Top pair resonance searches with the ATLAS detector

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Transcript Top pair resonance searches with the ATLAS detector

Top pair resonance searches
with the ATLAS detector
钟家杭
University of Oxford
[email protected]
Frontier Physics Working Month
Outline
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Background information
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Top reconstruction
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Top pair resonance searches
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Boosted tops
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Top quark
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Lifetime ~ 5x10-25 s
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Decay before hadronization
Almost exclusively via t -> W + b
Spin=1/2, charge=2/3
 The heaviest known quark
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m(t)=173.2±0.9 GeV (Tevatron)
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hadron
67%
e
11%
μ
11%
τ
11%
31 Aug 2012
The energy frontier at TeV
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Beyond the Standard Model
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Two benchmark BSM models used in experiments
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Z’ in a leptophobic topcolor model
Proxy to narrow resonance: Γ/m=1.2%
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Kaluza-Klein gluon (KKG) in Randall-Sundrum extra dimension models
KKG branching ratio
Proxy to broad resonance: Γ/m=15.3%
Phys. Rev. D 77 (2008) 015003
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Generic search, applicable
to other BSM models
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Spin-0 Lee-Wick Higgs
Spin-2 KK graviton
…
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The ATLAS detector
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Leptons in ATLAS
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Only prompt leptons are considered signal
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Fixed-cone isolation to suppress QCD contribution
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Electron:
Energy cluster of high EM fraction, matching to a track
Muons:
Combined tracking in both Inner Tracker and Muon Chambers
Mostly real leptons from heavy-flavor quark
Both calo-based and track-based
Hadronic tau channel not included
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Jets in ATLAS
Sequential clustering algorithms : Kt, C/A, anti-Kt
 AntiKt as the mainstream jet algorithm
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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
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For antiKt4 jets
Using tracks associated with the jet
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Secondary vertices
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Impact parameter
Multivariate algorithms, 70% efficiency
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Leptonic top reconstruction
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t -> W + b -> l+v+b
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One Lepton
High missing transverse energy (MET)
High transverse mass MT between lepton and MET (due to W mass)
mT  2 pTl ETmiss (1  cos  )
One b-tagged antiKt4 jet.
Neutrino reconstruction
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Assuming MET fully from neutrino, solve pz(v) using W-mass
Under-constrained in di-lepton channel
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Hadronic top reconstruction
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t -> W + b -> q+q+b
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Resolved:
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3 antiKt4 jets
2 antiKt4 jets, if one has high mass.
Boost
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Boosted:
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One energetic antiKt10 jet
with substructure cuts
One energetic C/A1.5 jet
using HEPTopTagger
Discrimination against QCD
R ~ m / p
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Hadronic top reconstruction
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Jet substructure
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Jet mass> 100 GeV
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2
𝑚2 = ( 𝐸𝑖 ) −( 𝑝𝑖 )
First splitting scale 𝑑12 >40 GeV
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Re-clustering jet constitutes with Kt algorithm.
The splitting scale of the last step. 𝑑𝑖𝑗 =min(pTi, PTj) x ΔRij
mt
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mt/2
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Top pair resonance search
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Select ttbar-like events
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Di-lepton
1 lepton + 4(3) jets (resolved)
1 lepton + 1 jet + 1 fat jet (boosted)
Fully hadronic (HEPTopTagger)
2 fb-1, EPJC72 (2012) 2083
2 fb-1, arXiv:1207.2409
5 fb-1, ATLAS-CONF-2012-102
Reconstruct 𝑀𝑡𝑡 or equivalent
Look for peaks in 𝑀𝑡𝑡 spectrum
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τ (had)
14%
Di-lepton
6%
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Fully
hadronic
46%
1-lepton
(e, µ)
34%
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Single Lepton Boosted ttbar
Single lepton trigger
 Exactly one offline lepton
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ETmiss>35GeV, MT>25GeV
 Solve neutrino pz with W
mass constraint
 Closest antiKt4 jet as from
the leptonic top
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One antiKt10 fat jet
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Electron pT > 25 GeV
Muon pT > 20 GeV
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pT > 250 GeV
m > 100 GeV
𝑑12 > 40 GeV
dR(akt4, akt10)>1.5
pT > 30 GeV
0.4 < ΔR(lepton, jet) <1.5
Signal selection efficiency
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Single Lepton Boosted ttbar
M=2.5 TeV
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Single Lepton Boosted ttbar
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tt= l + v + akt4 + akt10 (4-vector sum)
Leptonic top mass
(l + v + akt4)
Hadronic top mass
(fat jet)
