ntification<br />
in D mesons analysis.<br />
The track reconstruction out of the raw hit data from the <strong>de</strong>tectors is the har<strong>de</strong>st part of the processing,<br />
because no data reduction can be done so far. All subsequent parts can take advantage of the results<br />
<strong>de</strong>rived from the tracking, like an assumption of the momentum and charge of the particle.<br />
In this section we <strong>de</strong>scribe the filter strategy and some implementation scenarios for selected algorithms.
10.4. Feature Extraction and Event Selection 259<br />
10.4.1 Filter Strategy<br />
The process of event filtering can be broken down into several largely in<strong>de</strong>pen<strong>de</strong>nt steps. Some of this<br />
steps have to be performed in real time by <strong>de</strong>dicated processors, others are better running on CPU or at<br />
off-line stage of data analysis. In the first step, the data of each <strong>de</strong>tector are preprocessed already in the<br />
readout electronics (FEE) to make a compression of data, to minimize the bandwidth of the data transfer.<br />
The second step, the focus of this section, is a local pattern recognition within sub<strong>de</strong>tectors, that will be<br />
the base of selecting interesting events. The third step consists of global track finding and fitting, making<br />
full event reconstruction in the setup.<br />
In the following we will <strong>de</strong>scribe two approaches for the most <strong>de</strong>manding task, the selection of events<br />
containing <strong>de</strong>cays of D-mesons. One of them is more hardware oriented to be implemented in a first<br />
filter level. The other is more software oriented to achieve a more accurate and precise processing in the<br />
second filter level.<br />
In or<strong>de</strong>r to filter out <strong>de</strong>cays of D-mesons the data of the silicon vertex <strong>de</strong>tector (STS) is used to track the<br />
particle traces. Special high resolution <strong>de</strong>tectors (MAPS) are used for the <strong>de</strong>termination of the primary<br />
and secondary vertices. Finally a <strong>de</strong>cision whether the event is selcted or not, has to be generated<br />
according to the invariant mass of particles coming from a secondary vertex, using assumed particle<br />
i<strong>de</strong>ntity.<br />
Here is an overview of the filter strategy and the used algorithms. Details of the concrete algorithms are<br />
given in Chapter 13.<br />
• Tracking of STS data.<br />
Tracking algorithms can be divi<strong>de</strong>d into local and global methods. Local methods process the<br />
tracks in<strong>de</strong>pen<strong>de</strong>nt from each other. Some few points generate an initial track candidate. Using<br />
interpolation or extrapolation additional points are collected. When more points can be found the<br />
track candidate is assumed to be good, otherwise the track is discar<strong>de</strong>d. A method is global when<br />
all points are processed by the algorithm in the same way. The algorithm produces a list of tracks<br />
or a list where tracks can be found easier than in the original data. Global methods can be seen as<br />
transformation.<br />
We have implemented one of the well-known global methods, the Hough transform, in or<strong>de</strong>r to<br />
investigate its hardware (e.g. FPGA) applicability for a first filter level. The Hough transform uses<br />
a parametric <strong>de</strong>scription of a track by a set of its parameters. Once the track mo<strong>de</strong>l and <strong>de</strong>tector<br />
measurement mo<strong>de</strong>l are given, all hits in the <strong>de</strong>tector can be projected into the track parameter<br />
space creating a complex <strong>de</strong>nsity distribution (histogram) with local maxima. In this case the track<br />
recognition becomes a search for local maxima corresponding to tracks.<br />
A very fast software implementation of a local method is a cellular automaton algorithm. The cellular<br />
automaton method creates short track segments in neighbored <strong>de</strong>tector planes and links them<br />
into tracks. Being essentially local and parallel cellular automata avoid exhaustive combinatorial<br />
searches. Since cellular automata operate with highly structured information, the amount of data<br />
to be processed in the course of the track search is significantly reduced. Cellular automata employ<br />
a very simple track mo<strong>de</strong>l which leads to utmost computational simplicity and a fast algorithm.<br />
• Track following through the MAPS <strong>de</strong>tector.<br />
The readout time of a MAPS <strong>de</strong>tector is in the or<strong>de</strong>r of 10 µs, that is a relatively high time period<br />
compared with the about 10 MHz event rate. This leads to an event pileup of approximately<br />
100 events in this <strong>de</strong>tector type. The only feasible way to follow a track through this bulk of accumulated<br />
multi event data is to expand the fitting of the found tracks from the STS tracking into<br />
this <strong>de</strong>tector.
260 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
The Kalman filter is an algorithm to calculate an optimal estimation of a value based on any<br />
kind of measurements taking into acount also their accuracy (e.g. <strong>de</strong>tector resolution and multiple<br />
scattering). Based on a measurement it updates its estimate and generates a new more precise<br />
prediction of the value.<br />
The Kalman filter is implemented with different emphasis, one is optimized for processing speed,<br />
the other for precision.<br />
• Primary and secondary vertex <strong>de</strong>termination.<br />
The <strong>de</strong>termination of the primary vertex is done by expanding the Kalman filter process through<br />
the MAPS <strong>de</strong>tector to the approximate vertex position.<br />
All particle tracks that do not intersect this primary vertex have to be processed once again. For<br />
all combinations of tracks the nearest points of intersection (χ 2 ) have to be calculated. If there is a<br />
near intersection this point is a possible secondary vertex and the invariant mass of this tracks with<br />
an approximate momentum from the tracking and an assumed particle i<strong>de</strong>ntity is calculated.<br />
For J/ψ event selection the procedure is following:<br />
1. tracking of TRD data;<br />
2. select electrons and positrons;<br />
3. roughly estimate their momenta from <strong>de</strong>flection angle in the magnetic field;<br />
4. select electron-positron pairs with invariant mass close to the J/ψ mass;<br />
5. propagate tracks of these candidates to STS;<br />
6. merge them with found STS tracks or use them as seeds to find tracks in STS;<br />
7. improve track parameters in the target region;<br />
8. calculate invariant mass.<br />
J/ψ event selection can use measurements of other <strong>de</strong>tectors if necessary.<br />
Fig. 10.11 gives an overview of the algorithms and their association during event processing.<br />
10.4.2 Implementation Scenarios for Selected Algorithms<br />
In this section we <strong>de</strong>scribe an assumption of the requirements for implementation and processing for a<br />
selection of concrete algorithms.<br />
Aiming their implementation in all levels of event selection the algorithms are being <strong>de</strong>veloped in two<br />
complementary directions: from the high level in their base form to the hardware implementation in<br />
L1/FPGA and vice versa. Such strategy allows to investigate both efficiency and applicability of the<br />
algorithms. The algorithms in their base level form are <strong>de</strong>scribed in the chapter concerning physics<br />
performance.<br />
Here we give short <strong>de</strong>scription of the Hough transform method as it can be implemented in L1/FPGA.<br />
The Hough transform is aimed for a direct implementation in hardware to provi<strong>de</strong> a very fast tracking<br />
for the first filter level. A very simplified version of a Kalman filter is shown together with a possible<br />
hardware implementation.
10.4. Feature Extraction and Event Selection 261<br />
Event Processing Steps<br />
STS Data<br />
HT/CA Track Fin<strong>de</strong>r<br />
KF Track Fit<br />
PV Fin<strong>de</strong>r<br />
PV GeoFit<br />
Performance<br />
RICH Data<br />
EN Ring Fin<strong>de</strong>r<br />
Track Merger<br />
KF Track Fit<br />
SV GeoFit<br />
SV ConstrFit<br />
Select/Discard Event<br />
TRD Data<br />
CA Track Fin<strong>de</strong>r<br />
KF Track Fit<br />
09 Dec 2004, Hd Ivan Kisel, KIP, Uni-Hei<strong>de</strong>lberg<br />
Uni Hei<strong>de</strong>lberg 6<br />
10.4.2.1 Hough Transform<br />
Figure 10.11: Event processing steps<br />
The Hough transform is a global tracking algorithm and therefore its number of operations is proportional<br />
to the number of hits to process. It has the advantage that it is robust against additional or missing noisy<br />
<strong>de</strong>tector hits and also sensitiv to ill-<strong>de</strong>fined objects. A <strong>de</strong>tailed <strong>de</strong>scription of the algorithm and the<br />
physical performance is given in 13.1.1. Here we <strong>de</strong>scribe a possible implementation of the Hough<br />
transform using Field Programmable Gate Array (FPGA) and lookup tables (LUT), like used for the<br />
hardware processing units (L1/FPGA) of the first level farm (see 10.3.2).<br />
The <strong>de</strong>tector hits with the coordinates x, y, z are transformed in a parameter space according to 1/Pz,<br />
Px/Pz and Py/Pz. It is divi<strong>de</strong>d of several 2-dimensional Hough transforms where each <strong>de</strong>tector slice<br />
(red area in <strong>de</strong>tector in fig. 10.12) contributes to a certain plane (red area in Hough histogram) in the 3dimensional<br />
Hough histogram. In the first step the hits are stored in a buffer according their y/z-position<br />
using a LUT. Hits with different y/z are processed subsequent by calculating a 2-dim. Hough transform<br />
for each y/z value. A second LUT <strong>de</strong>termines the shape of the curve in the Hough space generated by a<br />
hit. The curves of all hits are accumulated in a Hough histogram. A peak <strong>de</strong>termines a found track and<br />
its momentum parameters 1/Pz, Px/Pz, Py/Pz.<br />
The goal is to process one <strong>de</strong>tector hit per clock cycle. A 10 Gbit/s input link is able to transfer 150 · 10 6<br />
hits/s, expecting a hit is co<strong>de</strong>d with 64 bit. The necessary frequency for processing therefore is 150<br />
MHz. The processing time <strong>de</strong>pends only on the number of hits in an event. With 1,500 to 10,000 hits per<br />
event a rough estimate of the processing time is between 10µs to 100µs. As each 10 Gbit/s link can be<br />
processed in real-time the number of nee<strong>de</strong>d Hough units is about the same as <strong>de</strong>tector data links from<br />
the STS are nee<strong>de</strong>d, that are approximately 200.<br />
To process one <strong>de</strong>tector hit in one clock cycle the complicated calculations of the Hough transform<br />
according to the real <strong>de</strong>tector geometry and the magnetic field are implemented with LUTs. Using LUTs<br />
also inhomogeneities of the magnetic field can be consi<strong>de</strong>red and put into calculation.<br />
The Hough transform consists of two parts (see fig. 10.12). First the y-z projection of a track as a straight<br />
line applied. As <strong>de</strong>scribed earlier the 3-dimensional Hough histogram is <strong>de</strong>composed into several 2dimensional<br />
Hough histograms. In principle this <strong>de</strong>composition can be calculated using the y and z<br />
coordinate of a hit. In a first LUT the numbers of the 2-dimensional Hough-histograms are stored where
262 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
Y<br />
X<br />
Z<br />
Py/Pz<br />
Px/Pz<br />
from Active Buffer<br />
buffer<br />
x,y,z<br />
x,z<br />
LUT<br />
y,z<br />
LUT<br />
Hough-histogram<br />
1/Pz<br />
peak finding<br />
Px/Pz<br />
1/Pz, Px/Pz, Py/Pz<br />
Figure 10.12: 3-dimensional Hough transform and hardware implementation.<br />
a hit contributes. The output of this LUT is used to store the hits according to this 2-dimensional Hough<br />
planes.<br />
In the second step the 2 dimensional Hough histograms are calculated. This can be done subsequent or<br />
in parallel. A second LUT is accessed using the x and z coordinate of a hit and it outputs the co<strong>de</strong>d shape<br />
of the transformed curve in the Hough space. The slope of this curve is <strong>de</strong>pendant on the z coordinate,<br />
the start value is <strong>de</strong>pendant on the x coordinate of the hit.<br />
The accumulation of the Hough curves to a histogram is done in a systolic array of simple processing<br />
elements (see fig. 10.13). Each element consists of a counter to store the histogram value, a flip flop for<br />
the short-term storage of the Hough curve, and a multiplexer to select from two neighboring elements<br />
to <strong>de</strong>termine the shape. In every clock cycle a new start value is input to the array and the appropriate<br />
element in the first row is set. In the next cycle, in parallel to the setting of a new start bit in the first row,<br />
the former bit is transferred to the directly neighbored element or the diagonal element in the second row,<br />
and so on. The multiplexers of the elements of one row to select the particular input are controlled by<br />
one bit per row, that are <strong>de</strong>layed by shift registers. The slope of a curve can be choosen arbitrary between<br />
the minimum and maximum slope of 45 and 90 <strong>de</strong>gree.<br />
The counter of each cell of the histogram stores the number of hits from the different <strong>de</strong>tector layers that<br />
lay on a trajectory of a track with the associated parameters. The counter not just counts the number of<br />
hits, but each hit of a certain <strong>de</strong>tector layer sets a certain bit in the cell. At the end it can be seen which<br />
layer has contributed to the track candidate. Clusters or nearby hits are counted as one hit (with a larger<br />
size), but do not inflate the counter value. When all bits of all layers are set, there is at least one hit in<br />
every <strong>de</strong>tector layer. So the track candidate is accepted as a found track with the parameters <strong>de</strong>termined<br />
by the cell position. It also happens that tracks do not pass all <strong>de</strong>tector layers or that hits are missing due<br />
to <strong>de</strong>tector inefficiencies. Acceptable tracks should come from the vertex, there has to be one hit in the
10.4. Feature Extraction and Event Selection 263<br />
x<br />
LUT<br />
<strong>de</strong>tector<br />
hit coordinates<br />
x, z<br />
1 bit/row<br />
z<br />
shift registers<br />
start<br />
Figure 10.13: Implementation of a Hough transform unit as a systolic array of simple processing elements. Each<br />
processing element consists of a counter to store the histogram value, a flip flop for the short-term storage of the<br />
Hough curve, and a multiplexer to select from two neighboring elements to <strong>de</strong>termine the shape. The array is<br />
controlled by a start value and a 1 bit/row control word.<br />
first layer (STS3), and there should be at least two other hits in the layers STS4 to STS7. Other rules for<br />
the acceptance of a track in <strong>de</strong>pendance of the different counter states are programmable.<br />
An efficient implementation as a systolic array within a FPGA was elaborated. To implement a 2dimensional<br />
Hough histogram with 31 × 93 cells together with the peak finding unit and the units to<br />
control the LUTs and memories, about 35.000 to 40.000 logic cells are nee<strong>de</strong>d, what fits into a mid-size<br />
to large state-of-the-art FPGA. About 8×(1M ×16) SRAMs as external memory are nee<strong>de</strong>d for the large<br />
LUTs and the hit buffer.<br />
10.4.2.2 Fast Kalman Filter Hardware<br />
The Kalman filter is an algorithm to calculate an optimal estimation of a value based on any kind of<br />
measurement taking into account also their accuracy. Based on a measurement it updates its estimate<br />
and generates a new more precise prediction of the value.<br />
In our case the prediction of the position of a track hit in a previous <strong>de</strong>tector layer was calculated by<br />
assuming a straight line in the non-bending y-z plane and a parabola in the magnetic x-z plane of the<br />
<strong>de</strong>tector. The Kalman filter algorithm was simplified in terms of complexity as well as accuracy of<br />
the calculations, e.g the noise and error covariance was chosen to believe the latest measurement. The<br />
measurement nearest to the target has the lowest influence of multiple scattering because it has passed<br />
the fewest <strong>de</strong>tector planes. As the calculations are aimed to be processed directly in the parallel hardware<br />
of a FPGA, the coefficients and parameters of the Kalman filter are presented as integer values with 10<br />
CNT<br />
D Q
264 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
to 12 bits resolution. Prior to the calculations these values have to be mapped to a new number range.<br />
The calculation itself then are mostly simple additions where the result once again has to be converted<br />
to the new range of the result value. The LUTs to convert the ranges of the values are comparable small<br />
because only 10 to 12 addresses are nee<strong>de</strong>d. They may well be implemented using the internal resources<br />
of a FPGA. Also ad<strong>de</strong>rs can be implemented efficiently in FPGAs.<br />
The hardware challenge is the realization of the <strong>de</strong>tector hit memory. It is addressed by the predicted<br />
position of a hit and has to output the relative position of the nearest hit stored in the memory. This is<br />
the functionality of an associative memory. In or<strong>de</strong>r to store the accumulated data of ca. 100 events<br />
according to the geometry and position of a hit, several tenth of Mbit are nee<strong>de</strong>d.<br />
The Kalman filter implementation works very efficient. Simulations of the <strong>de</strong>scribed algorithm with<br />
Monte Carlo data showed that without pileup about 98 % of the nearest hits were from the same track.<br />
With a pileup of 100 events the performance drops by about 10 %. This means that for about 12 % of the<br />
tracks the nearest hit to the prediction was not from the same track but from a track from an event that<br />
was piled up in the <strong>de</strong>tector. The efficiency shows a strong <strong>de</strong>pen<strong>de</strong>ncy upon the momentum of a track.<br />
For tracks with a momentum P < 1 GeV/c the efficiency very fast is much smaller than 80 %. For tracks<br />
with a momentum P > 1 GeV/c the efficiency is better than 90 %.<br />
The processing time for the Kalman filter track following through the MAPS <strong>de</strong>tectors is proportional to<br />
the number of tracks that have to be processed.<br />
Primary Vertex Determination<br />
The primary vertex is i<strong>de</strong>ntified by calculating the z coordinate of the points of intersection in the nonbending<br />
y-z plane. To save processing power an intersection of a found particle track is calculated not<br />
with all tracks, but only with about max. 100 previously stored tracks with opposite charge (sign of<br />
bending found by the tracking). To <strong>de</strong>termine whether a track is coming from the primary vertex the<br />
z coordinates of the intersections are histogrammed. If one of the calculated z coordinates is equal to<br />
the peak of the histogram (the position of the primary vertex) it is flagged as "from primary vertex".<br />
A calculation of the x-position at the vertex position <strong>de</strong>livers additional accuracy for the origin of the<br />
particle.<br />
First simulations of this algorithm showed that only about 5 % of the tracks found by the tracking remain,<br />
that are most probably from a secondary vertex. The position of these possible secondary vertices has to<br />
be calculated in a next processing step.<br />
A track can be <strong>de</strong>scribed by parameters co<strong>de</strong>d in less than 100 bit. The memory nee<strong>de</strong>d for the storage<br />
of the 2 × 100 tracks therefore is very low (totally ca. 20 kbit).<br />
The calculations nee<strong>de</strong>d for the <strong>de</strong>termination of the point of intersection is comparable with the complexity<br />
nee<strong>de</strong>d for the update step of the Kalman filter for the linear y-z plane. The parameters of the<br />
tracks are co<strong>de</strong>d in the same way as they are used and output from the Kalman filter. In this way an<br />
efficient implementation with FPGA is possible, using ad<strong>de</strong>rs and internal memory for the LUTs. In<br />
or<strong>de</strong>r to process as many as possible of the up to hundred calculations of the point of intersection in<br />
parallel, many parallel units within one FPGA <strong>de</strong>vice are used. Taking advantage of this parallelism the<br />
processing time for this step is in the or<strong>de</strong>r of one cycle per track.<br />
10.5 Controls (ECS)<br />
The Experiment Control System (ECS) has to ensure the coherent and safe operation of the CBM experiment.<br />
One main requirement is the easy integration of in<strong>de</strong>pen<strong>de</strong>ntly <strong>de</strong>veloped components.
10.5. Controls (ECS) 265<br />
10.5.1 General Description<br />
The Experiment Control System is used to supervise and operate all <strong>de</strong>tector hardware, the common<br />
experimental infrastructure and it provi<strong>de</strong>s the status of <strong>de</strong>tector components for the CBM DAQ. It interfaces<br />
to the <strong>GSI</strong> infrastructure and to the SIS accelerator.<br />
The ECS does not <strong>de</strong>al with the safety of personnel.<br />
10.5.2 Detailed requirements<br />
The ECS is capable of operating the <strong>de</strong>tector hardware without the DAQ system. Therefore it should<br />
wherever possible use its own control path to the hardware.<br />
The ECS is build as a client-server mo<strong>de</strong>l. The clients are the distributed user interfaces (GUI), archiving<br />
stations, alarm handlers, and other high-level interfaces. The servers are agents running either in the DCS<br />
boards or workstations or single board computers which interface to the specific <strong>de</strong>tector or infrastructure<br />
hardware.<br />
Clients and servers communicate over IP networks with protocols like channel access (CA), DIM or<br />
similar.<br />
The ECS can be partitioned in sub-<strong>de</strong>tectors for <strong>de</strong>velopment and separate testing on a per agent basis.<br />
The ECS has to integrate in<strong>de</strong>pen<strong>de</strong>ntly <strong>de</strong>veloped components by providing interoperability between a<br />
small number of allowed standards (field busses, SCADA systems, common hardware)<br />
10.5.2.1 Functionality<br />
The ECS provi<strong>de</strong>s for setting the <strong>de</strong>tector system into a runnable status by loading parameters and configuration<br />
files from the database to <strong>de</strong>tector and trigger hardware. For speed of operation the database<br />
will be distributed and local caches in agents or intermediate management layers will be used (LAM and<br />
WAM).<br />
The ECS monitors operational parameters from <strong>de</strong>tectors, trigger hardware, high and low voltage supplies,<br />
gas systems, position measurement systems, and environment and provi<strong>de</strong>s a GUI to these process<br />
variables (PV) to the user.<br />
All relevant process variables are archived to the database. Historical views and trending is provi<strong>de</strong>d to<br />
the user and via APIs to the analysis software.<br />
The state of critical process variables is constantly monitored and compared against pre<strong>de</strong>fined boundaries.<br />
The Alarm handling client alerts the operator and logs alarm states and acknowledgments to log<br />
files (or database).<br />
Interlocks and <strong>de</strong>tector safety are provi<strong>de</strong>d with <strong>de</strong>dicated hardware (i.e. PLCs), but the ECS monitors<br />
this hardware and the interlock status.<br />
Access Control to modification of parameters in the ECS and in the database are provi<strong>de</strong>d through user<br />
accounts and passwords.
266 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
10.5.3 Possible Implementation<br />
10.5.3.1 Connections<br />
It is advisable to use different paths for ECS and DAQ in or<strong>de</strong>r to guarantee status messages and state<br />
transitions to be received regardless of the state of the DAQ. The different paths can be provi<strong>de</strong>d in two<br />
ways, either by a completely separated network or by using extra fiber bundles of the same type as used<br />
for the DAQ. In this case it has to be guaranteed that the connecting network infrastructure (switches)<br />
can not be blocked. There has to be the possibility for all components in the ECS and DAQ to switch on<br />
and off remotely, either successively by the control network or by a separate power distribution system.<br />
10.5.3.2 Software<br />
For the reason of maintainability and licensing costs we want to use wherever possible open source<br />
software. There are several packages which are used with good experience in the HEP community, like<br />
EPICS and DIM. Some of the collaborators already have used these packages in previous experiments<br />
and can build on their knowledge. One big advantage of these packages is that one can influence the<br />
<strong>de</strong>velopment of this software oneself by contributing new solutions for new hardware or interfaces.<br />
On the other hand there are many laboratory style hardware setups like gas systems, high voltage supplies,<br />
connections to PLCs, which are build around commercial SCADA packages like LabView. Of<br />
course we will try to interconnect these sub systems to the general ECS by writing gateways.<br />
10.5.3.3 Hardware<br />
The hardware which will be supervised by the ECS fall in two categories:<br />
• Standard Hardware<br />
• The DCS board<br />
Standard Hardware<br />
Early on a set of standardized hardware components which can be reused in the different <strong>de</strong>tector sections<br />
has to be i<strong>de</strong>ntified, as there are:<br />
• High Voltage<br />
• Low voltage power supplies<br />
• Crates and racks<br />
• Temperature sensors<br />
• Position sensors (Critical for STS tracking stations)<br />
• Gas supply systems, valves, flow meters<br />
Through the standardization we will achieve fewer different components, more reusable parts in hardware<br />
(spares) and software and bigger discounts in the acquirement.
10.5. Controls (ECS) 267<br />
10.5.4 The Detector Control System (DCS)<br />
The <strong>de</strong>tector control system (DCS) is an agent unit for many <strong>de</strong>tector front-end components. It acts as a<br />
status and event server for the ECS system as well as a client for controlling all front-end electronics.<br />
The DCS will be implemented as a single board computer 2 . It consists of DCS hardware (DCS board),<br />
an operating system and the DCS application.<br />
10.5.4.1 Functional Description<br />
The main tasks of DCS are to securely switch on and off front-end electronics, to configure all components<br />
(including FPGAs), and to set all software and hardware parameters. Additionally the DCS should<br />
implement the runtime refresh for all FPGAs exposed to high radiation.<br />
DCS generates control events and passes them to the experiment control system (ECS), and finally it<br />
produces all necessary information for generating the <strong>de</strong>tector status in the ECS.<br />
The basic principle is to watch and control all necessary <strong>de</strong>tector parameters like temperature, chamber<br />
gas pressure, supply voltages and many others. Therefore, the DCS needs to generate and pass control<br />
events if anything goes wrong.<br />
10.5.4.2 Implementation Issues<br />
The central processing element should be implemented on an FPGA due to the ability to configure DCS<br />
components during runtime of the experiment. The processor may either be a hard processor core (like<br />
PPC (Xilinx Virtex 4) or a soft core if its performance is acceptable. In 2012 the cost of a sufficient<br />
FPGA will be in the same scale as a microcontroller. Therefore FPGAs will become a powerful and<br />
highly flexible substitution to standard microcontrollers.<br />
The field bus between DCS and ECS should be a TCP/IP based protocol since this is a robust standard<br />
implementation based on a well known technology. It is not yet <strong>de</strong>ci<strong>de</strong>d to implement it copper based or<br />
to use fibre optics instead.<br />
For flexibility and simplicity reasons, we propose to run embed<strong>de</strong>d Linux on the DCU boards, since the<br />
application can run as a Linux process, and all infrastructure like TCP/IP stack, process management,<br />
mounting external file systems etc. is inherently available.<br />
10.5.4.3 DCS Operation<br />
The DCS watches four different types of parameters:<br />
• Threshold parameters need be set and verified during normal operation<br />
• Non critical parameters which will be read out from time to time like event counters<br />
• Switches need to be set like power on and power off<br />
• Parameter values like the chamber temperature or the voltage of the power supplies which need to<br />
be watched and will generate an error event if a threshold will be hit.<br />
2 It is therefore sometimes referred as DCS-board for clarity
268 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
The concept of control software is <strong>de</strong>centralized which means that the DCS tries to solve minor problems<br />
by its own. As long as everything is fine, a good-signal will be sent to the DCS either automatically or<br />
upon ECS request. This good signal may contain additional information like event counts etc. As soon<br />
as this signal is not received within a specified time, the ECS expects an error of the corresponding DCS<br />
and tries to reboot it.<br />
If a threshold value is missed, a control event will be generated. Currently we differentiate four priorities<br />
of control events:<br />
a) immediate event: a critical value was significantly violated. Therefore we need an immediate<br />
reaction like emergency shut off.<br />
b) critical event: A critical threshold value was reached.<br />
c) warning event: A critical value comes close to a threshold .<br />
d) info event: The DCU was able to resolve a problem by its own. This is an information to the DCC<br />
DCS also acts as a client for ECS commands: It should react on events like load configuration, configure<br />
FEE components, send status report, and switch on and off of the FEE power supply.<br />
10.5.4.4 Research Work<br />
A similar DCS system was build for the ALICE readout electronics. Therefore we expect some new<br />
i<strong>de</strong>as when this system will be used to control the ALICE Experiment. We assume that major parts of<br />
the ALICE DCS may be reused for the CBM <strong>de</strong>tector.<br />
The new concepts inclu<strong>de</strong> radiation tolerance (see chapter fault tolerance), partial runtime reconfiguration<br />
of the front-end electronics if FPGAs are used, and new parameters nee<strong>de</strong>d to be watched.<br />
Additional research work inclu<strong>de</strong>s making the DCS a fully distributed, fault tolerant system. Therefore<br />
we need to ensure that no critical events will be lost by introducing redundancy.<br />
10.5.4.5 The ALICE DCS Board<br />
An appropriate <strong>de</strong>vice was build for the ALICE experiment, which may serve as a starting point for further<br />
consi<strong>de</strong>rations. The ALICE DCS board has a very high <strong>de</strong>gree of flexibility, which is accomplished<br />
by using Alteras Excalibur FPGA with embed<strong>de</strong>d ARM processor core on which the Linux operating<br />
system is running. In addition, the integrated, programmable FPGA allows the integration of specific<br />
functionality in a very flexible way and is being used to custom fit the <strong>de</strong>vice to the specific requirements<br />
of the various <strong>de</strong>tectors. It is now being used by most ALICE <strong>de</strong>tectors. The FPGA configuration and the<br />
program co<strong>de</strong> for the CPU is stored in a Flash ROM from which the system is automatically configured<br />
after power-up. An ADC for digitizing analog signals coming from the <strong>de</strong>tector, a SDRAM chip, and<br />
a FastEthernet PHY transceiver chip complete the system. Full control over all on-board configurable<br />
components, such as the FLASH memory or the FPGA, is ensured and mutual reconfiguration of the<br />
boards in case of failure is feasible with a JTAG chain.<br />
The ARM processor runs Linux as operating system, therefore simplifying the <strong>de</strong>velopment of application<br />
software since the well known GNU standard tools (compiler, <strong>de</strong>bugger, and libraries) can be used.<br />
For instance, a web server was successfully ported and operated on the board. This allows for a very<br />
comfortable configuration and monitoring scheme of individual <strong>de</strong>tectors, based on the http protocol<br />
together with the common gateway interface (CGI) using any web browser in combination with the onboard<br />
web server. The high level control and monitoring functionality of the <strong>de</strong>tector control system is
10.5. Controls (ECS) 269<br />
Figure 10.14: A photo of the<br />
ALICE DCS front-end configurable,<br />
low cost single board <strong>linux</strong> computer,<br />
running Ethernet as fieldbus,<br />
operable in magnetic fields.<br />
based on the Distributed Information Management System (DIM). This requires a so-called DIM-server<br />
running on the DCS single board computer. This server is responsible for publishing measured slowcontrol<br />
data to the next higher instances in the hierarchical DCS system. Commands to the DCS single<br />
board computer are also sent to the server. An appropriate DIM server was ported and is operational<br />
on the first prototypes of the <strong>de</strong>vice. All programs necessary for starting the system and its operation<br />
are permanently stored in the Flash ROM. Therefore, the DCS single board computer can be operated<br />
stand-alone and it does not require a network connection in or<strong>de</strong>r to perform the basic control tasks.<br />
This feature is especially important in terms of safety requirements where a proper and secure operation<br />
of the <strong>de</strong>tector has to be guaranteed even in cases where part of the higher levels of the control system<br />
are not working. During operation the Ethernet connection is required only for publishing measured<br />
data. It is also used in spy mo<strong>de</strong> to access on-line data without affecting the main <strong>de</strong>tectors data stream.<br />
This feature is very useful in particular during the <strong>de</strong>bugging phase of the <strong>de</strong>tectors and even during test<br />
measurements where performance is not essential.<br />
The communication with the DCS board requires a reliable field bus. One possible network technology<br />
which is discussed very actively in industry at the moment is Ethernet as field bus. One advantage of<br />
using Ethernet is its wi<strong>de</strong> use and therefore the availability of cheap standard components. However,<br />
the proper function of Ethernet even in a harsh environment with electromagnetic background noise has<br />
to be ensured. Another complication arises due to the presence of strong magnetic fields since standard<br />
network <strong>de</strong>vices use a transformer for electrical signal <strong>de</strong>coupling. In case of the DCS board this problem<br />
is solved by replacing the transformer with a small amplifier circuit which boosts the output signal of the<br />
physical layer chip. Measurements were done with a setup consisting of a DCS single board computer<br />
and a standard Ethernet switch with 50 m UTP CAT5 cable between the two <strong>de</strong>vices and verified the<br />
proper function of the modification.<br />
Although different commercial network interfaces for Ethernet exist, a different approach was chosen<br />
for the DCS board. The Medium Access Controller (MAC) of the DCS board is realized as a very<br />
lightweight synthesizable module in VHDL, called Easynet. By the renouncement of collision <strong>de</strong>tection<br />
this <strong>de</strong>vice uses only a minor fraction of the FPGA resources. Besi<strong>de</strong>s the benefit of eliminating<br />
external chips this approach allows in addition to complement the existing Ethernet protocol with quality<br />
of service functionality, allowing for the reservation of bandwidth and implementing high priority,<br />
reliable messages. Such functionality can be integrated and operated with existing commercial network<br />
components provi<strong>de</strong>d that all participating MACs adhere to such functionality.<br />
Figure 10.14 shows a photo of the low cost DCS board as it is used in the <strong>de</strong>tector control system of<br />
ALICE at the LHC. The board will be used for example in the TRD, TPC, and PHOS sub<strong>de</strong>tectors<br />
and will be responsible for monitoring and control of the overall working conditions of these <strong>de</strong>tectors<br />
like voltages, temperatures, and pressures. Furthermore, it can be used as a test read out system of the<br />
<strong>de</strong>tectors. This functionality already proved very useful during tests and conditioning of the ALICE TRD
270 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
<strong>de</strong>tector. The system is able to react autonomously to critical situations in or<strong>de</strong>r to avoid damages of the<br />
<strong>de</strong>tectors. In addition, the board is used to initialize and configure the front end electronics. Table 10.4<br />
summarizes the overall features of the board.<br />
CPU ARM922T, 32-bit RISC<br />
FPGA 100 000 gates (1 000 000 optional)<br />
4 160 Logic elements (38 400 optional)<br />
SDRAM 32 <strong>MB</strong><br />
Flash memory (ROM) 4 <strong>MB</strong> (8 <strong>MB</strong> optional)<br />
ADC 8 channel, 16-bit<br />
Power consumption < 4 W<br />
Table 10.4: Key parameters of the ALICE DCS single board computer.<br />
10.5.5 Configurations and Update Management<br />
The Configurations and Update Management system is part of ECS software. Its key feature is the ability<br />
to handle numerous different configurations of all parts of the electronics. These configurations inclu<strong>de</strong><br />
<strong>de</strong>tector test procedures as well as different scenarios during lifetime of the experiment.<br />
In the case of a large <strong>de</strong>tector, a configuration and update management system needs to manage FPGA<br />
hardware configurations, software applications, and all parameters of the front-end electronics.<br />
For the optimal use of limited storage possibilities on <strong>de</strong>tector control <strong>de</strong>vices and the immense amount<br />
of data to be saved on a server or to be distributed to the <strong>de</strong>tector control <strong>de</strong>vices, it is necessary to<br />
<strong>de</strong>velop a new strategy for handling the data.<br />
10.5.5.1 Functional Description<br />
Due to the large number of processed <strong>de</strong>tector configurations and hardware, software or parameter updates,<br />
a fully <strong>de</strong>centralized system architecture is required. The <strong>de</strong>centralized character of the architecture<br />
is based on the i<strong>de</strong>a to transfer some of the management tasks into the <strong>de</strong>vice and thereby reduce<br />
communication efforts and to process configurations as close to the <strong>de</strong>vice as possible.<br />
The management environment should be redundant to guarantee highest availability from configurations<br />
databases and servers. Redundancy is also required for having access to additional hardware <strong>de</strong>vices for<br />
solving problems during a reconfiguration or update procedure (disaster recovery).<br />
The configuration and update system has to guarantee a fast configuration and update process since the<br />
<strong>de</strong>tector will be unavailable during a setup or update. This also holds for configuration repository: it is<br />
important to <strong>de</strong>velop a new method for a <strong>de</strong>centralized storage of configurations and updates and new<br />
algorithms to get the <strong>de</strong>vice status with a minimum of communication.<br />
Finally the monitoring of the configuration and management process is necessary to <strong>de</strong>ci<strong>de</strong> whether the<br />
configuration or update was completed successfully. In case of failure the management unit is able to<br />
generate an event for notifying the experiment control system.<br />
10.5.5.2 Implementation Issues<br />
We propose a multiple level <strong>de</strong>centralized client server architecture. The architecture is based on a very<br />
scalable multi-level server network.
10.6. Computing 271<br />
The backbones of this network are so called Local Area Management (LAM) servers. A LAM is responsible<br />
for a set of <strong>de</strong>tector control units (DCU). The LAM has the competency to manage and store the<br />
configuration and updates releases and to <strong>de</strong>termine which one should be <strong>de</strong>ployed for a <strong>de</strong>vice.<br />
The DCUs are the last <strong>de</strong>vices with the functionality to communicate with the management servers. The<br />
end <strong>de</strong>vices could be configured or updated by the DCU, e.g. they provi<strong>de</strong> the necessary features for<br />
configuring <strong>de</strong>vices that can not or should not directly communicate over the network protocol. On top<br />
of the LAM servers are one or more layers of Wi<strong>de</strong> Area Management (WAM) servers. They exten<strong>de</strong>d<br />
the functionality of LAMs for coordination and synchronization tasks.<br />
To <strong>de</strong>velop an efficient methodology for configuration and update management it is important to offer<br />
a facility to <strong>de</strong>scribe relationships between <strong>de</strong>vice classes and configurations of them. Due to these<br />
<strong>de</strong>mands we <strong>de</strong>ci<strong>de</strong>d to use the object oriented UML technology.<br />
Both configurations and updates are <strong>de</strong>scribed and mo<strong>de</strong>lled by an UML scheme. Using the UML input,<br />
the management system will be able to automatically synthesize instances of the classes. These instances<br />
are <strong>de</strong>scribed using XML. The XML co<strong>de</strong>d data contain all parameters nee<strong>de</strong>d to communicate between<br />
management system and managed <strong>de</strong>vices. These files could contain both information about a current<br />
configuration of a <strong>de</strong>vice and binary co<strong>de</strong> to update a <strong>de</strong>vice.<br />
The information gain of the XML Documents will be saved in a <strong>de</strong>centralized database located in all<br />
servers through the architecture. Using the database the management system will be enabled to supervise<br />
the configurations states of all managed <strong>de</strong>vices.<br />
10.5.5.3 Research Work<br />
A preliminary prototype system was already <strong>de</strong>veloped to show proof of concept. Additional research is<br />
necessary for implementing the full data flow.<br />
The focus of research work is<br />
• A new algorithm for the <strong>de</strong>centralized management of configurations and update releases.<br />
• An algorithm to recover the last working configuration in case of errors<br />
• Test and performance evaluation<br />
10.6 Computing<br />
The last stage of the readout chain consists of a compute farm for processing complete events in realtime.<br />
This High Level Processing System (HLPS) will be built with commodity processing elements<br />
connected by a commodity network. While technical implementations cannot be predicted at this point<br />
of time, the physics requirements are well <strong>de</strong>fined and concepts for processing mo<strong>de</strong>ls can be discussed.<br />
10.6.1 Physics requirements<br />
The accelerator complex will <strong>de</strong>liver beams of heavy ions and protons to the experiment for about<br />
5·10 6 seconds per year, stretched over 4-5 months (see section 11). Four main physics programs are<br />
envisioned at the moment; two programs for the measurement of rare signals (J/ψ and open charm),<br />
which have such a distinct <strong>de</strong>cay topology that the event selection system <strong>de</strong>scribed in section 10.4 can<br />
reject background events. The other observables are either indistinguishable from the background on an<br />
individual basis (low-mass di-lepton pairs) or abundant enough in a minimum bias event sample.
272 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
• J/ψ<br />
A signal rate of 0.3 Hz is expected at an interaction rate of 10 MHz for Au+Au collisions. The<br />
irreducible background rate in the current experimental setup is 50 Hz which is negligible compared<br />
to the bandwidth of the archiving system - assuming an efficient event selection scheme.<br />
The estimated run time is one year of Au+Au, one year of A+A and several months of p+p (see<br />
section 11).<br />
• Open charm<br />
A signal rate of 0.6 Hz is expected at an interaction rate of 10 MHz for Au+Au collisions. A<br />
reduction of the background rate to less than the maximum output of the DAQ (25 kHz) seems<br />
achievable. This program can run in parallel to the J/ψ program.<br />
• Low-mass di-lepton pairs<br />
No event selection scheme is applicable here because the signal cannot be uniquely i<strong>de</strong>ntified<br />
in an individual event but has to be <strong>de</strong>duced from ensembles. Therefore, the interaction rate<br />
cannot exceed the maximum input rate into the high level processing farm and/or the output to the<br />
permanent storage (25 kHz), yielding a signal rate of 0.5 Hz. The expected run time is 36 weeks<br />
for A+A collisions and 30 weeks for p+p and p+A interactions.<br />
• Hyperons<br />
The hyperon program is a subset of the low-mass di-lepton pair run.<br />
10.6.2 Event structure<br />
The multiplicity of charged primary particles produced in a central Au+Au collision at 25 AGeV is 900,<br />
out of which 600 charged tracks will be <strong>de</strong>tected (and in addition gammas and neutrons in the ECAL).<br />
The data structure in the front-end is dictated by the self-triggered electronics and the push architecture<br />
and is portioned into time slices which may contain one or up to 100 events. We assume that the frontend<br />
electronics and level-1 event selection will reduce the raw data information - consisting of clusters<br />
of ADC counts, characterized by time stamps and organized in time slices - into single event structures<br />
containing hit information.<br />
10.6.2.1 Event size<br />
The main tracking <strong>de</strong>vice is the Silicon Tracker System (STS) consisting of 3 layers inner tracker (ITS)<br />
and 4 silicon strip layers. 600 charged tracks will create 4200 hits, beam <strong>de</strong>ltas will add another 300<br />
hits of incoherent background in the ITS. After the first levels of processing, only hit coordinates, charge<br />
sums and tracking parameters for each event will be passed on to high level processing. The data volume<br />
is estimated to be 17 kbyte ITS data, 20 kbyte for the strips and 60 kbyte of track information.<br />
The occupancy in the RICH <strong>de</strong>tector is assumed to be 10%, resulting in a data volume per event of about<br />
10 kbyte.<br />
The TRD consists of three stations with 12 planes in total. Assuming local pattern recognition and data<br />
reduction, the event size into the high level system is about 40 kbyte of hit information and 60 kbyte of<br />
tracking parameters; amounting to 100 kbyte. In addition to these hits, we expect secondary tracks to<br />
contribute to the data volume by a similar amount of hits, so that the total volume increases to about<br />
200 kbyte.<br />
The ECAL adds about 20 kbyte (assuming 25% occupancy and local tower analysis), the RPC produces<br />
about 8 kbyte.
