Similar a Search for Excited Randall-Sundrum Gravitons from Warped Extra Dimensions with Semi-Leptonic Diboson Final States using the ATLAS detector at the LHC
The FAST Project - Next Generation UHECR Observatory -Toshihiro FUJII
Similar a Search for Excited Randall-Sundrum Gravitons from Warped Extra Dimensions with Semi-Leptonic Diboson Final States using the ATLAS detector at the LHC (20)
Search for Excited Randall-Sundrum Gravitons from Warped Extra Dimensions with Semi-Leptonic Diboson Final States using the ATLAS detector at the LHC
1. Search for Excited Randall-Sundrum Gravitons from
Warped Extra Dimensions with Semi-Leptonic
Diboson Final States using the ATLAS detector at
the LHC
Eric Williams
Columbia University
July 2nd, 2012
Thesis Defense
2. Talk Overview
The Large Hadron Collider
The ATLAS detector
Why extra dimensions?
The analysis
Sources of systematic uncertainties
Final results and conclusions
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
2 / 41
4. The Large Hadron Collider (LHC)
27 km circumference, 100 meters underground
Collides counter-rotating proton beams at center-of-mass
energy = 7 TeV (now at 8 TeV!)
Delivered over 5 fb−1 of 7 TeV data to ATLAS in 2011
Beams collide at the centers of four experiments (detectors):
ATLAS, ALICE, CMS and LHC-b
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
4 / 41
6. The ATLAS Detector
The ATLAS (A Toroidal LHC ApparatuS) detector is designed to be a ‘general-purpose’
detector undertaking a broad range of physics analyses.
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
6 / 41
7. The ATLAS Detector
ATLAS is composed of components, each optimized for particular functions
Inner Detector: measures the momentum and
trajectories charged particles
Electromagnetic Calorimeters: measures the
energies of electrons, photons, and others
Hadronic Calorimeters: measures the energies
of the hadronic particles (‘jets’, protons,
neutrons)
Muon System: measures the momenta of
muons in the event
The combination of these systems allow for
measurments of ‘missing transverse energy’;
the signature of particles not detected, such as
neutrinos
The goal of particle detection is to reconstruct the kinematics of each collision
(particle energies, directions, charges and masses), to determine whether
something “interesting” happened during that event
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
7 / 41
9. Why extra dimensions? RS1 Model
Original Randall-Sundrum (RS1) model offers a solution to the
hierarchy problem by postulating a 5th space-time bounded by two
(3 + 1)-dimensional branes.
Gravity is localized at
y = 0, called the UVor Planck-brane.
SM particles reststricted
to y = πR (IR- or TeVbrane).
Only gravity can
propagate through
‘bulk’.
Physical masses rescaled
by e−πkR : gravity is weak.
The resulting metric is nonfactorizable and depends on the radius y
and curvature k −1 of the extra dimension:
ds2 = e−2ky ηµν dxµ dxν + dy 2 ;
0 ≤ y ≤ πR
Therefore the RS warped geometry model proposes a solution to the
‘hierarchy problem’ with reasonable values of kR ∼ 11
Massive excited graviton modes (G∗ ) are a defining feature
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
9 / 41
10. Why extra dimensions? Bulk RS Model
Modern RS models (bulk RS) allow SM particles into 5-D bulk
Overlap of 5-D profiles at TeV brane (and the Higgs) determine
particles masses
Suppressed coupling to bosons and light
fermions; negligible rates to γγ and
Enhanced coupling to heavy particles
¯
(tt,ZZ and W W )
← motivates search in WW
channel!
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
G*!
G*!
G*!
G*!
G*!
WW
ZZ
HH
gg
tT
July 2nd, 2012
10 / 41
11. Analysis Outline
Analysis Strategy
QCD Multijet Estimation
Event Preselection
Data/MC Samples
Signal (W +jets) Control Region
Object and Event Selection
Signal Region
(*The Ω symbol in corner of following slides denotes my contributions)
12. Analysis Outline
Analysis Strategy
QCD Multijet Estimation
Event Preselection
Data/MC Samples
Signal (W +jets) Control Region
Object and Event Selection
Signal Region
13. Analysis Outline
Analysis Strategy
QCD Multijet Estimation
Event Preselection
Data/MC Samples
Signal (W +jets) Control Region
Object and Event Selection
Signal Region
→ This analysis ( νjj) part of a larger diboson resonance effort at ATLAS
which includes other decay channels:
, jj, ν and ν ν.
14. Analysis Strategy and Previous Limits
Diboson resonances (M > 500 GeV) are characterized by:
a high-pT W boson, decaying leptonically → ν, ( = e, µ)
Select events with one high pT isolated lepton
miss
Require large missing transverse energy (ET )
a high-pT W or Z boson, decaying hadronically → jj
Require at least two high pT jets
a peak in the four-body invariant mass M ( νjj)
Look for excess in the invariant mass of the system
Set 95% confidence limits on a narrow M( νjj) excess
Previous RS1 G∗ → V V mass exclusion limits
Experiment
L [fb−1 ]
Process
Mass
Exclusion
CMS
ATLAS
D0
4.9
1.02
5.4
G∗ → ZZ
RS1
G∗ → ZZ
RS1
G∗
RS1 → WW
1000 GeV
845 GeV
754 GeV
*Currently no published limits on bulk RS graviton production!
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
14 / 41
15. Analysis Outline
Analysis Strategy
QCD Multijet Estimation
Event Preselection
Data/MC Samples
Signal (W +jets) Control Region
Object and Event Selection
Signal Region
16. Data/MC samples
Data samples:
L = 4.701 ± 0.183 fb−1
Events checked for good detector status (Good Runs List)
Monte-Carlo samples:
Weights applied to MC events to account for pile-up, as well as trigger and
reconstruction efficiencies.
Background cross sections normalized to (N)NLO with scale factors (k-factors)
Full detector simulation, reconstructed with same software as data
Backgrounds
W +jets
Z+jets
¯
Top (tt and st)
W W/W Z/ZZ
Generator
Alpgen+Herwig/Jimmy
Alpgen+Herwig/Jimmy
MC@NLO+Herwig/Jimmy
Herwig+Jimmy
Signals (M = 500 -1500)
G∗ → νjj
RS1
G∗
Bulk → νjj
E. Williams (Columbia U.)
Generator
Pythia
CalcHEP+Atlfast II
G∗ → W W → νjj thesis defense
July 2nd, 2012
16 / 41
17. Analysis Outline
Analysis Strategy
QCD Multijet Estimation
Event Preselection
Data/MC Samples
Signal (W +jets) Control Region
Object and Event Selection
Signal Region
18. Object Selection: Electrons and Muons
Ω
Electrons are selected based on shower shape requirements and
cluster/track matching (tight++)
Muons are selected based on track quality and the combination of
tracks from the muon system and inner detector (combined)
Both electrons and muons have requirements on:
104
ATLAS Internal
X → eν jj
s= 7 TeV
103
∫ Ldt = 4.701 fb
-1
102
Events
Events
longitudinal and transverse impact parameters
transverse energy isolation
transverse momentum
eνjj
Data
W+jets
Top
µνjj
ATLAS Internal
4
10
Data
W+jets
Top
X → µν jj
Z+jets
QCD
Diboson
s= 7 TeV
103
102
10
∫ Ldt = 4.701 fb
Z+jets
-1
QCD
Diboson
10
0.5
0.5
(data-MC)/MC
1
10-1
(data-MC)/MC
1
10-1
0
-0.5
0
50
100
150
200
250
300
350
400
450
500
0
-0.5
0
50
100
150
Electron Pt [GeV]
200
250
300
350
400
450
500
Muon Pt [GeV]
*Plots shown after pre-selection and QCD estimation (details later)
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
18 / 41
19. Object Selection: Jets and Emiss
T
Ω
Jets:
Reconstructed using the anti-kt
algorithm with cone size 0.4
Calibrated to the hadronic scale
Required to be central with high
transverse momentum
Energy fraction associated with leading primary vertex (JVF) used to
reject pile-up jets
Emiss :
T
The missing transverse energy (Emiss ) is defined as the negative
T
vector sum of transverse momenta of all the objects in the event
Emiss is reconstructed using the MET RefFinal algorithm
T
Calorimeter cells used are calibrated individually corresponding to the
physics object to which they are associated1
1
My ATLAS ‘service’ work involved the study of the calibration of low-pT objects in the Emiss calculation
