lνlνlν

Transcription

lνlνlν
Measurement of the WWW ∗ → lνlνlν final state
√
in pp collisions at s = 8 TeV
with the ATLAS detector
Martina Pagacova
University of Freiburg
Graduiertenkolleg
9th July 2014
Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
09/07/2014
1 / 21
Introduction
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Introduction
2
Overview of analysis
3
Signal regions
4
Fake lepton background estimation
5
Conclusion&Plans
Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
09/07/2014
2 / 21
Introduction
Standard Model of particle physics (SM)
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a gauge theory based on 3 fundamental symmetries SU (3)C × SU (2)L × U (1)Y
very successful in describing currently available experimental data
not a complete theory explaining all physical phenomena (dark matter, gravity, ...)
interactions
I electromagnetism (γ)
I weak interaction (W ± , Z )
I strong interaction (g)
elementary particles
I 6 quarks u, c, t, d, s, b
I 6 leptons (e, νe , µ, νµ , τ, ντ )
EWSB
I spontaneous electroweak
symmetry breaking via BEH
mechanism
Martina Pagacova (UNI Freiburg)
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Introduction
Standard model
Standard Model of particle physics (SM)
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Electroweak SM
a gauge theory based on 3 fundamental symmetries SU (3)C × SU (2)L × U (1)Y
very successful in describing currently available experimental data
not a complete theory explaining all physical phenomena (dark matter, gravity, ...)
interactions
I electromagnetism (γ)
I weak interaction (W ± , Z )
I strong interaction (g)
elementary particles
I 6 quarks u, c, t, d, s, b
I 6 leptons (e, νe , µ, νµ , τ, ντ )
EWBS
I spontaneous electroweak
symmetry breaking via BEH
mechanism
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Introduction
QGC
Processes with quartic gauge boson couplings (QGC)
What are they?
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processes where a QGC vertex contributes
predicted by SM but not yet observed
How can they be measured?
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two classes of QGC processes
triple gauge boson production (e.g. WWW )
vector boson scattering (VBS)
What can we learn from measuring them?
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observe the SM QGC processes
test EWSB and Higgs properties
constrain anomalous Quartic Gauge Couplings (aQGC)
News!
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first evidence of a process containing VVVV vertex in EW VBS W ± W ± → W ± W ±
same-sign W ± W ± jj analysis: arXiv:1405.6241
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Introduction
aQGC
Look at physics beyond the SM with QGC: aQGC
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assume SM is a low energy approximation of a more complex one
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consider effective Lagrangian (SM + higher-dimension operators)
Leff = LSM +
X X c (d )
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dim d
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Λd −4
(d )
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can parametrize low energy effects from beyond SM physics
model independent, complementary to direct searches
generally requires additional unitarization (killing model independence)
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set limits on relevant effective aQGC parameters
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Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
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6 / 21
Overview of analysis
1
Introduction
2
Overview of analysis
3
Signal regions
4
Fake lepton background estimation
5
Conclusion&Plans
Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
09/07/2014
7 / 21
Overview of analysis
Analysis targets
Analysis targets
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measurement WWW ∗ → lνlνlν production cross section (l = e, µ)
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includes H → WW signal
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setting limits on anomalous Quartic Gauge Coupling (aQGC)
SM cross-section
W −W +W +
W −W −W +
Martina Pagacova (UNI Freiburg)
@8TeV
4.95 fb
2.65 fb
WWW ∗ → lνlνlν analysis
@14TeV
11.42 fb
6.84 fb
09/07/2014
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Overview of analysis
Object selection
Object selections
ELECTRONS
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MUONS
Central electrons (author is 1 or 3)
pT > 10 GeV
|η| < 1.37 or 1.52 < |η| < 2.47
Tight++
Object quality flag
ET cone20/ET < 0.10 for pT > 20GeV
ET cone20/ET < 0.07 for pT < 20GeV
pT cone20/pT < 0.04
|d0 /σ (d0 )| < 3.0
|z0 sin (θ)| < 0.4mm
No duplicate µ or e within ∆R < 0.1
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tight STACO Combined
pT > 10 GeV
|η| < 2.5
MCP ID Hits selection
ET cone20/ET < 0.10 for pT > 20GeV
ET cone20/ET < 0.07 for pT < 20GeV
pT cone20/pT < 0.04
|d0 /σ (d0 )| < 3.0
|z0 sin (θ)| < 1.0mm
No duplicate µ within ∆R < 0.1
JETS
ETmiss
Anti-kt 4 LC Topo Jets
pT > 25GeV
|η| < 4.5
|JVF| > 0.5 for jets with |η| < 2.4 and
pT < 50GeV
I No duplicate µ or e within ∆R < 0.2
I MET_RefFinal_STVF reconstructed from
METUtility
I propagate leptons smearing energy
scale
I propagate jet calibration
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Signal regions
1
Introduction
2
Overview of analysis
3
Signal regions
4
Fake lepton background estimation
5
Conclusion&Plans
Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
09/07/2014
10 / 21
Signal regions
Signal region definitions
Event selection
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exactly 3 leptons passing our selection requirements
