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Defensa de la tesis para optar al grado de Doctor presentada por Patricia Lobelle Pardo

Measurement of the top quark production cross section and search for the SM Higgs boson in dilepton final states with the CMS detector at the LHC pp collider at √s= 7 TeV. Defensa de la tesis para optar al grado de Doctor presentada por Patricia Lobelle Pardo

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Defensa de la tesis para optar al grado de Doctor presentada por Patricia Lobelle Pardo

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  1. Measurement of the top quark productioncrosssection and searchforthe SM Higgsboson in dilepton final stateswiththe CMS detector at the LHC ppcollider at √s= 7 TeV Defensa de la tesis para optar al grado de Doctor presentada por Patricia LobellePardo Dirigida por Dr. Javier Cuevas Maestro Santander, 21 de Julio de 2011

  2. Outline • Standard Model , top, Higgs • LHC and CMS • Objectreconstruction • Top quark productioncrosssection • Searchfor SM Higgsboson • Conclusions

  3. Standard Model Succesfullyexplains experimental data to date … stillmany open questions • Origin of mass /origin of electroweak symmetry breaking  Higgs? • unification of forces • fundamental symmetry of forces and matter • where is antimatter • unification of quantum physics and general relativity • number of space/time dimensions • what is dark matter • what is dark energy Mattercomposed of fermions (quarks, leptons) Interactingviaforcecarriers(bosons)

  4. Top/Higgsboson at 7 TeV Tevatron LHC Ttbardileptoncandidate

  5. Introduction • 2 leptonphysicsisanimportantpart of the CMS analysisprogram SM processes and new physics produce dilepton final states • Clear signature, easierto observe at anearlierstage… • Study of processescontaining2 leptons(electrons/muons) + MET + 0/2 jets • Understandthe SM backgroundsbeforemeasuringanysignal of new physics In thisthesis: Backgroundformany new physicssearches • ttbarproductioncrosssection • Searchfor SM Higgs H  WW One of themostsensitive channels at LHC

  6. Introduction • Thesisfocusesonmeasurements done with2010 data • Analysisstrategiesdefinedbeforethe data taking, result of manydetailedstudies, improvements in the detector knowledge… and adaptedtodifferentEcmscenariosplannedforthe LHC startup 10 TeV 14 TeV

  7. LHC and CMS

  8. LHC • Proton-protoncollider at CERN • Design √s = 14 TeV • Proton-protoncollisions at √s = 7 TeV • From 30th March – 6th November 2010 • (initialtests & physics at √s =0.9,2.36 TeVby • end 2009) Severalexperiments  ATLAS, CMS, LHCb, ALICE • Pb-Pb collisions at 2.76 TeV/nucleon • 8th November – 16th Dec 2010

  9. CMS Tracker: all-silicon, largesolidanglecoverage |h|<2.4, excellent position and momentumresolution ECAL: homogeneous, crystal (PbWO4) calorimeter, highlysegmented, excelentenergyresolution HCAL: scintillators/brass, |h|<5 Muon system: DT, RPC,CSC • Top/Higgsanalysisrequireexcellent performance of • thewhole detector toefficientlyreconstruct • Muons • Electrons • Jets • MissingTransverseEnergy (MET) • b quark jet tagging

  10. Objectdefinition

  11. Muons • Muon Reconstruction: • Standalone : informationfrom muon systemonly • Global: informationfrom muon system & tracker • Globalmuons: startingfromstandalone muon, searchfor compatible tracks in thetrackersystem • Trackermuons: startingfromallthetracks in thetracker, associatetosegments in the muon system • Muon Identification: • Qualityrequirementsonreconstructedmuons •  Quality of thetrackfit, number of goodreconstructed hits in tracker and muon chambers… • - Promptmuons are producedclosetothe PV  cutonimpactparameter (IP) • Muon Isolation: • Sum of tracks pt, ECAL hits ET, HCAL hits ET in a conearound muon requiredtobesmallerthan a giventhreshold • Iso = (SumPt_tracks + SumET_ECAL + SumET_HCAL)/pt

