Silicon Detector Readout - HEPHY

CMS TrackerSilicon Strip SensorFront-EndElectronicsM.Friedl: Silicon Detector Readout 14 June 20124

Various CMS Tracker ModulesElectronicsSensorsM.Friedl: Silicon Detector Readout 14 June 20126

Silicon Strip DetectorsWire bondCMS Test Sensor with various geometries (1998) Belle Sensor with 45° strips (2004)• Typically 300µm thick, strip pitch 50...200µm• Reverse bias voltage for full depletion 50...500V• Connection by wire bondsM.Friedl: Silicon Detector Readout 14 June 20127

Silicon Pixel DetectorsCMS Pixel Readout Scheme CMS Pixel Sensor ATLAS Pixel Sensor• Pixels can be square (CMS) or oblong (ATLAS)• Structure size similar to strip detectors, but N 2 channels• Connection by bump bondsM.Friedl: Silicon Detector Readout 14 June 20128

Principle of Operationcharged particle trackFront-end amplifier+E+-+-+---+++p -implantn-type bulkn + -implant• p-n junction is operated at reverse bias to drain free carriers• Traversing charged particle creates electron-hole pairs• Carriers drift towards electrodes in the electric field• Moving carriers induce current in the circuit → current sourceM.Friedl: Silicon Detector Readout 14 June 20129

Equivalent Circuit of the DetectorIC detCurrent source withcapacitor in parallel• Applies to many types of detectors, not only silicon• Example: wire chamberCoaxial capacitor configurationMoving charges induce current• Example: photomultiplier tubeSmall platesCharge (current) is amplified in each stageM.Friedl: Silicon Detector Readout 14 June 201210

Comparison: Voltage vs. Current SourceProperty Voltage Source Current SourceIDEALVoltage constant + anythingCurrent anything V constantIdle (no power) Open (I=0) Shorted (V=0)IProperty Voltage Source Current SourceREAL(Linear) equivalentcircuit+VR VResistor causes Internal voltage drop Internal current dropIR IConversionNorton-Thevenin equivalent: R V = R I ; V = I R V/IExamplesBatteryWall plug (AC)DetectorNIM module outputsM.Friedl: Silicon Detector Readout 14 June 201211

Moving ChargesM.Friedl: Silicon Detector Readout 14 June 201212

Ramo’s Theorem (1939)• Moving charges between inside electric field (e.g. parallelplates) induces current in electrodesi = E q v• Current is proportional to electric field E, (moving) charge qand velocity v of the charge• It doesn’t matter if the charges eventually reach theelectrodes or not, only motion counts• Fully valid for parallel plate capacitor configuration (largearea diode)• A bit more complicated for strip detectors → more laterM.Friedl: Silicon Detector Readout 14 June 201213

A Bit of Theory+• Space chargedensity is given bydoping• Electric field iscalculated byPoisson’s equation• Potential is found byintegration of fieldn +0ρeNEn-type bulkp +DxxE maxϕ• Shown here: fulldepletion = spacecharge just extendsover full detector-V deplxxM.Friedl: Silicon Detector Readout 14 June 201214

Bias Voltage and Depletion• In reality, the electric field is imposed by applied bias voltage• What happens if V bias < V depl ?Electric field does not cover full bulkOnly part of detector contributes tocharge collection → lower efficiencyDo not operate a detector like that• What happens if V bias > V depl ?Linear offset is added to electric fieldField tends to become more flatFaster charge collection (Ramo)Limited by breakdown voltageEExxM.Friedl: Silicon Detector Readout 14 June 201215

Induced Currents (1)i [nA]600500400300200100Detector Currents -- E lectrons and Holes ContributionsD=300µm, r=4kΩcm, V=79/158VV=V depl 8007006005004003002001000i [nA]1000900V=2 V deplisum0 5 10 15 20time [ns]ieih00 5 10 15 20 25 30 35 40 45 50time [ns]M.Friedl: Silicon Detector Readout 14 June 201216

