1. Data-driven background determination in 1-lepton SUSY A. Koutsman, F. Koetsveld & W. Verkerke 21 april 2008 SUSY CSC Note1&2 is ready!

2. 21 april 2008NIKHEF ATLAS Outing A. Koutsman2 SUSY event selection: One lepton mode SUSY Dominant backgrounds: Top pair (separate 1l, 2l) W+jets  QCD  Z+jets 1 fb -1 After selection Effective mass [GeV] GOAL = estimate and understand backgrounds from data TARGET = Develop methods to discover/exclude SUSY with 1 fb -1

3. 21 april 2008NIKHEF ATLAS Outing A. Koutsman3 Seeking SUSY SUSY abundant at high missing E T Problem: -SM shape at high missing E T also unknown -no direct measurement possible (if SUSY exists) -MC possibly unreliable  data- driven estimation Possible solution: -measure at low missing E T & high M T and high missing E T & low M T (both regions practically SUSY-free from kinematic considerations) -combine info and extrapolate to high missing E T,M T - SUSY contamination in low missing E T,M T signal region control region 1 fb -1 After selection Effective mass [GeV]

4. 21 april 2008NIKHEF ATLAS Outing A. Koutsman4 Combined fit method Main Idea: Define a signal region (SUSY rich) and a control region Construct a model for each background sample Use the combined model for extrapolation Explicitly account for SUSY contamination in control region Key issues to understand: - Shape of each SM background - Amount and shape of SUSY in control region - Amount of correlations between observables signal region control region Observables: Missing E T M T = mass E T +lepton M top = invariant mass of 3 jet system with highest sum p T

5. 21 april 2008NIKHEF ATLAS Outing A. Koutsman5 Fitting the background In absence of correlations, simple factorizing multi-dimensional models E.g. P ttbar (M T,E T,m top ) = P 1 (M T )  P 2 (E T )  P 3 (m top ) Combined fit: model describing combined background in control region  extrapolate to signal region P total (M T,E T,m top ) = N tt1l * P tt1l (M T,E T,m top ) + N tt2l * P tt2l (M T,E T,m top ) + N wnj * P wnj (M T,E T,m top ) + N susy * P susy (M T,E T,m top ) (Ansatz model) Ansatz model for SUSY contamination in control region For low values of E T, SUSY distribution described by a gentle slope For low values of M T, SUSY distribution is flat N.B. All plots for 1 fb -1

6. 21 april 2008NIKHEF ATLAS Outing A. Koutsman6 Structure 1) Combined fit with FIXED SHAPES Uses most MC information Proof of SUSY Ansatz concept 2) Combined fit with FLOATING SHAPES Ideally float all shape parameters 3) Combined fit with EXTRAPOLATION Test of complete procedure N.B. All plots for 1 fb -1

7. 21 april 2008NIKHEF ATLAS Outing A. Koutsman7 Combined fit with FIXED SHAPES Include generic SUSY contribution in fit (gauss in E T, gentle slope in M T,landau in m top ) and fit to data with SUSY (SU3) contamination Fix shapes from pre-fits to each background component and float only the component fractions Combined fit with SUSY on 1 fb -1 of data Fit Truth N tt2l = 15 ± 30 70 N tt1l = 509 ± 35 502 N wjets = 194 ± 35 173 N su3 = 293 ± 24 271 W+jets TTbar Dileptonic TTbar Semileptonic SU3 Next step: does the fit work in an unbiased way? missing E T MTMT M top

8. 21 april 2008NIKHEF ATLAS Outing A. Koutsman8 Combined fit with FIXED SHAPES Fix shapes from pre-fits to each background component and float only the component fractions Run fit 1000 times on toy-MC samples drawn from combined background p.d.f. fitted to MC-data  pull distributions for the yield of SUSY sample Fit is unbiased! All studied SUSY points work using the Ansatz! W+jets TTbar Dileptonic TTbar Semileptonic SU3 Next step: floating shapes missing E T MTMT M top

9. 21 april 2008NIKHEF ATLAS Outing A. Koutsman9 Combined fit with CORRELATIONS Effect of correlations is not huge…  Aim to introduce a subset of most significant correlations in final model A fixed shape fit with factorizing pdf’s for each component can be compared to the simple sideband subtraction method (assumption: shape in E T is the same for all M T ) Example of parameter correlation M top slope E T Refining of the method using conditional pdf’s to describe correlations (gradual change of E T as function of M T ) Combined fit with all non-negligible correlation coefficients floating (shape parameters fixed) Next step: floating shape parameters fit result sliced data

10. 21 april 2008NIKHEF ATLAS Outing A. Koutsman10 The goal is to be able to float all SM shape parameters in the ‘final’ combined fit  data-driven (N.B. SUSY shape is the Ansatz) Combined fit with floating shapes on 1 fb -1 of data The fit procedure works fine with all the W+jets & tt1l shapes floating, returning the correct yields of the SM backgrounds and SUSY signal Floating the M T,E T -shapes of tt2l sample makes the fit become unstable and the parameters highly correlated. The fit with these parameters floating is not possible without additional information Combined fit with FLOATING SHAPES W+jets TTbar Dileptonic TTbar Semileptonic SU3 Next step: extrapolation to signal region missing E T MTMT M top Pull distributions for yields of tt2l, W+jets and SU3 samples Fit is unbiased! SU3tt2lW+jets

