The Measurement of the W mass at LEP

1. The Measurement of the W massat LEP XXXIX Recontres de Moriond, April 2004 Ann Moutoussi, CERN

2. Outline • Introduction: the Standard Model and MW • Measurement of MW: • Direct reconstruction • Systematic errors • QCD related errors • Results and conclusions

3. W W W W H t Mw within the Standard Model Mw can be computed • at Born level from a, Mz , GF • Higher order radiative corrections involve Mt, MH: e.g O(a, as ,Mz , GF , Mtop, Mhiggs) Precision measurements of Mw check the prediction If consistent > SM still OK, Use measurements to predict Mhiggs If not consistent > Hints for New Physics?

4. No update since last winter The LEP goal for MW PP Colliders80.454 ±0.059GeV/c2 EW fits (LEP/SLD)80.373±0.033GeV/c2 EW Fits (LEP/SLD) with Mtop80.378±0.023GeV/c2 LEP Goal:precision of ~40 MeV …Very difficult task.. • First phase optimise statistical power of analysis • Last years fight known and new systematics!

5. Hadronic (4q) Semileptonic (qqln) Leptonic q q l n n l q q q l q n 44% 46% Low Mw sensitivity e+e- W+W- • ~40K events in total W decay modes: Leptonic: W ln (32%) Hadronic:W  qq (67%)

6. Mreco MW measurement Event-by-event reconstruction of the invariant masses of W decay products • Identify and best reconstruct leptons (e,m,tau) • Best Cluster jets and measure energy and direction • Statistical sensitivity limited by resolution of jet/lepton energies and momenta • Can improve resolutions using the knowledge of ECM and Energy-Momentum conservation optionally: equal W mass constraint

7. Minus : • Particle to Jet association • mixing between jets from different Ws • smearing of Mw distribution Statistics: Optimise clustering algorithms • Jet-Jet association to a W • Wrong pair • Loss of all Mw information • Statistics: Optimise pairing algorithms(~85% correct pairing) Mw Reconstruction(1) qqqq Plus: No unmeasured particles, Fully constrained system

8. Mw Reconstruction(2) qq ln • Plus: • Only two jets • no loss of information due to particle mixing or combinatorial bkg • Considered golden channel • Minus : • Neutrino • 3 unknowns • only 2 constrains fit

9. After the kinematic Fit: Mreco True Mw qq ln Mreco Mjet Mreco still far from underlying Mw distribution Reconstructed Mw

10. W Mass extraction • To relate Mreco to Mw use Monte Carlo events • Fit Mreco with analytical function(eg BW) and then correct it using MC or • Compare Mreco distribution to MC predictions at different Mw values In practice, only one MC sample is generated, at a reference value MWref. Predictions at other values of MW are obtained by re-weighting the events Assume MC events are identical to data, except from Mw!  Discrepancies between data and MC are sources of systematic errors

11. Systematics

12. Systematics(largest) (Expected final statistical error for LEP  25 MeV) Source Currently/MeV • LEP Energy determination 17 • Detector Simulation • Jet & Leptons energy/direction 15 • QCD simulation • Jet Fragmentation 18 • Jet-Jet interactions(4q) 93 Unacceptable!!

13. q W- e- _ q e+ W+ q _ q Simulation of a MC event(1) Fragmentation (quarks  hadrons): • parton shower (large Q2, pQCD) • hadronisation (phenomenological) Available models: Jetset, Herwig, Ariadne. All models: • need to be tuned to data(generally Z  qq, LEP1). • Simulate Data ~as well/bad! Jetset globaly better used as Reference MC from all LEP experiments

14. Hard process: e+e-4q q • parton shower (large Q2, pQCD) W- • hadronisation (phenomenological) e- _ q d~0.1 fm e+ W+ q _ q • Colour reconnection: hadronic interaction between W decays • d(W+,W-) < 1 fm Simulation of a MC event(2) • Fragmentation (quarks  hadrons): • Interconnection effects • Bose-Einstein correlations: momenta of identical bosons tend to be correlated. Not included in reference MC

15. W1 Any evidence for such effects? Look for BE in data W2 Bose-Einstein Correlations (BEC) • Intra-W :BEI not relevant for Mreco • Bettwen-W’s:BEB: could cause wrong particle-dijet association • Mw shifts ~ 35 MeV(LUBOEI) Main Observable: distance in momentum space between pairs of charged pions: Q2=(pi-pj)2

16. eg BEB BEI Final DMWdown from ~35 to ~15 MeV Observation BEC in W+W- events • Inter W, BEI confirmed • Between W’s, BEB, disfavoured