Induced Currents (2)• Typical silicon detector (D=300µm)• Very low (

Induced Currents (3)• Both electrons and holes contribute to overall current, butcannot be distinguished in reality• Integral over time (area under curve) is the collected chargeIf all charges reach electrodes, this is identical to the number ofcreated pairs∫ i dt ≈ 3.6 fC ≡ 22500 e for a 300µm thick detectorFor comparison: ~10 10 e every 20ns in a 25W bulb (230VAC)• In a simple parallel plate geometry, contributions ofelectrons and holes are equalHowever, it’s not that simple in a strip detector…M.Friedl: Silicon Detector Readout 14 June 201218

Induced Current Measurement• Quite difficult due to noise constraintsDetector Currents -- E lectrons and Holes ContributionsD=300µm, r=4kΩcm, V=79/158Visum600500400V=V deplSingle shoti [nA]300200100Averaged00 5 10 15 20 25 30 35 40 45 50time [ns]• Every amplifier has a limited bandwidth and thus rise time• Nonetheless, exponential decay is clearly visibleM.Friedl: Silicon Detector Readout 14 June 201219

Strip Detector Case• Ramo theorem still holds, but with some modifications• Why?Charge movement is determined by electric field (which isapproximately the same as for the parallel plate case)Induced currents are calculated by (virtual) weighting fieldNow the moving charges influence a current onto several stripsdepending on the geometry and distance• How to calculate weighting field?Electrode under consideration is held at unity potential, allother electrodes at zeroM.Friedl: Silicon Detector Readout 14 June 201220

Strip Detector Simulation (1)• 300 µm thick, 50 µm pitch, n-bulk, p-strips, V bias =1.6 x V deplDrift Potential & FieldLinear color scale!M.Friedl: Silicon Detector Readout 14 June 201221

Strip Detector Simulation (2)• 300 µm thick, 50 µm pitch, n-bulk, p-strips, V bias =1.6 x V deplWeighting Potential & FieldNonlinear color scale!M.Friedl: Silicon Detector Readout 14 June 201222

Strip Detector Simulation (3)• 300 µm thick, 50 µm pitch, n-bulk, p-strips, V bias =1.6 x V deplInduced currentssumh +e -Integratedcurrents:Q e- = 3338 eQ h+ = 20019 eQ sum = 23356 eMeasured chargeis dominated byholes:86% @ p=50µm82% @ p=75µm77% @ p=120µm…53% @ p=500µmM.Friedl: Silicon Detector Readout 14 June 201223

Strip Detector Case• Due to the very nonlinear weighting field, the charges whichdrift towards the electrode largely dominate the overallinduced current• Doesn’t seem very relevant, but it actually has practicalimplications → Lorentz shiftM.Friedl: Silicon Detector Readout 14 June 201224

Lorentz Shift• In a magnetic field, charge movement is deflected due toLorentz force which depends on the carrier mobility• Resulting in an angle (approximately ~12° for e, ~4° for h at1.8T) and spreading of signals over several stripsParticlefrom IPh +e -B||zn-sideshort strips along r-phi+HVp-sidelong strips along z-HVM.Friedl: Silicon Detector Readout 14 June 201225

Lorentz Shift Compensatione - h +n-sideshort strips along r-phi+HVe -Particlefrom IPp-sidelong strips along z-HVB||zh +Particlefrom IPBzBzM.Friedl: Silicon Detector Readout 14 June 201226

Silicon Detector Summary• Various Geometries:(Diode), strips, pixels• Detector is a current source || capacitancep-n junction operated under reverse bias voltage > V depl• Charged particle creates electron-hole pairsCarrier motion in the electric field induces current on electrodesSignal is typically

• Silicon Detector• Front-End Amplifier• Signal Transmission• Back-End Signal Processing• SummaryM.Friedl: Silicon Detector Readout 14 June 201228

Front-End Amplifier PrincipleI inV outPreamplifier(Integrator)Shaper(Filter)• Located close to the sensor• First stage: IntegratorDetector current → charge• Second stage: FilterLimit bandwidth to reduce noiseM.Friedl: Silicon Detector Readout 14 June 201229

