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Top Turns Ten March 2 nd, 2005. Measurement of the Top Quark Mass The Low Bias Template Method using Lepton + jets events Kevin Black, Meenakshi Narain.

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Presentation on theme: "Top Turns Ten March 2 nd, 2005. Measurement of the Top Quark Mass The Low Bias Template Method using Lepton + jets events Kevin Black, Meenakshi Narain."— Presentation transcript:

1 Top Turns Ten March 2 nd, 2005

2 Measurement of the Top Quark Mass The Low Bias Template Method using Lepton + jets events Kevin Black, Meenakshi Narain Boston University 4 high P T Jets  2 from the b-quarks  2 from hadronically decaying W 1 Isolated high P T lepton  Muon or electron  Tau not used in this analysis Neutrino

3 Backgrounds W+Jets  Real high P T lepton  Neutrino  Multiple Jets   ~12 pb ± 25% Multijet Events  One Jet fakes the signature of an isolated lepton  Mismeasured transverse momentum

4 Event Selection At least 4 jets with P T > 20 GeV, |  | <2.5 Isolated Muon or Electron with P T > 20 GeV  Muon |  | <2.0  Electron |  | <1.1 Missing E T > 20 GeV  +jets e+jets From Cross-Section Measurement

5 Topological Variables Form log likelihood of signal over background for each variable and combine Low Bias (“LB”) discriminant is built from four topological variables to give extra discrimination between top and background E T A ´ 3 2 £ Smallest eigenvalue of P K T m i n ´ ( m i n ¢R ij ) _ E j 2 T E T W P ij ´ P a p a i p a j P a j ~ p a j 2 L t b = P j = 4 i = 4 L t b i ( f i ) D LB = 1 1 + 1 : 25 e ¡ L t b H T 2 ´ H T 2 H k

6 Topological Variables

7 Topological Likelihood Discriminant LB disc > 0.4 (optimal cut) ● Remove ~50% background ● Retain ~ 85% Top Using each topological variable separately there is some separation between signal and background however combining them in a likelihood gives optimal separation

8 Identifying b-quark Jets Each top event has two b-quarks travel a few mm and decay Search for jets which point back to secondary vertex Largest backgrounds for top do not have heavy flavor Same event selection, except  Jet Pt > 15 GeV  Require one or more tagged jets

9 Kinematic Fitting Kinematic Fit:  1 unknown: longitudinal momentum of the neutrino  3 constraints Top quark and antiTop quark have the same mass 2 jets have the invariant mass of the W lepton+neutrino have invariant mass of the W  2C fit for top mass  Experimentally see Jets not partons ! try out every permutation

10 Kinematic Fitting Complications g g Initial state gluon radiation - extra jet, not from the top-antitop decay Final stage gluon radiation - extra jet, splits the energy from one parton->2 jets Neutrino: - 2 possible solutions - different starting points for fit

11 Performance of the Fit In parton matched correct solution, RMS ~ 18 GeV, Lowest  2 all events RMS ~ 30 GeV In parton matched events, the lowest  2 solution is correct ~37% of the time Lowest chisq solution Parton matched correct solution

12 Effect of b-tagging Requiring one or more b-tagged jets increases the expected S/B dramatically  without tag ~ 1/2.6  with b-tagged ~ 3/1 (also lower jet p T requirement) Reduction of incorrect permutations:  12: untagged, 6 single tag, 2 double tag Higher Probability of getting correct solution !  better resolution 0 Tags 2 Tags

13 Method to measure the top quark mass Make Templates for signal events  9 different mass points between 150-200 GeV Background Templates from W+jets MC Use simple Poisson likelihood for the number of signal and background compared to data  constrain the number of background events to the expected. Signal 175 GeV Background

14 Multijet Distributions W+jets Multijet data Discriminant

15 Event Yield - Topological Analysis e+jetsmu+jets top27.5 ± 2.220.4 ± 0.9 W+Jets9.5 ± 2.222.0 ± 2.6 Multijet12.0 ± 0.552.6 ± 0.5 e+jetsmu+jets Preselection8780 +  fit 2 <10 7868 +D LB >0.44945 b b p p E T jet

16 Event Yield – b-tagged Analysis e+jets single tag e+jets double tag mu+jets single tag mu+jets double tag Preselection 389245 Fit Convergence 366225 e+jetsmu+jets top30.5 ± 2.422.0 ± 1.75 W+Jets7.0 ± 0.64.3 ± 0.3 Multijet4.5 ± 0.40.7 ± 0.05