T
G∗ → W W → νjj thesis defense
July 2nd, 2012
E. Williams (Columbia U.)
19 / 41
20. Analysis Outline
Analysis Strategy
QCD Multijet Estimation
Event Preselection
Data/MC Samples
Signal (W +jets) Control Region
Object and Event Selection
Signal Region
21. QCD Multijet Estimation
Ω
QCD template method
Before scaling
Events
QCD templates from data
104
ATLAS Internal
X → µν jj
s= 7 TeV
103
‘Anti-Electrons’: reverse only isolation
requirement
‘Anti-Muons’: reverse only transverse
impact parameter significance
→ ‘non-pointing’
∫ Ldt = 4.701 fb
-1
102
Data
W+jets
Top
QCD
Z+jets
Diboson
10
1
10-1
(data-MC)/MC
0.5
0
-0.5
0
50
100
150
200
250
300
350
400
450
500
MT(lep,Emiss) [GeV]
T
Subtract W +jets contamination from QCD
templates
Fit QCD template to data using
miss
MT ( , ET ) distribution
Events
After scaling
104
ATLAS Internal
X → µν jj
s= 7 TeV
103
∫ Ldt = 4.701 fb
-1
2
10
Data
W+jets
Top
Z+jets
QCD
Diboson
10
1
10-1
(data-MC)/MC
Let W/Z+jets normalization float
0.5
0
-0.5
0
50
100
150
200
250
300
350
400
450
500
MT(lep,Emiss) [GeV]
T
Scale Factors
eνjj
µνjj
QCD
W/Z+jets
0.30 ± 0.05
1.10 ± 0.01
0.22 ± 0.05
1.09 ± 0.01
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
21 / 41
22. Analysis Outline
Analysis Strategy
QCD Multijet Estimation
Event Preselection
Data/MC Samples
Signal (W +jets) Control Region
Object and Event Selection
Signal Region
23. Preselection Yields
Ω
Event preselection criteria:
At least two jets with pT > 40 GeV,
lead jet pT > 100 GeV
Events
eνjj
One lepton (e/µ) with pT > 30 GeV
8000
ATLAS Internal
Data
W+jets
Top
X → eν jj
7000
s= 7 TeV
∫ Ldt = 4.701 fb
6000
Z+jets
-1
5000
QCD
Diboson
4000
3000
Emiss > 40 GeV
T
2000
1000
µνjj
37994 ± 152
1270 ± 16
15124 ± 30
474 ± 4
929 ± 36
55792 ± 160
55163
55.0 ± 1.0
8.0 ± 0.2
1.9 ± 0.1
388.4 ± 5.8
64.2 ± 1.0
15.3 ± 0.3
E. Williams (Columbia U.)
45712 ± 170
1802 ± 17
16309 ± 31
490 ± 4
499 ± 16
64812 ± 174
64233
44.5 ± 0.9
6.5 ± 0.2
1.4 ± 0.1
313.8 ± 5.1
51.3 ± 0.9
12.7 ± 0.2
0.5
0
-0.5
2
4
6
8
10
12
14
16
18
20
Avg Int per Xing
µνjj
Events
W +jets
Z+jets
Top
Diboson
QCD
Total Bkgd
Data
G∗
Bulk (800 GeV)
G∗
Bulk (1000 GeV)
G∗
Bulk (1200 GeV)
G∗
RS1 (750 GeV)
G∗
RS1 (1000 GeV)
G∗
RS1 (1250 GeV)
eνjj
ATLAS Internal
9000
Data
W+jets
Top
X → µν jj
8000
s= 7 TeV
∫ Ldt = 4.701 fb
Z+jets
-1
7000
QCD
Diboson
6000
5000
4000
3000
2000
1000
(data-MC)/MC
Process
(data-MC)/MC
Preselected event yields (errors stat. only)
0.5
0
-0.5
2
G∗ → W W → νjj thesis defense
4
6
8
10
12
14
16
18
20
Avg Int per Xing
July 2nd, 2012
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24. Data/MC preselection plots
Ω
µνjj
Events
ATLAS Internal
X → eν jj
103
∫
102
s= 7 TeV
-1
Ldt = 4.701 fb
Events
eνjj
104
104
Data
W+jets
Top
Z+jets
QCD
Diboson
Gkk(800GeV)
Gkk(1000GeV)
Gkk(1200GeV)
ATLAS Internal
X → µν jj
103
∫
102
10
s= 7 TeV
-1
Ldt = 4.701 fb
Data
W+jets
Top
Z+jets
QCD
Diboson
Gkk(800GeV)
Gkk(1000GeV)
Gkk(1200GeV)
10
10-1
0.5
0.5
(data-MC)/MC
1
10-1
(data-MC)/MC
1
0
100
200
300
400
500
600
p (lep,Emiss) [GeV]
T
Events
104
ATLAS Internal
X → eν jj
103
∫
102
0
-0.5
0
700
s= 7 TeV
-1
Ldt = 4.701 fb
100
200
300
400
500
T
104
Data
W+jets
Top
Z+jets
QCD
Diboson
Gkk(800GeV)
Gkk(1000GeV)
Gkk(1200GeV)
600
ATLAS Internal
X → µν jj
103
∫
102
10
700
p (lep,Emiss) [GeV]
T
Events
-0.5
0
s= 7 TeV
-1
Ldt = 4.701 fb
T
Data
W+jets
Top
Z+jets
QCD
Diboson
Gkk(800GeV)
Gkk(1000GeV)
Gkk(1200GeV)
10
10-1
0.5
0.5
(data-MC)/MC
1
10-1
(data-MC)/MC
1
0
-0.5
0
100
200
300
400
500
600
700
0
-0.5
0
100
200
300
400
500
p (j,j) [GeV]
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
600
700
p (j,j) [GeV]
T
T
July 2nd, 2012
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25. Analysis Outline
Analysis Strategy
QCD Multijet Estimation
Event Preselection
Data/MC Samples
Signal (W +jets) Control Region
Object and Event Selection
Signal Region
26. Signal (W +jets) Control Region
Ω
Process
W +jets control region definition:
Preselection Criteria
pT ( , Emiss ) > 200 GeV
T
pT (jj) > 200 GeV
M (jj) < 65 or M (jj) > 115 GeV
eνjj
W+jets
Z+jets
Top
Diboson
QCD
Total Bkgd
Data
µνjj
4004 ± 44
123 ± 5
1135 ± 8
40 ± 1
74 ± 15
5376 ± 48
5404 ± 0.0
3572 ± 43
132 ± 5
951 ± 8
37 ± 1
69 ± 5
4760 ± 44
4743 ± 0.0
Signal control region yields (errors stat. only)
eνjj
µνjj
450
350
data
400
MC backgrounds
350
data
MC backgrounds
300
G* (750 GeV)
G* (750 GeV)
300
250
250
200
200
150
150
100
100
50
50
0
50
100
150
200
250
300
0
50
100
150
200
250
M(jj) [GeV]
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
300
M(jj) [GeV]
July 2nd, 2012
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27. Signal Control Region Sidebands
Ω
Use the M (jj) sidebands to scale W/Z+jets background to data.
M (jj) > 115 GeV
10
1032
Data 2011 2011
Data 2011
Data
W+jetsW+jets
W+jets
Top Top
Top
Z+jets Z+jets
Z+jets
103
102
102
QCD QCD
Diboson
Diboson
QCD
Diboson
10
10
Events
Events
Events
Events
M (jj) < 65 GeV
Data 2011
W+jets
Top
103
Z+jets
102
10
QCD
Diboson
10
1
1
1
-1
10-1
10-1
significance
significance
significance
10
10-1
2
2
0
0
-2
-2
significance
1
2
0
-2
0
500
2
0
-2
500
500
1000
1000
1000
W/Z+jets SF
1500
1500
1500
2000
2000 2000
2500
2500 2500
M(lννjj) [GeV]
M(l M(lν jj) [GeV]
jj) [GeV]
1.11 ± 0.02
Average W/Z+jets SF
500
1000
W/Z+jets SF
1500
2000
2500
M(lν jj) [GeV]
1.02 ± 0.01
1.02 ± 0.03
W/Z+jets MC is scaled by average SF in signal (control) region.
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
27 / 41
28. Analysis Outline
Analysis Strategy
QCD Multijet Estimation
Event Preselection
Data/MC Samples
Signal (W +jets) Control Region
Object and Event Selection
Signal Region
31. W/Z+jets systematics
Ω
To estimate, use low/high dijet mass sideband scale factors as a
function of M( νjj) as ‘envelope’ of uncertainty.