Shaper Bandwidth Reduction• Example: APV25 front-end amplifier (CMS)AVG Noise APV 13025Amplitude [a.u.]Nosie [ADC]2015105Frequency01.E+02 1.E+03 1.E+04 1.E+05 1.E+06 1.E+07 1.E+08Frequency [Hz]SimulationMeasurementM.Friedl: Silicon Detector Readout 14 June 201230

Example: VA2 Chip Input Stage• VA2 is a general-purpose front-end amplifier chip with 128inputs and multiplexed output• “Slow” shaper in the µs range ≡ low noiseM.Friedl: Silicon Detector Readout 14 June 201231

Shaper OutputTp~2µsAmplitudeVA2General purposeTp~50nsTimeAmplitudeAPV25CMSParticle hitTime• T p …shaping time (or peaking time)• Faster shaping can be a necessity of the experiment todistinguish subsequent events, but also implies larger noiseM.Friedl: Silicon Detector Readout 14 June 201232

“Low-Noise” Amplifiers• Nearly all front-end chips are called “low-noise”• General feature of the integrator+shaper combination• Noise is typically given by ENC (equivalent noise charge)referred to the input• ENC = a + b ⋅ C det (a,b...const, C det ...detector capacitance)• Examples:T p [ns]ENC [e]VA2 (~1993) 2000 60 + 11 / pFAPV25 (CMS, 1999) 50 250 + 36 / pF• How can noise depend on the detector capacitance?M.Friedl: Silicon Detector Readout 14 June 201233

Simplified Noise Modelv sIC deti pAmplifier noise,projected to the input• Amplifier noise is projected to voltage noise source andcurrent noise source at input• Integrator measures charge (integrated current)• Superposition analysis (one by one, other voltage sourcesare closed, other current sources are open; very simplified):Q n = ∫ i p dt + C det ⋅ V s = a + b ⋅ C det = ENCM.Friedl: Silicon Detector Readout 14 June 201234

Full Chip Example: APV25 (CMS)For each of the 128 channelsMUX gaininverterpipeline128:1MUXDifferentialcurrentoutput amppreampshaperAPSPS/H• Shaping time: 50ns, sampling: 40MHz• Analog pipeline (192 cells) to store data untiltrigger arrives, optional APSP filter, 128:1multiplexer, differential output driver8.1mmM.Friedl: Silicon Detector Readout 14 June 2012357.1mm

APV25 in ActionSensorPitchAdapterAPV25BondwiresHybridM.Friedl: Silicon Detector Readout 14 June 201236

Shaper Output Sampling• Usually, shaper output is sampled once at the peakThen those values are multiplexed (1:128) to the outputPeak sampleAmplitudeParticle hit• The timing is given by a constant offset from the particle hit(as supplied by an external trigger, e.g. scintillator)• What happens if there are several particles with differenttiming?M.Friedl: Silicon Detector Readout 14 June 201237Time

Pile-up Events• Strip detector measurement in a high intensity beam• Trigger – hit ambiguities and non-peak sampling can occur“pileups”Trigger from this particleAlso returns several other samples > 0!M.Friedl: Silicon Detector Readout 14 June 201238

How to Avoid Such Ambiguities?• Better timing information implies more data, more energyand/or a higher noise figure• Faster Shaping = narrower output pulsesLimited by noise performance• On-chip pulse shape processing (APV25)“Deconvolution” filter which processes samples and essentiallynarrows down the output to a single bunch crossing• Off-chip data processingUsing multiple subsequent samples and apply a pulse shape fitM.Friedl: Silicon Detector Readout 14 June 201239

Hit Time Finding• Shaper output curve is well known with two parametersPeak amplitude, peak timing• Event-by-event fit of shaping curve determines those twoTiming resolution of ~3ns (RMS) measured with APV25Signal [e]3500030000250002000015000strips= 317 - 320clwidth=4tmax=89.25 nsamp=34775 echi2/ndf=5.695e+00Data above thresholdData below thresholdIntCal fitentries []500400300(cal. fit (spline) - TDC) p sideh_tdc_cal_diff_0_1_pyEntries 13155Mean 0.02441RMS 2.281Underflow 0Overflow 02c / ndf148.4 / 97Constant 480.5 ±5.3Mean1.568e-09 ±1.900e-02Sigma 2.16 ±0.011000020050000Threshold0 50 100 150 200 250 300Time [ns]1000-15 -10 -5 0 5 10 15tpeak_cal-tpeak_TDC [ns]M.Friedl: Silicon Detector Readout 14 June 201240

