search for excited randall-sundrum gravitons from warped extra dimensions with semi-leptonic diboson...
DESCRIPTION
PhD defense presentationTRANSCRIPT
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Search for Excited Randall-Sundrum Gravitons fromWarped Extra Dimensions with Semi-Leptonic
Diboson Final States using the ATLAS detector atthe LHC
Eric Williams
Columbia University
July 2nd, 2012
Thesis Defense
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Talk Overview
The Large Hadron Collider
The ATLAS detector
Why extra dimensions?
The analysis
Sources of systematic uncertainties
Final results and conclusions
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The Large Hadron Collider
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The Large Hadron Collider (LHC)
27 km circumference, 100 meters underground
Collides counter-rotating proton beams at center-of-massenergy = 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-bE. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 4 / 41
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The ATLAS Detector
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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.
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The ATLAS Detector
ATLAS is composed of components, each optimized for particular functions
Inner Detector: measures the momentum andtrajectories charged particles
Electromagnetic Calorimeters: measures theenergies of electrons, photons, and others
Hadronic Calorimeters: measures the energiesof the hadronic particles (‘jets’, protons,neutrons)
Muon System: measures the momenta ofmuons in the event
The combination of these systems allow formeasurments of ‘missing transverse energy’;the signature of particles not detected, such asneutrinos
The goal of particle detection is to reconstruct the kinematics of each collision(particle energies, directions, charges and masses), to determine whethersomething “interesting” happened during that event
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Why extra dimensions?Original Randall-Sundrum (RS1) model
Modern ‘Bulk’ Randall-Sundrum (Bulk RS) model
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Why extra dimensions? RS1 Model
Original Randall-Sundrum (RS1) model offers a solution to thehierarchy problem by postulating a 5th space-time bounded by two(3 + 1)-dimensional branes.
Gravity is localized aty = 0, called the UV-
or Planck-brane.
Only gravity canpropagate through
‘bulk’.
SM particles reststrictedto y = πR (IR- or TeV-brane).
Physical masses rescaledby e−πkR: gravity is weak.
The resulting metric is nonfactorizable and depends on the radius yand curvature k−1 of the extra dimension:
ds2 = e−2kyηµνdxµdxν + dy2; 0 ≤ y ≤ πR
Therefore the RS warped geometry model proposes a solution to the‘hierarchy problem’ with reasonable values of kR ∼ 11Massive excited graviton modes (G∗) are a defining feature
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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) determineparticles masses
Suppressed coupling to bosons and lightfermions; negligible rates to γγ and ``
Enhanced coupling to heavy particles(tt,ZZ and WW )← motivates search in WWchannel!
G*! WW G*! ZZ G*! HH G*! gg G*! tT
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Analysis Outline
Analysis Strategy
Data/MC Samples
Object and Event Selection
QCD Multijet Estimation
Event Preselection
Signal (W+jets) Control Region
Signal Region
(*The Ω symbol in corner of following slides denotes my contributions)
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Analysis Outline
Analysis Strategy
Data/MC Samples
Object and Event Selection
QCD Multijet Estimation
Event Preselection
Signal (W+jets) Control Region
Signal Region
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Analysis Outline
Analysis Strategy
Data/MC Samples
Object and Event Selection
QCD Multijet Estimation
Event Preselection
Signal (W+jets) Control Region
Signal Region
→ This analysis (`νjj) part of a larger diboson resonance effort at ATLASwhich includes other decay channels: ````, ``jj, `ν`` and `ν`ν.
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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 leptonRequire large missing transverse energy (EmissT )
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 systemSet 95% confidence limits on a narrow M(`νjj) excess
Previous RS1 G∗ → V V mass exclusion limits
Experiment L [fb−1] ProcessMass
Exclusion
CMS 4.9 G∗RS1 → ZZ 1000 GeVATLAS 1.02 G∗RS1 → ZZ 845 GeV
D0 5.4 G∗RS1 →WW 754 GeV
*Currently no published limits on bulk RS graviton production!
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Analysis Outline
Analysis Strategy
Data/MC Samples
Object and Event Selection
QCD Multijet Estimation
Event Preselection
Signal (W+jets) Control Region
Signal Region
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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 andreconstruction efficiencies.
Background cross sections normalized to (N)NLO with scale factors (k-factors)
Full detector simulation, reconstructed with same software as data
Backgrounds Generator
W+jets Alpgen+Herwig/JimmyZ+jets Alpgen+Herwig/JimmyTop (tt and st) MC@NLO+Herwig/JimmyWW/WZ/ZZ Herwig+Jimmy
Signals (M = 500 -1500) Generator
G∗RS1 → `νjj PythiaG∗Bulk → `νjj CalcHEP+Atlfast II
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Analysis Outline
Analysis Strategy
Data/MC Samples
Object and Event Selection
QCD Multijet Estimation
Event Preselection
Signal (W+jets) Control Region
Signal Region
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Object Selection: Electrons and Muons Ω
Electrons are selected based on shower shape requirements andcluster/track matching (tight++)
Muons are selected based on track quality and the combination oftracks from the muon system and inner detector (combined)
Both electrons and muons have requirements on:
longitudinal and transverse impact parameterstransverse energy isolationtransverse momentum
eνjj µνjj
Electron Pt [GeV]0 50 100 150 200 250 300 350 400 450 500
(dat
a-M
C)/
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-0.5
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Eve
nts
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410 DataW+jets
Top
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ATLAS Internal
jjν e→X
= 7 TeVs-1 Ldt = 4.701 fb∫
Muon Pt [GeV]0 50 100 150 200 250 300 350 400 450 500
(dat
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ATLAS Internal
jjνµ →X
= 7 TeVs-1 Ldt = 4.701 fb∫
*Plots shown after pre-selection and QCD estimation (details later)
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Object Selection: Jets and EmissT Ω
Jets:Reconstructed using the anti-ktalgorithm with cone size 0.4
Calibrated to the hadronic scale
Required to be central with hightransverse momentum
Energy fraction associated with leading primary vertex (JVF) used toreject pile-up jets
EmissT :
The missing transverse energy (EmissT ) is defined as the negativevector sum of transverse momenta of all the objects in the event
EmissT is reconstructed using the MET RefFinal algorithm
Calorimeter cells used are calibrated individually corresponding to thephysics object to which they are associated1
1My ATLAS ‘service’ work involved the study of the calibration of low-pT objects in the Emiss
T calculation
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Analysis Outline
Analysis Strategy
Data/MC Samples
Object and Event Selection
QCD Multijet Estimation
Event Preselection
Signal (W+jets) Control Region
Signal Region
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QCD Multijet Estimation Ω
QCD template method
QCD templates from data
‘Anti-Electrons’: reverse only isolationrequirement‘Anti-Muons’: reverse only transverseimpact parameter significance→ ‘non-pointing’
Subtract W+jets contamination from QCDtemplates
Fit QCD template to data usingMT (`, EmissT ) distribution
Let W/Z+jets normalization float
Before scaling
) [GeV]miss
T(lep,ETM
0 50 100 150 200 250 300 350 400 450 500
(dat