Modulate applied W/Z+jets scale factor within this ‘envelope’ and
measure change in M( νjj) in signal region.
V+jets Scale Factor
The largest systematic uncertainty is due to uncertainy of W/Z+jets
scale factor.
Systematic from W/Z+jets scale factor
1.4
1.2
Sample
1
eνjj
µνjj
+14.45%
−2.06%
+14.57%
−2.08%
+14.71%
−2.23%
+14.72%
−2.23%
0.8
W +jets
0.6
0.4
0.2
0
200
Average
M(jj) < 65
M(jj) > 115
400
600
Z+jets
800
1000 1200 1400 1600 1800 2000
M(lν jj) (M(j,j) > 115GeV or M(j,j) < 65GeV)
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
31 / 41
32. Systematic Uncertainties
Ω
Systematics shown as Average (Min/Max)%
Source
Backgrounds (%)
α
Signal PDF
Jet Energy Scaleα
Luminosityα
Jet Energy Resolutionα
Trigger SFα
Emiss α
T
Lepton Energy Scaleα
Lepton Energy Resolutionα
Lepton Reco SFα
Lepton ID SFα
W/Z+jets SFβ
QCDγ
Signal (%)
10.1 (5.3/17.9)
3.9
1.6 (0.3/2.9)
1.1 (0.5/1.7)
1.1 (0.4/1.6)
<1
<1
<1
<1
9.0 (8.8/9.1)
90 (80/100)
5
4.8 (2.5/9.6)
3.9
1.5 (0.3/3.0)
1.2 (0.6/1.7)
0.1 (0.1/0.1)
<1
<1
<1
<1
-
α: Applies to non-W/Z+jets backgrounds only
β: Applies to W/Z+jets backgrounds only
γ: Applies to QCD background only
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
32 / 41
33. Theoretical Systematics
Theoretical systematics from uncertainties on cross-section, parton
distribution functions (PDFs), and initial/final state radiation (ISR/FSR).
Systematic
WW
W W/W Z/ZZ (σ)
¯
tt (σ)
¯
tt (shape)
tb + tqb + tW (σ)
WZ
ZZ
5%
-
7%
-
5%
-
¯
tt
+7.0%
−9.6%
8%
-
single
top
8%
¯
tt shape systematic from:
Uncertainty on top quark mass → 3%
ISR/FSR → 5%
Generator: MC@NLO/POWHEG → 2.5%
Parton shower model: HERWIG/PYTHIA → 5%
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
33 / 41
34. Final Results and Conclusions
Signal Yields with Systematics
Statistical Analysis
G∗ Exclusion Limits
Conclusions
Future Prospects
35. Signal Region Yields with Systematics
Ω
eνjj
µνjj
Events
eνjj
Process
Data
W+jets
Top
Diboson
QCD
Z+jets
Gkk(800GeV)
Gkk(1000GeV)
Gkk(1200GeV)
102
Signal region event yields (errors stat. + syst.)
10
1
10-1
significance
594 ± 57
15 ± 2
518+50
−73
63 ± 8
16 ± 11
1206+77
−94
1318
34.9 ± 2.7
3.6 ± 0.3
0.4 ± 0.1
163 ± 12.8
18.3 ± 1.5
3.1 ± 0.3
2
0
-2
0
200
400
600
800
1000
1200
1400
1600
1800
2000
M(lν jj) [GeV]
µνjj
Events
698 ± 64
14 ± 2
614+59
−86
76 ± 9
18 ± 24
1420+91
−110
1452
44.0 ± 3.4
4.0 ± 0.3
0.5 ± 0.1
208.2 ± 18.0
21.8 ± 1.7
3.4 ± 0.3
Data
W+jets
Top
Diboson
QCD
Z+jets
Gkk(800GeV)
Gkk(1000GeV)
Gkk(1200GeV)
102
10
1
10-1
significance
W +jets
Z+jets
Top
Diboson
QCD
Total backgrounds
Data
Bulk G∗ (800 GeV)
Bulk G∗ (1000 GeV)
Bulk G∗ (1200 GeV)
RS1 G∗ (750 GeV)
RS1 G∗ (1000 GeV)
RS1 G∗ (1250 GeV)
2
0
-2
0
200
400
600
800
1000
1200
1400
1600
1800
2000
M(lν jj) [GeV]
The greatest deviation from the background prediction occurs at
M (eνjj) = 1000 GeV with p-value = 0.14.
Lacking evidence for new physics, limits on the hypothetical signal
rate are determined with the CLs method.
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
35 / 41
36. Statistical Analysis
M ( νjj) distributions are used as inputs to a poisson Negative
Log-Likelihood Ratio (NLLR) test statistic.
Test statistics separates ‘signal-like’ events from ‘background-like’ events
Multiple pseudo-experiments (PEs) are run under background-only (H0) and
signal+background (H1) hypothesis
Relative location of NLLR(data) to NLLR(H0) and NLLR(H1) distributions
quantify exclusion or discovery!
Confidence levels (CL) defined as fractions
of PEs to right of solid line (data)
CLs =
CLs+b
CLb
If CLs < 1 − 0.95 → excluded at 95% CL
For each mass point, a 95% excluded value of σ × BR is calculated for
background median, ±1, 2σ, and data. Then compared to signal σ × BR.
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
36 / 41
39. G∗ → W W → νjj Summary
Expected/Observed lower mass limits from RS1 and Bulk RS
gravitons:
Signal
RS1 G∗ (exp.)
Bulk RS G∗ (exp.)
RS1 G∗ (obs.)
Bulk RS G∗ (obs.)
eνjj
w/o sys
1017
814
928
818
eνjj
w/ sys
966
728
915
727
µνjj
w/o sys
982
795
982
738
µνjj
w/ sys
907
693
934
631
Comb.
w/o sys
1065
838
973
849
Comb.
w/ sys
952
749
936
714
This analysis is the first exotic diboson resonance search in the
νjj channel at the LHC.
These are the first limits set on Bulk RS W W decay!
Current best limit on RS1 Graviton to W W (754 → 936 GeV)!
Analysis approved by Exotics group
Paper is in final stage of approval, should be submitted to PRD
∼week! (https://cdsweb.cern.ch/record/1456099)
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
39 / 41
40. Future Prospects
The future of LHC collisions promises higher energies and luminosities
(already collected > 5 fb−1 of 8 TeV data)!
Increase in signal cross sections
Concurrent increase in background
production and pile-up!
Highly boosted decay products
→ jet merging
σ× BR [pb]
What does this mean for diboson searches?
7 TeV
1
8 TeV
10-1
10-2
10-3
400
600
800
1000
1200
1400
1600
G*Bulk Mass [GeV]
W W
W
W W
W
W W W
W
W W
W W
W
W
W W W
W W W
W W
W W
W
W W W
W
W W
W W
W
W
W W
W W
WW
W W W
W
W W
W W W
W
W W
W W
W
W W W
W
pT p
p
p (W)≫M(W) (W)≫M(W)(W)≫M(W) T(W)≫M(W)
pT(W)~M(W)
p
pT(W)~0
pT(W)~0 T(W)~0 p T(W)~M(W)T(W)~M(W) T(W)≫M(W) p
p
pT(W)≫M(W) p p
Tp
T p
)~0
(W)~0 T(W)~0 T(W)~0(W)~M(W) T(W)~M(W)T(W)~M(W) T(W)≫M(W)
pT(W)~0T(W)~M(W) p pp(W)~M(W)pT(W)≫M(W)
p pp pT
W)~0 pT(W)~M(W)(W)~M(W)TpT(W)≫M(W) (W)≫M(W) T(W)≫M(W) T(W)≫M(W)
p pT(W)~M(W) T(W)~0(W)~M(W) T p
p
T
T
T
W W
W
Solution: Use merged jets to reduce backgrounds
Much to look forward to at the LHC in 2012 and beyond!