10.6. Computing 273<br />
The total event size of a central collision - processed hits, tracking parameters etc. - is therefore<br />
335 kbyte. Running at 25 kHz with minimum bias events (the average event size is about 1/4 of a central<br />
collision) will result in a data rate of about 2.1 Gbyte/s into the high level processing system. The lowlevel<br />
event selection will certainly bias the data sample towards more central collisions, so the data rate<br />
could be as high as 4.2 Gbyte/s.<br />
After reconstruction and physics analysis the HLPS adds the event summary to the data stream (see the<br />
following paragraphs). Some of the intermediate information may be dropped or compressed, so the final<br />
data rate to be archived is estimated at 4.6 Gbyte/s.<br />
10.6.2.2 Event hierarchy<br />
The inter<strong>de</strong>pen<strong>de</strong>ncies between the various <strong>de</strong>tector data <strong>de</strong>termine the hierarchy of processing steps and<br />
the <strong>de</strong>gree of parallelization. The STS provi<strong>de</strong>s the primary vertex position, track impact parameters,<br />
primary track momenta, secondary vertices and secondary track momenta. The TRD provi<strong>de</strong>s track<br />
trajectories (straight lines) which can be mapped into track momenta for primary tracks. Together with<br />
the charge information, the TRD can i<strong>de</strong>ntify high momentum electrons by itself. Matching these tracks<br />
with the ones in the STS would improve the momentum resolution and allow to distinguish secondary<br />
from primary tracks. The RICH provi<strong>de</strong>s PID but needs track trajectories and track momenta (taken<br />
from the STS). The same holds true for the RPC (TRD tracks or STS + TRD tracks). The ECAL finally<br />
provi<strong>de</strong>s information on energy, position and PID.<br />
10.6.3 High level event reconstruction<br />
The main steps in the event reconstruction are the TRD tracking and momentum fitting, track fitting and<br />
primary and secondary vertex finding in the STS and a global trajectory fit (STS, TRD and hits and the<br />
PID <strong>de</strong>tectors), followed by an analysis of the <strong>de</strong>tectors providing PID. Two processing scenarios will be<br />
pursued:<br />
• Flat scenario: Starting from the raw data a full event is reconstructed at once. Results from pattern<br />
recognition at the lower levels may be used as seeds.<br />
• Hierarchical scenario: The results of the in<strong>de</strong>pen<strong>de</strong>nt sub-event reconstruction at the lower levels<br />
are used as input to the global reconstruction, which combines the various processed <strong>de</strong>tector<br />
information.<br />
The hierarchical approach takes advantage of the event reconstruction steps performed partially in hardware<br />
and avoids the duplication of the processing of the i<strong>de</strong>ntical raw data fragments. However, this may<br />
result in a slight loss of efficiency and/or resolution if the <strong>de</strong>tector response and the low level pattern<br />
recognition is not fully un<strong>de</strong>rstood.<br />
Besi<strong>de</strong>s the creation of Event Summary Data (ESD) as the result of a full event reconstruction, the<br />
High-Level Processing System provi<strong>de</strong>s an online analysis of the physics observables like weak <strong>de</strong>cay<br />
topologies and invariant mass spectra of leptons pairs (low and high mass) and open charm. The size of<br />
the ESD is typically 5% - 10% of the raw data. This exten<strong>de</strong>d ESD will be passed on to the permanent<br />
archiving system optionally together with the compressed (e.g. track mo<strong>de</strong>l + packed residuals) <strong>de</strong>tector<br />
data.
274 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
10.6.4 Estimate of computing power and storage<br />
The total amount of data (raw data and processed information) accumulated in a year of running is<br />
23 Pbyte if we assume Au+Au collisions. Approximately half of the time proton-induced reactions and<br />
lighter systems will be studied. Even if the event size is smaller (about 10% in the best case), the <strong>de</strong>crease<br />
in event size might be compensated for by an increase in rate.<br />
At the beginning of 2005, 10 Tbyte of fast disks will cost about 25 k, including disk servers. The<br />
harddrive areal <strong>de</strong>nsity has been increasing by a factor two during the last years [201]. However the<br />
capacity per volume will not scale with that rate as the performance of the I/O interfaces does not scale<br />
at similar rates. The very visible trend is the use of smaller volumes. As a consequence the cost per<br />
bit is <strong>de</strong>creasing at the slower rate of 1.37 to 1.5 per year. Obviously there are many different trends<br />
conceivable. Therefore any assumptions ma<strong>de</strong> for the year 2014 may easily have an error of a factor 2.<br />
Today’s costs for slow mass storage (tape) is less: about 2.5 k for 10 TByte, but in view of the data rate<br />
of several Gbytes/s a tape solution will probably not be very applicable. For instance there is significant<br />
hid<strong>de</strong>n cost associated with magnetic tapes, such as the requirement to reprocess them periodically and<br />
their storage. The disk mass store will not require backup schemes, as there are low overhead techniques<br />
to protect against the loss of data without ternary storage. Finally there are many other emerging permanent<br />
storage techniques, such as organic memories or holographic memories. They will be monitored<br />
carefully during the <strong>de</strong>velopment of the CBM Experiment.<br />
It should be noted in this context that there is a large variety of advanced data compression techniques,<br />
taking into account the physics signature of the data. It has been shown that standard lossless compression<br />
schemes, e.g. entropy coding, can reduce the raw data volume to 50% [202], while advanced<br />
techniques like e.g. track and cluster mo<strong>de</strong>lling are able to compress the raw data volume of tracking<br />
<strong>de</strong>tectors by a factor of 10 and more [203]. Such methods assume a good knowledge of the <strong>de</strong>tector performance<br />
and will therefore be not very efficient in the first year of data taking, but the experiment will<br />
not run at full luminosity and read-out rate in the beginning anyhow. Assuming that the CBM-<strong>de</strong>tector<br />
data can be compressed by such advanced methods by a factor of 5 and that only this information is<br />
stored together with the exten<strong>de</strong>d ESDs, the <strong>de</strong>mand on the mass storage shrinks to about 5 Pbyte/year.<br />
Timing measurements of processing data from existing <strong>de</strong>tector systems and from <strong>de</strong>tailed simulations<br />
for future experiments are used to estimate the computing power nee<strong>de</strong>d for the full reconstruction of<br />
CBM-events. The NA49 experiment has recor<strong>de</strong>d central Au+Au collisions at 30 AGeV and its acceptance<br />
roughly matches the one of CBM, but the number of space points per track is much larger (about<br />
a factor of 10). The reconstruction is not optimized for speed. It takes approx. 4 minutes to reconstruct<br />
a central event. Assuming that the cluster finding and track fitting scales with the number of hits, one<br />
can predict a timing of 24 seconds for CBM on a processor with a performance of 1 kSI2k. Detailed<br />
simulations of the performance of the tracking system of the CMS and the ALICE experiments have<br />
been performed. The CMS tracker is very similar to the CBM, i.e. several layers of pixel and strip<br />
<strong>de</strong>tectors. The DAQ-TRD [204] reports a tracking performance of 0.35 seconds for about 10 tracks in a<br />
b-jet (8 layers, on a 1 GHz CPU corresponding 1 kSI2k). The seed finding takes less than 10%. Extrapolating<br />
the performance to 600 tracks would give a timing of 210 seconds, but it is not clear how much<br />
of the processing time is due to pile-up. The ALICE barrel tracker consists of the TPC as the pattern<br />
recognition <strong>de</strong>vice and 6 layers of silicon <strong>de</strong>tectors, the ITS (2 pixel, 2 drift and 2 strip <strong>de</strong>tectors). The<br />
trackers for the High Level Trigger in ALICE have been optimized for speed without <strong>de</strong>teriorating the<br />
tracking efficiency and resolution. Both trackers, a cluster fin<strong>de</strong>r / track follower approach and a Hough<br />
transformation tracker, need about 3 seconds on a 1 kSI2k machine. Taking these tracks as seeds for a<br />
Kalman filter into the ITS, one needs one additional second for the global track fit.<br />
Today’s machines typically have a compute power of 2 kSI2k. If one would try to analyse level-1 selected<br />
CBM-events (about 1/2 of the multiplicty of a central collision) today, one would need about one second
10.7. CBM Simulation and Analysis Framework 275<br />
(ALICE HLT) or 6 seconds (NA49) per event. Processing at 25 kHz would require 2500 (150000 resp.)<br />
CPUs. Assuming an increase of the computational performance at equal cost of either 30% per year or a<br />
factor 2 in 18 months, the number of CPUs would <strong>de</strong>crease in 2015 by a factor of 14 - 100, resulting in<br />
250 - 900 CPUs in the case of a fast optimized tracker. Clusters of such a size and even larger ones are<br />
state-of-the-art today. The cost of a 900 CPU cluster is about 2 M.<br />
10.6.5 Offline computing<br />
Taking into account, (a) that the experiment will take data over several months a year, (b) that the online<br />
event selection schemes are very <strong>de</strong>manding and require a good alignment of the <strong>de</strong>tectors and an online<br />
calibration strategy and (c) the costs of the archiving and retrieving system, the online reconstruction<br />
should be sufficiently efficient and accurate so that a second reconstruction and analysis pass, called<br />
offline processing, is not necessary. Only a limited re-processing e.g. for selected events or selected<br />
sub-<strong>de</strong>tectors, may be consi<strong>de</strong>red.<br />
10.6.6 Cost estimate<br />
The costs for the HLPS cluster will be about 2 M. The yearly costs for mass storage based on fast disks,<br />
including for servers, comes in addition. Finally, the physics analysis of the ESDs requires computing<br />
power. ALICE estimates that the CPU power nee<strong>de</strong>d for reconstruction (Tier0/Tier1) is approximately<br />
the same as for analysis (Tier1/Tier2). At CBM, most of the reconstruction and some fraction of the<br />
physics analysis are already done by the online system, so 1-1.5 M for central plus 2-3 M for <strong>de</strong>central<br />
offline computing seem to be sufficient.<br />
10.7 CBM Simulation and Analysis Framework<br />
10.7.1 Introduction<br />
The <strong>de</strong>velopment of the current simulation and analysis framework has started at the end of 2003. The<br />
<strong>de</strong>cision was taken at the time to build the simulation tool for the Technical Design Reports of the CBM<br />
<strong>de</strong>tector using the OO programming technique and C++ as an implementation language.<br />
10.7.2 Design and implementation<br />
The schematic <strong>de</strong>sign of the CBM framework (CbmRoot) is shown in Fig. 10.15.<br />
The CBM framework <strong>de</strong>sign follows some basic requirements:<br />
• The framework is based on the ROOT system.<br />
• The framework should give the user the possibility to create simulated data and also to perform<br />
data analysis.<br />
• Geant3 and Geant4 transport engine should be supported.<br />
• The user co<strong>de</strong> that creates simulated data should not <strong>de</strong>pend on a particular monte carlo engine.<br />
For that purpose, the virtual monte carlo interface from the ROOT system has been used.<br />
It should also provi<strong>de</strong> some basic functionalities:
276 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing<br />
Magnet<br />
Target<br />
PIPE<br />
Cave<br />
STS<br />
TRD<br />
TOF<br />
RICH<br />
ECAL<br />
Geometry<br />
Manager<br />
GeoInterface<br />
Module<br />
Detector<br />
Field Map<br />
ROOT<br />
Magnetic<br />
Field<br />
Virtual MC<br />
Run Manager<br />
Tasks<br />
Delta<br />
Primary<br />
Generator<br />
digitizers<br />
Tracking<br />
Geant3<br />
Geant4<br />
FLUKA<br />
IO Manager<br />
RunTime<br />
DataBase<br />
EVGEN<br />
Root files<br />
MCPoints, Hits,<br />
Digits, Tracks<br />
Oracle<br />
Configuration<br />
Parameters<br />
Geometry<br />
Root files<br />
Configuration<br />
Parameters<br />
Geometry<br />
Urqmd<br />
Pluto<br />
ASCII<br />
Particle<br />
Generator<br />
Figure 10.15: Schematic <strong>de</strong>sign of the CBM simulation and analysis framework<br />
• Input/Output procedures.<br />
• Parameters <strong>de</strong>finition ( geometry of the <strong>de</strong>tectors, physic process <strong>de</strong>finition, hit digitization, etc.)<br />
• Implementation of the algorithms: the analysis should be organized in tasks.<br />
The CBM Framework incorporates these requirements by <strong>de</strong>fining the following set of classes:<br />
10.7.2.1 The Run Manager class: CbmRun<br />
This class controls the whole simulation and analysis program, providing methods to configure and<br />
add the different tasks which can be realized. For the simulation part, this inclu<strong>de</strong>s methods to set the<br />
different:<br />
• input and output files<br />
• event generators<br />
• monte carlo transport engines<br />
• magnetic field map <strong>de</strong>finitions<br />
• material and medium <strong>de</strong>finitions<br />
• passive and active <strong>de</strong>tector <strong>de</strong>finitions<br />
In the analysis case, the same class is used to organize the reconstruction process into a list of separated<br />
tasks, giving the user the possibility to switch on/off part of the reconstruction chain at run time.
10.7. CBM Simulation and Analysis Framework 277<br />
10.7.2.2 The Monte Carlo Application: CbmMCApplication<br />
This class uses the services of the ROOT Virtual Monte Carlo Application interface ( class TVirtualM-<br />
CApplication ) to <strong>de</strong>fine the actions at each stage of the simulation run. These are:<br />
• Geometry construction<br />
• Geometry initialization<br />
• Storage of primary track in an external stack container<br />
• Pre-tracking action<br />
• Stepping action and dispatching the hit processing to individual sensitive <strong>de</strong>tectors<br />
• Post-tracking action<br />
10.7.2.3 The Input/Output Manager: CbmRootManager<br />
This class is responsible of writing and reading all persistent data objects created in memory during a<br />
simulation run. The storage of all information collected by the different sensitive <strong>de</strong>tectors is done on<br />
an event by event basis (an event means in this context one interaction between one beam particle and<br />
the target). All persistent objects are serialized and stored into binary ROOT files. An interface class<br />
(CbmMCPoint) is provi<strong>de</strong>d to <strong>de</strong>fine the structure of registered hits in a <strong>de</strong>tector. Each <strong>de</strong>tector can<br />
then provi<strong>de</strong> a more specific implementation following the CbmMCPoint API. All registered hits will<br />
be collected into <strong>de</strong>dicated lists, one list corresponding to one <strong>de</strong>tector entity. The ROOT class TTree is<br />
used to organize the output data into a "ntuple like" data structure. In the analysis case, the CbmRoot-<br />
Manager provi<strong>de</strong>s methods to read this information. The user can select a subset of all registered list<br />
corresponding to his analysis tasks <strong>de</strong>finition. A partial input/ouput mechanism is supported.<br />
10.7.2.4 Parameter classes<br />
Classes to contain and to manage all the numerical information nee<strong>de</strong>d to process the data (parameter).<br />
In or<strong>de</strong>r to analyse the simulated data, several numerical parameters are nee<strong>de</strong>d, as for example, calibration/digitization<br />
parameters or geometry positions of <strong>de</strong>tectors. One common characteristic to most of<br />
these parameters is that they will go through several different versions corresponding, for example, to<br />
changes in the <strong>de</strong>tectors <strong>de</strong>finition or any other condition. This makes it necessary to have a parameter<br />
repository with a well-<strong>de</strong>fined versioning system. The runtime database (realized through the CbmRuntimeDb<br />
class) is such a repository. Different inputs are supported : Ascii format, ROOT binary format<br />
and Oracle Database input.<br />
10.7.2.5 Tasks Classes (CbmTask)<br />
For each event we need to accomplish various tasks or reconstruction algorithms. The CbmTask is<br />
an abstract class <strong>de</strong>fining a generic API allowing to execute one task and to navigate through a list of<br />
tasks. The user can create his own algorithm inheriting from CbmTask. Each task <strong>de</strong>fines the relevant<br />
input data and parameter and creates its particular output data during the initialization phase. During the<br />
execution phase, the relevant input data and parameters are retrieved from the input file and the output<br />
data objects are stored in the output file.
278 Data Acquisition, Event Selection, Controls, On-line/Off-line Computing
11 Beam requirements and run time estimate<br />
11.1 Beam requirements<br />
The research programme to be performed with the CBM experiment requires the following beam performances:<br />
• Heavy-ion beam intensities of 10 9 particles per second up to the energies of 35 AGeV for U and<br />
45 AGeV for nuclei with Z = 0.5 A.<br />
• Proton beams with intensities of 10 10 protons per second up to an energy of 90 GeV<br />
• Beam spot at the target position not larger than 5 mm 2 .<br />
• The beam profile should be very narrow, the intensity outsi<strong>de</strong> a radius of 3 mm from the beam axis<br />
(halo) should be below 10 −6 of the total beam intensity in or<strong>de</strong>r to avoid damages of the Silicon<br />
Pixel <strong>de</strong>tectors.<br />
• The beam intensity fluctuations should not exceed a factor of 2 with respect to the average value<br />
during extraction.<br />
11.2 Runtime estimate<br />
The envisaged experimental programme inclu<strong>de</strong>s the following topics:<br />
• Compressed baryonic matter studies: systematic investigation of nucleus-nucleus (A+A) collisions<br />
at beam energies ranging from 2 - 45 AGeV (Z/A = 0.5) and up to 35 AGeV for Z/A = 0.4;<br />
• Measurements on the production of strangeness, low-mass vector mesons, open and hid<strong>de</strong>n charm,<br />
and bottonium and in proton-nucleus collisions up to energies of 90 GeV. These data serve as<br />
reference for heavy-ion collisions (nuclear matter at saturation <strong>de</strong>nsity). Moreover, data on charm<br />
and bottom production at threshold energies (which do not exist up to now) will shed light on the<br />
production mechanisms of heavy quarks.<br />
• Measurement of elementary production cross sections of charm (charmonium, D mesons), light<br />
vector mesons, multistrange hyperons, and exotica like pentaquarks etc. in proton-proton collisions<br />
at beam energies up to 90 GeV.<br />
The Data Acquisition (DAQ) System of CBM will be able to record minimum-bias heavy-ion collision<br />
events at a rate of 25 kHz. A high-speed trigger system will be used for the measurement of rare probes<br />
such as charmonium, and D mesons.<br />
279
280 Beam requirements and run time estimate<br />
11.2.1 Nucleus-nucleus collisions<br />
11.2.1.1 J/ψ meson measurements<br />
The J/ψ multiplicity is expected to be about 5 · 10 −6 per minimum bias Au+Au collision at 25 AGeV<br />
[205]. This value is assumed to be one quarter of the value for central collisions (see figure 11.1).<br />
Taking into account the branching ratio of 6% for the <strong>de</strong>cay into a lepton pair and the efficiency (incl.<br />
acceptance and trigger) of 0.1 the <strong>de</strong>tected J/ψ yield is about 3 · 10 −8 per event. At a reaction rate of 10<br />
MHz the number of recor<strong>de</strong>d J/ψ mesons is about 2.6 · 10 4 per day. For the J/ψ measurement the trigger<br />
will require an (i<strong>de</strong>ntified) e+e- pair with a transverse momentum above 1 GeV/c for each lepton. The<br />
primary reaction rate of 10 MHz will be reduced by the trigger conditions down to a level which can be<br />
handled by the DAQ system.<br />
beam energy J/ψ mult. J/ψ yield runtime<br />
(AGeV) min. bias <strong>de</strong>tected per week (weeks)<br />
10 5 · 10 −8 1.8 · 10 3 10<br />
15 6 · 10 −7 2.2 · 10 4 10<br />
20 2 · 10 −6 7 · 10 4 10<br />
25 5 · 10 −6 1.8 · 10 5 5<br />
30 1.0 · 10 −5 3.6 · 10 5 2<br />
35 1.5 · 10 −5 5.4 · 10 5 1<br />
Figure 11.1: D mesons and J/ψ multiplicities<br />
calculated for central Au+Au<br />
collisions using the HSD transport co<strong>de</strong><br />
Table 11.1: Expected statistics and run time for J/ψ measurements in minimum bias Au+Au collisions<br />
The total run time for the J/ψ measurements in the Au+Au system amounts to about 1 year including<br />
commissioning (see table 11.1). Another year is planned for an intermediate mass system (A=100) and<br />
for a light collision system such as C+C up to 45 AGeV beam energy. The integral run time for J/ψ<br />
measurements in A+A collisions is about 2 years.<br />
11.2.1.2 D meson measurements<br />
According to figure 11.1 the D 0 meson multiplicity is about 1.2 · 10 −4 for central Au+Au collision at<br />
25 AGeV corresponding to 3 · 10 −5 for minimum bias collisions. Taking into account the branching
11.2. Runtime estimate 281<br />
ratio of about 4% for the <strong>de</strong>cay into a kaon-pion pair, a geometrical acceptance of 0.5, and a trigger<br />
efficiency of 0.1 the <strong>de</strong>tected D 0 yield is 6 · 10 −8 per event. According to first estimates (see chapter 18)<br />
it will be possible to <strong>de</strong>velop a D 0 meson trigger based on the displaced vertex of the kaon and the pion.<br />
This requires high-resolution online tracking and particle i<strong>de</strong>ntification. According to the simulations<br />
it should be possible to reduce the primary reaction rate of 10 MHz to about 10 kHz by the trigger<br />
(suppression factor of about 1000). Consequently, the recor<strong>de</strong>d number of D 0 mesons in minimum bias<br />
Au+Au collisions at 25 AGeV is about 0.6 per second and about 5 · 10 4 per day. The D 0 measurements<br />
can be performed in parallel to the J/ψ experiments. In addition we will measure charged D mesons via<br />
their <strong>de</strong>cay into a kaon and two pions.<br />
beam energy D 0 mult. D 0 yield runtime<br />
(AGeV) min. bias <strong>de</strong>tected per week (weeks)<br />
15 7 · 10 −7 8 · 10 3 10<br />
20 7 · 10 −6 8 · 10 4 10<br />
25 3 · 10 −5 3.3 · 10 5 5<br />
30 7 · 10 −5 8 · 10 5 2<br />
35 1.3 · 10 −4 1.5 · 10 6 1<br />
Table 11.2: Expected statistics and run time for D 0 meson measurements in minimum bias Au+Au collisions<br />
11.2.1.3 Low-mass vector meson measurements<br />
The ρ-meson multiplicity is about 22 per central Au+Au collision at 25 AGeV corresponding to about 5<br />
per minimum bias collision. The branching ratio for the <strong>de</strong>cay into an electron-positron pair is 4.5·10 −5 .<br />
Assuming a <strong>de</strong>tection efficiency of 0.1 (incl. geometrical acceptance) the number of measured ρ-mesons<br />
is expected to be about 2.2 · 10 −5 per event. The combinatorial background in the electron-positron<br />
invariant mass spectrum has two major sources: Dalitz <strong>de</strong>cays of the π0 (and η )-mesons and γ-conversion<br />
in the target and the <strong>de</strong>tector materials. The gamma rays stem predominantly from π0 <strong>de</strong>cays. According<br />
to simulations, about 40 Cherenkov rings are found in the RICH <strong>de</strong>tector in a central Au+Au collision<br />
at 25 AGeV. Consequently, a trigger on double rings will not reduce consi<strong>de</strong>rably the primary reaction<br />
rate. Therefore, for the following beam time estimate we do not assume to use a trigger.<br />
Figure 11.2: Multiplicity of low-mass<br />
vector mesons calculated for central<br />
Au+Au collisions using the HSD transport<br />
co<strong>de</strong><br />
With a recor<strong>de</strong>d minimum bias event rate of 25 kHz (about 2 · 10 9 events per day, corresponding roughly<br />
to the statistics in figure 4.4), we expect to record about 5 · 10 4 ρ-mesons per day for Au+Au collisions
282 Beam requirements and run time estimate<br />
at 25 AGeV. The production of low-mass vector mesons will be systematically studied in A+A collisions<br />
for various A in the beam energy range from 8 to 45 AGeV. Assuming a run time of 2 weeks for each<br />
A+A system with A = 200, 100, 12 and 6 energy steps the total run time is about 36 weeks beam on<br />
target.<br />
11.2.1.4 Hyperons, antiprotons, event-by-event fluctuations, collective flow phenomena, exotica<br />
No <strong>de</strong>dicated trigger is required for the measurement of (multi-strange) hyperons, of antiprotons, of<br />
fluctuations and of hadron flow. For example, the multiplicity of Ω − -hyperons in Au+Au collisions is<br />
about 4 · 10 −2 . Assuming a <strong>de</strong>tection efficiency of 1 % and a minimum bias event rate of 25 kHz we can<br />
collect about 10 Ω − per second.<br />
Moreover, the CBM <strong>de</strong>tector is well suited to search for exotic objects like multiquark systems, shortlived<br />
multistrange clusters, kaonic bound systems, etc.<br />
Billions of minimum bias events can be taken within one day. The data can be taken either in short<br />
<strong>de</strong>dicated runs or in parallel to other measurements with a down-scaled minimum bias trigger.<br />
11.2.1.5 Medium energy research programme with HADES<br />
The beam energy range between 2 and 8 AGeV can be studied with the HADES spectrometer. The<br />
research program inclu<strong>de</strong>s the measurement low-mass-vector mesons (ρ,ω,φ ) and hadrons in nucleusnucleus,<br />
proton-nucleus and proton-proton collisions. The integral run time is expected to be about 2<br />
years.<br />
11.2.2 Proton-nucleus and proton-proton collisions<br />
11.2.2.1 J/ψ meson measurements<br />
One year of run time is nee<strong>de</strong>d for the J/ψ measurements in proton-nucleus collisions using three different<br />
nuclear targets and about 10 proton beam energies. Several months of run time is nee<strong>de</strong>d for the<br />
measurement of the J/ψ production excitation function in proton-proton collisions at beam energies close<br />
to the threshold.<br />
11.2.2.2 D meson measurements<br />
The D meson measurements in p+A and p+p collisions are particularly important as a reference for the<br />
A+A data. No data on D meson production are available at proton energies below 200 GeV. We plan to<br />
measure the excitation function of open charm production in proton induced reactions (targets H, C, Au)<br />
from threshold beam energies to 90 GeV. Like in A+A collisions, the D meson measurements will run in<br />
parallel to the charmonium experiments.<br />
11.2.2.3 Low-mass vector meson measurements<br />
The production of low-mass vector mesons will be systematically studied in p+A and p+p collisions for<br />
various A in the beam energy range from 8 up to 90 GeV for proton beams. As we have not anticipated<br />
a <strong>de</strong>dicated trigger for low-mass vector mesons, we will also take data on hyperons, antiprotons, and<br />
exotica during these measurements. For these proton induced reactions we expect a total run time of<br />
about 30 weeks.
11.2. Runtime estimate 283<br />
11.2.2.4 Exploratory study of Bottonium and B-meson production<br />
The production cross section of bottonium has not been measured in proton-induced reactions below<br />
proton energies of about 200 GeV. The ϒ meson can be i<strong>de</strong>ntified via its dilepton <strong>de</strong>cay which has a<br />
branching ratio of 2.4% for ϒ → e + e − and 2.5% for ϒ → µ + µ − . The production threshold for upsilon<br />
(mass 9.46 GeV/c 2 ) in p+p collisions (fixed target) is at a laboratory energy of about 65 GeV. Extrapolating<br />
from 200 GeV down to 90 GeV one estimates a cross section for upsilon production of about<br />
0.1 pb/nucleon [206] for proton-nucleus collisions (corresponding to about 0.02 nb for p+Au collisions).<br />
With a reaction cross section for p+Au of 1.5 b one obtains a ϒ multiplicity of about 10 −11 . Assuming<br />
a proton beam intensity of 1 · 10 10 /s and a 5% interaction target, the rate of produced ϒ mesons then is<br />
0.005/s. Taking into account the branching ratio and a <strong>de</strong>tection efficiency of 5%, the rate of measured<br />
ϒ mesons is about 0.02 per hour or 13 ϒ per month.<br />
The production cross section for open beauty production in proton-nucleus collisions has been measured<br />
at 800 GeV [207]. B ± mesons <strong>de</strong>cay into J/ψ and a K meson with a branching ratio of 10 −3 , and can<br />
be i<strong>de</strong>ntified by a displaced vertex of a J/ψ meson. By extrapolating theoretical calculations down to<br />
90 GeV one estimates a cross section for B ± meson production of about 1 pb/nucleon [206] for protonnucleus<br />
collisions (corresponding to about 0.2 nb for p+Au collisions). With a reaction cross section for<br />
p+Au of 1.5 b one obtains a B ± meson multiplicity of about 10 −10 . Assuming a proton beam intensity of<br />
1·10 10 /s and a 5% interaction target, the rate of produced B ± mesons then is 0.05/s. Taking into account<br />
the branching ratio of 10 −3 and a <strong>de</strong>tection efficiency of 5%, the rate of measured B ± mesons is about<br />
0.01 per hour corresponding to about 7 B ± per month.<br />
According to these estimates a <strong>de</strong>cent measurement of open or hid<strong>de</strong>n beauty at SIS 300 energies would<br />
require higher beam intensities than 10 10 protons per second. On the other hand, the production cross<br />
sections close to threshold are not known, and an exploratory measurement with a run time of about 1<br />
month should be performed.
284 Beam requirements and run time estimate
Part III<br />
Physics performance<br />
285
12 Experimental conditions<br />
12.1 Hit <strong>de</strong>nsities and rates<br />
The expected particle rates and hit <strong>de</strong>nsities have been calculated for inclusive and central Au+Au<br />
collisions at 25 AGeV. The events are generated by UrQMD and transported through the setup using<br />
GEANT4. The setup comprises the following <strong>de</strong>tector subsystems: 7 Silicon Tracking Stations insi<strong>de</strong> a<br />
dipole magnet with field on, the RICH <strong>de</strong>tector, 3 TRD stations, the RPC stop wall, and the ECAL. The<br />
particle yields inclu<strong>de</strong> both primary charged particles as generated by UrQMD, and secondary charged<br />
particles - mostly electrons and positrons - created in the <strong>de</strong>tector materials. The primary and secondary<br />
particle yields are shown separately and summed up in figure 12.1.<br />
number of charged particle / event<br />
1200<br />
1000<br />
800<br />
600<br />
400<br />
200<br />
all<br />
primary<br />
secondary<br />
0 2 4 6 8 10 12<br />
z (m)<br />
Figure 12.1: Number of charged particles from central Au+Au collisions at 25 AGeV as registered by the <strong>de</strong>tector<br />
stations along the beam axis according to a calculation using UrQMD and GEANT4. Red curve: primaries, blue<br />
curve: secondaries, black curve: sum of both.<br />
The two-dimensional hit-<strong>de</strong>nsity distributions in the last STS station, in the 3 TRD stations, in the RPC,<br />
and in the ECAL are shown in figure 12.2. The charged particle yields are calculated for central Au+Au<br />
collisions at 25 AGeV, and inclu<strong>de</strong> both primaries and secondaries. The yields in the ECAL inclu<strong>de</strong> also<br />
neutral particles (gammas and neutrons).<br />
The one-dimensional hit <strong>de</strong>nsity distributions for central Au+Au collisions at 25 AGeV are presented in<br />
figure 12.3 for the first 6 Silicon Tracking Stations, and in figure 12.4 for the last STS station, the 3 TRD<br />
stations, the RPC, and the ECAL. The distributions are calculated along the horizontal (red histograms)<br />
and the vertical symmetry axis (blue histograms) of the <strong>de</strong>tectors.<br />
The expected rates calculated for inclusive Au+Au collisions at 25 AGeV (at a reaction rate of 10 MHz)<br />
are presented in figure 12.5 for the first 6 Silicon Tracking Stations, and in figure 12.6 for the last STS<br />
station, the 3 TRD stations, the RPC, and the ECAL.<br />
287
288 Experimental conditions<br />
STS7, z = 1(m)<br />
y (cm)<br />
50<br />
40<br />
30<br />
20<br />
10<br />
0<br />
-10<br />
-20<br />
-30<br />
-40<br />
-50<br />
-50 -40 -30 -20 -10 0 10 20 30 40 50<br />
TRD2, z = 6(m)<br />
y (cm)<br />
400<br />
300<br />
200<br />
100<br />
0<br />
-100<br />
-200<br />
-300<br />
x (cm)<br />
-400<br />
0<br />
-400 -300 -200 -100 0 100 200 300 400<br />
TOF, z = 10(m)<br />
y (cm)<br />
600<br />
400<br />
200<br />
0<br />
-200<br />
-400<br />
x (cm)<br />
-600<br />
0<br />
-600 -400 -200 0 200 400 600<br />
x (cm)<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
0<br />
0.022<br />
0.02<br />
0.018<br />
0.016<br />
0.014<br />
0.012<br />
0.01<br />
0.008<br />
0.006<br />
0.004<br />
0.002<br />
0.01<br />
0.008<br />
0.006<br />
0.004<br />
0.002<br />
TRD1, z = 4(m)<br />
y (cm)<br />
y (cm)<br />
300<br />
200<br />
100<br />
0<br />
-100<br />
-200<br />
-300<br />
0<br />
-300 -200 -100 0 100 200 300<br />
TRD3, z = 8(m)<br />
500<br />
400<br />
300<br />
200<br />
100<br />
0<br />
-100<br />
-200<br />
-300<br />
-400<br />
x (cm)<br />
-500<br />
0<br />
-500-400-300-200-100 0 100 200 300 400 500<br />
ECAL, z = 12(m)<br />
x (cm)<br />
-800<br />
-800 -600 -400 -200 0 200 400 600 800<br />
Figure 12.2: Two-dimensional <strong>de</strong>nsity distributions (hits/cm 2 ) of charged (primary and secondary) particles in<br />
the last STS station, in the 3 TRD stations, in the RPC and in the ECAL for central Au+Au events at 25 AGeV.<br />
The hits in the ECAL inclu<strong>de</strong> both charged particles and neutrals (gammas and neutrons).<br />
y (cm)<br />
800<br />
600<br />
400<br />
200<br />
0<br />
-200<br />
-400<br />
-600<br />
x (cm)<br />
0.04<br />
0.035<br />
0.03<br />
0.025<br />
0.02<br />
0.015<br />
0.01<br />
0.005<br />
0.014<br />
0.012<br />
0.01<br />
0.008<br />
0.006<br />
0.004<br />
0.002<br />
0.014<br />
0.012<br />
0.01<br />
0.008<br />
0.006<br />
0.004<br />
0.002<br />
0
12.1. Hit <strong>de</strong>nsities and rates 289<br />
STS 1, z = 0.05(m)<br />
/event<br />
2<br />
Hits/cm<br />
2<br />
10<br />
10<br />
-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5<br />
cm<br />
STS 3, z = 0.2(m)<br />
/event<br />
2<br />
Hits/cm<br />
10<br />
1<br />
-10 -8 -6 -4 -2 0 2 4 6 8 10<br />
cm<br />
STS 5, z = 0.6(m)<br />
/event<br />
2<br />
Hits/cm<br />
1<br />
-1<br />
10<br />
-30 -20 -10 0 10 20 30<br />
cm<br />
STS 2, z = 0.1(m)<br />
/event<br />
2<br />
Hits/cm<br />
/event<br />
2<br />
Hits/cm<br />
2<br />
10<br />
10<br />
1<br />
10<br />
-1<br />
10<br />
-5 -4 -3 -2 -1 0 1 2 3 4 5<br />
cm<br />
STS 4, z = 0.4(m)<br />
1<br />
-20 -15 -10 -5 0 5 10 15 20<br />
cm<br />
STS 6, z = 0.8(m)<br />
/event<br />
2<br />
Hits/cm<br />
1<br />
-1<br />
10<br />
-40 -30 -20 -10 0 10 20 30 40<br />
cm<br />
Figure 12.3: Hit <strong>de</strong>nsity of charged (primary and secondary) particles from central Au+Au collisions at 25 AGeV<br />
as calculated for the first 6 Silicon Tracking Stations. The red lines show the <strong>de</strong>nsity profile along the x axis, the<br />
blue curves along the y axis. The difference between the red and blue distributions is due to the magnetic dipole<br />
field.
290 Experimental conditions<br />
STS7, z = 1(m)<br />
/event<br />
2<br />
Hits/cm<br />
1<br />
-1<br />
10<br />
-2<br />
10<br />
-50 -40 -30 -20 -10 0 10 20 30 40 50<br />
cm<br />
TRD2, z = 6(m)<br />
/event<br />
2<br />
Hits/cm<br />
10<br />
-2<br />
-3<br />
10<br />
-400 -300 -200 -100 0 100 200 300 400<br />
cm<br />
TOF, z = 10(m)<br />
/event<br />
2<br />
Hits/cm<br />
10<br />
-2<br />
-3<br />
10<br />
-600 -400 -200 0 200 400 600<br />
cm<br />
TRD1, z = 4(m)<br />
/event<br />
2<br />
Hits/cm<br />
/event<br />
2<br />
Hits/cm<br />
-2<br />
10<br />
-3<br />
10<br />
-300 -200 -100 0 100 200 300<br />
cm<br />
TRD3, z = 8(m)<br />
-2<br />
10<br />
-3<br />
10<br />
-500-400-300-200-100 0 100 200 300 400 500<br />
cm<br />
ECAL, z = 12(m)<br />
/event<br />
2<br />
Hits/cm<br />
10<br />
-2<br />
-3<br />
10<br />
-4<br />
10<br />
-800 -600 -400 -200 0 200 400 600 800<br />
cm<br />
Figure 12.4: Hit <strong>de</strong>nsity of charged (primary and secondary) particles from central Au+Au collisions at 25 AGeV<br />
as calculated for the last STS station, the 3 TRD stations, the RPC and the ECAL. The yields in the ECAL inclu<strong>de</strong><br />
both charged particles and neutrals (gammas and neutrons). The red lines show the <strong>de</strong>nsity profile along the x<br />
axis, the blue curves along the y axis. The difference between the red and blue distributions is due to the magnetic<br />
dipole field.
12.1. Hit <strong>de</strong>nsities and rates 291<br />
STS 1, z = 0.05(m)<br />
2<br />
MHz/cm<br />
2<br />
10<br />
10<br />
-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5<br />
cm<br />
STS 3, z = 0.2(m)<br />
2<br />
MHz/cm<br />
10<br />
1<br />
-10 -8 -6 -4 -2 0 2 4 6 8 10<br />
cm<br />
STS 5, z = 0.6(m)<br />
2<br />
MHz/cm<br />
10<br />
1<br />
-1<br />
10<br />
-30 -20 -10 0 10 20 30<br />
cm<br />
STS 2, z = 0.1(m)<br />
2<br />
MHz/cm<br />
2<br />
MHz/cm<br />
2<br />
10<br />
10<br />
1<br />
-5 -4 -3 -2 -1 0 1 2 3 4 5<br />
cm<br />
STS 4, z = 0.4(m)<br />
10<br />
1<br />
-20 -15 -10 -5 0 5 10 15 20<br />
cm<br />
STS 6, z = 0.8(m)<br />
2<br />
MHz/cm<br />
1<br />
-1<br />
10<br />
-40 -30 -20 -10 0 10 20 30 40<br />
cm<br />
Figure 12.5: Rates of charged (primary and secondary) particles in the first 6 Silicon Tracking Stations for<br />
minimum bias Au+Au events at 25 AGeV assuming an interaction rate of 10 MHz. The red lines show the <strong>de</strong>nsity<br />
profile along the x axis, the blue curves along the y axis. The difference between the red and blue distributions is<br />
due to the magnetic dipole field.
