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HWW and WW Analysis Update: Synchronized Progress and Improved Selections

Stay updated on the latest advancements in the HWW and WW analysis with a focus on muons in the final state. Tasks like Monte Carlo, Trigger, and Drell-Yan estimation are being covered efficiently. Proposed selection changes promise a gain of ~30% for signal events. Efficiencies and distributions are in good shape, setting a strong foundation for further studies. Stay connected with the progress of the muon selection level and trigger studies. Learn about effective tag and probe methods, fake rates, and the l+d method for background estimation. Keep track of the HWW analysis status and upcoming trigger efficiency studies. For more detailed information, visit the provided links.

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HWW and WW Analysis Update: Synchronized Progress and Improved Selections

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  1. Update on H→WW→2μ2ν Oct. 8, 2010 IFCA – U. Oviedo

  2. Introduction • The work is going on in the HWW and WW analysis (focusing muons in the final state) • We keep ourselves synchronized • The list of Task proposedduring last meeting is almost completely covered: • Monte Carlo • Trigger • Tag and Probe • Fake Rates • Jet Veto • Top tagging • Drell-Yan estimation • Plus Multivariate Techniques (BDT) in WW and HWW Rebeca Gonzalez Suarez (08/10/2010)

  3. WW synchronization • The μμ channel was already synchronized: Rebeca Gonzalez Suarez (08/10/2010)

  4. WW synchronization • Also synchronized in ee and eμ: Rebeca Gonzalez Suarez (08/10/2010)

  5. Updated selection for WW • Some changes were proposed for the WW analysis: • Use of a tighter cut in the projected MET • Open the η of the jets from 3 to 5 • Muon PT range from 20/20 to 10/20 (2 regions) • The HWW analysis is planned to go as close as possible the the WW analysis : • We don’t use the projected MET (yet, will be studied) • The PT range in Higgs is already 10/20 • We can implement the change in the η of the jets considered for the CJV (that should be identical) Rebeca Gonzalez Suarez (08/10/2010)

  6. Effect of the proposed selection Monte-Carlo WW Spring10 sample Baseline WW analysis (WW sample, μμ channel) Gain of ~ 30% for signal Rebeca Gonzalez Suarez (08/10/2010)

  7. The new selection in perspective Normalizing to 1fb-1 @ 7TeV For WW signal and some of the main processes to be studied 30% better in signal, similar for top and effective against Zμμ With 100pb-1, it will mean the selection of more than one signal event (~6), with < 2 events of background Rebeca Gonzalez Suarez (08/10/2010)

  8. Status of the HWW analysis Following WW direction: Muon selection becomes identical (10/20) Same MET (Track corrected) Same Jets for the Central Jet Veto (PF, |η| < 5, ETRAW > 20) Test of the cut evolution 3.1pb-1 QCD, W+jets, Z+jets, top, WW, WZ, ZZ, tW included Cross-sections × BR (leptons) for Higgs signal < 1 pb (NNLO) selection efficiencies of the analysis at muon selection level are < 10% (for μμ) : with 10 pb-1 at muon selection < 0.9 Higgs events (160) expected in this channel Rebeca Gonzalez Suarez (08/10/2010)

  9. Kinematical distributions Everything in good shape Still far from the start of the real the work here 3.1 pb-1 After CJV Rebeca Gonzalez Suarez (08/10/2010)

  10. Trigger Studies Electron and muon triggers systematically checked for each table once samples are available Check results can be found in the twiki https://twiki.cern.ch/twiki/bin/viewauth/CMS/HiggsWGHLTValidate And in the offline DQM GUI DQMGUI Example Next: 1032 Waiting for Higgs to WW samples Some examples for 2E31 trigger Menu, performed with 3.9.0.pre5 RelVal samples in next slide (with tt Fastsim, no HWW available) lowest unprescaled: HLT_Mu11 HLT_Ele17_SW_CaloEleId_L1R  high eff. for dilepton final states Would like to study new triggers in 1E32 table  samples? Rebeca Gonzalez Suarez (08/10/2010)

  11. Trigger Efficiencies Efficiency Vs η and PT HLT_Mu11 HLT_Ele17_SW_CaloEleId Efficiency definition: fraction of selected events passing HLT requirement (top selection eμ) Rebeca Gonzalez Suarez (08/10/2010)

  12. Tag and Probe Zmm VBTF cuts • Tag: • GlobalMuonPT • TrackerMuon • HLT_Mu9 • |η| < 2.1 • pT > 20 GeV • |d0 | < 0.2 • Isolated • GM normalized χ2 < 10 • At least one pixel hit • Segments matched in at least 2 muon stations • At least one muon hit matched to the global fit • Number of tracker hits > 10 • Probes: • Trackswith pT > 5 GeV Passing probes: • GlobalMuonPT • TrackerMuon • |h| < 2.4 • pT > 20 GeV • |d0 | < 0.02 • Isolated • At least one muon hit matched to the global fit • Number of tracker hits > 10 Monte Carlo: Zmumu Summer10 sample With all certified data up to now: 4.43 pb-1 (/Zmumu/Summer10-START36_V9_S09-v1/GEN-SIM-RECO) Rebeca Gonzalez Suarez (08/10/2010) 12

  13. Muon ID + Iso Efficiency of the Muon ID + isolation cuts, obtained in data Vs Monte-Carlo, as a function of the PT of the ‘Probe’ And as a function of the η of the ‘Probe’ Rebeca Gonzalez Suarez (08/10/2010)

