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Kali Calo

Kali Calo. Vanya BELYAEV. Iterative p 0 calibration. The “standard” procedure HERA-B Robust (as soon as p 0 peak is vizible ) “ Millipede-like ” algorithms are fragile Rely only on “ standard ” reconstruction technique No “ dedicated ” reconstruction

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Kali Calo

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  1. KaliCalo Vanya BELYAEV

  2. Iterative p0 calibration • The “standard” procedure • HERA-B • Robust (as soon as p0 peak is vizible) • “Millipede-like” algorithms are fragile • Rely only on “standard” reconstruction technique • No “dedicated” reconstruction • Can be done “track-independent” • Requires only limited information • Can be rather fast ( “on-line” mode) Vanya Belyaev (Nikhef & ITEP )

  3. Rely on “multiplicative” calibration • 0 ~ Eprs<<Eecal, • the best contribution from Eseed ~ Eecal • simultaneous Ecal/Prs calibration is difficult • Needed? Sensitivity to Prs is not large • For physics: Eprs > E0, for calibration Eprs < E1 • Contradiction? Eprs > E0 : small background + large statistics Eprs < E1 : large background + small statistics Vanya Belyaev (Nikhef & ITEP )

  4. Eprs Eprs > E0 : small background + large statistics - fast convergency to “wrong” constants Eprs < E1 : large background + small statistics - slower convergency to “correct” constants Combine! • Few iterations with Eprs > E0 • Then switch to Eprs < E1 • (Intermediate scenario ? ) g1: Eprs < E1 g2: Eprs > E0 Vanya Belyaev (Nikhef & ITEP )

  5. Data Flow for Kali-p0 (I) ROOT NTuple/TTree DST or DAQ Kali-p0 Job fmDST Vanya Belyaev (Nikhef & ITEP )

  6. Data Flow for Kali-p0 (II) 2k+(4-5): 3-5 iterations are OK 2k+9 : 2-3 iterations are OK Make histos using the current estimate for calibration constants Fit histograms Get corrections for calibration constants Iterate up to convergency produce the final set of calibration constants ROOT NTuple/TTree Set of Calibration constrants CondDB (?) (optional) Vanya Belyaev (Nikhef & ITEP )

  7. Data Flow for Kali-p0 (III) ROOT NTuple/TTree Kali-p0 Job fmDST Set of Calibration constrants CondDB (?) (optional) The secondary iterations Vanya Belyaev (Nikhef & ITEP )

  8. Kali-p0 Job • Regular Gaudi-based job • Actually “stripped-down” version of DaVinci • (optionally) apply constants to Ecal digits • Calibrate/re-calibrate/mis-calibrate • (re-recontruct) Calorimeter objects Clusters, Hypos, Neutral ProtoParticles, Photons • LoKi-based algorithm that acts on LHCb::Particles • StdLooseAllPhotons • Find good p0→gg candidates with loose cuts • Fill n-tuple • (optionally) Destroy TES! • Write femto-DST Vanya Belyaev (Nikhef & ITEP )

  9. Kali-p0: fmDST Easy to (mis)Calibrate! “Natural” input for Kali Job • Write only Spd/Prs/Ecal/Hcal digits that make contributions into “good” photons from “good” p0-candidates • Write in TES-format: Raw/Ecal/Digits Raw/Spd/Digits Raw/Prs/Digits Raw/Hcal/Digits • 500k minimum bias MC09 events on input: • 380k evens with “good” p0 : 150MB of fmDST • ~ 330 bytes/event, mainly due to Gaudi overhead • ~ 300GB for 109 available MC09 statistics Vanya Belyaev (Nikhef & ITEP )

  10. Kali-p0: Calo(re-)Reco • Defines the rules (using only the standard stuff) for Calo (re)-reconstruction • Mainly definition of neutrality criteria: Use Tracks (only for DST of DAQ/farm input Use Spd Use both (.OR. mode) ( DST/DAQ/farm) Use None (all clusters are “neutral”) Clearly the definition for the first pass is the most important for the subsequent processing Vanya Belyaev (Nikhef & ITEP )