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
40 / 41
42. Object Definitions
Muons
Electrons
egammma author 1 or 3
1,2,1,2,1
STACO combined muons1,2,2,1
|η| < 2.47 w/ crack region excluded1,2,1,2,1
pT > 30 GeV
good object quality (el OQ & 1446 == 0)1,2,1
|η| < 2.41,2,1,2,1
pT > 30 GeV
nBLayerHits > 0 || !expectBLayerHit1,2,1,1
tight++ electron1,2,1,2,1
nPixHits + nPixelDeadSensors > 11,2,1,2,1
|el trackz0pv| < 1 mm2,1,2
nSCTHits + nSCTDeadSensors ≥ 61,2,1,2,1
impact parameter significance wrt. primary vertex
√
|el trackd0pv/ el tracksigd0pv| < 102,1,2
nPixHoles + nSCTHoles < 31,2,1,2,1
Isolation
CaloIsoCorrection::GetPtNPVCorrectedIsolation
etcone30 corrected < 6 GeV2
Jets and Emiss
T
TRT extension1,2,1,1
N = nTRTOutliers + nTRTHits
if |η| < 1.9 then require:
nTRTOutliers/N < 0.9 && N > 5
if |η| > 1.9 && N > 5 then require:
nTRTOutliers/N < 0.9
|z0 exPV| < 1 mm2,1,
AntiKt4TopoEMJets (EM + JES)
1,2,1,2,1
pT > 40 GeV, |ηEM | < 2.8
LOOSER jet cleaning requirements
|JVF| > 0.751,2,1,2,1
MET RefFinal within |ηcl | < 4.91,2,2
SM
1. W → ν/Z →
2. EWK (W W ,W/Zγ)
E. Williams (Columbia U.)
impact parameter significance2,1,2
√
|d0 exPV/ cov d0 exPV| < 3
Isolation1,2
CorrectCaloIso::CorrectEtCone30Rel
etcone30 corrected/pT < 0.14
ptcone30/pT < 0.15
Higgs
1. W → ν ν
2. W → νjj
SUSY
1. 1 lepton
G∗ → W W → νjj thesis defense
July 2nd, 2012
42 / 41
43. Data/MC samples
Data samples used:
L = 4.701fb−1 from period D-M
(OflLumi-7TeV-002)
NTUP SMWLNUJJ, p833 skims
Egamma and Muons streams
SM W/Z GRL
Monte-Carlo samples used:
NTUP SMWZ, r3043 r2993 p833 (mc11c)
Weights applied to MC events to account for pile-up, as well as trigger and
reconstruciton efficiencies.
Background cross sections normalized to N(N)LO with k-factors
Backgrounds
W +jets
Z+jets
W W/W Z/ZZ
¯
Top (tt and st)
Generator
Alpgen+Herwig/Jimmy
Alpgen+Herwig/Jimmy
Herwig+Jimmy
MC@NLO+Herwig/Jimmy
Signals (M = 500 -1500)
G∗ → νjj
RS1
G∗ → νjj
bulk
W → νjj
E. Williams (Columbia U.)
Cross Sections [pb]
14060
1070
44.9/18.5/5.96
164, 83.93
Generator
Pythia
CalcHEP+Atlfast II
Pythia
G∗ → W W → νjj thesis defense
July 2nd, 2012
43 / 41
44. Data/MC samples: Alpgen W +jets reweighting
W +jets is the dominant background
It has been observed that ALPGEN W +jets samples over-estimate the
background in high W pT regimes
However Sherpa W +jets MC backgrounds match the data better
than the Alpgen samples in these regions
eνjj
µνjj
Truth Pt of W Boson 2 2 0
-1
6
10
L dt ~ 4.71 pb
Events
107
107
Events
Events
Events
Truth Pt of W Boson 2 1 0
W e
W e
Alpgen
Sherpa
105
10
10
107
7
L dt ~ 4.71 pb
W µ
W µ
Alpgen
Sherpa
5
104
104
10
103
10
103
3
3
102
102
10
101
10
101
1.8
1.6
1.4
1.2
11
0.8
0.6
0.4
0.2
00
0
Data / MC
2
10-2
2
SHERPA/ALPGEN
1
10-1
10-1
SHERPA/ALPGEN
1
10-1
10-1
Data / MC
-1
6
10
10
105
100
200
300
400
500
600
700
800
900
1000
Truth pT of W Boson [GeV]
Generator-level pT of W Boson [GeV]
2
10-2
2
1.8
1.6
1.4
1.2
11
0.8
0.6
0.4
0.2
0
00
100
200
300
400
500
600
700
800
900
1000
Truth pT of W Boson [GeV]
Generator-level pT of W Boson [GeV]
Comparison of Alpgen and Sherpa W +jets generator-level W pT
Due to the fact that Sherpa samples were not available with
sufficient statistics, the solution:
→ reweight Alpgen W +jets to match Sherpa generator-level W pT
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
44 / 41
45. miss
pT ( , ET ), ALPGEN→ SHERPA truth W pT reweighting
104
ATLAS Internal
X → eν jj
103
s= 7 TeV
∫ Ldt = 4.701 fb
-1
102
eνjj
With Reweighting
Events
Events
W/out Reweighting
Data 2011
W+jets
Top
104
ATLAS Internal
X → eν jj
103
∫ Ldt = 4.701 fb
Z+jets
-1
Diboson
QCD
102
10
0.5
0.5
0
0
100
200
300
400
500
600
0
-0.5
700
0
100
200
300
400
500
600
104
ATLAS Internal
X → µν jj
103
s= 7 TeV
∫ Ldt = 4.701 fb
-1
102
Data 2011
W+jets
Top
700
Pt(lep+met)
Events
Pt(lep+met)
Events
QCD
Diboson
1
-0.5
104
ATLAS Internal
X → µν jj
103
s= 7 TeV
∫ Ldt = 4.701 fb
Z+jets
-1
Diboson
QCD
102
10
Data 2011
W+jets
Top
Z+jets
Diboson
QCD
10
1
10-1
0.5
0.5
significance
1
10-1
significance
Z+jets
10-1
significance
1
µνjj
Data 2011
W+jets
Top
10
10-1
significance
s= 7 TeV
0
-0.5
0
100
200
300
400
500
600
700
0
-0.5
0
100
200
300
400
500
Pt(lep+met)
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
600
700
Pt(lep+met)
July 2nd, 2012
45 / 41
46. pdijet , ALPGEN→ SHERPA truth W pT reweighting
T
With Reweighting
104
ATLAS Internal
Data 2011
W+jets
Top
X → eν jj
103
s= 7 TeV
∫ Ldt = 4.701 fb
eνjj
104
ATLAS Internal
Diboson
QCD
∫ Ldt = 4.701 fb
102
1
0.5
0.5
0
-0.5
0
100
200
300
400
500
600
0
-0.5
700
0
100
200
300
400
500
600
p (j,j) [GeV]
ATLAS Internal
Data 2011
W+jets
Top
X → µν jj
103
s= 7 TeV
∫ Ldt = 4.701 fb
T
Events
104
104
ATLAS Internal
s= 7 TeV
∫ Ldt = 4.701 fb
Z+jets
-1
Diboson
QCD
102
Data 2011
W+jets
Top
X → µν jj
103
Z+jets
-1
700
p (j,j) [GeV]
T
Events
QCD
Diboson
10-1
significance
1
Diboson
QCD
102
10
10
1
10-1
0.5
0.5
significance
1
10-1
significance
Z+jets
10
10-1
significance
s= 7 TeV
-1
10
µνjj
Data 2011
W+jets
Top
X → eν jj
103
Z+jets
-1
102
Events
Events
W/out Reweighting
0
-0.5
0
100
200
300
400
500
600
700
0
-0.5
0
100
200
300
400
500
p (j,j) [GeV]
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
600
700
p (j,j) [GeV]
T
T
July 2nd, 2012
46 / 41
47. Emiss , ALPGEN→ SHERPA truth W pT reweighting
T
ATLAS Internal
104
X → eν jj
s= 7 TeV
103
∫ Ldt = 4.701 fb
-1
102
eνjj
With Reweighting
Events
Events
W/out Reweighting
Data 2011
W+jets
Top
X → eν jj
s= 7 TeV
103
Z+jets
Diboson
QCD
∫ Ldt = 4.701 fb
-1
102
10
0.5
0.5
0
0
100
200
300
400
500
0
-0.5
600
0
100
200