Z -mass window → reduce WZ and ZZ background
b-jet veto → reduce t t̄ contribution
ETmiss → coming from leptonic W decay
Optimization
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done separately for 3 regions according to the number of lepton pairs of same flavor
and opposite charge SFOS
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0SFOS, 1SFOS (eeµ + µµe), 2SFOS (eee + µµµ)
categorization driven by main expected irreducible WZ background
Signal regions
Lepton pT
ETmiss
Z veto
b-tagged jet veto
Martina Pagacova (UNI Freiburg)
0SFOS
1SFOS
2SFOS
pT > 20 GeV
ETmiss > 41GeV ETmiss > 36GeV
|mSFOS − mZ | > 15GeV
70% b-tagging efficiency operating point
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Signal regions
MC prediction in signal regions
0SFOS
−→
1SFOS
−→
2SFOS
−→
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Fake lepton background estimation
1
Introduction
2
Overview of analysis
3
Signal regions
4
Fake lepton background estimation
5
Conclusion&Plans
Martina Pagacova (UNI Freiburg)
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Fake lepton background estimation
Fake leptons
Fake lepton background
Source of fake leptons
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mis-reconstructed leptons
produced in light, heavy flavor jets or conversions
Background estimation
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reducible background
dominated by Z +jets, t t̄ and single top
estimated from generalised matrix method (developed by ATLAS SUSY group:
arXiv:1404.2500)
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Fake lepton background estimation
Generalised MxM
Generalised MxM
,→ fully data-driven method
Measurable quantities
NT # tight leptons
NL # loose leptons
Physical quantities
NR # real leptons
NF # fake leptons
Real and fake lepton efficiencies ϸreal , ϸfake
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relate NT /L with NR/F
measured from DATA in signal-free regions of phase space
Weight w
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applied for every tight/loose combination separately
Example
I event with 3 pre-selected leptons eeµ with configuration TLL
I MxM will produce the following
Input


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
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eeµ, TLL −→ 



Martina Pagacova (UNI Freiburg)
Output
LLL
···
wLLL
eL eL µL
Fails cuts
wLTT
wTTT
eL eT µT
eT eT µT
Fails cuts
Passes cuts
···
LTT
TTT
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Fake lepton background estimation
Generalised MxM
Loose/tight selection
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loose leptons: pass all pre-selection requirements & fail any of the signal requirements
tight leptons: satisfy signal requirements in addition to pre-selected requirements
Electron definition
Muon definition
Pre-selected electrons
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Pre-selected muons
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Central electrons (author is 1 or 3)
pT > 10 GeV
|η| < 1.37 or 1.52 < |η| < 2.47
Medium++
Object quality flag
No duplicate µ or e within ∆R < 0.1
Signal muons
Signal electrons
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Tight++
ET cone20/ET < 0.10 for pT > 20GeV
ET cone20/ET < 0.07 for pT < 20GeV
pT cone20/pT < 0.04
|d0 /σ (d0 )| < 3.0
|z0 sin (θ)| < 0.4mm
Martina Pagacova (UNI Freiburg)
tight STACO Combined
pT > 10 GeV
|η| < 2.5
MCP ID Hits selection
No duplicate µ within ∆R < 0.1
WWW ∗ → lνlνlν analysis
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ET cone20/ET < 0.10 for pT > 20GeV
ET cone20/ET < 0.07 for pT < 20GeV
pT cone20/pT < 0.04
|d0 /σ (d0 )| < 3.0
|z0 sin (θ)| < 1.0mm
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Fake lepton background estimation
Generalised MxM
Distributions with exactly 3 tight leptons
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event selection
Pre-selection cuts
GRL
trigger
= 3 selected leptons with pT > 10GeV
trigger matching
jet cleaning
data quality
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generalised MxM used to estimate
B
W +jets, singleTop, WW (from Diboson (WW +WZ +ZZ )), t t̄ (from ttbar (t t̄+t t̄V )
B
fake leptons
⇓
Martina Pagacova (UNI Freiburg)
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09/07/2014
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Fake lepton background estimation
Generalised MxM
Validation of fake background
first attempt
fake leptons estimated from MC (left) and from generalised MxM (right)
107
ATLAS Preliminary
∫L dt = 20.3 fb ,
-1
s = 8 TeV
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105
SD3PDSpecial_3Boson_fakes/PtLepSignal_TTT
Data (13756.00)
Diboson (6953.79)
Z (4462.48)
DYg (1953.96)
ttbar (520.06)
Signal (57.00)
Single Top (22.34)
Triboson (11.10)
W (0.00)
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103
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102
Overfl. Data: 217, MC: 0.00
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10-1
20
2
40
60
80
100
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pT signal leptons [GeV] (=3 tight lep)
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20
40
-1
s = 8 TeV
SD3PDSpecial_3Boson_fakes/PtLepSignal_TTT
Data (13756.00)
Fake leptons (10029.31)
WZ (5483.33)
ZZ (1464.28)
ttbarZ (99.08)
Signal (57.00)
ttbarW (49.72)
Triboson (11.10)
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1
10-1
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120
140
pT signal leptons [GeV] (=3 tight lep)
Martina Pagacova (UNI Freiburg)
∫L dt = 20.3 fb ,
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103
1
ATLAS Preliminary
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10
Data / Exp.