292 Experimental conditions<br />
STS7, z = 1(m)<br />
2<br />
MHz/cm<br />
1<br />
-1<br />
10<br />
-50 -40 -30 -20 -10 0 10 20 30 40 50<br />
cm<br />
TRD2, z = 6(m)<br />
2<br />
MHz/cm<br />
-2<br />
10<br />
-3<br />
10<br />
-400 -300 -200 -100 0 100 200 300 400<br />
cm<br />
TOF, z = 10(m)<br />
2<br />
MHz/cm<br />
-2<br />
10<br />
-3<br />
10<br />
-600 -400 -200 0 200 400 600<br />
cm<br />
TRD1, z = 4(m)<br />
2<br />
MHz/cm<br />
2<br />
MHz/cm<br />
-1<br />
10<br />
-2<br />
10<br />
-300 -200 -100 0 100 200 300<br />
cm<br />
TRD3, z = 8(m)<br />
-2<br />
10<br />
-3<br />
10<br />
-500-400-300-200-100 0 100 200 300 400 500<br />
cm<br />
ECAL, z = 12(m)<br />
2<br />
MHz/cm<br />
-2<br />
10<br />
-3<br />
10<br />
-800 -600 -400 -200 0 200 400 600 800<br />
cm<br />
Figure 12.6: Rates of charged (primary and secondary) particles in the last STS station, in the 3 TRD stations,<br />
in the RPC and in the ECAL for minimum bias Au+Au events at 25 AGeV assuming an interaction rate of 10<br />
MHz. The rates in the ECAL inclu<strong>de</strong> both charged particles and neutrals (gammas and neutrons). The red lines<br />
show the <strong>de</strong>nsity profile along the x axis, the blue curves along the y axis. The difference between the red and blue<br />
distributions is due to the magnetic dipole field.
12.1. Hit <strong>de</strong>nsities and rates 293<br />
The following tables list hit rates, hit <strong>de</strong>nsities and <strong>de</strong>tector areas for the TRD and the RPC for different<br />
emission angles. The hit <strong>de</strong>nsities refer to charged primary and secondary particles emitted in central<br />
Au+Au collisions at 25 AGeV as calculated with UrQMD. The rates are calculated for 10 MHz minimum<br />
bias Au+Au collisions at 25 AGeV. The cell size was <strong>de</strong>termined by the requirement that the occupancy<br />
is below 5 %. Due to position resolution requirements the maximum cell sizes are limited to 10 cm 2 for<br />
the TRD and to 20 cm 2 for the RPC.<br />
The <strong>de</strong>tector areas were calculated assuming an elliptic shape which takes into account the <strong>de</strong>flection of<br />
charged particles in horizontal direction, i.e. the horizontal dimension of the <strong>de</strong>tectors is 1.5 times the<br />
vertical dimension. It should be noted that for the TRD with pad readout the quoted number of cells<br />
correspond to 10% occupancy due to the fact that in average two pads fire per particle. Each of the TRD<br />
stations will consist of 3-4 layers which means that the number of electronic channels is 3-4 times larger<br />
than the number of cells quoted in the tables.<br />
emission angle [mrad] TRD 1 dist. 4 m<br />
rates area N cell size # o f cells<br />
[kHz/cm 2 ] [m 2 ] [cm −2 ] [cm 2 ]<br />
50 ÷ 100 100. 0.52 4.5·10 −2 1.1 4700<br />
100 ÷ 150 53. 0.96 2.6·10 −2 1.9 5100<br />
150 ÷ 200 26. 1.38 1.4·10 −2 3.6 3800<br />
200 ÷ 250 17. 1.82 0.78·10 −2 6.4 2800<br />
250 ÷ 300 9.6 2.29 0.46·10 −2 10. (11.) 2300<br />
300 ÷ 350 7.1 2.83 0.34·10 −2 10. (15.) 2800<br />
350 ÷ 400 4.4 3.43 0.21·10 −2 10. (24.) 3400<br />
400 ÷ 450 2.0 4.12 0.09·10 −2 10. (54.) 4100<br />
450 ÷ 500 0.9 4.91 0.04·10 −2 10. (121.) 4900<br />
sum 22.3 33900<br />
emission angle [mrad] TRD 2 dist. 6 m<br />
rates area N cell size # o f cells<br />
[kHz/cm 2 ] [cm 2 ] [cm −2 ] [cm 2 ]<br />
50 ÷ 100 50. 1.17 2.2·10 −2 2.2 5300<br />
100 ÷ 150 25. 2.17 1.3·10 −2 3.9 5600<br />
150 ÷ 200 13. 3.09 0.66·10 −2 7.5 4100<br />
200 ÷ 250 7.5 4.09 0.36·10 −2 10. (14.) 4100<br />
250 ÷ 300 5.0 5.17 0.24·10 −2 10. (21.) 5200<br />
300 ÷ 350 3.3 6.37 0.17·10 −2 10. (30.) 6400<br />
350 ÷ 400 2.1 7.72 0.10·10 −2 10. (48.) 7700<br />
400 ÷ 450 1.0 9.26 0.05·10 −2 10. (106.) 9300<br />
450 ÷ 500 0.4 11.0 0.02·10 −2 10. (240.) 11000<br />
sum 50.1 58700
294 Experimental conditions<br />
emission angle [mrad] TRD 3 dist. 8 m<br />
rates area N cell size # o f cells<br />
[kHz/cm 2 ] [cm 2 ] [cm −2 ] [cm 2 ]<br />
50 ÷ 100 32. 2.08 1.4·10 −2 3.6 5800<br />
100 ÷ 150 15. 3.85 0.7·10 −2 6.7 5700<br />
150 ÷ 200 7.9 5.50 3.9·10 −3 10. (13.) 5500<br />
200 ÷ 250 4.8 7.27 2.3·10 −3 10. (22.) 7300<br />
250 ÷ 300 2.7 9.19 1.4·10 −3 10. (36.) 9200<br />
300 ÷ 350 2.0 11.3 0.95·10 −3 10. (52.) 11300<br />
350 ÷ 400 1.3 13.7 0.65·10 −3 10. (77.) 13700<br />
400 ÷ 450 0.6 16.5 0.29·10 −3 10. (170.) 16500<br />
450 ÷ 500 0.3 19.6 0.13·10 −3 10. (383.) 19600<br />
sum 89.1 94600<br />
emission angle [mrad] TOF dist. 10 m<br />
rates area N cell size # o f cells<br />
[kHz/cm 2 ] [cm 2 ] [cm −2 ] [cm 2 ]<br />
50 ÷ 100 20. 3.19 8.9·10 −3 5.6 5700<br />
100 ÷ 150 13. 5.83 6.5·10 −3 7.7 7600<br />
150 ÷ 200 6.6 8.08 3.2·10 −3 15.7 5100<br />
200 ÷ 250 4.5 10.2 2.0·10 −3 20. (25.) 5100<br />
250 ÷ 300 2.6 12.3 1.4·10 −3 20. (37.) 6200<br />
300 ÷ 350 2.1 14.3 1.0·10 −3 20. (50.) 7100<br />
350 ÷ 400 1.8 16.1 0.69·10 −3 20. (73.) 8000<br />
400 ÷ 450 0.8 17.7 0.31·10 −3 20. (162.) 8800<br />
450 ÷ 500 0.4 19.2 0.14·10 −3 20. (365.) 9600<br />
sum 106.8 63200
12.2. Hadron multiplicities and momentum distributions from UrQMD calculations 295<br />
12.2 Hadron multiplicities and momentum distributions from UrQMD<br />
calculations<br />
Table 12.1 lists the particle multiplicities from central Au+Au collisions as calculated with the UrQMD<br />
event generator. The laboratory momenta of pions, protons, and kaons calculated with UrQMD for<br />
central Au+Au collisions are shown in the figures 12.7 for beam energies of 15, 25, and 35 AGeV.<br />
particle multiplicity per event<br />
15 25 35<br />
AGeV AGeV AGeV<br />
γ 10 14 17<br />
π + 240 332 398<br />
π − 268 362 429<br />
π 0 266 365 437<br />
η 25 36 45<br />
K + 30 41 49<br />
K − 7 13 18<br />
K 0 31 42 50<br />
p 165 161 159<br />
n 183 176 173<br />
Λ 23 28 31<br />
Σ + 7 9 10<br />
Σ 0 7 9 9<br />
Σ − 8 10 10<br />
Ξ 0 0.617 0.961 1.191<br />
Ξ − 0.637 0.983 1.210<br />
Ω − 0.011 0.022 0.033<br />
¯p 0.024 0.139 0.328<br />
¯n 0.022 0.137 0.323<br />
¯Λ 0.017 0.103 0.244<br />
Σ ¯+<br />
Σ¯ 0.005 0.031 0.072<br />
0 Ξ¯ 0.005 0.029 0.068<br />
0 0.002 0.010 0.028<br />
Ξ¯− 0.002 0.011 0.027<br />
Table 12.1: Particle multiplicities in UrQMD, central Au+Au collisions, impact parameter b=0 fm.
296 Experimental conditions<br />
yield/event<br />
yield/event<br />
yield/event<br />
10<br />
1<br />
-1<br />
10<br />
-2<br />
10<br />
-3<br />
10<br />
-4<br />
10<br />
10<br />
1<br />
-1<br />
10<br />
-2<br />
10<br />
-3<br />
10<br />
10<br />
1<br />
-1<br />
10<br />
-2<br />
10<br />
-3<br />
10<br />
Au+Au, 15 AGeV/c<br />
π+<br />
0 5 10 15 20 25 30<br />
p lab, GeV/c<br />
0 5 10 15 20 25 30<br />
p lab, GeV/c<br />
π-<br />
p<br />
K+<br />
K-<br />
Au+Au, 25AGeV/c<br />
π+<br />
0 5 10 15 20 25 30<br />
p lab, GeV/c<br />
π-<br />
p<br />
K+<br />
K-<br />
Au+Au, 35AGeV/c<br />
π+<br />
Figure 12.7: Particle yields per event as function of laboratory momentum calculated with the UrQMD mo<strong>de</strong>l<br />
for central Au+Au collisions at 15, 25, and 35 AGeV.<br />
π-<br />
p<br />
K+<br />
K-
12.3. Hadron multiplicities from HSD calculations 297<br />
12.3 Hadron multiplicities from HSD calculations<br />
As input for the simulations on rare probes like low-mass vector mesons, open and hid<strong>de</strong>n charm we use<br />
multiplicity predictions calculated with the Hadron-String Dynamics (HSD) mo<strong>de</strong>l version V2.4. The<br />
Hadron-String Dynamics (HSD) is a covariant microscopic transport mo<strong>de</strong>l <strong>de</strong>veloped to simulate pionnucleus,<br />
proton-nucleus reactions and relativistic heavy-ion collisions. The HSD transport approach<br />
provi<strong>de</strong>s the numerical test-particle solution of a coupled set of relativistic transport equations for particles<br />
with in-medium self-energies. It is based on quark, diquark, string and hadronic <strong>de</strong>grees of freedom.<br />
High energy inelastic hadron-hadron collisions are in HSD <strong>de</strong>scribed by FRITIOF 7.02 string mo<strong>de</strong>l including<br />
PYTHIA and JETSET whereas low energy hadron-hadron collisions are mo<strong>de</strong>lled on experimental<br />
cross section. The transport approach is matched to reproduce the nucleon-nucleon, meson-nucleon<br />
and meson-meson cross section data in a wi<strong>de</strong> kinematic range. Insi<strong>de</strong> HSD it has been also taken into<br />
account the formation and multiple rescattering of leading pre-hadrons and hadrons.<br />
Table 12.2 lists the particle multiplicities calculated for central Au+Au collisions. The yield of charged<br />
D mesons is un<strong>de</strong>restimated particularly for beam energies close to the threshold because the process of<br />
associated charm production via NN→DΛcN is not inclu<strong>de</strong>d in the HSD mo<strong>de</strong>l calculation.<br />
particles mass 10 15 20 25 30 35<br />
(MeV) (AGeV) (AGeV) (AGeV) (AGeV) (AGeV) (AGeV)<br />
π 0 135 221 264 300 337 361 382<br />
π − 140 233 293 333 368 397 423<br />
π + 140 201 261 298 332 361 386<br />
η 550 16 23 29 33 37 40<br />
K 0 498 21 31 37 42 47 52<br />
¯K 0 498 3 7 9 12 14 17<br />
K + 494 20 28 35 40 45 48<br />
K − 494 3 7 9 13 16 18<br />
ρ 0 775 9 15 19 23 25 26<br />
ω 0 783 19 27 34 38 42 46<br />
φ 1020 0.12 0.50 0.83 1.28 1.24 1.50<br />
Λ 1115 20 26 30 32 34 35<br />
Σ 0 1193 5.99 8.09 9.20 10.06 10.56 10.76<br />
Σ + 1189 4.19 5.69 6.55 7.18 7.72 8.74<br />
Σ − 1197 3.30 4.04 4.61 5.46 5.37 5.67<br />
Ξ 0 1315 0.13 0.20 0.34 0.40 0.45 0.45<br />
Ξ − 1321 0.18 0.22 0.32 0.48 0.33 0.42<br />
D 0 1864 1.15 · 10 −11 2.72 · 10 −7 6.67 · 10 −6 3.74 · 10 −5 1.11 · 10 −4 2.49 · 10 −4<br />
¯D 0 1864 8.76 · 10 −9 2.97 · 10 −6 3.05 · 10 −6 1.15 · 10 −4 2.78 · 10 −4 5.43 · 10 −4<br />
D + 1869 1.67 · 10 −11 3.34 · 10 −7 7.71 · 10 −6 4.17 · 10 −5 1.21 · 10 −4 2.67 · 10 −4<br />
D − 1869 6.76 · 10 −9 2.28 · 10 −6 2.34 · 10 −5 8.91 · 10 −5 2.16 · 10 −4 4.23 · 10 −4<br />
D + s 1969 2.13 · 10 −14 1.71 · 10 −8 7.50 · 10 −7 5.43 · 10 −6 1.84 · 10 −5 4.53 · 10 −5<br />
D − s 1969 2.18 · 10 −11 6.67 · 10 −8 1.26 · 10 −6 6.59 · 10 −6 1.92 · 10 −5 4.29 · 10 −5<br />
J/Ψ 3097 1.74 · 10 −7 2.44 · 10 −6 8.37 · 10 −6 1.92 · 10 −5 3.45 · 10 −5 5.49 · 10 −5<br />
Ψ ′<br />
3686 1.07 · 10 −10 1.69 · 10 −8 9.09 · 10 −8 2.56 · 10 −7 5.66 · 10 −7 9.96 · 10 −7<br />
Table 12.2: Particle multiplicities calculated for central Au+Au collisions (impact parameter of b = 0.5 fm) at<br />
different beam energies using the HSD co<strong>de</strong>
298 Experimental conditions<br />
According to the HSD mo<strong>de</strong>l the multiplicity of the low-mass vector mesons (ρ 0 , ω 0 , and φ) varies with<br />
time during the collision. This is illustrated in figure 12.8 which shows the time <strong>de</strong>pen<strong>de</strong>nt ρ (all charges),<br />
ω and φ meson multiplicities for central Au+Au collisions (impact parameter b=0.5fm) at a beam energy<br />
of 25 AGeV. We take the maximum value of the time <strong>de</strong>pen<strong>de</strong>nt yield as input for the simulations (i.e.<br />
one third of the value for ρ 0 due to isospin). These yields are plotted in figure 12.9 as function of beam<br />
energy.<br />
Figure 12.8: Yield of ρ(all charges), ω, φ mesons as function of collision time, calculated with HSD for Au+Au<br />
collisions at 25 AGeV, impact parameter b = 0.5 fm<br />
Figure 12.9: ρ 0 , ω, and φ multiplicities calculated with HSD for central Au+Au collisions (impact parameter b<br />
= 0.5 fm) as function of beam energy.
12.4. Hadron multiplicities: experimental results 299<br />
12.4 Hadron multiplicities: experimental results<br />
Hadron multiplicities have been measured at AGS and SPS in Au+Au and Pb+Pb collisions by the E802<br />
and the NA49 collaborations [208, 209, 210, 211, 212, 213]. The results are listed in table 12.3. The<br />
measured pion yields are substantially lower than predicted by the transport mo<strong>de</strong>ls UrQMD and HSD,<br />
whereas the measured K + yields are 10-20 % higher than the results of the mo<strong>de</strong>l calculations.<br />
10.6 20 30 40<br />
(AGeV) (AGeV) (AGeV) (AGeV)<br />
Apart 363±10 349±5 349±5 349±5<br />
π − 217.5±15 275±20 322±16<br />
π + 134±10 184.5±13 239±17 293±15<br />
K + 24±3 40±2 55.3±3.0 59.1±3<br />
K − 3.8±0.5 10.4±0.5 16.1±0.8 19.2±1.0<br />
φ 1.91±0.45 2.57±0.10<br />
Λ 18.1±1.9 45.6±3.4<br />
¯Λ 0.017±0.005 0.74±0.06<br />
Table 12.3: Hadron multiplicities measured in Au+Au and Pb+Pb collisions [208, 209, 210, 211, 212, 213]<br />
12.5 Knock-On electrons<br />
The flux of knock-on electrons produced by the very intense heavy-ion beam in the CBM target might<br />
<strong>de</strong>teriorate the performance of the Silicon Tracking Stations which are located in close vicinity of target.<br />
Simulations have been performed using the standard CBMRoot (version Oct 2004) and the Geant3<br />
co<strong>de</strong>. The yield of knock-on electrons seen by the Silicon Tracking stations has been calculated for the<br />
following conditions:<br />
• a gold target of 0.25 mm thickness (1% interaction probability for a gold projectile)<br />
• gold beam at an energy of 25 AGeV<br />
• Carbon vacuum pipe of 0.5 mm thickness<br />
• distance between the target and the Silicon stations of 5, 10, 20, 40, 60, 80, and 100 cm<br />
• two magnetic field configurations: a symmetric field distribution with a maximum field value of 1<br />
T (version 3), and an asymmetric field distribution with a maximum field value of 1.4 T (version<br />
4).<br />
The distribution of the knock-on electrons at the STS planes is very inhomogeneous due to the focusing<br />
properties of the magnetic field. About 20% of the electrons are focused on two hot spots, as it illustrated<br />
in figure 12.10 for the first STS stations. In this case, the electron distribution peaks at x=7 and y=± 5<br />
mm, exhibiting <strong>de</strong>nsities of up to 2.4 electrons per cm 2 and per projectile. The total number of knock-on<br />
electrons hitting the STS per gold projectile is 12, 13., 8., 1., 0.4, 0.3, 0.1 (+-4%) for the first up to<br />
the seventh STS plane, respectively. At the maximum gold beam intensity, the electron flux in the hot<br />
spot area of the first STS plane amounts up to 2.4×10 9 /(cm 2 s). This effect will <strong>de</strong>teriorate the <strong>de</strong>tection<br />
efficiency, in particular for negative particles, and will cause an enhanced radiation damage of the silicon<br />
<strong>de</strong>tectors in the hot spot zone.
300 Experimental conditions<br />
The calculation was performed with the asymmetric field configuration (1.4 T maximum field). For the<br />
symmetric field configuration with a maximum field of 1 T, the yield of knock-on electrons hitting the<br />
STS planes is higher (16 electrons per projectile in the first STS plane). This effect is due to the lower<br />
magnetic field. Due to the large off-axis value of the Bx and Bz components of the symmetric magnetic<br />
field the intensity of knock electrons in the sixth and seventh STS plane is even 10 times higher than in<br />
the case of 1.4 T field.<br />
The flux of knock-on electrons can be reduced by introducing an asymmetric lead absorber of 4 mm<br />
thickness close to the beam pipe. The conical absorber reduces the number of knock-on electrons hitting<br />
the tracking stations by about a factor of 2. The resulting electron yields in the different STS planes<br />
are shown in figure 12.11. A further reduction of the electron flux onto the STS planes by an additional<br />
magnetic field in the target area will be investigated.<br />
Y position [cm]<br />
2<br />
1<br />
0<br />
-1<br />
-2<br />
-2 -1 0 1 2<br />
X position [cm]<br />
Figure 12.10: Density distribution of knock-on electrons in the first STS plane<br />
Number of KO electrons per STS<br />
5<br />
4<br />
3<br />
2<br />
1<br />
0<br />
0 20 40 60 80 100<br />
STS Position [cm]<br />
Figure 12.11: Yield of knock-on electron per gold projectile in the 7 STS planes.<br />
2.4<br />
2.2<br />
2<br />
1.8<br />
1.6<br />
1.4<br />
1.2<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
0
13 Event reconstruction<br />
The event reconstruction in the CBM experiment is a challenging task due to the high charged particle<br />
multiplicities encountered in fixed target heavy ion collisions at the envisaged collision energies (up to<br />
700 tracks in the <strong>de</strong>tector acceptance for central Au+Au collisions at 25 AGeV). It comprises local track<br />
finding and fitting in the STS and TRD, ring finding in RICH, cluster reconstruction in ECAL, global<br />
matching between STS, RICH, TRD, TOF and ECAL, and the reconstruction of primary and secondary<br />
vertices. In this section, we present the status of algorithms un<strong>de</strong>r <strong>de</strong>velopment for fulfilling these tasks.<br />
Track reconstruction is most difficult in the STS because of the extreme hit <strong>de</strong>nsities of up to 100/cm 2<br />
in the first tracking station. Moreover, the STS is located in an inhomogeneous magnetic field causing<br />
a continuous variation of the curvature along the trajectories. The difficulties of track reconstruction in<br />
the STS are illustrated in figure 13.1 <strong>de</strong>picting a central Au+Au collision at 25 AGeV as calculated with<br />
UrQMD and GEANT. The track reconstruction routines have to fulfill the following requirements:<br />
• track reconstruction efficiency of better than 90 % also for secondary particles with low momenta,<br />
• momentum resolution better that δp/p = 1% for p > 1 GeV/c,<br />
• secondary vertex reconstruction with high efficiency and high resolution,<br />
• fast algorithms for high-resolution online triggering of displaced vertices of D mesons.<br />
The track reconstruction problem can be split into track finding and track fitting. Up to now, most efforts<br />
went into the problem of tracking in the STS as the most challenging task. Different approaches to<br />
both track finding and the reconstruction of the initial track parameters are un<strong>de</strong>r investigation. For the<br />
track finding, Hough transform, Cellular Automaton and track following methods have been used. The<br />
Kalman filter and global fitting methods like the polynomial approximation are applied to the problem<br />
of momentum reconstruction. The Kalman filter was also used for the <strong>de</strong>termination of the primary and<br />
secondary vertices.<br />
Figure 13.1: Visualisation of a simulated central Au+Au event at 25 AGeV/c beam momentum in the STS region<br />
301
302 Event reconstruction<br />
In a similar way to the tracking in the STS, the reconstruction of rings in the RICH can be separated into<br />
ring finding and fitting. For ring finding, the method of centre guidance was used as well as standalone<br />
ring fin<strong>de</strong>rs using the Hough Transform or the Elastic Net algorithm.<br />
13.1 Track finding<br />
13.1.1 Hough Transform<br />
The Hough Transform is a global tracking algorithm and therefore its number of operations is proportional<br />
to the number of hits to process. It has the advantage that it is robust against noisy or missing<br />
<strong>de</strong>tector hits and also sensitiv to ill-<strong>de</strong>fined objects. We have implemented an algorithm based on the<br />
Hough Transform for fast tracking in the STS system in or<strong>de</strong>r to investigate its hardware (e. g. FPGA)<br />
applicability for a first trigger level.<br />
The Hough transform converts the coordinates of the <strong>de</strong>tector hits of particle tracks into the space of<br />
track parameters. In the bending (x-z) plane projection, the trajectory of tracks starting from the origin<br />
(target) in z direction can be approximated as parabolas:<br />
x =<br />
n e By<br />
z<br />
2 pz<br />
2<br />
(13.1)<br />
where n is the number of elementary charges, pz the z component of the momentum and By the y component<br />
of the magnetic field. In case of an inhomogenous magnetic field By may be any function of<br />
the hit coordinates x and z. For tracks starting with an angle θ = arctan px/pz, x → zsinθ − xcosθ and<br />
z → zcosθ + xsinθ and thus<br />
1<br />
pz<br />
= 2 (zsinθ − xcosθ)<br />
ne By (zcosθ + xsinθ) 2<br />
(13.2)<br />
One track with the parameters pz and θ is represented as one point in the Hough space (see fig. 13.2 a).<br />
One measured point (x, z) can contribute to several tracks, but all these tracks obey the above equation.<br />
This leads to an appropriate curve in the Hough space (see fig. 13.2 b). Several points of one track lead<br />
to several curves in the Hough space, that all intersect at the point that <strong>de</strong>scribes the parameters of the<br />
track (see fig. 13.2 c).<br />
In the y-z-plane the tracks can be <strong>de</strong>scribed approximately as a straight line from the origin. The mapping<br />
for this case is very simple: the parameter γ = arctan py/pz can be directly calculated from y/z. Due to<br />
multiple scattering of the particles during their path through the <strong>de</strong>tector planes, the real shape of the<br />
tracks differs from an exact straight line. Therefore, also a slightly curved line has to be taken into<br />
account.<br />
The two projections lead to a 3-dimensional Hough transform according to the parameters 1/pz , px/pz<br />
and py/pz. Assuming a minimum momentum pz equivalent to a maximum bending, the Hough parameter<br />
space can be confined. After its discretisation, the transformed hits are accumulated in a histogram. Peaks<br />
in this histogram <strong>de</strong>fine the parameters of a found track in the <strong>de</strong>tector. Due to the geometrical acceptance<br />
of the <strong>de</strong>tector and according to the bending of the track, momentum cuts are applied.<br />
The Hough transform method was applied to simulated central Au+Au data, using the standard setup of<br />
the STS system. The space points of tracks in the five <strong>de</strong>tector layers foreseen to be built of silicon strips<br />
(STS3 to STS7) have been discretised in 50 µm bins to match the <strong>de</strong>tector spatial resolution. Figure 13.3<br />
illustrates the track finding procedure in the x-z projection.
13.1. Track finding 303<br />
a)<br />
b)<br />
c)<br />
x<br />
x<br />
x<br />
<strong>de</strong>tector Hough space<br />
z<br />
1/Pz<br />
one track one point<br />
<strong>de</strong>tector Hough space<br />
z<br />
1/Pz<br />
one hit one curve<br />
<strong>de</strong>tector Hough space<br />
z<br />
1/Pz<br />
five hits five curves<br />
Figure 13.2: Hough transform of a track in the x-z-plane according to 1/pz and θ. a) One track in the <strong>de</strong>tector<br />
is represented by one point in the Hough space. b) One hit in the <strong>de</strong>tector can contribute to several tracks, that<br />
are represented by a curve in the Hough space. For this application, the real curves in the Hough space are close<br />
to straight lines. c) Each hit in each layer is transformed to its appropriate curve in the Hough space. All curves<br />
intersect at the point that <strong>de</strong>scribes the parameters of the track.<br />
The tracking efficiency of the algorithm is <strong>de</strong>fined as the ratio of found tracks divi<strong>de</strong>d by all tracks with<br />
hits in at least three <strong>de</strong>tector layers and a momentum larger than 1 GeV/c. Its momentum <strong>de</strong>pen<strong>de</strong>nce is<br />
shown in figure 13.4 for 15, 25 and 35 AGeV/c beam momentum. The resolution of the Hough histogram<br />
is 127 × 383 × 191. The efficiency for tracks with a momentum less than 1 GeV/c is very low because<br />
of the confinement of the Hough space. However, for triggering on open charm and charmonium, low<br />
momentum tracks are not of interest. For momenta above 1 GeV/c, the efficiency is about constant,<br />
slightly rising towards higher momenta.<br />
Ghost tracks correspond to found peaks that are accumulated from hits of different MC tracks. The ghost<br />
θ<br />
θ<br />
θ
304 Event reconstruction<br />
Figure 13.3: One 2-dimensional Hough plane filled with transformed hits. A central plane processing the hits<br />
near the beam pipe is shown here. Planes more apart from the beam pipe contain less transformed hits. There are<br />
seven peaks in the histogram (black points) corresponding to seven found particle tracks. A peak is <strong>de</strong>fined by<br />
more than three hits in consecutive <strong>de</strong>tector layers. Six peaks can be assigned to certain MC tracks. The lower<br />
most peak corresponds to no real track, but accumulates a peak from five hits of different tracks.<br />
Figure 13.4: Track finding efficiency for tracks with hits in at least three tracking stations as function of momentum<br />
using the Hough transform method for central Au+Au events at different beam momenta<br />
rate is highest for low and high momenta. At low momenta, the track multiplicity is highest and thus<br />
combinatorial coinci<strong>de</strong>nces are more likely. Tracks at high momenta are less numerous, but correspond<br />
to almost straight lines near the beam pipe with high track <strong>de</strong>nsities. The mean numbers of efficiency<br />
and ghost rate for the three beam momenta are given in table 13.1. While the efficiency is almost the<br />
same, the ghost rate increases quickly with beam momentum.<br />
Both the efficiency and the ghost rate <strong>de</strong>pend on the multiplicity of the event, the number of <strong>de</strong>tector
13.1. Track finding 305<br />
35 GeV 25 GeV 15 GeV<br />
number of STS hits/event 5000 4000 3500<br />
efficiency (P > 1 GeV/c) 91 % 90 % 91 %<br />
ghost rate 36 % 16 % 7 %<br />
Table 13.1: Efficiency and ghost rate of tracking using the Hough transform for central Au+Au events at different<br />
beam energies<br />
layers and the resolution in the Hough space. Better results can be expected for events with less tracks and<br />
<strong>de</strong>tector setups with more <strong>de</strong>tector layers. The efficiency can be improved by increasing the resolution<br />
of the histogram of the Hough transform.<br />
In section 10.4.2.1 a possible hardware implementation for the processing of a 10 Gbit/s input data stream<br />
of <strong>de</strong>tector hit data in real time is <strong>de</strong>scribed. The time nee<strong>de</strong>d for processing a central event is of the<br />
or<strong>de</strong>r of 100µs. The algorithm, in particular the adjustment to strip <strong>de</strong>tectors, will be <strong>de</strong>veloped further<br />
when a more final state of the <strong>de</strong>tector <strong>de</strong>scription is available. An application of the Hough transform<br />
for the TRD <strong>de</strong>tector is in preparation.<br />
13.1.2 Cellular Automaton method<br />
Cellular automata have already successfully been used for data filtering and track searching in high<br />
energy physics [214, 215, 216, 217]. The use of a cellular automaton for track searching is motivated<br />
by its intrinsic simplicity resulting in consi<strong>de</strong>rably speeding up this part of the reconstruction process,<br />
which is usually the most time-consuming one.<br />
Cellular automata [218] are dynamical systems that evolve in discrete, usually two-dimensional spaces<br />
consisting of cells. Each cell can take several states. In the simplest case, the cell state can be <strong>de</strong>scribed<br />
by a single-bit: 0 or 1. The laws of evolution are local, i.e., the dynamics of the system is <strong>de</strong>termined<br />
by an unchanged set of rules (for example a table) that relates the new state of a cell to the states of its<br />
nearest neighbors. The update of the states of the cells is done simultaneously at discrete time instants.<br />
A cellular automaton possesses a number of advantageous features when used for track recognition.<br />
Being essentially local and parallel, cellular automata avoid exhaustive combinatorial searches, even<br />
when implemented on conventional computers. Since cellular automata operate with highly structured<br />
information (for instance sets of track segments connecting space-points), the amount of data to be<br />
processed in the course of the track search is significantly reduced. Further reduction of information to<br />
be processed is achieved by smart <strong>de</strong>finition of the segment neighborhood. Usually cellular automata<br />
employ a very simple track mo<strong>de</strong>l which leads to utmost computational simplicity and a fast algorithm.<br />
In the literature, two kinds of cellular automata for track searching are <strong>de</strong>scribed: algorithms which are<br />
similar to the game “Life” and use space-points as cell units [214]; segment-based algorithms which use<br />
short track segments [215, 216, 217] as cell units. Here a segment-based cellular automaton is used. A<br />
simple 2D illustration of the cellular automaton algorithm is shown in Fig. 13.5.<br />
The cellular automaton is constructed by <strong>de</strong>fining cells, neighbours, rules of evolution and time evolution.<br />
A cell is <strong>de</strong>fined as a short track segment connecting two space-points on neighbouring stations. In or<strong>de</strong>r<br />
to make the algorithm faster, only integer cell states with a simple meaning are consi<strong>de</strong>red — the cell<br />
state <strong>de</strong>fines the place of the segment in an optimising (in the sense of χ 2 ) sequence. In the beginning all<br />
cell states are set to unity because each segment can, in principle, initiate the optimal sequence.<br />
Two segments are consi<strong>de</strong>red neighbours if and only if they share a common space-point, and they form a<br />
curve which points to the target region. A parabolic representation of a track mo<strong>de</strong>l in the bending plane
306 Event reconstruction<br />
1<br />
2<br />
3 4<br />
Collect tracks Create tracklets<br />
Figure 13.5: A simple illustration of the cellular automaton algorithm. It creates tracklets, links and numbers<br />
them as possibly situated on the same trajectory, and collects tracklets into track candidates.<br />
is chosen as the simplest and therefore fastest approximation of a particle trajectory in an inhomogeneous<br />
magnetic field.<br />
The evolution process is divi<strong>de</strong>d into:<br />
• forward evolution when the automaton iteratively updates the states of all cells having neighbours;<br />
• backward pass when the automaton collects optimal sequences starting from cells with the highest<br />
states.<br />
During the forward evolution the automaton takes each cell and looks for its leftward neighbours. If there<br />
is such a neighbour and its state is equal to the cell’s state, the cell’s state will be increased by one. When<br />
the automaton completes a loop over all the cells, their previous states are simultaneously replaced by the<br />
increased ones. This process is iteratively repeated until there are no neighbouring cells with the same<br />
states. This procedure is a simplified version of the rule SAFE-PASS [218]. The forward evolution of<br />
the automaton is illustrated in Fig. 13.5. At the end of the forward evolution, the state of each cell is<br />
equal to the length of an optimising sequence that can be traced leftwards starting from this cell.<br />
The backward pass starts with investigating the set of cells that have the highest state. These cells are<br />
consi<strong>de</strong>red as the first segments of track candidates. For each cell the automaton performs a loop over the<br />
cell’s leftward neighbours looking for the best prolongation of the track candidate. To be a prolongating<br />
one a cell must have a state lower by unity. If such a cell is found, the automaton assigns it to the track<br />
candidate, looks for its leftward neighbours and so on. The candidate tracing stops when a segment with<br />
the state of unity is assigned to the candidate. The baseline algorithm marks all segments assigned to a<br />
track as used and the automaton proceeds by assembling the next track candidate starting with another<br />
cell that has the highest state and is not marked as already used.<br />
After the completion of the backward pass, an additional test of track qualities is performed. This provi<strong>de</strong>s<br />
the rejection of ghost tracks which could acci<strong>de</strong>ntally be reconstructed from hits belonging to<br />
different real tracks. A quality estimator which favours long and smooth tracks is used for each track.<br />
The algorithm was applied to central Au+Au collisions at 25 AGeV beam energy simulated by UrQMD<br />
and transported through the CBM <strong>de</strong>tector setup. A position resolution of 10 µm in the STS was assumed.<br />
For the TRD, a strip readout of 5 mm long strips with 500 µm resolution was taken. Having<br />
the inhomogeneous magnetic field in STS, we use a straight line track mo<strong>de</strong>l in the non-bending projec-<br />
5<br />
6
13.1. Track finding 307<br />
tion and a local parabolic approximation in the bending projection. In the field free region of the TRD<br />
<strong>de</strong>tector the pure straight line approach is used in the algorithm.<br />
For evaluation purposes all simulated and reconstructed tracks are subdivi<strong>de</strong>d into several categories.<br />
The “all set” comprises tracks which intersect the sensitive regions of at least three tracking stations. A<br />
“reference” track should in addition have a momentum greater than 1 GeV/c. The reference set of tracks<br />
can also inclu<strong>de</strong> tracks of particular physics interest such as secondary tracks from interesting <strong>de</strong>cays<br />
and primary tracks coming from the target region. In addition to these tracks, the “extra set” of tracks,<br />
containing low-momentum tracks, is also consi<strong>de</strong>red.<br />
Efficiency<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
0<br />
0 2 4 6 8 10 12 14 16 18 20<br />
Momentum (GeV/c)<br />
Figure 13.6: Reconstruction efficiency versus momentum of particle in the STS sub-<strong>de</strong>tector for the “all set”<br />
selection of tracks (see text)<br />
A reconstructed track is assigned to a generated particle if at least 70% of its hits have been caused by<br />
this particle. A generated particle is regar<strong>de</strong>d as found if it has been assigned to at least one reconstructed<br />
track. If the particle is found more than once, all additionally reconstructed tracks are regar<strong>de</strong>d as clones.<br />
A reconstructed track is called ghost if it is not assigned to any generated particle (70% criterion).<br />
Table 13.2 shows efficiencies of track finding in the STS <strong>de</strong>tector for all sets of tracks obtained by<br />
applying the algorithm to central Au+Au events at 25 AGeV transported through the CBM <strong>de</strong>tetcor setup.<br />
The reconstruction efficiency for reference primary tracks is 97%, while the efficiency of all reference<br />
tracks is slightly lower because of the presence of secondary tracks originating far downstream from the<br />
target region. The total efficiency (see figure 13.6) for all tracks is about 70% because of a large fraction<br />
of soft secondary tracks that suffers significant multiple scattering in the <strong>de</strong>tector material. The track<br />
mo<strong>de</strong>l must be also improved in or<strong>de</strong>r to increase the efficiency of slow tracks as they are more sensitive<br />
to the magnetic field. The clone rate is negligible; the ghost level is at 5%. The track finding efficiencies<br />
in the TRD (table 13.2) show a similar behaviour as in the STS.<br />
Track category Efficiency (%), STS Efficiency (%), TRD<br />
Reference tracks 94.89 93.32<br />
All tracks 71.45 86.67<br />
Extra tracks 23.43 60.50<br />
Clones 0.01 0.00<br />
Ghost 4.58 8.00<br />
Table 13.2: Efficiency of track reconstruction in the STS and TRD sub<strong>de</strong>tectors for central Au+Au collisions at<br />
25 AGeV
308 Event reconstruction<br />
It has to be noted that the implementation of the track finding algorithms is strongly <strong>de</strong>pen<strong>de</strong>nt on the<br />
<strong>de</strong>tailed <strong>de</strong>tector geometry and layout. There can be, for instance, two different versions of the algorithm<br />
working in projections or in space. The first version will create track candidates in projections and then<br />
combine them into space tracks. In the second approach the algorithm creates space points and then<br />
combines them into tracks. The track finding algorithm presented here finds tracks working directly with<br />
space points, thus emulating pixel <strong>de</strong>tectors. The algorithms will be further <strong>de</strong>veloped according to the<br />
STS and TRD <strong>de</strong>sign choices.<br />
13.1.3 Conformal Mapping<br />
One of the standard methods of track recognition in the magnetic field is the method of conformal mapping<br />
[220]. It is based on a hit coordinate transformation simplifying the problem of pattern recognition.<br />
In a homogeneous magnetic field charged particles follow a circular path in the bending plane. This<br />
assumption could be used as a simplest approximation for CBM dipole magnet field. In the conformal<br />
mapping method, the circular equation of the particle trajectory<br />
(x − a) 2 + (y − b) 2 = R 2<br />
is transformed into a straight line with the prescriptions:<br />
If one fixes R by imposing the relation<br />
one obtains a straight line of the form:<br />
u = x<br />
x2 y<br />
, v =<br />
+ y2 x2 .<br />
+ y2 a 2 + b 2 = R 2<br />
v = 1<br />
− ua<br />
2b b<br />
(13.3)<br />
(13.4)<br />
This straight line can then be used for pattern recognition by establishing a search road following the<br />
points, to find out which points belong to a given straight line. A fit to such a straight line in (u,v) space<br />
will then yield the coordinates of the center of the circle, a and b, and together with eq. 13.4 the radius R<br />
is also <strong>de</strong>termined.<br />
A track finding procedure for STS is based on a fast algorithm [221] with conformal mapping transformation<br />
of the hits (CM track fin<strong>de</strong>r). The track finding efficiency of this algorithm is shown in fig. 13.7.<br />
It varies from 70 to 98% for momenta greater than 1 GeV/c. The efficiency for particles with lower<br />
momenta could be improved by further tuning of the STS layout and parameters of the algorithm.<br />
13.1.4 3D track-following method<br />
The track-following method reconstructs tracks based on the hits measured in the STS tracking stations.<br />
The algorithm should be stable with respect to initial vertex coordinates and the STS geometry. We used<br />
some approaches known from [222].