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410 DataW+jets
Top
QCDZ+jets
Diboson
ATLAS Internal
jjνµ →X
= 7 TeVs-1 Ldt = 4.701 fb∫
After scaling
) [GeV]miss
T(lep,ETM
0 50 100 150 200 250 300 350 400 450 500
(dat
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Top
Z+jets
QCD
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ATLAS Internal
jjνµ →X
= 7 TeVs-1 Ldt = 4.701 fb∫
Scale Factors eνjj µνjj
QCD 0.30 ± 0.05 0.22 ± 0.05W/Z+jets 1.10 ± 0.01 1.09 ± 0.01
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Analysis Outline
Analysis Strategy
Data/MC Samples
Object and Event Selection
QCD Multijet Estimation
Event Preselection
Signal (W+jets) Control Region
Signal Region
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Preselection Yields Ω
Event preselection criteria:
One lepton (e/µ) with pT > 30 GeV
At least two jets with pT > 40 GeV,lead jet pT > 100 GeV
EmissT > 40 GeV
Preselected event yields (errors stat. only)
Process eνjj µνjj
W+jets 37994± 152 45712± 170Z+jets 1270± 16 1802± 17Top 15124± 30 16309± 31Diboson 474± 4 490± 4QCD 929± 36 499± 16Total Bkgd 55792± 160 64812± 174Data 55163 64233G∗Bulk (800 GeV) 55.0± 1.0 44.5± 0.9G∗Bulk (1000 GeV) 8.0± 0.2 6.5± 0.2G∗Bulk (1200 GeV) 1.9± 0.1 1.4± 0.1G∗RS1 (750 GeV) 388.4± 5.8 313.8± 5.1G∗RS1 (1000 GeV) 64.2± 1.0 51.3± 0.9G∗RS1 (1250 GeV) 15.3± 0.3 12.7± 0.2
eνjj
Avg Int per Xing2 4 6 8 10 12 14 16 18 20
(dat
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C)/
MC
-0.5
0
0.5
Eve
nts
1000
2000
3000
4000
5000
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7000
8000DataW+jets
Top
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Diboson
ATLAS Internal
jjν e→X
= 7 TeVs-1 Ldt = 4.701 fb∫
µνjj
Avg Int per Xing2 4 6 8 10 12 14 16 18 20
(dat
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MC
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2000
3000
4000
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Top
Z+jets
QCD
Diboson
ATLAS Internal
jjνµ →X
= 7 TeVs-1 Ldt = 4.701 fb∫
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Data/MC preselection plots Ω
eνjj µνjj
) [GeV]miss
T(lep,E
Tp
0 100 200 300 400 500 600 700
(dat
a-M
C)/
MC
-0.5
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nts
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1
10
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410 DataW+jetsTopZ+jetsQCDDiboson
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
ATLAS Internal
jjν e→X
= 7 TeVs-1 Ldt = 4.701 fb∫
) [GeV]miss
T(lep,E
Tp
0 100 200 300 400 500 600 700
(dat
a-M
C)/
MC
-0.5
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(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
ATLAS Internal
jjνµ →X
= 7 TeVs-1 Ldt = 4.701 fb∫
(j,j) [GeV]T
p0 100 200 300 400 500 600 700
(dat
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(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
ATLAS Internal
jjν e→X
= 7 TeVs-1 Ldt = 4.701 fb∫
(j,j) [GeV]T
p0 100 200 300 400 500 600 700
(dat
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(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
ATLAS Internal
jjνµ →X
= 7 TeVs-1 Ldt = 4.701 fb∫
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Analysis Outline
Analysis Strategy
Data/MC Samples
Object and Event Selection
QCD Multijet Estimation
Event Preselection
Signal (W+jets) Control Region
Signal Region
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Signal (W+jets) Control Region Ω
W+jets control region definition:
Preselection Criteria
pT (`,EmissT ) > 200 GeV
pT (jj) > 200 GeV
M(jj) < 65 or M(jj) > 115 GeV
Process eνjj µνjj
W+jets 4004± 44 3572± 43Z+jets 123± 5 132± 5Top 1135± 8 951± 8Diboson 40± 1 37± 1QCD 74± 15 69± 5Total Bkgd 5376± 48 4760± 44Data 5404± 0.0 4743± 0.0
Signal control region yields (errors stat. only)
eνjj µνjj
M(jj) [GeV]
50 100 150 200 250 3000
50
100
150
200
250
300
350
400
450data
MC backgrounds
G* (750 GeV)
M(jj) [GeV]
50 100 150 200 250 3000
50
100
150
200
250
300
350 data
MC backgrounds
G* (750 GeV)
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Signal Control Region Sidebands Ω
Use the M(jj) sidebands to scale W/Z+jets background to data.
M(jj) < 65 GeV
jj) [GeV]νM(l0 500 1000 1500 2000 2500
signif
icanc
e
-2
0
2
Even
ts
-110
1
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210
Data 2011W+jetsTopZ+jetsDibosonQCD
jj) [GeV]νM(l500 1000 1500 2000 2500
sign
ifica
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ts
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1
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310Data 2011W+jetsTopZ+jetsQCDDiboson
jj) [GeV]νM(l500 1000 1500 2000 2500
sign
ifica
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-2
0
2
Even
ts
-110
1
10
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310Data 2011W+jetsTopZ+jetsQCDDiboson
W/Z+jets SF 1.11 ± 0.02
M(jj) > 115 GeV
jj) [GeV]νM(l500 1000 1500 2000 2500
sign
ifica
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0
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310Data 2011W+jets
Top
Z+jets
QCD
Diboson
W/Z+jets SF 1.02 ± 0.01
Average W/Z+jets SF 1.02 ± 0.03
W/Z+jets MC is scaled by average SF in signal (control) region.
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Analysis Outline
Analysis Strategy
Data/MC Samples
Object and Event Selection
QCD Multijet Estimation
Event Preselection
Signal (W+jets) Control Region
Signal Region
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Signal Region Ω
Signal region definition:
Preselection criteria
pT (`,EmissT ) > 200 GeV
pT (jj) > 200 GeV
65 <M(jj) < 115 GeV
Process eνjj µνjj
W+jets 698± 20 594± 21Z+jets 14± 2 15± 2Top 614± 6 516± 5Diboson 76± 2 63± 1QCD 18± 6 16± 2Total Bkgd 1420± 22 1204± 22Data 1453 1328GBulk (800 GeV) 44.0± 0.9 34.9± 0.8GBulk (1000 GeV) 4.0± 0.1 3.6± 0.1GBulk (1200 GeV) 0.5± 0.0 0.4± 0.0GRS1 (750 GeV) 208.2± 4.3 162.8± 3.7GRS1 (1000 GeV) 21.8± 0.6 18.3± 0.5GRS1 (1250 GeV) 3.4± 0.1 3.1± 0.1
Signal region yields (errors stat. only)
eνjj
jj) [GeV]νM(l0 200 400 600 800 1000 1200 1400 1600 1800 2000
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
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DataW+jetsTopDibosonQCDZ+jets
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
µνjj
jj) [GeV]νM(l0 200 400 600 800 1000 1200 1400 1600 1800 2000
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
10
210
DataW+jetsTopDibosonQCDZ+jets
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
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Sources of Sytematic UncertaintiesW/Z+jets Scale Factor Uncertainty
Measurement Systematic Uncertainties
Theoretical Systematic Uncertianties
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W/Z+jets systematics Ω
To estimate, use low/high dijet mass sideband scale factors as afunction of M(`νjj) as ‘envelope’ of uncertainty.
Modulate applied W/Z+jets scale factor within this ‘envelope’ andmeasure change in M(`νjj) in signal region.
The largest systematic uncertainty is due to uncertainy of W/Z+jetsscale factor.
jj) (M(j,j) > 115GeV or M(j,j) < 65GeV)νM(l
200 400 600 800 1000 1200 1400 1600 1800 2000
V+
jets
Sca
le F
acto
r
0
0.2
0.4
0.6
0.8
1
1.2
1.4
AverageM(jj) < 65M(jj) > 115
Systematic from W/Z+jets scale factor
Sample eνjj µνjj
W+jets+14.45% +14.71%−2.06% −2.23%
Z+jets+14.57% +14.72%−2.08% −2.23%
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Systematic Uncertainties Ω
Systematics shown as Average (Min/Max)%
Source Backgrounds (%) Signal (%)
Signal PDFα - 5
Jet Energy Scaleα 10.1 (5.3/17.9) 4.8 (2.5/9.6)
Luminosityα 3.9 3.9Jet Energy Resolutionα 1.6 (0.3/2.9) 1.5 (0.3/3.0)Trigger SFα 1.1 (0.5/1.7) 1.2 (0.6/1.7)Emiss αT 1.1 (0.4/1.6) 0.1 (0.1/0.1)Lepton Energy Scaleα < 1 < 1Lepton Energy Resolutionα < 1 < 1Lepton Reco SFα < 1 < 1Lepton ID SFα < 1 < 1
W/Z+jets SFβ 9.0 (8.8/9.1) -QCDγ 90 (80/100) -
α: Applies to non-W/Z+jets backgrounds onlyβ: Applies to W/Z+jets backgrounds onlyγ: Applies to QCD background only
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Theoretical Systematics
Theoretical systematics from uncertainties on cross-section, partondistribution functions (PDFs), and initial/final state radiation (ISR/FSR).
