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Study of Accidental Activity at the Front Barrel of the KOTO Detector Ryota Shiraishi Yamanaka Group Kuno-Yamanaka Group Year-End Presentation 2019 Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019 Introduction


  1. Study of Accidental Activity at the Front Barrel of the KOTO Detector Ryota Shiraishi Yamanaka Group Kuno-Yamanaka Group Year-End Presentation 2019 Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019

  2. Introduction The KOTO experiment K L → π 0 ν ¯ Purpose : To observe the decay . ν Signal : 2 photons + “nothing” ➥ detected at the ➥ other veto detectors CsI calorimeter make sure of no extra hits CsI π 0 K L γ γ ν ¯ ν 2 Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019

  3. Accidental Signal Loss Accidental hits on veto detectors coincident with the π 0 decay could cause signal loss. Major sources… • Other K L decay • Neutron from the J-PARC primary beam line Veto Window Discarded π 0 decay (Acceptance loss) signal @CsI Accidental hit Accidental hits need @veto detector to be reduced. 3 Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019

  4. Purpose of This Study • To understand accidental activities at the Front Barrel of the KOTO detector. • To calculate accidental hit rates by using data taken in 2019. • To check consistency of accidental hit rates between physics-triggered data and TMON- triggerd data. K L → π 0 ν ¯ Physics trigger…trigger to collect data ν TMON trigger…trigger to reproduce accidental hits 4 Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019

  5. Front Barrel • Sandwich of lead & plastic scintillators • 2.75m long • Sampled by125MHz FADC • 16 modules • 32 readout channels View from the downstream side (inner/outer layers are read separately) Front Barrel 5 Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019

  6. TMON Trigger TMON trigger is… A random trigger generated from the signals of the Target Monitor . The rate is proportional to the beam intensity. We use this trigger to reproduce accidental activities and overlay the waveforms on generated waveforms in simulation. Plastic Scintillators TMON Trigger Proton 50° Beam 16° Au KOTO Beam Line Target 6 Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019

  7. Energy Distribution FBAREne {FBARModID==0 && ExtTrigType==2} TMON data FBAREne {FBARModID==0 && ExtTrigType==2 && FBAREne<50} h h # of events Entries Entries 30082 30082 Mean Mean 2.337 2.337 10 4 4 RMS RMS 10 4.122 4.122 Energy is distributed up to ~600 MeV. 10 3 3 10 Now, set the energy threshold 10 2 2 10 to 2 MeV. 0 5 10 15 20 25 30 0 2 30 FBAREne [MeV] Consider only events with FBAREne:FBARModID {ExtTrigType==2} ➤ FBAREne:FBARModID {ExtTrigType==2} 600 FBAREne [MeV] 600 FBAREne > 2 MeV. 4 10 FBAREne [MeV] 500 3 10 400 Higher counts 300 2 10 in inner channels 200 ➞ 10 100 Lower counts 0 in outer channels 0 1 0 5 10 15 20 25 30 FBARModID FBARModID 7 Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019

  8. Comparison between Phys. & TMON data Rate[Hz] per bin(= 1clock=8ns) FBAR Rate ch0 (E > 2 MeV) FBAR Rate ch0 (E>2.000000MeV) FBAR Rate ch0 (E>2.000000MeV) × 10 3 3 600 × 10 600 Rate = #events / ( ∆ T × #triggered) − : Physics − : TMON 500 ( ∆ T = 1clock = 8ns) Rate [Hz] 400 Rate [Hz] 300 200 Earlier timing region 100 (phys./tmon) -> consistent ratio (phys / tmon) 10 0 10 20 30 40 50 60 70 Ratio 1.5 1 0.5 − 10 0 10 20 30 40 50 60 70 Later timing region FBARPTime [clock] FBARPTime [clock] -> subtle discrepancy exists 8 Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019

  9. Rates in 10 - 20 clock timing E > 2MeV, FBAR Rate ch0 (E>2 MeV) FBAR Rate ch0 (E>2.000000MeV) FBAR Rate ch0 (E>2.000000MeV) 300 × 10 3 FBAR Rate E>2.000000MeV 10 < FBARPTime < 20 3 10 × 600 (FBARPTime>10.000000 && FBARPTime<20.000000) 3 10 × 300 500 − : Physics 400 Rate [Hz] 250 Rate [Hz] − : TMON 300 Rate [Hz] 200 Inner Channels Rate [Hz] 200 150 100 (phys./tmon) ratio (phys / tmon) 10 0 10 20 30 40 50 60 70 100 Ratio 1.5 1 0.5 50 Outer Channels 10 0 10 20 30 40 50 60 70 − FBARPTime [clock] (phys./tmon) FBARPTime [clock] ∆ T 1 Ratio ratio (phys / tmon) 0 5 10 15 20 25 30 1.2 Energy Threshold : 2MeV 1.1 1 0.9 Rate = #events/( ∆ T × #triggered) 0 5 10 15 20 25 30 FBARModID FBARModID ∆ T = ∆ T 1 Ratio = Phys./TMON ⟶ = 1 ~ 1.1 Primary beam line side ➞ Good agreement 9 Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019

