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Measurement of the Top Quark Cross section in the tau+jets Channel

Measurement of the Top Quark Cross section in the tau+jets Channel. William P. Edson , Teeba Rashid, Dr. Sajjad Alam 1 Dr. Dick Greenwood, Anirvan Sircar 2 Dr. Patrick Skubic , Dr. Muhammad Saleem , Dr. Brad Abbot, Dr. Phil Gutierrez, Christopher Walker, David Bertsche 3

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Measurement of the Top Quark Cross section in the tau+jets Channel

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  1. Measurement of the Top Quark Cross section in the tau+jets Channel William P. Edson, Teeba Rashid, Dr. Sajjad Alam1 Dr. Dick Greenwood, Anirvan Sircar2 Dr. Patrick Skubic, Dr. Muhammad Saleem, Dr. Brad Abbot, Dr. Phil Gutierrez, Christopher Walker, David Bertsche3 Dr. Serban Protopopescu4 1: State University of New York at Albany 2: Louisiana Tech University 3: University of Oklahoma 4: Brookhaven National Laboratory Jan. 31st 2013

  2. Overview • Physics Channel • Analysis Samples • Object Selection • Event Selection • Tau Selection • QCD Multijet Template method • Ensemble Tests • Linearity Test • Results • Systematic Uncertainties • Previous Question Responses • Internal Note: http://cds.cern.ch/record/1627649

  3. Physics Channel b q’ g W+ t g q τ W- t ντ g b Top Pair Branching Fractions for ttbar decays[1]

  4. Samples

  5. Object Selection • Trigger: • Tau29_medium_xe35_noMu (B-K) • Tau29T_medium_xe35_noMu_3L1J10(L-M) • Jets: • Anti-Kt 0.4 TopoCluster jets • PT > 20 GeV • JVF > 0.75 • |η| < 2.5 • B-tagging: • BTaggingCalibrationDataInterface 00-01-02 • Tau: • Anti-Kt 0.4 TopoCluster jets • PT > 20 GeV • |η| < 2.3 • tau_EleBDTMedium != 1 • tau_muonVeto != 1

  6. Event Selection

  7. Tau Selection If more than 1 tau candidate following object selection: • Check for number of prongs per candidate • multiple 1-prongs, event is rejected • single 1-prong present , proceed using this tau for analysis • else (only 3-prong) use highest BDTJetscore tau for analysis • other 3-prong taus are kept as jets

  8. QCD Multijet Template Method • Templates for the MET and dijet mass are constructed for three cases: • 1-prong reconstructed taus • 3-prong reconstructed taus • Combined 1 and 3-prong • BaseLine: • Full Event and Tau Selection • Control: • Full Event Selection • Tau Identification passing either: • Likelihood > -40 • BDTJetScore > 0.1 • AND not passing Tight selection for same tauID

  9. MET, Dijet Mass Correlation Plot Dijet Mass (GeV) MET (GeV))

  10. QCD Multijet Template Method contd. • Template for QCD taken as the shape difference in the concatenated MET and dijet mass histograms for Data control sample with the control samples from MC: • ttbarsemileptonic • W + jets • Z + jets • single top • diboson

  11. Add Iterative info here • Previous Results relied on a fixed scale factor to luminosity for signal MC in the control region. Scaling the MC in this way implied a prior knowledge of what the top cross section value is. • To this end, we have altered the analysis to instead determine the scale factor for signal MC using an iterative approach beginning with an arbitrary cross section from which the scale factor is calculated. • The cross section resulting from the fit using this scale factor is then used to recalculate new scale factors and the process repeated until the cross section value converges.

  12. Resulting Fractions from Fit MET Mjj Fit Result of Data to Signal MC, QCD Multijet, and other MC Backgrounds for concatenated MET & Mjj for Combined (1 & 3-prong), chi2/ndf: 1.21609

  13. Data Fit with Results Including Signal and all Backgrounds Both plots are for the combined 1 & 3-prong case

  14. Data Fit with Results Including Signal and all Backgrounds contd. Both plots are for the combined 1 & 3-prong case Additional comparison plots using other variables found in backup slides 38 and 39

  15. Signal and QCD Output • Signal and QCD output event count results are determined using the output fractions from the fitting analysis

