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σ E γ comparison using. Woochun Park Univ of South Carolina Feb 26, 2005 @EMC. Photon energy resolution (BaBar Note# 583). σ γ has more than an estimate of photon energy resolution since it includes track momentum uncertainty. We subtract this effect in quadrature after estimating:.
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σEγcomparison using Woochun Park Univ of South Carolina Feb 26, 2005 @EMC
Photon energy resolution (BaBar Note# 583) • σγhas more than an estimate of photon energy resolution since it includes track momentum uncertainty. • We subtract this effect in quadrature after estimating: • We are not able to distinguish Xc1 and Xc2, so • ΔM (Mχci- MJ/ψ) < 0.447: MPDGχc =MPDGxc1 else MPDGχc =MPDGxc2. (Need to study about σEγdependence on χci . More ideas in page 8-9.)
Selecting samples • Following BAD#139, “Inclusive charmonium state analysis in B” • Analysis 23 (14.5.5) SP5 MC • Jpsitoll skim:AllEvents: 2.25%; B0B0b: 4.78%;B+B-: 5.36%; ccb: 5.67% • For J/ψ (only for μμ today): • With radiation recovery. Selectors are not decided yet. • One “Tight” muon and one “Very Tight” muon (cut opt. in next page). • Geometric constraint on vertex. • p*J/ψ< 2.0 GeV/c, Meeis not decided. and 3.06 < Mμμ < 3.13 GeV. • For χc1,2: • GoodPhotonLoose List • Zernike(4,2) moment < 0.15 • Reject photons from π0candidate with no constained mass b/w 0.117 and 0.147, Emin = 30MeV, Lat < 0.8 • 0.12 < Eγ< 1.0 GeV • To suppress hadronic split-offs, photon should be at least 9 degree from any charged tracks. • p* < 1.7 GeV/c
J/ψ→μμOptimization • For each muNN cuts, estimate signal and background with all cuts applied in signal window, 3.06 < Mμμ < 3.13 GeV. Run1 data used. • (muNNTight, muNNVeryTight) is selected based upon S2/B.
Using J/ψ→μμ(Run1) Off-resonance(error) vs cont MC(line) Offdata = 56±7.5 (2.35 fb-1) contMC = 50.1±2.7 Life becomes simple if data is like this!!! Ratio = 1.12 ± 0.16 On-resonance(error) vs MC(line) Ondata = 7692±88(19.5 fb-1) BBMC+scaled Offdata = 5892±77 Ratio = 1.31 ± 0.02 • Muon efficiency correction would make them more inconsistent. • There is no clear peak from continuum BG. Easy to model BG shape. • Shapes are consistent b/w OnPeak & BBMC.
Emeas MC Ecalc Etrue DATA For all Emeas spectrum (50MeV binnings will be in next page)
Divide Emeas by 50MeV from 200MeV and 800MeV. Fit each plot with Gaussian+Pol1. • Subtract track momentum uncertainty in quadrature. BB MC Next page DATA
DATA DATA MC MC RESULT • Data and MC looks consistent except [400, 450] MeV in Emeas. • More statistics come from J/ψ→ee. • Ntuple generations are very smooth. Higher priority on batch queue usage will definitely help me to get faster results. RUN2 D*->D0 gamma Emeas [400, 450] Emeas
σEγdependence on Mχc1,2 • Assuming that we mis-assign Xc1 mass to Xc2 (Xc2 decay width (2.11±0.16 MeV) is about twice bigger than Xc1 (0.91±0.13 MeV). ) • ΔMXc = -46MeV (MXc1 = 3510.59 MeV :MXc2 = 3556.26 MeV) • δEcalc~ -2 (ΔMXc) MXc ≈ -0.325 GeV2 • MXcPDG 2 - MψPDG 2 ≈ 2.85 GeV2 • δEcalc ≈ -0.11 Ecalc (mis-assignment causes 11% error in Ecalc per event.) • δσEγ= -0.11/ Ecalc ≈ -25% per event when Ecalc = 0.44 GeV • If we are confused in DATA as much as MC, it’s just fine on the purpose of measuring relative photon energy resolution. • We need to estimate how much different mis-assignment rate between MC and DATA. • Maximum likelihood fit on σEγand R(Yxc1/Yxc2)could be one alternative way. R measurement could be a physics topic, “inclusive Xc braching ratio analysis”.
eMicroVeryTight and eMicroTight w/o radiation recovery electron. muMicroTight and muMicroLoose 3.05 < Mee< 3.12 and 3.07 < Mμμ < 3.12 GeV. Fit with Gaussian + Pol2 Very preliminary Study on R (Run1) BB MC Signal MC OnData R=2.46 ± 0.07(sigMC) R=4.06 ± 0.75 (BB MC) R=11.6 ± 4.7(OnPeak) PDG R= 4.54 ± 1.59
DATA DATA MC MC Δ(σEγ) Δ(δσEγ) X-axis is Ecalc (page 8 hasEmeas x-axis) J/ψ→μμ Run1 σEγ/Ecalc More presentation is advised at EMC software/calibration meeting tomorrow. δσEγ /Ecalc
How to include μ efficiency correction?? With 2 month-old in BaBar, it’s very difficult to find. I tried ntpBlockContents set "mu : Momentum CMMomentum MCIdx PIDWeight(muNNTight)“ It only gives me 1.0 weight and 0 status all the time which doesn’t see to reasonable. Then, I include pidCfg_mode tweak * and pidCfg_mode weight * But, my BtaTupleApp doesn’t recognize pidCfg_mode command. To-do • Move on to Run4 to take advantage of the best statistics dataset. • Simulate combinatoric background. • study about σEγdependence on χci • μ efficiency correction to compare MC with DATA. Question