Technical Design Report Super Fragment Separator

Fragment Monitoring
DRAFT
As example, the ring experiments only depend on the history of the pulses delivered to the
CR/RESR/NESR complex, e.g.:
• intensity,
• charge and mass distributions,
• contaminants,
• deviations from nominal beam optics.
They are of interest as for bunches all event-wise information gets lost in the transfer processes.
However, this is also the information that is needed as slow control feedback data, which is described
in the general NUSTAR-DAQ section. The collection of these data will be done by the
local stand-alone Super-FRS DAQ together with an on-line analysis process that runs as data
server for the Super-FRS’s slow control and the experiments bunch monitoring. The data server
should provide a list of information it can deliver and provide a selection mechanism. Together
with the information provided by the accelerator sections one is then able to monitor the full
production process. This will also allow the accelerator controls to get specific feedback information
from the experiments, allowing a very effective optimization of the setup data (see general
NUSTAR-DAQ section). The necessary R&D will be done in close relation with the accelerator
controls group.
Tracking experiments
Another class of experiments requires tracking ions through the separator, e.g.:
• experiments performed at the final focus (MF4) of the Super-FRS,
• experiments in the high energy branch R 3 B.
Here the main issue is to record event-wise information about individual particles through the setup.
As the selection process leads to substantial reduction factors (typ. 10 -6 PF4 � Caves, typ. 10 -3
MF2 � Caves), coincidences have to be build from the end of the beam line. This means, especially
for the diagnostic detectors at the entrance of the main separator, that at rates of several 10
MHz the spread in velocities for different isotopes with similar Bρ will lead to overlapping events.
This problem corresponds to the task of tracking particles with small yields while reconstructing
their interaction vertices as in high energy physics. Here this is usually overcome by storing the
data first in the front-end electronics while subsequently transferring and reducing it in a multi step
triggering process. In our case this problem can be reduced to the problem of finding a plausible
candidate in a certain time interval for an identified particle at one of the experiments.
There are several solutions, as discussed below, which have to be evaluated in close collaboration
with the planned experiments:
i. a suitable reduction rate can be achieved already by demanding a coincidence window,
where events are taken. The particular coincidences are evaluated off-line.
ii. Coincidences are fully evaluated on-line.
Option (i) can be realized in different ways. The conventional approach is to adjust cable delays to
digitize all data from the experiment within a coincidence time (e.g. given by a gate). This is,
however, also the most inflexible approach in view of the different DAQs that should be coupled
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