17 Ensemble Tests Pull:  ~ 1 Mean ~0 Calibration Consistent With Slope 1 And 0 offset Statistical Error (GeV) Mass Calibration Pull Topological: Expected Error ~6.1 GeV Tagged: Expected Error ~4.2 GeV

18 Topological Analysis Results: Red: background only Blue: background + top Fit 44.2§ 6.6 ttbar events, expect 47.9  8.8 events

19 Tagged Analysis Results Red: background only Blue: background + top Fit 49.2§ 6.3 ttbar events, expect 52.4  4.2 events

20 Comparison with Expectation Tagged Selection Topological Selection

21 Topological Discriminant in Data Tagged Selection Topological Selection Red: background only Blue: background + top Discriminant Mass (GeV)

22 Systematic Errors: Jet Energy Scale  S = E T Jet - E T  ETET Photon + Jet Events - electromagnetic scale more precisely known - Compare the transverse energy of the jet and photon and compute  S - Do the same with Monte Carlo events and compare the difference between data and MC

23 Variation of Distributions with the Jet Energy Scale Perform Ensemble Tests with +1 , -1  compared to nominal JES up and down for top JES up and down for Wjets Ensemble tests +6.8 -6.5 GeV topological +4.7 -5.3 GeV tagged

24 Systematic Errors: Gluon Radiation g g To obtain bounds: - consider the variation seen in events with and without gluon radiation Conservative approach but not much is known about gluon radiation in top decays!

25 Gluon radiation: Kinematics of Jets Matched Matched –Tagged Gluon Jet Gluon Jet –Tagged 4 jets, 1 not matched 4 jets, all matched Ensemble tests §2.6 GeV topological §2.4 GeV tagged

26 Signal Model Compare the nominal sample  ALPGEN/PYTHIA ttbar vs tt+1j ttbar + 0j ttbar + 1 j ttbar +2 j Ensemble tests +2.3 GeV topological +2.3 GeV tagged

27 Systematic Uncertainty SourceTopological (GeV/c 2 )b-tagged (GeV/c 2 ) Statistical  Jet Energy Scale  Jet Resolution  Gluon Radiation  Signal Model  Background Model  b-tagging  Calibration (fitting bias)  Trigger  MC Statistics  Total Systematic 

28 Cross-Checks Vary the Discriminant Cut Drop Constraint on background Constrained (Poisson) Unconstrained Topological 169.9 ± 5.8 GeV 170.7 ± 6.5 GeV Tagged170.6 ± 4.2 GeV171.8 ± 4.8 GeV D > 0.25 170.5 ± 5.5 GeV D > 0.3 170.6 ± 5.5 GeV D > 0.4 169.9 ± 5.8 GeV D > 0.45 170.3 ± 6.5 GeV D > 0.5 169.2 ± 5.6 GeV D > 0.55 167.0 ± 6.5 GeV

29 Summary and Outlook First measurement of the top quark mass at D  using b-tagging  best for Run II so far Result  Topological analysis  b-tagged analysis

30 Backup Slides

31 Event Selection: e+jets 4 jets P T > 20 GeV, |  | <2.5 1 electron P T > 20 GeV, |  | <1.1  EM Fraction > 0.9  Isolation < 0.15  Hmatrix < 50 (shower shape)  EM Likelihood > 0.85 (multivariate)  Track Match E T > 20 GeV, lepton , E T  triangle cuts Second high P T isolated lepton veto Primary Vertex in SMT fiducial range, with at least 3 tracks Primary Vertex within 1 cm of z position of electron track

32 Muon +Jets 4 jets P T > 20 GeV, |  | <2.5 1 muon P T > 20 GeV, |  | <2.0  Isolated from jets E T > 20 GeV, lepton , E T  triangle cuts Second high P T isolated lepton veto Primary Vertex in SMT fiducial range, with at least 3 tracks Primary Vertex within 1 cm in z of muon track

33 Jet Corrections Parton Matched Jets from W Parton Matched Jets from Top Parton Matched Jets Z ! b ¹ b

34 Discriminant Cut

35 Can we combine the two analyses Simplest way – remove the tagged events from the topological analysis  Find 95 events  Anti-tag efficiency Top ~40% W+jets and QCD ~90%  Expect 80% are background after removal of the tagged events. Redo ensemble tests, expected statistical error ~11.0 GeV Combined expected error would be ~3.9 (rather then 4.2) However, systematic dominated so only a few percent overall improvement


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