11. 21 april 2008NIKHEF ATLAS Outing A. Koutsman11 Define two SideBands and the signal region M T > 150 & E T > 200 Fit the combined model in the sidebands and extrapolate to signal region (errors and correlations propagated correctly) Combined fit with EXTRAPOLATION Next step: check other SUSY points TTbar Semileptonic SB1 SB2SIGNAL Fit Truth in SIG N tt2l = 4.7 ± 7.9 5 N tt1l = -1.1 ± 3.9 0 N wjets = -1.2 ± 2.7 2 N su3 = 95.6 ± 4.0 91 Fit Truth in FULL N tt2l = 17 ± 54 70 N tt1l = 485 ± 59 502 N wjets = 227 ± 68 173 N su3 = 287 ± 38 271 Extrapolate to full parameter space Combined fit in the control region has enough information to constrain and correctly extrapolate the background samples to the signal region A generic SUSY model in the control region accounts correctly for the contamination and is extrapolated to find the right yield of SUSY events in the signal region Can do with minimal MC input

12. 21 april 2008NIKHEF ATLAS Outing A. Koutsman12 Fit the combined model in the sidebands and extrapolate to signal region (errors and correlations propagated correctly) Combined fit with EXTRAPOLATION Last step: study systematics Valildated the procedure for various SUSY points SM backgrounds and SUSY are correctly extrapolated in an unbiased way!

13. 21 april 2008NIKHEF ATLAS Outing A. Koutsman13 How stable is the complete procedure under energy scale variations? Study of relative variation of measured SUSY cross-section: σ sel Systematic uncertainties Uncertainties due to MC statistics listed as these might be dominated by small event counts (e.g. the number of events that migrate due to systematic check) Both the shape fit stability (1 st column) and extrapolation stability (2 nd column) studied Variations of order 5%  procedure is stable

14. 21 april 2008NIKHEF ATLAS Outing A. Koutsman14 Summary of work in CSC Note All of the preceding work has been included in the CSC note. Have enough information with 1 fb -1 in M T,E T,m top to constrain SM background (tt 1l,tt 2l,W+jets) with a combined fitting procedure  Allows for clean determination of SUSY excess in data Can do with minimal MC input (  data driven) Checked validity of procedure for various SUSY points Stability of fit studied under possible energy scale variations  More information from additional control samples to get a handle on the tt2l shape parameters  In the final model introduce significant correlations

15. 21 april 2008NIKHEF ATLAS Outing A. Koutsman15 Floating tt2l shapes Floating the M T,E T -shapes of tt2l sample makes the fit become unstable and the parameters highly correlated. The fit with these parameters floating is not possible without additional information Get additional information on the tt2l shape by performing a simultaneous fit to a tt2l-enriched sample Why is tt2l in the 1-lepton(electron) mode after SUSY selection? What tt2l events make it through? # events @ 1fb -1 % tt  ee3022 tt  μμ00 tt  ττ129 tt  eμ2518 tt  eτ6347 tt  μτ54 0τ : 40 % 1τ : 51 % 2τ : 9 % ONGOING WORK…

16. 21 april 2008NIKHEF ATLAS Outing A. Koutsman16 tt2l events in 1-lepton mode What happens with the 2 nd lepton for 0τ events? How does tau decay in 1τ events? 2 nd lepton % out of acceptance, |eta| < 2.50 out of acceptance, p T > 20 GeV17 mis-ID as jet59 mis-ID or |eta| < 2.514 mis-ID or p T > 20 GeV10 tau-decay% 2-particle τ  ντ a1±τ  ντ a1± 20 τ  ντ π±τ  ντ π± 15 τ  ντ ρ±τ  ντ ρ± 28 τ  ν τ ‘other’ 9 3-particle τ  ν τ ν l l 28 2-particle: 72 % 3-particle: 28 % mis-ID: 83 % other: 17 % N.B. tt  ee truth info

17. 21 april 2008NIKHEF ATLAS Outing A. Koutsman17 Main idea: W-decay into qqbar and lnu has the same kinematics. Use the tt1l sample to simulate the shape of tt2l in E T,M T  Take a pure sample of tt1l  find the 2 jets from W-decay  substitute these jets by a lepton and a neutrino τ : 2-particle decay (1 jet + 1 neutrino) mis-ID e : jet  apply SUSY selection  calculate E T,M T and you have the tt2l-shape Using tt1l for tt2l shape τ / mis-ID e ν Selection of pure tt1l sample: > 3 light jets + >0 b-jet (p T >20) missing E T > 20 1 ‘good’ lepton with p T >20 150 < m top < 190 (highest p T sum of 1 b-jet and 2 light-jets) 70 < m W < 90 (gives the 2 correct light jets)

