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Trento University & INFN

Top Mass and Cross Section at the Tevatron. Ambra Gresele. Trento University & INFN. IFAE, Pavia 19-21 April 2006. Tevatron Run II. 1fb -1 per experiment on tape ~1.3 fb -1 delivered luminosity Peak luminosity 1.7 x 10 32 cm -2 s -1 Presented here: ~ 700 pb -1.

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Trento University & INFN

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  1. Top Mass and Cross Section at the Tevatron Ambra Gresele Trento University & INFN IFAE, Pavia 19-21 April 2006

  2. Tevatron Run II • 1fb-1 per experiment on tape • ~1.3 fb-1 delivered luminosity • Peak luminosity 1.7 x 1032cm-2s-1 • Presented here: ~ 700 pb-1 Goal of Run II per experiment:

  3. 15% 85% Top production and decay • Production: mainly • Decay: BR(t  W b) ~ 100% • All-hadronic: 44% • Lepton + jets: 30% • Dilepton: 5% di-lep all-had lep+jets

  4. Why measuring the top mass? • Top massisrelated to W, Higgs (and other observables) • When all W, t, H measured: test SM (and to test you have to measure well…) • Radiative corrections affect observables Game of ElectroWeak fits

  5. Mass Measurement Methods Build likelihood from matrix element(s), PDFs and transfer functions (connect quarks and jets) Pick a test statistic (e.g. recontructed mass) Template Method Matrix Element Method Create “templates” using events simulated with different mt values (+background) Integrate over unmeasured quantities (e.g. quark energies) Perform maximum likelihood fit to extract measured mt Calibrate measured mt and uncertainty using simulation Less assumptions / robust measurement Better statistical precision expected w/ using more info All methods in all channels are well validated by a blind sample

  6. CDF Template Method: l+jets • W->jj dijet mass distribution is a resonance • Resonance peaks stands out at 80.4 GeV/c2 • Sensitive to shifts in jet energy scale (JES) • Datasets • Data • Background MC • ttbar MC mjj template Mtop template mtopreco Mass fitter • Mass Fitter • Finds best top mass and jet-parton assignment • One # per event based on overconstrained system • Additional selection cut on resultingc2 Parameterize Likelihood Fit • Likelihood Fit • Fit mtopreco and wjj distributions in data to sum of signal and background parametrizations • Constrain background and JES with prior knowledge • Parametrizations • For both templates, as a function of top mass and JES • For both signal and background gives JES, top mass!

  7. CDF Template Results (I) 680 pb-1 mtreco templates w/ fit overlaid mjj templates w/ fit overlaid Mtop = 173.4 ± 2.5 (stat. + DJES) GeV/c2 Miscalibrationin units of sc,external calib. DJES= -0.3 ± 0.6 (stat. + Mtop) sc 318 pb-1: Mtop = 173.5 +3.9-3.8(stat. + DJES) GeV/c2

  8. CDF Template Results (II) Likelihood contours in Mtop-DJES plane

  9. CDF Matrix Element Method: dileptonic channel The complete information contained in an event (x) regarding the top mass can be expressed as the conditional probability: If the momentum of each parton could be exactly deduced from final-state particles, the calculation of d/dx would be simple. Instead we must integrate over quantities which are unknown and, in addition, quark energies are not directly measured. The total expression for the probability of a given pole mass for a specific event can be written:

  10. 750 pb-1 CDF Matrix Element results • Best measurement in challenging dilepton channel • Could reach 2 GeV (stat)sensitivity by end of run II

  11. 370 pb-1 Template Method: l+jets Event-by-event Mtop by c2 fit Use 69 candidateevents with 1 b-tagged jet Mtop = 170.6  4.2 (stat)  6.0 (syst) GeV/c2

  12. Combination of CDF and D0 Top Mass

  13. Top Pair Production Cross Section sinel=70mb so 7M events/s at 1032/cm2s but 1 tt in 1010 events • s ttis crucial: • Check of perturbative QCD • Window to NP • Look at all possible channels • Starting point for all properties analysis • tt is background of searches M. Cacciari et al. JHEP 0404:068 (2004) N. Kidonakis and R. Vogt, Phys. Rev. D 68 114014 (2003) Need better quality