300
400
500
ATLAS Internal
104
X → µν jj
s= 7 TeV
∫ Ldt = 4.701 fb
103
-1
102
Data 2011
W+jets
Top
600
MEt [GeV]
Events
MEt [GeV]
Events
QCD
Diboson
1
-0.5
ATLAS Internal
104
X → µν jj
s= 7 TeV
∫ Ldt = 4.701 fb
103
Z+jets
Diboson
QCD
-1
102
10
Data 2011
W+jets
Top
Z+jets
Diboson
QCD
10
1
10-1
0.5
0.5
significance
1
10-1
significance
Z+jets
10-1
significance
1
µνjj
Data 2011
W+jets
Top
10
10-1
significance
ATLAS Internal
104
0
-0.5
0
100
200
300
400
500
600
0
-0.5
0
100
200
300
400
MEt [GeV]
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
500
600
MEt [GeV]
July 2nd, 2012
47 / 41
48. plepton , ALPGEN→ SHERPA truth W pT reweighting
T
ATLAS Internal
104
Data 2011
W+jets
Top
X → eν jj
s= 7 TeV
103
∫ Ldt = 4.701 fb
s= 7 TeV
∫ Ldt = 4.701 fb
10
1
10-1
0.5
0.5
significance
1
0
-0.5
0
50
100
150
200
250
300
350
400
450
0
-0.5
500
0
50
100
150
200
250
300
350
ATLAS Internal
104
Data 2011
W+jets
Top
X → µν jj
s= 7 TeV
103
∫ Ldt = 4.701 fb
Diboson
QCD
102
ATLAS Internal
104
450
500
Data 2011
W+jets
Top
X → µν jj
s= 7 TeV
103
Z+jets
-1
400
Lepton Pt [GeV]
Events
Lepton Pt [GeV]
Events
QCD
Diboson
102
10-1
∫ Ldt = 4.701 fb
Z+jets
-1
Diboson
QCD
102
10
10
1
10-1
0.5
0.5
significance
1
10-1
significance
Z+jets
-1
10
µνjj
Data 2011
W+jets
Top
X → eν jj
103
Diboson
QCD
102
significance
ATLAS Internal
104
Z+jets
-1
eνjj
With Reweighting
Events
Events
W/out Reweighting
0
-0.5
0
50
100
150
200
250
300
350
400
450
500
0
-0.5
0
Lepton Pt [GeV]
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
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100
150
200
250
300
350
400
450
500
Lepton Pt [GeV]
July 2nd, 2012
48 / 41
49. miss
MT ( , ET ), ALPGEN→ SHERPA truth W pT reweighting
104
With Reweighting
ATLAS Internal
Data 2011
W+jets
Top
X → eν jj
s= 7 TeV
103
∫ Ldt = 4.701 fb
104
s= 7 TeV
∫ Ldt = 4.701 fb
1
10-1
0.5
0.5
significance
1
0
-0.5
0
50
100
150
200
250
300
350
400
450
0
-0.5
500
MT(lep,Emiss) [GeV]
0
50
100
150
200
250
300
104
ATLAS Internal
Data 2011
W+jets
Top
X → µν jj
s= 7 TeV
103
∫ Ldt = 4.701 fb
104
450
500
Data 2011
W+jets
Top
X → µν jj
s= 7 TeV
∫ Ldt = 4.701 fb
Z+jets
-1
Diboson
QCD
102
400
ATLAS Internal
103
Z+jets
-1
350
MT(lep,Emiss) [GeV]
T
Events
T
Events
QCD
Diboson
10
10-1
Diboson
QCD
102
10
10
1
10-1
0.5
0.5
significance
1
10-1
significance
Z+jets
102
10
µνjj
Data 2011
W+jets
Top
X → eν jj
-1
Diboson
QCD
102
significance
ATLAS Internal
103
Z+jets
-1
eνjj
Events
Events
W/out Reweighting
0
-0.5
0
50
100
150
200
250
300
350
400
450
500
MT(lep,Emiss) [GeV]
0
-0.5
0
T
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
50
100
150
200
250
300
350
400
450
500
MT(lep,Emiss) [GeV]
T
July 2nd, 2012
49 / 41
50. N jets, ALPGEN→ SHERPA truth W pT reweighting
ATLAS Internal
104
X → eν jj
s= 7 TeV
∫ Ldt = 4.701 fb
103
-1
102
eνjj
With Reweighting
Data 2011
W+jets
Top
Events
Events
W/out Reweighting
X → eν jj
s= 7 TeV
Z+jets
Diboson
QCD
∫ Ldt = 4.701 fb
103
102
10
-1
Data 2011
W+jets
Top
Z+jets
QCD
Diboson
10
1
10-1
0.5
0.5
significance
1
10-1
significance
ATLAS Internal
104
0
-0.5
2
4
6
8
10
0
-0.5
12
2
4
6
8
10
12
ATLAS Internal
104
X → µν jj
s= 7 TeV
∫ Ldt = 4.701 fb
103
-1
102
Data 2011
W+jets
Top
Jet N
Events
Events
Jet N
104
Diboson
QCD
∫ Ldt = 4.701 fb
103
102
-1
Data 2011
W+jets
Top
Z+jets
Diboson
QCD
10
1
10-1
0.5
0.5
significance
1
10-1
significance
X → µν jj
s= 7 TeV
Z+jets
10
µνjj
ATLAS Internal
0
-0.5
2
4
6
8
10
0
-0.5
12
2
4
6
8
10
Jet N
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
12
Jet N
July 2nd, 2012
50 / 41
51. plead
T
jet
, ALPGEN→ SHERPA truth W pT reweighting
104
ATLAS Internal
X → eν jj
s= 7 TeV
103
∫ Ldt = 4.701 fb
-1
102
eνjj
With Reweighting
Events
Events
W/out Reweighting
Data 2011
W+jets
Top
104
X → eν jj
s= 7 TeV
∫ Ldt = 4.701 fb
Z+jets
-1
Diboson
QCD
102
10
0.5
0.5
0
0
100
200
300
400
500
600
0
-0.5
700
0
100
200
300
400
104
ATLAS Internal
X → µν jj
s= 7 TeV
103
∫ Ldt = 4.701 fb
-1
102
Data 2011
W+jets
Top
500
600
700
Lead Jet Pt [GeV]
Events
Lead Jet Pt [GeV]
Events
QCD
Diboson
1
-0.5
104
ATLAS Internal
X → µν jj
s= 7 TeV
103
∫ Ldt = 4.701 fb
Z+jets
-1
Diboson
QCD
102
10
Data 2011
W+jets
Top
Z+jets
Diboson
QCD
10
1
10-1
0.5
0.5
significance
1
10-1
significance
Z+jets
10-1
significance
1
µνjj
Data 2011
W+jets
Top
10
10-1
significance
ATLAS Internal
103
0
-0.5
0
100
200
300
400
500
600
700
0
-0.5
0
Lead Jet Pt [GeV]
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600
700
Lead Jet Pt [GeV]
July 2nd, 2012
51 / 41
52. psecond
T
jet
, ALPGEN→ SHERPA truth W pT reweighting
104
ATLAS Internal
X → eν jj
s= 7 TeV
103
∫ Ldt = 4.701 fb
-1
102
eνjj
With Reweighting
Events
Events
W/out Reweighting
Data 2011
W+jets
Top
104
X → eν jj
s= 7 TeV
∫ Ldt = 4.701 fb
Z+jets
-1
Diboson
QCD
102
10
0.5
0.5
0
0
100
200
300
400
500
600
0
-0.5
700
0
100
200
300
400
104
ATLAS Internal
X → µν jj
s= 7 TeV
103
∫ Ldt = 4.701 fb
-1
102
Data 2011
W+jets
Top
500
600
700
Second Jet Pt [GeV]
Events
Second Jet Pt [GeV]
Events
QCD
Diboson
1
-0.5
104
ATLAS Internal
X → µν jj
s= 7 TeV
103
∫ Ldt = 4.701 fb
Z+jets
-1
Diboson
QCD
102
10
Data 2011
W+jets
Top
Z+jets
Diboson
QCD
10
1
10-1
0.5
0.5
significance
1
10-1
significance
Z+jets
10-1
significance
1
µνjj
Data 2011
W+jets
Top
10
10-1
significance
ATLAS Internal
103
0
-0.5
0
100
200
300
400
500
600
700
0
-0.5
0
Second Jet Pt [GeV]
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600
700
Second Jet Pt [GeV]
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53. ¯
tt Control Region Definition and Yields
¯
¯
tt control region is used to check tt agreement in high-pT region.
