1 / 13

QCD Estimation Update Using Chi-Squared Minimization by William Edson at SUNY Albany

This update focuses on QCD estimation using chi-squared minimization method by William Edson from SUNY at Albany. The equation and results, including ensemble tests with Gaussian fit, are discussed along with the backup proceeding on acceptance and efficiency work. The results cover various reconstructions scenarios and detailed cutflow analysis.

falala
Télécharger la présentation

QCD Estimation Update Using Chi-Squared Minimization by William Edson at SUNY Albany

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. ttbarτ + jets:Update on QCD Estimation William Edson SUNY at Albany

  2. Chi-squared minimization • Equation: • N(x): total number of events of type x for distribution • n(x)i: number of events in bin of type x • frac(Sig): fraction of N(Remain) expected to be Signal • binfrac(x)i: fraction of events in bin of type x expected from MC or template • σi: uncertainty in bin i

  3. Chi-squared minimization cont. • σi determined by adding in quadrature • bin error: • data • signal, MC • QCD template • other backgrounds, MC • statistical error: • data: signal region (times 2) • data: background region • other backgrounds, MC (times 2) • signal, MC • signal and other backgrounds combined, MC: background region

  4. Results • Chi-square: 3.747 • signal fraction: 0.91933 +/- 0.157592 • signal fraction for all data: 0.819601

  5. Ensemble tests with result signal fraction Results with Gaussian Fit Associated Errors Mean: 0.764889 +/- 0.002659 Sigma: 0.0805555 +/- 0.0020661

  6. Linear Fit with Signal Fraction from 0.1 - 0.8 y(0): -0.00998677 +/- 0.05173513 slope: 0.912698 +/- 0.1009633

  7. Back-up

  8. Proceeding Acceptance and Efficiency Work • Efficiency: Limiting to events in 105200 sample satisfying: • contain truth matched taus • single prong • muonVeto and eleBDTMedium == 0 • calo-seeded taus • Acceptance: Using all MC types • Nrec: MC events passing entire cutflow • Ngen: 105200 events using mc and trueTau branch information matched to single prong, BDTJetScore > 0.7 taus

  9. Highest pTbjet reconstruction • Results for plot: • chi-square: 7.341 • p-value: 0.7709 • ndf: 11 • chi/ndf: 0.6674

  10. 2nd highest pTbjet reconstruction • Results for plot: • chi-square: 13.76 • p-value: 0.3166 • ndf: 12 • chi/ndf: 1.147

  11. Dijet reconstruction • Results for plot: • chi-square: 6.133 • p-value: 0.8643 • ndf: 11 • chi/ndf: 0.5575

  12. Closest Top mass reconstruction • Results for plot: • chi-square: 5.342 • p-value: 0.8035 • ndf: 9 • chi/ndf: 0.5936

  13. Cutflow • C0: GRL • C1: Trigger • C2: Primary vertex with ntracks > 4 • C3: Electron/muon overlap, larVeto • C4: Jet cleaning • C5: Lepton Veto • C6: njets >= 4 with eta < 2.5 and |jvf| > 0.75 • C7: MET > 60GeV • C8: MT < 70GeV • C9: Sum ET < 500GeV • C10: >= 1 bjet • C11: Tau n ≥ 1, BDTScore > 0.7 • C12: Trigger matched tau n ≥ 1 and pT >= 40GeV • C13: MC tau object match

More Related