Systematic WW WZ ZZ tt singletop
WW/WZ/ZZ (σ) 5% 7% 5% - -
tt (σ) - - - +7.0%−9.6% -
tt (shape) - - - 8% -
tb+ tqb+ tW (σ) - - - - 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%
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Final Results and ConclusionsSignal Yields with Systematics
Statistical Analysis
G∗ Exclusion Limits
Conclusions
Future Prospects
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Signal Region Yields with Systematics Ω
Process eνjj µνjj
W+jets 698± 64 594± 57Z+jets 14± 2 15± 2
Top 614+59−86 518+50
−73Diboson 76± 9 63± 8QCD 18± 24 16± 11
Total backgrounds 1420+91−110 1206+77
−94Data 1452 1318Bulk G∗ (800 GeV) 44.0± 3.4 34.9± 2.7Bulk G∗ (1000 GeV) 4.0± 0.3 3.6± 0.3Bulk G∗ (1200 GeV) 0.5± 0.1 0.4± 0.1RS1 G∗ (750 GeV) 208.2± 18.0 163± 12.8RS1 G∗ (1000 GeV) 21.8± 1.7 18.3± 1.5RS1 G∗ (1250 GeV) 3.4± 0.3 3.1± 0.3
Signal region event yields (errors stat. + syst.)
eνjj
jj) [GeV]νM(l0 200 400 600 800 1000 1200 1400 1600 1800 2000
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
10
210
DataW+jetsTopDibosonQCDZ+jets
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
µνjj
jj) [GeV]νM(l0 200 400 600 800 1000 1200 1400 1600 1800 2000
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
10
210
DataW+jetsTopDibosonQCDZ+jets
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
The greatest deviation from the background prediction occurs atM(eνjj) = 1000 GeV with p-value = 0.14.Lacking evidence for new physics, limits on the hypothetical signalrate are determined with the CLs method.
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Statistical Analysis
M(`νjj) distributions are used as inputs to a poisson NegativeLog-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) andsignal+background (H1) hypothesis
Relative location of NLLR(data) to NLLR(H0) and NLLR(H1) distributionsquantify exclusion or discovery!
Confidence levels (CL) defined as fractionsof 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 forbackground median, ±1, 2σ, and data. Then compared to signal σ ×BR.
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RS1 G∗ Observed Limits w/ Systematicseνjj+µνjj
[GeV]G*m
600 800 1000 1200 1400
B [pb]
× σ
110
1
10 WW)→
RS1 G*→(pp σ
Expected Limit
σ 1±Expected
σ 2±Expected
Observed limit
[GeV]G*m
600 800 1000 1200 1400
B [pb]
× σ
110
1
10
1 Ldt = 4.7 fb∫
ATLAS
Internal
Lower mass exclusion limits
Expected Observed
G∗RS1 952 GeV 936 GeV
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Bulk RS G∗ Observed Limits w/ Systematicseνjj+µνjj
[GeV]G*m
500 600 700 800 900 1000 1100 1200
B [pb]
× σ
210
110
1
10 WW)→
Bulk G*→(pp σ
Expected Limit
σ 1±Expected
σ 2±Expected
Observed limit
[GeV]G*m
500 600 700 800 900 1000 1100 1200
B [pb]
× σ
210
110
1
10
1 Ldt = 4.7 fb∫
ATLAS
Internal
Lower mass exclusion limits
Expected Observed
G∗Bulk 749 GeV 714 GeV
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G∗ → WW → `νjj Summary
Expected/Observed lower mass limits from RS1 and Bulk RSgravitons:
Signal eνjj eνjj µνjj µνjj Comb. Comb.w/o sys w/ sys w/o sys w/ sys w/o sys w/ sys
RS1 G∗ (exp.) 1017 966 982 907 1065 952Bulk RS G∗ (exp.) 814 728 795 693 838 749
RS1 G∗ (obs.) 928 915 982 934 973 936Bulk RS G∗ (obs.) 818 727 738 631 849 714
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 WW decay!
Current best limit on RS1 Graviton to WW (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)
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Future Prospects
The future of LHC collisions promises higher energies and luminosities(already collected > 5 fb−1 of 8 TeV data)!
What does this mean for diboson searches?
Increase in signal cross sections
Concurrent increase in backgroundproduction and pile-up!
Highly boosted decay products→ jet merging Mass [GeV]BulkG*
400 600 800 1000 1200 1400 1600
BR
[pb]
×σ
-310
-210
-110
17 TeV
8 TeV
W
W
W
W
W W
pT(W)~0 pT(W)~M(W) pT(W)≫M(W)
W
W
W
W
W W
pT(W)~0 pT(W)~M(W) pT(W)≫M(W)
W
W
W
W
W W
pT(W)~0 pT(W)~M(W) pT(W)≫M(W)
W
W
W
W
W W
pT(W)~0 pT(W)~M(W) pT(W)≫M(W)
W
W
W
W
W W
pT(W)~0 pT(W)~M(W) pT(W)≫M(W)
W
W
W
W
W W
pT(W)~0 pT(W)~M(W) pT(W)≫M(W)
W
W
W
W
W W
pT(W)~0 pT(W)~M(W) pT(W)≫M(W)
W
W
W
W
W W
pT(W)~0 pT(W)~M(W) pT(W)≫M(W)
W
W
W
W
W W
pT(W)~0 pT(W)~M(W) pT(W)≫M(W)
W
W
W
W
W W
pT(W)~0 pT(W)~M(W) pT(W)≫M(W)
W
W
W
W
W W
pT(W)~0 pT(W)~M(W) pT(W)≫M(W)
W
W
W
W
W W
pT(W)~0 pT(W)~M(W) pT(W)≫M(W)
Solution: Use merged jets to reduce backgrounds
Much to look forward to at the LHC in 2012 and beyond!
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Backups
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Object Definitions
Electrons
egammma author 1 or 31,2,1,2,1
|η| < 2.47 w/ crack region excluded1,2,1,2,1
good object quality (el OQ & 1446 == 0)1,2,1
pT > 30 GeV
tight++ electron1,2,1,2,1
|el trackz0pv| < 1 mm2,1,2
impact parameter significance wrt. primary vertex|el trackd0pv/
√el tracksigd0pv| < 102,1,2
IsolationCaloIsoCorrection::GetPtNPVCorrectedIsolation
etcone30 corrected < 6 GeV2
Jets and EmissT
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
Muons
STACO combined muons1,2,2,1
pT > 30 GeV
|η| < 2.41,2,1,2,1
nBLayerHits > 0 || !expectBLayerHit1,2,1,1
nPixHits + nPixelDeadSensors > 11,2,1,2,1
nSCTHits + nSCTDeadSensors ≥ 61,2,1,2,1
nPixHoles + nSCTHoles < 31,2,1,2,1
TRT extension1,2,1,1
N = nTRTOutliers + nTRTHits
if |η| < 1.9 then require:nTRTOutliers/N < 0.9 && N > 5if |η| > 1.9 && N > 5 then require:nTRTOutliers/N < 0.9
|z0 exPV| < 1 mm2,1,
impact parameter significance2,1,2
|d0 exPV/√cov d0 exPV| < 3
Isolation1,2
CorrectCaloIso::CorrectEtCone30Reletcone30 corrected/pT < 0.14ptcone30/pT < 0.15
SM Higgs SUSY1. W → `ν/Z → `` 1. W → `ν`ν 1. 1 lepton2. EWK (WW ,W/Zγ) 2. W → `νjj
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Data/MC samplesData samples used:
L = 4.701fb−1 from period D-M(OflLumi-7TeV-002)
SM W/Z GRL
NTUP SMWLNUJJ, p833 skims
Egamma and Muons streams
Monte-Carlo samples used:
NTUP SMWZ, r3043 r2993 p833 (mc11c)
Weights applied to MC events to account for pile-up, as well as trigger andreconstruciton efficiencies.
