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Estimation of W+jets background using Z+jets as a control sample

This study focuses on estimating the background contribution of W+jets using Z+jets as a control sample in high-energy physics research. Various analyses and datasets are explored to determine the background contamination levels and develop estimation methods. The theoretical cross-section uncertainties and selection cuts are discussed, along with the W/Z ratio variations based on jet multiplicities. The study concludes with projected errors in the W/Z normalization factor and discussions on systematic uncertainties.

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Estimation of W+jets background using Z+jets as a control sample

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  1. Estimation of W+jets background using Z+jets as a control sample I. Besana T.Lari U.De Sanctis Maria Ilaria Besana, Umberto De Sanctis, Tommaso Lari (Milano group)

  2. Contents: • Introduction • Datasets and selection cuts • W/Z as a function of jet multiplicity • Background contamination as a function of jet multiplicity • Estimation of backgroud W+jets to top analysis • Conclusion and outlook I. Besana T.Lari U.De Sanctis

  3. Introduction: • Update ofpreviousanalyses: • http://indico.cern.ch/getFile.py/access?contribId=8&resId=0&materialId=slides&confId=25489 • http://indico.cern.ch/getFile.py/access?contribId=12&resId=0&materialId=slides&confId=25360 • http://indico.cern.ch/getFile.py/access?contribId=5&resId=1&materialId=slides&confId=52962 • Similar work doneby: • Marisa Sandhoff (Wuppertal) : http://indico.cern.ch/getFile.py/access?contribId=49&sessionId=6&resId=0&materialId=slides&confId=31799 • LBNL group : Atlas note ATL-PHYS-COM-2007-100 • Bonn group : http://indico.cern.ch/getFile.py/access?contribId=3&resId=0&materialId=slides&confId=45163 http://indico.cern.ch/getFile.py/access?contribId=6&resId=0&materialId=slides&confId=55855 I. Besana T.Lari U.De Sanctis

  4. Introduction: motivation • theoretical Xsection of W+jets is rather uncertain especially ratio: W+0j : W+1j : W+2j : W+3j : W+4j : W+5j • tool: Z+jets - Z is “easy ” to select with high purity (but σW~10*σZ) - idea: use Z to determine σW and properties of W+jets - assumption: σW+4jets = c *σZ+4jets (σW+0jets / σZ+0jets ) c = coef which takes into account mass difference for W and Z • distributions for W and Z should look similar I. Besana T.Lari U.De Sanctis

  5. Datasets: I. Besana T.Lari U.De Sanctis Datasets at 10 TeV rel 14: Alpgen datasets haven’any filter on jets.

  6. DATASETS: I. Besana T.Lari U.De Sanctis ! Not checked yet: QCD contamination in W and Z selected sample, how to estimate and subtract its contribution from data

  7. Selectioncuts: objectdefinition I. Besana T.Lari U.De Sanctis

  8. Selectioncuts: eventselection Z ee: • Trigger: e20i • 2 electrons with pT > 20 GeV, muon veto • 80 GeV < invariant mass < 100 GeV • max (|ETmissX|, |ETmissY|) < 3 σgauss W eν: • Trigger: e20i • 1 electron with pT > 20 GeV , muon veto • ETmiss > 20 GeV Top selection requires in addition: • at least 4 jets with pT >20 GeV & |η|<2.5 • at least 3 jets with pT >40 GeV & |η|<2.5 I. Besana T.Lari U.De Sanctis

  9. W/Z RATIO AS A FUNCTION OF NJETS MC level: Pythia vs Alpgen vs McAtNlo I. Besana T.Lari U.De Sanctis

  10. W/Z ratioas a functionofNjets: Reco level: Pythia vs Alpgen vs McAtNlo I. Besana T.Lari U.De Sanctis

  11. W/Z ratio as a function of Njets : Reco level (1jet norm.): Pythia vs Alpgen vs McAtNlo I. Besana T.Lari U.De Sanctis

  12. W/Z ratioas a functionofNjets: Reco level (2jet norm.): Pythia vs Alpgen vs McAtNlo I. Besana T.Lari U.De Sanctis

  13. I. Besana T.Lari U.De Sanctis

  14. I. Besana T.Lari U.De Sanctis

  15. EventSelectioncuts • e10i trigger chain (10**31 menu) • Electrons medium and isolated as before • W selection: • 1 electron pt >20 GeV, no muon pt>20GeV, • etmiss > 20 GeV, mT(e,EtMiss) cut. • Z selection: • 2 electrons pt>20 GeV, no muon pt>20GeV • max (|ETmissX|, |ETmissY|) < 3 σgauss • 80 GeV < invariant mass < 100 GeV I. Besana T.Lari U.De Sanctis

  16. Background contaminationfor Z: inclusive and low jet multiplicity sample Selection for ratio measurment [80GeV-100GeV] I. Besana T.Lari U.De Sanctis Z can be selected with high purity!