17. CR models • Based on Ariadne, AR2: • Based on HERWIG (Herwig-CR) DMW ~ 70MeV • Based on the JETSET string model:SK1: • it has a free parameter kI controlling the reconnection probability P DMW ~ 40MeV P=1 DMW ~400MeV P=0.5 DMW ~115MeV P=0.3 DMW ~ 50MeV DMWFar too large! Any evidence for such effects/models? Look for CR effects in data

18. Data • -SK1(extreme parameter) No CR: CR: A -Jetset W- W- C W+ W+ D B • The ratio of particle flow between the inter and intra-W regions is built: (A + B) / (C + D) The particle flow analysis • Most CR models predict a modified particle flow in W+W- events: • Measurement sensitive only to extreme scenarios, i.e SK1 with high CR probability and not so to Herwig, Ariadne

19. preferred value: kI=1.18, P~0.5 • kI valueexcluded at 1s  value used for CR studies and DMW evaluation= ~100 MeV! (CR P) Do something to make analyses more robust! LEP results from particle flow Fit LEP measurement for free parameter k (CR P)

20. Towards a less CR sensitive analysis:

21. Proposed solution: modify clustering algorithm to dismiss information from those particles. • “purer” information • loss of statistical precision The logic • Interconnection effects mainly occur in the inter-W region and between soft particles Many variations of jet algorithms (cones, pcuts) have been considered aiming for the best combination of Robustness against reconnection effects with minimal information loss

22. Algorithms simple and intuitive measurement less sensitive to CR independent of specific model implementation Reduction of DMW Good reduction factors for all available models! e.g for R=0.5, 2.3-2.6 smaller DMW with ~25% increase of stat. error:

23. e.g DELPHI, Cone algorithm R=0.5 DELPHI preliminary: • Exclude extreme scenarios. • Minimum at ~1.3, P~0.5 k A by-product: Measure CR? • The difference between MW measured with cone/pcut and standard analyses (DMC-S) is sensitive to CR effects:

24. Results

25. ± ± 80.426±0.034 ± ± ± LEP Combination 80.378±0.023 Mw=80.412±0.042 GeV/c2 ± Mw GeV Results qq ln 80.411±0.032(stat) ±0.030(syst)GeV/c2 qqqq 80.420±0.035(stat) ±0.101(syst)GeV/c2 (Weight of qqqq in combination: 0.09%)

26. Mw Mtop GeV mH Mw and Mtop, MHiggs Mw wants a low Higgs Mass...

27. After all this work…. • Ongoing LEP efforts to find optimal jet clustering and make qqqq measurement robust against CR • If all experiments use them • Total error in hadronic channel: ~110  ~60 MeV. • Total error from ~42 to ~39 MeV • Weight of hadronic channel in combination: 0.09%  0.29%. *Learn something about Final State Interactions too...* • Detector Systematics still an issue after all these years.. • Final values for Summer?!?!

28. Results qq ln qqqq Mw=80.411±0.032(stat) ±0.030(syst)GeV/c2 Mw=80.420±0.035(stat) ±0.101(syst)GeV/c2 Combined: Mw=80.412±0.042 GeV/c2 Weight of qqqq in combination: 0.05% 

29. Detector Simulation • As measurement is calibrated using MC Systematic errors related to the detector arise from discrepancies in the detector simulation. • Most effort devoted to Jet Energy, Mass and Direction: Jet Energy (mass, multiplicity,etc) calibrated, checked and MC tuned using Z  qq events: • Clean enviroment, Ebeam~Ejet, • Jets back to back  well separated e.g Compare Ejet/Ebeam as a function of polar angle q , for Data and MC (ratio) for total energy, Ejet And for individual types of particles (Echarged, Ephotons, etc)

30. (Ejet/Ebeam)Data/MC (Ejet/Ebeam)Data/MC cosq cosq Jet Energy Simulation 2000 publication Preliminary results Towards final results Better: simulation of Calorimeter endcaps, photon energy calibration, treatment of small Q calorimeter measurements ,etc etc Small changes on Mw ~ size of calorimeter systematic

31. Data MC Charged2 qneut Jet2 qChar qq en Data-MC= -0.024±0.007 Jet1 rad Jet Direction simulation Test done with W events: Compare Data and MC DQ=qneutral-qChargerd, q being the dijet angle Jet1-Jet2 Charged1 • Collecting the full statistics allowed • relevant sensitivity • qq enbad surprise • Data different from MC • by 24mrad

32. Particles associated to a jet # Data MC qq en Angle to lepton/degrees The electron channel: qq en What could make neutral dijet Q be more open in Data than in MC? Look near the electron….. • EM shower of v.energetic electrons • not well simulated. • Existing algorithm to collect electrons cloud not adequate. New electron reconstruction Mw from qq enmoved by ~100 MeV…

33. WW production at LEP Theoretical precision ~0.5% Thanks to 2000 calculations RACOONWW, YFSWWwith improved O(a) corrections LEP measurement precision ~1% Very good agreement