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Overfl. Data: 217, MC: 0.00
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Entries
Entries
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Data / Exp.
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WWW ∗ → lνlνlν analysis
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2
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80
100
120
140
pT signal leptons [GeV] (=3 tight lep)
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20
40
60
80
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120
140
pT signal leptons [GeV] (=3 tight lep)
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Fake lepton background estimation
Generalised MxM
Comments on the distributions
Left plot
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fake lepton contribution estimated from MC samples
fairly good DATA/MC agreement
huge systematics
Right plot
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fake leptons are estimated from generalised MxM
DATA/MC agreement not so good: fake leptons are over-estimated
discrepancies well understood: real and fake rates borrowed from other analysis with
different object selections (not optimal for our set up)
Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
09/07/2014
19 / 21
Conclusion&Plans
1
Introduction
2
Overview of analysis
3
Signal regions
4
Fake lepton background estimation
5
Conclusion&Plans
Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
09/07/2014
20 / 21
Conclusion&Plans
Conclusion&Plans
Conclusion
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analysis set up
signal regions defined
generalised MxM implemented
first validation plots with 3 tight leptons shown
real and fake rates measurement ongoing
Plans
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study charge misID contribution in 0SFOS
start writing internal documentation of the analysis
Thank you for attention!
Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
09/07/2014
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BACKUP SLIDES
Martina Pagacova (UNI Freiburg)
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MC samples
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WWW: VBFNLO
WW/WZ/ZZ: Powheg+Pythia8
ttbar: MC@NLO
ttbarV: Alpgen+Jimmy
W+jets: Alpgen+Jimmy
single Top: MC@NLO
VVV: Madgraph+Pythia
Z+jets
Z+gamma+Jets (Sherpa)
Z+Jets inclusive (Sherpa): remove overlap with Sherpa Zgamma samples
low mass (m < 40 GeV) Z+Jets (Alpgen): remove 40 < m < 60 GeV overlap
Z+Jets+heavy flavor (Alpgen): remove light flavor overlap
Note: same, new, outdated, updated
Martina Pagacova (UNI Freiburg)
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Event pre-selections
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GRL
data12_8TeV.periodAllYear_DetStatus-v61-pro14-02_DQDefects-00-01-00_PHYS_StandardGRL_All_Good
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trigger
Electrons: EF_e24vhi_medium1 or EF_e60_medium1
Muons: EF_mu24i_tight or EF_mu36_tight
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three leptons
exactly 3 leptons passing object quality selections
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trigger matching
at least one of selected leptons is matched to at least one of the required triggers and
has an offline pT at least 1 GeVabove the trigger threshold
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jet cleaning
remove events with "Looser Bad" jets (all jets - not just those passing jet object selections)
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data quality
reject LAr Error and corrupted Tile events
Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
09/07/2014
3 / 16
Signal to background optimization: procedure
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simultaneously maximize our signal yield and efficiency×purity
ϸ·π =
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S2
S + B σs
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R
Ldt
variations performed on lepton pT , mT and ETmiss with thresholds from 15 to 75 GeV
in steps of 20 GeV
minimum lepton pT always kept at least above 20 GeV
optimize separately in regions with pre-selection cuts and 0, 1, and 2 SFOS lepton pairs
Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
09/07/2014
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Signal to background optimization: 0SFOS
Most significant operating point
pT1,2,3 > 20 ;mT > 0 GeV; ETmiss > 0 GeV
+ b-veto (70% b-jet efficiency operating point)
Martina Pagacova (UNI Freiburg)
S
3.15 ± .03
3.11 ± .03
WWW ∗ → lνlνlν analysis
B
11.4 ± .9
6.9 ± .5
ϸ · π (10−3 )
4.43
5.24
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Signal to background optimization: 1SFOS
Most significant operating point
pT1,2,3 > 20 ;mT > 0 GeV; ETmiss > 41 GeV
+ Z -veto w/ optimized mass window |mSFOS − mZ | > 15 GeV
+ b-veto (70% b-jet efficiency operating point)
Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
S
4.32 ± .03
3.60 ± .03
3.55 ± .03
B
418 ± 4
57 ± 2
49 ± 2
ϸ · π (10−3 )
0.288
1.38
1.55
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Signal to background optimization: 2SFOS
Most significant operating point
pT1,2,3 > 20 ;mT > 0 GeV; ETmiss > 36 GeV
+ Z -veto w/ optimized mass window |mSFOS − mZ | > 15 GeV
+ b-veto (70% b-jet efficiency operating point)
Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