Background cross sections normalized to N(N)LO with k-factors
Backgrounds Generator Cross Sections [pb]
W+jets Alpgen+Herwig/Jimmy 14060Z+jets Alpgen+Herwig/Jimmy 1070WW/WZ/ZZ Herwig+Jimmy 44.9/18.5/5.96Top (tt and st) MC@NLO+Herwig/Jimmy 164, 83.93
Signals (M = 500 -1500) Generator
G∗RS1 → `νjj PythiaG∗bulk → `νjj CalcHEP+Atlfast IIW ′ → `νjj Pythia
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Data/MC samples: Alpgen W+jets reweighting
W+jets is the dominant background
It has been observed that ALPGEN W+jets samples over-estimate thebackground in high W pT regimes
However Sherpa W+jets MC backgrounds match the data betterthan the Alpgen samples in these regions
eνjj
-1L dt ~ 4.71 pb0i eAW
Sherpa
0 100 200 300 400 500 600 700 800 900 1000
Dat
a / M
C
00.20.40.60.8
11.21.41.61.8
2
Eve
nts
-210
-110
1
10
210
310
410
510
610
710
Truth Pt of W Boson 2 1 0
-1L dt ~ 4.71 pb0i eAW
AlpgenSherpa
Truth pT of W Boson [GeV] Generator-level pT of W Boson [GeV]
Even
ts
SH
ERPA
/ALP
GEN
107
105
103
101
10-1
2
1
0
µνjj
-1L dt ~ 4.71 pb0iµ AW
Sherpa
0 100 200 300 400 500 600 700 800 900 1000
Dat
a / M
C
00.20.40.60.8
11.21.41.61.8
2
Eve
nts
-210
-110
1
10
210
310
410
510
610
710
Truth Pt of W Boson 2 2 0
-1L dt ~ 4.71 pb0iµ AW
AlpgenSherpa
Truth pT of W Boson [GeV]
107
105
103
101
10-1
2
1
0
Even
ts
SH
ERPA
/ALP
GEN
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 withsufficient statistics, the solution:
→ reweight Alpgen W+jets to match Sherpa generator-level W pTE. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 44 / 41
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pT (`, EmissT ), ALPGEN→ SHERPA truth W pT reweighting
W/out Reweighting With Reweighting
eνjj
µνjj
Pt(lep+met)0 100 200 300 400 500 600 700
sign
ifica
nce
-0.5
0
0.5
Eve
nts
-110
1
10
210
310
410Data 2011W+jets
Top
Z+jets
Diboson
QCD
ATLAS Internal
jjν e→X
= 7 TeVs-1 Ldt = 4.701 fb∫
Pt(lep+met)0 100 200 300 400 500 600 700
sign
ifica
nce
-0.5
0
0.5
Eve
nts
-110
1
10
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310
410Data 2011W+jets
Top
Z+jets
QCD
Diboson
ATLAS Internal
jjν e→X
= 7 TeVs-1 Ldt = 4.701 fb∫
Pt(lep+met)0 100 200 300 400 500 600 700
sign
ifica
nce
-0.5
0
0.5
Eve
nts
-110
1
10
210
310
410Data 2011W+jets
Top
Z+jets
Diboson
QCD
ATLAS Internal
jjνµ →X
= 7 TeVs-1 Ldt = 4.701 fb∫
Pt(lep+met)0 100 200 300 400 500 600 700
sign
ifica
nce
-0.5
0
0.5E
vent
s
-110
1
10
210
310
410Data 2011W+jets
Top
Z+jets
Diboson
QCD
ATLAS Internal
jjνµ →X
= 7 TeVs-1 Ldt = 4.701 fb∫
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pdijetT , ALPGEN→ SHERPA truth W pT reweighting
W/out Reweighting With Reweighting
eνjj
µνjj
(j,j) [GeV]T
p0 100 200 300 400 500 600 700
sign
ifica
nce
-0.5
0
0.5
Eve
nts
-110
1
10
210
310
410Data 2011W+jets
Top
Z+jets
Diboson
QCD
ATLAS Internal
jjν e→X
= 7 TeVs-1 Ldt = 4.701 fb∫
(j,j) [GeV]T
p0 100 200 300 400 500 600 700
sign
ifica
nce
-0.5
0
0.5
Eve
nts
-110
1
10
210
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410Data 2011W+jets
Top
Z+jets
QCD
Diboson
ATLAS Internal
jjν e→X
= 7 TeVs-1 Ldt = 4.701 fb∫
(j,j) [GeV]T
p0 100 200 300 400 500 600 700
sign
ifica
nce
-0.5
0
0.5
Eve
nts
-110
1
10
210
310
410Data 2011W+jets
Top
Z+jets
Diboson
QCD
ATLAS Internal
jjνµ →X
= 7 TeVs-1 Ldt = 4.701 fb∫
(j,j) [GeV]T
p0 100 200 300 400 500 600 700
sign
ifica
nce
-0.5
0
0.5E
vent
s
-110
1
10
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410Data 2011W+jets
Top
Z+jets
Diboson
QCD
ATLAS Internal
jjνµ →X
= 7 TeVs-1 Ldt = 4.701 fb∫
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EmissT , ALPGEN→ SHERPA truth W pT reweighting
W/out Reweighting With Reweighting
eνjj
µνjj
MEt [GeV]0 100 200 300 400 500 600
sign
ifica
nce
-0.5
0
0.5
Eve
nts
-110
1
10
210
310
410 Data 2011W+jets
Top
Z+jets
Diboson
QCD
ATLAS Internal
jjν e→X
= 7 TeVs-1 Ldt = 4.701 fb∫
MEt [GeV]0 100 200 300 400 500 600
sign
ifica
nce
-0.5
0
0.5
Eve
nts
-110
1
10
210
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410 Data 2011W+jets
Top
Z+jets
QCD
Diboson
ATLAS Internal
jjν e→X
= 7 TeVs-1 Ldt = 4.701 fb∫
MEt [GeV]0 100 200 300 400 500 600
sign
ifica
nce
-0.5
0
0.5
Eve
nts
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1
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410Data 2011W+jets
Top
Z+jets
Diboson
QCD
ATLAS Internal
jjνµ →X
= 7 TeVs-1 Ldt = 4.701 fb∫
MEt [GeV]0 100 200 300 400 500 600
sign
ifica
nce
-0.5
0
0.5E
vent
s
-110
1
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410Data 2011W+jets
Top
Z+jets
Diboson
QCD
ATLAS Internal
jjνµ →X
= 7 TeVs-1 Ldt = 4.701 fb∫
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pleptonT , ALPGEN→ SHERPA truth W pT reweighting
W/out Reweighting With Reweighting
eνjj
µνjj
Lepton Pt [GeV]0 50 100 150 200 250 300 350 400 450 500
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MT (`, EmissT ), ALPGEN→ SHERPA truth W pT reweighting
W/out Reweighting With Reweighting
eνjj
µνjj
) [GeV]miss
T(lep,ETM
0 50 100 150 200 250 300 350 400 450 500
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= 7 TeVs-1 Ldt = 4.701 fb∫
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N jets, ALPGEN→ SHERPA truth W pT reweighting
W/out Reweighting With Reweighting
eνjj
µνjj
Jet N2 4 6 8 10 12
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Jet N2 4 6 8 10 12
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Jet N2 4 6 8 10 12
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Jet N2 4 6 8 10 12
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plead jetT , ALPGEN→ SHERPA truth W pT reweighting
W/out Reweighting With Reweighting
eνjj
µνjj
Lead Jet Pt [GeV]0 100 200 300 400 500 600 700
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Lead Jet Pt [GeV]0 100 200 300 400 500 600 700
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psecond jetT , ALPGEN→ SHERPA truth W pT reweighting
W/out Reweighting With Reweighting
eνjj
µνjj
Second Jet Pt [GeV]0 100 200 300 400 500 600 700
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tt Control Region Definition and Yields
tt control region is used to check tt agreement in high-pT region.
