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Warm LC DAQ Tom Markiewicz SLAC

Warm LC DAQ Tom Markiewicz SLAC. LCWS Victoria 30 July 2004. Introduction & Caveats. I am not qualified to give this talk Version of this talk given in Cornell’03 DAQ Assumptions No QSR backgrounds (dominant SLC background) No trigger problems 0.1 Hz trigger in 1995 lead to 10% deadtime

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Warm LC DAQ Tom Markiewicz SLAC

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  1. Warm LC DAQTom MarkiewiczSLAC LCWS Victoria 30 July 2004

  2. Introduction & Caveats • I am not qualified to give this talk • Version of this talk given in Cornell’03 DAQ • Assumptions • No QSR backgrounds (dominant SLC background) • No trigger problems • 0.1 Hz trigger in 1995 lead to 10% deadtime • Dead-timeless 120 Hz trigger in 2015 • IP Backgrounds dominate data load • Muon backgrounds not yet included • At the appropriate time real DAQ experts will design system • Channel counts, resolution, range, mean occupancy, occupancy fluctuations, buffer sizes • Smart readout (front-end intelligence)

  3. Snowmass 2001 LD Background Occupancies @ 500 GeV for LD

  4. Detector Occupanciesfrom e+e- Pairs @ 500 GeVfcn(bunch structure, integration time) TESLA NLC

  5. LD Data Rates from e+e- Pairs @ 500 GeV presented at Cornell’03 ALCPG DAQ Session Bytes*Hits*192 *120

  6. Today’s Talk • Update expected front-end data load • SiD Detector • Hit’s based on Toshi Abe’s GEANT simulations • Beamstrahlung photon interactions producing • e+e- incoherent pairs • Hadrons • m+m- • Assume one Z H event per train crossing

  7. e+e- Pairs @ 500 GeV

  8. Hadronic 2-photon events at NLC/GLC

  9. Detector Occupancies Study by T. Abe

  10. Tracking Detector Hits per Train(T. Abe)

  11. Calorimeter Hits per Train(T. Abe)

  12. Muon Hits per Train(T. Abe)

  13. Bytes/hit per DetectorBrute Force

  14. Silicon Detector Data Load

  15. Conclusions • Largest change with respect to the exceedingly crude 2003 estimate is TPC vs. Si-Tracker and “dumb readout” assumption of 100 bytes/hit • Total front end data load for SiD seems modest, even by SLD standard • Wire systems (CDC, CRID) dominated SLD data • Would like to better understand integration of machine info with detector

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