S
2.76.03
1.88 ± .02
1.85 ± .02
B
514 ± 7
49 ± 2
44 ± 1
ϸ · π (10−3 )
0.00954
0.0451
0.0485
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Background composition in 0SFOS region
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background composition study for region with no lepton pair SFOS performed
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splitting into channels according to lepton charge composition could help
+++/---: no signal, mainly WZ and ZZ bkg
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Bkg sources in 0SFOS: WZ
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approach
events with lepton misID determined by looking for matched truth lepton within ∆R < 0.1
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outcome
major contribution from real leptons WZ → lνττ (higher statistics needed)
non negligible contribution from charge misID electrons
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next steps
request for new WZ MC filtered samples (ZZ and t t̄ as well)
discussions with the e/gamma group about possible charge misID estimation technique
classification
◦ all events
x charge misID lepton events
+ other misID lepton events
(fakes)
samples
◦ WZ where Z → ee/µµ
◦ WZ where Z → ττ
Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
09/07/2014
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Bkg sources in 0SFOS: t t̄
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approach
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outcome
events with lepton misID determined by looking for matched truth lepton within ∆R < 0.1
major contribution from real leptons t t̄ → W (lν )bW (lν )b+ leptonic B-meson decay
10 − 20% coming from fake lepton (jets faking leptons)
,→ fake definition differs from one in MxM where also non-isolated leptons are fakes
classification
◦ all events
x charge misID lepton events
+ other misID lepton events
(fakes)
Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
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Fake rate measurement
Fake rate f
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probability that a fake lepton satisfying pre-selected requirements pass also tight ones
measured for each flavour separately in special control regions
Control regions
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our main source of fake leptons is Z +jets sample → following CRs definition is proposed
similar to the ones defined by WZ analysis: https://cds.cern.ch/record/1663539
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CR1: Z + "fake" µ
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exactly 2 signal electrons from Z → ee → TAG
exactly 1 pre-selected muon → PROBE
b-jet veto → to be closer to our SRs
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CR2: Z + "fake" e
exactly 2 signal muons from Z → µµ → TAG
exactly 1 pre-selected electron → PROBE
b-jet veto → to be closer to our SRs
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CR1/CR2 tight denotes that the probe lepton passes also tight requirements
Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
09/07/2014
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aQGC unitarization I
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aQGC parametrized using fs0 and fs1 in linear implementation
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unitarity violated already at LHC energies → unitarization needed
form factor unitarization scheme applied in VBFNLO
energy-dependent form factor suppressing amplitude
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F (s ) =
(1 + Λs2 )n
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FF
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ΛFF
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n
maximal scale satisfying real unitarity bound
estimated using exponent n = 31
exponent to prevent breaking of unitarity
n = 1 chosen for determining cross-sections and event generation1
Prescription from VBFNLO authors
Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
09/07/2014
12 / 16
aQGC unitarization II
Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
09/07/2014
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FF reweighting: lepton pT distributions
• black: aQGC
• red: aQGC with FF
• blue: SM
Figure: W − W − W +
Figure: W − W + W +
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normalized to 20fb−1
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WWW ∗ → lνlνlν analysis
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FF reweighting: W − W − W +
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event selection: lepton pT > 25/10/10GeV, ETmiss > 25GeV
x-axis: fs0 in 10−9 GeV −4 / y-axis: fs1 in 10−9 GeV −4
Event yield w/o FF (SM: 4.8 events)
without FF
with FF
Acceptance×efficiency w/o FF
with FF
without FF
Martina Pagacova (UNI Freiburg)
WWW ∗ → lνlνlν analysis
09/07/2014
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FF reweighting: W − W + W +
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event selection: lepton pT > 25/10/10GeV, ETmiss > 25GeV
x-axis: fs0 in 10−9 GeV −4 / y-axis: fs1 in 10−9 GeV −4
Event yield w/o FF (SM: 9.1 events)
without FF
with FF
Acceptance×efficiency w/o FF
with FF
without FF
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09/07/2014
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