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Update of the Fiducial calibration study in 2km WC detector

Update of the Fiducial calibration study in 2km WC detector. 2km pre-meeting 7 July, 2006 G. Mitsuka T2K-2km working group. Contents. Motivation Fiducial PMT geometry Criteria to identify the vertex in/out FV Fiducial PMT simulation in 2KM Water Cherenkov detector Summary

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Update of the Fiducial calibration study in 2km WC detector

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  1. Update of the Fiducial calibration study in 2km WC detector 2km pre-meeting7 July, 2006 G. Mitsuka T2K-2km working group

  2. Contents • Motivation • Fiducial PMT geometry • Criteria to identify the vertex in/out FV • Fiducial PMT simulation in 2KM Water Cherenkov detector • Summary • (From now on, Fiducial PMT is shortened to FVPMT)

  3. Motivation • In the WC detector, fiducial volume is expected as one of the large systematic errors (difficult to calibrate fiducial volume) • Need to implement new fiducial calibration system An idea of FV calibration • Set the array of PMTs(FVPMT) around FV boundary • Vertex is identified as in/out by FVPMT signals In order to check whether FV calibration will works well or not • Performance test of the candidate PMT for FVPMT(2inch PMT : Hamamatsu R9869) is carried out in the 1kton detector  R9869 fulfills requirements • Estimate the efficiency of FV calibration and error by using 2km simulation with FVPMTs Update

  4. How to set the array of FVPMT • Requirements • Avoid the effect of shadow of FVPMT • Identify the FV boundary with high resolution • Solutions • 2inch PMTs are set with a distance of 50cm • FVPMT is set on the FV boundary R9869 with water proof

  5. FVPMT geometry Z direction R direction (Top,Bottom) FV boundary IFPMT 50cm 50cm OFPMT Fiducialvolume Inward-Facing PMT = IFPMTOutward-Facing PMT = OFPMT Front & End-cap 104PMTs + Barrel 360PMTs = Total 464PMTs

  6. Criteria for in/out identification(1) FVout event L • Vertex is identified as FVin/out by FVPMT hits FVout requires OFPMT hits FVin requires IFPMT hits • Hit due to scattering or reflection is cut by PMT-facing direction and m direction OFPMT Hit FVin event OFPMT No-hit FV boundary IFPMT Hit

  7. Estimation of efficiency and error • Estimate the FV calibration efficiency and error by using 2km WC simulation with FVPMTs • Neutrino events are simulated with taking account of the neutrino flux at 2km position • These events are independently reconstructed of FVPMT by 2km official reconstruction software • Sample events are 1-ring m-like event (~170000)

  8. Event reconstruction with FVPMT Reconstruction performance seems to be good even with FVPMT

  9. FV identification efficiency (Z dir) Efficiency = • ID as FVin(ID) • ID as FVout(ID) • X,Y,Z is fitted position • Events in R(=sqrt(X2+Y2)) < 150cm are selected  except for less efficient region (FV barrel edge) • Efficiency curve shows sharp shift at FV boundary

  10. FV identification efficiency (R dir) • Events in -300<Z<100cm are selected • Efficiency curve shows sharp shift at FV boundary • ID as FVin(ID) • ID as FVout(ID) Efficiency summary

  11. Additional study • FV calibration efficiency and error with 464’s FVPMT were estimated  predict that FV calibration works well • For the cost reason, the number of FVPMTs is required to be much small  search for the alternative configuration • Assuming the half number of FVPMTs, check the efficiency and error

  12. How to decrease FVPMT • FVPMTs set on the endcap and frontcap are very important to calibrate the FV edge, because m of CCQE interaction are almost forward scattered • Try to remove barrel FVPMTs ( next page) • zbs and ntuple files are tentatively same as full FVPMT version, skip barrel FVPMT when reading ntuple

  13. What FVPMT is skipped • used PMT • skipped PMT Type 2 Type 1 Y(cm) Y(cm) Z(cm) Z(cm) Full464 – skip240 = 224 PMTs used 464 – 210 = 254 PMTs used

  14. Calibration efficiency (Zdir:(x2+y2)1/2<150cm) • FVin(ID) original / modified • FVout(ID) original / modified Type 2 Type 1

  15. Calibration efficiency(Rdir:-300<z<100cm) • FVin(ID) original / modified • FVout(ID) original / modified Type 2 Type 1 Same level inside FV, worse outside FV Worse efficiency in/out FV

  16. Efficiency as a function of En FV out (full)FV in (full)FV out (type2)FV in (type2) Efficiency 80% of all events En(MeV)

