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EMCal & PID

EMCal & PID. Rikard Sandström Universite de Geneve MICE collaboration meeting 26/6-05. Outline. Introduction Definition of background & good event Setup Beam, background, detectors. Performance & results Summary. Introduction. Provided a clear definition of background.

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EMCal & PID

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  1. EMCal & PID Rikard Sandström Universite de Geneve MICE collaboration meeting 26/6-05

  2. Outline • Introduction • Definition of background & good event • Setup • Beam, background, detectors. • Performance & results • Summary

  3. Introduction • Provided a clear definition of background. • Using neural network to do PID in G4MICE. • Increased difficulty by choosing larger p rms of beam. • Now also using tracker, TOF. • More aggressive filtering and cuts.

  4. Definition of good event • A good event is a event which leaves a hit in TOF2. • T_min = light speed between TOF1 & TOF2 • T_max = half light speed - “” -.

  5. Definition of downstreambackground • A downstream background is an good event where no hit in TOF2 is (in truth) an antimuon. • Hence, empty TOF2 events are not background nor signal -> lost.

  6. The beam • Background from decay of muon beam. • Less monochrome beam in p_z than earlier: • 10 mm pi rad, 4D emittance • Pz = 196.2 +- 30.7 MeV/c • Px = 0 +- 28.4 MeV/c • Z_start = -6011 mm (after diffuser) • T = 0 +- 70 ps (corresponding to TOF resolution) • Causes worse PID than earlier beam. • Considerable scraping in cooling channel. • Muons are often off-phase in RF system.

  7. Sources of background • Particles get lost in RF system and decay. • TOF window. • Particles decaying in flight. • Tricky… • Particles decay during the EMCal gate at rest. • Short gate / TDC / don’t stop muons in calorimeter. • Particles decay in time window of other event. • Needs to be studied. • In addition, RF BG will hit TOF2.

  8. Tracker and TOF • Using Gaussian(truth,std) • P_t and P_z resolution from Ellis simulation of SciFi in presence of RF background. • 1.75 resp 2.41 MeV/c • TOF resolution 70 ps. • Could be ignoring systematic effects! • Forcing TOF window rejects mu decay at rest. • Individually, p and tof not good variables for PID. • Calculate tofError = tof-[expected tof using <pz>,m_mu] • Excellent for PID

  9. Calorimeter • Standard 4 layer KLOE light spaghetti. • Fiber, lead, glue. • Amp(t) ~ (t/T)^2 exp(-t/T), T=8 ns best exp fit. • Open gate 100 ns. • 17 cm/ns transversal delay (along fiber to PMT). • Still manually triggered. • In future, could make use of expected muon range given p in tracker.

  10. Two principle ideas of calorimeter • Either range based calorimeter… • Given momentum, range of muon is well defined. • …or avoiding muon decay in calorimeter • Will cause additional background in • own event (100 ns/2mus -> 3.4 % probability) • other event (600*0.1/1000 = 6 % probability) • Best of both worlds? • Have simulated two alternative designs (sandwich & smörgås), no time to analyze results yet.

  11. Performance • Filtering on TOF2. • Output-> Good/bad events • Using Neural Network to clean up. • Good events -> signal/bg • 10 pi mm rad gives • 16.68% bad events • Mostly scraping • 7.5% of scraped events leave electrons at tof2. • 99.557% input purity • Only ~130k Events.

  12. Inputs (1) Off phase in RF

  13. Inputs (2) Sum[sqrt(adcL*adcR)] Due to mu decay at rest

  14. Too few events

  15. Efficiency • Plots show efficiency for muon id and background id. • Background ID is poor, caused by too small sample?

  16. Purity • Choosing purity and efficiency means choosing a cut value. • Working under assumption target = • efficiency > 99.9 % • purity > 99.8 % • Achieved!

  17. Performance for subsystems (No Ckov2) good

  18. Comments on results • Lower p_z rms gave better result, but... • Target achieved, do we want to do better? • When are we happy? • Room for improvements: • Expected muon range in EMCal. • Transverse size in EMCal. • Getting rid of decay at rest in EMCal (geometry or TDC?) • Background detection efficiency expected to improve with larger sample. • Positive effect on purity. • Must find memory leak. • Ignoring possible correlations in tracker • Ex. Resolution as function of p_t.

  19. Summary • G4MICE + Neural Net shows downstream PID works. • Also with scraping, huge p_rms and emittance. • Ckov2 can give further improvements. • More data desired. • Two major sources of background not included: • Overlap of muons. • Decay of muons in window of other events. • Need spill based simulation! • Invite you to my talk in the software session!

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