18. 21 april 2008NIKHEF ATLAS Outing A. Koutsman18 Results with substitution method Statictics is the limiting factor for this method; very few tt1l  tt2l substituted events survive SUSY selection Stringent selection for pure tt1l sample One hard jet  neutrino leaves 3 hard jets SUSY selection requires 4 hard jets Events with at least 5 original hard jets needed to survive substitution method Hard gluon must radiate off b- or t-quarks otherwise 3-jet hadronic top mass not reconstructed ν Possible solutions: Investigate method on truth level Tune down SUSY selection criteria to allow more events Use ATLFAST to produce more ttbar events

19. 21 april 2008NIKHEF ATLAS Outing A. Koutsman19 Continue studies to constrain and handle the tt2l background in 1-lepton SUSY: Substitution method with tuned down SUSY selection Develop selection criteria for an unbiased tt2l-enriched sample to be used in a simultaneous fit (use Top group knowledge) Change model parametrisation to distinguish SUSY from tt2l Use extra variables in the combined fit Repeat the whole procedure for 1-muon SUSY (so far 1-electron) Outlook for combined fit method Δφ(l,MET) last ATLAS T&P Week F.Spanom lj CSC Note1&2 D.Tovey Continue studies to constrain and handle the tt2l background in 1-lepton SUSY: Substitution method with tuned down SUSY selection Develop selection criteria for an unbiased tt2l-enriched sample to be used in a simultaneous fit (use Top group knowledge) Change model parametrisation to distinguish SUSY from tt2l Use extra variables in the combined fit Repeat the whole procedure for 1-muon SUSY (so far 1-electron) Study the combined fit method on 100pb -1 with possibility of putting tt2l into tt1l combinatorics Use FDR2 data with SU4 (low-mass high cross section point) model as practice for first data

20. 21 april 2008NIKHEF ATLAS Outing A. Koutsman20 CSC Study targeted at 1fb -1 of data. Will have much less data in 2008 (2009…) Now turning to studies on what can be learned from 10 -100 pb -1 of data Study backgrounds with relaxed selection See to which extent high cross-section SUSY points (e.g. SU4) can be seen or excluded with limited data (FDR2) Outlook for combined fit method

21. 21 april 2008NIKHEF ATLAS Outing A. Koutsman21 Back-up slides

22. 21 april 2008NIKHEF ATLAS Outing A. Koutsman22 Multidimensional method ‘Old’ MT Method: extrapolate W+jets/ttbar bkg from control region (low MT) to signal region (high MT) Main Idea: Improve method Try to use additional observables for extrapolation (e.g. m top ) Explicitly account for SUSY contamination in control region Key issues to understand - Amount of correlations between observables and significance of correlations - Amount and shape of SUSY in control region Multidimensional method Method MT S. Asai, Y. Kataoka, H. Okawa, Y.Tomishima Overestimated by factor 2.5

23. 21 april 2008NIKHEF ATLAS Outing A. Koutsman23 Shapes of backgrounds

24. 21 april 2008NIKHEF ATLAS Outing A. Koutsman24 Triggers Trigger-efficiencies (e mode): tt1ltt2lWSU1SU2SU3SU4 L1_XE1000.680.760.730.991.000.970.87 L1_EM25I L1_MU20 0.92 0.02 0.96 0.02 0.91 0.01 0.93 0.02 0.86 0.00 0.91 0.02 0.88 0.03 L2_4jet500.970.98 1.000.990.97 L2_e25i L2_mu20i 0.85 0.06 0.87 0.10 0.81 0.01 0.90 0.05 0.86 0.29 0.80 0.03 0.80 0.07 EF_jet1600.300.370.460.860.930.840.45 EF_2jet1200.220.300.330.780.860.680.30 EF_4jet500.650.670.680.831.000.860.66 EF_e25i EF_mu20i 0.75 0.06 0.78 0.06 0.68 0.01 0.80 0.05 0.86 0.29 0.74 0.03 0.74 0.07 EF_4jet50 || EF_e25i || EF_mu20i 0.910.930.920.961.000.950.92 EF_4jet50 || XE_100 || EF_e25i || EF_mu20i 0.960.990.971.00 0.99 4jet50 and missing E T trigger have high efficiency Single electron trigger efficiency ~80-90% Single muon trigger in e-mode ~0.01-0.05 Inclusive efficiency very high ~95-100% results comparable to previously shown

25. 21 april 2008NIKHEF ATLAS Outing A. Koutsman25 Results with substitution method tt2l events in 1-lepton SUSY tt1l  tt2l (misID substituted) events in 1-lepton SUSY tt1l  tt2l (tau-decay substituted) events in 1-lepton SUSY

26. 21 april 2008NIKHEF ATLAS Outing A. Koutsman26 Release 12 Samples W+0,1,2,3,4,5 partons: Wenu+nJets (n=2..5)#5223-5226 Wmunu+nJets (n=3..5)#8203-8205 Wtaunu+nJets (n=2..5)#8208-8211 T1 (MC@NLO) #5200: separate at truth-level between semi-leptonic (e, mu, tau) di-leptonic (ee, mumu, tautau, emu, etau, mutau) SUSY: SU1 #5401 SU2 #5402 SU3 #5403 SU4 #6400 SU6 #5404 SU8 #5406