60
¯
tt control region definition:
Data
t( t )+X
W → l ν +HF+X
W → l ν +X
*
Z/ γ →l +l +X
VV+V γ
Multijet
G* → WW (M=1 TeV)
W’ → WZ (M=1 TeV)
50
40
≥ 2 b-tagged jets w/ pT > 40 GeV
∫ Ldt = 4701.39 pb
30
-1
20
pT (jj) > 200 GeV
10
M (jj) < 65 GeV or M (jj) > 115 GeV
0
significance
3
eνjj
100
150
200
250
50
100
150
200
250
0
295 ± 17
23 ± 4
301 ± 17
0±0
300
PT (Emiss) [GeV]
T
µνjj
80
¯
tt
¯
N on − tt
Data
RS1 G∗ (M = 1 TeV)
300
-1.5
-30
Process
50
1.5
279 ± 16
19 ± 4
301 ± 17
0±0
Data
t( t )+X
W → l ν +HF+X
W → l ν +X
*
Z/ γ →l +l +X
VV+V γ
Multijet
G* → WW (M=1 TeV)
W’ → WZ (M=1 TeV)
70
60
50
∫ Ldt = 4701.39 pb
40
-1
30
20
10
¯
tt control region yields (errors stat. only)
0
significance
3
50
100
150
200
250
50
100
150
200
250
1.5
0
-1.5
-30
MT (l , Emiss) [GeV]
T
E. Williams (Columbia U.)
∗
G
→ W W → νjj thesis defense
July 2nd, 2012
53 / 41
54. Impact Parameter
●
Distance between the point of closest approach of a track and primary vertex
Transverse IP d0 is this distance in transverse plane x,y
●
d0 significance = |d0|/(σ(d0))1/2
●
Longitudinal IP z0 is the z-coordinate of this point
●
55. W+jets QCD contamination
Goal is to estimate, and correct for, the amount of W+jets events in QCD
template. This method assumes that e → jet ∼ jet → e.
i) Create W +jets ‘contamination’ samples by running over W+jets MC
with QCD ‘anti-lepton’ requirements:
electrons: Reverse calorimeter isolation (etcone 30 > 6 GeV)
muons: Reverse ‘pointing’ (|d0sig| > 3 GeV)
ii) Scale W +jets contamination template with W +jets cross-section and
lumi to get estimated distribution of W +jets events in QCD template
iii) Subtract W +jets contamination template from un-scaled QCD
template
iv) Scale new QCD template from fit to data
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
55 / 41
56. W+jets QCD contamination
QCD ∼ 18% W +jets in eνjj
QCD ∼ 7% W +jets in µνjj
103
Unscaled QCD
103
Unscaled QCD
W+jets contamination
W+jets contamination
102
102
10
10
1
1
0
50
100
150
200
250
300
350
400
450
500
0
50
100
150
200
250
300
350
400
450
500
MT(µ,Emiss) [GeV]
MT(e,Emiss) [GeV]
T
T
103
QCD w/out W+jets sub
QCD w/out W+jets sub
102
QCD w/ W+jets sub
QCD w/ W+jets sub
2
10
10
10
1
1
0
50
100
150
200
250
300
350
400
450
MT(e,Emiss)
T
E. Williams (Columbia U.)
500
10-1
0
50
100
[GeV]
G∗ → W W → νjj thesis defense
150
200
250
300
350
400
450
500
MT(µ,Emiss) [GeV]
T
July 2nd, 2012
56 / 41
57. W+jets QCD contamination
µνjj
ATLAS Internal
Data 2011
W+jets
Top
X → eν jj
s= 7 TeV
103
Events
Events
eνjj
104
∫ Ldt = 4.701 fb
-1
Diboson
QCD
0.5
significance
1
10-1
0.5
0
-0.5
0
50
100
150
200
250
104
300
350
400
ATLAS Internal
s= 7 TeV
∫ Ldt = 4.701 fb
0
-0.5
500
0
50
100
150
200
250
400
450
ATLAS Internal
10
500
Data 2011
W+jets
Top
X → µν jj
s= 7 TeV
103
∫ Ldt = 4.701 fb
Z+jets
-1
QCD
Diboson
102
350
MT(lep,Emiss) [GeV]
T
4
Z+jets
-1
300
[GeV]
Data 2011
W+jets
Top
X → eν jj
103
450
MT(lep,Emiss)
T
Events
significance
1
Events
Z+jets
10
10-1
Diboson
QCD
102
10
10
1
10-1
0.5
0.5
significance
1
10-1
significance
s= 7 TeV
102
10
With W+jets
subtraction
Data 2011
W+jets
Top
X → µν jj
∫ Ldt = 4.701 fb
-1
Diboson
With out
W+jets
subtraction
ATLAS Internal
103
QCD
Z+jets
102
104
0
-0.5
0
50
E. Williams (Columbia U.)
100
150
200
250
300
350
400
450
MT(lep,Emiss)
T
500
0
-0.5
[GeV]
G∗ → W W → νjj thesis defense
0
50
100
150
200
250
300
350
400
450
500
MT(lep,Emiss) [GeV]
T
July 2nd, 2012
57 / 41
58. νjj QCD Estimation
µνjj
ATLAS Internal
Data 2011
W+jets
Top
X → eν jj
s= 7 TeV
103
∫ Ldt = 4.701 fb
-1
W/out
Events
Events
eνjj
104
Diboson
1
10-1
0.5
0.5
significance
1
0
-0.5
0
50
100
150
200
250
300
350
400
450
0
-0.5
500
MT(lep,Emiss) [GeV]
0
50
100
150
200
250
300
104
ATLAS Internal
Data 2011
W+jets
Top
X → eν jj
s= 7 TeV
103
∫ Ldt = 4.701 fb
500
Data 2011
W+jets
Top
X → µν jj
s= 7 TeV
∫ Ldt = 4.701 fb
Z+jets
Diboson
QCD
102
10
1
10-1
0.5
0.5
significance
1
10-1
significance
450
-1
10
scaling
400
ATLAS Internal
103
QCD
Diboson
102
QCD
104
Z+jets
-1
350
MT(lep,Emiss) [GeV]
T
Events
Events
T
With
QCD
Z+jets
10
10-1
significance
s= 7 TeV
102
10
scaling
Data 2011
W+jets
Top
X → µν jj
∫ Ldt = 4.701 fb
-1
Diboson
QCD
ATLAS Internal
103
QCD
Z+jets
102
104
0
-0.5
0
50
100
150
200
250
300
350
400
450
MT(lep,Emiss)
T
500
0
-0.5
0
50
[GeV]
150
200
250
300
350
400
450
500
MT(lep,Emiss) [GeV]
T
Scale Factors
eνjj
µνjj
QCD
V+jets
E. Williams (Columbia U.)
100
0.30 ± 0.05
1.10 ± 0.01
0.22 ± 0.05
1.09 ± 0.01
G∗ → W W → νjj thesis defense
July 2nd, 2012
58 / 41
59. νjj QCD Estimation
QCD distributions before and after scaling.
eνjj
µνjj
No QCD scaling
No QCD scaling
After QCD scaling
2
After QCD scaling
102
10
10
10
1
1
0
50
100
150
200
250
300
350
400
450
500
0
50
100
mT(e,MET) [GeV]
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
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200
250
300
350
400
450
500
mT(mu,MET) [GeV]
July 2nd, 2012
59 / 41
60. Preselection Definition
Reject event if:
dR( , jet) < 0.4
Contains any looser bad jets
Jets found in LAr hole (simple veto)
Data, require pT > 40 × (1−BCH CORR JET)/(1−BCH CORR CELL)
MC, require pT > 40 GeV, only applied to fraction of MC events
corresponding to affeted data lumi (∼ 17%)
Has noise burst with LArError = 2
Fails QCD triangle cut
Require:
Lepton trigger:
Data
Period
Run
Range
Electron
Trigger
Muon
Trigger
D-J
K
L-M
179710 → 186755
186873 → 187815
188902 → 191933
EF e20 medium
EF e22 medium
EF e22vh medium1
EF
EF
EF
EF
mu18
mu18
mu18
mu40
MG or EF mu40 MSonly barrel
MG medium or EF mu40 MSonly barrel
MG medium or
MSonly barrel medium
First primary vertex has Ntrack >= 3
→ Only one lepton (e/µ) with pT > 30 GeV
→ At least two jets with pT > 40 GeV
→ Lead jet pT > 100 GeV
→ Emiss > 40 GeV
T
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
60 / 41
61. Signal Significance
The ultimate goal of an experimental search for a new particle is to state whether or not
a statistically significant observation of the signal has been made. In other words, to
answer the canonical question:
Given the data, is it possible to distinguish between two hypotheses?
Three main steps toward answering this question:
1 Define a test-statistic which optimizes the
separation of the signal+background
hypothesis (H1) and the background-only
hypothesis (H0)
2 Run an appropriate number of
pseudo-experiments (Frequentist) for both
hypothesis, incorporating all signal and
background nuisance parameters (systematics)
in a coherent way (Bayesian).