  12. Electrons • Reconstruction • Energydepositions in ECAL matchedtotracks in tracker • Twoapproachesforelectronseeding: • ECAL driven: Startingfrom ECAL superclusters and searchfor compatible hits in thetrackerinnerlayers • - Trackerdriven: Use alltracks as startingpoint • Identification : selectpromptelectrons and rejectfakes • Basedonshowerproperties, track-clustermatching, H/E … • Rejection of electronsfromconversions: • - Impactparameter • Missing hits • Partnerconversiontrack Dist (distance of closestapproach of bothtrackes in phi plane), Dcot(q) • Isolation: • Sum of trackspT, ECAL hits ET, HCAL hits ET in a conearoundelectronrequiredtobesmallerthan a giventhreshold • Iso = (SumPt_tracks + SumET_ECAL + SumET_HCAL)/pt

  13. Jets • Experimental signatures of quarks and gluons • Hadronsdetected as clusters of energies in calorimeter, gatheredtogetherby • Jet Algorithmsto deduce thefourmomentum of theparentparton • Anti kTwith a cone R=0.5 standardalgorithm in CMS • Calorimeter Jets (CaloJet): Fromenergydepositions in HCAL & ECAL • Jet Plus Tracks(JPT): CaloJetscorrectedbymomentum of chargedtracks in tracker • ParticleFlow Jets(PF): Informationfromall sub-detector usedtoreconstructallparticles in theevent • Track Jets (TJ): fromtracksonly • Jets are correctedfor non-linearity and inhomogeneity of calorimeter response  JES mostimportantuncertaintyrelatedto jets

  14. b-tagging • Exploitproperties of b-quarks: • Lifetime: t ~1.5 ps decaylength ~1.8mm (at 20GeV) • Secondarydecayvertex, displaced trackswithlarge IP • Severalalgorithms discriminantssensitivetotheflavourcontent of the jet • IP-based • TrackCounting basedontrack IP • 2nd highest IP significance in jet: HighEfficiency • 3rd highest  highpurity • Jet Probability: probability that the given set of tracks come from P.V. • SV • Simple SecondaryVertex: basedonreconstruction of a secondary • Vertex in a jet. • -Discriminatorisflightdistancesignificance. Taggingefficienciesmeasured in data and MC  data/MC scalefactorsconsistentwith 1 within 10-20%

  15. Missing ET • Imbalancedtransverseenergy in theevent • Signature of onlyweaklyor non-interactingparticles • Causedby real undetectedparticles, mis-measured jets, detector effects… Crucial objectformanymeasurements needstobeverywellunderstood • CaloMET: depositions in ECAL+ HCAL • tcMET: expectedenergydepositions of goodtracks of chargedhadronsreplacedwiththeircorrespondingmomentum • PFMET: computedfromthelist of individuallyreconstructedparticles in theevent, combiningallsubdetectorinformation

  16. 2010 LHCRun • 47 pb-1 of ppcollision data at 7 TeVdeliveredbythe LHC  43 pb-1recordedby CMS • Averagefraction of operationalchannels per CMS sub-system>99% • Overall data takingefficiencies ~92% Reachedinstantaneousluminositypeak 2e32 Hz/cm2 • Onlyhighestquality data usedforphysicsanalyses ~ 85% • Full 2010 data sample: 36 pb-1 Excellent detector performance Many SM measurements

  17. SM re-discovery at 7 TeV

  18. Top crosssectionmeasurement • Motivation • Top production and decay • Top dileptonsignaltopology and eventselection • Measurementwith 3 pb-1 • Measurementwith 36 pb-1 • Yields • Leptonefficiencydetermination • Data-drivenbackgroundestimation • Systematicuncertainties • Cross-section

  19. Top Quark Physics • Special role in the EWK sector and in QCD • Heaviestknownelementaryparticle • Top and W massesconstrainHiggsmass • Short lifetime: uniquewindowonbare quarks A toolfor precise SM studies • Special role in various SM extensionsthrough EWSB • New physicsmightbepreferentiallycoupledto top • Non-standardcouplingsbetween top and gauge bosons • New particles can produce/decayto tops Sensitiveprobeto new physics • A majorsource of backgroundformanysearches • (Higgs, SUSY…) • A tooltounderstand/calibratethe detector, all sub-detectorsinvolved

