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

2. Outline nIntroduction: the Standard Model and M W nMeasurement of M W :  Direct reconstruction  Systematic errors  QCD related errors nResults and conclusions

3. Mw within the Standard Model Mw can be computed at Born level from , M z, G F nHigher order radiative corrections involve M t, M H : e.g O( ,  s  M z, G F, 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? t WW H W W

4. The LEP goal for M W PP Colliders 80.454 ±0.059GeV/c2 EW fits (LEP/SLD) 80.373±0.033GeV/c2 EW Fits (LEP/SLD) with Mtop 80.378±0.023GeV/c2 LEP Goal:precision of ~40 MeV …Very difficult task.. nFirst phase optimise statistical power of analysis nLast years fight known and new systematics! No update since last winter

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

6. MW measurement  Identify and best reconstruct leptons (e,m,tau) nBest Cluster jets and measure energy and direction Event-by-event reconstruction of the invariant masses of W decay products  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 M reco

7. Mw Reconstruction(1) qqqq 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) Plus : No unmeasured particles, Fully constrained system

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

9. Reconstructed Mw Mreco still far from underlying Mw distribution After the kinematic Fit: Mreco True Mw M jet M reco qq l

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

11. Systematics

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

13. nparton shower (large Q 2, pQCD) Fragmentation (quarks  hadrons): Simulation of a MC event(1) nhadronisation (phenomenological) e+e+ e-e- W+W+ W-W- q _q_q q _q_q 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.  parton shower (large Q 2, pQCD) nFragmentation (quarks  hadrons): Simulation of a MC event(2) nHard process: e + e -  4q e+e+ e-e- W+W+ W-W- q _q_q q _q_q nInterconnection effects  Bose-Einstein correlations: momenta of identical bosons tend to be correlated. d~0.1 fm  Colour reconnection: hadronic interaction between W decays d(W +,W - ) < 1 fm  hadronisation (phenomenological) Not included in reference MC

15. Bose-Einstein Correlations (BEC)  Intra-W :BEI not relevant for M reco W1W1 W2W2  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 : Q 2 =(p i -p j ) 2 Any evidence for such effects? Look for BE in data

16. Observation BEC in W + W - events nInter W, BEI confirmed nBetween W’s, BEB, disfavoured  M W down from ~35 to ~15 MeV Final BEB BEI eg

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

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

19. LEP results from particle flow  preferred value: k I =1.18, P~0.5  k I value excluded at 1   value used for CR studies and  M W evaluation= ~100 MeV! Do something to make analyses more robust! Fit LEP measurement for free parameter k (CR P) (CR P)

20. Towards a less CR sensitive analysis:

21. The logic nInterconnection effects mainly occur in the inter-W region and between soft particles Proposed solution: modify clustering algorithm to dismiss information from those particles.  “purer” information  loss of statistical precision 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. Reduction of  M W  M W (MeV) ModelStandardR=0.5rad SK1, k I ~2~115~50 Herwig~40~15 Good reduction factors for all available models!  M W e.g for R=0.5, 2.3-2.6 smaller  M W with ~25% increase of stat. error: Algorithms simple and intuitive measurement less sensitive to CR independent of specific model implementation

23. A by-product: Measure CR? The difference between M W measured with cone/pcut and standard analyses (  M C-S ) is sensitive to CR effects:  DELPHI, Cone algorithm R=0.5 e.g DELPHI preliminary: nExclude extreme scenarios. nMinimum at ~1.3, P~0.5

24. Results

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

26. Mw and Mtop, MHiggs mH Mw Mtop GeV 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 nIf 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...* nDetector Systematics still an issue after all these years.. nFinal values for Summer?!?!

