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
1 jiahang.zhong@cern.ch
31 Aug 2012

Top quark
 Lifetime ~ 5x10 -25 s
 Decay before hadronization
 Almost exclusively via t -> W + b
 Spin=1/2, charge=2/3

2
The heaviest known quark
 m(t)=173.2±0.9 GeV (Tevatron) jiahang.zhong@cern.ch
e
11%
μ
11%
τ
11% hadron
67%
31 Aug 2012

The energy frontier at TeV
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31 Aug 2012

Beyond the Standard Model
 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% KKG branching ratio
Phys. Rev. D 77 (2008) 015003
 Generic search, applicable to other BSM models
 Spin-0 Lee-Wick Higgs


Spin-2 KK graviton
…
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The ATLAS detector
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31 Aug 2012

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
6 jiahang.zhong@cern.ch
31 Aug 2012

Jets in ATLAS
 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
7 jiahang.zhong@cern.ch
31 Aug 2012

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) m
T

2 p
T l
E
T miss
( 1
 cos
 
)
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
8 jiahang.zhong@cern.ch
31 Aug 2012

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 jet using HEPTopTagger
Discrimination against QCD
9 jiahang.zhong@cern.ch

R ~ m / p
31 Aug 2012

Hadronic top reconstruction
 Jet substructure
 Jet mass> 100 GeV
 𝑚 2 = ( 𝐸 𝑖
)
2
−( 𝑝 𝑖
)
2
 First splitting scale 𝑑
12
>40 GeV
 Re-clustering jet constitutes with Kt algorithm.
The splitting scale of the last step.
𝑑 𝑖𝑗
=min(p
Ti
, P
Tj
) x ΔR ij m t m t
/2
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31 Aug 2012

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)
2 fb -1 , EPJC72 (2012) 2083
2 fb -1 , arXiv:1207.2409
5 fb -1 , ATLAS-CONF-2012-102
 Reconstruct 𝑀 𝑡 𝑡 or equivalent
 Look for peaks in 𝑀 𝑡 𝑡 spectrum
τ (had)
14%
Di-lepton
6%
Fully hadronic
46%
1-lepton
(e, µ)
34%
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31 Aug 2012

Single Lepton Boosted ttbar
 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 mass constraint with W
 Closest antiKt4 jet as from the leptonic top

 p
T
> 30 GeV
0.4 < ΔR(lepton, jet) <1.5
 One antiKt10 fat jet

 p
T
> 250 GeV m > 100 GeV

 𝑑
12
> 40 GeV dR(akt4, akt10)>1.5
12
Signal selection efficiency jiahang.zhong@cern.ch
31 Aug 2012

Single Lepton Boosted ttbar
M=2.5 TeV
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Single Lepton Boosted ttbar
 tt= l + v + akt4 + akt10 (4-vector sum)
Leptonic top mass
(l + v + akt4)
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Hadronic top mass
(fat jet) jiahang.zhong@cern.ch
31 Aug 2012

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

Single Lepton Boosted ttbar
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31 Aug 2012

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

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
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More results are coming… jiahang.zhong@cern.ch
31 Aug 2012

Boosted Top
 New challenge: TeV frontier
 Top decay products are more collimated
ΔR ~ m/P
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Boosted Top: Leptonic
 Lepton collinear with the b-quark
 Signal acceptance suffers from the fixed-cone isolation cuts
Signal selection efficiency
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Boosted Top: Leptonic
 Mini-isolation


JHEP 1103:059 (2011)
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
Fixed-cone isolation
Isolation cut
Boost, dR=m top
/E top b-jet lepton
Mini-isolation
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31 Aug 2012

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
22 jiahang.zhong@cern.ch
31 Aug 2012

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
I.
II.
III.
Mass drop/filtering
Trimming
Pruning
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31 Aug 2012

Boosted Top: Jet grooming
Mass drop/filtering
 Works on C/A jet
Phys.Rev.Lett.100:242001 (2008)
(J. Butterworth, A. Davidson, M. Rubin, G. Salam)
 More optimized for two-body hadronic decay
 W/Z -> qq, H -> bb
Mass drop
24 jiahang.zhong@cern.ch
Filtering
31 Aug 2012

Boosted Top: Jet grooming
Trimming

JHEP 1002:084 (2010)
(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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31 Aug 2012

Boosted Top: Jet grooming
Pruning
 arXiv:0912.0033 (2009)
(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
 Reduce unnecessary catchment area
27 antiKt R=1.0 (ungroomed) antiKt R=1.0 (trimmed) jiahang.zhong@cern.ch
31 Aug 2012

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

Boosted Top: Substructure
 Splitting scale
 Re-clustering jet constitutes with Kt algorithm.
The splitting scale of the last step. 𝑑 𝑖𝑗
=min(p
Ti
, P
Tj
) x ΔR ij 𝑑
12
≈ 𝑚 𝑡𝑜𝑝
/2 𝑑
23
≈ 𝑚 𝑊 /2
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31 Aug 2012

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

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
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31 Aug 2012

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
32 jiahang.zhong@cern.ch
31 Aug 2012