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Experimental aspects of top quark physics Lecture #2

Experimental aspects of top quark physics Lecture #2. Regina Demina University of Rochester Topical Seminar on Frontier of Particle Physics Beijing, China 08/15/05. Outline. Invariant mass Template method to measure top mass Matrix element method Jet energy scale calibration on W-boson

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Experimental aspects of top quark physics Lecture #2

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  1. Experimental aspects of top quark physics Lecture #2 Regina Demina University of Rochester Topical Seminar on Frontier of Particle Physics Beijing, China 08/15/05

  2. Outline • Invariant mass • Template method to measure top mass • Matrix element method • Jet energy scale calibration on W-boson • Combined result • Constraint on Higgs mass • Control questions Regina Demina, Lecture #2

  3. Invariant mass • Top quark decays so fast there is no time to put it on a bathroom scale • We measure its mass through energy and momentum of its products: • tbW, Wqq’ • E(t)=E(b)+E(q)+E(q’) • P(t)=P(b)+p(q)+p(q’) • M2(t) = E2(t)-p2(t) • M, E, p in GeV Regina Demina, Lecture #2

  4. Challenges of Mtop Measurement Lepton+Jets Channel • Leading 4 jets combinations • 12 possible jet-parton assignments • 6 with 1 b-tag (b-tag helps) • 2 with 2 b-tags • Poor jet energy scale and resolution • Hard to find the correct combination Observed Final state Complicated final state to reconstruct Mtop Good b-tagging and jet energy scale and resolution and good algorithm to reconstruct Mtop Regina Demina, Lecture #2

  5. Template method • c2 mass fitter: • Finds top mass that fits event best • One number per event • Additional selection cut on resultingc2 Data Wbb MC Massfitter tt MC Signals/background templates Datasets Data Likelihoodfit Likelihood fit: Best signal + bkgd templates to fit datawith constraint on background normalization Result Regina Demina, Lecture #2

  6. Mass Fitter (event by event) • Try all jet-parton assignments with kinematic constraints, but assign b-tagged jets to b-partons • Select the rec. mass Mt from the choice of lowest c2 • Badly reconstructed Mt (c2 > 9 ) is removed Top mass isfree parameter All jets are allowed to be float according to their resolutions to satisfy that M(W+)=M(W-)=80.4 GeV, M(t)=M(t) Regina Demina, Lecture #2

  7. Templates for different number of tags More correct combination with b-tag Mt(GeV/c2) Mt(GeV/c2) Mt(GeV/c2) Mt(GeV/c2) Bkgd is large in the 0-tag Regina Demina, Lecture #2

  8. Signal templates for different masses • Samples: Herwig with Mtop = [130 to 230] GeV • Get analytical functions (2 Gaussian + gamma) of reconstructed mass, Mt as a function of true mass, Mtop • Fit parameters: linear depend. on Mtop Smooth PDFs (Mt | true Mtop) Mt(GeV/c2) Regina Demina, Lecture #2

  9. Result on Mtop Comb. –Log Likelihood Expected error Regina Demina, Lecture #2

  10. Top mass using matrix element method in Run I • Method developed by DØ (F. Canelli, J. Estrada, G. Gutierrez) in Run I Single most precise measurement of top mass in Run I Mt =180.1±3.6(stat) ±4.0(syst) GeV/c2 Systematic error dominated by JES 3.3 GeV/c2 With more statistics it is possible to use additional constraint on JES based on hadronic W mass in top events – in situ calibration Regina Demina, Lecture #2

  11. Matrix element method • Goal:measure top quark mass • Observables:measured momenta of jets and leptons • Question:for an observed set of kinematic variables x what is the most probable top mass • Method: start with an observed set of events of given kinematics and find maximum of the likelihood, which provides the best measurement of top quark mass • Our sample is a mixture of signal and background Regina Demina, Lecture #2

  12. Matrix Element Method W(x,y) is the probability that a parton level set of variables y will be measured as a set of variables x probability to observe a set of kinematic variables x for a given top mass dnσ is the differential cross section Contains matrix element squared f(q) is the probability distribution than a parton will have a momentum q Normalization depends on mt Includes acceptance effects Integrate over unknown q1,q2, y q b q’ t t Regina Demina, Lecture #2

  13. Transfer functions (partonjet) • Partons (quarks produced as a result of hard collision) realize themselves as jets seen by detectors • Due to strong interaction partons turn into parton jets • Each quark hardonizes into particles (mostly p and K’s) • Energy of these particles is absorbed by calorimeter • Clustered into calorimeter jet using cone algorithm • Jet energy is not exactly equal to parton energy • Particles can get out of cone • Some energy due to underlying event (and detector noise) can get added • Detector response has its resolution • Transfer functions W(x,y) are used to relate parton energy y to observed jet energy x Regina Demina, Lecture #2

  14. Top ID in “lepton+jets” channel • 2 b-jets • Lepton: electron or muon • Neutrino (from energy imbalance) • 2 q’s – transform to jets of particles • Note that these two jets come from a decay of a particle with well measured mass – W-boson – built-in thermometer for jet energies Regina Demina, Lecture #2

  15. JES in Matrix Element • All jets are corrected by standard DØ Jet energy scale (pT, h) • Overall JES is a free parameter in the fit – it is constrained in situ by mass of W decaying hadronically • JES enters into transfer functions: Regina Demina, Lecture #2