  16. Remaining Events

  17. Tau ID Systematic Study For “OR” Analysis • Samples: • Signal Samples: Z → ττ final states selected with one tau decaying via muon while the other hadronically • Control Samples: Primarily W → μν + jet data driven events • Background further reduced by subtracting the number of events with the same charge (SS) for muon and tau candidate from the number of events where the muon and candidate have opposite charge (OS)

  18. Tau ID Systematic Study For “OR” Analysis Contd. • Samples Divided into 2 regions: • Those passing TauID OR tight selection and OS-SS subtraction • Those failing both tight selections but passing OS-SS subtraction • Further define five variables: • NiW: Number of control events in region i after MC predicted Zττ contribution removed • Nid: Number of data events in region i • NiS: Number of MC predicted Zττ events in region i • Nibkd: Number of background events in regioni • Npred: Predicted number of signal in region 1

  19. Tau ID Systematic Study For “OR” Analysis Contd. • Tau ID Uncertainty is Estimated based on comparison of N1S and Npred. • Equations: • N2bkd = N2d - N2S • N1bkd = N2bkd * (N1W/ N2W) • This assumes the shape of the background is given by the shape of the control sample • Npred = N1d - N1bkd

  20. Tau ID Systematic Study For “OR” Analysis Contd.BDT Distributions in Regions 1 and 2 Comparison of stacked Signal and Control Samples scaled to NiS and Nibkd respectively to data in defined regions 1 (left) and 2 (right) for the combined 1 and 3-prong case

  21. Results • Combined (1 & 3-prong): • 1-prong: • 3-prong: • SM NNLO prediction: for top mass of 173.3 GeV [2] • NikHEF Result [3]:

  22. Systematic Uncertainties for Combined Result

  23. Systematic Uncertainties • 3-prong • 1-prong

  24. Cross Section Comparison Plots

  25. Previous Comments (12/20/2013) • LAr hole treatment: • In 3.1 you say you are vetoing events with jets / electrons in the LAr hole. This doesn't seem to correspond to the jet / Etmiss and egammarecommendations • >Our analysis now does as prescribed on the twiki pages. • Then in 3.3 you say you reject electrons in the hole (this is inconsistent with 3.1, where you say you reject the event), but egamma recommends not to do this, • >The discussion was misleading. This discussion was about Lar noise bursts and was mixed up with LArHole. We fixed the text now. • Muon& electron scale factors:In sections 3.3 and 3.4 you say you are using scale factors for electrons and muons - how are these used in your case where you veto electrons & muons, rather than select them? • >This was a misinterpretation, electron energy is scaled using the prescribed correction factor and the muonpT is smeared again following prescription • Please provide details on which jet calibration configuration is used and which b-tagging calibration is used. • >We used anti-kt4 algorithm with EM+JES calibration for 2011 data as recommended by the top working group. (slide 5) • >For b-tagging calibration we used MV1 tagger with the calibration recommended by the flavor tagging group for 2011 data. (slide 6) • >Version 00-01-02 of the BTaggingCalibrationDataInterface was used. (slide 5)

  26. Previous Comments (12/20/2013) contd. • Has this idea to use an OR of the likelihood and BDT tau ID been discussed with the tau CP group? How are the systematic uncertainties for this OR determined? • >No, This has not been shown in tau CP group meetings. However, the study is done separately by Serban for the tau ID related systematics and added as Appendix C to the note (see backup slides 17-20). This study tells us that tau ID related systematic uncertainties are not much different in the case of OR than as those if evaluated separately. • Please provide some details on the trigger scale factors and efficiencies you are using. • >The triggers used in our analysis have expected average efficiencies in the appropriate data-periods around 70% as measured on the signal sample. These triggers selections are initially used by the charged higgs analysis (for mH < mt) in ttbar decay with tau + jets final states: https://cds.cern.ch/record/1419805?ln=en# • Correlation between m(jj) and MET: • Can you provide some plots demonstrating in the MC that m(jj) and MET are uncorrelated? • >See slide 9 • Can you provide the formula used in the fit and which minimization technique that is used? • >We used the TFraction Fitter. The fit is performed using the signal templates taken from the MC , QCD template taken from the data (loose sample) (see slide 10). • For minimization this uses MINUIT2

  27. Previous Comments (12/20/2013) contd. • Ensemble tests: • To test the impact of fitting two 1D distributions, please could you make ensemble tests based on the 2D MET-m(jj) distribution - you create the 2D distribution (with the same >>binning you have in the fit) and then draw toy experiments using poisson random numbers for each bin. You can then extract the 1D distributions from each 2D toy and pass them >>to the fit procedure. In addition to the linearity test - can you also produce the pull distributions? • > Work still in progress. • The offset and slope of the linearity test look to be inconsistent with 0 and 1, respectively. Is this corrected for? Also, the linear fit in Fig 8 seems to be quite poor - chi2 of 54 for 4 >>degrees of freedom - have you investigated this? • > The non-linearity is very small compared to our errors. Currently working on the 2D MET-Dijet Mass Distribution from last suggestion to hopefully solve this.