  10. How we will reduce accidental hits Accidental activities by neutrons coming from the J-PARC primary beam line Iron Wall To reduce the neutron flux, we installed a 33cm-thick iron wall. Iron Wall KOTO Detector Primary Beam Line KOTO neutron detector 10 Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019

  11. Summary / To do • Confirmed consistency of accidental counting rates in physics/TMON data. • To reduce neutrons from the primary beam line, we installed an iron wall and will check the reduction e ff ect. 11 Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019

  12. Backup Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019

  13. Detector View from the downstream side 13 Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019

  14. Waveforms at the Front Barrel Waveform Examples FBAR.Data:Iteration$ FBAR.Data:Iteration$ {FBAR.ModID==0 && Entry$==256} {FBAR.ModID==0 && Entry$==706} FBAR.Data:Iteration$ {FBAR.ModID==0 && Entry$==256} FBAR.Data:Iteration$ {FBAR.ModID==0 && Entry$==706} 520 ADC counts ADC counts FBAR.Data FBAR.Data 515 900 510 800 505 700 500 495 600 490 500 485 0 10 20 30 40 50 60 70 0 10 20 30 40 50 60 70 0 20 0 40 Iteration$ Iteration$ Time [clock=8ns] Time [clock=8ns] Physics-triggerd event TMON-triggerd event Energy : 13.8 [MeV] Energy : 3.1 [MeV] Time : 17.7 [clock=8ns] Time : 47.3 [clock=8ns] Consider an energy threshold and timing distributions. 14 Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019

  15. Time Distribution Take the moving average -> make waveforms smoother Calculate a parabolic curve using three samples around the peak. The parabola time closer to the nominal time (~31 clocks) for the Front Barrel is selected. Tend to have a structure like a broad hill. ➤ TMON Physics Parabola FABRPTime {FBARModID==0 && FBAREne>2 && FABRPTime {FBARModID==0 && FBAREne>2 && curve FBARPTime>-10 && (ScaledTrigBit&0x1)==0x1} FBARPTime>-10 && ExtTrigType==2} FBARPTime {FBARModID==0 && FBAREne>2 && FBARPTime>-10 && ExtTrigType==2} FBARPTime {FBARModID==0 && FBAREne>2 && FBARPTime>-10 && (ScaledTrigBit&0x1)==0x1} htemp htemp htemp htemp Entries Entries 8044 8044 Entries Entries 78920 78920 Mean Mean 28.49 28.49 Mean Mean 28.95 28.95 3500 350 RMS RMS 16.34 16.34 RMS RMS 15.4 15.4 Dominated by 3000 300 Concentrated around # of events # of events 2500 accidental hits 250 the nominal time 2000 200 1500 150 1000 100 50 500 Parabola 0 0 0 10 20 30 40 50 60 0 10 20 30 40 50 60 30 30 time FBARPTime FBARPTime FBARPTime [clock] FBARPTime [clock] 15 Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019

  16. Moving Average FBARWfm[0]:Iteration$ {Entry$==153} wfm2 wfm2 600 ADC Calculation Code Entries Entries 64 64 Mean x Mean x 31.5 31.5 580 Mean y Mean y 503.8 503.8 Std Dev x 18.47 Std Dev x 18.47 Std Dev y 16.24 Std Dev y 16.24 560 540 520 500 480 460 0 10 20 30 40 50 60 /sw/koto/e14ana/release/v4.01.10/AnalysisLibrary/UserProjects/ Time [clock] E14ProdLibrary/E14ProdDstConv/src/E14CrateData125MHz.cc Averaged Wfm wfm wfm wfm 600 ADC Entries Entries 60 60 Mean x Mean x 31.5 31.5 Take the average of five Mean y Mean y 580 503 503 Std Dev x 17.32 Std Dev x 17.32 Std Dev y 15.12 Std Dev y 15.12 560 consecutive samples. 540 520 Make waveforms smoother and 500 mitigate local fluctuations. 480 460 0 10 20 30 40 50 60 Time [clock] 16 Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019

  17. Parabola Interpolation Method Moving Average Peak Search ptime Nominal Time Condition Calculation of ptime 17 Ryota Shiraishi 2019.12.23 Kuno-Yamanaka Group Year-End Presentation 2019

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