  17. Background contaminationfor W: inclusive and low jet multiplicity sample Selection for ratio measurement: [40 GeV, 90 GeV] I. Besana T.Lari U.De Sanctis

  18. Selection of W, Z candidates • All numbers normalized to 10 pb-1 • W signal (for purity) is sum of en and tn decays • Background in Z selection < 0.01% (but QCD not included yet) • We need to correct the number of W candidates for the efficiency e of mT cut • We need to correct for the background to W selection • Systematics on the two corrections need to be studied. • In the following, assume : - background known to 20% • - D(1-e)/(1-e) = 50% I. Besana T.Lari U.De Sanctis

  19. W/Z ratio • (Very preliminar) overall error on W/Z normalization factor: • 2.1% using 0 jet selection (0.6% with 100 pb-1) • 4.2% using 1 jet selection (1.5% with 100 pb-1) • 10.4% using 2 jet selection (5.9% with 100 pb-1) • QCD background not included yet • Error from MC statistics on ratios is small (0.04 to 0.12) • As long as efficiencies ratios, acceptance ratios, JES, etc. are the same as in • to the top signal region (3-4 high pt jets) we do not care! These effects need to be • included on systematic error on the extrapolation (later). I. Besana T.Lari U.De Sanctis

  20. Ratio of ratios • Call Rn = (W+njets)/(Z+njets) • Rn depends on n differently according to different generators. This is a systematics in extrapolating to top signal region (large n) • We can use measured values of R2/R0 and R1/R0 to test/tune/constrain generator predictions R1/R0 = 0.791 ± 0.039 ± 0.026 R2/R0 = 0.726 ± 0.076 ± 0.044 First error is statistics for 10 pb-1. Second is systematics, dominated by the efficiency term. Statistical error on MC prediction is <0.01 (sarebbe carino confontare col valore a livello di verita’ MC) I. Besana T.Lari U.De Sanctis

  21. Background contaminationfor Z: top-antitop signalregion Mee invariant mass (200 pb-1) NO cut on ETmiss I. Besana T.Lari U.De Sanctis Mee invariant mass (200 pb-1) Cut on ETmiss

  22. I. Besana T.Lari U.De Sanctis

  23. Evaluationof background tosemileptonic top-antitop sample (200 pb-1) I. Besana T.Lari U.De Sanctis 22 % difference between Alpgen and Pyhia

  24. Three-jetinvariant mass distribution (200 pb-1) Alpgen I. Besana T.Lari U.De Sanctis Good agreement !

  25. Conclusion & Outlook W+jets background can be estimated from Z+jets: • with a statistical error of …% (according to Alpgen) at 200 pb-1 , • difference between Alpgen and Pythia of 22%, • using R1/R0 and R2/R0 (RN=W+Njet/Z+Njet) to constraint the spread of Montecarlo predictions and reduce associated systematics looks promising. Next steps: • include QCD background, • study systematics: constrain generator dependence with first data. I. Besana T.Lari U.De Sanctis

  26. Backup I. Besana T.Lari U.De Sanctis

  27. Pythiasystematicerror at MC level (rel 12) There is a distortion in the pT shape of the most energetic jet wich comes from doing an η cut on the 2nd electron in Z ee, but not on the ν of W eν I. Besana T.Lari U.De Sanctis

  28. Pythiasystematicerror at MC level (rel 12) I. Besana T.Lari U.De Sanctis

  29. Etmissdistribution: I. Besana T.Lari U.De Sanctis Selection cut: max (|ETmissX|, |ETmissY|) < 3 σgauss

  30. Selectioncuts: efficiency W selection Pythia I. Besana T.Lari U.De Sanctis Alpgen

  31. Selectioncuts:efficiency Z selection Pythia Alpgen I. Besana T.Lari U.De Sanctis Ratio (signal/background) > 200

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