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New Results from D0 on the W width, charge asymmetry and on gauge couplings

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  1. New Results from D0 on the W width, charge asymmetry and on gauge couplings Sarah Eno (U. Maryland)for the D0 Collaboration Wine & Cheese, FNAL

  2. Outline W discovered in 1983. 26 years of W physics! How well do we know the W? • Updated measurement of the muon charge asymmetry from W decays (4.9 fb-1) (How is the W made?) • New limits on trilinear gauge boson couplings (0.7-1 fb-1) (How well does it play with its siblings?) • W width (1 fb-1) (What’s its life expectancy?) Run IIa Run IIb Wine & Cheese, FNAL

  3. D0 Detector Liquid-argon sampling calorimeters Central (CC)|η| < 1 and Endcap (EC)‏ Coverage: |η| < 4.2 Silicon Microstrip Tracker (SMT) |η|<3 Central Fiber Tracker (CFT) |η|<2 2 T magnetic field Muon system Drift chambers and scintillatorcounters 1.8 T toroids |η|<2 Junjie Zhu 3

  4. Data Samples Many, many thanks to the accelerator division!! Wine & Cheese, FNAL

  5. W How are W’s made? Wine & Cheese, FNAL

  6. Muon asymmetry u quark momentum distribution (in proton) harder than d. W+ tends to go along proton direction, the W- in the antiproton direction. W asymmetry arXiv: 0901.0002 x W rapidity At Tevatron energies, for W’s 0.0017<x<1 at LO. Wine & Cheese, FNAL

  7. Muon asymmetry Since can not reconstruct pZof the neutrino, measure muon charge asymmetry instead.* Muon asymmetry influenced by W rapidity asymmetry but also by polarization and left-handed couplings of the W and the V-A structure of the W decay. Cartoon stolen from CDF web site * For a method of indirectly reconstruction the rapidity, see CDF, Phys. Rev. Lett. 102, 181801 (2009) Wine & Cheese, FNAL

  8. Muon asymmetry Muon asymmetry is more similar to W asymmetry for high PTmuons from low PT W’s. Wine & Cheese, FNAL

  9. Muon charge asymmetry New D0 result, using 4.9 fb-1, updates previous results. Most recent published results are: • D0: Measurement of the Muon Charge Asymmetry from W Boson Decays, Phys. Rev. D77, 011106 (2008), 0.3 fb-1 • D0: Measurement of the Electron Charge Asymmetry, Phys. Rev. Lett 101, 211801 (2008), 0.7 fb-1 • CDF: W boson charge asymetryvs W rapidity, Phys. Rev. Lett. 102, 181801 (2009), 1 fb-1 • CDF: lepton charge asymmetry, Phys. Rev. D71, 051104, 0.17 fb-1 Wine & Cheese, FNAL

  10. Selection Wine & Cheese, FNAL

  11. Challenges • As long as they are charge independent, efficiencies, acceptances, and luminosity cancel in the ratio (frequent reversal of solenoid and toroid polarities helps) • Backgrounds can dilute asymmetry • Charge mis-identification is a potential problem that can dilute asymmetry • Need to correct for momentum smearing since asymmetry depends on muon PT Wine & Cheese, FNAL

  12. Backgrounds • Multijet background estimated using matrix method based on isolation. Background efficiency (εB(η,PT)) estimated using events with low MET (<10 GeV) and a jet with PT>10 GeV. Systematics on εB estimated by varying cuts used to reduce W contamination. • W/Z backgrounds estimated from MC (PYTHIA) normalized to NNLO cross section. Monte Carlo statistics dominant source of uncertainty. • Background fractions binned in eta and muon PT. Only 1 bin in eta for eta>1.6 Wine & Cheese, FNAL

  13. Muon Track Muon Jet Charge misidentification Run IIa, 3 same-sign Z’s out of 48452 Run IIb, 14 same-sign Z’s out of 120417 negligible Wine & Cheese, FNAL

  14. Momentum smearing Because of finite momentum resolution, bins in reconstructed PT contain events from other PT bins. Since the shape of this asymmetry depends on PT, correction is needed. Uncertainty determined by varying the momentum resolution within uncertainties. Wine & Cheese, FNAL

