QCD and Top backgrounds in W+jets and Rjets

1. QCD and Top backgrounds in W+jets and Rjets Alessandro Tricoli (CERN) on behalf of W+jets and Rjets groups W+jets and Rjets EBMeeting 3rd May 2013

2. Overview • Progress made in understanding QCD multi-jet and Top backgrounds • Better understanding of QCD background in W m and e channels, e.g. pileup, trigger and template dependencies • Systematics available for QCD in electron channel • Top background estimations available in both m and e channels with most of systematics included • To do list getting smaller and smaller • big effects already addressed, remaining sub-leading effects to be considered A. Tricoli

3. QCD Methods recap • Both m and e channels fit MET distribution (10-60 GeV) in exclusive jet multiplicity bins, using data-driven template for QCD and other processes from MC • QCD Control samples (Templates); • Mu channel: uses same trigger as for signal and reverts impact parameter significance (d0/s(d0)>3) • Electron Channel: uses logical OR of a few loose electron triggers and revert some electron identification requirements, plus anti-isolation (etcone30/eT> 0.2). Control sample split in 2 data-periods: D-K and L-M • See my presentation on 25thFebruary WZ subgroup for more details A. Tricoli

4. QCD – W->mn +jets Pileup • Investigation of reasons for increase ofQCD background wrt2010 • Is difference of 3x-5x between 2010 and 2011 due to the broadening of the MET distribution with more pile-up? • Previous results were inconclusive • Study QCD fractions in different samples • Low/Medium/High Pileup • D-K and L-M Periods • Low/Medium/High jet pT A. Tricoli

5. QCD – W->mn +jets Pileup • QCD Fractions increases when pileup increases, in all three tests • QCD Fractions for m=0-4 close to 2010 values (pileup conditions rather similar) • Pileup is cause of increased pileup in 2011 wrt 2010 A. Tricoli

6. QCD – W->mn +jets Comparison with W inclusive • W inclusive group uses different definition of QCD control sample • 0.1 < ptcone20/pT<0.5 • Good agreement on QCD fraction between our results and theirs when same selection is used • Reason for different strategy is bias on jet kinematics by reversing relative isolation Reversed D0 Reversed Iso Jet pT biased in all templates tested except our nominal (reversed d0) A. Tricoli

7. QCD – W->mn +jets Comparison with W inclusive • Larger W Contamination in QCD control sample found with our selection (reverted impact param significance) wrt W inclusive method • Frac. of expected Wmnevents in QCD control region: 42% vs 13% with 0 jets W+jets Wincl • Studying if we should subtract this contamination or try different template definition • Find a balance between contamination and jet pT bias A. Tricoli

8. QCD – W->mn +jets Template shape bias • Our method assumes no change of shape in moving QCD events from • the control region to the signal region • Test this hypothesis by comparing the shape of QCD MC in the signal selection to the data templates • The heavily signal contaminated templates (i.e. 1 & 3) show large differences in the zero jet bin, others are all more similar • Clear trend: templates have harder met spectrum than MC • Is this a real bias or more general MC-data discrepancy for QCD? A. Tricoli

9. QCD – W->en +jets Comparison with Inclusive group • Believe we have resolved differences with inclusive group • Very good agreement • Inclusive group also see period dependence consistent with us A. Tricoli

10. QCD – W->en +jets Uncertainties • Uncertainties considered so far • Fit range (5-20 GeV) • Varying the anti-isolation requirement (different cone sizes and cut values) • Sherpa instead of Alpgen • Statistical uncertainty • Study of template bias • Different failed tight requirements (different isEM sub-sets) • adding following requirement to pass at a time (in addition to loose+track quality): • Envelope of these then taken for an additional systematic A. Tricoli

11. QCD – W->en +jets Uncertainties • Due to significantly reduced stats in the QCD template for TRACKMATCH bit reversal • Either we increase stat. or eliminate stat fluctuations from sys. A. Tricoli

12. QCD – W->en +jets Trigger Statistics • Statistical fluctuations dominate systematics at high Njets • From period L5 new triggers were introduced specifically for QCD background estimations in the electron channel • EF_e22vh_loose_4j15_a4tc_EFFS • EF_e22vh_loose_3j20_a4tc_EFFS • Loosely-identified electrons + 2 and 3 jets respectively (beware of e/j overlap) with 15,20 GeV thresholds on HLT jets (Full Scan) • Increase statistics of QCD Control Sample for 2 and more jets • Statistics increase of factor 2 to 5 • 2.0x (Njets =2) • 3.4x (Njets =3) • 3.6x (Njets =4) • 4.1x (Njets =5) • 5.0x (Njets ≥6) • Need to check bias on distributions as 30 GeV cut offline on jet threshold is not at jet trigger efficiency plateau A. Tricoli