13.1. Track finding 309<br />
Efficiency<br />
0.4<br />
1<br />
0.8<br />
0.6<br />
0.2<br />
0<br />
0 5 10 15 20 25 30<br />
Moment, GeV/c<br />
Figure 13.7: Track finding efficiency of the CM track fin<strong>de</strong>r as function of track momentum<br />
Figure 13.8: Prediction and search in XoZ projection<br />
Figure 13.9: Prediction and search in YoZ projection<br />
The track recognition procedure is accomplished in 3D space on both x-z and y-z projections simultaneously.<br />
The procedure alternates between both views, predicting a track position on the next station and<br />
searching for hits in the vicinity of the predicted position.<br />
Starting from the middle of the target area (see Fig. 13.9), this point is sequentially connected with all hits<br />
in the first station in y-z view, where tracks are close to straight lines. The straight lines driven via these
310 Event reconstruction<br />
two points are prolonged to the plane of the second station. All hits in an asymmetrical corridor around<br />
the intersection point are then used for fitting a parabola in x-z view (fig. 13.8) which is prolonged to the<br />
next station. Since several prolongations can happen, we set asi<strong>de</strong> corridors around each point predicted<br />
on the third station. A similar corridor is set in the y-z view on the third station. If hits are found in this<br />
limits, they are attached to the track. The method continues the track prolongation and searching for hits<br />
in corridors around the predicted position towards the outer stations.<br />
600<br />
500<br />
400<br />
300<br />
200<br />
100<br />
0<br />
-0.04 -0.03 -0.02 -0.01 0 0.01 0.02 0.03 0.04<br />
Figure 13.10: Difference between predicted and true<br />
hit x position in the 4th station<br />
1200<br />
1000<br />
800<br />
600<br />
400<br />
200<br />
0<br />
-1.5 -1 -0.5 0 0.5 1 1.5<br />
Figure 13.12: Difference between predicted and true<br />
hit x position in the 7th station<br />
1600<br />
1400<br />
1200<br />
1000<br />
800<br />
600<br />
400<br />
200<br />
0<br />
-0.05-0.04-0.03-0.02 -0.01 0 0.01 0.02 0.03 0.04 0.05<br />
Figure 13.11: Difference between predicted and true<br />
hit y position in the 4th station<br />
2500<br />
2000<br />
1500<br />
1000<br />
500<br />
0<br />
-0.2 -0.15 -0.1 -0.05 -0 0.05 0.1 0.15 0.2<br />
Figure 13.13: Difference between predicted and true<br />
hit y position in the 7th station<br />
The obvious weakness of this approach consists of its <strong>de</strong>pen<strong>de</strong>nce on the vertex initialization. This results<br />
in only 10 % of the secondary tracks to be reconstructed. The track finding efficiency for secondary tracks<br />
will be improved by removing hits already attached to found tracks and starting the algorithm from vertex<br />
positions other than the main vertex.<br />
An essential ingredient of the method is the careful calculation of corridor widths <strong>de</strong>pending on the<br />
station number and the sign of the particle charge. These parameters were obtained by Monte-Carlo
simulations of typical heavy-ion events in the STS. Since the conventional approach to use symmetrical<br />
3σ corridors had failed being too inefficient, we use the distributions of <strong>de</strong>viations between real hit<br />
positions and their predictions by prolonging straight line or parabola for all seven stations. Examples of<br />
these distributions are shown in figs. 13.10-13.13.<br />
First results with this algorithm give a track finding efficiency of 91 – 94 % for track momenta greater<br />
than 1 GeV, almost in<strong>de</strong>pen<strong>de</strong>nt on the momentum. The average number of ghost tracks, having at least<br />
one wrongly attached hit, is 1.6 per event. Further improvements rely on a reduction of the corridor<br />
widths by usage of a more realistic track mo<strong>de</strong>l and/or the Kalman filter technique.<br />
13.2 Track fitting<br />
13.2.1 Kalman filter – first approach<br />
A track fitting procedure used for the reconstruction of the track parameters is based on the Kalman filter.<br />
The Kalman filter technique has several advantages:<br />
• treatment of multiple scattering and energy loss locally by including a noise term;<br />
• inversion of a matrix with the dimension of the measurement;<br />
• in its smoother version it gives the best estimate at all measurement positions.<br />
Here we follow the implementation of the Kalman filter as it is <strong>de</strong>scribed in [216, 217, 223, 224].<br />
In general, the Kalman filter addresses the problem of trying to estimate the state vector R of a discretetime<br />
process that is gouverned by the linear stochastic difference equation [225]<br />
Rk = Ak−1Rk−1 + νk−1, k = 1,...,N, (13.5)<br />
where the matrix Ak−1 relates the state at step k − 1 to the state at step k, {ν} is the process noise – a<br />
sequence of in<strong>de</strong>pen<strong>de</strong>nt Gaussian variables which can, for example, account for the influence of multiple<br />
scattering on the state vector. The input information for the filter is a sequence of measurements {u}<br />
<strong>de</strong>scribed by a linear function of the vector R<br />
uk = HkRk + ηk, k = 1,...,N, (13.6)<br />
where the matrix Hk in this so-called measurement equation relates the state to the measurement uk. Here<br />
ηk, representing the measurement error, is a sequence of Gaussian random variables with the covariance<br />
matrix Vk.<br />
The state vector is<br />
R = (x, y, tx, ty, q/p) T , (13.7)<br />
where tx = px/pz, ty = py/pz, p is the momentum and q the charge of the track.<br />
Three procedures for the propagation of track parameters have been implemented:<br />
1. the linear extrapolator [216, 217] for fast propagation in field free regions;<br />
2. the parabolic extrapolator [223, 224] for fast estimation of the track parameters in the magnetic<br />
field;<br />
3. the fourth or<strong>de</strong>r Runge-Kutta extrapolator [223, 224] for propagation in the inhomogeneous magnetic<br />
field.
312 Event reconstruction<br />
Currently measurements of pixel and strip <strong>de</strong>tectors are implemented in the fitting procedure. The track<br />
projection matrix for a pixel <strong>de</strong>tector is straightforward. For a strip measurement with a stereo angle α<br />
the matrix H is given by:<br />
H = (cosα, sinα, 0, 0, 0). (13.8)<br />
Thus, a sub<strong>de</strong>tector (here STS or TRD) can be treated as a mixture of pixel and strip <strong>de</strong>tectors.<br />
For the <strong>de</strong>scription of material present in the <strong>de</strong>tector we use an approximate approach since tracing<br />
a trajectory through the full <strong>de</strong>scription of the <strong>de</strong>tector is prohibitive in CPU. All surfaces used in the<br />
fit are <strong>de</strong>scribed in a simplified form of cylin<strong>de</strong>rs, cones or planes. They are divi<strong>de</strong>d into three types:<br />
measurement surfaces, material surfaces, and extrapolation surfaces, at which the track parameters are<br />
required for future use.<br />
The track fit algorithm first provi<strong>de</strong>s an approximate trajectory, which is extrapolated to all surfaces to<br />
find intersections and to or<strong>de</strong>r and store all crossed surfaces. These or<strong>de</strong>red surfaces together with the<br />
hits are then used to modify the track parameters and covariance matrix taking into account multiple<br />
scattering and energy loss when a material surface is crossed [226, 227].<br />
25000<br />
20000<br />
15000<br />
10000<br />
5000<br />
Constant 2.504e+04<br />
Mean 0.0001572<br />
Sigma 0.007348<br />
0<br />
-0.05 -0.04 -0.03 -0.02 -0.01 0 0.01 0.02 0.03 0.04 0.05<br />
Resolution (p_reco-p_mc)/p_mc<br />
30000<br />
25000<br />
20000<br />
15000<br />
10000<br />
5000<br />
Constant 3.028e+04<br />
Mean 0.01027<br />
Sigma 1.208<br />
0<br />
-10 -8 -6 -4 -2 0 2 4 6 8 10<br />
Pull q/p<br />
Figure 13.14: Residuals and normalised residuals of the estimated track momentum at the track vertex z-position<br />
obtained from 1000 events of central Au+Au collisions at 25 AGeV in the asymmetric inhomogeneous magnetic<br />
field<br />
Table 13.3 and figure 13.14 show residuals and normalized residuals (pulls) of the track parameters at<br />
the track vertex z-position obtained from 1000 events of central Au+Au collisions at 25 AGeV in the<br />
inhomogeneous magnetic field. The Monte Carlo simulated tracks were transported trough the STS<br />
sub<strong>de</strong>tector and their positions were smeared with σ = 10 µm in or<strong>de</strong>r to emulate double si<strong>de</strong>d strip<br />
<strong>de</strong>tectors with orthogonal strips in x and y direction. An i<strong>de</strong>al pattern recognition has been used to<br />
test the quality of the fitting procedure. All tracks having crossed at least four <strong>de</strong>tectors are used for<br />
histogramming.<br />
Parameter Resolution Pull<br />
x 23 µm 1.05<br />
y 19 µm 1.00<br />
tx 0.63 mrad 1.02<br />
ty 0.60 mrad 1.00<br />
p 0.73 % 1.21<br />
p pv 0.63 % 1.20<br />
Table 13.3: Resolutions and pulls of the fitted track parameter distributions at the track vertex z-position. The<br />
momentum resolution is given without (p) and with (p pv ) constraint to the primary vertex
13.2. Track fitting 313<br />
A measure of the reliability of the fit are the pull distributions of the fitted track parameters. The reconstructed<br />
track parameters and covariance matrix at the vertex where the track originates are obtained by<br />
propagating the track parameters at the measurement position closest to the vertex, taking into account<br />
the remaining material traversed.<br />
Table 13.3 shows the RMS of the Gaussian fits to the residual and normalised residual distributions. All<br />
pulls are centred at zero indicating that there is no systematic shift in the reconstructed track parameter<br />
values. The distributions are well fitted using Gaussian functions with small tails caused by the various<br />
non-Gaussian contributions to the fit. The q/p pull shows slightly un<strong>de</strong>restimated errors. This can be a<br />
result of several approximations ma<strong>de</strong> in the fitting procedure mainly in the part of material treatment.<br />
It should be noted that the pulls of the slopes parameters tx, ty are most sensitive to multiple scattering,<br />
while the pull of the inverse momentum is sensitive also to the treatment of energy loss. The momentum<br />
estimation is influenced also by the accumulated error of track propagation in the magnetic field of the<br />
sub<strong>de</strong>tector. After the primary vertex is reconstructed the tracks can be refitted with additional constraint<br />
to the primary vertex position. This improves consi<strong>de</strong>rably the average track momentum resolution to<br />
0.63%.<br />
δp/p (%)<br />
2.0<br />
1.5<br />
1.0<br />
0.5<br />
0<br />
0 1 2 3 4 5 6 7 8 9 10<br />
p (GeV/c)<br />
Figure 13.15: Average momentum resolution as a function of p<br />
In table 13.3 the average momentum resolution δp/p for reconstructed tracks is shown to be 0.73%.<br />
There are two main contributions to the momentum resolution [225]:<br />
• the error due to multiple scattering is given by δp/p ∼ 1/β, which for relativistic particles is almost<br />
constant;<br />
• the error due to the position measurement is proportional to p, i.e. δp/p ∼ p.<br />
Minor effects, like imperfect track propagation in the inhomogeneous field and intrinsic features of the<br />
fitting routine influence the momentum resolution, especially for low momentum tracks. Figure 13.15<br />
shows the average momentum resolution as a function of momentum. The resolution is worse for high<br />
momentum tracks, indicating that the error in the position measurement starts to play a dominant role.<br />
The next steps in the <strong>de</strong>velopment of the Kalman track fitter will inclu<strong>de</strong> simplification and speeding up<br />
the fitting procedure in or<strong>de</strong>r to <strong>de</strong>velop a fast algorithm of fitting tracks for the online event selection.
314 Event reconstruction<br />
13.2.2 Kalman filter - second approach<br />
In a second in<strong>de</strong>pen<strong>de</strong>nt approach, we assume that un<strong>de</strong>r the conditions of the inhomogeneous magnetic<br />
field and multiple scattering of charged particles, the trajectories in the x-z plane 1 could be approximated<br />
by<br />
xk = akz 2 k + bkzk + ck, k = 1,...,7,<br />
where xk is the result of measurement, zk is the z-coordinate of the kth <strong>de</strong>tector. Thus, the fitting trajectory<br />
will be <strong>de</strong>scribed by a piecewise curve consisting of parabola fragments<br />
In or<strong>de</strong>r to formulate the Kalman filter algorithm concerning our problem, we <strong>de</strong>termine the state vector<br />
as<br />
Rk = (ak,bk,ck) T<br />
and the measurement vector as<br />
where ξk is the measurement error and Hk is the matrix<br />
uk = HkRk + ξk , (13.9)<br />
Hk = z 2 k ,zk,1 , (13.10)<br />
To start the Kalman process 13.5, we have to estimate the initial values of the state parameters and the<br />
covariance matrix of errors related to the initial state,and <strong>de</strong>termine the transformation matrix Ak. The<br />
initial values of the state parameters are the parameters of a parabola traced through the hits in the three<br />
first <strong>de</strong>tectors. The covariance matrix is <strong>de</strong>termined by the formula [228]:<br />
where<br />
⎛<br />
Z = ⎝<br />
z 2 1 z1 1<br />
z 2 2 z2 1<br />
z 2 3 z3 1<br />
cov( R) = (Z T WZ) −1 , (13.11)<br />
⎞<br />
⎛<br />
⎠,<br />
⎜<br />
W = ⎝<br />
1<br />
ξ 2 0 0<br />
0 1<br />
ξ 2<br />
0<br />
0 0 1<br />
ξ 2<br />
We assume that the transformation matrix Ak has the following form<br />
Ak =<br />
⎛<br />
⎝<br />
f k a 0 0<br />
0 f k b 0<br />
0 0 f k c<br />
⎞<br />
⎞<br />
⎟<br />
⎠. (13.12)<br />
⎠. (13.13)<br />
In case of the homogeneous magnetic field Ak is the i<strong>de</strong>ntity matrix; for an inhomogeneous magnetic<br />
field Ak may significantly differ from it. To <strong>de</strong>termine its diagonal elements, we use the hits in three<br />
consecutive <strong>de</strong>tector planes and calculate the parameters of the corresponding parabola ak−1,bk−1,ck−1.<br />
We then skip the first hit, add the next <strong>de</strong>tector plane and calculate the parameters of this parabola<br />
ak,bk,ck. Then,<br />
f k a = ak/ak−1, f k b = bk/bk−1, f k c = ck/ck−1,<br />
which <strong>de</strong>termines the transformation matrix from the state k − 1 to the state k. The analysis shows that<br />
the values fa and fb are quit close to unity, while fc significantly differs from unity.<br />
The Kalman filter algorithm as <strong>de</strong>scribed above has been applied to central Au+Au events at 25 AGeV<br />
beam energy, simulated in the CBM STS system. Only tracks with hits in all seven tracking stations<br />
were consi<strong>de</strong>red; i<strong>de</strong>al track finding and a position resolution of 10 µm were assumed. The preliminary<br />
results of the Kalman filter are compared in figure 13.16 to those obtained by a least-squares parabolic<br />
fit. Evi<strong>de</strong>ntly, the Kalman filter provi<strong>de</strong>s a more accurate momentum reconstruction than global fitting<br />
methods.<br />
1 The application of the Kalman filter in the y-z plane is analogous to that <strong>de</strong>scribed here.
13.2. Track fitting 315<br />
120<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
-0.1 -0.05 0 0.05 0.1 0.15 0.2<br />
120<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
0.24 0.25 0.26 0.27 0.28 0.29 0.3<br />
Figure 13.16: Distribution of Δp/p in central Au+Au collisions at 25 AGeV beam energy for tracks with hits<br />
in all seven STS stations. Left: Results obtained by the Kalman filter; right: results obtained with a least-squares<br />
parabolic fit.<br />
13.2.3 Parabolic approximation<br />
In contrast to the Kalman filter, this global approach to momentum reconstruction is based on the integration<br />
of the equations of motion in the field and obtains the track parameters by a least squares criterium<br />
on the hit coordinates.<br />
The equations of motion of a charged particle in a magnetic field read<br />
dβ e<br />
=<br />
dS Pc [−Hy + tanα(Hz cosβ + Hx sinβ)] (13.14)<br />
and<br />
dα e<br />
=<br />
dS Pc [Hx cosβ + Hz sinβ], (13.15)<br />
where P is the momentum, β the azimuthal angle between the projection of the momentum vector on the<br />
x-z plane and the Z axis, α the <strong>de</strong>ep angle between the momentum vector and the x-z plane, S the track<br />
length and Hx, Hy and Hz the components of the magnetic field.<br />
The exact integration of the coupled equations 13.14 and 13.15 is complicated. If, however, |Hy| ≫ |Hx|<br />
and |Hy| ≫ |Hz|, as is the case in the CBM dipole field, the track can in a 0 th step be approximated by a<br />
parabolic helix curve and the hit coordinates are <strong>de</strong>scribed by a parabola in the x-z plane:<br />
The estimation of the track momentum in the 0 th step is then<br />
x = az 2 + bz + c. (13.16)<br />
P0 = 0.3 ¯H<br />
, (13.17)<br />
2acosα<br />
where ¯H = 1<br />
2 (H1y + HNy) is the mean of the y components of the magnetic field at the first and last<br />
measured point of the track.<br />
This momentum estimate serves as input for the 1 st step of the algorithm, which uses a 3 rd or<strong>de</strong>r approximation<br />
for the azimuthal angle:<br />
β = β0 + ( dβ<br />
dS )S=0S + 1<br />
2 (d2 β<br />
dS 2 )S=0S 2 + 1<br />
6 (d3 β<br />
dS 3 )S=0S 3 . (13.18)
316 Event reconstruction<br />
The non-uniformity of the magnetic field and the energy loss of the particle are taken into account at this<br />
step [229]. The value of the momentum is calculated as:<br />
P1 = P0 + P ′ (H, dH<br />
dS )S + P′′ (H, dH<br />
dS , d2 H<br />
dS 2 )S2 , (13.19)<br />
where P0 was calculated from equation 13.17 and P ′ and P ′′ are functions of the magnetic field and its<br />
<strong>de</strong>rivatives.<br />
Number of particles<br />
4<br />
10<br />
3<br />
10<br />
0 1 2 3 4 5 6 7 8 9 10<br />
p (GeV/c)<br />
Figure 13.17: Momentum spectrum of charged particles accepted by the STS system in central Au+Au collisions<br />
at 25 AGeV<br />
The algorithm was applied to space points of tracks obtained from the transport of 1,000 UrQMD events<br />
(central Au+Au at 25 AGeV beam energy) through the STS system by the simulation framework CBM-<br />
ROOT. I<strong>de</strong>al track finding was assumed. The space points were smeared in the x and y coordinates<br />
according to an assumed position resolution of 20 µm. The momentum spectrum of accepted charged<br />
tracks is shown in figure 13.17.<br />
Number of tracks<br />
100<br />
80<br />
60<br />
40<br />
20<br />
3<br />
× 10<br />
Mean 0.251<br />
RMS 2.205<br />
Constant 1.111e+05 ± 231<br />
Mean 0.02246 ± 0.00153<br />
Sigma 0.8371 ± 0.0017<br />
0<br />
-25 -20 -15 -10 -5 0 5 10 15 20 25<br />
(p - p ) / p (%)<br />
reco<br />
/ p (%)<br />
p<br />
σ<br />
1.8<br />
1.6<br />
1.4<br />
1.2<br />
1<br />
0.8<br />
0.6<br />
0 1 2 3 4 5 6 7 8 9 10<br />
p (GeV/c)<br />
Figure 13.18: (Left) distribution of the relative difference of reconstructed and true momentum for tracks with<br />
p < 10 GeV/c and a minimum of three hits in the STS. The full line shows a Gaussian fit with a σ = 0.84 %. (Right)<br />
Relative momentum resolution as function of momentum. The results were obtained for i<strong>de</strong>al track finding.<br />
To assess the quality of momentum reconstruction obtained with the algorithm <strong>de</strong>sribed above, the reconstructed<br />
momenta are compared to the simulated ones. Figure 13.18 (left) shows the distribution of<br />
the relative difference of reconstructed and true momentum. The mean resolution is 0.84 %; its momentum<br />
<strong>de</strong>pen<strong>de</strong>nce is shown in the right panel of figure 13.18. The resolutions in the angles β and α are
13.2. Track fitting 317<br />
Number of tracks<br />
70000<br />
60000<br />
50000<br />
40000<br />
30000<br />
20000<br />
10000<br />
Mean -0.05287<br />
RMS 3.778<br />
Constant 7.15e+04 ± 159<br />
Mean -0.08521 ± 0.00243<br />
Sigma 1.202 ± 0.003<br />
0<br />
-25 -20 -15 -10 -5 0 5 10 15 20 25<br />
β - β (mrad)<br />
reco<br />
(mrad)<br />
β<br />
σ<br />
1.6<br />
1.4<br />
1.2<br />
1<br />
0.8<br />
0.6<br />
0 1 2 3 4 5 6 7 8 9 10<br />
p (GeV/c)<br />
Figure 13.19: (Left) distribution of the difference of reconstructed and true azimuthal angle β for tracks with<br />
p < 10 GeV/c and a minimum of three hits in the STS. The full line shows a Gaussian fit with σ = 1.2 mrad.<br />
(Right) Resolution in β as function of momentum. The results were obtained for i<strong>de</strong>al track finding.<br />
Number of tracks<br />
50000 Mean -0.007802<br />
RMS 2.313<br />
40000<br />
Constant<br />
Mean<br />
4.48e+04 ± 114<br />
0.001443 ± 0.001463<br />
30000<br />
20000<br />
10000<br />
Sigma 0.6321 ± 0.0019<br />
0<br />
-10 -8 -6 -4 -2 0 2 4 6 8 10<br />
α - α (mrad)<br />
reco<br />
(mrad)<br />
α<br />
σ<br />
1.2<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
0 1 2 3 4 5 6 7 8 9 10<br />
p (GeV/c)<br />
Figure 13.20: (Left) distribution of the difference of reconstructed and true <strong>de</strong>ep angle α for tracks with p < 10<br />
GeV/c and a minimum of three hits in the STS. The full line shows a Gaussian fit with σ = 0.6 mrad. (Right)<br />
Resolution in α as function of momentum. The results were obtained for i<strong>de</strong>al track finding.<br />
shown in figures 13.19 and 13.20. Both angles are reconstructed with an accuracy of about 1 mrad. The<br />
reconstruction accuracy for all three parameters is worse for low momentum tracks because of the higher<br />
track curvature and the lower number of STS hits.<br />
Number of tracks<br />
2000 Mean -0.5733<br />
1800<br />
RMS 2.185<br />
1600<br />
Constant 1885 ± 19.3<br />
1400<br />
Mean -0.4112 ± 0.0081<br />
1200<br />
1000<br />
800<br />
600<br />
400<br />
200<br />
Sigma 0.8606 ± 0.0099<br />
0<br />
-10 -8 -6 -4 -2 0 2 4 6 8 10<br />
(p - p ) / p (%)<br />
Figure 13.21: Distribution of the difference between reconstructed and true momentum obtained for tracks<br />
reconstructed by the CM track fitter in central Au+Au collisions at 25 AGeV beam energy. The full line shows a<br />
Gaussian fit with σ = 0.86 %.<br />
reco
318 Event reconstruction<br />
The algorithm has also been tested with the Conformal Mapping track fin<strong>de</strong>r (section 13.1.3). Figure<br />
13.21 shows the relative difference of reconstructed and true momentum using tracks reconstructed by the<br />
CM fin<strong>de</strong>r. The mean resolution of about 0.86 % is only slightly worse than in case of i<strong>de</strong>al track finding.<br />
We conclu<strong>de</strong> that real track finding has only a minor influence on the performance of the momentum<br />
reconstruction.<br />
The reconstruction algorithm will be further improved in a 2 nd step, in which the numerical solution<br />
of the equations of motions will yield more precise values of the track parameters. The results of the<br />
first step as presented here will serve as input for this second step, which is still un<strong>de</strong>r <strong>de</strong>velopment.<br />
Preliminary results show that momentum and angular resolutions can be improved by a factor of 1.5 - 2.<br />
13.2.4 Polynomial approximation<br />
This algorithm reconstructs the particle momentum directly from the hits in the Silicon Tracking System<br />
(STS). It consists of two steps. First, the track curve is fitted by a polynomial vector function, using the<br />
smoothness of the trajectory. Three types of approximation were applied: polynomials, cubic splines and<br />
B-splines.<br />
The optimisation problem is <strong>de</strong>scribed by the residual function<br />
N<br />
2 2 ˆx(zi) − xi ˆy(zi) − yi<br />
F = {<br />
+<br />
}, (13.20)<br />
i=0<br />
σ i x<br />
where xi,yi are the trajectory hits, ˆx(z), ˆy(z) the coordinate approximations, σ i x,σ i y the measurement errors<br />
and N the number of hits in the tracking system. It should be noted that F is a quadratic functional of<br />
the parameters <strong>de</strong>scribing the coordinate functions ˆx(z), ˆy(z). This means that the optimisation problem<br />
is reduced to a very fast procedure of multiplication of an a priory prepared matrix with the vectors of hit<br />
coordinates.<br />
In the second step, the constructed functions ˆx(z), ˆy(z) are used to <strong>de</strong>termine the approximate value ˆp of<br />
the momentum. The momentum reconstruction is based on the equations of motion:<br />
xzz = kq(1 + x2 z + y 2 z ) 1 2<br />
p<br />
σ i y<br />
{xzyzBx − (1 + x 2 z )By + yzBz}, (13.21)<br />
yzz = kq(1 + x2 z + y2 z ) 1 2<br />
{(1 + y<br />
p<br />
2 z )Bx − xzyzBy − xzBz}, (13.22)<br />
where p and q are momentum and charge of the particle, respectively, and Bx,By,Bz the components<br />
of the nonuniform magnetic field in the point (x,y,z). xz, yz and xzz, yzz <strong>de</strong>note the first and second<br />
<strong>de</strong>rivatives of x and y with respect to z, respectively.<br />
With the <strong>de</strong>nsity function<br />
f (α,z, ˆx(z), ˆy(z)) = | ˆxzz − αkQ(1 + ˆx 2 z + ˆy 2 z ){ ˆxz ˆyzBx − (1 + ˆx 2 z )By + ˆyzBz}| 2<br />
+ | ˆyzz − αkQ(1 + ˆx 2 z + ˆy 2 z ) 1 2 {(1 + ˆy 2 z )Bx − ˆxz ˆyzBy − ˆxzBz}| 2 ,<br />
the approximated value ˆp is <strong>de</strong>rived as the inverse of α minimising the functional<br />
G(α) =<br />
ze<br />
zb<br />
(13.23)<br />
f (α,z, ˆx(z), ˆy(z)g(z)dz, (13.24)<br />
where g(z) is a weight function and zb,ze the z coordinates of the first and last STS <strong>de</strong>tector, respectively.<br />
Since G(α) is a quadratic functional of the parameter α, a fast non-iterative procedure for the evaluation<br />
of ˆp can be constructed.
13.2. Track fitting 319<br />
Figure 13.22: Distribution of relative momentum residuals using the polynomial approximation algorithm. Left<br />
column: without multiple scattering; right column: with multiple scattering in the STS. The track approximations<br />
are polynomial (top row), cubic spline (centre row) and B-spline (bottom row).<br />
This algorithm has been applied to simulated tracks in the momentum range 1 - 10 GeV/c with hits in<br />
all seven stations of the STS. I<strong>de</strong>al track finding was assumed. The distribution of relative errors with<br />
and without taking into account multiple scattering in the tracking stations are shown in figure 13.22<br />
for the three types of track mo<strong>de</strong>ls. The first and second moments of the relative momentuk residual<br />
distributions are summarised in table 13.4. While in the absence of multiple scattering, the spline ap-
320 Event reconstruction<br />
Track mo<strong>de</strong>l < Δp/p > [%] σp/p [%] < Δp/p [%] σp/p [%]<br />
no MS no MS MS MS<br />
polynomial -0.02 0.28 -0.02 0.76<br />
cubic spline 0.08 0.17 0.09 0.79<br />
B spline 0.01 0.16 0.00 0.78<br />
Table 13.4: Mean and RMS of the momentum residual distributions of figure 13.22<br />
proximations give better results, the performance in the presence of multiple scattering is similar for all<br />
three approximations (σP = 0.75 − 0.80%).<br />
13.2.5 Orthogonal polynomial sets<br />
The method of accurate momentum reconstruction with orthogonal polynomial sets constructs an explicit<br />
function which gives the momentum in terms of measurable quantities: position and direction of a track<br />
at the entrance of the spectrometric field and the <strong>de</strong>flection angle as the effect of the field onto the track<br />
momentum [234,235,236]. This experimental input information can be provi<strong>de</strong>d e. g. by a Kalman filter<br />
operating on hits registered in the CBM silicon tracking system (STS) (see section 13.2.2).<br />
In the inhomogeneous magnetic field of CBM, the <strong>de</strong>flection angle φ, <strong>de</strong>fined between the first and the<br />
last tracking station, can be expressed as a function of five variables:<br />
1. (x1,x2): the coordinates of a point in the first STS <strong>de</strong>tector;<br />
2. (x3,x4): the tangents of the trajectory in the point (x1,x2);<br />
3. x5 = 1/pc, where p is the momentum and c the speed of light.<br />
The task is to construct the inverse function<br />
which provi<strong>de</strong>s the accurate momentum restoration [234].<br />
p = p(x1,x2,x3,x4,φ), (13.25)<br />
The procedure consists of two steps. First, the <strong>de</strong>flection angles for the given magnetic field are calculated<br />
for a set of representative trajectories. The explicit function 13.25 is then constructed on the basis of these<br />
trajectories.<br />
To choose a representative set of trajectories, the experimental ranges [Ai,Bi] of the variables xi are<br />
normalised to the range [-1,+1] by <strong>de</strong>fining<br />
gi = 2xi − Ai − Bi<br />
. (13.26)<br />
Bi − Ai<br />
For each variable gi, a discrete number Ni of “points” are choosen according to the Tchebycheff distribution:<br />
g αi<br />
i = cos (2αi − 1)π<br />
, αi = 1,...,Ni. (13.27)<br />
2Ni<br />
The numbers N1,N2,...,N5 have to be chosen such that the required accuracy is achieved. They <strong>de</strong>termine<br />
the collection of fixed trajectories that are traced through the magnetic field (given in form of a <strong>de</strong>tailed<br />
field map) applying a numerical integration2 . For each trajectory, the <strong>de</strong>flection angle φ(x1,x2,x3,x4,x5)<br />