Occupancy ReductionBelleSVD2VA1TATp~800nsBelle → Belle II:40 x increase in luminosityThresholdTime over threshold ~ 2000ns (measured)Belle IISVDAPV25Tp~50nsThresholdGain ~12.5Belle IISVD withHit time findingTime over threshold ~ 160ns (measured)Pulse shapeprocessingRMS(tmax)~3nsSensitive time window ~ 20nsGain ~8Total gain ~100Markus Friedl (HEPHY Vienna): Status of SVD 12 November 201141

Front-End Amplifier Summary• Integrated circuits with typically 128 channels• 2 stages:Preamplifier (integrator: current → charge)Shaper (band-pass filter to reduce noise)• Noise is referred to input and expressed as charge: ENC = a + b ⋅ C det (a,b...const, C det ...detector capacitance)• Shaper bandwidth determined speed and noiseFast ≡ large noise; slow ≡ low noiseRequired speed is usually defined by the experimentSlow shaping and pile-up can lead to ambiguitiesTricks to circumvent speed limitation, e.g. hit time findingM.Friedl: Silicon Detector Readout 14 June 201242

• Silicon Detector• Front-End Amplifier• Signal Transmission• Back-End Signal Processing• SummaryM.Friedl: Silicon Detector Readout 14 June 201243

Why?• Detector front-end is usually quite crowdedRadiation environment does not allow commercial electronicsMaterial budget should be as low as possiblePower consumption as well (requires cooling = material)• Thus, only inevitable electronics is put at the front-end• Everything else is conveniently located in a separate roomoutside the detector, traditionally called “counting house”Allows access during machine and detector operationM.Friedl: Silicon Detector Readout 14 June 201244

Example: CMS Experiment• Electronics hall is almostas big as experimentalcavern• Signal distance up to100m• Huge amount of signaltransmission linesElectronicscavernExperimentalcavernM.Friedl: Silicon Detector Readout 14 June 201245

Generic Transmission Chain< 2m up to 100mFront-endRepeater• Signal directionsReadout (large amount): front-end to back-end,analog or digitalControls (small amount): back-end to front-end,digital (clock, trigger, settings)• Usually, the front-end chips cannot drive the full pathRepeater (driver/receiver) is needed to amplify signalsBack-endM.Friedl: Silicon Detector Readout 14 June 201246

Excursion: Electrical Signal TransmissionV SR SR L• Single-endedagainst GNDHuge ground loopGND compensation≈R SR L• Single-ended incoaxial cableNo ground loopGND compensationV S+(from APV)EL5173-150pF50Ω50Ω150pF30m CAT7 cable100ΩADCdaughterboard(~100MHzbandwidth)(to PC)• Differential twistedpair (+shield)Largely immuneM.Friedl: Silicon Detector Readout 14 June 201247

Cable Bandwidth• Every cable has a finite bandwidth / dampingNonlinear attenuation with rising frequency• Example: CAT7network cable(shieldedtwisted pairs)• Significantespecially foranalog signaltransmissionNormalized loss [dB]10-1-2-3-4-5-6-7TheoryMeasurement30m CAT7 Transfer Function1 10 100Frequency [MHz]M.Friedl: Silicon Detector Readout 14 June 201248

Alternative: Optical Fiber• Fibers have extremely high bandwidth and very little loss• Also automatically provide electrical isolation betweensender and receiver sides• However: requires conversion on both ends, which makes anoptical link more expensive than a cable• Best suitable for long-haul, high-speed digital datatransmission such as telecom• Nonetheless also often used in HEP experiments• Optical transmission usually implies digital signals with NRZcoding (pure AC signal with only very short DC sequences)M.Friedl: Silicon Detector Readout 14 June 201249