  17. Efficiency summary • Black : Full FVPMT • Blue : type1 • Red : type2 • type2 keeps 81% efficiency inside FV, although type1 is 78% • According to the efficiency curve, type2 could be realistic (unit is %)

  18. Shadow effects of FVPMT (1) (w/o FVPMT is normalized by the number of events in FV) Ring-counting PID • w/o FVPMT • w/ FVPMT • w/o FVPMT • w/ FVPMT Events Events Excess appeared, but not affect Single-ring Likelihood Likelihood According to the comparison of Ring-counting and PID, FVPMT doesn’t seem to affect 1-ring m-like events

  19. Shadow effects of FVPMT (2) Hatched type requires identification as FVin Efficiency of QE,Non-QE and NC in 1-ring m-like events (unit is %) Efficiency of miss-PID in 1-ring m-like QE events (unit is %)

  20. Error of efficiency e : Efficiency of FV identification Real data MC Table of errors of MC efficiency In all types, error is smaller than 1%

  21. Summary • Checked the efficiency and error by using fitted 2km MC  predict FV calibration works well • Vertex of 1-ring m-like events are correctly identified with efficiency > 80% • Error of identification efficiency is less than 0.5% • Searched for alternative FVPMT setup  Even if the half number of FVPMTs, keep the efficiency of 80%

  22. Backup ….

  23. miss-identified event • FVin events miss-identified as FVout • Outwrd-going event whose vertex is near from FV boundary OFPMT hit around exit point • LowE event whose vertex is almost center of FV  Neither PMT hits • FVout events miss-identified as FVin • Inward-going event whose vertex is near from FV boundary  IFPMT hits, but OFPMT no-hit

  24. Slope of Efficiency curve in FV q1 q1 + q2 = p/2q1 >q2 q2 OFPMT hits due to scattering or reflection  identified as FVout event cos(q2) is generally large  Hit is ignored by angle cutcos(q2) is generally small  Hit is taken into account in the calibration criteria Z

  25. Systematic error of FV DATA MC FV syst. error

  26. Introduction • Reconstruction is applied for generated MC~170000events(shown at last meeting) • FV identification criteria is improved • Estimate the error of FV calibration

  27. Summary • Improved criteria is applied for fitted MC • Events are correctly identified with efficiency > 80% • Error of identification efficiency is 0.7% • In preparation for the commitment of improved routines • Studying the configuration using lower number of PMTs as keeping efficiency and error

  28. Summary • Checked the efficiency and error by assuming the half number of FVPMTs • type2 keeps 81% efficiency in/out FV • Error of efficiency is less than 0.6% in all geometries • type2 could be realistic geometry

  29. Error of Identification efficiency Systematic error of FV • Error of identification efficiency • Calibration system (Q:+/-20%,Nhit:+/-10%)  0.07% • Neutrino interaction (nonQE:+/-20%,NC: +/-30%)  0.33% • Reconstruction (PID:+/-4%,RingCounting:+/-5%)  0.33% • Energy scale (+/-2%)  0.11% NinID : #events in FV e : Efficiency of FV identification Real data MC Error of efficiency = 0.48%

  30. Error of efficiency NinID : #events in FV e : Efficiency of FV identification Real data MC Table of errors of MC efficiency

  31. Criteria for in/out identification(1) Fitted vertex Cross point VTX-Cross point = LVC FVout event FVout event L OFPMT Hits IFPMT OFPMT Hit L- LVC 0 FVin event IFPMT FVin event Hits OFPMT No-hit FV boundary IFPMT Hit L- LVC 0 If OFPMT hit (L-Lvc < 0) ID as FVoutelse if IFPMT hit != 0 ID as FVinelse(i.e. No-IFPMT hit)  ID as FVout

  32. Criteria for in/out identification(2)Merit of FVPMT facing both sides Backward extrapolated cross point exists&&VTX-Corss(forward) > VTX-Cross(Backward)  Hits around backward cross point are taken into account in order to correct miss-fitted event miss-fittedFVout event OFPMT Hit • miss-fitted FVout eventTrue vertex(★) is FVoutFitted vertex(●) is FV in OFPMT hit can correct FVin to FVout • miss-fitted FVin event • True vertex(★) is FVinFitted vertex(●) is FVout OFPMT hit can correct FVin to FVout miss-fittedFVin event IFPMT Hit

  33. Criteria for in/out identification(3)Hits by scattering or reflection OFPMT hits due to the scattering or reflection  Identified as FVout by these OFPMT hits In order to avoid such miss-ID cosq(PMT dir~particle dir) > 0.8 ignore hit q OFPMT Hit

  34. Ring counting likelihood (check) • Full • Type1 • Type2 Efficiency dlfct

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