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Top pair resonance searches with the ATLAS detector

Top pair resonance searches with the ATLAS detector. 钟家杭 University of Oxford Jiahang.Zhong@cern.ch Frontier Physics Working Month. Outline. Background information Top reconstruction Top pair resonance searches Boosted tops. Top quark. Spin=1/2, charge=2/3 The heaviest known quark

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Top pair resonance searches with the ATLAS detector

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  1. Top pair resonance searcheswith the ATLAS detector 钟家杭 University of Oxford Jiahang.Zhong@cern.ch Frontier Physics Working Month

  2. Outline • Background information • Top reconstruction • Top pair resonance searches • Boosted tops jiahang.zhong@cern.ch

  3. Top quark • Spin=1/2, charge=2/3 • The heaviest known quark • m(t)=173.2±0.9 GeV (Tevatron) • Lifetime ~ 5x10-25 s • Decay before hadronization • Almost exclusively via t -> W + b jiahang.zhong@cern.ch

  4. The energy frontier at TeV jiahang.zhong@cern.ch

  5. Beyond the Standard Model • Two benchmark BSM models used in experiments • Z’ in a leptophobictopcolor modelProxy to narrow resonance: Γ/m=1.2% • Kaluza-Klein gluon (KKG) in Randall-Sundrum extra dimension modelsProxy to broad resonance: Γ/m=15.3% KKG branching ratioPhys. Rev. D 77 (2008) 015003 • Generic search, applicable to other BSM models • Spin-0 Lee-Wick Higgs • Spin-2 KK graviton • … jiahang.zhong@cern.ch

  6. The ATLAS detector jiahang.zhong@cern.ch

  7. Leptons in ATLAS • Only prompt leptons are considered signal • Electron: Energy cluster of high EM fraction, matching to a track • Muons: Combined tracking in both Inner Tracker and Muon Chambers • Fixed-cone isolation to suppress QCD contribution • Mostly real leptons from heavy-flavor quark • Both calo-based and track-based • Hadronic tau channel not included jiahang.zhong@cern.ch

  8. Jets in ATLAS • Sequential clustering algorithms : Kt, C/A, anti-Kt • AntiKtas the mainstream jet algorithm • R=0.4 as the standard jet • R=1.0 known as the fat jet (boosted hadronic top jet) • C/A algorithm with R=1.5 used for HEPTopTagger • B-tagging • For antiKt4 jets • Using tracks associated with the jet • Secondary vertices • Impact parameter • Multivariate algorithms, 70% efficiency jiahang.zhong@cern.ch

  9. Leptonic top reconstruction • t -> W + b -> l+v+b • One Lepton • High missing transverse energy (MET) • High transverse mass MT between lepton and MET (due to W mass) • One b-tagged antiKt4 jet. • Neutrino reconstruction • Assuming MET fully from neutrino, solve pz(v) using W-mass • Under-constrained in di-lepton channel jiahang.zhong@cern.ch

  10. Hadronic top reconstruction • t -> W + b -> q+q+b • Resolved: • 3 antiKt4 jets • 2 antiKt4 jets, if one has high mass. • Boosted: • One energetic antiKt10 jet with substructure cuts • One energetic C/A1.5 jetusing HEPTopTagger • Discrimination against QCD Boost jiahang.zhong@cern.ch

  11. Hadronic top reconstruction • Jet substructure • Jet mass> 100 GeV • First splitting scale >40 GeV • Re-clustering jet constitutes with Kt algorithm. The splitting scale of the last step.=min(pTi, PTj) x ΔRij mt/2 mt jiahang.zhong@cern.ch

  12. Top pair resonance search • Select ttbar-like events • Di-lepton • 1 lepton + 4(3) jets (resolved) • 1 lepton + 1 jet + 1 fat jet (boosted) • Fully hadronic (HEPTopTagger) • Reconstruct or equivalent • Look for peaks in spectrum 2 fb-1, EPJC72 (2012) 2083 2 fb-1, arXiv:1207.2409 5 fb-1, ATLAS-CONF-2012-102 jiahang.zhong@cern.ch

  13. Single Lepton Boosted ttbar • Single lepton trigger • Exactly one offline lepton • Electron pT > 25 GeV • MuonpT > 20 GeV • ETmiss>35GeV, MT>25GeV • Solve neutrino pz with W mass constraint • Closest antiKt4 jet as from the leptonic top • pT > 30 GeV • 0.4 < ΔR(lepton, jet) <1.5 • One antiKt10 fat jet • pT > 250 GeV • m > 100 GeV • > 40 GeV • dR(akt4, akt10)>1.5 Signal selection efficiency jiahang.zhong@cern.ch