3 Define confidence levels designating exclusions
2012 Higgs → γγ 4.7fb−1 result
or discoveries
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
61 / 41
62. 1) Define test-statistic: Likelihood-Ratio
Neyman-Pearson lemma suggests that the most powerful test for
statistically separating two point hypotheses is the likelihood-ratio
test, that is:
L(s + b|x)
Λ=
L(b|x)
s = signal
b = background
x = data
L = likelihood
Rate of signal or background events follow a Poisson distribution,
appropriate choice for likelihood functional form:
L(s + b) =
E. Williams (Columbia U.)
(s + b)x e−(s+b)
(b)x e−b
, L(b) =
x!
x!
G∗ → W W → νjj thesis defense
July 2nd, 2012
62 / 41
63. 1) Define test-statistic: Likelihood-Ratio
With this choice, combining likelihoods from multiple channels (e.g. X → Y and
X → Z) as well as from multiple bins within a discriminating variable (e.g.
M (X)) is natural:
channels bins
Λ(x) =
i
j
(sij + bij )xij e−(sij +bij ) (bij )xij e−(bij )
/
.
xij !
xij !
In the high-statistics limit the distributions of -2 ln Λ are expected to converge to
(χ2 − χ2 ), thus it is more common to use:
s+b
b
NLLR(x) = −2 ln(Λ(x))
channels bins
= −2
sij − xij ln 1 +
i
j
sij
bij
This test statistic decreases monotonically for increasingly signal-like (decreasingly
background-like) experiments. Can be used to order data outcomes relative to
each other in hypothesis significance
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
63 / 41
64. 2) Pseudo-Experiments: A Semi-Frequentist Approach
Assuming that the data is drawn randomly from a Poisson parent distribution, we
can create pdfs of NLLR(x) for both the signal+background hypothesis (H1) and
the background-only (H0) hypothesis, by conducting pseudo-experiments
Systematic uncertainties (nuisance parameters) are incorporated by sampling a
bifurcated Gaussian distribution with the ±σ uncertainties estimated for each
source (hence ‘Semi’-Frequentist)
m
m
The pseudo-experiment background (Bj ) and signal (Sj ) yields are then given as:
bkgd
Nsys
m
Bj
=
0,m
Bj (1
bkgd
gi )
+
i
sig
Nsys
0,m
m
Sk = Sk (1 +
sig
gi )
i
Where B 0,m (S 0,m ) is the nominal background (signal) poisson yield for channel j (k)
and bin m. g bkgd (g sig ) is the contribution from systematic uncertainty i.
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
64 / 41
65. 2) Pseudo-Experiments: A Semi-Frequentist Approach
Running O(20k) pseudo-experiments, we evaulate the NLLR distributions under
the H0, NLLR(x = Db ), and H1, NLLR(x = Ds+b ), hypotheses. Where:
Nbins Nb
Nbins
m
Bj ,
Db =
m
j
Ds+b =
Nb
m
Ns
m
Bj +
(
j
N
m
Sk )
k
Bkgd Only
Sig + Bkgd
-2ln(Λ(x))
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
65 / 41
66. 2) Pseudo-Experiments: A Semi-Frequentist Approach
Running O(20k) pseudo-experiments, we evaulate the NLLR distributions under
the H0, NLLR(x = Db ), and H1, NLLR(x = Ds+b ), hypotheses. Where:
Nbins Nb
Nbins
m
Bj ,
Db =
m
j
Ds+b =
Nb
m
Ns
m
Bj +
(
j
N
m
Sk )
k
Bkgd Only
Sig + Bkgd
NLLR(xdata)
-2ln(Λ(x))
Location of measured data on NLLR pdf (Prior Predictive Ensemble) used to
quantify exclusion/discovery
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
66 / 41
67. 3) Modified Frequentist Confidence Levels: CLs
Confidence levels defined as the fraction of outcomes predicted to fall
outside of the specified confidence interval
CLs+b : fraction of H1 pseudo-experiments less signal-like than data
∞
CLs+b = Ps+b (X ≥ Xobs ) =
P(x = Ds+b ) dP
NLLR(x=Dobs )
CLb : fraction of H0 pseudo-experiments less signal-like than data
∞
CLb = Pb (X ≥ Xobs ) =
P(x = Db ) dP
NLLR(x=Dobs )
Therefore...
High CLs+b → data signal-like. (otherwise, used for exclusion)
High CLb (or low 1 − CLb ) → data not background like.
For discovery, (1-CLb ) ≡ p-value = the probability, under H0 hypothesis, that background
fluctuated to produce observed signal. Typically require (1-CLb ) < 5σ(4.3 × 10−7 ) to
claim discovery
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
67 / 41
68. 3) Modified Frequentist Confidence Levels: CLs
N
Bkgd Only
Sig + Bkgd
1-CLb
CLs+b
NLLR(xdata)
-2ln(Λ(x))
Therefore...
High CLs+b → data signal-like. (otherwise, used for exclusion)
High CLb (or low 1 − CLb ) → data not background like.
For discovery, (1-CLb ) ≡ p-value = the probability, under H0 hypothesis, that background
fluctuated to produce observed signal. Typically require (1-CLb ) < 5σ(4.3 × 10−7 ) to
claim discovery
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
68 / 41
69. 3) Modified Frequentist Confidence Levels: CLs
The strictly frequentist CLs+b confidence level, while a powerful
statistical tool, is unstable if the background model dramatically
disagrees with the data:
Background overestimated → low CLs+b → possible exclusion!
Background underestimated → high CLs+b → possible discovery!
The solution: The modified frequentist confidence level, CLs
CLs ≡
CLs+b
CLb
Normalizing CLs+b with CLb removes the dependence on background
modelling and leads to more conservative limits on H1 hypothesis, as
well as lower false exclusion rate (type II error) than nominal (1− CL)
A signal model is then excluded at or above
95% confidence level if CLs ≤ 0.05
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
69 / 41
70. νjj Signal Systematics
Acceptance systematics for ‘bulk’ Randal-Sundram GRS (M = 700 GeV) sample.
Systematic
JES
JER
LES
LER
All Clusters
Met PileUp
ID SF
Reco SF
Trigger SF
Iso SF
Signal PDF
Luminosity
V+jets
Total
eνjj [%]
2.83
0.90
0.06
0.06
0.10
0.03
0.85
0.91
0.55
2.00
5.00
3.90
0.00
µνjj [%]
2.63
0.99
0.07
0.08
0.06
0.07
0.04
0.39
1.74
1.00
5.00
3.90
0.00
7.40
7.23
Muon energy resolution chosen as ’worst’ smearing between ID and MS.
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
70 / 41
71. νjj Background Systematics
Table: eνjj percent ∆ acceptance.
Systematic
Wjets
Zjets
TTBar
Single
Top
Diboson
QCD
JES
JER
LES
LER
All Clusters
Met PileUp
ID SF
Reco SF
Trigger SF
Iso SF
Luminosity
MJ Normalization
V+jets
(10.99)
(1.14)
(0.1)
(0.42)
(0.51)
(0.45)
(0.96)
(0.81)
(0.56)
(2)
5
(18.04)
(6.96)
(0.8)
(1.59)
(1.56)
(2.13)
(0.92)
(0.83)
(0.53)
(2)
5.11
4.78
0.06
0.18
0.14
0.91
0.78
0.89
0.88
0.56
2
3.9
-
8.37
1.39
0.08
0.07
1.25
0.85
0.88
0.88
0.56
2
3.9
-
10.33
3.13
0.05
0.08
1.69
1.72
0.89
0.8
0.59
2
3.9
-
80.0
-
5
5.11
6.74
9.76
12.28
Total
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
80.0
July 2nd, 2012
71 / 41
72. νjj Background Systematics
Table: µνjj percent ∆ acceptance.
Systematic
Wjets
Zjets
TTBar
Single
Top
Diboson
QCD
JES
JER
LES
LER
All Clusters
Met PileUp
ID SF
Reco SF
Trigger SF
Iso SF
Luminosity
MJ Normalization
V+jets
(10.75)
(0.27)
(0.4)
(1.21)
(0.29)
(0.12)
(0.04)
(0.39)
(1.71)
(1)
5.23
(9.08)
(7.57)
(0.86)
(2.37)
(0.49)
(0.84)
(0.04)
(0.41)
(1.75)
(1)
5.34
7.3
0.63
0.08
0.79
0.42
0.43
0.04
0.37
1.74
1
3.9
-
9.41
1.55
0.58
0.14
0.64
0.72
0.04
0.38
1.73
1
3.9
-
10.48
5.45
0.3
0.37
1.96
1.91
0.04
0.39
1.74
1
3.9
-
100.0
-
5.23
5.34
8.6
10.5
14.2
Total
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
100.