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Single Lepton Boosted ttbar
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W+jets background
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Data-driven normalization
Multijets
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Fully data-driven
Can be further
improved by b-tagging
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Single Lepton Boosted ttbar
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Single Lepton Boosted ttbar
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Search for local data excess
with BumpHunter
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Set 95% CL upper limits on xsec
Replace the theoretical line with your favorite model
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Top pair resonance search
Di-lepton
One-lepton
(Resolved)
One-lepton
(Boosted)
Fully hadronic
Integrated
luminosity
2 fb-1
2 fb-1
2 fb-1
4.7 fb-1
Z’ limits
-
0.5 – 0.88 TeV
0.6 – 1.15 TeV
0.7 – 1.3 TeV
KKG limits
0.5 – 1.08 TeV
0.5 – 1.13 TeV
0.6 – 1.5 TeV
0.7 – 1.5 TeV
More results are coming…
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Boosted Top
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New challenge: TeV frontier
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Top decay products are more collimated
ΔR ~ m/P
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Boosted Top: Leptonic
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Lepton collinear with the b-quark
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Signal acceptance suffers from the fixed-cone isolation cuts
Signal selection efficiency
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Boosted Top: Leptonic
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Mini-isolation
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JHEP 1103:059 (2011)
Variable-cone size ΔR=KT/pT
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Parameter KT, e.g. 15 GeV
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Lepton pT (easier than top pT)
Sum up tracks pt within the cone
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Sufficient angular resolution
Fixed-cone
isolation
b-jet
Isolation cut
Boost, dR=mtop/Etop
Mini-isolation
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lepton
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Three jets tend to overlap.
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Use single jet with large radius
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Need rejection against QCD
=> Substructure variable
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Need to get rid of soft component from
underlying event and pileup
=> Jet Grooming
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Not limited to top decay
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Boost
Boosted Top: Hadronic
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Boosted Top: Jet grooming
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Algorithms to reduce soft components from UE and PU
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I.
II.
III.
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Jet kinematics more close to the constituents of hard scattering
Better resolution/discrimination of the substructure variables
Mass drop/filtering
Trimming
Pruning
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Boosted Top: Jet grooming
Phys.Rev.Lett.100:242001 (2008)
Mass drop/filtering
(J. Butterworth, A. Davidson, M. Rubin, G. Salam)
 Works on C/A jet
 More optimized for two-body hadronic decay
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W/Z -> qq, H -> bb
Mass drop
Filtering
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Boosted Top: Jet grooming
JHEP 1002:084 (2010)
Trimming
(D. Krohn, J. Thaler, L. Wang)
 Use jet constituents to build Kt subjets (e.g. R=0.2)
 Remove soft subjets
 Applicable to any jet, any physics scenario
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Boosted Top: Jet grooming
arXiv:0912.0033 (2009)
Pruning
(S. Ellis, C. Vermilion, J. Walsh)
 Recluster jet constituents with C/A or Kt algorithm
(no need of subjets)
 Veto wide angle and soft constituents during jet formation
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Boosted Top: Jet grooming
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Reduce unnecessary catchment area
antiKt R=1.0 (ungroomed)
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antiKt R=1.0 (trimmed)
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Boosted Top: Substructure
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Jet mass are more discriminating after trimming
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Boosted Top: Substructure
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Splitting scale
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Re-clustering jet constitutes with Kt algorithm.
The splitting scale of the last step. 𝑑𝑖𝑗 =min(pTi, PTj) x ΔRij
𝑑12 ≈ 𝑚𝑡𝑜𝑝 /2
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𝑑23 ≈ 𝑚𝑊 /2
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Boosted Top: Substructure
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N-subjettiness (τN)
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Re-clustering with Kt algorithm until exactly N subjets are formed
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Smaller τN+1 /τN => Structure described better with additional sujet
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Boosted Top: HEPTopTagger
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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
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Summary
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ttbar resonance are searched in all channels at ATLAS
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Systematics still have large impact on the sensitivity
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Unfortunately, we don’t have the luck yet…
Uncertainty of performance at high pt
Understanding realistic performance of new techniques
Rooms to improve…
New techniques for new challenges
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Boosted top/object
Increased luminosity
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31 Aug 2012