A new way to identify top quarks

A new way to identify top quarks
Torben Schell
Institute for Theoretical Physics, Heidelberg University
IMPRS-PTFS
May 8, 2014
T. Schell (ITP – U Heidelberg)
HEPTopTagger
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Outline
1
Top quarks?
2
From a hard process to a LHC event and back
3
HEPTopTagger
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Top quarks?
Standard Model of particle physics
[http://en.wikipedia.org/wiki/File:Standard Model of Elementary Particles.svg]
T. Schell (ITP – U Heidelberg)
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Top quarks?
Top history and basics
1995 discovery at the Tevatron
5
2
1
0
-1
160
170
180
190
2
Top Mass (GeV/c )
4
2
Events/(10 GeV/c )
1973 postulated by Kobayashi and Maskawa
to allow for CP violation in the Standard
Model
∆ln(likelihood)
6
3
2
1
mass mt ≈ 173 GeV
0
80
100
120
140
160
180
200
220
240
2
260
280
Reconstructed Mass (GeV/c )
[CDF, Phys. Rev. Lett. 74, 2626 (1995)]
Why are we interested in top quarks?
decay before hadronization
weak scale mass → largest coupling to the Higgs boson → perfect
laboratory to study electroweak symmetry breaking
mediate Higgs production and decay from/to massless particles
physics beyond the Standard Model
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From a hard process to a LHC event and back
Production and decay on parton level ...
top quark pair production at leading order
top quark decay
b
t
q
W
q¯
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From a hard process to a LHC event and back
... and an event simulation for the LHC
parton density functions
parton shower
hard final and initial state
radiation
underlying event
hadronization
(pile–up)
[SHERPA, arXiv:0811.4622]
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From a hard process to a LHC event and back
Jet clustering
Reconstruction of parton level gluons and quarks from calorimeter data
1
Find the minimal distance of all
objects dmin = min(dij , diB ).
2
If dmin ∈ {dij }, join the two
corresponding objects.
If dmin ∈ {diB }, remove object i
→ jet.
3
Iterate until no objects are left.
kT : dij = min(pT ,i , pT ,j )
diB = pT ,i
C/A: dij =
∆Rij
R
∆Rij
R
diB = 1
anti-kT :
∆R
dij = min( pT1,i , pT1,j ) R ij
diB =
1
pT ,i
[Cacciari, Salam, Soyez, arXiv:0802.1189]
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From a hard process to a LHC event and back
Jet filtering
Remove impurities from underlying event by reclustering the jet with an
optimized cone size → reduced area.
start from the calorimeter data that ended up in jet
recluster with a reduced cone size Rfilt
keep only the Nfilt hardest objects
recluster to one object → filtered jet
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actual analysis, the numbers do not yet includ
Higgs [30].
HEPTopTagger
How to detect top quarks?
The algorithm proceeds in the following ste
ΔRbjj
1. define a fat jet using the C/A algorithm
problem: tops decay products will decay
into all directions
→ can not be distinguished from
background
3
103
2
solution: boosted top quarks → fat jets
102
1
10
use moderately boosted tops
0
0
200
400
600
PT[GeV]
1
[Plehn et al. arXiv:1006.2833]
HEPTopTagger
T. Schell (ITP – U Heidelberg)
Figure 2: Left: partonic Rbjj vs pT distributio
only for tagged top quarks and based on the reco
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HEPTopTagger
HEPTopTagger – Steps I
[arXiv:1006.2833]
b
1
t
construction of fat jets:
C/A algorithm with R = 1.5
require pT > 200 GeV
q
W
q¯
2
search for hard substructures:
undo last clustering step: j → j1 j2
mass drop criterion: neglect j2 if mj1 > 0.8mj
iterate until mi < msub = 30 GeV
→ hard substructures
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HEPTopTagger
HEPTopTagger – Steps II
3
filtering:
filter a triple of hard substructures to reduce contamination from
underlying event → 3 jets (j1 , j2 , j3 ).
4
mass range cut:
reject the top candidate if its mass is not inside a mass window
around mt : 150 GeV < m123 < 200 GeV
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HEPTopTagger
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HEPTopTagger
HEPTopTagger – Steps III
5
mass plane cuts: ask for 0.85 mmWt <
mij
m123
< 1.15 mmWt
[Plehn et al. arXiv:1006.2833]
additional cuts to reduce background:
13
if m23 ≈ mW 0.2 < arctan m
m12 < 1.3; else
6
(tag)
pT -cut: Finally, require pT
T. Schell (ITP – U Heidelberg)
m23
m123
> 0.35
> 200 GeV
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HEPTopTagger
It is actually used
close collaboration with ATLAS group of Prof. Sch¨oning
350
[ATLAS, CERN-PH-EP-2012-291]
Data 2011
Z' (1 TeV) σ = 1.3 pb
300
tt
250
Multijet
200
ATLAS
150
∫ L dt = 4.7 fb
σ × BR(Z'→ tt) [pb]
Events / 100 GeV
used in ATLAS analyses
Obs. 95% CL upper limit
102
Exp. 95% CL upper limit
Exp. 1 σ uncertainty
Exp. 2 σ uncertainty
10
Leptophobic Z' (LOx1.3)
ATLAS
HEPTopTagger
-1
1
s = 7 TeV
100
HEPTopTagger
10-1
50
0
500
s = 7 TeV
∫ L dt = 4.7 fb
-1
1000
1500
2000
2500
3000
0.6
0.8
1
1.2
tt Mass [GeV]
[ATLAS, CERN-PH-EP-2012-291]
(a)
T. Schell (ITP – U Heidelberg)
tt
Multijet
HEPTopTagger
1.8
2
2
Obs. 95% CL upper limit
Exp. 95% CL upper limit
Exp. 1 σ uncertainty
KK
BR(g → tt) [pb]
vents / 100 GeV
25
1.6
(a)
35
10
searches for
flavor violation
in the top-Higgs
sector
Data 2011
30
g (1.6 TeV) σ = 0.35 pb
[Greljo, Kamenik, Kopp, arXiv:1404.1278]
KK
1.4
Z' Boson Mass [TeV]
10
Exp. 2 σ uncertainty
KK gluon (LO)
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ATLAS
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HEPTopTagger
Recent developments
extensions and improvements (cut order, distance measure, angular
correlations, N–Subjettiness, low transverse momenta, . . . )
[Plehn et al. arXiv:1111.5034 & arXiv:1312.1504]
reconstruction of heavy resonances
[in preparation]
dσ
fb
GeV
dmrec
t
semilept. tt
s = 8 TeV
150
dσ
fb
GeV
dmrec
t
lept. W+jets
s = 8 TeV
1000
1 - εB
next step: full–hadronic decay of t ¯t H
1
0.98
old default
p
T,fat
> 300 GeV
0.96
100
old default
new default
djsum
new default
djsum
500
50
0.94
pT,fat = [200,250] GeV
0.92
0.9
p
T,fat
= [250,300] GeV
0.88
0.86
0
0
100
200
300
[GeV]
mrec
t
T. Schell (ITP – U Heidelberg)
0
0
100
200
300
[GeV]
mrec
t
HEPTopTagger
0
R = 1.8, s = 13 TeV
0.2
0.4
0.6
0.8
1
εS
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Summary
Summary
there are many reasons to study top quarks
the HEPTopTagger allows to reconstruct hadronically decaying top
quarks in a moderately boosted regime based on jet substructure
close collaboration with experimentalists which use the
HEPTopTagger in ATLAS analyses
T. Schell (ITP – U Heidelberg)
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