  11. Kali-p0: NTuple/TTree $LHCBHOME/group/calo/ecal/vol10/Pi0/KaliPi0_Tuples.root • Very simple structure: p0 : mass, energy, ET g1,g2 : energy, ET, Eprs, Espd, seed-cell-id • 13 variables: more compression is possible (x2?) • Pre-cuts (rather loose to allow the refinement): m(p0) < 250 MeV/c2, ET(p0) > 800 MeV • Photons are ordered according to Eprs: • Easier to apply Eprs cuts & choose the proper photon • 500k minimum bias events: 30 MB • 30 GB for available 109 MC09 statistics Vanya Belyaev (Nikhef & ITEP )

  12. Kali-p0: analysis utilities translate from calib.f and calibr.kumac Choice Use Python & PyROOT • Project histograms with constants: • C++ (T)Projector-based : ../root/Kali_Pi0.C • Not flexible enough  But it works… • Python’(TPy)Selector meets some problems • Fit histograms: KaliCalo/Pi0HistoFit.py • fitPi0Histo: • primitive: gaussian + 3rd order polynom • can (& should!) be improved e..g using Albert’s trick • Initial values, background shape, re-iterate, fir stability & fit-quality: We need to fit in automatic regime 6k histograms! • Steering: not ready yet.. • Monday afternoon: news from Dasha: steering is OK Vanya Belyaev (Nikhef & ITEP )

  13. Kali-p0: current status • Up to last Thursday was OK with lhcb3 nightly • CVS HEAD • C++ Selector need to be fixed • Python Selector to be fixed • p0-fit to be improved • Analysis steering from Dasha to be integrated • But for all components we have something working! • “Ready” for full scale test with GRID Vanya Belyaev (Nikhef & ITEP )

  14. Kali-p0: Few plots all min(Eprs) > 10 MeV min(Eprs )< 10 MeV, max(Eprs)> 10 MeV max(Eprs) < 10 MeV Vanya Belyaev (Nikhef & ITEP )

  15. Kali-p0 steering from Dasha Vanya Belyaev (Nikhef & ITEP )

  16. Kali-p0 steering from Dasha Vanya Belyaev (Nikhef & ITEP )

  17. Short-term plans: • Run Kali-p0 (using GRID) for all available 109 events • Get the estimate of Ecal calibration • #events? • Run various mis-calibration scenarios on fmDST • robust? • Refine p0 selection • Define the optimal treatment of Eprs cuts for different steps • Define the working scenario for “off-line” calibration • Optionally: • refine Calo(re-)Recosettings, next slide Vanya Belyaev (Nikhef & ITEP )

  18. Medium –term plans • (Complete with short-term plans) • Make estimate of CPU in ‘on-line’-like scenario • Currently totally dominated by technical overhead: read/unpack (2000/40000) • Find Calo(re-)Recoconfiguration acceptable for “on-line” settings ”UseTracks” ? • Special Kali-p0-runs for EFF • possibly with slightly prescaled input event rate? • Is it possible to run Kali at f >> 2kHz ? • It is possible to run Kali at O(1MHz) • New data instead of secondary iterations!! • Ask for some Kali-p0-FEST at EFF Vanya Belyaev (Nikhef & ITEP )

  19. “Kali-p0Reference manual” $KALICALOROOT/python/KaliCalo/KaliPi0.py gaudirun.py KaliPi0.py DATA.py python KaliPi0.py ./KaliPi0.py from Gaudi.Configuration import * from Configurables import KaliPi0Conf KaliPi0Conf( FirstPass = True , UseTracks = True , UseSpd = False , FemtoDst = ‘output.fmDST’ ) Vanya Belyaev (Nikhef & ITEP )

  20. Kali-p0: Summary • (Some) progress in Kali(-p0) framework • Resurrect 2k+(4/5) code • “Ready” for full-scale test with 109 events • Few tiny (pure technical) aspects to be solved • GRID is essential • fmDST are very useful My dream: on-lineKali-p0 Vanya Belyaev (Nikhef & ITEP )

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