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First look at  -jet Samples using BDT e-ID Algorithm Hai-Jun Yang University of Michigan (with X. Li and B. Zhou) ATLAS egamma Meeting March 9, 2009.

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Presentation on theme: "First look at  -jet Samples using BDT e-ID Algorithm Hai-Jun Yang University of Michigan (with X. Li and B. Zhou) ATLAS egamma Meeting March 9, 2009."— Presentation transcript:

1 First look at  -jet Samples using BDT e-ID Algorithm Hai-Jun Yang University of Michigan (with X. Li and B. Zhou) ATLAS egamma Meeting March 9, 2009

2 H. Yang - BDT e-ID2 Motivation To estimate the dijet and  jet rejection rates using various e-ID algorithms (IsEM, Likelihood and BDT). MC samples for test include –DS108087,  jet –DS105802, JF17 dijet –DS106050, Z  ee signal

3 H. Yang - BDT e-ID3 MC  jet samples for test samples N_electron DS  jet DS JF17 dijets DS Z  ee N_events N_candidate Et>17 GeV, |  |< N_candidate (precuts) With EM/Track match Rejection/Efficiency after precuts Rejection 9.5 Rejection 42.7 Acceptance 86.7%

4 H. Yang - BDT e-ID4 Comparison of Input Variables

5 H. Yang - BDT e-ID5 Comparison of Input Variables  -jets electrons dijets

6 H. Yang - BDT e-ID6 Results of IsEM Et(jet) > 17GeV, Tight cuts - Efficiency (Z  ee) = 70.9% - Rejection (  jet) = 426(±4.7%) - Rejection (jf17) = 3092(±5.9%)

7 H. Yang - BDT e-ID7 e-ID (Likelihood) log(ElectronWt/BgWt) Et(jet) > 17GeV - Efficiency = 71% - Rej(  jet)=20(±1%) - Rej(jf17)=5200(±7.6%)

8 H. Yang - BDT e-ID8 e-ID (BDT_dijet) Et(jet) > 17GeV - Efficiency = 71% - Rej(  jet)=591(±5.5%) - Rej(jf17)=47830(±23%) BDT trained for dijets

9 H. Yang - BDT e-ID9 BDT peaks in  jet samples?

10 H. Yang - BDT e-ID10 BDT trained for dijets BDT

11 H. Yang - BDT e-ID11 BDT trained for dijets BDT

12 H. Yang - BDT e-ID12 e-ID (BDT_  jet) Et(jet) > 17GeV - Efficiency = 71% - Rej(  jet)=1788(±9.6%) - Rej(jf17)=19081(±15%) BDT trained for  jets

13 H. Yang - BDT e-ID13 BDT trained for  jets BDT

14 H. Yang - BDT e-ID14 BDT trained for  jets BDT

15 H. Yang - BDT e-ID15 BDT trained for dijets (top 10 vars) RankInput variableGini index 1Etcone20 / Et46.08% 2E2tsts1-Emins1(Emax2-Emin in LAr.1 st )8.60% 3No. of TRT hits / No. of B-layer hits6.68% 4deta1 between track and EM cluster5.21% 5Number of pixel hits4.48% 6F1(frac. of E deposited in LAr. 1 st samp)4.32% 7Ethad1/Et (E leakage in hcal. 1 st samp)3.94% 8E237 / E % 9Eta of inner track2.33% 10Number of B-layer hits2.19%

16 H. Yang - BDT e-ID16 BDT trained for  jets (top 10 vars) RankInput variableGini index 1Number of B-layer hits21.49% 2 Ntrk (  R=0.3) 17.94% 3  Pt (  R=0.3) 11.41% 4Number of pixel hits11.17% 5E233 / E % 6E237 / E % 7No. of TRT hits / No. of B-layer hits4.52% 8deta1 between track and EM cluster4.49% 9Etcone20 / Et4.20% 10F1(frac. of E deposited in LAr. 1 st samp)1.97%

17 H. Yang - BDT e-ID17 Summary samples e-IDs DS  Jet Rejection DS JF17 dijets Rejection DS Z  ee Acceptance IsEM (tight)426(±4.7%)3092(±5.9%)71%(±0.4%) Likelihood20(±1.0%)5200(±7.6%)71%(±0.4%) BDT (for dijets)591(±5.5%) 426(±4.7%) 47830(±23%) 27176(±17%) 71%(±0.4%) 77%(±0.3%) BDT (for  jets) 1788(±9.6%)19081(±15%)71%(±0.4%)

18 H. Yang - BDT e-ID18 Backup Slides

19 H. Yang - BDT e-ID19 BDT peaks in  jet samples?

20 H. Yang - BDT e-ID20 Comparison of Input Variables

21 H. Yang - BDT e-ID21 Comparison of Input Variables

22 H. Yang - BDT e-ID22 Comparison of Input Variables

23 H. Yang - BDT e-ID23 Comparison of Input Variables

24 H. Yang - BDT e-ID24 Comparison of Input Variables

25 H. Yang - BDT e-ID25 Comparison of Input Variables


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