is calculated.<br />
2 The Runge-Kutta method is used.
13.2. Track fitting 321<br />
Let the range of these <strong>de</strong>flections be [A6,B6]. We normalise the <strong>de</strong>flections to the interval [-1, +1]:<br />
g6 = 2ϕ − A6 − B6<br />
B6 − A6<br />
and, by analogy with equation 13.27, choose a discrete number of values of g6 by<br />
(13.28)<br />
g α6<br />
6 = cos (2α6 − 1)π<br />
, α6 = 1,...,N6, N6 ≤ N5. (13.29)<br />
2N6<br />
Now, applying inverse interpolation, we calculate the corresponding values of g5 in the amount equal to<br />
the product Π 5 i=1 Ni.<br />
With this set of values, the <strong>de</strong>sired function is constructed by the use of the Tchebycheff polynomials<br />
<strong>de</strong>fined by<br />
T0(x) = 1; T1(x) = x; Tn+1(x) = 2xTn(x) − Tn−1(x) (n ≥ 1). (13.30)<br />
These polynomials form an orthogonal set [237]<br />
<br />
Tj(Xα)Tk(Xα) = const · δ jk<br />
if<br />
g5 can be expressed in the form<br />
g5 = <br />
α<br />
Xα = cos<br />
i jklm<br />
(13.31)<br />
(2α − 1)π<br />
, α = 1,...,N. (13.32)<br />
2N<br />
Ci jklmTi(g1)Tj(g2)Tk(g3)Tl(g4)Tm(g6), (13.33)<br />
where the sum runs over i = 0,...,N1 − 1; j = 0,...,N2 − 1; k = 0,...,N3 − 1; k = 0,...,N4 − 1; m =<br />
0,...,N6 − 1. The coefficients Ci jklm can be calculated taking into account the orthogonality of the<br />
Tchebycheff polynomials:<br />
<br />
Ci jklm =<br />
α1<br />
α1α2α3α4α6<br />
where the sums run over αi = 1,...,Ni.<br />
α2<br />
g5α 1 α 2 α 3 α 4 α 6 Ti(g1)Tj(g2)Tk(g3)Tl(g4)Tm(g6)<br />
( <br />
Ti(g1)) 2 ( <br />
Tj(g2)) 2 ( <br />
Tk(g3)) 2 ( <br />
Tl(g4)) 2 ( , (13.34)<br />
Tm(g6)) 2<br />
α3<br />
The algorithm <strong>de</strong>scribed above was applied to the CBM tracking system by computing trajectories for<br />
the range and number of the variables x1 − x6 as given in table 13.5. The total number of “points” for<br />
which trajectories were calculated is 625. The <strong>de</strong>flection angles of all trajectories were calculated by<br />
transport through the magnetic field. For each combination (α1,α2,α3,α4) and for N6 = 7 values of the<br />
<strong>de</strong>flection angle, the momentum variable was calculated by inverse interpolation. The 4,375 expansion<br />
coefficients Ci jklm were then <strong>de</strong>termined according to equation 13.34.<br />
To estimate the accuracy of the method, tracks with random values of x1,x2,x3,x4 and p, uniformly<br />
distributed in their respective ranges, were transported through the magnetic field and the <strong>de</strong>flection<br />
angle ϕ was calculated. Then, using the set of coefficients Ci jklm and equation 13.33, the corresponding<br />
value of the momentum pcim was calculated. The absolute and relative differences between reconstructed<br />
and true momemtum are shown in figure 13.23. We see that the RMS of the method, which takes into<br />
account the inhomogeneity of the magnetic field and the spatial distribution of all possible trajectories<br />
through the spectrometer magnet, is about 0.15%.<br />
Lowering the upper limits N1, N2, N3, N4, N6, we obtain, without changing the coefficients, a leastsquares<br />
fit to the computed trajectories. This is a consequence of the Tchebycheff polynomials being<br />
α4<br />
α6
322 Event reconstruction<br />
Ai Bi Ni<br />
x1 -1.5 2. 5<br />
x2 -2. 2. 5<br />
x3 -0.3 0.44 5<br />
x4 -0.37 0.37 5<br />
x5 0.1 1. 7<br />
x6 0.025577 0.277585 7<br />
Table 13.5: Ranges [Ai,Bi] and number of “points” for variables x1,x2,x3,x4,x5,x6<br />
Figure 13.23: Distributions of p − pcim (left, in MeV/c) and p−pcim<br />
p<br />
coefficients Ci jklm<br />
(right), using the complete set of expansion<br />
orthogonal. The number and significant coefficients can be found by a Fisher test, giving the or<strong>de</strong>r of<br />
the polynomials above which the RMS of the residuals does not <strong>de</strong>crease significantly. Our analysis has<br />
shown that without loss in accuracy, only 89 significant coefficients can be used.<br />
In or<strong>de</strong>r to estimate the accuracy of the method on data close to real events, we applied the algorithm<br />
to data generated by Monte-Carlo simulations for the reaction Au+Au at 25 AGeV beam energy. Figure<br />
13.24 presents the distributions of absolute and relative difference between reconstructed and true momentum<br />
for positively charged tracks. Only the 89 significant coefficiencts were used. The dispersion of<br />
the distribution p−pc<br />
p is about 0.26%.<br />
It must be noted that this result is obtained only for positively charged particles, because the tracing of<br />
the basic set of trajectories through the magnetic field was realised for such tracks. For a small part of<br />
tracks (approximately 10%), the parameters of which are out of the ranges of variables x1,x2,x3,x4,x6,<br />
we used the approximation of the uniform magnetic field. This reduces the overall resolution to about<br />
0.34 %.<br />
In summary, the algorithm provi<strong>de</strong>s the possibility to reconstruct the momentum of charged particles
13.3. Primary vertex fitting 323<br />
Figure 13.24: Distribution of p− pc (left, in Mev/c) and p−pc<br />
p (right) for positively charged particles from Monte<br />
Carlo events<br />
registered in the STS system with high accuracy (σp ≈ 0.34%). The accuracy can be further improved by<br />
separate momentum reconstruction for particles of different charges and by subdivision of the momentum<br />
range into a intervals.<br />
13.3 Primary vertex fitting<br />
13.3.1 Minimisation of track impact parameters<br />
A straightforward approach to the <strong>de</strong>termination of the primary vertex coordinates exploits the fact that it<br />
is the origin of the majority of the tracks measured in the STS (see figure 13.1). Therefore, the dispersion<br />
of the track extrapolation coordinates x and y to a plane of constant z will be minimal for z = zPV . The<br />
mean values of x and y in the primary vertex z plane then give the coordinates of the primary vertex.<br />
An algorithm based on this method has been tested for central Au+Au events at 25 AGeV beam energy<br />
simulated by UrQMD and transported through the STS sub<strong>de</strong>tector by the simulation framework<br />
CBMROOT. Tracks were reconstructed by the Conformal Mapping track fin<strong>de</strong>r (section 13.1.3) and the<br />
Parabolic Approximation track fitter (section 13.2.3). The dispersion of track impact parameters was<br />
calculated for three z planes (z = −5 cm, z = 0 cm, z = 5 cm) and parametrised by a parabola, the minimum<br />
of which <strong>de</strong>fined the vertex z position. The mean values of track impact parameters in this z plane<br />
were taken as x and y coordinates of the primary vertex. The distributions of the difference between<br />
reconstructed and true primary vertex coordinates are shown in figure 13.25. A precision of about 10 µm<br />
in x, 5 µm in y and 20 µm in z is reached. This values can still be improved by the implementation of the<br />
second step of momentum reconstruction in the parabolic approximation.<br />
13.3.2 Geometrical fit with Kalman filter<br />
The algorithm for fitting the primary vertex is based on the Kalman estimator and smoother. The term<br />
“geometrical fit” means that the vertex fit is performed on tracks without particle i<strong>de</strong>ntification.<br />
Given a few hundreds of primary tracks, there is no need neither for a preliminary selection of primary
324 Event reconstruction<br />
120<br />
100<br />
80<br />
60<br />
40<br />
20<br />
Mean -1.573<br />
RMS 9.857<br />
Constant 1<strong>28.5</strong> ± 5.8<br />
Mean -1.412 ± 0.360<br />
Sigma 9.752 ± 0.277<br />
0<br />
-50 -40 -30 -20 -10 0 10 20 30 40 50<br />
μ m<br />
120<br />
100<br />
80<br />
60<br />
40<br />
20<br />
250<br />
200<br />
150<br />
100<br />
0<br />
-100 -80 -60 -40 -20 0 20 40 60 80 100<br />
μ m<br />
50<br />
Mean -0.794<br />
RMS 5.437<br />
Constant 237.5 ± 11.0<br />
Mean -0.8221 ± 0.1920<br />
Sigma 5.291 ± 0.159<br />
0<br />
-50 -40 -30 -20 -10 0 10 20 30 40 50<br />
μ m<br />
Mean -4.312<br />
RMS 20.25<br />
Constant 129.4 ± 5.9<br />
Mean -3.915 ± 0.706<br />
Sigma 19 ± 0.5<br />
Figure 13.25: Distributions between reconstructed and true primary vertex coordinates (top left: x, top right: y,<br />
bottom: z) using the Conformal mapping track fin<strong>de</strong>r and the parabolic approximation for track fitting. The full<br />
lines show Gaussian fits.<br />
tracks nor for an initial guess of the primary vertex position. The estimates of the track parameters and<br />
their covariance matrices are extrapolated to the mid z-plane of the target (see <strong>de</strong>tails in section 13.2.1).<br />
After extrapolation the vertex fit is performed consi<strong>de</strong>ring tracks as straight lines.<br />
The fit problem is to obtain an estimation of the vertex position V = (xv, yv, zv) using the given set of<br />
the track parameter estimates. For this purpose every track originating from the primary vertex is treated<br />
as an in<strong>de</strong>pen<strong>de</strong>nt measurement of the vertex position [230, 231]. The fit is performed with V as <strong>de</strong>sired<br />
unknown vector and the track estimates Tk as known measured quantities.<br />
To construct the vertex fitting procedure we need to know the <strong>de</strong>pen<strong>de</strong>nce of the track parameters on the<br />
vertex position. Since all tracks are linearised at z = z0, the track mo<strong>de</strong>l reads<br />
x(z) = x0 +tx · (z − z0), y(z) = y0 +ty · (z − z0) . (13.35)<br />
Let the kth track originate from the vertex with unknown slopes (ak, bk). The mo<strong>de</strong>l of the kth measurement<br />
can then be written as: ⎛<br />
⎞<br />
xv − ak(zv − z0)<br />
⎜<br />
⎟<br />
⎜ yv − bk(zv − z0) ⎟<br />
Tk = ⎜<br />
⎟<br />
⎜<br />
⎟<br />
⎝ ak<br />
⎠ + ηk , (13.36)<br />
bk<br />
where Tk = (x0k, y0k, txk, tyk) T is the known vector of the k th track parameter estimates and ηk is an<br />
unknown vector of errors in Tk. The errors are assumed to be Gaussian with known covariance matrix.<br />
The mo<strong>de</strong>l (13.36) is clearly nonlinear in the first and second components and has to be linearised before<br />
applying the usual Kalman filter formalism. Assuming the estimated vector Rk = (xv, yv, zv, ak, bk) T ,
13.3. Primary vertex fitting 325<br />
one can obtain the linearised measurement matrix:<br />
⎛<br />
1<br />
⎜ 0<br />
Hk = ⎜<br />
⎝ 0<br />
0<br />
1<br />
0<br />
−ak<br />
−bk<br />
0<br />
(z0 − zv)<br />
0<br />
1<br />
⎞<br />
0<br />
⎟<br />
(z0 − zv) ⎟<br />
0<br />
⎟<br />
⎠<br />
0 0 0 0 1<br />
and the measurement mo<strong>de</strong>l becomes<br />
, (13.37)<br />
Tk = Hk · Rk + ηk . (13.38)<br />
Note that the matrix Hk <strong>de</strong>pends on unknown quantities. Therefore the whole fit procedure has to be repeated<br />
a few times using the fitted values zv, ak, bk from the previous iteration. The number of iterations<br />
is fixed to be three.<br />
The Kalman filter formalism cannot be directly applied to the constructed mo<strong>de</strong>l, since the total number<br />
of unknown quantities (3 + 2 · Ntracks) is large. As the unknown slopes ak, bk are used only in the<br />
k th measurement and have no further influence on the vertex position, there is no need to store and<br />
update the corresponding covariance matrix elements; they are therefore used only temporarily as “virtual<br />
parameters” for the k th measurement.<br />
Since the last two parameters of the vector R are replaced for each track, the covariance matrix C is<br />
partially initialised adding every new measurement:<br />
where inf <strong>de</strong>notes a large value.<br />
Ck =<br />
⎛<br />
⎜<br />
⎝<br />
C11 k−1 C12<br />
k−1 C13<br />
k−1 0 0<br />
C12 k−1 C22<br />
k−1 C23<br />
k−1 0 0<br />
C13 k−1 C23<br />
k−1 C33<br />
k−1 0 0<br />
0 0 0 inf 0<br />
0 0 0 0 inf<br />
⎞<br />
⎟<br />
⎠<br />
, (13.39)<br />
After the vertex fitting at each iteration to improve the track parameters, all used tracks are refitted by the<br />
same vertex fit procedure but with the vertex parameters V and the vertex part of the covariance matrix<br />
C being fixed. This step is equivalent to the smoother part of the Kalman filter formalism.<br />
Parameter Resolution (µm) Pull<br />
xv 1.07 1.09<br />
yv 0.87 1.01<br />
zv 5.15 1.08<br />
Table 13.6: Residuals and normalised residuals (pulls) of the primary vertex parameters obtained from<br />
1000 events of central Au+Au collisions at 25 AGeV in the asymmetric inhomogeneous magnetic field<br />
Table 13.6 gives the precision of the primary vertex reconstruction obtained from 1000 events of central<br />
Au+Au collisions at 25 AGeV. The algorithm provi<strong>de</strong>s a very high accuracy: the residuals of the xv and<br />
yv positions of the primary vertex are about 1 µm, and the zv position is reconstructed with an accuracy<br />
of 5 µm. The normalised residuals (pulls) are close to unity. Some increase of the pulls of the xv and zv<br />
coordinates are probably due to the track propagation error in the bending plane and to the linear track<br />
mo<strong>de</strong>l approximation in the vertex region.<br />
The total number of reconstructed tracks used in the primary vertex fitting routine (Figure 13.26) is quite<br />
large. In or<strong>de</strong>r to investigate the <strong>de</strong>pen<strong>de</strong>nce of the vertex resolution on this number, the primary vertex
326 Event reconstruction<br />
22<br />
20<br />
18<br />
16<br />
14<br />
12<br />
10<br />
8<br />
6<br />
4<br />
2<br />
0<br />
0 100 200 300 400 500 600 700 800 900 1000<br />
Number of tracks<br />
Figure 13.26: Number of reconstructed tracks per<br />
event used by the primary vertex fit algorithm for central<br />
Au+Au collisions at 25 AGeV<br />
Resolution x v , y v (µm)<br />
2.0<br />
1.5<br />
1.0<br />
0.5<br />
0<br />
0<br />
0 50 100 150 200 250 300 350 400 450 500<br />
Number of tracks<br />
Figure 13.27: Primary vertex position resolutions<br />
versus number of tracks used in the primary vertex fit<br />
(the scale for zv is shown on the right si<strong>de</strong>)<br />
fitting routine was applied to a randomly selected subset of tracks (Figure 13.27). Such ∼ 1/ √ N type<br />
behavior allows a significant simplification of the fitting routine in case the maximal precision of the<br />
primary vertex is not required. This will be especially important for online event selection where time<br />
consumptions are crucial.<br />
13.4 Secondary vertex fitting<br />
13.4.1 Geometrical fit with Kalman filter<br />
This method of secondary vertex fitting is a straight forward application of the Kalman filter. Similarly<br />
to the primary vertex fit (see section 13.3.2), the track mo<strong>de</strong>l is a straight line in the vertex region, but the<br />
vertex coordinates and track parameters are now treated simultaneously. Thus, the algorithm provi<strong>de</strong>s not<br />
only the vertex position, but also improved estimations of the track parameters, including their momenta.<br />
Let a vertex V = (xv,yv,zv) be composed of n tracks with slopes ak,bk and momenta pk. The (3 + 3n)dimensional<br />
state vector R is given by:<br />
R = (xv,yv,zv, a1,b1, p1, ... an,bn, pn) . (13.40)<br />
The Kalman filter is implemented in the standard operational form using the whole covariance matrix of<br />
the state vector R. This standard implementation as well as the use of momenta instead of their inverse<br />
values allow to incorporate any type of constraints on “vertex-tracks” or “tracks-tracks” parameters into<br />
the Kalman filter.<br />
Let the track estimate Tk = (xk,yk,txk,tyk,Pk) T be linearised at z = z0. In the original track estimate the<br />
signed inverse momentum (q/P)k is measured; therefore the covariance matrix of Tk has to be converted<br />
to the momentum measurement. The measurement matrix is constructed in the same way as in the<br />
primary vertex fit where momentum and track slopes are directly measured:<br />
Hk =<br />
⎛<br />
1 0 −ak 0 0 0 ··· z0 − zv 0 0 ··· 0 0 0<br />
⎜ 0 1 −bk 0 0 0 ··· 0 z0 − zv 0 ··· 0 0 0<br />
⎟<br />
⎜<br />
⎟<br />
⎜ 0 0 0 0 0 0 ··· 1 0 0 ··· 0 0 0 ⎟<br />
⎜<br />
⎟<br />
⎝ 0 0 0 0 0 0 ··· 0 1 0 ··· 0 0 0 ⎠<br />
0 0 0 0 0 0 ··· 0 0 1 ··· 0 0 0<br />
⎞<br />
x v<br />
y v<br />
z v<br />
15<br />
10<br />
5<br />
Resolution z v (µm)<br />
(13.41)
13.4. Secondary vertex fitting 327<br />
Since the matrix Hk contains many vanishing elements, the Kalman filter algorithm can be significantly<br />
sped up eliminating all operations with zero elements of Hk. The algorithm proceeds track by track and<br />
finally obtains the estimates of the vertex position and smoothed track parameter estimates composing<br />
the vertex together with the corresponding covariance matrix.<br />
Parameter Resolution (µm) Pull<br />
xv 12.8 1.05<br />
yv 10.6 1.05<br />
zv 69.3 1.06<br />
Table 13.7: Residuals and normalised residuals (pulls) of the secondary vertex parameters obtained from 10 5 D 0<br />
<strong>de</strong>cays in the inhomogeneous magnetic field<br />
As an example, table 13.7 shows the residuals and the normalised residuals of the D 0 <strong>de</strong>cay vertex<br />
parameters. The pulls show that the errors are well estimated. The longitudinal resolution is 69 µm. The<br />
particle hypotheses (π − , K + ) have been used in the track fit procedure to properly account for multiple<br />
scattering effects.<br />
13.4.2 Mass and topological constrained fit with Kalman filter<br />
Precision of the secondary vertex parameters obtained in the geometrical vertex fit (see section 13.4.1)<br />
can be improved [231, 232] by taking into account several assumptions on the tracks associated to the<br />
vertex.<br />
These assumptions should be expressed in terms of constraints on the state vector parameters. Each<br />
constraint is an equation on the parameters or is treated as an additional measurement. The equationtype<br />
constraint can also be consi<strong>de</strong>red as a measurement with σeq−constr = 0. Thus, setting σeq−constr to a<br />
relatively small value, the equation-type constraint can be treated by the Kalman filter as a measurement.<br />
Since the constraints are applied after the geometrical fit, this implies additional steps of the Kalman<br />
filter algorithm with the modified measurement matrix and gain. In the algorithm a value of σeq−constr is<br />
taken to be two or<strong>de</strong>rs of magnitu<strong>de</strong> less than the covariance matrix elements after the geometrical fit.<br />
Such small value is enough to satisfy all the constraints when they do not contradict each other.<br />
Two types of constraints have been inclu<strong>de</strong>d into the secondary vertex fit: a mass constraint and a topological<br />
constraint.<br />
The mass constraint can be applied in the case of one or several combinations of particles in the vertex are<br />
known to originate from a narrow width mass state. Here we consi<strong>de</strong>r the case of a single mass constraint,<br />
since multiple mass constraints can be treated in a similar way. Following the notations from [231,232],<br />
let Z be a set of those tracks which are required by the mass constraint to form the invariant mass M. Let<br />
us <strong>de</strong>fine:<br />
⎛ ⎞<br />
⎛ ⎞<br />
nk =<br />
⎜<br />
⎝<br />
nxk<br />
nyk<br />
nzk<br />
⎟<br />
⎠ =<br />
1<br />
<br />
1 + a 2 k + b2 k<br />
⎜<br />
⎝<br />
ak<br />
bk<br />
1<br />
⎟<br />
⎠. (13.42)<br />
Px = <br />
nxk pk, Py = <br />
nyk pk, Pz = <br />
nzk pk, (13.43)<br />
k∈Z<br />
k∈Z<br />
k∈Z<br />
k∈Z<br />
where mk, nk are the mass and direction of k-th particle.<br />
k∈Z<br />
E = <br />
Ek = <br />
p2 k + m2 k , (13.44)
328 Event reconstruction<br />
Then the mass constraint reads<br />
M 2 = E 2 − P 2 x + P 2 y + P 22 z . (13.45)<br />
Taking the partial <strong>de</strong>rivatives of M 2 one can calculate a linearised matrix H of the mass measurement:<br />
H3k =<br />
<br />
2pknzk nxknykPy + nxknzkPz − 1 − n2 <br />
xk<br />
Px ,<br />
<br />
<br />
H3k+1 = 2pknzk nxknykPx + nyknzkPz − 1 − n2 <br />
yk<br />
Py ,<br />
H3k+2 = 2pkEE −1<br />
k − 2(nxkPx + nykPy + nzkPz)<br />
The elements of H that corresponds to k /∈ Z are zeros.<br />
k ∈ Z . (13.46)<br />
The mass constraint is used by Kalman filter as an ordinary one-dimensional measurement with the<br />
measured value M 2 , the error σeq−constr and the measurement matrix H.<br />
The topological constraint is used to point a mother particle to the (already) known primary vertex. The<br />
mother track starts at the secondary vertex (xv,yv,zv), has momentum P = (Px,Py,Pz) as <strong>de</strong>fined above<br />
and has to point to the primary vertex Vpv = (xpv,ypv,zpv) :<br />
This requirement can be written as a set of three constraints:<br />
(V −Vpv) × P = 0 . (13.47)<br />
0 = (zv − zpv)Py − (yv − ypv)Pz ,<br />
0 = (xv − xpv)Pz − (zv − zpv)Px ,<br />
0 = (yv − ypv)Px − (xv − xpv)Py .<br />
(13.48)<br />
The constraint can be inclu<strong>de</strong>d directly into the Kalman filter as three in<strong>de</strong>pen<strong>de</strong>nt measurements with<br />
zero values and errors σeq−constr. As a result, the mother track will point exactly to the primary vertex.<br />
The primary vertex errors can also be taken into account. The most elegant way to do this is to add the<br />
primary vertex parameters into the state vector [231, 232]:<br />
R = (xv,yv,zv, a1,b1, p1, ... an,bn, pn, xp,yp,zp) , (13.49)<br />
with the primary vertex covariance matrix inclu<strong>de</strong>d into the exten<strong>de</strong>d covariance matrix of the state<br />
vector.<br />
Three constraints (Eq. 13.48) are ad<strong>de</strong>d one by one. For the first constraint linearised measurement<br />
matrix H is :<br />
H0 = 0 ,<br />
H1 = −Pz ,<br />
H2 = Py ,<br />
···<br />
H3k = pknzk((yv − yp)nzknxk − (zv − zp)nxknyk) ,<br />
H3k+1 = pknzk((yv − yp)nzknyk − (zv − zp)(n2 yk − 1)) ,<br />
H3k+2 = −(yv − yp) + (zv − zp)nyk ,<br />
···<br />
H3n+3 = 0 ,<br />
H3n+4 = Pz ,<br />
H3n+5 = −Py ,<br />
(13.50)
13.4. Secondary vertex fitting 329<br />
with (nxk, nyk, nzk) <strong>de</strong>fined above in the mass constraint part.<br />
The constructed topological constraint is a one-dimensional measurement with the measured value equal<br />
to 0, the error σeq−constr and the measurement matrix H.<br />
The other two constraints (Eq. 13.48) are treated in the same way.<br />
2000<br />
1800<br />
1600<br />
1400<br />
1200<br />
1000<br />
800<br />
600<br />
400<br />
200<br />
Constant 1843<br />
Mean 5.114e-05<br />
Sigma 0.006134<br />
0<br />
-0.05 -0.04 -0.03 -0.02 -0.01 0 0.01 0.02 0.03 0.04 0.05<br />
Resolution (Zsv_reco - Zsv_mc), cm<br />
2400<br />
2200<br />
2000<br />
1800<br />
1600<br />
1400<br />
1200<br />
1000<br />
800<br />
600<br />
400<br />
200<br />
Constant 2228<br />
Mean 0.006488<br />
Sigma 1.058<br />
0<br />
-10 -8 -6 -4 -2 0 2 4 6 8 10<br />
Pull Zsv<br />
Figure 13.28: Residuals and normalized residuals (pulls) of the secondary vertex z-position obtained from 10 5<br />
D 0 <strong>de</strong>cays in the inhomogeneous magnetic field by applying the full sequence of the vertex fitting routines: the<br />
geometrical fit and the fits with mass and topological constraints<br />
Parameter G G+M G+T G+M+T<br />
xv 12.8 12.1 2.5 2.4<br />
yv 10.6 10.5 2.7 2.5<br />
zv 69.3 63.4 65.1 61.3<br />
Table 13.8: Accuracy (in µm) of the secondary vertex parameters obtained from 10 5 D 0 <strong>de</strong>cays in the inhomogeneous<br />
magnetic field by applying different sequences of the vertex fitting routines: the geometrical (G) fit and the<br />
fits with mass (M) and topological (T) constraints<br />
Fig. 13.28 and table 13.8 show residuals and normalized residuals of the D 0 <strong>de</strong>cay vertex parameters<br />
obtained by the full chain of the vertex fitting algorithms. The pull of the secondary vertex z-position<br />
shows that the vertex parameters are well estimated. The longitudinal resolution is improved comparing<br />
to the geometrical fit and now equals 61 µm. Particle hypothesis have been used during the track fits to<br />
properly account for multiple scattering effects, and in the vertex fit procedure to apply the constraints.<br />
Table 13.8 gives also accuracy of the secondary vertex parameters for different combinations of the<br />
vertex routines. One can see that the mass constraint mainly improves the z-position of the vertex while<br />
the topological constraint increases the resolution of the transversal parameters of the vertex. The best<br />
resolution is reached by applying both, mass and topological, constraints.<br />
Parameter S S+G S+G+M S+G+T S+G+M+T<br />
pπ + 0.81 0.78 0.50 0.69 0.43<br />
pK− 0.82 0.79 0.62 0.71 0.54<br />
Table 13.9: Relative momentum resolution δp/p (in %) of the secondary tracks obtained from 10 5 D 0 <strong>de</strong>cays<br />
in the inhomogeneous magnetic field by applying different sequences of the track and vertex fitting routines:<br />
the standalone (S) track fit, the geometrical (G) vertex fit and the vertex fits with mass (M) and topological (T)<br />
constraints
330 Event reconstruction<br />
Table 13.9 shows the relative momentum resolutions of the secondary tracks at different stages of the<br />
event reconstruction. The mass constraint secondary vertex fit gives the most significant improvement of<br />
the momentum resolution for both particles. The best accuracy is reached applying all constraints. The<br />
difference in the momentum resolution behavior of π + and K − is probably due to their masses.<br />
The next step will be the application of the secondary vertex routines to physics analysis and <strong>de</strong>tector<br />
optimization in or<strong>de</strong>r to get the maximum event selection efficiency in the online data reconstruction.<br />
13.5 RICH ring finding<br />
In chapter 3.2 particle i<strong>de</strong>ntification with the RICH <strong>de</strong>tector is discussed. While ring-track matching and<br />
its implication for the efficiency and purity of particle i<strong>de</strong>ntification with the RICH <strong>de</strong>tector is discussed<br />
there in <strong>de</strong>tail, methods for ring finding and fitting are subject of this and the next section.<br />
13.5.1 Track extrapolation<br />
Ring finding can directly be combined with ring-track matching if the extrapolation of charged tracks to<br />
the photo<strong>de</strong>tector plane of the RICH <strong>de</strong>tector is used as possible ring center. A ring can then be searched<br />
for each track, see section 13.6. By <strong>de</strong>finition, only those rings can be correctly i<strong>de</strong>ntified with this<br />
method whose track was <strong>de</strong>tected by the tracking system. All rings belonging to primary vertex tracks<br />
are thus reliably found. However, a lot of fake rings are constructed from background hits or signals<br />
from different rings due to the high track <strong>de</strong>nsity, see fig. 13.29 examples (5) and (4), respectively. As<br />
is discussed in section 3.2 in the context of ring-track matching, a lot of rings from secondary electrons<br />
are seen in the RICH <strong>de</strong>tector which are not <strong>de</strong>tected by the tracking system. Since the track <strong>de</strong>nsity in<br />
the photo<strong>de</strong>tector plane is rather high, a track farther away from a certain ring center will be matched to<br />
this ring (see example (2) in fig, 13.29). In case more tracks could be matched to one ring, the one with<br />
the closest distance to the ring center would be taken. A careful cleaning up of the found ring sample is<br />
therefore essential for this ring finding method and has to be studied in <strong>de</strong>tail before this method could<br />
be used reliably. Also, double rings being too close are hardly recognized. A removal of hits allocated to<br />
found rings would help to find these rings. In addition, information from other <strong>de</strong>tectors (TOF, TRD) can<br />
be used to reject protons, kaons and pions from the track sample which is used for extrapolation. Having<br />
less tracks, less fake rings are found.<br />
13.5.2 Hough Transform<br />
The Hough Transform was studied as an option for a standalone ring fin<strong>de</strong>r providing center and radius<br />
for each ring. It can as well be used to give an estimate of center and radius of the rings which then<br />
can be used as input for fitting the ring as <strong>de</strong>scribed in section 13.6. The Hough transform framework<br />
is often applied to cope with low resolution search of rings. The Hough transform is robust to a certain<br />
extent concerning topological gaps in rings (semicircles at <strong>de</strong>tector edges) and concerning a high noise<br />
background [246, 247]. It converts points of the measurement space, i.e. hits, to points in the parameter<br />
space. In case of circles in the RICH <strong>de</strong>tector the coordinates of the parameter space are the ring centers<br />
and their radii.
13.5. RICH ring finding 331<br />
Figure 13.29: Selected region of photo<strong>de</strong>tector plane of the RICH <strong>de</strong>tector. The signals from PMTs are shown<br />
as while the track extrapolations of all charged particles to the <strong>de</strong>tector plane are plotted as +, the center of a<br />
found ring is shown as ×. The numbering shows examples for: (1) good candidates, extrapolation and ring center<br />
lie close together; (2) probably ring from secondary electron, no track extrapolation lies close to the ring center; (3)<br />
not recognized double ring; (4) + (5) fake rings from combination of background hits or signals from neighboring<br />
rings.<br />
Through three arbitrary signal points (xi,yi), i = 1,2,3 a unique circle can be drawn with the center<br />
and the radius<br />
xc = 1<br />
2<br />
(x2 2 − x2 3 + y22 − y23 )(y1 − y2) − (x2 1 − x2 2 + y21 − y22 )(y2 − y3)<br />
, (13.51)<br />
(x2 − x3)(y1 − y2) − (x1 − x2)(y2 − y3)<br />
yc = 1 (x<br />
2<br />
2 1 − x2 2 + y21 − y22 )(x2 − x3) − (x2 2 − x2 3 + y22 − y23 )(x1 − x2)<br />
(x2 − x3)(y1 − y2) − (x1 − x2)(y2 − y3)<br />
(13.52)<br />
<br />
Rc = (xi − xc) 2 + (yi − yc) 2 . (13.53)<br />
However, calculating ring center and radius for all 3-point combinations from a typical central Au+Au<br />
event at 25 AGeV (about 40 rings and signals in 1000 photomultipliers, see section 3.3.4), 1.7 · 10 8<br />
combinations have to be processed. This requires about 5000 s Cpu-Time on a 2.2 GHz computer. The<br />
resulting ring centers show a wi<strong>de</strong> distribution in the parameter space and nearly fill the full circle of<br />
real rings. This effect can easily be un<strong>de</strong>rstood consi<strong>de</strong>ring the fact, that ring center and radius from<br />
neighboring hits are only vaguely <strong>de</strong>termined. Using hits farther away results in a much better precision<br />
in the <strong>de</strong>termination of the ring centers. Therefore a procedure was <strong>de</strong>veloped reducing the number of<br />
combinations to 1/3 or even 1/5 of the above values by not combining neighboring hits. The resulting<br />
distribution of ring centers is presented in fig. 13.30. The Cpu-Time necessary to process one event was<br />
reduced to less than 80 s.
332 Event reconstruction<br />
In the future the procedure can be improved by first i<strong>de</strong>ntifying clusters of hits and estimating the number<br />
of rings from the number of hits these clusters contain, and only then running the Hough transform on<br />
these separated clusters.<br />
Figure 13.30: An example of the distribution of ring centers extracted with the Hough transform (small dots)<br />
with reduced number of hits (see text). The hits () are shown for one of the photo<strong>de</strong>tector planes for a central<br />
Au+Au collision at 25 AGeV.<br />
In the next step of the usual Hough transform strategy, ring centers and radii are <strong>de</strong>termined by the search<br />
for the most populated places in the parameter space. A simple method would consist of collecting all<br />
calculated centers (xc,yc) in histograms of proper granularity and <strong>de</strong>fining a cut-off value in the signal<br />
height to select real ring centers. The radii corresponding to each center can then be found similarly.<br />
Unfortunately, this method cannot be used here because of the largely different number of hits for rings of<br />
varying size (see fig. 3.23) resulting in different statistics and signal heights in the proposed histograms.<br />
Therefore, a contraction mapping method was used in which ring centers are searched for in these (xc,yc)<br />
histograms by means of averaging over local maxima in various steps. The first iteration inclu<strong>de</strong>s the<br />
following steps:<br />
1. Collection of all ring centers in a two-dimensional histogram with a granularity of 8.4 × 8.4 mm 2<br />
and computation of the mean values 〈xc〉, 〈yc〉, 〈Rc〉 and ΔR 2 = 〈R 2 c〉 – 〈Rc〉 2 for each of the bins.<br />
2. For bins containing more than 30 ring centers and ΔR 2 < 0.4 cm 2 neighboring bins are searched.<br />
A bin with number j is called neighboring to a bin with number i if (〈xc(i)〉 − 〈xc( j)〉) 2 + (〈yc(i)〉<br />
– 〈yc( j)〉) 2 ≤ 〈Rc(i)〉 2 . The average of all these centers is performed, { xcen[0], ycen[0], Rcen[0] },<br />
and used as input for the next iteration.<br />
The second contraction mapping accomplishes the estimation of centers and radii, this iteration could be<br />
repeated several times while reducing the granularity of the histogram in each step.<br />
1. The ring centers extracted from the first iteration (xcen[0], ycen[0]) are collected in a histogram with<br />
a granularity of 8 × 8 cm 2 and their mean values are calculated in each bin, xcen[1] = 〈xcen[0]〉,<br />
ycen[1] = 〈ycen[0]〉 and Rcen[1] = 〈Rcen[0]〉.<br />
2. Again for each center the neighboring bins are searched, here, all within a distance of 3 cm were<br />
taken. The mean of these centers is calculated, { xcen[2], ycen[2], Rcen[2] } and could be used for a<br />
next step in the iteration.
13.5. RICH ring finding 333<br />
Two iterations of the contraction mapping turned out to be enough to estimate parameters for most of the<br />
rings. After the second and last iteration, all rings were rejected to which less than a certain number of<br />
hits within a distance of 2-6 cm could be assigned. This range of distances was chosen since the majority<br />
of rings lies in this region (see fig. 3.14).<br />
Figure 13.31: Found ring centers (+) and radii after the second iteration of the contraction mapping. The central<br />
part of this picture corresponds to the fragment shown in fig. 13.29. All single rings are reliably found, however,<br />
the method has still uncertainties when <strong>de</strong>aling with overlapping rings.<br />
All reconstructed ring center and radii are shown in fig. 13.31. They can serve as an input for the ring<br />
fitting method introduced in section 13.6 which will yield more precise center and radii of the rings. In<br />
general, it could be shown that for all single rings the method works reliably. Further improvement is<br />
nee<strong>de</strong>d for overlapping rings, semicircles at the <strong>de</strong>tector edges and clusters of noise. Also, due to the<br />
rejection of rings with less than a certain number of hits, a lower bor<strong>de</strong>r on the radius of recognized rings<br />
is given.<br />
13.5.3 Elastic Net for standalone RICH ring finding<br />
The elastic net method [238] is a kind of artificial neural network [239, 240] that has been used for track<br />
recognition in high energy physics [215, 217, 241, 242]. The elastic net algorithm is one of the best<br />
optimization algorithms in terms of efficiency and speed.<br />
The method is well illustrated on a simple example of the traveling salesman problem (TSP). The traveling<br />
salesman problem is a classic problem in the field of combinatorial optimization, in which efficient<br />
methods for maximizing or minimizing a function of many in<strong>de</strong>pen<strong>de</strong>nt variables is sought. The problem<br />
is to find for a number of cities with given positions the shortest tour in which each city is visited once.<br />
All exact methods known for <strong>de</strong>termining an optimal route require a computing effort that increases<br />
exponentially with the number of cities, so in practice exact solutions can be attempted only on problems<br />
involving a few hundred cities or less. The traveling salesman problem thus belongs to the large class of<br />
non<strong>de</strong>terministic polynomial time complete problems. Many heuristic algorithms were <strong>de</strong>veloped for the<br />
TSP aiming to bypass the combinatorial difficulties [243]. One of the most successful approaches to the<br />
problem is the elastic net of Durbin and Willshaw [238]. The elastic net can be thought of as a number of<br />
beads connected by elastics to form a ring. The essence of the method is to iteratively elongate a circular
334 Event reconstruction<br />
close path in a non uniform way until it eventually passes sufficiently near to all the cities to <strong>de</strong>fine a<br />
tour.<br />
a b dc c<br />
e f<br />
d e f<br />
a b c<br />
Figure 13.32: Example of the progress of the elastic net method in the traveling salesman problem with<br />
100 cities [238]<br />
Following the <strong>de</strong>formable template approach [239], let us <strong>de</strong>note the cities byxi. We are going to match<br />
these cities with template coordinatesya such that <br />
a |ya −ya+1| is minimum and that eachxi is matched<br />
by at least one ya. Define a binary neuron sia to be 1 if a is matched to i and 0 otherwise. The following<br />
energy expression is to be minimized in a valid tour:<br />
E (sia,ya) = <br />
sia · |xi −ya| 2 + γ · <br />
|ya −ya+1| 2 . (13.54)<br />
ia<br />
The multiplier γ governs the relative strength between matching and tour length. Applying the mean field<br />
approximation [239] one can <strong>de</strong>rive the dynamical equation:<br />
<br />
Δya = η 2 <br />
<br />
via · (xi −ya) + γ · (ya+1 − 2ya +ya−1) , (13.55)<br />
where continuous neurons via <strong>de</strong>scribe matching of a to i:<br />
i<br />
a<br />
via = e−|xi−ya| 2 /T<br />
<br />
b e−|xi−yb| 2 . (13.56)<br />
/T<br />
Here the “temperature” T is <strong>de</strong>creasing at each update of templatesya, and η is the parameter controlling<br />
the minimization speed.<br />
The algorithm is thus a procedure for the successive recalculation of the positions of a number of points<br />
of the plane in which the cities lie. The points <strong>de</strong>scribe a closed path which is initially a small circle<br />
centered on the middle of the distribution of cities and is gradually elongated non-uniformly to eventually<br />
pass near all the cities and thus <strong>de</strong>fine a tour around them, see Fig. 13.32 (for <strong>de</strong>tails see the original<br />
paper [238]). Each point on the path moves un<strong>de</strong>r the influence of two types of force (see Eq. 13.55):<br />
1. the first moves it towards those cities to which it is nearest;<br />
2. the second pulls it towards its neighbors on the path, acting to minimize the total path length.<br />
By this process, each city becomes associated with a particular section on the path. The tightness of the<br />
association is <strong>de</strong>termined by how the force contributed from a city <strong>de</strong>pends on its distance, and the nature<br />
of this <strong>de</strong>pen<strong>de</strong>nce changes as the algorithm progresses. Initially all cities have roughly equal influence<br />
on each point of the path. Subsequently a larger distance becomes less favored and each city gradually<br />
becomes more influenced by the points on the path closest to it.<br />
The elastic net algorithm produces tours of the same quality as other well known heuristic algorithms [244].
13.5. RICH ring finding 335<br />
Evolution of the elastic net coordinates in continuous space results in significantly large number of iterations<br />
without changing the or<strong>de</strong>r of the cities. This can be avoi<strong>de</strong>d if the net no<strong>de</strong>s will force to coinci<strong>de</strong><br />
with cities at each iteration. Such modification of the elastic net has been <strong>de</strong>veloped by us in or<strong>de</strong>r to<br />
increase speed of the net. In this so-called discrete algorithm the elastic net can be represented as a<br />
closed tour passed exactly through a subset of the cities. An iteration consists of adding new cities to or<br />
releasing some cities from the net.<br />
File name Number of cities Extra path (%) Time, ms Time per city, µs<br />
berlin52 52 0.00 0.98 19<br />
st70 70 4.27 1.27 18<br />
kroA100 100 3.03 1.46 15<br />
lin105 105 0.78 1.84 18<br />
ch130 130 5.59 2.56 20<br />
tsp225 225 5.34 4.36 19<br />
pcb442 442 8.37 12.35 28<br />
pr1002 1002 6.12 24.94 25<br />
pr2392 2392 8.42 58.53 24<br />
Table 13.10: Extra path length (in % to the optimum) and time (in ms) of the discrete ENN algorithm in the TSP<br />
problem for several distributions of cities with known optimal tour<br />
Results of application of the discrete ENN algorithm to several distributions of cities with known optimal<br />
tour are presented in Table 13.10. The algorithm has good performance for real-life applications and is<br />
extremely fast. Numbers in the last column of the table show almost constant execution time per city<br />
that means linear behavior of the algorithm with respect to increase of the combinatorial complexity of<br />
the problem.<br />
Based on the discrete elastic net we have <strong>de</strong>veloped an algorithm for standalone RICH ring reconstruction.<br />
The algorithm has been already successfully tested on RICH data of the COMPASS experiment<br />
[245]. Here we focus on maximizing the speed of the algorithm aiming its implementation in the<br />
Level-1 trigger. The task of ring finding in the RICH <strong>de</strong>tector with about 1000 hits per event is similar in<br />
combinatorial complexity to the pr1002 example in the table 13.10. Having now additional knowledge<br />
of the form of the final tour one can expect increase of the speed down to a few milliseconds per event.<br />
The task is to reconstruct rings by measured hits on a <strong>de</strong>tection plane of the RICH <strong>de</strong>tector. As circular<br />
form of rings is pre<strong>de</strong>fined there is no need in internal forces of the elastic net. In contrast to the TSP<br />
problem here the net does not pass through all hits. The task is to find rings surroun<strong>de</strong>d by maximum<br />
hits within errors of measurements. The interaction force between hits and the net does not <strong>de</strong>pend on<br />
distance. In this case noise hits do not attract the net making the algorithm robust. The net converges to<br />
the area of maximum con<strong>de</strong>nsation of hits within 2–3 iterations, therefore the total time to reconstruct an<br />
event is proportional to:<br />
TL1ENN ∼ Nrings · Nhits per ring. (13.57)<br />
Since the rings are in<strong>de</strong>pen<strong>de</strong>nt, the algorithm reconstructs them one by one 3 . The elastic net algorithm<br />
performs searching for a ring in a local area of the <strong>de</strong>tector plane. When the ring found by the elastic net<br />
is accepted, all hits belonging to the ring are marked as used. The algorithm repeats until it recognizes<br />
rings among hits left on the plane. Rings are fitted at the step of searching. Example of a reconstructed<br />
event is given in Fig. 13.33.<br />
The performance of the L1ENNRingFin<strong>de</strong>r algorithm is presented in Table 13.11. The “all set” contains<br />
3 In a hardware implementation the algorithm can run in parallel several elastic nets.
336 Event reconstruction<br />
Figure 13.33: Example of a RICH event reconstructed by the L1ENNRingFin<strong>de</strong>r algorithm. Upper and bottom<br />
parts of the RICH <strong>de</strong>tector are shown separately. Reconstructed rings are blue, while Monte Carlo rings are drawn<br />
in red color (with slightly scaled radius to avoid overlapping with the reconstructed rings).<br />
Rings set Performance (%) Number of rings<br />
Reference set efficiency 92.21 1425<br />
All set efficiency 80.52 4179<br />
Extra set efficiency 74.47 2754<br />
Clone rate 3.26 142<br />
Ghost rate 14.98 652<br />
Found MC rings/event 33<br />
Time/event (ms) 1.07<br />
Table 13.11: Performance of the L1ENNRingFin<strong>de</strong>r algorithm taken on 100 events of central Au-Au collisions<br />
at 35 AGeV<br />
rings with more than 5 hits. In the “reference set” we put rings which originate from the target region<br />
and have more than 15 hits. The other rings form the “extra set”.<br />
A reconstructed ring is assigned to a generated Monte Carlo ring if there is at least 70% hits correspon<strong>de</strong>nce.<br />
A Monte Carlo ring is regar<strong>de</strong>d as found if it has been assigned to at least one reconstructed<br />
ring. If the ring is found more than once, all additionally reconstructed rings are regar<strong>de</strong>d as clones. A
13.6. RICH ring fitting 337<br />
reconstructed ring is called ghost if it is not assigned to any Monte Carlo ring using 70% criteria.<br />
The L1ENNRingFin<strong>de</strong>r algorithm shows a very good efficiency for reference rings (92%). Ghost rate<br />
will be suppressed at the next step when rings will be matched to tracks from other <strong>de</strong>tectors.<br />
Because of its computational simplicity and extremely high speed (1 ms), the algorithm is consi<strong>de</strong>red to<br />
be further implemented in hardware which can increase the speed by another few or<strong>de</strong>rs of magnitu<strong>de</strong>.<br />
13.6 RICH ring fitting<br />
The ring fitting methods presented in this section could come as a second step after ring finding if center<br />
and radius were not yet precisely <strong>de</strong>termined by the ring finding algorithm. The next step towards particle<br />
i<strong>de</strong>ntification with the RICH <strong>de</strong>tector, ring-track matching, is discussed in chapter 3.2.<br />
13.6.1 Robust ring fitter<br />
The RFit algorithm presented in this section was <strong>de</strong>veloped using experience from the CERES/NA45<br />
experiment at CERN and needs the approximate center and ring radius as input. Both can be taken from<br />
any of the methods <strong>de</strong>scribed in the previous section 13.5. The method has already been implemented in<br />
the CBM simulation framework cbmroot [62].<br />
RFit implements two approaches estimating the ring parameters from a set of signal points (hits) measured<br />
by the RICH <strong>de</strong>tector. Both of them require, besi<strong>de</strong>s hits, rough values of circle center coordinates<br />
and radius (ring guidance) as an input. The first approach is based on the least square fit of circles and<br />
circular arcs. This fit can be <strong>de</strong>fined as the following minimization problem. Given n points (xi,yi),<br />
1 ≤ i ≤ n, the objective function is <strong>de</strong>fined by<br />
V ≡ σ 2 n<br />
= d 2 i /n, (13.58)<br />
where, di is the geometric distance from the point (xi,yi) to the circle,<br />
<br />
<br />
di = <br />
(xi − x0) 2 + (yi − y0) 2 <br />
<br />
− r<br />
,<br />
(x0,y0) is the ring center, r is its radius. The minimization of V is a nonlinear problem that has no closed<br />
form solution, therefore all known algorithms for finding the minimum of V are either approximative or<br />
iterative and, hence, time consuming. The RFit algorithm uses the MINUIT package for minimization,<br />
more precisely, the ROOT::TMinuit class is implemented. Values of (x0,y0) and r providing the<br />
minimum to V are taken as coordinates of the searched ring center and its radius.<br />
The second approach is a generalization of the first one using the so called robustness [248, 249, 250]. It<br />
should be used for data with background and overlapping rings. Actually, it is the previous least square<br />
procedure enlarged only with a special weight function which is iteratively changed during calculations.<br />
Now, in place of (13.58), the function to be minimized is taken in the form:<br />
V ≡ σ 2 n<br />
= wid 2 n<br />
i / wi, (13.59)<br />
where weights wi are so-called Tukey’s bi-weights [251],<br />
wi =<br />
⎧<br />
⎨<br />
⎩<br />
i=1<br />
<br />
1 − d2 i<br />
c 2 T σ2<br />
i=1<br />
i=1<br />
2<br />
, di < c T σ,<br />
0, otherwise.<br />
(13.60)
338 Event reconstruction<br />
It is clear that due to Tukey’s bi-weights the contribution of hits to V <strong>de</strong>creases as their distance, di, from<br />
the ring increases. Besi<strong>de</strong>s, the most distant points (di > c T σ) are ignored at all. The strategy of ring<br />
search is similar to the simulated annealing scheme [252] with c T playing the role of a temperature. By<br />
setting c T to a big initial value in the first step, almost all hits are taken into account in a given vicinity of<br />
a guidance point. After finding the first rough image of the ring by minimizing V , it is gradually refined<br />
by a stepwise <strong>de</strong>crease of c T , and V is minimized with this smaller c T . Here, the MINUIT package<br />
is enabled for minimization, too. As a result of this “annealing” process the required circle turns out<br />
to be placed near the global minimum of the “potential” V after several iterations of the “temperature”<br />
<strong>de</strong>crease. The minimum “temperature” to which c T should drop is <strong>de</strong>fined by statistical fluctuations of<br />
the ring radii.<br />
In the CBM simulation framework cbmroot estimates for ring center and radius were used as input<br />
for the CbmRichRingFin<strong>de</strong>r class resulting in a set of fitted rings around these guidances wherever<br />
possible:<br />
• For each guidance only hits which lie within a distance of 1.5rguidance, rguidance = 5 cm, or any<br />
other preliminary estimation, are taken with weights wi = 1. All other hits are neglected by setting<br />
wi = 0. If the number of hits taken into account is less than some threshold value, the guidance<br />
un<strong>de</strong>r consi<strong>de</strong>ration is neglected. The threshold can be user <strong>de</strong>fined, otherwise the <strong>de</strong>fault value 3<br />
is taken.<br />
• Calculation of ring parameters using RFit algorithm, i.e. setting cT = 5 as the initial value and<br />
performing the following loop while cT > 1:<br />
– calculate wi using the Tukey function and the current values of σ and cT ;<br />
– minimize V varying (x0,y0) and r;<br />
– reduce cT by a factor of two: cT / = 2.<br />
• If the ring radius is larger than a · relectron, the ring is consi<strong>de</strong>red as fake and rejected.<br />
• If several guidance points belong to the same ring, i.e. the distance between both guidances is less<br />
than the ring radius, their parameters are compared. The guidance which gives the smallest σ is<br />
taken, that means the one being closest to the fitted ring center.<br />
A result of CBM RICH simulation data processing by the robust fitting algorithm is shown in Fig. 13.29.<br />
As can be seen, the precision for type (1) rings is very good. A small study (61 UrQMD events, central<br />
Au+Au collisions at 25 AGeV) has shown that for e ± and π ± coming from the primary vertex the ring<br />
fitting method was successful with close to 100% efficiency. The precision of the ring radius fitting has<br />
been found to be about 2 mm, or 4% in case of the electron rings.<br />
Further improvements of this algorithm should cover the problem of ring fitting in case of close and<br />
overlapping rings. Also possible distortions of the rings to ellipses due to the imaging properties of the<br />
mirror (see fig. 3.12) should be taken into account. A replacement of MINUIT by a specialized algorithm<br />
could save computing time.