Comparison: Copper vs. Optical FiberProperty Copper Cable Optical FiberCable rigid delicate (e.g. radius)Connectors huge variety few standardsSize/weight large smallBandwidth limited highLoss high lowDriver + receiver cheap expensiveLevel isolation no yesM.Friedl: Silicon Detector Readout 14 June 201250

Example: CMS Tracker (1)• Optical fiber required because of material budgetDetector ModuleClock & TriggerResetControl (I2C)AnalogOptohybridLLD1MU-sMUPatchPanel1296MFSPatchPanelAnalogReceiverDAQInterfaceDataProcessingTTCrxFEDAnalog Optical LinkParameters37,000 channels100m fiber length1310nm infrared lightStep-index single-mode fiberIntensity modulation40MHz readout speedI2C control interfaceExperimental Cavern: Radiation ZoneCounting Room• Exceptional case: analog optical transmissionSpecial requirements for linearity, gain stability and noiseM.Friedl: Silicon Detector Readout 14 June 201251

Example: CMS Tracker (2)Analog OptohybridMU-sMU ConnectionMFS ConnectionRugged Multi-Ribbon CableAnalogReceiverASICAnalog Rx ModuleLaser Transmitter• Several components are customized and thus expensiveO(10000) are small quantities for industry• Estimated cost per link: ~150 € (cf. ~15 € with cable)M.Friedl: Silicon Detector Readout 14 June 201252

Example: Belle II Silicon Vertex Detector• Analog APV25 readout is through copper cable to FADCs• Junction box provides LV to front-end• APV25 drives 12m cables!1748APV25chips~2mcoppercableJunctionbox~10mcoppercableFA DC +P R OCFinesse TransmitterBoard (FTB)Unified opticaldata link (>20m)COPPERFront-endhybridsRad-hardDC/DCconvertersAnalog level translation,data sparsification andhit time reconstructionUnified Belle IIDAQ systemM.Friedl: Silicon Detector Readout 14 June 201253

Example: Belle II Silicon Vertex Detector• Using same APV25 chip as in CMS, but much shorterdistance → no optical link required• Analog signals are attenuated in long copper cableFirst attempt was an analog equalizer chip (enhancing higherfrequencies) with moderate successLater tried purely digital filter after digitizationPerfect regeneration with digital signal processing (FIR filter) atthe back-end inside an FPGAMultiplication of 8 consecutive samples with 8 filter coefficientsand summing in real-time (40 MHz)M.Friedl: Silicon Detector Readout 14 June 201254

Example: Belle II Silicon Vertex DetectorOptimized channelNon-optimized channelRaw APV25 outputwithoutFIR• FIR filter with 8 coefficients operating continuously at 40MHz• Removes cable loss and reflections due to imperfect termination!M.Friedl: Silicon Detector Readout 14 June 201255

Signal Transmission Summary• Signals of large number of readout channels to betransmitted to back-end for data processing• Options: copper cable or optical fiber• Copper is much cheaper, but has frequency-dependent lossCan be compensated e.g. with digital FIR filter at back-end• Optical links are more complicated to handleUsually digital with NRZ codingException: CMS Tracker uses analog optical linksM.Friedl: Silicon Detector Readout 14 June 201256

• Silicon Detector• Front-End Amplifier• Signal Transmission• Back-End Signal Processing• SummaryM.Friedl: Silicon Detector Readout 14 June 201257

Purpose of the Back-End• Perform all the steps which can’t be done in the front-endFront-end ADC FPGADAQ• Readout chain:Receiver (electrical or optical), digitization (if analog input),data processing and reduction in FPGA (field programmablegate array), output to DAQ (data acquisition)• Receiver for clock, trigger and controls (centrally distributed)M.Friedl: Silicon Detector Readout 14 June 201258

Example: CMS-Pixel-FED• FED means “FrontEnd Driver”(misleading)• Contains all theelementsmentioned beforeAnalog optical receiversADCsFPGAsCLK, TriggerFPGAsFPGATo DAQM.Friedl: Silicon Detector Readout 14 June 201259

