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reno-specific muon spectrum

reno-specific muon spectrum. GLG4Scint.cc  scintillation process  reemission process  energy deposition G4Cerenkov.cc  cerenkov process. optical photons tracking. GLG4PMTOpticalModel.cc : optical photon interaction with PMT. scint/off scint/reemission 0

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reno-specific muon spectrum

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  1. reno-specific muon spectrum

  2. GLG4Scint.cc  scintillation process  reemission process  energy deposition G4Cerenkov.cc  cerenkov process optical photons tracking GLG4PMTOpticalModel.cc : optical photon interaction with PMT scint/off scint/reemission 0 process/activate Cerenkov optical photon is disabled(turn off optical photon tracking), but still we have 'scintEdep'

  3. scintillation photon is ~ten times more than cerenkov photon • it takes ~3 sec for tracking of 10000 photons • how to count: • particle name==opticalphoton • process name==”Cerenkov”, “Scintillation”, “Reemission” • IBD event • positron is annihilated in ~10 mm • neutron is captured in ~100 mm • average path length of gammas is ~1000 mm

  4. IBD event at center (0,0,0) neutron (0,0,0) positron (0,0,0) optical photon generated annihilation: gamma (9.99, 12.7, 6.58) captured on Gd: gamma (-38.3, -225, 37.2) track length of gamma is ~ 1000 mm , which has about 16 steps occurring compton scattering e- e- • e- : tracking length 0.xx ~ xx.xx ex) tracking length 3.48 mm, 11.1 mm  optical photons are generated

  5. cerenkov only: ~1 event/3min. (~2000 n_photon_hits)

  6. <<< Event Catagory >>> topBotEvt topSideEvt sideBotEvt sideSideEvt totalEvt air: 18 veto only: 56 400 182 185 823 buffer only: 9 182 103 89 383 (catcher+target) : 49 156 135 136 476 all area: 1700 <<< Tagging efficiency >>> Air Veto only Buffer only Catcher+Target generated: 18 823 383 476 reconstructed: 0 781 380 473 tagging eff.: 0 94.9% 99.2% 99.4% (using OD) generated: 18 823 383 476 reconstructed: 0 0 287 476 tagging eff.: 0 0 74.9% 100% (using ID)

  7. Using OD pmts

  8. Check untagged events • Air only: 16 events (photonHit==0), 2 events (noHitPMT==0) • Target only (3 events) • 1 clst events(3) : • sideSide: #214, #707, #1633(through going buffer)  veto stopping muon events  it’s ok! • Buffer only (3 events) • 1 clst events(1) : • topSide: #213  veto stopping muon event  it’s ok! • 0 clst events(2) : • noHitPMT==0 : #554, #1195  veto stopping muon events  need to be checked!! • Veto only (42 events) • 1 clst events(29) : • topSide: 27 events  #897, #1500 veto stopping muon  25 events need to be checked!! • sideSide: #562, #1556  veto stopping muon  it’s ok! • 0 clst events(13) : • noHitPMT==0: #155  need to be checked!! • noHitPMT==0: 12 events  veto stopping muon  need to be checked!!

  9. What do untagged events look like? • (1) noHitPMT==0: • through going muon: air only(#1605, #1664), veto only(#155) • stopping muon: • buffer only: #554, #1195 • veto only: #29, #63, #290, #422, #495, #647, #986, #1056, • #1108, #1407, #1540, #1695 • (2) through going muon events reconstructed to one cluster event • 25 events: all topSide events

  10. (1)의 경우 #1605 #155

  11. (2)의 경우 #40 #1690

  12. through going muon momentum [MeV] Veto stopping muon momentum [MeV]

  13. Tagging efficiency (using OD pmts) • using through going muon events only Air Veto only Buffer only Catcher+Target generated: 18 786 368 459 reconstructed: 0 760 368 459 tagging eff.: 0 96.7% 100.0% 100.0% • 26(veto only) through going muon events are reconstructed to 1 cluster events : #155 + (2) • using all muon events (including veto stopping muon events) Air Veto only Buffer only Catcher+Target generated: 18 823 (37) 383 (15) 476 (17) reconstructed: 0 781 (21) 380 (12) 473 (14) tagging eff.: 0 94.9% 99.2% 99.4% •  Generated: stopping muon 37 + 15 + 17 = 69 events • Reconstructed: 21 of 37 stopping muons are reconstructed to 2 cluster events (veto only) • 12 of 15 stopping muons are reconstructed to 2 cluster events (buffer only) • 14 of 17 stopping muons are reconstructed to 2 cluster events (target only)

  14. Summary • Target only: • 459 (through going muon)  459 (2 cluster) • 17 (stopping muon)  14 (2 cluster), 3(1 cluster) • Buffer only: • 368 (through going muon)  368 ( 2 cluster) • 15 (stopping muon)  12 (2 cluster), 1 (1 cluster), 2 (no cluster (noHitPMT=0)) • Veto only: • 786 (through going muon)  760 (2 cluster), 25 (1 cluster), 1 (no cluster (noHitPMT=0)) • 37 (stopping muon)  21 (2 cluster), 4 (1 cluster), 12 (no cluster (noHitPMT=0))

  15. What is need to be checked • Need to check cut condition for ‘noHitPMT’: through going 이나 stopping muon을 스킵하는 경우가 있음 (15 events). • Stopping muon을 제대로 골라내지 못하는 경우: stopping muon을 2 cluster event로 reconstruct하는 경우가 있음 (47 events).  위의 두 사항이 해결되면 (target + catcher + buffer)를 지나는 모든 이벤트를 태깅할 수 있다. • 모서리를 치고 지나가는 뮤온: through going muon을 1 cluster event로 reconstruct하는 경우가 있음 (25 events). • 모서리치고 지나가는 뮤온으로부터 나온 neutron이 얼마나 되는지…

  16. to-do list • muon tagging efficiency using reno-specific muon spectrum: • through-going muon • stopping muon • inefficiency • muon induced backgrounds: • through going muon rate, stopping muon rate • neutron rate in the active detector region due to through going muon (or stopping muon) • total neutron rate in the target and correlated background rate, ..

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