tt control region definition:
≥ 2 b-tagged jets w/ pT > 40 GeV
pT (jj) > 200 GeV
M(jj) < 65 GeV or M(jj) > 115 GeV
Process eνjj µνjj
tt 295± 17 279± 16Non− tt 23± 4 19± 4Data 301± 17 301± 17
RS1 G∗ (M = 1 TeV) 0± 0 0± 0
tt control region yields (errors stat. only)
) [GeV]T
miss(ETP
0 50 100 150 200 250 300
sig
nific
an
ce
3
1.5
0
1.5
30 50 100 150 200 250 300
10
20
30
40
50
60Data
)+Xtt(+HF+Xν l→W+Xν l→W
+X
l+l→*
γZ/γVV+V
Multijet WW (M=1 TeV)→G* WZ (M=1 TeV)→W’
1 Ldt = 4701.39 pb∫
) [GeV]T
miss(l , ETM
0 50 100 150 200 250
sig
nific
an
ce
3
1.5
0
1.5
30 50 100 150 200 250
10
20
30
40
50
60
70
80Data
)+Xtt(+HF+Xν l→W+Xν l→W
+X
l+l→*
γZ/γVV+V
Multijet WW (M=1 TeV)→G* WZ (M=1 TeV)→W’
1 Ldt = 4701.39 pb∫
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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
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W+jets QCD contamination
Goal is to estimate, and correct for, the amount of W+jets events in QCDtemplate. This method assumes that e→ jet ∼ jet→ e.
i) Create W+jets ‘contamination’ samples by running over W+jets MCwith 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 andlumi to get estimated distribution of W+jets events in QCD template
iii) Subtract W+jets contamination template from un-scaled QCDtemplate
iv) Scale new QCD template from fit to data
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W+jets QCD contamination
QCD ∼ 18% W+jets in eνjj QCD ∼ 7% W+jets in µνjj
) [GeV]miss
T(e,ETM
0 50 100 150 200 250 300 350 400 450 500
1
10
210
310Unscaled QCD
W+jets contamination
) [GeV]miss
T,Eµ(TM
0 50 100 150 200 250 300 350 400 450 500
1
10
210
310Unscaled QCD
W+jets contamination
) [GeV]miss
T(e,ETM
0 50 100 150 200 250 300 350 400 450 500
1
10
210
310QCD w/out W+jets sub
QCD w/ W+jets sub
) [GeV]miss
T,Eµ(TM
0 50 100 150 200 250 300 350 400 450 500-110
1
10
210 QCD w/out W+jets sub
QCD w/ W+jets sub
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W+jets QCD contamination
With outW+jetssubtraction
With W+jetssubtraction
eνjj µνjj
) [GeV]miss
T(lep,ETM
0 50 100 150 200 250 300 350 400 450 500
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`νjj QCD Estimationeνjj µνjj
W/out
QCD
scaling
) [GeV]miss
T(lep,ETM
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With
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Scale Factors eνjj µνjj
QCD 0.30 ± 0.05 0.22 ± 0.05V+jets 1.10 ± 0.01 1.09 ± 0.01
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`νjj QCD Estimation
QCD distributions before and after scaling.
eνjj µνjj
mT(e,MET) [GeV]
0 50 100 150 200 250 300 350 400 450 500
1
10
210
No QCD scaling
After QCD scaling
mT(mu,MET) [GeV]
0 50 100 150 200 250 300 350 400 450 500
1
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No QCD scaling
After QCD scaling
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Preselection Definition
Reject event if:dR(`, jet) < 0.4Contains 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 eventscorresponding to affeted data lumi (∼ 17%)
Has noise burst with LArError = 2Fails QCD triangle cut
Require:Lepton trigger:
Data Run Electron MuonPeriod Range Trigger Trigger
D-J 179710→ 186755 EF e20 medium EF mu18 MG or EF mu40 MSonly barrelK 186873→ 187815 EF e22 medium EF mu18 MG medium or EF mu40 MSonly barrelL-M 188902→ 191933 EF e22vh medium1 EF mu18 MG medium or
EF mu40 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
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Signal Significance
The ultimate goal of an experimental search for a new particle is to state whether or nota statistically significant observation of the signal has been made. In other words, toanswer 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 theseparation of the signal+backgroundhypothesis (H1) and the background-onlyhypothesis (H0)
2 Run an appropriate number ofpseudo-experiments (Frequentist) for bothhypothesis, incorporating all signal andbackground nuisance parameters (systematics)in a coherent way (Bayesian).
3 Define confidence levels designating exclusionsor discoveries 2012 Higgs → γγ 4.7fb−1 result
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1) Define test-statistic: Likelihood-Ratio
Neyman-Pearson lemma suggests that the most powerful test forstatistically separating two point hypotheses is the likelihood-ratiotest, that is:
Λ =L(s+ b|x)
L(b|x)
s = signalb = backgroundx = dataL = likelihood
Rate of signal or background events follow a Poisson distribution,appropriate choice for likelihood functional form:
L(s+ b) =(s+ b)xe−(s+b)
x!, L(b) =
(b)xe−b
x!
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1) Define test-statistic: Likelihood-Ratio
With this choice, combining likelihoods from multiple channels (e.g. X → Y andX → Z) as well as from multiple bins within a discriminating variable (e.g.M(X)) is natural:
Λ(x) =
channels∏i
bins∏j
(sij + bij)xij e−(sij+bij)
xij !/
(bij)xij e−(bij)
xij !.
In the high-statistics limit the distributions of -2 ln Λ are expected to converge to(χ2s+b − χ2
b), thus it is more common to use:
NLLR(x) = −2 ln(Λ(x))
= −2
channels∑i
bins∑j
[sij − xij ln
(1 +
sijbij
)]
This test statistic decreases monotonically for increasingly signal-like (decreasinglybackground-like) experiments. Can be used to order data outcomes relative toeach other in hypothesis significance
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2) Pseudo-Experiments: A Semi-Frequentist Approach
Assuming that the data is drawn randomly from a Poisson parent distribution, wecan create pdfs of NLLR(x) for both the signal+background hypothesis (H1) andthe background-only (H0) hypothesis, by conducting pseudo-experiments
Systematic uncertainties (nuisance parameters) are incorporated by sampling abifurcated Gaussian distribution with the ±σ uncertainties estimated for eachsource (hence ‘Semi’-Frequentist)
The pseudo-experiment background (Bmj ) and signal (Smj ) yields are then given as:
Bmj = B0,mj (1 +
Nbkgdsys∑i
gbkgdi )
Smk = S0,mk (1 +
Nsigsys∑i
gsigi )
Where B0,m (S0,m) is the nominal background (signal) poisson yield for channel j (k)and bin m. gbkgd (gsig) is the contribution from systematic uncertainty i.
