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analysis strategy Data/MC samples selection and tools MC studies a look at data plans

Status of the B  D sJ D (*) Analysis B  D sJ D (*) Working Group, Breco Meeting, October 15 th , 2003. analysis strategy Data/MC samples selection and tools MC studies a look at data plans. Analysis Strategy. look for decays B  D sJ + D (*)

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analysis strategy Data/MC samples selection and tools MC studies a look at data plans

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  1. Status of the B DsJ D(*) AnalysisB DsJ D(*)Working Group, Breco Meeting, October 15th, 2003 • analysis strategy • Data/MC samples • selection and tools • MC studies • a look at data • plans

  2. Analysis Strategy • look for decays B  DsJ+ D(*) • considerDs+(*) D(*) andDs+(*) D(*)p0andDs+(*) D(*)gfinal states(24 decays) • reconstruct D0  Kp, Kpp0, K3p, D+ Kpp, DS+  fp, K*0K(6 Ds+D0or 2 Ds+D-submodes/B) • reconstructD*0 D0p0, D0g, D*+  D0p+,D+p0 , D*s  Dsg • establish signals, measure BRs, perform angular analysis( DsJ quantum numbers) N.B.: Belle did not reconstruct the decays B  DsJ+ D* (onlyB  DsJ+ D)

  3. Signals Seen by BELLE EPS’03 status(for 123.7 106 BB events): • B  DsJ+ (2317) D,DsJ+ (2317) Dsp0 247 evts Br = (8.5+2.1-1.9±2.6)x10-4 • B  DsJ+ (2460) D,DsJ+ (2460) Ds*p0 • B  DsJ+ (2460) D,DsJ+ (2460) Dsg 247 evts BR = (8.5+2.1-1.9±2.6)x10-4 246 evts BR = (17.8+4.5-3.9±5.3)x10-4 409 evts BR = (6.7+1.3-1.2±2.0)x10-4

  4. BaBar Data Sample • Run 1 + Run 2 fully processed (Run 1 reprocessed in September for consistency) • production on skim BCMultiHad at CCin2p3 (Analysis13b, release 10 data reconstruction) • selection rate 0.2% (typically 400 events out of 200000 per job) • 1235 Ntuples, available both at In2p3 and SLAC. NBB = 87612796 +- 49568 (stat) +- 964605 (syst)

  5. Monte Carlo Samples • exclusive signal/background MC (SP4) done: • B  DsJ+ (2317) D(*)(m= 2317 MeV/c2; G = 1 MeV)DsJ+ (2317) Dsp0 • B  DsJ+ (2460) D(*) (m= 2457 MeV/c2; G = 1 MeV)DsJ+ (2460) Ds(*)p0 ; DsJ+ (2460) Dsg c) B  Ds(*)+ D(*) 2000-14000 events per Ds D decay submode, (i.e. fp x Kp, …); might need more.15 Ntuples, available at both IN2P3 and SLAC • generic B MC: not yet (wait for skimming?)

  6. Tools • BToDs2D skim:pre-selection; not used yet, but will be included in the next production round • BRecoNtuple with CTD2sDSequence: selection of the8x3B final states (tight D selection cuts); ntuple production • DsJDUser package:ntuple analysis a) code for histogram production b) (growing) collection of histogram analysis tools • DsJDUser HN forum: improve communication

  7. BToDs2D Skim (I) • Reconstructed 3 bodies decay: B0 D(*)Ds(*)p0 B0 D(*)Ds(*)g B+ D(*)0Ds(*) g B+ D(*)0Ds(*)g • 16 modes total, 8 for neutral and 8 for charged B • main code contained in: FilterTools/BToD2sDPath.tclEventTagTools/TagMakeBRecoToD2sD.{hh,cc}CompositionSequences/CompD2sDSequence.{hh,cc,tcl}

  8. BToDs2D Skim (II) • set corresponding tagbits BchToD0Dspi0 BchToDstar0Dspi0 BchToD0Dsstarpi0 BchToDstar0Dsstarpi0 BchToD0Dsgamma BchToDstar0Dsgamma BchToD0Dsstargamma BchToDstar0Dsstargamma B0ToDchDspi0 B0ToDstarDspi0 B0ToDchDsstarpi0 B0ToDstarDsstarpi0 B0ToDchDsgamma B0ToDstarDsgamma B0ToDchDsstargamma B0ToDstarDsstargamma • BToDs2D given by the logical or of them

  9. BToDs2D Skim (III) • particle lists: • charged tracks/neutrals • evtShapeTrkList GoodTracksVeryLoose • evtShapeNeuList GoodPhotonLoose • candidates • D0List : D0ChrgKHardDefault • DcList : DcToKPiPiDefault • DsList : DsMainDefault • Dstar0List : Dstar0ChrgKSemiHardDefault • DstarList : DstarChrgKDefault • DsstarList : DsstarMainLoose • pi0List : pi0DefaultMass • gamma : GoodPhotonDefault