14 Hadron i<strong>de</strong>ntification<br />
For the i<strong>de</strong>ntification of primary hadrons in CBM, the time-of-flight (TOF) <strong>de</strong>tetcor system will be used.<br />
In this section, we study its ability for i<strong>de</strong>ntification of charged pions, kaons and protons. The TOF<br />
system is located at approximately 10 m downstream of the target. For the results discussed below, we<br />
assume a time resolution of 80 ps (see chapter 5).<br />
14.1 Acceptance for TOF i<strong>de</strong>ntified particles<br />
Since the TOF system covers approximately the same angular acceptance as the STS, the requirement<br />
of a hit in TOF does not result in a restriction in the acceptance region. The acceptance probability,<br />
however, is reduced for unstable particles due to <strong>de</strong>cay-in-flight between STS and TOF.<br />
(GeV/c)<br />
t<br />
p<br />
2<br />
1.8<br />
1.6<br />
1.4<br />
1.2<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
π+<br />
0<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
rapidity<br />
(GeV/c)<br />
t<br />
p<br />
2<br />
1.8<br />
1.6<br />
1.4<br />
1.2<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
+<br />
K<br />
0<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
rapidity<br />
(GeV/c)<br />
t<br />
p<br />
2<br />
1.8<br />
1.6<br />
1.4<br />
1.2<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
p<br />
0<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
rapidity<br />
Figure 14.1: Acceptance for positively charged hadrons in central Au+Au collisions at 25 AGeV<br />
Figure 14.1 shows the geometrical acceptance for primary pions, kaons and protons, requiring at least<br />
four hits in the STS and a hit in a TOF <strong>de</strong>tector. The overall acceptances, calculated for central Au+Au<br />
events at 25 AGeV and p+A events at 80 AGeV with the UrQMD transport co<strong>de</strong>, are listed in table 14.1.<br />
Its <strong>de</strong>pen<strong>de</strong>nce on beam energy is shown in figure 14.2. Note that the acceptance calculation was done<br />
with a fixed magnetic field for all energies. By modification of the field, the acceptances can to some<br />
extent be optimised for different collision systems.<br />
reaction particle<br />
π + π − K + K − p<br />
central Au+Au at 25 AGeV (%) 39.7 39.4 34.3 35.1 54.4<br />
p + Au at 80 GeV (%) 27.6 24.9 25.5 32.8 1.6<br />
Table 14.1: Total acceptance values for two reactions<br />
14.2 Hadron i<strong>de</strong>ntification by time-of-flight<br />
The principle of particle i<strong>de</strong>ntification by time-of-flight relies on simultaneous measurement of momentum<br />
and velocity of a particle. Assuming that a track trajectory is reconstructed from the interaction<br />
vertex to the TOF system, the measured time-of-flight allows to calculate the velocity β of the particle.<br />
Together with the momentum p also following from track reconstruction, the (squared) mass of the<br />
339
340 Hadron i<strong>de</strong>ntification<br />
acceptance (%)<br />
65<br />
60<br />
55<br />
50<br />
45<br />
40<br />
35<br />
30<br />
25<br />
20<br />
π+<br />
+<br />
K<br />
10 15 20 25 30<br />
Au beam momentum (GeV/nucleon)<br />
Figure 14.2: Total acceptance in central Au+Au collisions as a function of the beam momentum for different<br />
hadron species<br />
particle can be calculated as<br />
m 2 = p 2 1<br />
<br />
− 1<br />
β2 p<br />
(14.1)<br />
In most cases, the TOF resolution σt dominates the error in the squared mass over the contributions of<br />
momentum and track length inaccuracies. Then, the error in m 2<br />
σ m 2 = 2p2<br />
β 2<br />
σt<br />
t<br />
(14.2)<br />
is in<strong>de</strong>pen<strong>de</strong>nt on m and is a quadratic function of the momentum. Because of this quadratic <strong>de</strong>pen<strong>de</strong>nce,<br />
the PID capability quickly <strong>de</strong>creases with increasing momentum as shown in figure 14.3 for positively<br />
charged particles. In the following, we concentrate on the separation of kaons from pions, since protons<br />
can be more easily i<strong>de</strong>ntified due to the larger mass difference.<br />
For the quantitative PID, the two-dimensional probability <strong>de</strong>nsity function (<strong>PDF</strong>) has to be <strong>de</strong>rived as the<br />
sum of the single particle functions:<br />
<strong>PDF</strong>(p,m 2 ) = <br />
<strong>PDF</strong> (α) (p,m 2 ) , (14.3)<br />
α<br />
where the summation runs over the contributions of pions, kaons and protons. The single particle function<br />
can be written as<br />
<strong>PDF</strong> (α) (p,m 2 ) = rα(p) fα,p(m 2 ) , (14.4)<br />
where rα(p) is the momentum spectrum of particle α after the <strong>de</strong>tector acceptance. For illustration, we<br />
assume a purely Gaussian contribution of each particle with a momentum <strong>de</strong>pen<strong>de</strong>nt width:<br />
fα,p =<br />
1<br />
√<br />
2πσm2(p) exp<br />
<br />
− (m2 − m2 α) 2<br />
2σ2 m2 <br />
(14.5)<br />
It should be mentioned that this ansatz implies an uniform resolution over the full active volume of the<br />
TOF system without any <strong>de</strong>pen<strong>de</strong>nce of the <strong>de</strong>tector response on the particle species (specific energy<br />
loss). More complicated response function can, however, be incorporated in a similar fashion.
14.2. Hadron i<strong>de</strong>ntification by time-of-flight 341<br />
(GeV/c)<br />
lab<br />
p<br />
10<br />
9<br />
8<br />
7<br />
6<br />
5<br />
4<br />
3<br />
2<br />
1<br />
-0.2 0 0.2 0.4 0.6 0.8 1 1.2<br />
2<br />
2 4<br />
m (GeV /c )<br />
10<br />
2<br />
10<br />
10<br />
1<br />
)<br />
2<br />
3<br />
/d(m<br />
lab<br />
n/dp<br />
2<br />
Figure 14.3: Distribution of m 2 versus momentum<br />
for positively charged hadrons. The distance between<br />
target and TOF <strong>de</strong>tector is 10 m, the time resolution 80<br />
ps.<br />
d<br />
)<br />
2<br />
/ d(m<br />
lab<br />
dn / dp<br />
18<br />
16<br />
14<br />
12<br />
10<br />
8<br />
6<br />
4<br />
2<br />
total<br />
+ π<br />
+<br />
K<br />
p<br />
-0.2 0 0.2 0.4 0.6 0.8 1 1.2<br />
2<br />
2 4<br />
m (GeV /c )<br />
Figure 14.4: m 2 spectrum for positively charged particles<br />
at plab = 6 GeV/c. The solid line shows the fit<br />
to the spectrum, the dotted lines the contribution of the<br />
single particle species (π,K, p).<br />
The <strong>PDF</strong> is constructed by fitting the measured m 2 distribution in momentum bins, in this case by the sum<br />
of three Gaussians as <strong>de</strong>monstrated for simulated events in figure 14.4. The result of the parametrisation<br />
is shown in figure 14.5.<br />
(GeV/c)<br />
lab<br />
p<br />
10<br />
9<br />
8<br />
7<br />
6<br />
5<br />
4<br />
3<br />
2<br />
1<br />
-0.5 0 0.5 1 1.5<br />
2<br />
2 4<br />
m (GeV /c )<br />
Figure 14.5: Probability <strong>de</strong>nsity to measure positively charged hadrons (red: pions; green: kaons; blue: protons)<br />
as a function of squared mass and momentum<br />
Kaon i<strong>de</strong>ntification can be achieved on a track-by-track basis by <strong>de</strong>fining kaon candidates by a momentum<strong>de</strong>pen<strong>de</strong>nt<br />
window in the m 2 distribution. Such a procedure is typically used for the reconstruction of<br />
<strong>de</strong>cays by the invariant mass method, where PID is employed to select <strong>de</strong>cay daughter candidates. The
342 Hadron i<strong>de</strong>ntification<br />
<strong>PDF</strong> in this case is used to calculate efficiency and purity of the selection. Figure 14.6 shows the resolution<br />
in m 2 as a function of momentum for the chosen set of parameters. It can be seen that below<br />
3.5 GeV, the ±2σ separation of kaons and pions allows a clean selection of kaons. The efficiency of<br />
K + i<strong>de</strong>ntification is shown in figure 14.7 as function of the momentum for selection purities of 50% and<br />
90%.<br />
)<br />
4<br />
/c<br />
2<br />
(GeV<br />
2<br />
m<br />
σ<br />
0.45<br />
0.4<br />
0.35<br />
0.3<br />
0.25<br />
0.2<br />
0.15<br />
0.1<br />
0.05<br />
0<br />
1 2 3 4 5 6 7 8 9 10<br />
p (GeV/c)<br />
lab<br />
Figure 14.6: Resolution in m 2 as a function of momentum.<br />
The horizontal line indicates a ±2σ separation<br />
of pions and kaons.<br />
efficiency (%)<br />
100<br />
90<br />
80<br />
70<br />
60<br />
50<br />
40<br />
30<br />
20<br />
purity 90 %<br />
purity 50 %<br />
2 3 4 5 6 7 8 9<br />
p (GeV/c)<br />
lab<br />
Figure 14.7: Efficiency of K + i<strong>de</strong>ntification as a<br />
function of momentum for the selection purities 50%<br />
and 90%<br />
For the measurement of inclusive kaon spectra, the <strong>PDF</strong> can be used for a statistical unfolding of the<br />
measured spectrum. For each track, the probability to be a kaon can be calculated from the measured momentum<br />
and m 2 according to the <strong>PDF</strong>. Figure 14.8 compares the momentum spectra of pions, kaons and<br />
protons obtained in this way to the true distributions. The reconstructed midrapidity kaon mt spectrum is<br />
shown in figure 14.10, again compared to MC truth. With the event statistics used in the simulation (10 5<br />
central Au+Au events), the method works reliably up to a momentum of 8 GeV. Figure 14.10 shows the<br />
distributions of i<strong>de</strong>ntified hadrons in the y-pt plane. The upper momentum cutoff restricts the accessible<br />
pt range at forward rapidities.
14.2. Hadron i<strong>de</strong>ntification by time-of-flight 343<br />
lab<br />
dn / dp<br />
10<br />
2<br />
10<br />
1<br />
π+<br />
+<br />
K<br />
0 1 2 3 4 5 6 7 8 9 10<br />
p (GeV/c)<br />
lab<br />
Figure 14.8: Momentum distribution of accepted and<br />
i<strong>de</strong>ntified positively charged hadrons. The solid lines<br />
show hadrons accepted in STS and TOF, the points <strong>de</strong>note<br />
the reconstructed distributions.<br />
(GeV/c)<br />
t<br />
p<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
π+<br />
0<br />
-1 0 1 2 3 4 5<br />
rapidity<br />
220<br />
0<br />
2<br />
d n / dy / dpt<br />
200<br />
180<br />
160<br />
140<br />
120<br />
100<br />
80<br />
60<br />
40<br />
20<br />
(GeV/c)<br />
t<br />
p<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
p<br />
+<br />
K<br />
dy) at midrapidity<br />
t<br />
dm<br />
t<br />
dn / (m<br />
10<br />
1<br />
-1<br />
10<br />
0<br />
-1 0 1 2 3 4 5<br />
rapidity<br />
0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2<br />
mt<br />
(GeV/c)<br />
Figure 14.9: Transverse mass spectrum of K − at<br />
midrapidity. The solid line shows the spectrum of accepted<br />
particles, the points the reconstructed spectrum.<br />
16<br />
14<br />
12<br />
10<br />
8<br />
6<br />
4<br />
2<br />
0<br />
2<br />
d n / dy / dpt<br />
0<br />
-1 0 1 2 3 4 5<br />
rapidity<br />
Figure 14.10: Phase space distribution of TOF-i<strong>de</strong>ntified hadrons. The two solid lines show the geometrical<br />
acceptance of the STS and TOF and correspond to the polar angles 2.5 and 27 <strong>de</strong>grees. The dotted line shows the<br />
i<strong>de</strong>ntification limit for K + at p = 8 GeV/c.<br />
(GeV/c)<br />
t<br />
p<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
p<br />
60<br />
50<br />
40<br />
30<br />
20<br />
10<br />
0<br />
2<br />
d n / dy / dpt
344 Hadron i<strong>de</strong>ntification
15 Hyperons<br />
Hyperons will be measured in CBM by their <strong>de</strong>cay into charged hadrons, which are <strong>de</strong>tected in the STS<br />
and TOF systems. Table 15.1 shows the properties of the hyperons accessible by this method.<br />
The feasibility of the hyperon measurement in CBM has been studied in a first step using Monte-Carlo<br />
simulations un<strong>de</strong>r i<strong>de</strong>alised conditions: No magnetic field, i<strong>de</strong>al track finding, i<strong>de</strong>al particle i<strong>de</strong>ntification<br />
for the <strong>de</strong>cay daughters. Tracks were fitted by straight lines assuming the position resolution in the STS<br />
to be 10 µm. The momentum resolution was assumed to be 1 %. The study is based on 10 5 central<br />
Au+Au collisions at 25 AGeV, simulated by UrQMD and transported through the CBM setup. For the<br />
acceptance, the secondary charged tracks are required to have hits in at least four tracking stations and in<br />
TOF.<br />
Mass [GeV/c 2 ] Lifetime cτ [cm] Multiplicity Decay channel BR [%]<br />
Λ 1.116 7.89 36.6 p + π − 63.9<br />
Ξ − 1.321 4.91 0.99 Λ + π − 99.9<br />
Ω − 1.672 2.46 0.02 Λ + K − 67.8<br />
Table 15.1: Properties of the hyperons accessible through their <strong>de</strong>cays into charged hadrons. The yield of Λ<br />
contains the contribution of the Σ 0 <strong>de</strong>cay, which is experimentally not separable by the i<strong>de</strong>ntification method used<br />
in this section.<br />
15.1 Λ hyperons<br />
The geometrical acceptance for Λ, requiring both <strong>de</strong>cay daughters to be accepted in the STS and TOF<br />
<strong>de</strong>tectors, is shown in figure 15.1. Maximal acceptance (≈ 50 %) is achieved near midrapidity and<br />
intermediate transverse momentum. The total acceptance, given the original distribution as predicted by<br />
UrQMD, is 15.9 %. Releasing the constraints of PID, i. e. not requiring the tracks to enter TOF, results<br />
in an acceptance of 27.3 %. The magnetic field reduces the acceptance to 7.7 % (STS + TOF) and 18.1<br />
% (STS only), respectively.<br />
Figure 15.2 (left) shows the invariant-mass distribution for all pπ − pairs. The Λ signal is visible above a<br />
large combinatorial background ma<strong>de</strong> predominantly by primary particles. It is reconstructed by fitting<br />
a Gaussian on top of a second or<strong>de</strong>r polynomial for the background. The assumed momentum resolution<br />
of 1 % translates into an invariant-mass resolution of 0.86 MeV/c 2 . The signal to background ratio,<br />
calculated in the range of ±2σm, is about 0.12.<br />
To reduce the background, the <strong>de</strong>cay topology is exploited by the following geometrical cuts:<br />
• bpp The impact parameters of protons and pions, <strong>de</strong>fined as the distance of the track extrapolation<br />
to the interaction vertex in the target plane. This cuts reduces the amount of primary particles.<br />
• bla The impact parameter of the Λ candidate, <strong>de</strong>fined as the distance of the extrapolation of the<br />
pair momentum to the interaction vertex in the target plane. This cut reduces random combinations<br />
but also secondary Λ from Ξ and Ω <strong>de</strong>cays.<br />
These cuts were optimised with respect to the signal to background ratio by studying the simulated<br />
distributions of the cut variables for signal and background pairs. The values for S/B, significance and<br />
345
346 Hyperons<br />
pairs/0.3 MeV<br />
1200<br />
1000<br />
800<br />
600<br />
400<br />
200<br />
3<br />
× 10<br />
[GeV/c]<br />
T<br />
p<br />
2<br />
1.8<br />
1.6<br />
1.4<br />
1.2<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
0<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
y<br />
Figure 15.1: STS+TOF acceptance in the rapidity-pt plane for pπ − pairs from Λ <strong>de</strong>cays.<br />
0<br />
1.1 1.105 1.11 1.115 1.12 1.125 1.13<br />
2<br />
M [GeV/c ]<br />
inv<br />
pairs/0.3 MeV<br />
3<br />
× 10<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
1.1 1.105 1.11 1.115 1.12 1.125 1.13<br />
2<br />
M [GeV/c ]<br />
inv<br />
pairs/0.3 MeV<br />
50000<br />
40000<br />
30000<br />
20000<br />
10000<br />
1<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
0<br />
0<br />
1.1 1.105 1.11 1.115 1.12 1.125 1.13<br />
2<br />
M [GeV/c ]<br />
inv<br />
Figure 15.2: Invariant pπ − mass for all pairs (left), after blp cut (centre) and after blp+bla cut (right)<br />
Cut Cut value S/B ratio Significance efficiency<br />
no cut 0.12 144 1.00<br />
bpp > 0.10 cm 1.27 483 0.77<br />
+ bla < 0.02 cm 697 574 0.60<br />
Table 15.2: Signal to background ratio, significance and efficiency for primary Λ before cuts, after the bpp cut<br />
and after bpp and bla cuts. The significance corresponds to 10 5 central Au+Au events at 25 AGeV.<br />
efficiency are given in table 15.2. As figure 15.2 <strong>de</strong>monstrates, there is almost no remaining background<br />
after the application of the two cuts.<br />
Other cut variables like z position of the point of closest approach of the tracks and distance of closest<br />
approach were also studied but did not further improve the background reduction.<br />
To reconstruct the original Λ spectrum, the signal was extracted in bins of rapidity and pt. The integral<br />
over the Gaussian distribution was consi<strong>de</strong>red to be the uncorrected Λ yield in the respective phase space<br />
bin. Corrections for geometrical acceptance, branching ratio and cut efficiency were applied on a binby-bin<br />
basis. Figure 15.3 shows the corrected transverse momentum spectra in two rapidity bins and the
15.2. Ξ − hyperons 347<br />
corrected rapidity distribution in comparison to the initial input distributions generated by UrQMD. In<br />
case of incomplete pt coverage, the transverse spectrum was extrapolated assuming a thermal distribution<br />
dn<br />
d pt<br />
∝ pt e −mt/T<br />
(15.1)<br />
to obtain the dn/dy values. The rapidity distribution was fitted by a Gaussian function to obtain the total<br />
Λ yield to be 36.4, in good agreement with the input yield of 36.6 (see table 15.1). We conclu<strong>de</strong> that<br />
un<strong>de</strong>r the i<strong>de</strong>alised assumptions as <strong>de</strong>scribed above, the phase space distributions and total yield of Λ<br />
hyperons can be satisfyingly measured in the CBM setup. The required event statistics of central Au+Au<br />
collisions is of the or<strong>de</strong>r of 10 5 .<br />
dy<br />
T<br />
dn/dp<br />
ev<br />
1/N<br />
0.20<br />
0.18<br />
0.16<br />
0.14<br />
0.12<br />
0.10<br />
0.08<br />
0.06<br />
0.04<br />
0.02<br />
0.00<br />
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2<br />
p T [GeV/c]<br />
dy<br />
T<br />
dn/dp<br />
ev<br />
1/N<br />
0.45<br />
0.40<br />
0.35<br />
0.30<br />
0.25<br />
0.20<br />
0.15<br />
0.10<br />
0.05<br />
0.00<br />
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2<br />
p T [GeV/c]<br />
dn/dy<br />
ev<br />
1/N<br />
3.5<br />
3<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
0<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
y<br />
Figure 15.3: Λ phase space distributions in simulated central Au+au collision at 25 AGeV beam momentum. Left:<br />
pt spectrum for y = 0.8 − 1.0; centre: pt spectrum for y = 1.8 − 2.0; right: rapidity distribution. The histograms<br />
show the initial distributions, the solid points the reconstructed ones. The full lines show the fit functions as<br />
<strong>de</strong>scribed in the text.<br />
15.2 Ξ − hyperons<br />
The measurement of Ξ − hyperons in the <strong>de</strong>cay channel Ξ − → Λπ − → pπ − π − requires all three charged<br />
particles in the final state to be accepted by STS and TOF simultaneously. The geometrical acceptance for<br />
the Ξ − as function of rapidity and transverse momentum is shown in figure 15.4. The global acceptance<br />
for Ξ − as generated by UrQMD is 5.5 % (STS+TOF) and 16 % (STS only). Applying the magnetic field<br />
changes this numbers to 1.9 % (STS+TOF) and 7.7 % (STS only), respectively. This acceptance values<br />
already contain the Λ → pπ − branching ratio.<br />
For the reconstruction of the Ξ − , candidates for the Λ <strong>de</strong>cay daughter have to be selected. We apply<br />
an impact parameter cut of 0.05 cm for protons and pions. This reduces the combinatorial background<br />
significantly while cutting only marginally into the signal (efficiency for Λ from Ξ − <strong>de</strong>cay 98 %). Λ<br />
candidates are selected by a ±0.8 MeV window in the pπ − invariant mass. The combined efficiency for<br />
the Λ selection is 90 %. The invariant-mass distribution for combinations of selected Λ candidates with<br />
π − is shown in figure 15.5. We use the cuts <strong>de</strong>scribed in the previous section now for the Λ candidate<br />
and the π − . Again, the combination of impact parameter cuts on the daughters (blp) and on the pair<br />
momentum (bxi) turns out to be the appropriate one. The cut values, signal-to-background ratio and<br />
efficiency are listed in table 15.3.<br />
For the reconstruction of the original Ξ − distribution, Ξ − were generated according to the pt and y distributions<br />
predicted by UrQMD. 10 5 geometrically accepted Ξ − <strong>de</strong>cays were embed<strong>de</strong>d into full UrQMD<br />
events. The daughter tracks of Ξ hyperons produced by the UrQMD generator itself were removed from<br />
the events. Taking into account the Ξ − multiplicity, branching ratio and geometrical acceptance, this
348 Hyperons<br />
pairs/0.4 MeV<br />
90000<br />
80000<br />
70000<br />
60000<br />
50000<br />
40000<br />
30000<br />
20000<br />
10000<br />
[GeV/c]<br />
T<br />
p<br />
2<br />
1.8<br />
1.6<br />
1.4<br />
1.2<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
0<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
y<br />
Figure 15.4: STS+TOF acceptance in the rapidity-pt plane for Λπ − pairs from Ξ − <strong>de</strong>cays<br />
0<br />
1.3 1.305 1.31 1.315 1.32 1.325 1.33 1.335 1.34<br />
2<br />
M [GeV/c ]<br />
inv<br />
pairs/0.4 MeV<br />
1400<br />
1200<br />
1000<br />
800<br />
600<br />
400<br />
200<br />
0<br />
1.3 1.305 1.31 1.315 1.32 1.325 1.33 1.335 1.34<br />
2<br />
M [GeV/c ]<br />
inv<br />
pairs/0.4 MeV<br />
250<br />
200<br />
150<br />
100<br />
50<br />
1<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
0<br />
0<br />
1.3 1.305 1.31 1.315 1.32 1.325 1.33 1.335 1.34<br />
2<br />
M [GeV/c ]<br />
inv<br />
Figure 15.5: Invariant Λπ − mass for all pairs (left), after blp cut (centre) and after blp+bla cut (right)<br />
Cut Cut value S/B ratio Significance Efficiency<br />
no cut 0.004 4.5 0.58<br />
blp > 0.10 cm 0.35 29.4 0.42<br />
+ bxi < 0.01 cm 1075 36.5 0.17<br />
Table 15.3: Signal to background ratio, significance and efficiency for Ξ − before cuts, after the blp cut and after<br />
blp and bxi cuts. The efficiency before cuts is due to the Λ branching ratio and the Λ selection efficiency (see text).<br />
The significance corresponds to 10 5 central Au+Au events at 25 AGeV.<br />
corresponds to 1.8 · 10 6 events. The invariant-mass background with the appropriate event statistics was<br />
obtained by event mixing of fully simulated UrQMD events, again with the Ξ signal removed from the<br />
track sample. This background was then ad<strong>de</strong>d to the mass spectrum obtained from the events containing<br />
accepted Ξ − . This procedure provi<strong>de</strong>s sufficient statistics for the double differential extraction of Ξ −<br />
yields without the generation and transport of too many UrQMD events, which is CPU-prohibitive.<br />
The signal is again extracted from invariant-mass spectra in y-pt bins by fitting a Gaussian on top of a<br />
polynomial background (σm = 1.14MeV/c 2 ). The reconstructed spectra after corrections for acceptance<br />
and efficiency are compared in figure 15.6 to the original ones. The Ξ − yield is slightly un<strong>de</strong>restimated
15.3. Ω − hyperons 349<br />
by the method, which is probably due to the Gaussian <strong>de</strong>scription of the invariant-mass signal. The<br />
reconstructed yield (0.856) is 13 % lower than the initial one.<br />
dn/dpTdy<br />
1/Nev<br />
0.010<br />
0.008<br />
0.006<br />
0.004<br />
0.002<br />
0.000<br />
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2<br />
p T [GeV/c]<br />
dn/dpTdy<br />
1/Nev<br />
0.016<br />
0.014<br />
0.012<br />
0.010<br />
0.008<br />
0.006<br />
0.004<br />
0.002<br />
0.000<br />
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2<br />
p T [GeV/c]<br />
dn/dy<br />
1/Nev<br />
0.12<br />
0.1<br />
0.08<br />
0.06<br />
0.04<br />
0.02<br />
0<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
y<br />
Figure 15.6: Same as figure 15.3, but for Ξ − . The statistics corresponds to 1.8 · 10 6 events.<br />
15.3 Ω − hyperons<br />
The Ω − analysis was performed in the same way as for the Ξ − , replacing the secondary π − by K − . The<br />
geometrical acceptance, <strong>de</strong>fined by requiring STS and TOF hits for all three secondaries, is shown in<br />
figure 15.7. The overall acceptance is 3.3 %. Releasing the constraint of particles having to reach the<br />
TOF <strong>de</strong>tector gives an acceptance of 14.6 %. The magnetic field changes this numbers into 1.5 % and<br />
7.9 %, respectively.<br />
Λ candidates are selected in the same way as for the Ξ − analysis. The efficiency for the selection is 89 %.<br />
Figure 15.8 shows the invariant ΛK − mass spectrum before all cuts, after the impact parameter cut on<br />
the secondaries and after all cuts. The cut parameter values are 0.10 cm for the blk cut and 0.03 cm for<br />
the bom cut (see table 15.4). As in the case of Λ and Ξ − , the mass spectrum after all cuts is essentially<br />
background free. The efficiency of the Ω selection cuts is 67 %.<br />
[GeV/c]<br />
T<br />
p<br />
2<br />
1.8<br />
1.6<br />
1.4<br />
1.2<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
0<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
y<br />
Figure 15.7: STS+TOF acceptance in the rapidity-pt plane for ΛK − pairs from Ω − <strong>de</strong>cays<br />
1<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
0
350 Hyperons<br />
pairs/0.4 MeV<br />
2200<br />
2000<br />
1800<br />
1600<br />
1400<br />
1200<br />
1000<br />
800<br />
600<br />
400<br />
200<br />
3<br />
× 10<br />
0<br />
1.65 1.655 1.66 1.665 1.67 1.675 1.68 1.685 1.69<br />
M inv [GeV/c^2]<br />
pairs/0.4 MeV<br />
9000<br />
8000<br />
7000<br />
6000<br />
5000<br />
4000<br />
3000<br />
2000<br />
1000<br />
0<br />
1.65 1.655 1.66 1.665 1.67 1.675 1.68 1.685 1.69<br />
M inv [GeV/c^2]<br />
pairs/0.4 MeV<br />
7000<br />
6000<br />
5000<br />
4000<br />
3000<br />
2000<br />
1000<br />
0<br />
1.65 1.655 1.66 1.665 1.67 1.675 1.68 1.685 1.69<br />
M inv [GeV/c^2]<br />
Figure 15.8: Invariant ΛK − mass for all pairs (left), after blk cut (centre) and after blk+bom cut (right)<br />
Cut Cut value S/B ratio Significance Efficiency<br />
no cut 0.003 14.4 0.38<br />
blk > 0.10 cm 2.17 199 0.27<br />
+ bom < 0.02 cm 642 231 0.23<br />
Table 15.4: Signal to background ratio, significance and efficiency for primary Ω − before cuts, after the blk cut<br />
and after blk and bom cuts. The significance corresponds to 3.5 · 10 8 central Au+Au events at 25 AGeV.<br />
The Gaussian fit to the signal gives an invariant-mass resolution of σm = 1.20 MeV/c 2 . Figure 15.9<br />
compares the reconstructed distributions in pt and y to the input spectra generated by UrQMD. The<br />
10 5 simulated Ω − in the <strong>de</strong>tector acceptance correspond, according to multiplicity, branching ratios and<br />
acceptance, to 1.4·10 8 events. The reconstructed yield (2.29·10 −2 ) is close to the simulated multiplicity.<br />
dy<br />
T<br />
dn/dp<br />
ev<br />
1/N<br />
0.16<br />
0.14<br />
0.12<br />
0.10<br />
0.08<br />
0.06<br />
0.04<br />
0.02<br />
-3<br />
× 10<br />
0.00<br />
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2<br />
p T [GeV/c]<br />
dy<br />
T<br />
dn/dp<br />
ev<br />
1/N<br />
0.35<br />
0.30<br />
0.25<br />
0.20<br />
0.15<br />
0.10<br />
0.05<br />
-3<br />
× 10<br />
0.00<br />
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2<br />
p T [GeV/c]<br />
dn/dy<br />
ev<br />
1/N<br />
0.003<br />
0.0025<br />
0.002<br />
0.0015<br />
0.001<br />
0.0005<br />
0<br />
0 0.5 1 1.5 2<br />
y<br />
2.5 3 3.5 4<br />
Figure 15.9: Same as figure 15.3, but for Ω − . The statistics corresponds to 1.4 · 10 8 events.<br />
15.4 Conclusions<br />
The analyses presented in the last sections must be regar<strong>de</strong>d as a first step towards realistic feasibility<br />
studies for hyperon measurement in CBM. In particular, realistic track finding and fitting in the magnetic<br />
field will lead to worse results than obtained here by using transport simulations only. The numbers<br />
given in the previous sections thus have to be regar<strong>de</strong>d as upper limits. However, some preliminary<br />
conclusions can be drawn. The measurement of Λ, Ξ − and Ω − hyperons in the currently foreseen CBM<br />
setup is feasible; the setup of the STS system gives rise to a satisfactory acceptance coverage. The<br />
number of events required to obtain particle spectra and yields is of the or<strong>de</strong>r of 10 5 for Λ, 10 6 for Ξ −
15.4. Conclusions 351<br />
and 10 8 for Ω − . The latter number corresponds to some hours at the foreseen untriggered event taking<br />
rate.<br />
Number of events<br />
220<br />
200<br />
180<br />
160<br />
140<br />
120<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
1.1121.1131.1141.1151.1161.1171.1181.119 1.12<br />
Mass, GeV<br />
Figure 15.10: Reconstructed Λ mass obtained by usage of the parabolic approximation of track fitting. The full<br />
line shows a Gaussian fit with σm = 1.3MeV/c 2 .<br />
The next task in this study is to inclu<strong>de</strong> realistic tracking in the field. First steps in this direction have<br />
already been taken. Figure 15.10 shows the reconstructed Λ mass using a track fitting routine based<br />
on the parabolic approximation (see section 13.2.4). A Gaussian fit to the signal gives a mass of mΛ =<br />
1.116GeV/c 2 and a resolution of σm = 1.3MeV/c 2 .
352 Hyperons
16 Low-mass vector mesons<br />
16.1 Introduction<br />
Investigation of the invariant mass spectrum of short lived neutral vector mesons (ρ, ω, φ) via <strong>de</strong>tection<br />
of their electron-positron pairs is one of the major issue of the CBM physics. Besi<strong>de</strong>s of the electronpositron<br />
pairs that originate from the meson <strong>de</strong>cays, there is a huge number of electrons and positrons<br />
from other physical sources. Among them the Dalitz <strong>de</strong>cays and the gamma conversion in the target<br />
and <strong>de</strong>tector material budged are the most prominent ones. In addition, the charged pions misi<strong>de</strong>ntified<br />
as electrons contribute to the background. Although dozens of the vector mesons are produced in each<br />
central nucleus-nucleus collision, the dielectron <strong>de</strong>cay channel branching ratios of the vector mesons are<br />
very small (see Table 16.1) and sophisticated methods have to be <strong>de</strong>veloped to i<strong>de</strong>ntify real signals. In<br />
or<strong>de</strong>r to verify the feasibility of measurements of the invariant mass spectrum of these mesons a computer<br />
simulation have been performed.<br />
Particle N/event Decay BR pairs/event<br />
π o 372 π o → e + e − γ 1.198 × 10 −2 4.46<br />
η o 37 η o → e + e − γ 5.0 × 10 −3 0.18<br />
ω 12 ω → e + e − π o 5.9 × 10 −4 7.1 × 10 −3<br />
ω → e + e − 7.07 × 10 −5 8.5 × 10 −4<br />
φ 0.6 φ → e + e − η 1.3 × 10 −4 0.78 × 10 −4<br />
φ → e + e − 3.1 × 10 −4 1.86 × 10 −4<br />
ρ 22 ρ → e + e − 4.44 × 10 −5 9.8 × 10 −4<br />
Table 16.1: Meson multiplicities and their leptonic <strong>de</strong>cay channels inclu<strong>de</strong>d in the analysis.<br />
16.2 Simulation tools<br />
• Nucleus-nucleus collision event generator.<br />
There are no experimental data available on the particle multiplicities for nucleus-nucleus collisions<br />
at the SIS200 energies. Therefore, the relativistic transport co<strong>de</strong> UrQMD [253] was used as<br />
the event generator. Our data base contains three sets of simulated Au + Au central collision events<br />
at 15, 25 and 35 GeV/nucleon. Each set contains 10 5 events.<br />
• Vector meson <strong>de</strong>cays event generator.<br />
The PLUTO [254] event generator was applied to simulate the light vector meson <strong>de</strong>cays. The<br />
input to this co<strong>de</strong> was obtained from the UrQMD simulation and contains the meson rapidity<br />
and transverse momentum distributions. The multiplicities of the mesons were estimated from<br />
UrQMD and HSD [256] co<strong>de</strong> and STAR [255] experimental results. Average numbers of e + e −<br />
pairs produced via the <strong>de</strong>cay of various particles are presented in Table 16.1.<br />
• Transport co<strong>de</strong>.<br />
The CBM experimental set up geometry was inclu<strong>de</strong>d into the GEANT3 [257] package from<br />
353
354 Low-mass vector mesons<br />
CERN and the <strong>de</strong>dicated transport co<strong>de</strong> for CBM experiment was obtained. This package is a part<br />
of the CBM analysis framework called cbmroot.<br />
• Light vector meson analysis tools.<br />
The feasibility study of invariant mass spectrum of short lived neutral vector mesons are performed<br />
using a package of procedures and co<strong>de</strong>s named CAT (CBM Analysis Tools) which was <strong>de</strong>veloped<br />
by the Kraków group.<br />
16.3 Background suppression - cut strategy<br />
In or<strong>de</strong>r to suppress the combinatorial background, the following cuts have been applied to single tracks<br />
or track pairs:<br />
• The first cut - gamma conversion cut.<br />
This cut rejects a pair of e + and e − leptons if their closest proximity distance D is smaller than 250<br />
µm and the invariant mass of this leptonic pair is smaller than 0.1 GeV/c 2 .<br />
• The second cut - single particle cut.<br />
This cut is set on each particle (e + or e − ). The lepton is rejected if its track distance from the<br />
collision vertex is greater than 250 µm and its transverse momentum is smaller than 0.1 GeV/c.<br />
• The third cut - non-restrictive particle cut.<br />
This cut rejects e + or e − lepton if pairing this particle with all other unlike sign particles does not<br />
provi<strong>de</strong> any partner that fulfills all of the following conditions:<br />
1. The angle between the particle tracks is greater than 10 <strong>de</strong>grees.<br />
2. The transverse (vt) and longitudinal (vz) distances of the particle pair vertex from the collision<br />
vertex are smaller than 150 µm and 1 mm, respectively.<br />
3. The tracks distance D is smaller than 250 µm.<br />
• The forth cut - restrictive particle cut.<br />
This cut is removing the e + e − pair if it does not fulfill any of the following conditions:<br />
1. The angle between the tracks is greater than 10 <strong>de</strong>grees.<br />
2. The transverse (vt) and longitudinal (vz) distances of the particle pair vertex from the collision<br />
vertex are smaller than 150 µm and 1 mm, respectively.<br />
3. The tracks distance D is smaller than 250 µm.<br />
One has to note that the or<strong>de</strong>r in which the cuts are set is very important on the background suppression<br />
result.<br />
16.4 Results of signal to background ratio studies<br />
We started our analysis using a parametrized <strong>de</strong>tector acceptance and the following simplifying assumptions:<br />
• 100% efficiency of electron i<strong>de</strong>ntification.<br />
• 1% particle momentum resolution.<br />
• No magnetic field.
16.4. Results of signal to background ratio studies 355<br />
• Gold target thickness of 100 µm.<br />
• Vacuum beam pipe ma<strong>de</strong> of carbon fiber with a wall thickness of 0.5 mm.<br />
• Seven silicon tracking stations placed at the distances of 5, 10, 20, 40, 60, 80 and 100 cm downstream<br />
from the target. The first two tracking stations are 100 µm thick and the others are 200 µm<br />
thick.<br />
Figure 16.1 presents the simulated e + e − invariant mass spectrum resulting from 10 8 Au + Au central<br />
collisions at 25A GeV after the four cuts <strong>de</strong>scribed in sec. 1.3 have been applied (black dashed line).<br />
The combinatorial background, obtained by the so called same-event technique (solid red line) is clearly<br />
dominating the spectrum. The background-subtracted spectrum, shown by the histogram, satisfactorily<br />
reproduces the signal input to the simulation as indicated by the blue dashed-dotted line, thus confirming<br />
the background subtraction procedure. From this analysis, we <strong>de</strong>rive a signal-to-background ratios (S/B)<br />
of 95 and 250 for (ρ + ω) and φ mesons, respectively.<br />
]<br />
-1<br />
[(25 MeV)<br />
-4<br />
10<br />
-<br />
e<br />
+<br />
e<br />
/dM<br />
-<br />
10<br />
e<br />
+<br />
e<br />
dN<br />
-5<br />
-6<br />
10<br />
0 0.2 0.4 0.6 0.8 1 1.2 2<br />
[Gev/c ]<br />
M + -<br />
e e<br />
+ - e (1)<br />
+<br />
e<br />
-<br />
e-)<br />
2* (e e+<br />
)(e (2)<br />
polynomial fit to (2)<br />
(1) - polynomial fit<br />
Pluto + Geant4<br />
Figure 16.1: Simulated e + e − invariant mass spectrum for i<strong>de</strong>al case.<br />
In or<strong>de</strong>r to perform more realistic studies the pion misi<strong>de</strong>ntification and limited tracking efficiency were<br />
taken into account. Figure 16.2 presents invariant mass spectrum with 90% of tracking reconstruction<br />
efficiency. This effect lowers the signal-to-background ratio to 21 and 70 for (ρ + ω) and φ mesons,<br />
respectively. Another effect, the pion misi<strong>de</strong>ntification at the level of 0.01% lowers the S/B ratios to<br />
the values 60 and 148 for (ρ + ω) and φ mesons, respectively (see Fig. 16.3). The combined effect,<br />
inefficiency and pion misi<strong>de</strong>ntification, leads to S/B ratios equal to 14 and 37 for (ρ + ω) and φ mesons,<br />
respectively, as presented at figure 16.4.