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2) Pseudo-Experiments: A Semi-Frequentist Approach
Running O(20k) pseudo-experiments, we evaulate the NLLR distributions underthe H0, NLLR(x = Db), and H1, NLLR(x = Ds+b), hypotheses. Where:
Db =
Nbins∑m
Nb∑j
Bmj , Ds+b =
Nbins∑m
(
Nb∑j
Bmj +
Ns∑k
Smk )
N
-2ln(Λ(x))
Bkgd Only
Sig + Bkgd
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2) Pseudo-Experiments: A Semi-Frequentist Approach
Running O(20k) pseudo-experiments, we evaulate the NLLR distributions underthe H0, NLLR(x = Db), and H1, NLLR(x = Ds+b), hypotheses. Where:
Db =
Nbins∑m
Nb∑j
Bmj , Ds+b =
Nbins∑m
(
Nb∑j
Bmj +
Ns∑k
Smk )
N
-2ln(Λ(x))
Bkgd Only
Sig + Bkgd
NLLR(xdata)
Location of measured data on NLLR pdf (Prior Predictive Ensemble) used toquantify exclusion/discovery
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3) Modified Frequentist Confidence Levels: CLs
Confidence levels defined as the fraction of outcomes predicted to falloutside of the specified confidence interval
CLs+b: fraction of H1 pseudo-experiments less signal-like than data
CLs+b = Ps+b(X ≥ Xobs) =
∫ ∞NLLR(x=Dobs)
P(x = Ds+b) dP
CLb: fraction of H0 pseudo-experiments less signal-like than data
CLb = Pb(X ≥ Xobs) =
∫ ∞NLLR(x=Dobs)
P(x = Db) dP
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 backgroundfluctuated to produce observed signal. Typically require (1-CLb) < 5σ(4.3× 10−7) toclaim discovery
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3) Modified Frequentist Confidence Levels: CLs
N
-2ln(Λ(x))
Bkgd Only
Sig + Bkgd
NLLR(xdata)
1-CLb
CLs+b
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 backgroundfluctuated to produce observed signal. Typically require (1-CLb) < 5σ(4.3× 10−7) toclaim discovery
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3) Modified Frequentist Confidence Levels: CLs
The strictly frequentist CLs+b confidence level, while a powerfulstatistical tool, is unstable if the background model dramaticallydisagrees 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 backgroundmodelling and leads to more conservative limits on H1 hypothesis, aswell as lower false exclusion rate (type II error) than nominal (1− CL)
A signal model is then excluded at or above95% confidence level if CLs ≤ 0.05
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`νjj Signal Systematics
Acceptance systematics for ‘bulk’ Randal-Sundram GRS(M = 700 GeV) sample.
Systematic eνjj [%] µνjj [%]JES 2.83 2.63JER 0.90 0.99LES 0.06 0.07LER 0.06 0.08All Clusters 0.10 0.06Met PileUp 0.03 0.07ID SF 0.85 0.04Reco SF 0.91 0.39Trigger SF 0.55 1.74Iso SF 2.00 1.00Signal PDF 5.00 5.00Luminosity 3.90 3.90V+jets 0.00 0.00
Total 7.40 7.23
Muon energy resolution chosen as ’worst’ smearing between ID and MS.
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`νjj Background Systematics
Table: eνjj percent ∆ acceptance.
Systematic Wjets Zjets TTBar Single Diboson QCDTop
JES (10.99) (18.04) 4.78 8.37 10.33 -JER (1.14) (6.96) 0.06 1.39 3.13 -LES (0.1) (0.8) 0.18 0.08 0.05 -LER (0.42) (1.59) 0.14 0.07 0.08 -All Clusters (0.51) (1.56) 0.91 1.25 1.69 -Met PileUp (0.45) (2.13) 0.78 0.85 1.72 -ID SF (0.96) (0.92) 0.89 0.88 0.89 -Reco SF (0.81) (0.83) 0.88 0.88 0.8 -Trigger SF (0.56) (0.53) 0.56 0.56 0.59 -Iso SF (2) (2) 2 2 2 -Luminosity - - 3.9 3.9 3.9 -MJ Normalization - - - - - 80.0V+jets 5 5.11 - - - -
Total 5 5.11 6.74 9.76 12.28 80.0
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`νjj Background Systematics
Table: µνjj percent ∆ acceptance.
Systematic Wjets Zjets TTBar Single Diboson QCDTop
JES (10.75) (9.08) 7.3 9.41 10.48 -JER (0.27) (7.57) 0.63 1.55 5.45 -LES (0.4) (0.86) 0.08 0.58 0.3 -LER (1.21) (2.37) 0.79 0.14 0.37 -All Clusters (0.29) (0.49) 0.42 0.64 1.96 -Met PileUp (0.12) (0.84) 0.43 0.72 1.91 -ID SF (0.04) (0.04) 0.04 0.04 0.04 -Reco SF (0.39) (0.41) 0.37 0.38 0.39 -Trigger SF (1.71) (1.75) 1.74 1.73 1.74 -Iso SF (1) (1) 1 1 1 -Luminosity - - 3.9 3.9 3.9 -MJ Normalization - - - - - 100.0V+jets 5.23 5.34 - - - -
Total 5.23 5.34 8.6 10.5 14.2 100.
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Signal Control Region Plots (after scaling) Ω
eνjj µνjj
Dijet Mass [GeV]50 100 150 200 250 300
sign
ifica
nce
-2
0
2
Eve
nts
50
100
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350 DataW+jets
Top
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Diboson
Dijet Mass [GeV]50 100 150 200 250 300
sign
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50
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jj) [GeV]νM(l500 1000 1500 2000 2500
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310DataW+jets
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`νjj Signal Control Region Plots
eνjj µνjj
(j,j) [GeV]T
p0 100 200 300 400 500 600 700 800 900 1000
sign
ifica
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-2
0
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(j,j) [GeV]T
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* MC uncertainty (Lumi and W/Z+jets scale factor systematic) not included in significance
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`νjj Signal Control Region Plots
eνjj µνjj
[GeV]misstE
0 100 200 300 400 500 600 700
sign
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-2
0
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nts
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Data 2011W+jets
Top
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MET + Lepton Pt [GeV]200 300 400 500 600 700 800 900 1000
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* MC uncertainty (Lumi and W/Z+jets scale factor systematic) not included in significance
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`νjj Signal Control Region Plots
eνjj µνjj
Dijet Mass [GeV]200 400 600 800 1000 1200
sign
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-2
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* MC uncertainty (Lumi and W/Z+jets scale factor systematic) not included in significance
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`νjj signal templates
Fully simulated signal samples only available with masses:
M(G∗RS1) = 500− 1500 GeV, in 250 GeV steps
andM(G∗Bulk) = 500− 1500 GeV, in 100 GeV steps
To account for possibility of missing a signal with an intermediate mass value, aset of G∗RS1 and G∗Bulk signal templates were made, spanning the full mass rangein steps of 50 GeV.
`νjj mass from full-sim samples fit with Crystal Ball function:
N ·
exp− (x−x)2
2σ2 for x−xσ > −a
A · (B − x−xσ )−n for x−x
σ ≤ −a
where A = ( n|a| )n · exp− |a|
2
2 , and B = n|a| − |a|
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`νjj signal template fits
Mass(lvjj) (GeV)
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nts
/ ( 2
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Crystal Ball
Full-simulated G∗ samples (eνjj) with crystal ball functional fit for masses 500 GeV
(upper-left), 750 GeV (upper-right), 1000 GeV (middle-left), 1250 GeV (middle-right) and
1500 GeV (bottom row).E. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 78 / 41
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`νjj signal template parameter extraction
To create ‘in-between’ mass template points, the crystal ball fitparameters, as well as the signal acceptances are interpolated through a fitacross the signal mass range.The mean x, width σ and a parameters extracted and their trend are fittedwith simple functions:
x(x) = p0 + p1x (1)
σ(x) = p0 + p1x (2)
a(x) =p0
p1x2+ p2x (3)
n = 2 (4)
Parameter n fixed to 2, shape of the tail can be appropriately controlledsolely by the a parameter.Acceptance extrapolated through a Landau distribution which empiricallyfits the curve.