Boards and Crates• Such boards are typically built according to a certain(industrial) standard bus system“Standard”: VME (Versa Module Eurocard), size 9UObsolete: CAMAC, FastbusModern: µTCA• All those standards describeGeometry of modulesElectrical interface, power supplyBus system for communication with crate controller & PC• Organized in crates and racksM.Friedl: Silicon Detector Readout 14 June 201260

VME (9U) CratesEmpty crateas sold by industryBelle I SiliconVertex Detector(cable input)CMS Pixel-FED(optical input)M.Friedl: Silicon Detector Readout 14 June 201261

What’s an FPGA?• FPGA is a huge array of logical gates which can be combinedaccording to the user’s need• Programming by software using basic gates & library blockse.g. and, adder, latch, …, CPU coreEither by schematics or by VHDL programming languageM.Friedl: Silicon Detector Readout 14 June 201262

Comparison: FPGA vs. CPUProperty FPGA CPUParallelism any a few coresSpeed (clock) O(100MHz) O(1GHz)I/O lines O(1000) 64Best suitable forAt the back-endFast, simple, massiveparallel processingFirst low-level datareductionComplex, serial programsHigh-level dataprocessing (DAQ)M.Friedl: Silicon Detector Readout 14 June 201263

Example: APV25 Output Data StreamAmplitude [ADC]headerHit dataData frameidleStrip data (pedestals)Time [25ns]M.Friedl: Silicon Detector Readout 14 June 201264

Strip Data Composition• Analog signal output of one event is a multiplexed stream of128 data values, but not just the actual strip signalADC i = S i + N i + P i + CMNi…strip numberADC i …measured amplitude in ADC unitsS i …particle signalN i …noise (random fluctuations)P i …pedestal (zero value; individual for each strip)CMN…common mode noise (common to all strips in one event)• Pedestal and noise can be measured and saved for eachchannel, CMN is removed event-by-eventM.Friedl: Silicon Detector Readout 14 June 201265

How to Process Strip Data?ADCADCADC300200100402006040200(a)(b)(c)50 100 150 200 250Raw datastrip50 100 150 200 250Pedestal subtractedstrip50 100 150 200 250After common mode correctionstrip• Data stream withindividualpedestals (dots)• Dominated bypedestal variationM.Friedl: Silicon Detector Readout 14 June 201266Signal• Pedestals subtracted,common mode noise andindividual strip noiseremains• After commom modecorrection, average is atzero with random noiseexcursions for each strip• Next: Apply hit threshold

Typical Tasks for Silicon Strip DetectorDigitizationFrame DetectionR eorderingPedes tal S ubtractionCMC (2-pass)Hit FindingTime FindingFPGA ADC• ADC converts data to digital• Find and extract strip data• Put the strip data in natural order(needed if entangled, e.g. APV25)• Subtract zero value for each strip• Remove common-mode noise(appears on all strips in common)• Apply hit threshold (zero suppression,sparsification) = keep only hit data• Optional post-processing (e.g. APV25)M.Friedl: Silicon Detector Readout 14 June 201267

FPGA Limits• Simple state machine, but no complex programming(instruction list) as with a CPU• Typically integer arithmetic• Made for fast I/O and throughput; internal memory is limited• Ideal for first stage of data processing – O(10) times morethroughput than a state-of-the-art CPU• More complex operations at a later stage with reduced dataare performed on CPU farms (DAQ)M.Friedl: Silicon Detector Readout 14 June 201268

Back-End Signal Processing Summary• Performs digitization, data processing (reduction) andoutput to subsequent DAQ (computer farm) stagePedestal subtraction, common mode correction, zerosuppression• Boards following a bus module standardE.g. VME (9U)• Organized in crates and racks• Typically uses FPGAs (field programmable logic arrays)Ideal for low-level massive parallel processingMore powerful than CPUs for such tasksComplex calculations are done in subsequent computer farmM.Friedl: Silicon Detector Readout 14 June 201269

• Silicon Detector• Front-End Amplifier• Signal Transmission• Back-End Signal Processing• SummaryM.Friedl: Silicon Detector Readout 14 June 201270

Thank you for your attention!M.Friedl: Silicon Detector Readout 14 June 201271