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Top pair resonance searches with the ATLAS detector 钟家杭 University of Oxford Frontier Physics Working Month.

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Presentation on theme: "Top pair resonance searches with the ATLAS detector 钟家杭 University of Oxford Frontier Physics Working Month."— Presentation transcript:

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

2 Outline 31 Aug 2012jiahang.zhong@cern.ch1  Background information  Top reconstruction  Top pair resonance searches  Boosted tops

3 Top quark 31 Aug 2012jiahang.zhong@cern.ch2  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

4 The energy frontier at TeV 31 Aug 2012jiahang.zhong@cern.ch3

5 Beyond the Standard Model 31 Aug 2012jiahang.zhong@cern.ch4  Two benchmark BSM models used in experiments  Z’ in a leptophobic topcolor model Proxy to narrow resonance: Γ/m=1.2%  Kaluza-Klein gluon (KKG) in Randall-Sundrum extra dimension models Proxy to broad resonance: Γ/m=15.3%  Generic search, applicable to other BSM models  Spin-0 Lee-Wick Higgs  Spin-2 KK graviton  … KKG branching ratio Phys. Rev. D 77 (2008) 015003

6 The ATLAS detector 31 Aug 2012jiahang.zhong@cern.ch5

7 Leptons in ATLAS 31 Aug 2012jiahang.zhong@cern.ch6  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

8 Jets in ATLAS 31 Aug 2012jiahang.zhong@cern.ch7  Sequential clustering algorithms : Kt, C/A, anti-Kt  AntiKt as 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

9 Leptonic top reconstruction 31 Aug 2012jiahang.zhong@cern.ch8  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 p z (v) using W-mass  Under-constrained in di-lepton channel

10 Hadronic top reconstruction 31 Aug 2012jiahang.zhong@cern.ch9  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 jet using HEPTopTagger  Discrimination against QCD Boost

11 Hadronic top reconstruction 31 Aug 2012jiahang.zhong@cern.ch10 m t /2 mtmt

12 Top pair resonance search 31 Aug 2012jiahang.zhong@cern.ch11 2 fb -1, arXiv:1207.2409 2 fb -1, EPJC72 (2012) 2083 5 fb -1, ATLAS-CONF-2012-102

13 Single Lepton Boosted ttbar 31 Aug 2012jiahang.zhong@cern.ch12  Single lepton trigger  Exactly one offline lepton  Electron p T > 25 GeV  Muon p T > 20 GeV  E T miss >35GeV, M T >25GeV  Solve neutrino p z with W mass constraint  Closest antiKt4 jet as from the leptonic top  p T > 30 GeV  0.4 < ΔR(lepton, jet) <1.5 Signal selection efficiency

14 Single Lepton Boosted ttbar 31 Aug 2012jiahang.zhong@cern.ch13 M=2.5 TeV

15 Single Lepton Boosted ttbar 31 Aug 2012jiahang.zhong@cern.ch14  tt= l + v + akt4 + akt10 (4-vector sum) Leptonic top mass (l + v + akt4) Hadronic top mass (fat jet)

16 Single Lepton Boosted ttbar 31 Aug 2012jiahang.zhong@cern.ch15  W+jets background  Data-driven normalization  Multijets  Fully data-driven Can be further improved by b-tagging

17 Single Lepton Boosted ttbar 31 Aug 2012jiahang.zhong@cern.ch16

18 Single Lepton Boosted ttbar 31 Aug 2012jiahang.zhong@cern.ch17  Search for local data excess with BumpHunter  Set 95% CL upper limits on xsec Replace the theoretical line with your favorite model

19 Top pair resonance search 31 Aug 2012jiahang.zhong@cern.ch18 Di-lepton One-lepton (Resolved) One-lepton (Boosted) Fully hadronic Integrated luminosity 2 fb -1 4.7 fb -1 Z’ limits-0.5 – 0.88 TeV0.6 – 1.15 TeV0.7 – 1.3 TeV KKG limits0.5 – 1.08 TeV0.5 – 1.13 TeV0.6 – 1.5 TeV0.7 – 1.5 TeV More results are coming…

20 Boosted Top 31 Aug 2012jiahang.zhong@cern.ch19  New challenge: TeV frontier  Top decay products are more collimated ΔR ~ m/P

21 Boosted Top: Leptonic 31 Aug 2012jiahang.zhong@cern.ch20  Lepton collinear with the b-quark  Signal acceptance suffers from the fixed-cone isolation cuts Signal selection efficiency

22 Boosted Top: Leptonic 31 Aug 2012jiahang.zhong@cern.ch21  Mini-isolation  Variable-cone size ΔR=K T /p T  Parameter K T, e.g. 15 GeV  Lepton p T (easier than top p T )  Sum up tracks pt within the cone  Sufficient angular resolution JHEP 1103:059 (2011) b-jet lepton Isolation cut Boost, dR=m top /E top Fixed-cone isolation Mini-isolation

23 Boosted Top: Hadronic 31 Aug 2012jiahang.zhong@cern.ch22  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

24 Boosted Top: Jet grooming 31 Aug 2012jiahang.zhong@cern.ch23  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 I. Mass drop/filtering II. Trimming III. Pruning

25 Boosted Top: Jet grooming 31 Aug 2012jiahang.zhong@cern.ch24 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

26 Boosted Top: Jet grooming 31 Aug 2012jiahang.zhong@cern.ch25 Trimming  Use jet constituents to build Kt subjets (e.g. R=0.2)  Remove soft subjets  Applicable to any jet, any physics scenario JHEP 1002:084 (2010) (D. Krohn, J. Thaler, L. Wang)

27 Boosted Top: Jet grooming 31 Aug 2012jiahang.zhong@cern.ch26 Pruning  Recluster jet constituents with C/A or Kt algorithm (no need of subjets)  Veto wide angle and soft constituents during jet formation arXiv:0912.0033 (2009) (S. Ellis, C. Vermilion, J. Walsh)

28 Boosted Top: Jet grooming 31 Aug 2012jiahang.zhong@cern.ch27  Reduce unnecessary catchment area antiKt R=1.0 (ungroomed)antiKt R=1.0 (trimmed)

29 Boosted Top: Substructure 31 Aug 2012jiahang.zhong@cern.ch28  Jet mass are more discriminating after trimming

30 Boosted Top: Substructure 31 Aug 2012jiahang.zhong@cern.ch29

31 Boosted Top: Substructure 31 Aug 2012jiahang.zhong@cern.ch30  N-subjettiness ( τ N )  Re-clustering with Kt algorithm until exactly N subjets are formed   Smaller τ N+1 /τ N => Structure described better with additional sujet

32 Boosted Top: HEPTopTagger 31 Aug 2012jiahang.zhong@cern.ch31  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

33 Summary 31 Aug 2012jiahang.zhong@cern.ch32  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

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