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`νjj signal template parameter fits
G* Pole Mass [GeV]
400 600 800 1000 1200 1400 1600
Cry
stal
Bal
l Mea
n
600
800
1000
1200
1400
G* Pole Mass [GeV]
400 600 800 1000 1200 1400 1600
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stal
Bal
l Sig
ma
40
50
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90
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G* Pole Mass [GeV]
400 600 800 1000 1200 1400 1600
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stal
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l a
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3
G* Pole Mass [GeV]
400 600 800 1000 1200 1400 1600
Cry
stal
Bal
l n2
2.2
2.4
2.6
2.8
3
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 thex, σ, a, and n.
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`νjj signal template acceptance fit
G* Pole Mass [GeV]
400 600 800 1000 1200 1400 1600
Acc
epta
nce
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
Landau functional fit (in black) to the acceptances in the eνjj channelusing to the full-simulated G∗ samples (in blue) with masses 500, 750,1000, and 1500 GeV . Acceptances of template signal distributions wereextrapolated from fit.
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`νjj signal template cross-sections
Table: Summary of cross-sections times branching ratio and acceptances perchannel used to derive cross section limits at intermediate MG∗ mass values,where fully simulated samples were non available.
G∗ Mass σ × B Acceptance[GeV] [pb] eνjj µνjj Average
500 5.593 0.045 0.034 0.040550 4.597 0.065 0.048 0.057600 3.601 0.081 0.058 0.070650 2.643 0.089 0.065 0.077700 1.648 0.091 0.067 0.079750 0.614 0.089 0.068 0.079800 0.514 0.082 0.064 0.073850 0.413 0.075 0.059 0.067900 0.313 0.067 0.054 0.061950 0.212 0.060 0.049 0.0551000 0.027 0.051 0.041 0.0461050 0.095 0.047 0.040 0.0441100 0.078 0.041 0.036 0.0391150 0.061 0.036 0.032 0.0341200 0.044 0.032 0.029 0.0311250 0.027 0.030 0.027 0.0291300 0.023 0.026 0.023 0.0251350 0.019 0.023 0.021 0.0221400 0.015 0.021 0.019 0.0201450 0.012 0.018 0.017 0.0181500 0.008 0.018 0.018 0.018
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G∗ → eνjj signal templates
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
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0 )
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
00.02
0.040.060.08
0.10.12
0.140.16
0.180.2
0.22
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
E. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 83 / 41
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G∗ → µνjj signal templates
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
100
200
300
400
500
600
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000E
vent
s / (
10
)0
100
200
300
400
500
600
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
100
200
300
400
500
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
50
100
150
200
250
300
350
400
450
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0204060
80100120140
160180200220
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
20
40
60
80
100
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
10
20
30
40
50
60
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
5
10
15
20
25
30
35
40
45
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000E
vent
s / (
10
)0
5
10
15
20
25
30
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
2
4
6
8
10
12
14
16
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
1
2
3
4
5
6
7
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
1
2
3
4
5
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
0.5
1
1.5
2
2.5
3
3.5
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
0.5
1
1.5
2
2.5
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000E
vent
s / (
10
)0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
0.1
0.2
0.3
0.4
0.5
0.6
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
0.05
0.1
0.15
0.2
0.25
0.3
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
Mass(lvjj) (GeV)
0 200400600800100012001400160018002000
Eve
nts
/ ( 1
0 )
0
0.02
0.04
0.06
0.08
0.1
0.12
E. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 84 / 41
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Gkk → WW → `νjj signal templates
eνjj µνjj
jj) [GeV]νM(l
0 200 400 600 800 1000 1200 1400 1600 1800 2000-410
-310
-210
-110
1
10
210 Signal Mass [GeV]500600700800900100011001200130014001500
jj) [GeV]νM(l
0 200 400 600 800 1000 1200 1400 1600 1800 2000-410
-310
-210
-110
1
10
210 Signal Mass [GeV]500600700800900100011001200130014001500
Reconstructed M(`νjj) from AFII ‘bulk’ Graviton samples: 500-1500 GeV, 100 GeV steps
jj) [GeV]νM(l
0 200 400 600 800 1000 1200 1400 1600 1800 2000-410
-310
-210
-110
1
10
210Mass [GeV]
500550600650700750800850900950100010501100115012001250130013501400145015001550
jj) [GeV]νM(l
0 200 400 600 800 1000 1200 1400 1600 1800 2000-410
-310
-210
-110
1
10
210Mass [GeV]
500550600650700750800850900950100010501100115012001250130013501400145015001550
Reconstructed M(`νjj) from AFII ‘bulk’ Graviton samples: 500-1500 GeV, 100 GeV stepsplotted with signal templates for 550-1550 GeV in 100 GeV steps
E. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 85 / 41
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`νjj signal variable
Plot shown in `νjj signal region
MT (sys)
M(sys)
eνjj
0 200 400 600 800 1000 1200 1400 1600 1800 2000
Eve
nts
-110
1
10
210
310mc.alpgen.wjets, 1119.70mc.mcatnlo.top, 707.66mc.herwig.vv, 93.17qcd.alpgen, 44.18mc.alpgen.zjets, 25.59mc.rsg.m500.kmpl0, 1238.45mc.rsg.m1000.kmpl0, 28.69mc.rsg.m1500.kmpl0, 0.70
= 7 TeVs-1
Ldt = 4.701 fb∫
0 200 400 600 800 1000 1200 1400 1600 1800 2000
Eve
nts
-110
1
10
210
310mc.alpgen.wjets, 1119.70mc.mcatnlo.top, 707.46mc.herwig.vv, 93.10qcd.alpgen, 44.18mc.alpgen.zjets, 25.59mc.rsg.m500.kmpl0, 1238.45mc.rsg.m1000.kmpl0, 28.69mc.rsg.m1500.kmpl0, 0.70
= 7 TeVs-1
Ldt = 4.701 fb∫
µνjj
0 200 400 600 800 1000 1200 1400 1600 1800 2000
Eve
nts
-110
1
10
210
310 mc.alpgen.wjets, 867.96mc.mcatnlo.top, 544.23mc.herwig.vv, 72.11qcd.alpgen, 50.44mc.alpgen.zjets, 26.09mc.rsg.m500.kmpl0, 918.70mc.rsg.m1000.kmpl0, 22.49mc.rsg.m1500.kmpl0, 0.68
= 7 TeVs-1
Ldt = 4.701 fb∫
0 200 400 600 800 1000 1200 1400 1600 1800 2000
Eve
nts
-110
1
10
210
310 mc.alpgen.wjets, 867.47mc.mcatnlo.top, 544.30mc.herwig.vv, 71.94qcd.alpgen, 50.44mc.alpgen.zjets, 26.09mc.rsg.m500.kmpl0, 918.55mc.rsg.m1000.kmpl0, 22.49mc.rsg.m1500.kmpl0, 0.68
= 7 TeVs-1
Ldt = 4.701 fb∫
Mass distributions look better, especially for signal masses> 1 TeV
E. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 86 / 41
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G∗/W ′ → `νjj truth comparison plots
M = 500 GeV M = 1000 GeV
G*/W' pt [GeV]
0 50 100 150 200 250 300 350 400 450 500-410
-310
-210
-110G*
KKGW'
G*/W' pt [GeV]
0 50 100 150 200 250 300 350 400 450 500
-310
-210
-110G*
KKGW'
*)θcos(
-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 10
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0.1
G*KKG
W'
*)θcos(
-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 10
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0.1
G*KKG
W'
E. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 87 / 41
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G∗/W ′ → `νjj truth comparison plots
M = 500 GeV M = 1000 GeV
G*/W' #m
300 350 400 450 500 550 600 650 700
-410
-310
-210
-110
G*KKG
W'
G*/W' #m
800 850 900 950 1000 1050 1100 1150 1200
-310
-210
-110
G*KKG
W'
E. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 88 / 41
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G∗/W ′ → `νjj truth comparison plots
M = 500 GeV M = 1000 GeV
W/Z boson pt [GeV]
0 50 100 150 200 250 300 350 400 450 500-410
-310
-210
-110 G*kkG
W'
W/Z boson pt [GeV]
0 100 200 300 400 500 600 700 800 900 1000-510
-410
-310
-210
-110 G*kkG
W'
ηW/Z boson
-5 -4 -3 -2 -1 0 1 2 3 4 5
-410
-310
-210
-110 G*kkG
W'
ηW/Z boson
-5 -4 -3 -2 -1 0 1 2 3 4 5
-410
-310
-210
-110 G*kkG
W'
E. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 89 / 41
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G∗/W ′ → `νjj truth comparison plots
M = 500 GeV M = 1000 GeV
lepton pt [GeV]
0 50 100 150 200 250 300 350 400 450 500
-410
-310
-210
-110G*
KKGW'
lepton pt [GeV]
0 100 200 300 400 500 600 700 800
-410
-310
-210
-110G*
KKGW'
ηlepton
-5 -4 -3 -2 -1 0 1 2 3 4 5
-410
-310
-210
-110 G*KKG
W'
ηlepton
-5 -4 -3 -2 -1 0 1 2 3 4 5
-410
-310
-210
-110 G*KKG
W'
E. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 90 / 41
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G∗/W ′ → `νjj truth comparison plots
M = 500 GeV M = 1000 GeV
lepton pt [GeV]
0 50 100 150 200 250 300 350 400 450 500
-410
-310
-210
-110G*
KKGW'
lepton pt [GeV]
0 50 100 150 200 250 300 350 400 450 500
-210
G*KKG
W'
E. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 91 / 41
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G∗/W ′ → `νjj truth comparison plots
M = 500 GeV M = 1000 GeV
quark pt [GeV]
0 50 100 150 200 250 300 350 400 450 500
-410
-310
-210
-110G*
KKGW'
quark pt [GeV]
0 100 200 300 400 500 600 700 800
-410
-310
-210
-110G*
KKGW'
ηquark
-5 -4 -3 -2 -1 0 1 2 3 4 5-510
-410
-310
-210
-110G*
KKGW'
ηquark
-5 -4 -3 -2 -1 0 1 2 3 4 5
-410
-310
-210
-110 G*KKG
W'
E. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 92 / 41
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G∗/W ′ → `νjj Acceptances
M = 500 GeV M = 1000 GeV
Selection Cut0 1 2 3 4 5 6 7 8
Acc
epta
nce
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1 W'G*
KKG
Selection Cut0 1 2 3 4 5 6 7 8
Acc
epta
nce
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1 W'KKG
G*
Selection Cut0 1 2 3 4 5 6 7 8
/G*)
KK
Rel
ativ
e A
ccep
tanc
e (G
1
1.5
2
2.5
3
3.5
Selection Cut0 1 2 3 4 5 6 7 8
/G*)
KK
Rel
ativ
e A
ccep
tanc
e (G
1
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2
Cut 2: Lepton pt/etaCut 3: Jet pt/etaCut 4: EmissT
Cut 5: Pt(lepton,EmissT )Cut 6: Pt(dijet)Cut 7: M(dijet)
E. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 93 / 41
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`νjj Signal Region Plots
eνjj µνjj
(j,j) [GeV]T
p0 100 200 300 400 500 600 700 800 900 1000
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
10
210
310DataW+jetsTopDibosonQCDZ+jets
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
(j,j) [GeV]T
p0 100 200 300 400 500 600 700 800 900 1000
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
10
210
DataW+jetsTopDibosonQCDZ+jets
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
eνjj + µνjj
(j,j) [GeV]T
p0 100 200 300 400 500 600 700 800 900 1000
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
10
210
310 DataW+jetsTopDibosonZ+jetsQCD
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
E. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 94 / 41
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`νjj Signal Region Plots
eνjj µνjj
Lepton Pt [GeV]0 100 200 300 400 500 600 700 800
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
10
210
DataW+jetsTopDibosonQCDZ+jets
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
Lepton Pt [GeV]0 100 200 300 400 500 600 700 800
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
10
210
DataW+jetsTopDibosonQCDZ+jets
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
eνjj + µνjj
Lepton Pt [GeV]0 100 200 300 400 500 600 700 800
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
10
210
310 DataW+jetsTopDibosonZ+jetsQCD
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
E. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 95 / 41
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`νjj Signal Region Plots
eνjj µνjj
[GeV]misstE
0 100 200 300 400 500 600 700
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
10
210
DataW+jetsTopDibosonQCDZ+jets
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
[GeV]misstE
0 100 200 300 400 500 600 700
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
10
210
DataW+jetsTopDibosonQCDZ+jets
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
eνjj + µνjj
[GeV]misstE
0 100 200 300 400 500 600 700
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
10
210
310 DataW+jetsTopDibosonZ+jetsQCD
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
E. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 96 / 41
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`νjj Signal Region Plots
eνjj µνjj
(lep,MET)TM0 50 100 150 200 250 300 350 400 450 500
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
10
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DataW+jetsTopDibosonQCDZ+jets
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
(lep,MET)TM0 50 100 150 200 250 300 350 400 450 500
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
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DataW+jetsTopDibosonQCDZ+jets
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
eνjj + µνjj
(lep,MET)TM0 50 100 150 200 250 300 350 400 450 500
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
10
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310 DataW+jetsTopDibosonZ+jetsQCD
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
E. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 97 / 41
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`νjj Signal Region Plots
eνjj µνjj
)miss
T(lep,E
Tp
0 100 200 300 400 500 600 700 800 900 1000
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
10
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310DataW+jetsTopDibosonQCDZ+jets
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
)miss
T(lep,E
Tp
0 100 200 300 400 500 600 700 800 900 1000
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
10
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310DataW+jetsTopDibosonQCDZ+jets
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
eνjj + µνjj
)miss
T(lep,E
Tp
0 100 200 300 400 500 600 700 800 900 1000
sign
ifica
nce
-2
0
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nts
-110
1
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310 DataW+jetsTopDibosonZ+jetsQCD
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
E. Williams (Columbia U.) G∗ → WW → `νjj thesis defense July 2nd, 2012 98 / 41
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`νjj Signal Region Plots
eνjj µνjj
Jet Pt [GeV]Σ200 400 600 800 1000 1200 1400 1600 1800
sign
ifica
nce
-2
0
2
Eve
nts
-110
1
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310 DataW+jetsTopDibosonQCDZ+jets
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
Jet Pt [GeV]Σ200 400 600 800 1000 1200 1400 1600 1800
sign
ifica
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-2
0
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nts
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1
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310DataW+jetsTopDibosonQCDZ+jets
(800GeV)kkG(1000GeV)kkG(1200GeV)kkG
eνjj + µνjj
Jet Pt [GeV]Σ200 400 600 800 1000 1200 1400 1600 1800
sign
ifica
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-2
0
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nts
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1
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`νjj Signal Region Plots
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`νjj Signal Region Plots
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`νjj Signal Region Plots
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`νjj p-values
Mass eνjj µνjj Combined
500 0.604 0.172 0.381550 0.489 0.222 0.353600 0.374 0.206 0.286650 0.315 0.147 0.22700 0.368 0.121 0.223750 0.511 0.191 0.34800 0.69 0.393 0.559850 0.662 0.643 0.675900 0.454 0.706 0.608950 0.209 0.612 0.403
1000 0.14 0.451 0.2711050 0.183 0.352 0.2711100 0.208 0.327 0.2831150 0.182 0.329 0.273
The probabilities, or p-value ≡ 1 - CLb, that the background fluctuates to or above the data ineach channel. p-values for M≥ 1200 GeV are statistics limited and not reliable. Systematicuncertainties are included in this calculation.
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