356 Low-mass vector mesons<br />
]<br />
-1<br />
[(25 MeV)<br />
-<br />
e<br />
+<br />
e<br />
/dM<br />
+ -<br />
e e<br />
dN<br />
-4<br />
10<br />
10<br />
-5<br />
-6<br />
10<br />
-7<br />
+ - e e (1)<br />
+ + - -<br />
2* (e e )(e e ) (2)<br />
polynomial fit to (2)<br />
(1) - polynomial fit<br />
Pluto + Geant4<br />
10<br />
0 0.2 0.4 0.6 0.8 1 1.2<br />
2<br />
M + - [Gev/c ]<br />
Figure 16.2: Simulated e + e − invariant mass spectrum with 90% efficiency assumed.<br />
]<br />
-1<br />
[(25 MeV)<br />
-<br />
e<br />
+<br />
e<br />
/dM<br />
+ -<br />
e e<br />
dN<br />
-4<br />
10<br />
10<br />
-5<br />
-6<br />
10<br />
-7<br />
10<br />
0 0.2 0.4 0.6 0.8 1 1.2<br />
2<br />
M + - [Gev/c ]<br />
e e<br />
+ - e e (1)<br />
+ + - -<br />
2* (e e )(e e ) (2)<br />
polynomial fit to (2)<br />
(1) - polynomial fit<br />
Pluto + Geant4<br />
Figure 16.3: Simulated e + e − invariant mass spectrum with pion misi<strong>de</strong>ntification at the level of 0.01%.<br />
]<br />
-1<br />
[(25 MeV)<br />
-<br />
e<br />
+<br />
e<br />
/dM<br />
-<br />
+<br />
e e<br />
dN<br />
10<br />
10<br />
-4<br />
-5<br />
-6<br />
10<br />
0 0.2 0.4 0.6 0.8 1 1.2<br />
2<br />
M + - [Gev/c ]<br />
e e<br />
+ - e e (1)<br />
+ + - -<br />
2* (e e )(e e ) (2)<br />
polynomial fit to (2)<br />
(1) - polynomial fit<br />
Pluto + Geant4<br />
Figure 16.4: Simulated e + e − invariant mass spectrum with 90% efficiency assumed and pion misi<strong>de</strong>ntification<br />
effect at the level of 0.01 %<br />
e e
17 Charmonium<br />
The measurement of charmonium is one of the key goals of the CBM experiment. The main difficulty<br />
lies in the extremely low multiplicity expected in Au+Au collisions near the J/ψ production threshold.<br />
CBM will <strong>de</strong>tect the J/ψ meson in its leptonic <strong>de</strong>cay channels. For the dielectron measurement, the main<br />
task is the separation of electrons and pions and the suppression of electrons originating from secondary<br />
interactions. In case of the measurement in the µ + µ − channel, it is mandatory to suppress muons from<br />
weak <strong>de</strong>cays of pions and kaons.<br />
Figure 17.1 <strong>de</strong>picts the yields of open and hid<strong>de</strong>n charm as function of beam energy, obtained by the<br />
Hadron String Dynamics (HSD) mo<strong>de</strong>l. The calculations were performed for central events. These<br />
multiplicities serve as input for the simulations to be <strong>de</strong>scribed in the next sections. The UrQMD and<br />
HSD predictions for the multiplicites of all relevant particles produced in central Au+Au collisions at<br />
different beam energies are given in tables 12.1 and tables 12.2 (chapter 12).<br />
Figure 17.1: Multiplicities of D 0 , D 0 , D + , D − and J/ψ predicted for central Au+Au collisions as functions of<br />
beam energy by the HSD mo<strong>de</strong>l<br />
17.1 J/ψ <strong>de</strong>tection via e + e − <strong>de</strong>cay<br />
17.1.1 Signal and background simulation<br />
The simulation of signal and background were performed with the CBM software framework CBM-<br />
ROOT, using the standard setup with a gold target of 250 µm thickness, the beam pipe, the STS, the<br />
RICH and three TRD stations.<br />
For the J/ψ signal, we used the multiplicity as predicted by HSD. The J/ψ phase space distribution and<br />
the <strong>de</strong>cay kinematics were calculated with the PLUTO event generator, assuming a thermal source with<br />
a temperature of 150 (170, 190) MeV for beam energies of 15 (25, 35) AGeV, respectively.<br />
357
358 Charmonium<br />
The main background sources are<br />
• e + e − pairs from conversion of γ (mostly from π 0 and η <strong>de</strong>cay) in the material of target and <strong>de</strong>tectors,<br />
• Dalitz <strong>de</strong>cays of π 0 and η,<br />
• charged pions misi<strong>de</strong>ntified as electrons,<br />
• dielectronic <strong>de</strong>cays of low-mass vector mesons,<br />
• semileptonic <strong>de</strong>cay of open charm.<br />
The contribution from Drell-Yan is not yet consi<strong>de</strong>red. The background was obtained by transporting<br />
UrQMD events through the <strong>de</strong>tector setup. Since this generator does not <strong>de</strong>scribe charmed hadrons and<br />
leptonic <strong>de</strong>cays of vector mesons, these source were simulated by HSD and ad<strong>de</strong>d to the UrQMD events.<br />
Because of the fact that track reconstruction and particle i<strong>de</strong>ntification are not yet available, the following<br />
assumptions were ma<strong>de</strong> for the analysis:<br />
• The combined electron i<strong>de</strong>ntification in RICH and TRD gives an electron efficiency of 90 %. A<br />
pion suppression factor of 10 −4 can be achieved.<br />
• The momentum resolution is 1 %.<br />
• Secondary particles created by interactions in the <strong>de</strong>tectors can be recognised by the STS tracking<br />
routines. We therefore consi<strong>de</strong>r only particles originating from the target region.<br />
)<br />
-1<br />
(GeV<br />
t<br />
dn / dp<br />
10<br />
10<br />
1<br />
-1<br />
-2<br />
10<br />
-3<br />
10<br />
-4<br />
10<br />
-5<br />
10<br />
-6<br />
10<br />
-7<br />
10<br />
-8<br />
10<br />
π0 γ<br />
η<br />
±<br />
mis<strong>de</strong>ntified π<br />
D<br />
J/ Ψ<br />
-9<br />
10<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
pt<br />
(GeV/c)<br />
Figure 17.2: Transverse momentum distribution of electrons and positrons from various sources as calculated<br />
with UrQMD or HSD for central Au+Au collisions at 25 AGeV beam energy. Black: γ conversion in the target;<br />
blue: π 0 Dalitz <strong>de</strong>cay; green: η Dalitz <strong>de</strong>cay; magenta: misi<strong>de</strong>ntified charged pions for a suppression factor of<br />
10 −4 ; grey: open charm; red: J/ψ calculated with PLUTO assuming T = 170 MeV<br />
Figure 17.2 shows the transverse momentum spectra of accepted electrons for the different background<br />
sources, compared to the signal distribution. Most of the background processes create electrons with low
17.1. J/ψ <strong>de</strong>tection via e + e − <strong>de</strong>cay 359<br />
pt, in contrast to the leptonic J/ψ <strong>de</strong>cay. A pt cut at 1 GeV/c already suppresses most of the background<br />
tracks without cutting seriously into the signal.<br />
17.1.2 Acceptance and efficiency<br />
The single electron acceptance is <strong>de</strong>fined by requiring a hit in all three TRD stations. Since STS, RICH<br />
and TRD cover approximately the same angular acceptance, this implies that such tracks can be reconstructed<br />
in the STS. Figure 17.3 shows the pt and y distributions of the accepted J/ψ compared to the<br />
intial ones. The two-dimensional distribution of J/ψ accepted after the pt cut is shown in figure 17.4.<br />
Obviously, the pt cut does not restrict the acceptance region, which covers roughly one unit of rapidity.<br />
The total J/ψ efficiency, including geometrical acceptance and pt cut, is about 35 %.<br />
)<br />
-1<br />
dn/dp_t (GeV<br />
0.03<br />
0.025<br />
0.02<br />
0.015<br />
0.01<br />
0.005<br />
0<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
pt<br />
(GeV/c)<br />
dn/dy<br />
0.07<br />
0.06<br />
0.05<br />
0.04<br />
0.03<br />
0.02<br />
0.01<br />
0<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
y<br />
Figure 17.3: Distribution in transverse momentum (left) and rapidity (right) for J/ψ mesons. Black: all J/ψ<br />
<strong>de</strong>caying into e + e − ; red J/ψ accepted in the <strong>de</strong>tector; blue: J/ψ accepted after the pt cut at 1 GeV/c on the <strong>de</strong>cay<br />
daughters<br />
(GeV/c)<br />
t<br />
p<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
0<br />
1 1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 2.8 3<br />
Figure 17.4: Yield of J/ψ mesons in the pt vs. rapidity plane for geometrically accepted pairs after the pt cut<br />
Y<br />
300<br />
250<br />
200<br />
150<br />
100<br />
50<br />
0
360 Charmonium<br />
17.1.3 Signal to background ratio<br />
The invariant-mass spectrum is calculated from combinations of electrons and positrons (including<br />
misi<strong>de</strong>ntified pions) from the target region after applying the cut on pt. To obtain sufficient statistics<br />
from the simulated 145 k events from UrQMD, the event mixing technique was applied. The resulting<br />
“superevent” is equivalent to 2 · 10 10 events. Of course, by mixing events all physical correlations<br />
between the background electrons and positrons are neglected. Figure 17.5 compares the result of the<br />
event mixing technique with the invariant-mass spectrum obtained from the event-by-event analysis for<br />
a pt cut at 0.5 GeV/c.<br />
)<br />
2<br />
pairs/(20 MeV/c<br />
10<br />
10<br />
-3<br />
-4<br />
10<br />
-5<br />
-6<br />
10<br />
-7<br />
10<br />
-8<br />
10<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
2<br />
(GeV/c )<br />
Figure 17.5: Invariant e + e − mass spectra calculated for background pairs with the superevent method (red<br />
histogram) and with the event-by-event method (blue histogram) for a transverse momentum cut of pt > 0.5 GeV/c<br />
The invariant-mass distributions for the pt cut of 1 GeV/c and for different assumptions about the pion<br />
suppression factor are shown in figure 17.6 (left). While at a pion suppression of 100 no J/ψ signal can<br />
be seen, a suppression of 10 −4 suffices to almost eliminate the influence of misi<strong>de</strong>ntified pions on the<br />
signal-to-background ratio.<br />
The signal-to-background ratio can be further improved by requiring a larger minimal transverse momentum<br />
for the single tracks. Invariant-mass spectra for different cut values are compared in figure 17.6. The<br />
J/ψ region of the spectra are shown in linear representation in figure 17.7. The signal yield is <strong>de</strong>termined<br />
by fitting a Gaussian peak on top of a polynomial representing the combinatorial background. For the<br />
calculation of the signal-to-background ratio, the distributions are integrated in a ±2σm window around<br />
the peak. The resulting values of S/B and the J/ψ efficincy are given in table 17.1 for three different<br />
beam energies and pt cut values.<br />
pt cut S/B ε(J/ψ) S/B ε(J/ψ) S/B ε(J/ψ)<br />
GeV/c 15 AGeV 15 AGeV 25 AGeV 25 AGeV 35 AGeV 35 AGeV<br />
1 0.77 0.25 1 0.34 1.2 0.39<br />
1.3 1.48 0.13 2.5 0.17 3.5 0.19<br />
1.5 3.36 0.027 3.36 0.04 3.36 0.045<br />
Table 17.1: Signal-to-background ratio and J/ψ efficiency for central Au+Au collisions at 15, 25, and 35 AGeV.<br />
The efficiency comprises geometrical acceptance, losses due to the pt cut and electron i<strong>de</strong>ntification efficiency.<br />
minv
17.1. J/ψ <strong>de</strong>tection via e + e − <strong>de</strong>cay 361<br />
2<br />
pairs/ 40 MeV/c<br />
5<br />
10<br />
4<br />
10<br />
3<br />
10<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
2<br />
( GeV/c )<br />
minv<br />
2<br />
pairs / 40 MeV/c<br />
4<br />
10<br />
3<br />
10<br />
2<br />
10<br />
10<br />
pt<br />
>1GeV/c<br />
p > 1.3 GeV/c<br />
t<br />
p >1.5GeV/c<br />
t<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
2<br />
( GeV/c )<br />
Figure 17.6: Invariant e + e − mass spectra representing 2 · 10 10 central Au+Au collisions at 25 AGeV. Left: for<br />
a transverse momentum cut of pt > 1GeV/c and different pion suppression factors (magenta: 10 −2 ; green: 10 −3 ;<br />
blue: 10 −4 ; red: without pion contamination). Right: For different transverse momentum cuts (magenta: pt > 1<br />
GeV/c; green: pt > 1.3 GeV/c; blue: pt > 1.5 GeV/c) and a pion suppression of 10 −4 .<br />
8000<br />
6000<br />
4000<br />
2000<br />
0<br />
2.6 2.8 3 3.2 3.4 3.6<br />
2<br />
minv<br />
(GeV/c )<br />
2200<br />
2000<br />
1800<br />
1600<br />
1400<br />
1200<br />
1000<br />
800<br />
600<br />
400<br />
200<br />
0<br />
2.6 2.8 3 3.2<br />
minv<br />
3.4<br />
(GeV/c<br />
2<br />
)<br />
minv<br />
2.6 2.7 2.8 2.9 3 3.1 3.2 3.3 3.4 3.5<br />
2<br />
(GeV/c )<br />
Figure 17.7: Invariant e + e − mass spectra for different pt cuts with fit in the J/ψ mass region for 2 · 10 10 central<br />
Au-Au collisions at 25 AGeV<br />
17.1.4 Online event selection<br />
The previous sections have shown that 10 10 or more events are required for the measurement of J/ψ<br />
in the dielectron channel. This corresponds to a beam time of the or<strong>de</strong>r of some hours, the envisaged<br />
interaction rate being 10 6 for central reactions. However, the limited event archival rate calls for a highly<br />
selective online event selection. The selection <strong>de</strong>cision must be fast and efficient and should thus be<br />
based on a minimal amount of input data, coming from as few as possible <strong>de</strong>tector subsystems. In this<br />
first approach, we have focussed on the information available from the Transition Radiation Detectors<br />
(TRD), which <strong>de</strong>liver tracking as well as electron ID information while having a sufficiently fast <strong>de</strong>tector<br />
response.<br />
For the estimation of the event rejection possibilities using only TRD information, minimum bias Au+Au<br />
events at 25 AGeV beam energy generated by UrQMD were transported through the <strong>de</strong>tector setup using<br />
GEANT3 as transport engine. Only charged pions and protons as the main contributors to the background<br />
were consi<strong>de</strong>red; the acceptance is <strong>de</strong>fined by the first TRD station. We quantify the pion rejection due<br />
to the TRD measurement by the pion rejection factor PRF = 100 − k, where k is the percentage of<br />
500<br />
400<br />
300<br />
200<br />
100<br />
minv
362 Charmonium<br />
misi<strong>de</strong>ntified pions.<br />
The main cut variable is the single track transverse momentum as motivated in the previous section.<br />
We assume in this first step perfect momentum <strong>de</strong>termination. In a next step, the momentum will be<br />
reconstructed from the TRD information alone assuming that the particles originate from the target. A<br />
first approach to this problem is presented in the next section; alternatively, the momentum could be<br />
obtained quite performantly with the use of a lookup table.<br />
The event selection criterion is a pair of oppositely charged particles with an invariant mass greater than<br />
2 GeV/c 2 . Figure 17.8 shows the percentage of events fulfilling this criterion as a function of the single<br />
particle pt cut for different assumptions about the PRF. For a PRF of 98, equivalent to a pion suppression<br />
by a factor of 50 which is foreseen to be reached with the TRD <strong>de</strong>tectors, the event rejection factor is<br />
about 15 for a pt cut at 1 GeV/c. This parametric study shows that the inclusion of information from<br />
ECAL or RICH, resulting in a better pion suppression, is probably nee<strong>de</strong>d to arrive at higher event<br />
rejection factors.<br />
Survivors [%]<br />
2<br />
10<br />
10<br />
1<br />
-1<br />
10<br />
PRF = 98<br />
PRF = 10<br />
0.4 0.6 0.8 1 1.2 1.4<br />
Transversal momentum Pt [GeV/c]<br />
Figure 17.8: Percentage of minimum bias Au+Au events (25 AGeV) that survived the event selection (a pair of<br />
oppositely charged particles with invariant mass greater than 2 GeV/c 2 ) as a function of the minimal single particle<br />
pt for different values of the PRF. The full lines show the simulation results for primary particles only, the dotted<br />
lines take in addition into account secondary particles produced by <strong>de</strong>cays or interactions in the <strong>de</strong>tector materials.<br />
17.1.5 Fast track reconstruction in the TRD<br />
To study the possibility of fast J/ψ reconstruction using only information from TRD, J/ψ <strong>de</strong>cays into<br />
e + e − were simulated with the PLUTO generator and ad<strong>de</strong>d to background UrQMD events (central<br />
Au+Au at 25 AGeV). The combined events were transported through the experimental setup in the presence<br />
of the inhomogeneous CBM magnetic field using the CBMROOT <strong>de</strong>tector simulation framework.<br />
The TRD geometry consists of three stations located at 4 m, 6 m and 8 m distance from the target, respectively.<br />
Each station consists of three sensitive layers. The position resolution in x direction was assumed<br />
to be 0.4 mm, 0.5 mm and 0.6 mm for the three stations, respectively, and varied from 2.7 mm to 33 mm<br />
in the y direction according to the distance from the beam. The x and y directions alternate from layer to<br />
layer. This assumption emulates a MWPC type readout of the TRDs.<br />
A track is accepted if it traverses all three TRD stations. In this first approach, i<strong>de</strong>al track finding is<br />
assumed. The track parameters x, y, tx = px/pz and ty = py/pz, <strong>de</strong>fined at the z position of the first TRD
17.1. J/ψ <strong>de</strong>tection via e + e − <strong>de</strong>cay 363<br />
layer, were obtained at by the Kalman filter technique (section 13.2.1). Since the TRDs are operated<br />
outsi<strong>de</strong> of the magnetic field, a simple track mo<strong>de</strong>l can be used, resulting in a good timing performance<br />
of the Kalman filter algorithm.<br />
For the fast reconstruction of the original track parameters, we assume that the track originates from the<br />
primary vertex. Then, the inverse momentum can be approximated by<br />
q<br />
p =<br />
[x − (z − ztarget)tx] 1 +t 2 x<br />
<br />
1 +t 2 x +t 2 <br />
y dl By<br />
(zmagnet − ztarget)<br />
, (17.1)<br />
where ztarget and zmagnet are the z coordinates of the target midplane and the centre of the magnet, respectively,<br />
and q the charge of the particle. The average field integral dl By is obtained by a Monte<br />
Carlo simulation of electrons from J/ψ <strong>de</strong>cay as shown in figure 17.9. The relative precision is about<br />
5 %. Figure 17.10 <strong>de</strong>monstrates the accuracy of the momentum <strong>de</strong>termination by this approximation.<br />
The average momentum resolution is about 8 %.<br />
Figure 17.9: Distribution of the magnetic field constant<br />
(zmagnet − zvertex) dl By for the simulated e + and<br />
e − from J/ψ <strong>de</strong>cays<br />
Figure 17.10: Distribution of relative momentum<br />
residuals for e + and e − using the fast momentum reconstruction<br />
in the TRD (see text)<br />
Since in first approximation, the Bx and Bz components of the CBM dipole field are vanishing, the slope<br />
ty,i at the track origin can be approximated by ty, f measured in the TRD 1 . In the bending plane, tx, f<br />
will differ from tx,i by the <strong>de</strong>flection angle Δθ. Figure 17.11 shows the correlation between initial and<br />
final slope for pz = 1.3−1.4 GeV/c as resulting from the simulation. As expected, a linear <strong>de</strong>pen<strong>de</strong>nce is<br />
obtained. By a fit, Δθ = tx, f −tx,i is <strong>de</strong>rived. In this way, the <strong>de</strong>flection angle is calculated for 0.5GeV/c <<br />
pz < 1.5GeV/c. As can be seen in figure 17.12, its <strong>de</strong>pen<strong>de</strong>nce on pz can be parametrised as Δθ =<br />
0.304GeV/(cpz).<br />
Using this empirical <strong>de</strong>pen<strong>de</strong>nce, tx,i can be calculated from the measured tx, f . Figure17.13 compares its<br />
reconstructed to the true value. The original track slopes are reproduced with an accuracy of about 5 %.<br />
tx,i completes the momentum reconstruction at the primary vertex.<br />
The e + e − invariant mass spectrum, calculated with the momenta estimated by this method, is compared<br />
in figure 17.14 to the MC truth. Due to the limited precision of the momentum reconstruction, some<br />
signal pairs are shifted out of the J/ψ invariant mass region. Most of them (92 %), however, still satisfy<br />
a possible online condition minv > 2 GeV/c 2 (see section 17.1.4), as suggested in the previous section.<br />
1 The subscripts i and f stand for initial and final, respectively.
364 Charmonium<br />
Figure 17.11: Distribution in the tx,i −tx, f plane for e +<br />
and e − from simulated J/ψ <strong>de</strong>cays. The momentum range<br />
is 1.3 - 1.4 GeV/c.<br />
Figure 17.12: Deflection angle as function of momentum<br />
Figure 17.13: Reconstructed versus true tx,i for e + and e − from J/ψ <strong>de</strong>cay<br />
Figure 17.14: Invariant e + e − mass spectrum for tracks accepted in the TRD system. Left: calculated using the<br />
true electron momenta; right: calculated with the momenta obtained by the fast TRD reconstruction (see text). The<br />
relative normalisation of signal and background spectra is arbitrary. Note that the background spectrum does not<br />
contain misi<strong>de</strong>ntified charged pions.
17.2. J/ψ <strong>de</strong>tection via µ + µ − <strong>de</strong>cay 365<br />
17.1.6 Conclusions and next steps<br />
The feasibility studies presented in the previous sections have <strong>de</strong>monstrated that the measurement of<br />
J/ψ should be feasible in the foreseen CBM <strong>de</strong>tector setup provi<strong>de</strong>d that a charged pion suppression of<br />
10 3 can be reached. The required event number is of the or<strong>de</strong>r of 10 10 for 25 AGeV beam energy; it<br />
is a strong function of beam energy due to the steep J/ψ excitation function near the threshold. The<br />
event rejection factors achievable with the use of TRD only are of the or<strong>de</strong>r of 10 - 20 <strong>de</strong>pending on the<br />
transverse momentum cut applied and the pion suppression achieved by the TRD.<br />
The next steps towards more realistic simulations are:<br />
• implementation of track and momentum reconstruction with the STS based on realistic digitisers,<br />
in particular for the Silicon Strip <strong>de</strong>tectors,<br />
• full tracking from target to ECAL based on digitizers for STS, TRD, RPC and ECAL,<br />
• electron i<strong>de</strong>ntification and pion suppression obtained from realistic simulations of RICH and TRD,<br />
• further <strong>de</strong>velopment of fast momentum reconstruction methods using only TRD information,<br />
• inclusion of ECAL and/or RICH information for the fast event selection.<br />
It is clear that these studies will provi<strong>de</strong> crucial feedback for <strong>de</strong>tector optimisations. One case in point<br />
is the TRD, for which the position resolution requirements will be mainly <strong>de</strong>rived based on J/ψ selection<br />
requirements. The <strong>de</strong>tector layout (distance between layers and stations) and material budget are<br />
important issues, too.<br />
17.2 J/ψ <strong>de</strong>tection via µ + µ − <strong>de</strong>cay<br />
In addition to the dielectron measurement, the possibilitiy of the <strong>de</strong>tection of J/ψ mesons via their <strong>de</strong>cay<br />
into µ + µ − has been studied. This measurement would require a muon <strong>de</strong>tector located after the TOF<br />
wall. It might be either a longitudinally segemented ECAL or an additonal <strong>de</strong>dicated <strong>de</strong>vice behind the<br />
ECAL. The study presented in this section has been started recently and is still in a preliminary state.<br />
17.2.1 Signal and background simulation<br />
The simulation setup is the same as used for the dielectron channel (section 17.1). The J/ψ signal <strong>de</strong>cay<br />
was simulated with the PLUTO generator assuming a thermal source with a temperature of 130 MeV.<br />
The J/ψ multiplicity was taken from the HSD prediction (see figure 17.1). The background, consisting<br />
mainly of weak <strong>de</strong>cays of charged pions and kaons, was calculated with the UrQMD event generator.<br />
Both signal and background are transported through the <strong>de</strong>tector setup with CBMROOT employing<br />
GEANT3. All simulations were done for central Au+Au collisions at 25 AGeV beam energy.<br />
In this first step, the analysis is based on the following simplifying assumptions:<br />
• The muons are <strong>de</strong>tected with 100% efficiency in a plane located 11 m downstream of the target.<br />
• I<strong>de</strong>al track finding is assumed. The momentum resolution was assumed to be 1%.<br />
Fig. 17.15 <strong>de</strong>picts the transverse momentum distributions of muons at a distance of 11 m downstream<br />
of the target. At this distance about 7% of the pions and about 26% of the kaons un<strong>de</strong>rwent a weak
366 Charmonium<br />
t<br />
dn/dp<br />
10<br />
10<br />
-1<br />
-2<br />
-3<br />
10<br />
-4<br />
10<br />
-5<br />
10<br />
-6<br />
10<br />
-7<br />
10<br />
-8<br />
10<br />
-9<br />
10<br />
-10<br />
10<br />
-11<br />
10<br />
Mother particles<br />
π+/<br />
π-<br />
K+/K-<br />
K0 long<br />
1% misi<strong>de</strong>ntified π+/<br />
π-<br />
J/ Ψ<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
pt<br />
(GeV/c)<br />
Figure 17.15: Transverse momentum distribution of background and signal muons for central Au+Au collisions<br />
at 25 AGeV<br />
<strong>de</strong>cay into a muon and a muon neutrino. For muon transverse momenta above 1 GeV/c, pions and kaons<br />
contribute almost equally to the background. In addition to these background sources, figure 17.15<br />
contains a contribution of 1% misi<strong>de</strong>ntified pions and, for comparison, muons from the <strong>de</strong>cay of J/ψ<br />
mesons.<br />
Figure 17.16 compares the two-dimensional distribution of the muon transverse momenta for signal and<br />
background pairs (the relative yields do not reflect realistic multiplicities). The plot illustrates that a cut<br />
on the single muon transverse momentum of pt > 1 GeV/c suppresses about 99% of the background but<br />
only about 20% of the signal.<br />
(GeV/c)<br />
-<br />
μ<br />
t<br />
p<br />
4<br />
3.5<br />
3<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
0<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
pt<br />
μ+<br />
(GeV/c)<br />
45<br />
40<br />
35<br />
30<br />
25<br />
20<br />
15<br />
10<br />
5<br />
(GeV/c)<br />
-<br />
μ<br />
t<br />
p<br />
4<br />
3.5<br />
3<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
0<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
pt<br />
μ+<br />
(GeV/c)<br />
Figure 17.16: Transverse momentum of µ − versus transverse momentum of µ + for muons from J/ψ <strong>de</strong>cay (left)<br />
and for background muons (right)<br />
17.2.2 Signal to background ratio<br />
To obtain the combinatorial background in the dimuon invariant mass spectrum after the pt cut with<br />
sufficient statistics, the superevent method (combination of muons from different events) was used as<br />
<strong>de</strong>scribed in section 17.1. The spectrum calculated from the 21,000 simulated events thus corresponds<br />
to 4.4 · 10 8 central Au+Au events. Figure 17.17 <strong>de</strong>monstrates the validity of this method by comparing<br />
4<br />
10<br />
3<br />
10<br />
2<br />
10<br />
10
17.2. J/ψ <strong>de</strong>tection via µ + µ − <strong>de</strong>cay 367<br />
the spectra calculated event by event and from the superevent for a pt cut at 0.5 GeV/c.<br />
counts/(event*10MeV)<br />
-2<br />
10<br />
-3<br />
10<br />
-4<br />
10<br />
-5<br />
10<br />
10<br />
-6<br />
-7<br />
10<br />
-8<br />
10<br />
-9<br />
10<br />
Superevent<br />
Pt > 0.5 GeV/c<br />
Pt > 1 GeV/c<br />
Event-by-Event<br />
Pt > 0.5 GeV/c<br />
Pt > 1 GeV/c<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
m inv<br />
(GeV/c<br />
Figure 17.17: Dimuon invariant mass distributions of the background dimuon pairs. Red and black histogram:<br />
superevent method. Blue and green histogram: event-by-event method. The red and blue histograms correspond<br />
to a transverse momentum cut of pt > 0.5 GeV/c, the green and black histograms to pt > 1.0 GeV/c. The spectra<br />
are normalised to on event (central Au+Au at 25 AGeV).<br />
counts/(event*10MeV)<br />
-2<br />
10<br />
-3<br />
10<br />
-4<br />
10<br />
-5<br />
10<br />
10<br />
-6<br />
-7<br />
10<br />
-8<br />
10<br />
-9<br />
10<br />
Pt > 0.5 GeV/c<br />
Pt > 1.0 GeV/c<br />
Pt > 1.3 GeV/c<br />
Pt > 1.5 GeV/c<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
m inv<br />
(GeV/c<br />
Figure 17.18: Dimuon invariant mass spectra for central Au+Au collisions at 25 AGeV, including a 1% contamination<br />
of misi<strong>de</strong>ntified π + /π − mesons. The colors refer to different transverse momentum cuts (red: pt > 0.5<br />
GeV/c; green: pt > 1 GeV/c; blue: pt > 1.3 GeV/c; magenta: pt > 1.5 GeV/c).<br />
According to HSD calculations, the J/ψ multiplicity in central Au+Au collisions at 25 AGeV is about<br />
1.9 × 10 −5 . Taking into account the branching ratio of 6%, the yield of J/ψ mesons <strong>de</strong>caying into a<br />
dimuon pair is only about 10 −6 . Figure 17.18 presents the dimuon invariant mass spectra for different<br />
values of the transverse momentum cut on the single muons. The spectra contain a contribution of 1%<br />
misi<strong>de</strong>ntified charged pions. The J/ψ signal is not visible for any choice of the minimal pt. Figure<br />
17.19 shows the efficiency for the J/ψ <strong>de</strong>tection and the signal to background ratio, calculated in a ±2σm<br />
window around the signal peak, as function of the minimal single muon pt. For a cut at 1 GeV/c, the S/B<br />
2<br />
)<br />
2<br />
)
368 Charmonium<br />
ratio is about 0.2 %, the efficiency being about 42 %. Apparently, pt cuts above 1.5 GeV/c are prohibitive<br />
because of the rapid drop in <strong>de</strong>tection efficiency.<br />
The influence of charged pion misi<strong>de</strong>ntification is illustrated in figure 17.20, showing the invariant mass<br />
spectrum for different charged pion suppression factors. Varying the suppression between 10 −2 and 10 −3<br />
has no major impact on the background distribution in the J/ψ mass region.<br />
efficiency (%)<br />
2<br />
10 mu+/mu- from J/Psi<br />
10<br />
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6<br />
p cut (GeV/c)<br />
t<br />
signal/background<br />
-1<br />
10<br />
-2<br />
10<br />
-3<br />
10<br />
0.4 0.6 0.8 1 1.2 1.4 1.6<br />
p cut (GeV/c)<br />
t<br />
mu+/mu-<br />
Figure 17.19: Efficiency for J/ψ meson <strong>de</strong>tection (left panel) and signal to background ratio (right panel) as<br />
function of the transverse momentum cut pt<br />
counts/(event*10MeV)<br />
-5<br />
10<br />
-6<br />
10<br />
-7<br />
10<br />
Pt > 1 GeV/c. Misi<strong>de</strong>ntified pions:<br />
1.0 %<br />
0.5 %<br />
0.1 %<br />
0 0.5 1 1.5 2 2.5 3 3.5<br />
m inv<br />
(GeV/c<br />
Figure 17.20: Invariant mass spectrum of muon pairs from central Au+Au collisions at 25 AGeV after a transverse<br />
momentum cut of pt > 1 GeV/c. The spectra inclu<strong>de</strong> the combinatorial background, the J/ψ signal and<br />
different contributions of misi<strong>de</strong>ntified π + and π − mesons (red: 1%, green: 0.5%, blue: 0.1%).<br />
Further suppression of the background muons from weak meson <strong>de</strong>cays could achieved by measuring the<br />
kink angle between the trajectory of the meson and its <strong>de</strong>cay daughter. The distributions of this angle are<br />
shown in figure 17.21. By a cut in this variable, most of the muon background originating from pion or<br />
kaon <strong>de</strong>cay can be eliminated as shown in figure 17.22. The remaining background is almost exclusively<br />
due to misi<strong>de</strong>ntified pions, which cannot be suppressed by the kink angle cut. A measurement of J/ψ in<br />
2<br />
)
17.2. J/ψ <strong>de</strong>tection via µ + µ − <strong>de</strong>cay 369<br />
the dimuon channel thus requires a charged pion supression of 10 −3 or more and a measurement of the<br />
kink angle with a precision of a <strong>de</strong>gree or better.<br />
counts/event<br />
10<br />
1<br />
-1<br />
10<br />
-2<br />
10<br />
-3<br />
10<br />
-4<br />
10<br />
11 m<br />
all<br />
pt > 1 GeV/c<br />
0 20 40 60 80 100 120 140 160 180<br />
kink angle, <strong>de</strong>grees<br />
counts/event<br />
10 11 m<br />
all<br />
pt > 1 GeV/c<br />
1<br />
-1<br />
10<br />
-2<br />
10<br />
-3<br />
10<br />
-4<br />
10<br />
0 20 40 60 80 100 120 140 160 180<br />
kink angle, <strong>de</strong>grees<br />
Figure 17.21: Kink-angles between the trajectories of mesons and their <strong>de</strong>cay muons with transverse momentum<br />
cut pt > 1 GeV/c (green) and without (red). Left panel: pions; Right panel:kaons.<br />
counts/(event*10MeV)<br />
-5<br />
10<br />
-6<br />
10<br />
-7<br />
10<br />
-8<br />
10<br />
-9<br />
10<br />
Pt > 1 GeV/c, 0.1 % misi<strong>de</strong>ntified pions<br />
all<br />
kink angle < 1.0 <strong>de</strong>gree<br />
kink angle < 0.5 <strong>de</strong>gree<br />
kink angle < 0.1 <strong>de</strong>gree<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
m inv<br />
(GeV/c<br />
Figure 17.22: Invariant mass spectrum of muon pairs from central Au+Au collisions at 25 AGeV. The spectra<br />
inclu<strong>de</strong> the combinatorial background, the J/ψ signal and a 0.1% contribution of misi<strong>de</strong>ntified π + and π − mesons.<br />
The background is suppressed by the transverse momentum cut of pt > 1 GeV/c, and by different kink angle cuts<br />
of 1.0 o (red histogram), 0.5 o (blue histogram), and 0.1 o (green histogram).<br />
17.2.3 I<strong>de</strong>ntification of primary muons<br />
As shown in the previous section, a key issue in the measurement of J/ψ in the dimuon channel is the<br />
suppression of muons from weak <strong>de</strong>cays of pions and kaons. The separation of these muons from those<br />
emerging from the target area can be accomplished with a number of tracking <strong>de</strong>vices placed on the way<br />
to the muon-i<strong>de</strong>ntification <strong>de</strong>vice. In each tracking station of such a system, the position and the flight<br />
2<br />
)
370 Charmonium<br />
direction of a charged particle will be registered. In the current CBM setup, the STS and the three TRD<br />
stations serve as such tracking tools.<br />
A <strong>de</strong>cay of a pion or a kaon into a muon and a neutrino can be <strong>de</strong>tected due to a kink in the trajectory.<br />
In the following only pions <strong>de</strong>cays are consi<strong>de</strong>red because kink angles for kaon <strong>de</strong>cays are several times<br />
larger. In case the <strong>de</strong>cay occurs between two consecutive tracking stations, the position of the track of<br />
the <strong>de</strong>cay-muon extrapolated from the second tracking plane to the first tracking plane will substantially<br />
differ from the position of the pion registered in the first plane. If a pion does not <strong>de</strong>cay between two<br />
consecutive planes, the accuracy of the extrapolation will be limited by the multiple scattering in between<br />
the two planes, which is practically the same for pions and muons.<br />
2*R_max<br />
muon<br />
pion<br />
First Detector<br />
Fit<br />
Point<br />
Multiple Scattering<br />
Kink<br />
Second Detector<br />
muon<br />
muon<br />
ACCEPTED<br />
REJECTED<br />
a.u.<br />
6<br />
5<br />
4<br />
3<br />
2<br />
1<br />
muons multiple scattering<br />
RMS = 0.084<br />
pions kink<br />
RMS = 0.898<br />
0<br />
-2 -1.5 -1 -0.5 0 0.5 1 1.5 2<br />
distance in X coordinate [cm]<br />
Figure 17.23: Extrapolation of tracks between two consecutive tracking planes. The track in the second plane<br />
is extrapolated back to the first plane placed 2 m upstream. The distance to the original point in the first plane is<br />
projected onto an axis perpendicular to the initial momentum of a particle. Magenta: muons that un<strong>de</strong>rgo smallangle<br />
scattering, blue: pions that <strong>de</strong>cay into muons and neutrinos. Small-angle scattering takes place only in the<br />
air in between the two planes. A perfect position resolution in both tracking planes is assumed.<br />
The impact of pion <strong>de</strong>cay between two neighbouring tracking stations was studied in a first step assuming<br />
i<strong>de</strong>al position resolution and accurate <strong>de</strong>termination of the track angle in the tracking stations. Only<br />
multiple scattering in the air between the stations has been taken into account. Figure 17.23 shows results<br />
of simulations for pions <strong>de</strong>cayed in between the two planes (blue histogram) and muons (magenta). The<br />
distances between the true positions registered in the first tracking plane and positions extrapolated from<br />
the second plane were projected onto one of the axes perpendicular to the original direction of particles.<br />
The momenta of muons and pions at the first tracking plane are 2 GeV/c; the distance between the two<br />
planes is 2 m.<br />
In or<strong>de</strong>r to study the efficiency of the rejection of <strong>de</strong>cay-muons, we <strong>de</strong>fine a radius Rmax around the true<br />
position in the first tracking plane in which the extrapolated point will be searched for. All cases for<br />
which the extrapolation falls outsi<strong>de</strong> Rmax are rejected as <strong>de</strong>cay muons. Reducing Rmax results in a better<br />
rejection of pion <strong>de</strong>cays but also in a smaller efficiency for true muons. We <strong>de</strong>fine the Rejection Factor<br />
RF as<br />
f romπ<br />
Nµ (R < Rmax)<br />
RF =<br />
Nall . (17.2)<br />
π<br />
It quantifies the amount of background due to pion <strong>de</strong>cays that survive the selection criterion. The left<br />
panel of figure 17.24 shows RF as a function of the distance between the two tracking planes for different<br />
values of Rmax and for pions with 2 GeV/c momentum. The <strong>de</strong>pen<strong>de</strong>nce of RF on the pion momentum<br />
for a fixed Rmax = 1 mm is illustrated in the right panel of figure 17.24.
