search for new physics in mono-jet final states in pp collisions at … · 2017-03-14 · atlas...
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Search for New Physicsin mono-jet final states
in pp collisions at √s = 13 TeV with the ATLAS experiment at LHC
Giuliano Gustavino27 October 2016
Seminario Conclusivo XIX Ciclo
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ATLAS & LHC
The Large Hadron Collider (LHC) is the world’s largest and most powerful particle accelerator.
pp and PbPb collider Circumference: 27 km √s = 13 TeV Collision frequency: 40 MHz
Giuliano Gustavino
Multi-purpose experiment able to the detect
the wide spectrum of final states for high precision
Standard Model measurements and New Physics searches
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Hadron collisions
๏ Signal process + jets production ๏ Parton shower ๏ Fragmentation ๏ Hadron decays ๏ Beam remnants ๏ Underlying event
Large numbers of vertexes reconstructed in the same events!
PILEUP
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Mono-jet final stateThe monojet analysis is a search for events with a high transverse momentum jet and missing transverse momentum in the final state.
The monojet topology constitutes a clean and distinctive signature in searches for new physics beyond the Standard Model (SM) at colliders.
transverse planeWhat is MET?
MET measures the energy imbalance in the plane transverse to the colliding proton beams
What is a jet?
Hadrons are clustered together to make particle jets
high energy jet coming from
the initial states
large missing transverse
momentum (MET)
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The existence of a Dark Matter (DM) particle is a well-
established hypothesis that explains a range of astrophysical
and cosmological measurements.
The presence of a non-baryonic component in the universe is
inferred from the observation of its gravitational interactions
How can we study the Dark Matter?
direct detection based on scattering interaction detections
(DAMA, LUX etc.)
indirect detection experiments that look for final states given
by the DM annihilation (AMS, Ice-Cube etc.)
Pair production at LHC with large missing transverse
momentum in the detector
The detection of DM candidates in a collider can give complementary results with respect to the other DM detections.
Dark Energy 69%
Baryonic Matter 5%
Dark Matter 26%
DM
DM
SM
SM
Annihilation
Sca
tterin
g
Production
5
The Dark Matter paradigm
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Selection
MET > 250 GeV leading jet pT > 250 GeV , |eta| <2.4,
tight jet cleaning njet <= 4
|dɸ(MET, jets)| > 0.4 lepton veto MET>250 GeV
jet pT>250GeV, |η|<2.4,
tight quality
e & µ veto
Up to 3 other jets (pT>30GeV)
>0.4
SR
Residual dominant backgrounds given by the Z(νν)+jets and W(τhadν)+jets processes
Z(νν)+jets 58%W(τν)+jets 18%
W(µν)+jets 9%
W(eν)+jets 8%
top 4%others 3%
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Even
ts /
50 G
eV
2<10
1<10
1
10
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310
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510 ATLAS-1 = 13 TeV, 3.2 fbs
) Control Regionµµ AZ(>250 GeV miss
T>250 GeV, E
Tp
Data 2015Standard Model
) + jetsii AZ() + jetsio AW() + jetsiµ AW() + jetsi eAW(
ll) + jetsAZ(Dibosons
+ single toptt
[GeV]missTE
400 600 800 1000 1200 1400
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1<10
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510ATLAS
-1 = 13 TeV, 3.2 fbs) Control Regioni eAW(
>250 GeV missT
>250 GeV, ET
p
Data 2015Standard Model
) + jetsii AZ() + jetsio AW() + jetsiµ AW() + jetsi eAW(
ll) + jetsAZ(Dibosons
+ single toptt
[GeV]missTE
400 600 800 1000 1200 1400
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Analysis strategy3 control regions are defined (1µ, 2µ, 1e) to evaluate the V+jets backgrounds. ➡ to reduce the uncertainties due to the MC
modeling
Z(νν) W(µν)
~ Z(νν)*, W(µν) CR1µW(τν), W(eν), Zττ CR1eZ(µµ) CR2µZ(ee), diboson, top MCMultijet and NCB data-driven
systematic for the W/Z ratio vs pT and the EW/QCD corrections differences
MET ~ boson pT muons treated as
invisibles in the MET calculation
Even
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610ATLAS
-1 = 13 TeV, 3.2 fbs) Control Regioniµ AW(
>250 GeV missT
>250 GeV, ET
p
Data 2015Standard Model
) + jetsii AZ() + jetsio AW() + jetsiµ AW() + jetsi eAW(
ll) + jetsAZ(Dibosons
+ single toptt
[GeV]missTE
400 600 800 1000 1200 1400
Dat
a / S
M
0.5
1
1.5
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Shape binned fitMET binned simultaneous fit is performed to exploit the shape information increasing the sensitivity between signals and background
k1µ(i) x Z(νν)+jets W(µν)+jets
W(τν)+jets W(eν)+jets Z(ττ)+jets
Z(µµ)+jets + k2µ(i) x + k1e(i) x
[TeV]medM1−10 1
µU
pper
lim
it on
2−10
1−10
1
10
210-1=50GeV Exclusion 5 fbχm
Simplified shape fit 15 bins + overflow
Best counting
ATLAS SimulationInternal
The signal strength limit on DM samples improves by ~20% over
the best counting experiment (inclusive MET region).