  14. Trigger Efficiency using T&P Trigger efficiency defined as the fraction of muon fulfiling all the muonID + Isolation criteria and matching a HLT_Mu9 object Data: MC: Rebeca Gonzalez Suarez (08/10/2010)

  15. Fake Rates • The work started with the very early data • Last time we presented this: • It was a single muon rate measured in data with less than 15 nb-1 using tracks • The data available and the Monte Carlo were in agreement Higgs contribution to MUO-10-002 Rebeca Gonzalez Suarez (08/10/2010)

  16. l+d method • For WW and Higgs to WW, we have a method extensively studied in the CSA07 context oriented to the estimation of the W+jets background in di-muon final states • Well known and documented: CMS AN 2008/039 • Several talks about it available, for example (8 June): • http://indico.cern.ch/contributionDisplay.py?contribId=2&confId=88524 • Basically the idea is to look at QCD events with one good muon and look at the ‘fakeable objects’ that can be mistaken as a second muon (background in the analysis) • It is already possible to start the study in data Rebeca Gonzalez Suarez (08/10/2010)

  17. First Results with 4.43 pb-1 • Cleaning the data sample from W, Z and top events (loose VBTF and top selections) • Using the JetMet, JetMETTau and Jet datasets • Comparing with QCD inclusive Mu 15 Still lacking statistics in some PT bins to fully perform it The QCD selection in data can also be done in a better way (on going) Rebeca Gonzalez Suarez (08/10/2010)

  18. Next Step in Fakes • But that’s not all: Parallel fake rate study done within the group for top (see http://indico.cern.ch/conferenceDisplay.py?confId=96963) • Slightly different approach • We are working in merge the two concepts in one that can be applied in all the analysis, HWW, WW and top Yesterday’s talk in top dilepton meeting by Alicia http://indico.cern.ch/getFile.py/access?contribId=2&resId=0&materialId=slides&confId=96963 Rebeca Gonzalez Suarez (08/10/2010)

  19. Jet Veto/Track Jets/b-tagging • Studies continuously going on by Lara (many presentations) • For 1fb-1 and the three final states together (μμ, eμ and ee) • Applying the WW baseline selection (including softmuon) • Two b-tagging algorithms tested: • Track Counting (TC) • Secondary Vertex efficiency (SV) • Summer 10 samples /VVJets_7TeV-madgraph/Summer10-START36_V10-v1/GEN-SIM-RECO /TTbar/Summer10-START36_V9_S09-v1/GEN-SIM-RECO Little effect on the signal while greatly reducing the ttbar background Evenifbothalgorithms are HighEff… TrackCounting More efficient/less purity Secondary Vertex  More purity/less efficiency Rebeca Gonzalez Suarez (08/10/2010)

  20. Tagging efficiencies As a function of thebtaggingdiscriminant TrackcountingHighEfficiencyalgorithm High Eff Simple Secondary Vertex Btaggingefficiency Btaggingefficiency Mistagrate Mistagrate Based on the requirement of a minimum number of good quality tracks with an impact parameter significance exceeding a given threshold. Reconstructs the B decay vertex using an adaptive vertex finder, and then uses variables related to it, to calculate its btaggingdiscriminant. Rebeca Gonzalez Suarez (08/10/2010)

  21. Taggingefficiencies As a function of the jet ET TrackcountingHighEfficiencyalgorithm HighEff Simple SecondaryVertexalgorithm All jets (PF Jets) are inside |h| < 2.5 Rebeca Gonzalez Suarez (08/10/2010)

  22. b-tagging Results without b-tagging (including softmuon cut) assuming 1 fb-1 VV  229.2 TTbar  23.0 Applying b-tagging Cutonthe ET of the jets used as input forthebtagging (after CJV) /VVJets_7TeV-madgraph/Summer10-START36_V10-v1/GEN-SIM-RECO /TTbar/Summer10-START36_V9_S09-v1/GEN-SIM-RECO Rebeca Gonzalez Suarez (08/10/2010)

  23. HWW Multivariate Analysis (BDT) • We keep as up to date as possible the multivariate analysis for HWW and WW • We are starting to check the behavior of the data using our latest Training • Still need more statistics to fully prepare a dedicated training for 7 TeV -> Very early preliminary studies with data tt WW Z Example of the Higgs trainings at 7 TeV against WW, tt and Z+jets with data with 3.1pb-1 (not yet optimized) Rebeca Gonzalez Suarez (08/10/2010)

  24. Summary • Work ongoing in most of the main tasks of the WW and HWW analysis: • Synchronized and in-tune with the HWW and WW working groups • Trigger Validation done in every new release • Effort focused in Tag and Probe, Fake rates and top background estimation (CJV, Track jets and b-tagging) • Cut-based Analysis for WW and HWW is ready for the data • Continuous work in the Multivariate Analysis (BDT) • Also a Particle Flow study based in Particle Flow Muons, Met and Jet is going on (coming soon) Rebeca Gonzalez Suarez (08/10/2010)

  25. Backup

  26. b-tagging (TCHighEfficiency) PF Jets trackJets caloJets JPT Rebeca Gonzalez Suarez (08/10/2010)

  27. b-tagging (HighEffSimpleSecondaryVertex) trackJets PF Jets JPT caloJets Rebeca Gonzalez Suarez (08/10/2010)

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