July 2nd, 2012
72 / 41
73. Signal Control Region Plots (after scaling)
eνjj
Ω
µνjj
Events
Events
300
350
Data
W+jets
Top
300
Data
W+jets
Top
250
Z+jets
250
Z+jets
200
QCD
Diboson
200
QCD
Diboson
150
150
100
100
50
significance
significance
50
2
0
-2
2
0
-2
50
100
150
200
250
300
50
100
150
200
103
Data
W+jets
Top
102
250
Z+jets
103
Data
W+jets
Top
102
Z+jets
QCD
Diboson
QCD
Diboson
10
10
1
1
-1
-1
10
significance
10
significance
300
Dijet Mass [GeV]
Events
Events
Dijet Mass [GeV]
2
0
-2
2
0
-2
500
1000
1500
E. Williams (Columbia U.)
2000
2500
M(lν jj) [GeV]
500
G∗ → W W → νjj thesis defense
1000
1500
2000
2500
M(lν jj) [GeV]
July 2nd, 2012
73 / 41
74. νjj Signal Control Region Plots
Events
µνjj
Events
eνjj
Data
W+jets
Top
103
Z+jets
102
Data
W+jets
Top
103
Z+jets
102
QCD
Diboson
QCD
Diboson
10
10
significance
1
10-1
significance
1
10-1
2
0
-2
0
2
0
-2
100
200
300
400
500
600
700
800
900
1000
0
100
200
300
400
500
600
700
800
p (j,j) [GeV]
Data
W+jets
Top
103
Z+jets
102
Z+jets
102
QCD
Diboson
1000
T
Events
Events
Data
W+jets
Top
103
900
p (j,j) [GeV]
T
QCD
Diboson
10
10
significance
1
10-1
significance
1
10-1
2
0
-2
0
2
0
-2
100
200
300
400
500
600
700
800
900
1000
p (lep,Emiss)
T
0
100
200
300
400
500
600
700
800
900
1000
p (lep,Emiss)
T
T
T
* MC uncertainty (Lumi and W/Z+jets scale factor systematic) not included in significance
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
74 / 41
75. νjj Signal Control Region Plots
µνjj
Events
Events
eνjj
103
Data
W+jets
Top
3
10
102
Data
W+jets
Top
2
10
Z+jets
Z+jets
QCD
Diboson
QCD
Diboson
10
10
1
1
-1
-1
10
significance
significance
10
2
0
-2
2
0
-2
0
100
200
300
400
500
600
700
0
100
200
300
400
500
600
Data 2011
W+jets
Top
103
Z+jets
102
Data 2011
W+jets
Top
103
Z+jets
102
QCD
Diboson
QCD
Diboson
10
10
1
1
-1
-1
10
significance
10
significance
700
Emiss [GeV]
t
Events
Events
Emiss [GeV]
t
2
0
-2
2
0
-2
200
300
400
500
600
700
800
900
1000
200
300
400
MET + Lepton Pt [GeV]
500
600
700
800
900
1000
MET + Lepton Pt [GeV]
* MC uncertainty (Lumi and W/Z+jets scale factor systematic) not included in significance
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
75 / 41
76. νjj Signal Control Region Plots
µνjj
Events
Events
eνjj
103
Data 2011
W+jets
Top
2
10
103
Z+jets
QCD
Diboson
Z+jets
QCD
Diboson
10
10
1
10-1
significance
1
10-1
significance
Data 2011
W+jets
Top
102
2
0
-2
2
0
-2
200
400
600
800
1000
1200
200
400
600
800
Data
W+jets
Top
103
Data
W+jets
Top
102
Z+jets
QCD
Diboson
QCD
Diboson
10
10
1
1
-1
-1
10
significance
10
significance
1200
103
Z+jets
102
1000
Dijet Mass [GeV]
Events
Events
Dijet Mass [GeV]
2
0
-2
0
2
0
-2
100
200
300
400
500
600
700
800
0
100
200
300
Lepton Pt [GeV]
400
500
600
700
800
Lepton Pt [GeV]
* MC uncertainty (Lumi and W/Z+jets scale factor systematic) not included in significance
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
76 / 41
77. νjj signal templates
Fully simulated signal samples only available with masses:
M (G∗ ) = 500 − 1500 GeV, in 250 GeV steps
RS1
and
M (G∗ ) = 500 − 1500 GeV, in 100 GeV steps
Bulk
To account for possibility of missing a signal with an intermediate mass value, a
∗
set of G∗
RS1 and GBulk signal templates were made, spanning the full mass range
in steps of 50 GeV.
νjj mass from full-sim samples fit with Crystal Ball function:
2
N·
x
exp − (x−¯)
2σ 2
x
A · (B − x−¯ )−n
σ
2
n
where A = ( |a| )n · exp − |a| , and B =
2
E. Williams (Columbia U.)
n
|a|
for
for
x−¯
x
σ
x−¯
x
σ
> −a
≤ −a
− |a|
G∗ → W W → νjj thesis defense
July 2nd, 2012
77 / 41
79. νjj signal template parameter extraction
To create ‘in-between’ mass template points, the crystal ball fit
parameters, as well as the signal acceptances are interpolated through a fit
across the signal mass range.
The mean x, width σ and a parameters extracted and their trend are fitted
¯
with simple functions:
x(x) = p0 + p1 x
¯
(1)
σ(x) = p0 + p1 x
p0
+ p2 x
a(x) =
p1 x2
n=2
(2)
(3)
(4)
Parameter n fixed to 2, shape of the tail can be appropriately controlled
solely by the a parameter.
Acceptance extrapolated through a Landau distribution which empirically
fits the curve.
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
79 / 41
80. Crystal Ball Sigma
Crystal Ball Mean
νjj signal template parameter fits
1400
1200
1000
110
100
90
80
70
800
60
50
600
40
400
600
800
1000
1200
1400
1600
400
600
800
1000
3
2.5
1200
1400
1600
G* Pole Mass [GeV]
Crystal Ball n
Crystal Ball a
G* Pole Mass [GeV]
3
2.8
2.6
2
2.4
1.5
2.2
1
2
400
600
800
1000
1200
1400
1600
400
600
G* Pole Mass [GeV]
800
1000
1200
1400
1600
G* Pole Mass [GeV]
Fits of crystal ball parameters across full-simulated G∗ → eνjj vs M (G∗ )
shown. From left to right and top to bottom are the obtained fits for the
x, σ, a, and n.
¯
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
80 / 41
81. Acceptance
νjj signal template acceptance fit
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
400
600
800
1000 1200 1400 1600
G* Pole Mass [GeV]
Landau functional fit (in black) to the acceptances in the eνjj channel
using to the full-simulated G∗ samples (in blue) with masses 500, 750,
1000, and 1500 GeV . Acceptances of template signal distributions were
extrapolated from fit.
E. Williams (Columbia U.)
G∗ → W W → νjj thesis defense
July 2nd, 2012
81 / 41
82. νjj signal template cross-sections
Table: Summary of cross-sections times branching ratio and acceptances per
channel used to derive cross section limits at intermediate MG∗ mass values,
where fully simulated samples were non available.
500
550
600
650
700
750
800
850
900
950
1000
1050
1100
1150
1200
1250
1300
1350
1400
1450
1500
E. Williams (Columbia U.)
σ×B
[pb]
eνjj
5.593
4.597
3.601
2.643
1.648
0.614
0.514
0.413
0.313
0.212
0.027
0.095
0.078
0.061
0.044
0.027
0.023
0.019
0.015
0.012
0.008
G∗ Mass
[GeV]
0.045
0.065
0.081
0.089
0.091
0.089
0.082
0.075
0.067
0.060
0.051
0.047
0.041
0.036
0.032
0.030
0.026
0.023
0.021
0.018
0.018
Acceptance
µνjj
Average
0.034
0.048
0.058
0.065
0.067
0.068
0.064
0.059
0.054
0.049
0.041
0.040
0.036
0.032
0.029
0.027
0.023
0.021
0.019
0.017
0.018
0.040
0.057
0.070
0.077
0.079
0.079
0.073
0.067
0.061
0.055
0.046
0.044
0.039
0.034
0.031
0.029
0.025
0.022
0.020
0.018
0.018
G∗ → W W → νjj thesis defense
July 2nd, 2012
82 / 41