  20. Top quark production • Top quark pairsproduced in stronginteractionvia • gluon-gluonfusion dominantmode at LHC • Quark- antiquarkannihilation • Single top quarks producedvia EWK interaction: • t-channel, s-channel, tW-channel s-channel t-channel tW-channel

  21. Top quark decay BR(tWb)≈100% In SM top decaysalmostexclusivelyto W and b • Differentsignaturesaccordingtothe W decay: • Dileptonchannel • Lepton+jetschannel • Fullyhadronicchannel

  22. Top dileptontopology • 2 promptleptonsfrom W decay: • highpT, oppositecharged, isolated • METfromtheundetected neutrinos • 2 b-jets Mostphysicsobjects are used • Mainbackgrounds: • Drell-Yan no genuine MET • Diboson: WW,WZ,ZZ  smallhadronicactivity • W+jets oneisolatedlepton • Single top –tW one b-jet

  23. Analysisflow Trigger muon and electrontriggers • Muons • pT>20 GeV, |h|<2.4 • ID: globalMuon, trackerMuon, IP<0.02 cm, Nhits>10, chi2<10 • Iso<0.15 Leptonpairselection Electrons pT>20 GeV, |h|<2.5 EcalDriven, eID 90% efficientfor e fromWs , IP<0.04 cm , Iso <0.15 |Mll-Mz|>15 ee/mm Z veto Jet selection At least 2 PFJetswithcorrectedpT>30 GeV, |h|<2.5, Awayfromselectedleptons • At least 1 b-tagged jet • TrackCountingHighEfficiencydiscriminator • Loosepoint: 1.7 MET selection b-tagselection PFMET> 30 GeV ee/mm

  24. Top crosssectionwith 3 pb-1 Firstcrosssectionmeasurementalreadypossiblewithonly 3 pb-1 • Full selection applied: • 2 leptons, Z-bosonVeto:|M(ll)-M(Z)|>15 GeV • MET >30 (20) GeV in ee,mm, (em) • N(jets)≥2 11 candidates ( 3 ee, 3 mm, 5 em) observed in data Systematicuncertaintiesonxs DY and fakeleptonbackgroundsestimatedfrom data • Signalselection • Leptonselection: 4.4% • EnergyScale: 3.7% • Theoretical: 2.8% 6.4% Backgrounds 11% Luminosity 11%

  25. Top cross section with 3 pb-1 b-quark content of theselectedsample studied consistentwithttbarproduction First top cross section measurement at LHC σ(pp → t¯t) = 194 ± 72(stat.) ± 24(syst.) ± 21(lumi.) pb Consistent with NLO prediction of 157.5 (+23.2 −24.4) pb for a top quark mass of mt= 172.5 GeV/c2

  26. Expected and observedevents 36 pb-1 mm ee em

  27. Data/MC comparison

  28. Leptonefficiencies • Leptonefficiencies ( Reco, ID, ISO, trigger) measuredusingTag and Probemethod • Anunbiased and puresample of leptonsisselectedusing Z ll events • Oneleptonisrequiredtopass a tightselection ( “tag” ) • Theotherlepton(“probe”) needstosatisfyonlylooseselection • Tag & probepairsrequiredtobeconsistentwith Z toensurethepurity of theprobesample • Probeleptonsusedtomeasuretheefficiencies  requiredtopassthecuts of a givenselectionwhoseefficiency has tobemeasured Efficienciesestimated in data and MC  Scalefactorsextracted • Muon RECO/ID/ISO efficiencies ~99% • Electron RECO/ID/ISO ~ 99% /85-95%/98% • Triggerefficiencies > 97%, (99%) mm (ee/em) SFee= 0.923 ± 0.018, SFmm= 0.967 ± 0.013 , SFem= 0.947 ± 0.011

  29. Backgroundestimation: Drell-Yan • Off-peak DY events are one of themainsources of • background Come frommismeasured MET from jets/leptons Eventsoutsidethe control region can beestimated fromeventsinside in data, correctingby a scale factor Non-DY contributionsubtractedusingemuevents and correctingfordifferencesbetween e and m 76<mll<106

  30. Backgroundestimation: Drell-Yan Systematicuncertainty comes from thevariation of Rout/in withthe MET cut 50% Data-drivenestimate mm: 2.6 ± 1.2 (stats) ± 1.3 (sys.) ee: 0.7 ± 0.6 (stats) ± 0.3 (sys.)

