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Functional r equirements for BGV demonstrator ( Run 2)

not discussing performance requirements here. Functional r equirements for BGV demonstrator ( Run 2). this is work ongoing will soon be available in written (proper document). Generalities.

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Functional r equirements for BGV demonstrator ( Run 2)

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  1. notdiscussing performance requirementshere Functionalrequirements for BGVdemonstrator (Run 2) this is work ongoing will soon be available in written (proper document)

  2. Generalities • The main purpose of the BGV is to deliver transverse beam size values (one H and one V) per bunch at the highest possible rate • aim for a per-bunch statistical accuracy of ~5% in 3 min for 1011 p • The beam size values are extracted from transverse 2D (HxV) distributions, which can also be made available to the operators • Accessorily, it can also measure • a beam trajectory ( => position, slopes) • relative bunch amplitudes for any bunch slot ( => ghost charge!) • The BGV will be able to measure beam sizes at any energy and any beam intensity • of course, the data rate will scale with the bunch intensity and depend on energy and beam species NB: here, bunch slot = BCID

  3. Some basic facts • BGV demonstratoris for LHC Ring 2, but the ideais to later (after Run2) develop one BGV per ring. Thesewillbetwoindependentsystems, like the LDM of each ring. • In a first phase, the BGV demonstratorwill have to becommissioned by experts only • In a second phase, the BGV willbeused by CCC operators • but experts will continue to debug/improve/calibrate reflected in the control/monitoring architecture LHC Vac ? BGV ECS (PVSS) for experts LHC SCADA LHC CMW for LHC operation ? interface ? vacsys gastarget detector FE Readout boards DAQ slow control data storage slow control data storage event data storage

  4. What "event data" does the BGV produce and how ? • Upona "Level-0 trigger" the detector FE deliversanalogsignals of all fibres to the Readoutboard (TELL1) • The TELL1 boarddigitizes(ADC) the signal and performs(FPGAs) a zero-suppression (subtractpedestals, subtractcommon-mode, find candidate "hits" and construct a "cluster" fromthat). It creates a data bank for thistriggeredevent(BCID...) and putstogethera fixednumber of events in a multiple event package (MEP) beforesendingit by Gbit to a specificnode of the DAQ farm(as decided by the ODIN readoutsupervisor) • On the DAQ node an event-builderprocesswaitsuntilreceives MEP from all sources (TELL1s+ODIN), builds the events and passes these to an HLT process. The HLT processmakes the pattern recognition and fitting (tracks + vertex). The event data are thenpassed to a diskwriterprocess. signal 0 fibre channel 0 ADC clus. charge cluster position tracks and vertex

  5. DAQ flow

  6. Basic requirementsfrom CCC operation Monitoring: • beam size X and Y vs time • same for a selectable BCID (or set of BCIDs) • ghost charge vs time • beam positions (H, V) and slopes (H, V) vs time • same for a selectable BCID (or set of BCIDs) • histogram of event rate vs BCID Control: • detector • "turn ON/OFF" (to bedefinedwhatitmeans) • "reset BGV" (to bedefinedwhatitmeans) • load a fillingscheme and editwhich slots shouldbeconsidered for data acquisition • gastarget • control gas injection

  7. Basic requirementsfrom experts • Control: • restart a run • loada fillingscheme and editprescale factor per BCID • change the proportions of vertex : cluster : NZS trigger rates • send test pulse triggers • change L0 trigger thresholds • change HLT trigger cuts Difference to LHCb: • addbeamenergy and beam modes to ODIN bank (couldbeused to adjust HLT cuts per event ?) • event time ordering must berespected to ~1s • BGV DAQ acts ~like a "monitoring farm" in the sensethatit must produce online results (trends) based on selectedevents

  8. Event data sizes out of TELL1s Zero-suppressed data: • TELL1 data willdepend on numNcl of clusters per BGV event and data size scl per cluster (as for VELO, fixed) • Assume hereNcl = 300 and scl= 4 B • Thus 1.2 kB per triggeredevent • As a comparison the VELO (84 TELL1s) has for pp=8 TeV an event size of about 9 kB. • To the TELL1 data one shouldadd the transport overhead and the ODIN data • Assume about 1.5kB per event. Non-zerosuppressed data: of the order of 128*144*1B = ~20kB per triggeredevent 128channels + 16header channels 8bit ADC value

  9. Event data rates TELL1s to DAQ Zero-suppressed data from TELL1s to DAQ: • Absolute maximum = 1.5kB/Trg x 1 MTrg/s = ~1.5 GB/s distributed over 8 TELL1 sources (~ 200MB/s per source) • willprobablybeless, becausewe set a L0 trigger thresholdwhichkeeps the L0 rate below 1MHz (few 100 kHz)

  10. DAQ output event data categories • vertex data: these are the data used online to make the beam profiles. They are produced in the online reconstruction. • these are "final" results, i.e. include already the vertex resolution corrections • storing split vertices also allows to get the resolution (but without changing alignment) • cluster data: needed for online monitoring of pattern recognition and for offline verification of results. Allow to re-do the tracks and vertices, perform alignment, parametrise the vertex resolution corrections, etc. These data are appended to some events at a reduced rate for monitoring, but it should be possible to increase the rate for dedicated "calibration" runs. • NZS data (non-zerosuppressed): these "raw" data are needed to monitor pedestals and noise, to check the overall behaviour of the front-end part. The data are appended to some events but at a very reduced rate. • Additionally: histograms of vertex data, for example.

  11. DAQ output event data: vertex data These are the data used online to make the beam profiles. They are produced in the online reconstruction. • these are "final" results, i.e. include already the vertex resolution corrections Estimated data size: Minimum data are*: vertex track multiplicity 1 short 2B vertex 3D positions 3 floats 12B vertex position covariant matrix 9 floats 32B header data ODIN 50B Rate of about 3 Hz per bunch (max. 2800 bunches) Max rate: 3Hz x 2800 x 100B = 800 kB/s This should be the dominant data rate *Alternative: split vertices 1 & 2, mult & 3D => 2x(2B+12B) = 28B (don't need covariance)

  12. DAQ output event data: cluster data Needed for online monitoring of pattern recognition and for offline verification of results. Allow to re-do the tracks and vertices, perform alignment, parametrize the vertex resolution corrections, etc. These data are appended to some events at a reduced rate for monitoring, but it should be possible to increase the rate for dedicated "calibration" runs. Estimated data size: this is the same as the TELL1 data input to DAQ => 1.5kB/Trig. Rate: To keep reasonable compared to the vertex data, limit to about 80kB/s which would mean abut 50Hz maximum

  13. DAQ output event data: NZS data These "raw" data are needed to monitor pedestals and noise, to check the overall behaviour of the front-end part. The data are appended to some events but at a very reduced rate. Estimated data size: order of 20 kB Rate: To keep reasonable compared to the vertex data, limit to about 80kB/s which would mean about 4Hz maximum

  14. Slow control data Front end: • 128 SiPMTemp values • 32 SiPMbias voltages and currents ? • xxx LV states (or voltage and current values ?) Readout: ... DAQ: ... Vacuum: ...

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