  14. Dilepton Channel • Backgrounds: • Physics: WW/WZ/ZZ, Z tt • Instrumental: fake lepton • Selection: • 2 leptons ET>20GeV with opposite sign • >=2 jets ET>15GeV • Missing ET>25GeV (and away from any • jet) • HT=pTlep+ETjet+MET>200GeV • Z rejection s(tt) =  8.3 ± 1.5 (stat) ± 1.0 (syst) + 0.5 (lumi) pb

  15. Selection: 1 lepton with pT>20GeV/c >=3 jets with pT>15GeV/c Missing ET>20GeV Backgrounds: W+jets QCD Lepton+Jets Channel: Kinematics energetic discriminate central spherical • 7 kinematic variables in neural net binned likelihood fit s(tt) =  6.0 ± 0.6 (stat) ± 0.9 (syst) pb

  16. Selection: >=6 jets with pT>15GeV/c >=1 b tagged NN discriminant > 0.9 Huge QCD background ! All Hadronic Channel discriminate • 6 kinematic variables in neural net

  17. Summary of Top Pair Production Cross Sections

  18. The top mass is now know with an accurancy of 1.3%, limited by the systematic uncertainties which are dominated by the jet energy scale. With in situ JES calibration, dominant “systematic” now scales as 1/sqrt(N). Expect 2 GeV/c2 precision by LHC turn-on. All the cross section measurements are consistent with SM Conclusions

  19. Back up slides

  20. History of Mtop measurement • Top first observed at CDF & D0 in 1995. Tevatron’s Run I: ~110pb-1 • Run I Average: Mtop = 178.0  4.3 GeV/c2

  21. Jet Energy Corrections • The jet energy scale (JES) is the major source • of uncertainty in the top quark mass • measurement and inclusive jet cross section • Absolute scale: the jet energy measured in the • calorimeter needs to be corrected for any • non-linearity and energy loss in the un-instrumented • regions of each calorimeter (from MonteCarlo) • Relative scale: since the central calorimeters • are better calibrated and understood, this scales • the forward calorimeters to the central calorimeter • Scale (is obtained using Pythia and data di-jet events) • Multiple interactions: the energy from different • ppbar interactions during the same bunch crossing • falls inside the jet cluster (from minimum bias data) • Underlying event: is defined as the energy • associated with the spectator partons in a hard • collision event. • Out-of-cone: corrects the particle-leve energy • for leakage of radiation outside the clustering cone • used for jet definition

  22. The total systematic uncertainties in the central calorimeter • are the same order than RunI (significant improvement with • respect 2004 analyses) • Big improvements for plug jets with respect to RunI due • to new detectors ~3% jet pT uncertainty in top events

  23. Matrix Element Technique: dilept • Harder to reconstruct Mtop in dilepton events: two neutrinos make system underconstrained • Determination of probability is similar to l+jets • No W resonance  no fit for JES • Approximations havesignificant effect • MC calibration essential • Correct fitted mass for slope 0.85 • Correct for pull width of 1.49

  24. Matrix Element Technique: l+jets • Calibrate method against MC samples • Shows unbiased measurement • Error are rescaled to account for observed pull width—due to approximations in integration

  25. 750 pb-1 Matrix Element Results • JES here is constant multiplicative factor • Edata = EMC/JES • JES = 1.02 ± 0.02 • Consistent with template method • Virtually identical sensitivity with fewer events!

  26. Combination of CDF results • Use BLUE (Best Linear Unbiased Estimator) technique • NIM A270 110, A500 391 • Accounts for correlations in systematics • Stat correlations in progress • So far only combine measurements on independent datasets.

  27. 680 pb-1 Decay Length Technique B hadron decay length  b-jet boost  Mtop • Difficult, measure slope of exponential • But systematics dominated by tracking effects small correlation with traditional measurements! • Statistics limited now • Can make significant contribution at LHC

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