  31. Backgroundestimation: Fakeleptons • Eventswith “fake” leptons (W+Jets, QCD and semi-leptonictteventswhere a leptondoesnot come fromthedecay of a W) constitute a backgrounddifficulttopredict • Estimates of suchevents are basedonweightedcounting of leptonsfailingtightselectionsbutpassinglooserfakeableobject (FO) selections. • Tight-to-Loose (TL) ratio  probabilityof a fakeableobject (FO) topassthe full analysisselection. Computedin a QCD-dominatedsample: • Toestimatebkgswithfakeleptons TL ratio appliedtosamplewith • 2 leptonspassingnumeratorselections ( dominatedby real) • 1 leptonpassingnumeratorselection, otherfailing (combination of all) • 2 leptonsfailingnumeratorselection (dominatedby QCD)

  32. Systematics: Jet EnergyScale • One of themainsources of systematicuncertainty affects pt of the jets  MET Jet EnergyScaleuncertainties ~ 3-4% for jets with pt>30  takenfrom data base in pt,etabins  On top of that : - 1.5% toaccountfordifferences in software and calibrations - b-jet scale: 2% jets with (50<pt<200 GeV and eta<2.0), 3% otherwise Pt of the jets shiftedbythisvalue and alsopropagatedtothe MET Unclustered MET (10%)  1% effect Total uncertainty: 3.8% ee/mm 2.8% emu

  33. Systematics: b-tagging Efficiencies and mistagratesassociatedtotheworkingpointused (1.7) are shiftedbytheirrelativeuncertaintiestoobtain new b-tagdiscriminatorcuts. Data-MC scalefactors: SFlight= 1.0 ± 0.25 SFb= 1.0 ± 0.1 SFc= 1.0 ± 0.2 5% systematicuncertainty

  34. Summary of systematics • Uncertaintiesonsignalselection: • Backgroundsfrom MC: • Ztautau, VV and tW • 30% uncertaintyonthecrosssection • Detector effects, JES, btag • 38% Ztautau, VV • 32% tW Largestsystematicuncertainty Comes from b-tagging 15% uncertaintyonthe NLO crosssection • Theoretical systematicsestimated using ttbar MC samples produced with different configurations • Lepton selection: T&P + difference between tt and Z

  35. Cross sectionmeasurement N: Number of eventsobserved in data B: Number of backgroundevents A: signalacceptance L: luminosity • Analysiswascombinedwithotherdileptonmeasurements: 1 jet / 2-jets ( without b-tagging)

  36. Combined crosssection 12% precisionon top crosssection Measurements of the top crosssection in dilepton & lepton+jetschannels: s = 158 ± 10 (stats) ± 16 (syst) ± 6 (lumi) pb

  37. Searchforthe SM Higgsboson • Currentlimits • Higgsproduction and decay • HWW channel • Eventselection • Cut-basedanalysis • BDT analysis • Results and limits

  38. Higgslimits up to 2010 Theoreticallimits Finite and positive Higgscouplings • Experimental limits • LEP: mH > 114.4 GeV/c2 at 95% CL • Tevatron: Excludedthemassrange of 158 GeV/c2to173 GeV/c2 at 95%CL • Indirectconstraints • Derivedfrom precise EWK measurements: mH = 98 +58-37 GeV/c2 • (mH< 158 GeV/c2) (mH<185 GeV/c2ifincluding LEP2 results) A light Higgsisfavouredbymeasurements

  39. SM Higgsproduction Gluon-gluonfusion (ggH) Vector bosonfusion (VBF) In associationwith W,Z (VH) In associationwithtt (ttH) ggHdominantmode at LHC