34. Jet Mass Jetset Herwig Data 5 8 8 DMjet(12)/GeV DMjet1/GeV DMreco/GeV 4 4 2 0 0 0 Effect much smaller but ~20MeV 0 2 4 6 8 10 0 2 4 6 8 10 0 2 4 6 8 10 Dneutron Dneutron Dneutron Example: Jet Mass and Baryon # Jet Massenters into Dijet-Mass (Mjet12) and also shows some discrepancy between Data and MC Identical W  2q events, Hadronised with Jetset/Herwig Study DMjet1,DMjet12, DMreco Vs D (No of neutrons)

35. LEP Energy Kinematic fitthe absolute energy/momentum scale is calibrated by the LEP beam energy measurement • Ebeam measured from total bending field • Calibrated with resonant depolarization: • spin precession freq  Ebeam • intrinsic resolution ~ 200keV !! • only works up to 60GeV  extrapolation • At LEP2: • Error mainly from extrapolation. • Ebeam~20MeV (E/E~10-4!)  mW~17MeV …and will stay ~there

36. @ 91GeV ecm Z qq • = 6 GeV Peak=90.5GeV ALEPH: Energy resolution • Energy resolution for a calorimeter object adding ECAL + HCAL is: • Take into account particle ID to: • use momentum measurement of • tracks pointing to calorimeter objects • avoid double counting of energy. • apply specific calibrations. • build new objects with: Total Visible Energy (GeV)

37. Dq Df s =18mrad s =19mrad ALEPH: Jet Direction Jet direction information is based on tracks, addition of neutral objects improves resolution by 15% JetDq and Dfresolution

38. qCharged mrad qneut Z axis (qCharged -qneutral) Data/MC cos q Jet Direction simulation(1) Still at the Z pole: Difficult, as no refference (like Ebeam) Tests rely on “correct” position of tracks and check calorimeter objects by comparingqneutraltoqChargerdas a function ofqjet No significant effect, small systematic error But..

39. e+e- e+e- Angle to lepton/degrees The electron channel: qq en What is all this stuff there? Look near the electron…..at bhabha events.. Particles near an electron #

40. QCD models at LEP Available Models: All models: • need to be tuned to data(generally Z  qq, LEP1). • Simulate Data ~as well/bad! Jetset somewhat better used as Reference MC from all LEP experiments

41. Use Z  qq events from LEP1. Data and MC Energy and multiplicity distributions were compared as a function of angle to jet axis q Specific systematics for cones? • Cone and standard analysis can have different sensitivity to fragmentation: • cone could be more sensitive to angular distribution of particles inside jet No indications of new sources of systematics

42. Data Data JETSET JETSET HERWIG HERWIG Data/JETSET HERWIG/JETSET Data/JETSET HERWIG/JETSET Angular distributions • Jet Energy: • Velocity:

43. Data JETSET Dq qS - qC qS qC Inter-jet angle in W+W- events • M212 ~ 2E1E2(1 - cosq12) • Z  qq events too different  semileptonic W+W- events used. • independent sample • free from CR effects • Variable checked: For Data and Jetset No indications of new sources of systematics

44. Conclusions(2) • Statistical errors exceeded all expectations (analyses really pushed to the limit!) • Systematic errors dominant • A lot of effort invested to fight against the larger known (eg Colour Recconection) lead to more understanding of the causes and the design of promisingly more robust analyses • Detector Systematics. The precision required from Mw exceeds this of all previous analyses. Jets and the simulation (especially of neutral part) cannot rely on LEP1, more detail needed (10MeV!) • Effort put on guessing those unexpected systematics!

45. Fragmentation • “Traditionally”: • Compare different models: (various dX) • pass them through full analysis : Max DMw~20 MeV (Jetset-Herwig) But.. DMw is due to dX between Data & reference MC(Jetset) Latest work: • Identifyfragmentation variable, X, with significant dMw/dx • EstimatedX(Data-MC) at some control sample, eg Z events • Propagate dX(Data-MC) in refference MCMass distributionDMw

46. Method for MW measurement

47. Introduction The Standard Model and Mw

48. QCD effects on MW

49. Fragmentation • If all particles are detected and associated to Ws perfectly, discrepancies in fragmentation do not bias MW measurement. • Biases come from interplays: e.g

50. W W event selection • Semileptonic channel (qqln) (44 %) • 2 jets • 1 isolated lepton, 1 neutrino: missing E&P Efficiency ~70% Purity ~90-95% main bkg Wen, qq(g) • Hadronic channel (qqqq) (36 %) • 4 jets • large multiplicity • spherical topology • low missing E&P Efficiency ~80% Purity ~85% main bkgqq(g), ZZ Statistics: Use multivariable analyses (e.g neural networks, even for qqln events!)