  10. BToDs2D Skim (IV) • 4 new lists: • D0ChrgKHardDefault • D0ChrgKDefault withp*>1.3 GeV • Dstar0ChrgKSemiHardDefault • Dstar0ChrgKDefault withp*>1.0 GeV • DsMainDefault • merge ofDsToPhiPiDefault, DsToKsKDefault, DsToKstarKDefault • no DsToPhiRhoCDefault • DsstarMainLoose • use DsMainDefaultas input

  11. BToDs2D Skim (V) • estimated selection rates on-resonance data : 1.4% generic B0 : 9.4% generic B+ : 10.2% ccbar : 4.0% uds : 2.0% signal : ~50% For a summary, seehttp://www.slac.stanford.edu/BFROOT/www/Physics/Analysis/AWG/EHBDOC/DsJD/BToD2sDskimDOC.html http://www.slac.stanford.edu/BFROOT/www/Physics/Analysis/AWG/EHBDOC/skims/cm2-brecoskims.html

  12. CTD2sDSequence Selection • PID:NotaPion for D0 Kp, Ds fp, Ds K*0K Ktight for D0 K3p, Kpp0 andD+ Kpp • tracks: all p candidates are GTL • p0from D0: Eg>30MeV, LAT<0.8, mgg = [115,150]MeV • D mass window: ±20MeV (35MeV for D0  Kpp0) • g from D*  Dg and DsJDg:Eg>100MeV , veto g belonging to p0 with both photons having Eg>100MeV • D* Dm windows: ±4 MeV (D0p+), [130,170]MeV (D+p0), ±4 MeV (D0p0), ±30 MeV (D0g, Dsg) [basis of present ntuples, i.e. of everything shown below]

  13. DsJDUser package (I) growing collection of ntuple analysis tools for • histogram filling and book keeping • optimization of selection cuts and algorithms • determination of resolutions, efficiencies, ... • (automated) fitting, BR measurement, .... • angular analysis ... quite a bit of this is still missing, but some studies have been done   

  14. DsJDUser package (II) • Study of ntuples with filling of histograms at different levels • all candidates that pass the selections • best candidate(s) [more details later in this talk] • MC info • Set of scripts and kumacs to analyze the histograms How to find the right histogram?

  15. DsJDUser package (III) • 8 digits to individuate the histogram • 1 digit to distinguish between data, MC, best cand, sideband, etc. • 5 digit to identify the decay chain • 3 for the B mode • 2 for the D, Ds submodes • 2 digit to identify the histogram

  16. DsJDUser package (IV) • Decoding… • 1st digit: • 0=all candidates that pass selection • 1=best candidate(s) • 2=sideband • 4=MC Dss0 • 5=MC Dss1

  17. DsJDUser package (V) • 2-4 digit: B mode… • 2nd digit • 0=2 bodies • 1=p0 • 2=g 3rd digit 1=D+ 2=D*+ 3=D0 4=D*0  D0 p0 5=D*0  D0 g 4th digit 1=Ds+ 2=Ds*+ • 2 bodies used as a control sample

  18. DsJDUser package (VI) • 5-6 digits: D, Ds submodes • 4th digit: D, D0 • 0=inclusive • 1=Kp • 2=Kpp0 • 3=Kppp • 4=Kpp • 5th digit: Ds • 0=inclusive • 1=fp • 2=K*K

  19. DsJDUser package (VII) • 7-8 digits, histogram identifier (finally!) • some example: 01 mES, DE signal 02 DE, mESsignal 05 invariant mass m13vetoing 2 bodies decay and D resonances 29 invariant mass m23requiring MC truth match

  20. MC analysis: DE resolutionsDs0+ Dsp0 s(DE) is about 12MeV for Ds0+ Dsp0

  21. MC analysis: DE resolutions s(DE) is about 12MeV for Ds1+ Ds*p0

  22. MC analysis: DE resolutions for Ds1+ Dsg s(DE) is about 18MeV (Asymetric tail on negative DE values)

  23. MC analysis: DsJ mass resolutions Ds0+ Dsp0 s(m(Dsp0)) is about 8MeV/c2

  24. MC analysis: DsJ mass resolutions Ds1+ Ds*p0 s(m(Ds*p0)) is about 8MeV/c2

  25. MC analysis: DsJ mass resolutions Ds1+ Dsg s(m(Dsg)) is about 14MeV/c2

  26. B candidates multiplicity studies (I) Investigated different best selection criteria • Selected 1 best candidate per mode or 1 best candidate per event (between all modes) • used different discriminating variables best mES (nearest to 5.279) best DE (nearest to 0. for MC and 5 MeV for data) best c2 (nearest to 1.)

  27. B candidates multiplicity studies (II) • the c2 is computed using the difference of the mass of D and Ds in respect to their nominal mean and sigma value • to distinguish between modes with a p0 or a g the DE value is used for candidates with the same c2 • this criteria is still under study, hoping that could be improved (use of a LH?)

