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Electron PID with real data

Electron PID with real data. V.Egorychev ITEP. February, 2011. 2 e. 2 e. c. c. Introduction.

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Electron PID with real data

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  1. Electron PID with real data V.Egorychev ITEP February, 2011

  2. 2 e 2 e c c Introduction • The particle identification algorithm is based on evaluating the difference between the likelihood distributions of the signal (electron/positron from gamma conversion) and background hypotheses (hadrons from D0 K  ) • Electron ID - for each of the sub-detectors reference 2-dim histograms which correlate the measurement ( , Eprs, Ehcal ) in the sub-detectors with momentum (p) are constructed • is constructed as a 2 of a global matching procedure, which includes the balance of track momentum and the energy of the charged cluster in the Ecal and the matching between the corrected barycenter position of the cluster with extrapolated track impact point • For signal - Stripping12 (MagUp ) within Jpsi2MuMuLine was used to avoid any influence from trigger • For background – Stripping11 (MagUp) D02HHForPromptCharm line was used

  3. Electrons from gamma conversion Just for illustration energy/momentum ratio M(e+e-), MeV/c2 For the analysis Downstrem track candidates with M(e+e-) < 50 MeV/c2 were selected Purity is on 0.1% level

  4. Hadrons from D0 decays Just for illustration D0→ K π No “signal” behavior M(K), MeV/c2 energy/momentum ratio For the analysis track candidates within +- 25 MeV/c2 around D0 position were selected Purity is better than ~0.5% level

  5. CALO PIDs based on RD as the first approximation we assumed that the distributions for Long tracks and Downstream tracks are identical Mis_ID rate ~4% for electron eff 90% MC sample – Mis_ID rate for same strategy was 4-5% Combined Calo Delta Log –Likelihood without Brem fake rate vs efficiency Downstream tracks only

  6. CALO PIDs based on RD (by individual detectors) Mis-ID rate for εelectron ~ 90% NOTE! For RD we use DD combinations, for MC we used LL track combinations The performance for DD combination in MC was worse than for LL tracks Big improvement for electron ID with PRS (thanks to Dima) But I still look forward to see the tuning for variables involved in the CALO PIDs and hope to see those studies before my retirement we have acceptable agreement with MC prediction based on Long tracks

  7. Performance (strategy) • to check the performance of the CALO PID with new reference histograms based on RD the part of MB sample (Stripping12) and part of the stripped D0 sample (MagnDown) were re-done • performance PIDe: • signal efficiency by electron/positron from gamma conversion: • common cuts: pT > 0.1 GeV/c, VZe+e- > 900 mm, track 2/dof < 4 • in each momentum bin e/p ratio was fitted to calculate the number of electron candidates (Gauss+Polynomial) • misID from D0 K π (MagnDown)

  8. Eff/misID rate vs momentum with CALO DLLE (Ecal+Hcal+Prs) p, GeV/c p, GeV/c Efficiency for electron identification and misidentification rate, after requiring Delta log-likelihood (Ecal+Hcal+Prs) > cut_value as a function of momentum Electron efficiency for p < 5 GeV/c is lower that for higher p bins for electrons from gamma conversion the average iden. eff in the complete CALO system without Brem info is higher 90% for a misidentification rate of ~2% after requiring Δlog L > 3

  9. Performance DiElectron sample (Stripping12, MagUp, ~80% of staistics) was privately reconstructed with new PIDs histograms PID_CALO > 4.5 pTelectron > 3 GeV/c MIPS_dielectron < 4 2vertex < 9 CALO PID only without RICH N (1S) = 342  54 N (2S) + N (3S) = 206  44 N (2S) / (N (2S) + N (3S) )= 0.54  0.35 M(e+e-), GeV/c2

  10. Summary • reference histograms for CALO PIDs were produced based on  conversion and D0 samples • with electron identification efficiency of 90% the mis. identification rate is 4% (for downstream tracks). Good agreement with MC expectation. • for downstream electrons from gamma conversion the average identification eff. in the complete calorimeter system is ~90% for mis. identification rate of 2% after requiring Δlog L > 3 • it seems that we are at the limit of the method and, probably, further improvement could be done with J/  e+e- sample: • purity… • selection since RICH PID was used for stripping…

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