where i = 1,..,Nbin
7 bins used in the final results: METϵ[250,300,350,400,500,600,700,∞]GeV
3 normalization factors for each bin are applied (1 for each CR)
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ResultsEv
ents
/ 50
GeV
2<10
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Signal Region>250 GeV miss
T>250 GeV, E
Tp
Data 2015Standard Model
) + jetsii AZ() + jetsio AW() + jetsiµ AW() + jetsi eAW(
ll) + jetsAZ(Dibosons
+ single toptt) = (350, 345) GeV0
r¾, b~m()= (150, 1000) GeV
med, M
DM(m
=5600 GeVD
ADD, n=3, M
[GeV]missTE
400 600 800 1000 1200 1400
Dat
a / S
M
0.5
1
1.5
Dominant uncertainties (total 4-12%): statistical (3-10%), top (~3%), boson+jet modeling (2-5%)
low MET bins ➡ systematics unc. dominates high MET bins ➡ statistical unc. dominates.
Interpret results as limits
Good agreement is observed between data and MC expectations.
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DM interpretationResults interpretation: axial vector mediator, gq=0.25, gDM=1 (as recommended by the LHC Dark Matter Working group arXiv:1603.04156)
Contour Limit in the 2D plane DM vs Mediator mass
Limit on DM-proton scattering cross-section.
DM
DM
q
q jet
JP=1-
gq gDM
LHC limit gives complementary results wrt direct detection experiments
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DM interpretationOn-shell
- high xsecs - LHC exclusion
Off-shell - low xsec
- relic DM underproduced
Heavy mediator - production suppressed (σSD~Mmed-4)
- relic DM overproduced
On-shell
Off-shell
Heavy mediator
Heavy mediator
On-shell Off-shell
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Mono-jet vs Dijets searchesThe mediator can decay back to quarks
dijet signatures limit almost independent with the DM masses
Complementary results between the two kind of searches Lower mediator-SM coupling and higher mediator-DM coupling increase the relevance of the mono-jet results
q
q
q
q
Z’gq gq
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Future improvements
[GeV]Am0 500 1000 1500 2000
[GeV
]χ
m
0
200
400
)expσ 1 ±Expected limit (
Perturbativity Limit
Relic Density
ATLAS Internal-1 = 25 fbintL
Axial Vector MediatorDirac Fermion DM
= 1.0χ
= 0.25, gqg95% CL limits
χ
= 2
mAm
b-tag
3.2 fb-1 25 fb-1
CR1ph, more bins
more statistics expected increase of more than a factor 10 for the end of the year
more MET bins increase sensitivity at high MET
reducing low MET uncertainty by using CR1mu+bjets to evaluate the top background
(10-15% improv. in the low MET unc.)
reducing high MET uncertainty by introducing a new CR1gamma (similar to CR1mu) to evaluate Z(vv)+jets (10% improv. in the high MET unc.)
Only a subset of the signal samples used to produce the projection limits
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New fitting strategies
2D fit (MET, Njets) MET-dependent NFs for each MET bin Njet binning scheme: # jets: [1,2,3,4]
Nje
ts
MET
Goal: exploit the other useful informations of the final state
[GeV]Am0 500 1000 1500 2000
[GeV
]χ
m
0
200
400
Expected Limits with 1D Fit
Expected Limits with 2D Fit
ATLAS Internal-1 = 13 TeV, 3.2 fbs
Axial Vector MediatorDirac Fermion DM
= 1.0χ
= 0.25, gqg95% CL limits
Limits improvement of 20-35% observed wrt the standard strategy
2D fit (MET, BDT) BDT exploits also other final state informations (such as Njets, jets direction, angular variables between the jets and the MET)
to build a 1D discriminant MET-dependent NFs for each MET bin
BDT
MET
Average gains obtained on the limit of 18%
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Conclusions
Many improvements have been ideated and implemented in the mono-jet analysis based on the data samples of 3.2 fb-1 at √s=13 TeV.
The level of agreement between SM predictions and data has been translated in the DM (and other) scenarios (arXiv:1604.07773).
Complementarity of mono-jet, di-jet analysis and DD experiments ➡ leading role in the search for DM particles with low mass (<10 GeV).
The new amount of data will give the unique opportunity to look at never reached high MET distribution.
Increase of sensitivity for the next analysis generation: the decrease of the main uncertainties in the low and high MET spectrum exploiting other information in the final state
Dark Matter may be around the corner, it's just us find it!