  16. Signal Integration • Set of observables – momenta of jets and leptons: x • Integrate over unknown • Kinematic variables of initial (q1,q2) and final state partons (y: 6 x3 p) = 20 variables • Integral contains 15 (14)d-functions for e(m)+jets • total energy-momentum conservation: 4 • angles are considered to be measured perfectly: 2x4 jet +2 lepton • Electron momentum is also considered perfectly measured, not true for muon momentum: 1(0) • 5(6) dimensional integration is carried out by Vegas • The correspondence between parton level variables and jets is established by transfer functionsW(x,y) derived on MC • for light jets (from hadronic W decay) • for b-jets with b-hadron decaying semi-muonically • for other b-jets • Approximations • LO matrix element • qqttprocess only (no gluon fusion – 15%) Regina Demina, Lecture #2

  17. Background integration • W+jets is the dominant background process • Kinematics of W+jets is used as a representation for overall background (admixture of multijet background is a source of systematic uncertainty) • Contribution of a large number of diagrams makes analytical calculation prohibitively complex • Use Vecbos • Evaluate MEwjjjj in N points selected according to the transfer functions over phase space • Pbkg- average over points Regina Demina, Lecture #2

  18. Sample composition Lepton+jets sample • Isolated e (PT>20GeV/c, |h|<1.1) • Isolated m (PT>20GeV/c, |h|<2.0) • Missing ET>20 GeV • Exactly four jets PT>20GeV/c, |h|<2.5 (jet energies corrected to particle level) Use “low-bias” discriminant to fit sample composition • Used for ensemble testing and normalization of the background probability. • Final fraction of ttbar events is fit together with mass Regina Demina, Lecture #2

  19. Calibration on Full MC lepton+jets Regina Demina, Lecture #2

  20. Mt=169.5±4.4 GeV/c2 JES=1.034±0.034 calibrated calibrated DØ RunII Preliminary expected: 36.4% Regina Demina, Lecture #2

  21. Systematics summary Regina Demina, Lecture #2

  22. B-jet energy scale • Relative data/MC b/light jet energy scale ratio • fragmentation:+-0.71 GeV/c2 •  different amounts of p0, different p+ momentum spectrum •  fragmentation uncertainties lead to uncertainty in b/light JES ratio • compare MC samples with different fragmentation models: • Peterson fragmentation with eb=0.00191 • Bowler fragmentation with rt=0.69 • calorimeter response: +0.85 -0.75 GeV/c2 • uncertainties in the h/e response ratio • + charged hadron energy fraction of b jets > that of light jets •  corresponding uncertainty in the b/light JES ratio • Difference in pT spectrum of b-jets and jets from W-decay: 0.7 GeV/c2 Regina Demina, Lecture #2

  23. Gluon radiation q q e n • Extra jets from initial/final state gluons • 80% of the time, leading 4 jets correspond to 4 partons (qqbb) • Final effect on top mass0.34 GeV/c2 Regina Demina, Lecture #2

  24. Result and cross checks • Run II top quark mass based on lepton+jets sample: Mt=169.5 ±4.4(stat+JES) +1.7-1.6 (syst) GeV/c2 • JES contribution to (stat+JES) 3.3 GeV/c2 • Break down by lepton flavor • Mt(e+jets)=168.8 ±6.0(stat+JES) GeV/c2 • Mt(m+jets)=172.3 ±9.6(stat+JES)GeV/c2 • Cross check W-mass Regina Demina, Lecture #2

  25. Summary of DØ Mt measurements DØ Run II preliminary • Statistical uncertainties are partially correlated for all l+jets Run II results Regina Demina, Lecture #2

  26. Combination of Tevatron results JES is treated as a part of systematic uncertainty, taken out of stat error Regina Demina, Lecture #2

  27. Combination • Mt=172.7±2.9 GeV/c2 • Stat uncertainty: 1.7GeV/c2 • Syst uncertainty: 2.4GeV/c2 • hep-ex/0507091 • Top quark Yukawa coupling to Higgs boson • gt=Mt√2/vev=0.993±0.017 Regina Demina, Lecture #2

  28. Top Quark Mass: Motivation t H W W W W MW  mt2 MW  ln(MH) b CDF&D0 RUNII • Fundamental parameter of the Standard Model. • Important ingredient for EW precision analyses at the quantum level: which were initially used to indirectly determine mt. After the top quark discovery, use precision measurements of MW and mt to constrain MH. Regina Demina, Lecture #2

  29. What does it do to Higgs? • MH=91+45-32GeV/c2 • MH<186 GeV/c2 @95%CL 68% CL MW,GeV/c2 MH,GeV/c2 Mt,GeV/c2 Regina Demina, Lecture #2

  30. Projection for uncertainty on top quark mass Assumptions: • only lepton+jets channel considered • statistical uncertainty normalized at L=318 pb-1 to performance of current analyses. • dominant JES systematic is handled ONLY via in-situ calibration making use of MW in ttbar events. • remaining systematic uncertainties:include b-JES, signal and background modeling, etc (fully correlated between experiments) Normalized to 1.7 GeV at L=318 pb-1. • Since most of these systematic uncertainties are of theoretical nature, assume that we can use the large data sets to constrain some of the model parameters and ultimately reduce it to 1 GeV after 8 fb-1. Regina Demina, Lecture #2

  31. High statistics (LHC) approach In 100fb-1 about 1000 signal events is expected No jes systematics !!! Regina Demina, Lecture #2

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