  14. Single Lepton Boosted ttbar M=2.5 TeV jiahang.zhong@cern.ch

  15. Single Lepton Boosted ttbar • tt= l + v + akt4 + akt10 (4-vector sum) Leptonic top mass(l + v + akt4) Hadronic top mass(fat jet) jiahang.zhong@cern.ch

  16. Single Lepton Boosted ttbar • W+jets background • Data-driven normalization • Multijets • Fully data-driven Can be further improved by b-tagging jiahang.zhong@cern.ch

  17. Single Lepton Boosted ttbar jiahang.zhong@cern.ch

  18. Single Lepton Boosted ttbar • Search for local data excess with BumpHunter • Set 95% CL upper limits on xsec Replace the theoretical line with your favorite model jiahang.zhong@cern.ch

  19. Top pair resonance search More results are coming… jiahang.zhong@cern.ch

  20. Boosted Top • New challenge: TeV frontier • Top decay products are more collimatedΔR ~ m/P jiahang.zhong@cern.ch

  21. Boosted Top: Leptonic • Lepton collinear with the b-quark • Signal acceptance suffers from the fixed-cone isolation cuts Signal selection efficiency jiahang.zhong@cern.ch

  22. Boosted Top: Leptonic JHEP 1103:059 (2011) • Mini-isolation • Variable-cone sizeΔR=KT/pT • Parameter KT, e.g. 15 GeV • Lepton pT (easier than top pT) • Sum up tracks pt within the cone • Sufficient angular resolution Fixed-cone isolation b-jet lepton Isolation cut Boost, dR=mtop/Etop Mini-isolation jiahang.zhong@cern.ch

  23. Boosted Top: Hadronic • Three jets tend to overlap. • Use single jet with large radius • Need rejection against QCD => Substructure variable • Need to get rid of soft component from underlying event and pileup=> Jet Grooming • Not limited to top decay Boost jiahang.zhong@cern.ch

  24. Boosted Top: Jet grooming • Algorithms to reduce soft components from UE and PU • Jet kinematics more close to the constituents of hard scattering • Better resolution/discrimination of the substructure variables • Mass drop/filtering • Trimming • Pruning jiahang.zhong@cern.ch

  25. Boosted Top: Jet grooming Mass drop/filtering • Works on C/A jet • More optimized for two-body hadronic decay • W/Z -> qq, H -> bb Phys.Rev.Lett.100:242001 (2008)(J. Butterworth, A. Davidson, M. Rubin, G. Salam) Mass drop Filtering jiahang.zhong@cern.ch

  26. Boosted Top: Jet grooming JHEP 1002:084 (2010) (D. Krohn, J. Thaler, L. Wang) Trimming • Use jet constituents to build Ktsubjets (e.g. R=0.2) • Remove soft subjets • Applicable to any jet, any physics scenario jiahang.zhong@cern.ch

  27. Boosted Top: Jet grooming arXiv:0912.0033 (2009)(S. Ellis, C. Vermilion, J. Walsh) Pruning • Recluster jet constituents with C/A or Kt algorithm (no need of subjets) • Veto wide angle and soft constituents during jet formation jiahang.zhong@cern.ch

  28. Boosted Top: Jet grooming • Reduce unnecessary catchment area antiKt R=1.0 (ungroomed) antiKt R=1.0 (trimmed) jiahang.zhong@cern.ch

  29. Boosted Top: Substructure • Jet mass are more discriminating after trimming jiahang.zhong@cern.ch

  30. Boosted Top: Substructure • Splitting scale • Re-clustering jet constitutes with Kt algorithm. The splitting scale of the last step.=min(pTi, PTj) x ΔRij jiahang.zhong@cern.ch

  31. Boosted Top: Substructure • N-subjettiness (τN) • Re-clustering with Kt algorithm until exactly N subjets are formed • Smaller τN+1/τN => Structure described better with additional sujet jiahang.zhong@cern.ch

  32. Boosted Top: HEPTopTagger • A multi-step algorithm starting from a large-R C/A jet • Grooming: filter out soft component • Form up subjets • Impose Top and W mass constraints JHEP 1010:078 (2010)ATLAS-CONF-2012-065 jiahang.zhong@cern.ch

  33. Summary • ttbar resonance are searched in all channels at ATLAS • Unfortunately, we don’t have the luck yet… • Systematics still have large impact on the sensitivity • Uncertainty of performance at high pt • Understanding realistic performance of new techniques • Rooms to improve… • New techniques for new challenges • Boosted top/object • Increased luminosity jiahang.zhong@cern.ch

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