NEW
Backup Slides
Giuliano Gustavino
Other SR distributions
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T>250 GeV, E
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Data 2015Standard Model
) + jetsνν →Z() + jetsντ →W() + jetsνµ →W() + jetsν e→W(
ll) + jets→Z(Dibosons
+ single toptt) = (350, 345) GeV0
χ∼, b~m()= (150, 1000) GeV
med, M
DM(m
=5600 GeVD
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Leading jet p400 600 800 1000 1200 1400
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ll) + jetsAZ(Dibosons
+ single toptt) = (350, 345) GeV0
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) + jetsii AZ() + jetsio AW() + jetsiµ AW() + jetsi eAW(
ll) + jetsAZ(Dibosons
+ single toptt) = (350, 345) GeV0
r¾, b~m()= (150, 1000) GeV
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ll) + jetsAZ(Dibosons
+ single toptt) = (350, 345) GeV0
r¾, b~m()= (150, 1000) GeV
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Monojet results
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250 GeV < MET < 300 GeV MET > 700 GeV
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Monojet Limits
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Mono-jet limits with fixed mediator & DM mass and variable coupling
Contour Limit in the 3D plot with DM vs Mediator mass vs µ UL @95%
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SUSY interpretationsSUSY compressed scenarios
e.g. stop decays with small Δm = mstop-mLSP: signature: ISR + decay of two squarks
stop (t+LSP), sbottom (b+LSP), light squark (q+LSP).
[GeV]1t
~m260 280 300 320 340 360 380 400 420 440
[G
eV
]10
χ∼m
150
200
250
300
350
400
450
-1 = 13 TeV, 3.2 fbs
1
0χ∼ c→
1t~
production, 1t~1t~
All limits at 95% CL
ATLAS
)theory
SUSYσ1 ±Observed limit (
)expσ1 ±Expected limit (
= 8 TeVsATLAS
c + m
0
1χ∼ < m1t~m
W + mb + m
0
1χ∼ > m1t~m
[GeV]1b
~m100 150 200 250 300 350 400
[G
eV
]10
χ∼-m 1
b~m
6
8
10
12
14
16
18
20
)theory
SUSYσ1 ±Observed limit (
)expσ1 ±Expected limit (
-1 = 13 TeV, 3.2 fbs
1
0χ∼ b→
1b~
production, 1
b~
1b~
All limits at 95% CL
ATLAS
[GeV]q~
m
400 450 500 550 600 650 700
[G
eV
]0 1
χ∼-m q~
m
6
8
10
12
14
16
18
20
22
24
)theory
SUSYσ1 ±Observed limit (
)expσ1 ±Expected limit (
-1 = 13 TeV, 3.2 fbs
1
0χ∼ q→q~ production, q~q~
All limits at 95% CL
ATLAS
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LED interpretations
Large Extra Dimensions Extra spatial dimensions proposed as a way to
solve the hierarchy problem. Jet + graviton modes escaping detection
Number Of Extra Dimensions
2 3 4 5 6
Lo
we
r L
imit
[Te
V]
DM
3
4
5
6
7
8-1=13 TeV, 3.2 fbs
All limits at 95% CL
ATLAS)expσ 1 ±Expected Limit (
Observed Limit
Obs. Limit (after damping)
-1fb TeV, 20.3 = 8sATLAS
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µCR1EM1µ
µCR1EM2µ
µCR1EM3µ
µCR1EM4µ
µCR1EM5µ
µCR1EM6µ
µCR1IM7µ
Valu
e af
ter t
he fi
t
0.4
0.6
0.8
1
1.2
1.4
1.6
ATLAS-1 = 13 TeV, 3.2 fbs
Internal
CR1eEM1µ
CR1eEM2µ
CR1eEM3µ
CR1eEM4µ
CR1eEM5µ
CR1eEM6µ
CR1eIM7µ
Valu
e af
ter t
he fi
t
0.4
0.6
0.8
1
1.2
1.4
1.6
ATLAS-1 = 13 TeV, 3.2 fbs
Internal
µCR2EM1µ
µCR2EM2µ
µCR2EM3µ
µCR2EM4µ
µCR2EM5µ
µCR2EM6µ
µCR2IM7µ
Valu
e af
ter t
he fi
t
0.4
0.6
0.8
1
1.2
1.4
1.6
ATLAS-1 = 13 TeV, 3.2 fbs
Internal
Normalization factors
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Strategy comparison
0
0,05
0,1
0,15
0,2
250-300 400-500 700-800 > 1000
2015-likeCR2lCR1phCR1mubtag
MET [GeV]
rela
tive
unce
rtain
ty
Binning [250,300,350,400,500,600,700,800,900,1000,inf] GeV
CR1ph based strategy improves the high MET bins total unc. (~10%)
add other high met bins?
BLIND
Lint = 25 fb-1
CR2l based strategy suffers of
low statistics
b-tag based strategy yields
to an improvement in the low
MET regions (~10-15%)
Standard strategy CR2l based b-tag based CR1ph based
Z(vv)+jets from CR1mu Z(vv)+jets from CR2l top bkg from CR1mubtag Z(vv)+jets from CR1ph
CR1mu,CR1e,CR2mu CR1mu,CR1e,CR2mu,CR2e CR1mubveto, CR1mubtag,CR1e, CR2mu CR1ph,CR1mu,CR1e,CR2mu