  28. Previous Comments (12/20/2013) contd. • There should be 17 components for the JES uncertainty • >Work is in progress to produce and analyze the output. • 516-527: tau ID / energy scale uncertainties: Please could you provide some details and numbers here and references to where the numbers are derived? • >Since this analysis is closely following the charged higgs analysis with mH < mtop and have similar final state (as referenced in our note). These numbers are borrowed from charged higgs note • Tables 6-8: The b-tag uncertainty seems to be missing from the tables? • > See slides 22, 23 • Results: Please can you provide the dependence of the measured cross section as a function of the top mass - you can do this by re-running the analysis on the ttbar samples with a different top mass and then looking at how the measured cross section changes. • >We are working on this part, since this requires sample at different mass points. Will be added soon.

  29. Future Plans • Aiming for journal paper for the winter conference • Editorial Board desired for publication • Internal Note: http://cds.cern.ch/record/1627649

  30. Acknowledgements • Dr. Patrick Skubic • Dr. Muhammad Saleem • Dr. Brad Abbot • Dr. Phil Gutierrez • Dr. Dick Greenwood • Christopher Walker • Dr. SerbanProtopopescu

  31. References • Neil Collins, TopCross Section (Current Status and Early LHC Prospects). 10 March 2010. • M. Czakon, P. Fiedler, and A. Mitov, The total top quark pair production cross-section at hadron colliders through O(αS4), arXiv:1303.6254 [hep-ph]. • ATLAS Collaboration, Measurement of the ttbar production cross section in the tau+jets channel using the ATLAS detector, arXiv:1211.7205v2 [hep-ex]. • CMS Collaboration, Measurement of the top-antitop production cross section in the tau+jets channel in pp collisions at sqrt(s) = 7 TeV, arXiv:1301.5755v2 • ATLAS Collaboration, Measurement of the top quark pair production cross section in pp collisions at s√= 7 TeV in μ+τ final states with ATLAS, ATLAS-CONF-2011-119

  32. Back up

  33. Ensemble Tests • Pseudo data was created using constant fraction for other MC backgrounds and varying signal fractions (0.2 to 0.7 in steps of 0.1) • For each signal fraction, the bin content was randomized for templates for Signal and other MC backgrounds from baseline samples and QCD from the control samples • The three randomized templates coming together formed the pseudo data • The procedure was repeated 10,000 times for each fraction resulting in a histogram for each fraction which could be fit to a Gaussian

  34. Ensemble Test Result Examples Input Signal Fraction: 0.2 Input Signal Fraction: 0.7 Remaining result histograms included in Back up slides 31 and 32

  35. Ensemble Test Result Examples contd. Input Signal Fraction: 0.3 Input Signal Fraction: 0.4

  36. Ensemble Test Result Examples contd. Input Signal Fraction: 0.5 Input Signal Fraction: 0.6

  37. Linearity Test • The Gaussian mean values and errors of the Ensemble test runs (y) were plotted versus their corresponding input fraction (x) with the resulting linear fit below: Output Signal Fraction Input Signal Fraction

  38. Data Fit with Results Including Signal and all Backgrounds contd. Both plots are for the combined 1 & 3-prong case

  39. Data Fit with Results Including Signal and all Backgrounds contd. Both plots are for the combined 1 & 3-prong case

  40. Resulting Fractions from using Likelihood and BDT Analyses Individually Likelihood Analysis (Analysis A): BDT Analysis (Analysis B):

  41. Resulting Efficiencies from using Likelihood and BDT Analyses Individually

  42. Results • Analysis A • Combined (1 & 3-prong): • 1-prong: • 3-prong: • Analysis B • Combined (1 & 3-prong): • 1-prong: • 3-prong:

  43. MTW < 80 GeV Distribution of MTW from signal and Multijet control sample demonstrating the contribution of fakes in control sample and real τ in signal distribution

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