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

29. Detector Simulation nAs measurement is calibrated using MC Systematic errors related to the detector arise from discrepancies in the detector simulation. nMost 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 , for Data and MC (ratio) for total energy, Ejet And for individual types of particles (Echarged, Ephotons, etc)

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

31. Data-MC= -0.024±0.007 rad Data MC qq qq e Jet Direction simulation Test done with W events: Compare Data and MC  =  neutral -   Chargerd,  being the dijet angle Jet1-Jet2 Charged1 Collecting the full statistics allowed relevant sensitivity qqqq e  bad surprise Data different from MC by 24mrad  neut  Char Jet1 Jet2 Charged2

32. The electron channel: qq The electron channel: qq e Angle to lepton/degrees # Data MC Particles associated to a jet qq qq e 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 qq Mw from qq e moved by ~100 MeV…

33. WW production at LEP 1.Theoretical precision ~0.5% Thanks to 2000 calculations RACOONWW, YFSWW with improved O(a) corrections 2.LEP measurement precision ~1% Very good agreement

34. Example: Jet Mass and Baryon # Jet Mass Jetset Herwig Data Identical W  2q events, Hadronised with Jetset/Herwig Study  Mjet1,  Mjet12,  Mreco Vs  (No of neutrons) Jet Mass enters into Dijet-Mass (Mjet12) and also shows some discrepancy between Data and MC 0 2 4 6 8 10  Mjet(12)/GeV  neutron 8 4 0 0 2 4 6 8 10 Effect much smaller but ~20MeV  neutron  Mreco/GeV 0 2 4 6 8 10 8 4 0  Mjet1/GeV  neutron 5 2 0

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

36. ALEPH: Energy resolution nEnergy resolution for a calorimeter object adding ECAL + HCAL is:  = 6 GeV Peak=90.5GeV Total Visible Energy (GeV) @ 91GeV ecm Z qq nTake 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:

37. ALEPH: Jet Direction Jet  and  resolution  =18mrad    =19mrad Jet direction information is based on tracks, addition of neutral objects improves resolution by 15%

38. 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 comparing  neutral to   Chargerd as a function of  jet  neut  Charged Z axis cos  mrad  Charged -  neutral ) Data/MC No significant effect, small systematic error But..

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

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

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

42. Data/JETSET HERWIG/JETSE T HERWIG Data JETSET Angular distributions nJet Energy:nVelocity: HERWIG Data JETSET Data/JETSET HERWIG/JETSET

43. Inter-jet angle in W + W - events M 2 12 ~ 2E 1 E 2 (1 - cos   ) nZ  qq events too different  semileptonic W + W - events used.  independent sample  free from CR effects  Data JETSET nVariable checked: SS CC No indications of new sources of systematics  S - CC For Data and Jetset

44. Conclusions(2) nStatistical errors exceeded all expectations (analyses really pushed to the limit!) nSystematic 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  X)  pass them through full analysis : Max  Mw ~20 MeV (Jetset-Herwig ) Latest work: But..  Mw is due to  X between Data & reference MC(Jetset) 1.Identify fragmentation variable, X, with significant dMw/dx 2.Estimate  X(Data-MC) at some control sample, eg Z events 3.Propagate dX(Data-MC) in refference MC Mass distribution   Mw

46. Method for M W measurement

47. Introduction The Standard Model and Mw

48. QCD effects on M W

49. Fragmentation nIf all particles are detected and associated to Ws perfectly, discrepancies in fragmentation do not bias M W measurement. nBiases come from interplays: E, p spectra Baryon rates (e.g n,p ) Thresholds charged -> m  neutrals -> m  Angular size of jets Acceptance Jet algorithms Discrepancies MC-reality on fragmentation  x Detector f D (X) Reconstruction f A (X E ) e.g

50. W W event selection Semileptonic channel (qql   2 jets  1 isolated lepton, 1 neutrino: missing E&P Efficiency ~70% Purity ~90-95% main bkg We, qq(  Hadronic channel (qqqq) (   4 jets large multiplicity spherical topology  low missing E&P Efficiency ~80% Purity ~85% main bkg qq(  Statistics: Use multivariable analyses (e.g neural networks, even for qql events!)