13. QCD – W->en +jets Trigger Statistics and Bias No evidence of bias on MET from these triggers for 2 and more jets • Will check bias on other distributions, e.g. jet pT • Will evaluate impact on overall analysis uncertainty of gain in control sample statistics A. Tricoli

14. QCD – W->en +jets Trigger Bias • Three types of triggers used for collecting control sample • e20(22)_loose, e20(22)_looseTrk (= loose + track quality cuts) • e20(22)_loose1 • No trigger bias on control sample from different types of triggers on jet observables • However bias on electron kinematics (as expected) A. Tricoli

15. Top Background Summary • Have fits from 3-jet to 7-jets for both electron and muon channel • Have evaluated all major systematic uncertainties • But still have several cross checks to do with R+jets code • Remaining outstanding items • Understanding fits using MET and Top mass • Correlations between the QCD fit and top fit A. Tricoli

16. Top - Reminder of Method • Top background is one of the largest uncertainties • Use a full data-driven method • A ttbar template from data • An independent variable to normalize the ttbar template Can select a ‘pure’ttbar sample by requiring events with one or two b-jets Found using Transverse Sphericity yields the most stable fits, fits converge up to 7 jets Also studying Top mass and MET fits for comparison A. Tricoli

17. Top Fit Example Data - No b-tagging Njet=4 Top template: - B-tagged Data - Wc,b from MC QCD - Fixed in the fit W template - From MC - No b-tagging requirement A. Tricoli

18. Top Template Corrections • The b-tagged data-driven sample has slight biases with respect to the non-b-tagged sample • Correct for this using MC • The two distributions are normalised in the ratio so that when the corrections are applied the total area is not changed (correct for bias on shape only) A. Tricoli

19. Top - Wcc, Wbb Contamination • Question was raised in EdBoard about what k-factors to apply to the Wbb and Wcc samples • Estimate of the k-factor in the 1-jet and 2-jet bin where top contribution is small • Has small effect on the fit <4% at 3-jet (compared to 8% statistical uncertainty) • Use K-factor of 1.18 as systematic uncertainty A. Tricoli

20. Top - Uncertainties • Statistical uncertainties from the fit • W signal model • Fit using W Sherpa sample • Btagging bias correction • Use largest of statistical errors on Alpgen, or difference between PowhegvsAlpgen • Fit range, template shape dependence • Compare the pseudo-data sets to truth as a function of fit range • Wcc, Wbb contamination subtraction • Redo fits using K-factor of 1.18 • Standard MC-based uncertainties on W template including • B-tagging efficiency uncertainties (on b, c, and light) • JES, JER, lepton energy scale, etc A. Tricoli

21. Top Fit Results • Take the central value of the 3-jet bin with a grain of salt (sudden change with recent MC version, need to de-bug this) • 3-jet bin is dominated by JES (where the W signal is largest) • 7-jet bin is dominated by statistical uncertainties from the fit A. Tricoli

22. Top Fit Results • Detector level distributions look good Data-driven MC A. Tricoli

23. Top Open Problems • The Sherpa sample has poor statistics • Using sherpa as a modeling uncertainty has large fluctuations (red curve) • Using Sherpa for both W signal template and W contamination in Top control sample • Will use pseudo-data sets to evaluate if the modeling uncertainty is fully included in the fit range systematic Fractional uncertainty on N. of Top events A. Tricoli

24. Top Open Problems • Fits using top Mass and MET are very unstable and dependent on the fit range. • It would be helpful to have a second variable as a cross check • Need to re-do pseudo-data set fits to evaluate fit ranges for these variables A. Tricoli

25. QCD and Top - To Do List • QCD multi-jet background • Re-evaluate systematics in W->mn channel • Study W contamination in QCD control region and alternative control samples (with no kinematic bias) in W->mn channel • Study alternative method, e.g. isolation, in both channels • Cross check strategy of systematics with W inclusive group • Top background • Cross check all JES uncertainties, cutflow on MC with R+jets • Add electron, muonsystematics • Cross check results with alternative fit methods, i.e. MET and Top Mass, including their systematics • Adding fit range systematic uncertainty and closure tests • Correlation between QCD and Top data-driven estimations • Evaluate Top background on Z (follow Z+jets/CMS method) A. Tricoli

26. Backup A. Tricoli

27. Slide from 25 February Pileup – muons • No need of period dependence fit in Muon Channel since same trigger used for signal and background samples • pileup effects (e.g. broadening of MET distribution) in signal sample is well reproduced by background sample • Oppositely to electron channel, QCD fraction seems to go down in L-M, by a factor ˜3 wrt D-K • Is this because isolation becomes tighter with more pileup? Clear period-dependence of isolation distribution (D-K,L-M) QCD control sample Signal sample A. Tricoli

28. QCD – W->en +jets Systematics – 5th jet A. Tricoli