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HLT tau trigger with regional tracking

TISB Pisa 12/10/01. HLT tau trigger with regional tracking. G. Bagliesi, S. Dutta, S. Gennai, G. Sguazzoni. Process studied. Low luminosity : Susy gg->(bb) A/H(200,500) -> (bb) tt -> 2 Jets+X Main background is QCD (50<P T hat 170) Pixel “staged” scenario study:

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HLT tau trigger with regional tracking

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  1. TISB Pisa 12/10/01 HLT tau trigger with regional tracking G. Bagliesi, S. Dutta, S. Gennai, G. Sguazzoni

  2. Process studied • Low luminosity: • Susy gg->(bb) A/H(200,500) -> (bb) tt -> 2 Jets+X • Main background is QCD (50<PThat170) • Pixel “staged” scenario study: • 3 layers + 2 disk: “standard” • 2 layers + 1 disk: “staged” (preliminary results!) • ORCA 4_5_4, CMSIM 120 • But we are reading the DB with ORCA_5_1_2 • No pixel read-out inefficiency G. Bagliesi, S. Dutta, S. Gennai, C. Schmidt, G. Sguazzoni – bTau 250901

  3. Data samples G. Bagliesi, S. Dutta, S. Gennai, C. Schmidt, G. Sguazzoni – bTau 250901

  4. G. Bagliesi, S. Dutta, S. Gennai, C. Schmidt, G. Sguazzoni – bTau 250901

  5. L1 (iso) L1 (iso) calo L2 (iso) calo L3Tk (iso, #tk) L3Tk (iso) pixel No L2 applied on 1st jet: more flexibilility 1st jet .AND. calo 2nd jet trigger chain 1st jet trigger chain H/Att tracker 2nd jet G. Bagliesi, S. Dutta, S. Gennai, C. Schmidt, G. Sguazzoni – bTau 250901

  6. G. Bagliesi, S. Dutta, S. Gennai, C. Schmidt, G. Sguazzoni – bTau 250901

  7. What is new? • Look for a Pixel leading track in the jet matching cone (Rm=0.4, it was 0.1 before) • If no pixel leading track is found, take the most probable signal vertex • ~10% of good signal events recovered • ~3% change in bkg: more probable to find a leading track since more tracks are around… • Ptcut on leading track = 1 GeV (it was 3 GeV) • Reconstruct second tau jet (if any) pointing to the same signal vertex G. Bagliesi, S. Dutta, S. Gennai, C. Schmidt, G. Sguazzoni – bTau 250901

  8. Pt distribution from pythia G. Bagliesi, S. Dutta, S. Gennai, C. Schmidt, G. Sguazzoni – bTau 250901

  9. L2Tk jet tagging algorithm • “Good Track” definition • PT>1 Gev • |Z0-Zsignal|<0.2 • Jet tau tagging: • look for a fully reconstructed leading track with PT>1 GeV • (or calculate baricenter of tracks inside the cone) • Apply isolation cut (already described) • Scan on Rs, Ri to find optimal parameters • Rs=0.04, 0.06, 0.08, 0.1 • Ri=0.4, 0.35, 0.3, 0.25, 0.2

  10. Rs Ri L2Tk on first and second jet First jet only First and second jet

  11. L2Calo + L3Tk isolation With both Calo and Tk selection we can achieve the desired rejection factor.

  12. Summary Plot • Using: • Rs = 0.04 • Ri = 0.3 • And L2Calo on first jet we have: • Bkg Rej = 10-3 • Sig Eff. • MH500 = 45% • MH200 = 35%

  13. Staged pixel scenario • 2 barrel layers • 1 forward disk • Comments: • Track finder not optimized at seed level • Preliminary! • 10% signal efficiency degradation expected Not staged Staged

  14. TauTkTagging.cc TauTkTagging(float eta, float phi, G3EventProxy *ev) • methods>: • Vector<RecTrack> regionalTk() • Return a vector of reconstructed tracks inside jet cone and from the same primary vertex. • Bool isTau() • Return true if the jet pass Tk isolation criteria. • Committed under bTauAnalysis/TauTaggingAlgorithms (works with ORCA_5_1_2)

  15. Conclusions • Good signal efficiency ~40% (>30%) with ~103 background rejection factor is achievable using both jets for 500 Gev/c2 (200 Gev/c2) Higgs mass • “Tau class” committed and working. • To do: • Improve speed: conditional track finding implementation and evaluation • Study the SimTracks to tune better the algorithm • Tau Tagging: mass, vertex, I.P.

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