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Ecal Calibration 2k+10

Ecal Calibration 2k+10. Dasha Savrina, Victor Egorychev & Vanya Belyaev. Kali. Use 80M of real data 2k+10 First pass of Kali run (prepare fmDST ) using LHCBCOND.db_new by Olivier with a ll known corrections and coefficients

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Ecal Calibration 2k+10

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  1. Ecal Calibration 2k+10 Dasha Savrina, Victor Egorychev & Vanya Belyaev

  2. Kali • Use 80M of real data 2k+10 • First pass of Kali run (prepare fmDST) using • LHCBCOND.db_newby Olivier with all known corrections and coefficients • CVS HEAD of Calo/CaloReco + Corrections.py from Olivier • Prs+Ecalcorrections are applied “by-hand” at the second run by Kali • takes less than 15 minutes to get 85-90% jobs from Grid (A bit longer during working hours) • And few hours to get the remaining 10-15% Vanya Belyaev

  3. Starting point After 9 primary iterations l= (98.98±5.91)% Vanya Belyaev

  4. Re-reconstruct After 9 primary iterations l*= (99.49±2.19)% l= (98.51±6.81)% Vanya Belyaev

  5. Inner Zone Vanya Belyaev

  6. Middle Zone Vanya Belyaev

  7. Outer Zone Vanya Belyaev

  8. All Zones Vanya Belyaev

  9. One more re-reconstruction ? ”>2% unstable” • Outer 6,63 • Outer 20,50 • Outer 29,63 • Outer 31,1 • Outer 31,6 • Outer 31,11 • Outer 31,56 • Outer 32,3 • Outer 33,63 • Outer 51,63 • Outer 57,1 • Middle 31,59 • Inner 25,32 • Inner 35,21 l*= (99.98±0.50)% ”>5% unstable” • Outer 31,11 • Inner 35,21 917 cells > 0.5% 231 cells > 1% 14 cells > 3% 3 cells > 5% ”Low-occupancy” cells: • Outer. 57,63 • Outer, 55, 9 • Middle 44,51 ”Bad” cells: • Outer. 31,59 • Outer,18,63 • Outer, 26,63 • Outer, 24,1 • Outer,32,0 • Outer,57,63 • Middle, 29,0 ”No-fit” cells: • Outer. 20,50 • Outer, 31,58 • Outer, 32,0 • Middle , 1, 27 Vanya Belyaev

  10. import KaliCalo.Kali import KaliCalo.ZipShelve as ZipShelve dbase_name = “/afs/cern.ch/user/i/ibelyaev/cmtuser/caf_r3/RealData_II_zdb.gz” dbase= ZipShelve.open(dbase_name,’r’) dbase.ls() lambdas = dbase[‘Ecal_Second_Iteration’] Vanya Belyaev

  11. Compare with Albert&Ricardo More cells • Outer 9,34 • Outer 55, 9 • Outer 46,46 • Outer 8, 12 • Outer 51,55 • Middle 29,1 • Middle 40,14 • Middle 44, 51 • Middle 19,27 • Inner 26,23 • Inner 32,40 • Inner 45,19 • 2.5% agreements • 178 cells have >10% difference • 124 in outer • in general for ‘outermost parts’ • Few rows 6, 57, … • 16 in middle Vanya Belyaev

  12. Correlation plot Vanya Belyaev

  13. Ratio Vanya Belyaev

  14. (technical) numbers It scales nicely with number of of cores • fmDST reprocessing: • O(50) Grid jobs, less than 10 minutes each • NTuple processing • 1 primary iteration O(2 hours) @ CAF, 7 cores • Histo projection: O(¾hour) • Histo fitting: O(1¼hour) • 1 “long night” for ~8-9 iterations • The whole cycle around 2-3 days … Vanya Belyaev

  15. Proposal: It has been discussed with Computer Project Leader and Operation Coordinator: they have no immediate objections • Run Kali for O(2×108) events ~O(1 week) before each reprocessing • Use available DST for (all?) stripping streams • Computer model guarantees their presence on dist for all Tear1(&CERN) centers • “Group” –analysis jobs • The obtained corrections (after proper validation by Olivier) to be used in subsequent reprocessing Vanya Belyaev

  16. Summary in short: she works Vanya Belyaev

  17. Summary Monte Carlo suggests: ~2% Agreement with Albert& Ricardo: ~2.5% Next steps: Use 2-3×108 re-reconstructed data Note in preparation • Ecal calibration constants have been obtained from 2k+10 data • “Iteration convergency/stability”: rms = 0.3% • Clear improvement in p0 mass resolution has been observed • Note: p0 width is not a parameter for calibration! • The mass of p0 is fine Vanya Belyaev

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