  40. SM Higgsdecays • At Lowmass ( mH< 2mZ ) • H bb: BR ~0.85 buthuge QCD background • Htt: accessiblethrough VBF • Hgg: veryimportantdespitethelow BR (~0.002 ) duetotheexcellentg/jet separation and gresolution • HWW*2l2n: accesible throughggfusion and VBF, BR~1 at mH~160 GeV/c2 • HZZ*4l : alsoperformant ForHighermasses HWW* 2l2v and HZZ*4l

  41. H→WW*→2l2n Signal: 2 highpTisolatedleptons, MET and no hard jets • Mainsearchchannelforrange 140<mH<2mZ • -Highestbranching ratio formH >140 GeV/c2: 95% at mH = 160 GeV/c2 No masspeak (undetected neutrinos) Needs a goodbackgroundunderstanding • Backgrounds: • WW, tt, W+jets, Z+jets, tW, WZ, ZZ… • Twomaindiscriminants: • Anglebetweenleptons in thetransverseplane : main variable toreject WW (smallopeningangleforthesignaldueto spin correlations) • Jet Veto forttbarreduction

  42. Analysisflow muon and electrontriggers • Muons • pT>20 GeV, |h|<2.4 • ID: globalMuon, trackerMuon, IP<0.02 cm, Nhits>10, chi2<10 • Iso<0.15 Trigger Leptonpairselection Electrons pT>20 GeV, |h|<2.5 EcalDriven, eID 80% efficientfor e fromWs , IP<0.04 cm, Iso <0.10 WW preselection • Z veto |Mll-Mz|>15 • MET • Jet Veto • Top tagging(b-tag veto) Higgsselection MVA analysis Cut-basedanalysis

  43. Missing ET • Essentialto control Z+jetsbackground and reduce ittoanacceptablelevel • Projected MET This variable helpstosuppressZtautauthattendtohave MET alignedwithone of theleptons

  44. Jet Veto and top tagging Signal has littlehadronicactivity mainpropertytorejectttbarbackground Eventswith at leastone jet pT>25 GeV, |h|<5 are vetoed Presence of b-quarks in top eventsalsoexploited Top tagging soft muon + b-jet tagging - Muonsfrom b-quark decays are notisolated and havesofter pt - Look for b-tagged jets (TCHE > 2.1) remainingafter Jet Veto signal - Requiring no additionalsoftmuons and no b-tagged jets  ~40% top bkgreduction - Control samplefor top backgroundestimation

  45. Cut-basedanalysis • Secuentialcutsappliedonmaindiscriminant variables : • Pt of thehighest pt lepton (Ptmax) • Pt of thesecondlepton (Ptmin) • Dileptoninvariantmass (mll) • Anglebetweentheleptons in thetransverseplane (dPhi) Mostpowerful observable todistinguishthesignalfrom the irreducible WW background Dueto spin correlations, leptons fromHiggsdecaystendtohavesmaller openingangles

  46. Cut-basedanalysis • KinematicschangewiththeHiggsbosonmass massdependentoptimization

  47. BDT analysis • MVA analysisusedtoimprovesensitivity • BoostedDecisionTrees • Binaryclassifier • Samplesplittedbycuttingonthe variable thatgivesthebest S-B separation at eachstep • Training  SamplewithknownSignal and backgroundcomposition , selection of a set of discriminant variables… • Resultingfunctionappliedtothe data sample Massdependentoptimization (130,160,190) • Differentapproachesaccordingtothe training procedure, similar performance: • BDT 3D  separate trainings foreachbackground • BDT 1D  one single training againstallbackgroundstogether

  48. BDT analysis Input variables

  49. BDT 3D • Mainbackgrounds: WW, ttbar and Z+jets • 3 independent trainings usingthesame set of input variables and thencombinedinto a • Single variable BDT anti ttbar BDT anti Z BDT anti WW

  50. BDT 3D Final discriminant variable signal WW Z+jets X axis: BDT1 Y axis: BDT2 Z axis: BDT3 ttbar Signal-like background-like

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