  15. Results Data sample is large enough that errors on asymmetry are smaller than spread from PDF uncertainties. Will be useful for global PDF fits and reduce PDF uncertainty on W mass and width. Wine & Cheese, FNAL

  16. Results For muon PT> 35 GeV. Systematic uncertainties completely dominated by muon momentum resolution correction. Wine & Cheese, FNAL

  17. W How well does the W play with its siblings? Wine & Cheese, FNAL

  18. Charged triple gauge couplings Charged Triple Gauge Couplings (TGC) Probed by WW, WZ, and Wγ production 14 parameters at LO • SM • couplings that respect CP, SU(2)LxU(1)Y and EM gauge invariance • assume equal couplings for ZWW and γWW respecting CP Wine & Cheese, FNAL

  19. New from D0 WZ final state currently only accessible at the Tevatron. Wine & Cheese, FNAL

  20. Evidence for WW or WZ to lνjj* Phys. Rev. Lett. 102, 161801 (2009) Wine & Cheese, FNAL

  21. Anomalous couplings • affect total cross section • affect kinematic distributions. The PT of the dijet system is particular sensitive. WW cross sctaTGC/SM Δκ hadronic W PT ΔΔ WZ cross sctaTGC/SM hadronic W rapidity Δκ λ Wine & Cheese, FNAL SU(2)LxU(1) conserving aTGC

  22. aTGC Simulation: SM events produced with PYTHIA reweighted according to generator-level PT and ΔR using MC@NLO-based weights. Anomalous couplings distributions are generated by reweighting SM predictions using fit to ratio of the (LO) HZW* generator with and without aTGC. X is the PT of the dijet system * Phys. Rev. D 41, 2113 (1990) Wine & Cheese, FNAL

  23. Data: WW or WZ to lνjj Wine & Cheese, FNAL

  24. Limits See arXiv:0907.4398 SU(2)LxU(1)Y SU(2)LxU(1)Y equal couplings (γWW=ZWW) SU(2)LxU(1)Y Wine & Cheese, FNAL

  25. aTCG combining channels Wine & Cheese, FNAL

  26. aTGC Limits combining channels WW→lvlv WW lvjj WZ→lvll Wγ→lvγ Wine & Cheese, FNAL

  27. Uncertainties Type I: affects only normalization Type II: can change shapes of kinematic distributions as well Most important systematics are background cross sections and luminosity. Incorporating the systematic uncertainties degrades the limits by 30%. Systematics handled using methodology/code from W. Fisher, FERMILAB-TM-2386-E Wine & Cheese, FNAL

  28. aTGC Limits arXiv:0907.4952 Can be interpreted as measurements of the magnetic dipole and quadrupole moments. x2-x3 less sensitive to combined LEP results. Comparable sensitivity to an individual LEP exp. Wine & Cheese, FNAL

  29. W What’s the W’s life expectancy? Wine & Cheese, FNAL

  30. W Width Although one of the best-predicted, one of the least well-measured properties of the W. Current world average is : 2.050± 0.058 GeV (2.8% measurement) Due to insensitivity to “Oblique” corrections, expected to agree with SM prediction almost regardless of new physics. Rosneret al. Wine & Cheese, FNAL

  31. New from D0 • New measurement with 1 fb-1 of data • previous highest luminosity measurement from CDF (Phys. Rev. Lett. 100, 071801 (2008), 0.35 fb-1 • Using same data samples, MC simulations, and much of the same methodology as recent D0 W mass measurement, arXiv:0908.0766, submitted to Phys. Rev. Lett. Wine & Cheese, FNAL

  32. W transverse mass Mass width Width, to LO, is proportional to the fraction of events at high MT Wine & Cheese, FNAL

  33. W basics Two objects are measured in the detector: Lepton & Hadronic recoil (u). Neutrino is vector sum of lepton and recoil. Wine & Cheese, FNAL

  34. Event Selection Wine & Cheese, FNAL

  35. Outline Need Monte Carlo simulation to predict shapes of these observables for given width hypothesis NLO event generator : DØ uses ResBos [Balazs, Yuan; Phys ReV D56, 5558] + Photos[Barberio, Was; Comp Phys Com 79, 291] for W/Z production and decay: O(108) events + Parameterized detector model Reweighted using relativistic BW to produce W transverse mass templates + Detector calibration backgrounds data For more details, see talk by Jan Stark, FNAL Wine & Cheese, Mar. 20, 2009 • binned likelihood fit • data and template normalized to same area for MT<100 GeV • fit to high MT region (MT>100 Gev) gives width Model tested via a detailed “MC closure” test. As with mass, “blind” analysis. Wine & Cheese, FNAL