  28. B candidates multiplicity studies (III) • The more promising criteria seems simply to be the best DE (1 candidate per mode) • here some results extracted from generated tables: • The whole tables (for 2s and 3s cut, for 1 candidate per mode or 1 candidate per event) are in this location: http://www.slac.stanford.edu/~grancagn/internal/DsJD/

  29. B candidates multiplicity studies (IV) • Cross-feed under study, yet • Looking into the possibility to use the truth tree instead of the MC truth match • requiring that the mode of the best candidate is the actual mode generated • evaluate from the invariant mass m23 the cross-feed between different modes

  30. MC analysis: efficiency calculations With the best DE selection (1 cand per mode) The rest of the table here: http://www.slac.stanford.edu/~grancagn/internal/DsJD/de-a-2s.txt

  31. Background estimates in the DsJ signal region (from data itself) • To compute the background in the DsJ mass region we average the number of events observed in the data into two symetric (6s wide) sidebands around the DsJ mass region (-4 to –10 s and 4 to 10s ) Values currently used • Ds1+ Dsg: s=18 m=2460 • Ds1+ Ds*p0 : s=12 m=2460 • Ds0+ Dsp0:s=12 m= 2317

  32. Plans for cuts optimization We will test all different set of cuts (D selection, deltaE, Event shape variables, kinematic cuts) and compute S/S+B for each set of cuts, with S from signal montecarlo and B from the data itself (sidebands of the m(Dsg/p0) spectrum)

  33. Discriminating variables: m(Dg) For B  DDsJ+ (DsJ+ Dsg) M(Dsg) is a good discriminating variable Red is background Blue is signal MC The curve is the fraction of events cut by M(Dsg) > M(Dsg) cut Optimal cut M(Dsg) > 2.3 GeV/c2 (D) M(Dsg) > 2.4 GeV/c2 (D*)

  34. Discriminating variables: p(g) For B  DDsJ+ (DsJ+ Dsg) • p(g) is also a good discriminating variable • Correlation with M(Dsg) need to be studied (no big improvement in purities when both cuts applied) Red is background Blue is signal MC Curve: fraction of events cut by p(g) > p(g) cut Optimal cut M(Dsg) > 0.3 GeV/c

  35. Discriminating variables: p*(D) • Beause we have a 2 body decay, the signal p*(D) is restricted to a narrow range • Discriminating power vs bkg has to be investigated

  36. M(D(*)p0) for Ds0+ Dsp0 andDs1+ Ds*p0

  37. p(p0) for Ds0+ Dsp0 andDs1+ Ds*p0

  38. P*(D) in B  D(*)Ds0+ and B  D(*)Ds1+ Ds0+ Dsp0 andDs1+ Ds*p0

  39. Default analysis cuts • Use a 2 sigma cut on D masses • Use a 2 sigma cut on DE • Cut tight on D selection (except for D*+): c2 vtx, dalitz weight, Ktight • Plot m(Dg/p0) for –2s< DE <2s and mES>5.27 • Look also at DE for events with m(Dg/p0) in the DsJ mass region

  40. Expected signal and background with the current selection assuming Br(B DsJD)xBr(DsJ Dp0,g)=10-3 Mode s b b [mDg cut] s /S+B s /S+B [mDg cut] D+ Ds- pi0 9.2 50.0 14.5 1.19 1.88 D+ Ds*-pi0 3.5 18.5 6.0 0.75 1.14 D*+Ds- pi0 8.5 43.0 14.5 1.19 1.78 D*+Ds*-pi0 3.4 8.0 2.0 1.00 1.45 D0 Ds- pi0 14.6 235.0 71.0 0.92 1.58 D0 Ds*-pi0 4.9 83.5 24.0 0.52 0.91 D*0Ds- pi0 4.9 74.0 25.0 0.55 0.90 D*0Ds*-pi0 1.6 16.5 6.5 0.39 0.58 D+ Ds- gamma 15.9 21.0 3.5 2.61 3.60 D*+Ds- gamma 14.0 19.5 4.0 2.41 3.30 D0 Ds- gamma 23.2 119.5 44.0 1.94 2.83 D*0Ds- gamma 7.2 40.5 16.5 1.04 1.47

  41. A look at the data with the current (unoptimized) default cuts

  42. 2 body decays can be used as a calibration sample

  43. 2 body decays • We plan to compute the branching fractions of all decays B Ds(*)D(*) to test that we understand well selection efficiencies

  44. M(Dsg) for D(*)Dsg events in the signal box: all candidates vs best dE candidate (1 best candidate/B mode allowed)

  45. M(Dsg) for D(*)Dsg events in the signal box:same as previous but with cut m(D (*)g)>2.3(2.4)GeV/c2

  46. DE of D(*)Dsg events with m(D (*)g)>2.3(2.4)GeV/c2

  47. M(Dsg) per mode (Best candidate) m(D (*)g)>2.3(2.4)GeV/c2

  48. M(Ds*p0) for D(*)Ds*p0 events in the signal box and cut m(D (*)p0)>2.3(2.4)GeV/c2

  49. M(Dsp0) for D(*)Dsp0 events in the signal box and cut m(D (*)p0)>2.3(2.4)GeV/c2

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