17.2. J/ψ <strong>de</strong>tection via µ + µ − <strong>de</strong>cay 371<br />
RF<br />
×<br />
2.2<br />
2.0<br />
1.8<br />
1.6<br />
1.4<br />
1.2<br />
1.0<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
-3<br />
10<br />
0.5mm<br />
1mm<br />
1.5mm<br />
2mm<br />
2.5mm<br />
3mm<br />
0.0<br />
50 100 150 200 250 300 350 400 450 500<br />
distance [cm]<br />
RF<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
-3<br />
× 10<br />
1 GeV<br />
2 GeV<br />
3 GeV<br />
4 GeV<br />
5 GeV<br />
6 GeV<br />
7 GeV<br />
8 GeV<br />
9 GeV<br />
10 GeV<br />
0.0<br />
50 100 150 200 250 300 350 400 450 500<br />
distance [cm]<br />
Figure 17.24: Left: rejection of pions with 2 GeV/c momentum for different selection criteria Rmax as a function<br />
of distance between two tracking planes. Right: rejection of pions with selection criterion Rmax = 1mm for different<br />
momenta as a function of distance between two tracking planes.<br />
The efficiency of the selection for true muons is <strong>de</strong>fined as<br />
EF = Ntrue<br />
µ (R < Rmax)<br />
N true<br />
µ<br />
(17.3)<br />
and plotted in figure 17.25 as a function of the distance of the tracking stations for fixed muon momentum<br />
of 2 GeV/c and different Rmax (left panel) and for fixed Rmax = 1 mm and different muon momenta (right<br />
panel). For a given distance d between the tracking planes and for a given selection criterion Rmax, both<br />
RF and EF rise with particle momenta. However, the increase of the efficiency is stronger. Therefore, it<br />
is plausible to conclu<strong>de</strong> that the capability of separation of true muons from <strong>de</strong>cay muons improves with<br />
increasing particle momenta.<br />
EF<br />
1.0<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
0.5mm<br />
1mm<br />
1.5mm<br />
2mm<br />
2.5mm<br />
3mm<br />
0.0<br />
50 100 150 200 250 300 350 400 450 500<br />
distance [cm]<br />
EF<br />
1.0<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
1 GeV<br />
2 GeV<br />
3 GeV<br />
4 GeV<br />
5 GeV<br />
6 GeV<br />
7 GeV<br />
8 GeV<br />
9 GeV<br />
10 GeV<br />
0.0<br />
50 100 150 200 250 300 350 400 450 500<br />
distance [cm]<br />
Figure 17.25: Left: acceptance of true muons with 2 GeV/c momentum for different selection criteria Rmax as a<br />
function of distance between two tracking planes. Right: acceptance of true muons with selection criterion Rmax =<br />
1 mm for different momenta as a function of distance between two tracking planes.<br />
In or<strong>de</strong>r to study the signal to background ratio for the J/ψ i<strong>de</strong>ntification, the following assumptions were<br />
ma<strong>de</strong>:
372 Charmonium<br />
• the J/ψ multiplicity is 1.9 · 10 −5 per central event,<br />
• the phase-space distribution of J/ψ is according to the source parameters T=150 MeV and Δy = 0.8,<br />
• J/ψ <strong>de</strong>cays into muons with a branching ratio of 5.97 %.<br />
For the background, 1000 central Au+Au events at a beam energy of 25 AGeV generated by UrQMD<br />
were used. The geometrical acceptance of the CBM setup was roughly taken into account by a cut in the<br />
laboratory polar angle 5 o < θlab < 30 o . Out of 700 pions produced on average per central event, 400 fall<br />
into the geometric acceptance. Moreover, on average 6 of them have transversal momenta larger than 1<br />
GeV/c, which, due to the geometrical cut on θLAB, corresponds almost perfectly to the lower momentum<br />
limit of 2 GeV/c. Choosing Rmax = 1 mm and the distance between the two tracking planes as 2 m, the<br />
rejection factor for pions of 2 GeV/c momenta is 5 · 10 −4 . Thus, one can expect that the mean number of<br />
background muon pairs, misi<strong>de</strong>ntified as true muons, will be less than 9 · 10 −6 per central event.<br />
a.u.<br />
1<br />
-1<br />
10<br />
0 0.5 1 1.5 2 2.5 3 3.5 4<br />
2<br />
[GeV/c ]<br />
Figure 17.26: Invariant mass spectra of muon pairs. Magenta: true pairs from J/ψ <strong>de</strong>cays, blue: background<br />
due muons from pion <strong>de</strong>cays. The relative normalisation of both histograms reflects the expected ratio of signal to<br />
background pairs.<br />
On the other hand, in one central event about 0.8 · 10 −6 true muon-pairs from J/ψ <strong>de</strong>cays will be emitted<br />
on the average into the geometrical acceptance. Almost all of these muons have transverse momenta<br />
larger than 1 GeV/c, and about 65% of them pass through the selection criterion as <strong>de</strong>fined above. Therefore,<br />
one expects about 4 · 10 −7 signal pairs per central event. The invariant mass spectra of background<br />
and signal muon pairs are shown in figure 17.26, where the integral of the signal distribution is 30 times<br />
smaller than that of the background. The signal peak is calculated assuming a momentum resolution of<br />
1%. In the scenario outlined above, one can expect a signal to background ratio (S/B) of about 7.<br />
17.2.4 Conclusions and next steps<br />
The study presented in the previous sections gives only a rough impression on the feasibility of the J/ψ<br />
measurement via the dimuon <strong>de</strong>cay because of the i<strong>de</strong>alizing assumptions ma<strong>de</strong>. In or<strong>de</strong>r to arrive at<br />
more realistic estimates one has to take into account:<br />
• the limited i<strong>de</strong>ntification capability of the muon <strong>de</strong>tector,<br />
• the material budget in the <strong>de</strong>tectors increasing the effect of the small-angle scattering,<br />
• the finite spatial resolution of the tracking planes,<br />
minv
17.2. J/ψ <strong>de</strong>tection via µ + µ − <strong>de</strong>cay 373<br />
• the occupancy in the tracking planes limiting the global tracking close to the target area,<br />
• the contribution of kaon <strong>de</strong>cays to the background,<br />
• the increase of the background due to secondaries.<br />
The study of these issues will be possible once tracking routines become available, which is foreseen<br />
for the first half of the year 2005. In addition, the possibility of employing a pion absorber after the<br />
Silicon Tracking System, eliminating most of the background caused by pion and kaon <strong>de</strong>cay, will be<br />
investigated.
374 Charmonium
18 Open charm<br />
One of the major experimental challenges of the CBM experiment is the measurement of the D-meson<br />
hadronic <strong>de</strong>cay in the environment of a heavy-ion collision. Due to the extremely low D multiplicity<br />
close to threshold, background reduction exploiting the D 0 displaced vertex topology is mandatory. The<br />
online event selection, required to reduce the envisaged reaction rate of 10 MHz down to the archival rate<br />
of 25 kHz, necessitates fast and efficient track reconstruction algorithms and high resolution secondary<br />
vertex <strong>de</strong>termination. Particular difficulties in recognizing the displaced vertex of the rare D meson<br />
<strong>de</strong>cays are caused by:<br />
• weak hyperon <strong>de</strong>cays producing displaced vertices between the target and first silicon tracking<br />
station;<br />
• small angle scattering in <strong>de</strong>tectors and beam pipe limiting the accuracy of track reconstruction and<br />
vertexing.<br />
In this chapter, strategies for background suppression in the open charm measurement will be discussed.<br />
We concentrate on the D 0 meson which <strong>de</strong>cays into K − and π + with a branching ratio of 3.8%. The D 0<br />
mean life time is 127 µm/c.<br />
18.1 Signal and background simulation<br />
Signal D 0 <strong>de</strong>cays were generated assuming a Gaussian distribution in rapidity (σy = 1) and a thermal<br />
spectrum in pt with T = 200 MeV. Figure 18.1 shows the pt-y and zvertex distributions of the generated<br />
open charm <strong>de</strong>cays.<br />
The hadronic background for central Au+Au collisions at 25 AGeV was generated using the UrQMD<br />
mo<strong>de</strong>l. Each signal <strong>de</strong>cay was embed<strong>de</strong>d into one background event. The combined tracks were transported<br />
through the CBM <strong>de</strong>tector using the simulation framework CBMROOT (see section 10.7). The<br />
standard geometry of the STS sub<strong>de</strong>tector (7 stations at z = 5, 10, 20 , 40, 60, 80 and 100 cm) was used.<br />
The thickness of the first two stations is 100 µm, that of the others is 200 µm.<br />
In this first step, the simulation has been performed without magnetic field. I<strong>de</strong>al track finding was<br />
assumed. The momentum resolution was assumed to be 1 %. No particle i<strong>de</strong>ntification was used.<br />
18.2 Tracking and Vertexing<br />
All tracks traversing at least four STS stations are taken into account for the analysis. The track parameters<br />
are obtained by use of the Kalman filter algorithm (section 13.2.1). The primary vertex was<br />
<strong>de</strong>termined as <strong>de</strong>scribed in section 13.3.2 from all tracks reconstructed in the STS excluding those which<br />
formed well <strong>de</strong>tached vertices like K0 S and Λ <strong>de</strong>cays. The accuracy achieved by the primary vertex<br />
reconstruction is of the or<strong>de</strong>r of several µm in beam direction.<br />
To reconstruct secondary vertices ma<strong>de</strong> of two or three tracks, the algorithm <strong>de</strong>scribed in section 13.4.1<br />
has been used. Figure 18.2 shows the achieved resolution of 57 µm in the secondary vertex z coordinate.<br />
The reconstruction precision can be further improved by applying a mass constraint in the Kalman filter<br />
(see section 13.4.2).<br />
375
376 Open charm<br />
Figure 18.1: (Left) pt-y and (right) zvertex distributions of the generated D 0 <strong>de</strong>cays into π + and K − .<br />
Figure 18.2: Difference of reconstructed and true z position of the D 0 → π + K − <strong>de</strong>cay vertex.<br />
18.3 Background reduction<br />
To suppress the abundant combinatorial background in the invariant mass spectrum, the following cut<br />
variables have been studied:<br />
• IP: impact parameter of the track in the primary vertex z plane;
18.3. Background reduction 377<br />
• P: track momentum;<br />
• PT: track transverse momentum;<br />
• ZV: z position of track pair vertex;<br />
• C2: χ 2 of pair vertex fit;<br />
• PC: collinearity of pair momentum and pair vertex.<br />
All cuts are optimized by maximization of the significance S/ √ S + B, where S is the number of accepted<br />
signal pairs and B the number of background pairs, observed in the whole invariant mass (IM) region.<br />
Figures 18.3-18.5 <strong>de</strong>monstrate the optimization procedure for the IP, PT and ZV cuts.<br />
Figure 18.3: Left panel: single track impact parameter distributions for K − and π + from the D 0 <strong>de</strong>cay (red line)<br />
and background tracks (black line). Right panel: significance S/ √ S + B as a function of the cut parameter value.<br />
The maximum is obtained at bmin = 80µm.<br />
Figure 18.4: Left panel: single track pt distributions for K − and π + from the D 0 <strong>de</strong>cay (red line) and background<br />
tracks (black line). Right panel: significance S/ √ S + B as a function of the cut parameter value. The maximum is<br />
obtained at pt,min = 0.5 GeV/c.<br />
Due to the displaced <strong>de</strong>cay vertex of the D 0 , the single track impact parameter cut and the cut on the<br />
pair vertex z coordinate are most efficient in reducing the background. In addition, the high q value of
378 Open charm<br />
Figure 18.5: Left panel: two-track vertex z distributions for K − and π + pairs from the D 0 <strong>de</strong>cay (red line) and<br />
background pairs (black line). Right panel: significance S/ √ S + B as a function of the cut parameter value. The<br />
maximum is obtained at zv,min = 250µm.<br />
cut optimized value signal efficiency [%]<br />
track IP cuts 80 0.23 GeV/c reduced the combinatorial background by another factor of<br />
two.<br />
18.4 Analysis and results<br />
The combination of the cuts <strong>de</strong>scribed in the previous section reduced the background by a factor 2 · 10 4<br />
in the signal mass region. The signal efficiency is about 11 %, the geometrical acceptance about 48 %.
18.4. Analysis and results 379<br />
Figure 18.6: Monte Carlo invariant mass spectra after applying various single particle cuts. Black: no cuts;<br />
green: P cut, blue: PT cut; orange: IP cut. The magenta line shows the spectrum obtained by assuming perfect<br />
PID. Light blue: all single particle cuts; red: all cuts including cuts on the pair.<br />
Figure 18.7: The Armenteros-Podolanski plot: transverse momentum ˜pt of the oppositely charged <strong>de</strong>cay products<br />
versus their asymmetry in longitudinal momenta p ± L . Only pairs with a distance of closest approach less than<br />
0.5 mm are consi<strong>de</strong>red.<br />
In or<strong>de</strong>r to <strong>de</strong>termine a signal to background ratio with such a large background suppression factor at least<br />
few times 10 7 MC events need to be simulated. This is a time consuming task and in or<strong>de</strong>r to estimate<br />
the shape of the background in the signal IM region the so-called "MC super event" technique [258]<br />
was used. The superevent, constructed out of 6,000 UrQMD events transported through the setup, is<br />
equivalent to 3.6 · 10 6 events. Using the shape of the invariant mass background, calculated from this<br />
superevent, and taking into account the D 0 + ¯D 0 multiplicity of about 1.5·10 −4 , the branching ratio, geo-
380 Open charm<br />
metrical acceptance and signal efficiency, we arrive at the invariant mass spectrum shown in figure 18.8,<br />
which is roughly equivalent to 30 min of data taking at 1 MHz interaction rate for central Au+Au collisions.<br />
The D 0 <strong>de</strong>tection rate is about 1,000 per hour. It should be noted that this number is strongly<br />
<strong>de</strong>pen<strong>de</strong>nt on the primary D 0 multiplicity.<br />
Figure 18.8: Invariant mass spectrum after all cuts expected for 30 min of data taking at 1 MHz interaction rate<br />
for central collisions. The red line shows a Gaussian fit to the signal on top of a linear background.<br />
18.5 Influence of the material budget<br />
One limiting factor of the open charm <strong>de</strong>tection is the material budget in the tracking stations, <strong>de</strong>grading<br />
the secondary vertex <strong>de</strong>tection capability through multiple scattering. The currently preferred solution<br />
is to use MAPS <strong>de</strong>tectors which introduce a minimal amount of material. Alternative choices, like<br />
e.g. hybrid pixel sensors would be much more massive. To study the influence of the material budget,<br />
the simulation as <strong>de</strong>scribed before has been performed for 700 µm thick tracking stations. The analysis<br />
was carried out in complete analogy to the standard setup.<br />
Figure 18.9 compares the z vertex and impact parameter distributions for the simulation with thick tracking<br />
stations to the results obtained with the standard setup. The increased influence of multiple scattering<br />
is clearly visible. In or<strong>de</strong>r to obtain a comparable background suppression, the cuts have to be chosen<br />
more restrictive, resulting in a <strong>de</strong>crease of the signal efficiency by a factor of about four.<br />
18.6 Next steps<br />
The next steps are:<br />
• usage of tracking in the inhomogeneous magnetic field in the STS for the D 0 vertex finding, including<br />
realistic digitized <strong>de</strong>tector response;<br />
• analysis of the D + <strong>de</strong>caying to K − + π + + π + (and charge conjugate);
18.6. Next steps 381<br />
Figure 18.9: Reconstructed z-vertex of π + K − pairs (left) and single track impact parameters (right) calculated<br />
for background UrQMD events. The green histograms correspond to 700 µm thick tracking stations.<br />
• optimization of the STS geometry with respect to D 0 sensitivity;<br />
• study the beam energy <strong>de</strong>pen<strong>de</strong>nce of the D 0 measurement feasibility.
382 Open charm
19 Event-by-event fluctuations<br />
In the vicinity of the critical point, fluctuations of chemical and kinetic observables from event to event<br />
are expected. We have investigated the ability of the CBM <strong>de</strong>tector to <strong>de</strong>tect fluctuations in the eventwise<br />
K/π and p/π ratio by usage of the TOF system. This requires to measure the number of pions, kaons<br />
and protons in single events. Due to the limited number of tracks in the <strong>de</strong>tector acceptance (for central<br />
Au+Au at 25 AGeV around 360 pions, 25 kaons and 80 protons are accepted), fits to the squared mass<br />
distributions as <strong>de</strong>scribed in chapter 14 will not be possible.<br />
We therefore use the probability <strong>de</strong>nsity function <strong>de</strong>fined in equation 14.3 and introduce for N measured<br />
hadrons in the event the functional<br />
N<br />
L({θα}) := <strong>PDF</strong>(pi,m 2 N <br />
i ;{θα}) = θαr α (pi) f α p (m 2 i ) (19.1)<br />
i=1<br />
where the in<strong>de</strong>x α <strong>de</strong>notes the particle species (pion, kaon, proton). The momentum spectra r α (p) and the<br />
squared mass distributions f α (p,m 2 α) are obtained from the inclusive analysis as <strong>de</strong>scribed in chapter 14.<br />
The normalisations {θα} are free parameters. The functional is evaluated from the measured p and m 2<br />
of all tracks in the event.<br />
Maximising L with respect to {θα} gives the best estimate of the relative particle yields {θ ∗ α}, from<br />
which the eventwise particle ratios can be calculated. The maximisation procedure has to be performed<br />
for each event. Technically, it is more convenient to minimise the functional<br />
events<br />
4<br />
10<br />
3<br />
10<br />
2<br />
10<br />
10<br />
1<br />
l := −ln(L) = −<br />
data<br />
mixed events<br />
i=1<br />
N<br />
ln <strong>PDF</strong>(pi,m 2 i ;{θα}) <br />
i=1<br />
0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2<br />
/< π><br />
events<br />
4<br />
10<br />
3<br />
10<br />
2<br />
10<br />
10<br />
1<br />
α<br />
data<br />
mixed events<br />
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2<br />
+ /< π ><br />
(19.2)<br />
Figure 19.1: The event-by-event K/π (left) and p/π (right) ratios. The points show the distribution for real<br />
events, the histogram that for mixed events.<br />
We <strong>de</strong>fine as event-by-event fluctuation the RMS of the distribution of the fluctuating variable normalised<br />
to the mean value. It will have contributions from finite number statistics, experimental resolution and<br />
the "true" (dynamical) fluctuations:<br />
σ 2 = σ 2 stat + σ 2 exp + σ 2 dyn = σ 2 background + σ 2 signal<br />
(19.3)<br />
The background contribution (finite number statistics and <strong>de</strong>tector resolution) can be assessed by event<br />
mixing. For this purpose, a pool of tracks from real events is created. For each real event, a mixed event<br />
383
384 Event-by-event fluctuations<br />
UrQMD <strong>de</strong>tector acceptance + PID<br />
ratio data [%] mixed events [%] data [%] mixed events [%]<br />
/< π > 14.3 ± 0.05 14.1 ± 0.04 18.7 ± 0.06 18.6 ± 0.06<br />
/< π > 7.9 ± 0.02 9.7 ± 0.03 11.1 ± 0.04 12.6 ± 0.04<br />
Table 19.1: Relative widths of the event-by-event particles ratio distributions for data and mixed events<br />
with the same track multiplicity is created by randomly selecting tracks out of the pool. Each track of<br />
the pool is used only once; all tracks insi<strong>de</strong> one mixed event originate from different real events. The<br />
analysis is then performed for real and for mixed events. From the widths of the event-by-event particle<br />
ratio distributions, the dynamical fluctuations are calculated by<br />
<br />
σdyn = +<br />
σdyn = −<br />
σ 2 data − σ2 mixed (σ 2 data > σ2 mixed )<br />
<br />
σ2 mixed − σ2 data (σ 2 data < σ2mixed ) .<br />
ratio UrQMD <strong>de</strong>tector acceptance + PID<br />
/< π > 2.4 ± 0.4 2.3 ± 0.7<br />
/< π > -5.6 ± 0.06 -5.9 ± 0.1<br />
Table 19.2: Dynamical event-by-event fluctuations of the particle ratios<br />
(19.4)<br />
This analysis has been performed on 50,000 central Au+Au collision at 25 AGeV beam momentum,<br />
simulated with UrQMD and transported through the CBM setup. The TOF resolution was assumed to be<br />
80 ps. For the distributions f α (p,m 2 ) a Gaussian shape was assumed as shown in chapter 14. Figure 19.1<br />
shows the distributions of the K/π and p/π ratios for both real and mixed events. The values of the<br />
relative width are listed in table 19.1. The resulting dynamical fluctuations can be found in table 19.2. It<br />
can be seen that the fluctuations originally present in the UrQMD events are satisfyingly reproduced by<br />
the method.<br />
><br />
π<br />
) /<<br />
dyn<br />
σ<br />
(<br />
δ<br />
1<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
2 4 6 8 10 12 14<br />
N , 1e4 ev<br />
><br />
+<br />
π<br />
) /<<br />
dyn<br />
σ<br />
(<br />
δ<br />
0.14<br />
0.12<br />
0.1<br />
0.08<br />
0.06<br />
2 4 6 8 10 12 14<br />
N , 1e4 ev<br />
Figure 19.2: Statistical error of the dynamical event-by-event fluctuations of the K/π (left) and the p/π ratio<br />
(right) as functions of the number of analysed events. The solid line shows the expected behaviour ∼ 1/ √ N.<br />
The accuracy of the measurement can be improved by increasing the event statistics. The statistical<br />
error on σdyn is shown in figure 19.2 as function of the number of events used for the analysis. It is<br />
approximately proportional to 1/ √ Nev. For 2·10 6 events, the error of the K/π fluctuations is of the or<strong>de</strong>r<br />
of 0.1%.
Part IV<br />
Infrastructure and Safety<br />
385
20 Cave<br />
The CBM cave hosts both the HADES <strong>de</strong>tector and the CBM <strong>de</strong>tector. The experimental hall has an<br />
area of 38×22 m 2 and requires a height of 20 m for the CBM <strong>de</strong>tector and its handling with a crane.<br />
The cave can be entered via a variable labyrinth having a maximum opening of 6×6 m 2 which permits<br />
to transport large and heavy parts into the cave. Even larger parts are transported into the cave via an<br />
opening in the ceiling which has a size of 10×10 m 2 . The cave is equipped with a crane which can lift<br />
15 tons. The <strong>de</strong>tectors require a beam line with a height of 2.7 m. A si<strong>de</strong> view and a top view of the cave<br />
and the <strong>de</strong>tectors is presented in the figures 20.1 and 20.2. The experimental hall requires air condition<br />
at a temperature of 20 - 25 o C.<br />
The entrance to the experimental hall (labyrinth) is integral part of a building which provi<strong>de</strong>s room for<br />
• <strong>de</strong>tector and cave supplies,<br />
• mounting the <strong>de</strong>tectors,<br />
• computer center,<br />
• operation of the experiment (control room)<br />
• offices.<br />
The CBM annex building covers an area of 700 m 2 distributed over 3 storeys. As the entrance to the cave<br />
is below ground level, the building contains a shaft with a size of 6×6 m 2 in all 3 storeys. The shaft is<br />
equipped with a 15 tons crane.<br />
387
388 Cave<br />
Figure 20.1: Si<strong>de</strong> view of the CBM experimental hall equipped with the HADES <strong>de</strong>tector and with the CBM<br />
<strong>de</strong>tector.<br />
Figure 20.2: Top view of the CBM experimental hall.
21 Radiation protection<br />
According to the radiation protection regulations in Germany the dose rate outsi<strong>de</strong> the cave must not<br />
exceed a value of 5 · 10 −7 Sv/h. Typically, the interaction probability of the primary beam with the<br />
target is about 1 %. Therefore, nearly 100 % of the beam has to be stopped in a dump located behind<br />
the experimental setup. The concrete shielding of the cave and the geometry and the dimensions of the<br />
Iron beam dump haven been studied with the Monte-Carlo-co<strong>de</strong> FLUKA [260, 261]. As FLUKA is not<br />
capable of transporting heavy-ions, the primary beam was assumed to be composed of protons. The<br />
calculated dose values were finally scaled with the mass number of gold in or<strong>de</strong>r to have a conservative<br />
estimate for a gold beam. The expected dose rates in the CBM experimental hall for 10 9 Au ions per<br />
second at an energy of 30 AGeV are illustrated in figure 21.1. The shielding provi<strong>de</strong>d by the cave walls<br />
is sufficient to reduce the dose rate outsi<strong>de</strong> the cave to a value of 1 · 10 −7 Sv/h (blue color).<br />
Länge / m<br />
40<br />
30<br />
20<br />
10<br />
0<br />
Schnitt an Höhe=2m<br />
Strahleintritt<br />
Target<br />
Fe, 3mm<br />
Labyrinth<br />
-20 -10 0<br />
Breite / m<br />
10 20<br />
Dosisleistung / (Sv/h)<br />
5E-07<br />
100<br />
10<br />
1<br />
0.1<br />
0.01<br />
0.001<br />
1E-04<br />
1E-05<br />
1E-06<br />
1E-07<br />
1E-08<br />
1E-09<br />
1E-10<br />
1E-11<br />
1E-12<br />
Figure 21.1: Dose rates in the CBM experimental hall at a height of 2 m for a beam intensity of 10 9 Au ions per<br />
second at an energy of 30 AGeV.<br />
The iron beam dump is partly integrated in the back wall of the cave. The dose rate distribution at<br />
the beam dump was calculated separately in or<strong>de</strong>r to make use of a cylindrical symmetry. The dominant<br />
component of the dose at forward direction is due to muons. At the other directions the dose is dominated<br />
by the neutron component. According to the calculation, an iron beam dump of about 18 m length and<br />
diameters between 2 m and 7 m is required to absorb the radiation produced by a beam of 10 9 Au ions<br />
389
390 Radiation protection<br />
per second at an energy of 30 AGeV. The dose rate distribution at the dump is <strong>de</strong>picted in figure 21.2.<br />
Radius / m<br />
8<br />
6<br />
4<br />
2<br />
1<br />
concrete<br />
entry channel<br />
0.1<br />
0.01<br />
0.001<br />
0.0001<br />
1e-05<br />
iron<br />
1e-06<br />
1e-07<br />
0<br />
-9 -7 -5 -3 -1 1 3 5<br />
Länge / m<br />
7 9 11 13 15<br />
1e-08<br />
1e-09<br />
1e-10<br />
1e-11<br />
1e-12<br />
1e-13<br />
1e-14<br />
1e-15<br />
Dosisleistung / (Sv/h)<br />
Figure 21.2: Dose rate distribution at the CBM beam dump calculated with FLUKA for a beam intensity of 10 9<br />
Au ions per second at an energy of 30 AGeV.
Part V<br />
Organization and Responsibilities,<br />
Planning<br />
391
22 Planning and organization<br />
22.1 Cost estimates<br />
The overall cost estimate for the CBM experiment is summarized in table 22.1. The cost estimate of the<br />
CBM Silicon pixel and strip <strong>de</strong>tector is based on the construction costs of similar <strong>de</strong>tector components<br />
of ALICE. The cost range indicated for some of the items reflects different options where the <strong>de</strong>cision<br />
is still open, for example the technology of the RICH photon <strong>de</strong>tector, and the gaseous chambers of the<br />
Transition Radiation Detector (straw tubes, MWPC or GEM). The cost of the RPC has been estimated<br />
from the costs of the RPCs built for FOPI and ALICE.<br />
In addition to the uncertainties of the technology, the active area of the <strong>de</strong>tectors and their number of<br />
channels are still subject of ongoing physics performance simulations. For example, hadron i<strong>de</strong>ntification<br />
capability of CBM <strong>de</strong>pends on the time-of-light distance, which influences (quadratically) the size of the<br />
second and third TRD, of the RPC and of the ECAL. This affects also the number of channels, as the cell<br />
size in the outer regions of the third TRD and of the RPC are limited by position resolution rather than<br />
by occupancy. The cost estimates for the TRD, the RPC and the ECAL listed in table 22.1 are based on<br />
a TOF distance of 10 m.<br />
Detector system Cost (M)<br />
Silicon Pixel Detector 1 - 1.5<br />
Silicon Strip Detector 7<br />
Ring Imaging Cherenkov Detector 6 - 10<br />
Transition Radiation Detector 8 - 10<br />
TOF stop <strong>de</strong>tector (RPC) 5 - 7.4<br />
Electromagnetic Calorimeter + preshower 12.2<br />
Superconducting magnet 3<br />
Data acquisition and trigger 4 - 6<br />
Computing 3 - 6<br />
Infrastructure and installation 5<br />
Total <strong>de</strong>tector cost 54.2 - 68.1<br />
22.2 Responsibilities<br />
Table 22.1: Cost estimate for the CBM experiment<br />
A preliminary sharing of the responsibilities for the different tasks and subsystems of CBM are listed<br />
in table 22.2. This sharing is based on the interest expressed by the institutes taking into account their<br />
expertise and ongoing R&D activities. The assignment of the responsibilities is neither complete nor<br />
final. In particular, we search for new collaborating institutes to participate in the activities and to take<br />
responsibilities.<br />
393
394 Planning and organization<br />
Work package Institution<br />
Simulation and analysis framework <strong>GSI</strong> Darmstadt<br />
Track, vertex and momentum recon- KIP Univ. Hei<strong>de</strong>lberg, Univ. Mannheim, JINR-LHE<br />
struction<br />
Dubna, JINR-LIT Dubna<br />
Simulations hadron i<strong>de</strong>ntification via Hei<strong>de</strong>lberg Univ., Kiev Univ., NIPNE Bucharest,<br />
TOF, critical fluctuations<br />
INR Moscow, RBI Zagreb<br />
Feasibility study low-mass vector meson<br />
i<strong>de</strong>ntification via dilepton pairs<br />
Univ. Krakow, JINR-LHE Dubna<br />
Feasibility study charmonium i<strong>de</strong>ntifi- INR Moscow. <strong>GSI</strong>, PNPI St. Petersburg, <strong>GSI</strong>, RBI<br />
cation via dielectron and dimuon pairs Zagreb<br />
Feasibility study D-Meson i<strong>de</strong>ntifica- <strong>GSI</strong> Darmstadt, Czech Acad. Science Rez, Techn.<br />
tion<br />
Univ. Prague, IReS Strasbourg<br />
Feasibility study hyperons Polytech. Univ. St. Petersburg, JINR-LHE Dubna<br />
Delta electrons <strong>GSI</strong> Darmstadt<br />
Silicon Pixel Detector IReS Strasbourg, Frankfurt Univ., <strong>GSI</strong> Darmstadt,<br />
RBI Zagreb, Krakow Univ.<br />
Silicon Strip Detector Univ. Obninsk, SINP Moscow State Univ., CKBM<br />
St. Petersburg, KRI St. Petersburg RPC<br />
TOF <strong>de</strong>tector system with read-out LIP Coimbra, Univ. Santiago <strong>de</strong> Compostela, Univ.<br />
electronics<br />
Hei<strong>de</strong>lberg, <strong>GSI</strong> Darmstadt, NIPNE Bucharest, INR<br />
Moscow, FZ Rossendorf, IHEP Protvino, ITEP<br />
Moscow, Korea Univ.<br />
Krakow, Univ. Marburg<br />
Seoul, RBI Zagreb, Univ.<br />
Transition Radiation Detector (TRD JINR-LHE Dubna, <strong>GSI</strong> Darmstadt, Univ. Münster,<br />
MWPC based)<br />
PNPI St. Petersburg, NIPNE Bucharest<br />
Transition Radiation Detector (TRD JINR-LPP Dubna, FZR Rossendorf, Tech. Univ.<br />
straw based)<br />
Warsaw<br />
Ring Imaging Cherenkov Detector IHEP Protvino, <strong>GSI</strong> Darmstadt, Pusan Nat. Univ.,<br />
(RICH)<br />
PNPI St. Petersburg<br />
Electromagnetic Calorimeter (ECAL) ITEP Moscow, IHEP Protvino<br />
Forward Calorimeter INR Moscow<br />
Diamond Microstrip Start Detector <strong>GSI</strong>, Univ. Mannheim<br />
with read-out electronics<br />
Front-End Electronics, Trigger and KIP Univ. Hei<strong>de</strong>lberg, Univ. Mannheim, JINR LIT<br />
Data Acquisition<br />
Dubna, <strong>GSI</strong> Darmstadt, Univ. Bergen, KFKI Budapest,<br />
Silesia Univ. Katowice, PNPI St. Petersburg,<br />
Univ. Warsaw<br />
Design of a superconducting dipole<br />
magnet<br />
JINR-LHE Dubna, <strong>GSI</strong> Darmstadt<br />
Calculation of radiation doses Kiev Univ.<br />
Modification of HADES for 8 AGeV Czech Acad. Science Rez<br />
Table 22.2: Responsibilities
22.3. Organization 395<br />
22.3 Organization<br />
According to its constitution from October 2004 the organization of CBM consists of the Collaboration<br />
Board (CB), the Management Board (<strong>MB</strong>), the Technical Board (TB) and the Physics Board (PB).<br />
The CB is the policy and <strong>de</strong>cision making body of the CBM Collaboration. The CB is composed of<br />
one representative from each Member Institution. Each Institution has one vote in the CB. Members<br />
of the Management Board are ex-officio Members of the CB. The Chairperson of the CB is elected ad<br />
personam by the CB.<br />
The <strong>MB</strong> supervises the progress of the experiment, along the lines <strong>de</strong>fined by the CB and prepares<br />
<strong>de</strong>cisions for and makes recommendations to the CB. The <strong>MB</strong> review and act on recommendation of the<br />
Spokesperson and/or of Darmstadt Future Facility Management regarding all issues consi<strong>de</strong>red of major<br />
importance for the Collaboration. The <strong>MB</strong> may appoint review committees and task forces to provi<strong>de</strong><br />
advice on technical, scientific and technological <strong>de</strong>cisions, as nee<strong>de</strong>d.<br />
The TB assesses all technical aspects of the CBM <strong>de</strong>tector as <strong>de</strong>ci<strong>de</strong>d by the CB. The <strong>de</strong>sign, coordination<br />
and technical execution of the experiment are discussed and agreed upon in the TB. Technical <strong>de</strong>cisions,<br />
having important implications for the CBM <strong>de</strong>tector must be presented to the CB for endorsement. The<br />
TB is composed of the Project Lea<strong>de</strong>rs (including Sub-project Lea<strong>de</strong>rs). Ex-officio members are the<br />
Spokesperson and Deputy and the other coordinators. The TB is chaired by the Technical Coordinator.<br />
The Technical Coordinator monitors and coordinates the activities of all the projects, and is responsible<br />
for the overall technical performance, planning and scheduling of the CBM <strong>de</strong>tectors.<br />
The PB coordinates and assesses activities concerning physics topics of interest, including simulations<br />
and optimization of the physics performance of CBM. The PB is composed of the conveners and Coconveners<br />
of the physics performance working groups, who are nominated by the Spokesperson and<br />
confirmed by the <strong>MB</strong>. The PB is chaired by the Physics Coordinator.<br />
CBM has one Spokesperson. The Spokesperson is responsible to the Collaboration Board for the execution<br />
of the CBM project. The Spokesperson represents the CBM Collaboration to the Darmstadt Future<br />
Facility Committee, to its Management and to the outsi<strong>de</strong> world. The Spokesperson may appoint review<br />
committees and task forces to provi<strong>de</strong> advice on technical, scientific and technological <strong>de</strong>cisions,<br />
as nee<strong>de</strong>d.<br />
The Spokesperson, in consultation with the Management Board and the Darmstadt Future Facility Management,<br />
nominates for confirmation by the CB a number of Coordinators. The Coordinators report to<br />
the Spokesperson.<br />
The following persons have been elected up to now:<br />
Chairman of the Collaboration Board: M. Petrovici<br />
Spokesperson: P. Senger<br />
Technical Coordinator: W.F.J. Müller<br />
Physics Coordinator: V. Friese<br />
The structure of the Technical Board is shown in the upper part of figure 22.1. During the time period<br />
until the submission of the Technical Proposal the Physics Board is composed of the Physics Performance<br />
Working Groups as illustrated in the lower part of figure 22.1.
396 Planning and organization<br />
Technical Board Technical coordinator<br />
W.F.J. Müller<br />
Silicon Pixel<br />
RPC<br />
FEE/DAQ<br />
Silicon Strip<br />
ECAL<br />
HLT/offline<br />
Physics performance working groups<br />
Framework<br />
J/ψ → e+e-<br />
J/ψ → µ+µ-<br />
Tracking<br />
ρ, ω, φ → e+e-<br />
event by event<br />
Figure 22.1:<br />
RICH<br />
Start<br />
ECS<br />
Physics coordinator<br />
V. Friese<br />
hadron ID<br />
D meson<br />
TRD<br />
Magnet<br />
Cave<br />
Infrastructure<br />
Electron ID<br />
RICH<br />
Hyperons
22.4. Schedule 397<br />
22.4 Schedule<br />
This Technical Status Report still inclu<strong>de</strong>s alternative possible technical solutions for the various requirements<br />
of the planned experiments. It will take two more years of intensive R&D in or<strong>de</strong>r to <strong>de</strong>ci<strong>de</strong> upon<br />
the layout of the experiment, the technology of the <strong>de</strong>tectors, and on the trigger, DAQ, and FEE architecture.<br />
We plan to submit a Technical Proposal end of 2006. The <strong>de</strong>tailed <strong>de</strong>sign of the CBM subsystems<br />
including prototyping leading to the Technical Design Reports will take another 3-5 years. For the construction<br />
of the components we foresee 2-3 years. Installation of the first <strong>de</strong>tector components in the<br />
CBM cave will start in 2012. Commissioning of the experiment is planned for 2014 when the operation<br />
of SIS300 starts according to the present schedule. A global schedule for for the <strong>de</strong>sign, prototyping,<br />
construction, and installation of all CBM subsystems is presented in figure 22.4.
398 Planning and organization<br />
Nr. Vorgangsname<br />
1 CBM<br />
2 Definition of Buildings<br />
3 cave<br />
4 annex building<br />
5 simulation and analysis software<br />
6 simulations/feasibility studies<br />
7 <strong>de</strong>sign framework<br />
8 maintenance framework<br />
9 tracking in magnetic field<br />
10 vertex reconstruction<br />
11 momentum reconstruction<br />
12 global tracking<br />
13 hadron i<strong>de</strong>ntification<br />
14 electron i<strong>de</strong>ntification<br />
15 digitisers<br />
16 feasibility studies<br />
17 D-meson<br />
18 J/psi<br />
19 rho<br />
20 critical fluctuations<br />
21 hyperons<br />
22 SiliconTracking System (STS)<br />
23 Pixel <strong>de</strong>tectors<br />
24 Simulations, layout<br />
25 Sensor<br />
26 R&D, <strong>de</strong>sign<br />
27 prototyping<br />
28 production<br />
29 Fast read-out<br />
30 <strong>de</strong>sign<br />
31 General<br />
32 Det. Control, supplies<br />
33 mechanics, cooling<br />
34 assembly and test<br />
35 Strip <strong>de</strong>tectors<br />
36 Simulations, layout<br />
37 Sensor<br />
38 R&D, <strong>de</strong>sign<br />
39 prototyping<br />
40 production<br />
41 FEE chip<br />
42 R&D, <strong>de</strong>sign<br />
43 prototyping<br />
44 production<br />
45 General<br />
46 Mechanics, cooling<br />
47 Det control, supplies<br />
48 assembly and test<br />
Version vom Mi 22.12.04 WJacoby_D<br />
Struktur <strong>de</strong>s Zukunftsprojekts Mi 22.12.04<br />
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 201<br />
H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1<br />
Figure 22.2:
22.4. Schedule 399<br />
Nr. Vorgangsname<br />
1 CBM<br />
2 RICH<br />
3 simulations and concept studies<br />
4 radiator<br />
5 simulation, vessel <strong>de</strong>sign<br />
6 prototyping and test<br />
7 construction<br />
8 mirror<br />
9 mirror <strong>de</strong>sign<br />
10 prototyping<br />
11 production<br />
12 photo<strong>de</strong>tector<br />
13 UV <strong>de</strong>tector R&D<br />
14 UV <strong>de</strong>tector prototype<br />
15 UV <strong>de</strong>tector production<br />
16 FEE<br />
17 <strong>de</strong>sign and prototyping<br />
18 construction<br />
19 general<br />
20 mainframe <strong>de</strong>sign and construction<br />
21 gas system <strong>de</strong>sign and construction<br />
22 HV supply <strong>de</strong>sign and construction<br />
23 assembly, installation, test<br />
24 Transition Radiation Detector<br />
25 simulations and concept studies<br />
26 radiator<br />
27 R&D<br />
28 prototyping<br />
29 production<br />
30 fast gas chambers<br />
31 R&D<br />
32 prototyping<br />
33 production<br />
34 gas system<br />
35 R&D and prototype<br />
36 production and test<br />
37 Electronics<br />
38 FEE ASICs<br />
39 <strong>de</strong>sign<br />
40 prototyping<br />
41 production and test<br />
42 readout board<br />
43 <strong>de</strong>sign<br />
44 prototyping<br />
45 production and test<br />
46 Mainframe<br />
47 gas system, <strong>de</strong>sign and construction<br />
48 installation and test<br />
Version vom Mi 22.12.04 WJacoby_D<br />
Struktur <strong>de</strong>s Zukunftsprojekts Mi 22.12.04<br />
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 201<br />
H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1<br />
Figure 22.3:
400 Planning and organization<br />
Nr. Vorgangsname<br />
1 CBM<br />
2 Resistive Plate Chamber Array<br />
3 concept studies and layout<br />
4 <strong>de</strong>tector<br />
5 R&D module<br />
6 array prototyping<br />
7 production and test<br />
8 Electronics<br />
9 FEE ASICs<br />
10 <strong>de</strong>sign<br />
11 prototyping<br />
12 production and test<br />
13 readout board<br />
14 <strong>de</strong>sign<br />
15 prototyping<br />
16 production and test<br />
17 Mainframe<br />
18 gas system, <strong>de</strong>sign and construction<br />
19 assembly, installation, test<br />
20 Electromagnetic Calorimeter<br />
21 concept studies and layout<br />
22 <strong>de</strong>tector modules<br />
23 prototyping<br />
24 production and test<br />
25 readout electronics<br />
26 <strong>de</strong>sign<br />
27 prototyping<br />
28 production and test<br />
29 assembly, installation<br />
30 Data Acquisition and trigger<br />
31 <strong>de</strong>sign<br />
32 prototyping<br />
33 production<br />
34 installation<br />
35 test<br />
36 Experiment Control System<br />
37 <strong>de</strong>sign<br />
38 prototyping<br />
39 implementation<br />
40<br />
41 Infrastructure<br />
42 cave supplies<br />
43 <strong>de</strong>sign<br />
44 construction<br />
45 installation<br />
46 magnet supply<br />
47 <strong>de</strong>sign<br />
48 construction<br />
49 Installation<br />
50 <strong>de</strong>tector supply<br />
51 <strong>de</strong>sign<br />
52 construction<br />
53 Installation<br />
54 beamline<br />
55 <strong>de</strong>sign<br />
56 construction<br />
57 Installation<br />
58 vacuum system<br />
59 <strong>de</strong>sign<br />
60 construction<br />
61 Installation<br />
62 beamdump<br />
63 <strong>de</strong>sign<br />
64 construction<br />
65 Installation<br />
66 Technical Status Report<br />
67 submission<br />
68 Technical Proposal<br />
69 Submission<br />
Version vom Fr 07.01.05 WJacoby_D<br />
Struktur <strong>de</strong>s Zukunftsprojekts Fr 07.01.05<br />
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 201<br />
H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1<br />
03.01.<br />
Figure 22.4:<br />
01.01.
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