  36. Sensitivity 2 1 3 3 Wine & Cheese, FNAL

  37. Electron energy scale Same as for W mass measurement eta = 0 (normal incidence)‏ eta = 1 dE/dX0 (arbitrary units)‏ DEAD DEAD EM1 EM2 EM3 EM4 EM1 EM2 EM3 EM4 FH1 depth in radiation lengths (X0)‏ 4 X0 of dead material in front of the calorimeter made understanding the scale challenging. For more details, see talk by Jan Stark, FNAL Wine & Cheese, Mar. 20, 2009 Wine & Cheese, FNAL

  38. Tuning dead material on longitudinal shower shape Before tuning of material model: After tuning of material model: EM1 EM2 Fractional energy deposits, electrons with || < 0.2 EM1 EM2 Fractional energy deposits, electrons with || < 0.2 EM3 EM4 EM3 EM4 Wine & Cheese, FNAL

  39. Final Scale with Z’s After having corrected for the effects of the uninstrumented material: final energy response calibration, using Z ee, the known Z mass value from LEP: Emeasured =αxEtrue +β Use energy spread of electrons in Z decay to constrainαandβ. Result: α= 1.0111 ± 0.0043 β= -0.404 ± 0.209 GeV correlation: -0.997 Uncertainty dominated by Z statistics Wine & Cheese, FNAL

  40. Selection Efficiency Need to carefully model any dependence of the electron identification efficiency on the PT of the electron that might sculpt the shape of the MT distribution (instead of just changing the normalization). Because of the kinematics, the PT can correlate with other kinematic quantities that affect the identification efficiency. • Electron identification efficiencies affected by: • geometry (z of primary vertex, distance from module boundary in phi and eta) • electron PT • photon final state radiation • hadronic activity in the event • correlated with electron PT through W decay kinematics • scales with component parallel to electron direction (u||) • also scales with the magnitude of the overall activity in the event (Scalar ET)

  41. Electron ID efficiencies Track match efficiency versus eta and primary vertex z Overall identification efficiency versus u|| (data versus MC) Wine & Cheese, FNAL

  42. Dependence on electron PT electron PT electron PT Check of dependence of shower shape efficiency on electron PT. Black data, red: fast MC. The shape of the dependence is consistent with being the same. Wine & Cheese, FNAL

  43. Uncertainties on efficiency Most important is dependence on electron PT. Determined by comparing efficiency versus PT from Z->ee events to that from fast simulation. D0 Preliminary Compare data and MC for Zee for efficiency versus SET and electron PT and for efficiency versus eta and electron PT and look for evidence of slope. Compatible with no slope. Wine & Cheese, FNAL

  44. Modeling the Recoil No uT cut Events at high transverse mass are from off-shell W’s and from high PT W’s with recoil underestimated. • Transverse mass spectra from • the generator level (Red histogram), • electron energy response/resolution Included (Blue histogram), • recoil response (scale of 0.6) and resolution included (Green histogram), • MET resolution due to zerobias events included (Light blue histogram), • hadronic scale is set to 1 and also met resolution due to zerobias events included (Black histogram). Wine & Cheese, FNAL

  45. Modeling the recoil As seen in the detector Theorist view Cartoon version Measured “recoil” includes ISR, Underlying event, pileup, detector noise. Wine & Cheese, FNAL

  46. Two Recoil Methods The recoil library method Overlay recoils taken from the Z data on MC W’s arXiv: 0907.3713 Wine & Cheese, FNAL

  47. Recoil Library Method D0 MC D0 MC D0 MC Wine & Cheese, FNAL

  48. Recoil Library Method Map also includes total hadronic activity to use with electron ID dicing Wine & Cheese, FNAL

  49. Recoil Library Method Use Bayesian method of unfolding* to produce weights that can be used when assigning a measured recoil to a bin in true boson PT Note this method has no tunable parameters * G. D’Agostini, NIM A362, 487 (1995) Wine & Cheese, FNAL

  50. Recoil Library Using library without unfolding After unfolding Wine & Cheese, FNAL