Transcript of Search for dark matter candidates in events with a jet and missing transverse momentum using the...
- Slide 1
- Search for dark matter candidates in events with a jet and
missing transverse momentum using the ATLAS detector Pierre-Hugues
Beauchemin Tufts University Physical Sciences Symposia-2013,
Waltham, MA, 09/05/2013
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- Outline Monojet events Physics Motivation Main Standard Model
backgrounds Data-driven background estimates Motivation
Illustration of the techniques Application to monojet events
Results and interpretation Comparison to data Constraints on dark
matter Conclusions 2
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- Monojet events 3
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- Dark Matter Many observational evidences for a large amount of
dark matter in the universe 4 One of the strongest motivation for
new physics in HEP
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- Signature at Colliders Most popular explanation for the nature
of dark matter: Massive particles interacting very weakly with
matter (WIMPs) Dark matter was more abundant in early universe Dark
matter gets annihilated 5 Reverse is true: dark matter can be
produced in colliders WIMPs escape detection but can be inferred
from unbalance energy measurement in the transverse plane of the
detector Need recoil activity, typically jets Dark matter can be
signaled in jets+E T miss events at LHC
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- New Physics in monojet events Many new physics scenario
predicts high production rate for such final state: Generic dark
matter produced via contact interaction Invisible Higgs
Gauge-mediated SUSY breaking scenario: Gravitino+squark/gluino
production o Assume Production of graviton Kaluza-Klein mode in
large extra dimension scenarios Unparticle o Equivalent to LED+SUSY
in the bulk 6
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- Contribution from Standard Model Irreducible background Physics
processes with same final state Z +jets 7 q q Reducible background
Physics processes with different final states modified by detector
effects Wl +jets QCD multijet Non-collision events Others o
Dibosons (WW,WZ,ZZ) o Top (ttbar, single top)
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- Data-driven background estimates 8
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- 9 To determine how many SM events should pass the selections
defining the chosen final state, we must: predict the number of
irreducible and reducible single jets events produced in LHC
collisions : Estimate the probability that these SM events yield
the monojet signal defined by our event selections: Theoretical
calculation of various cross sections Number of collisions produced
(Luminosity) Probability distribution of observables for each
processes Detector effects on the distributions Standard Model
Predictions (I)
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- 10 The sensitivity to new phenomena depends on: The sensitivity
to new phenomena depends on: 2.The systematic uncertainty on the SM
expectations 1.The relative amount of new physics and SM
contribution Not under our control Is under our control 1. 2. THE
KEY IS TO CONTROL SYSTEMATIC UNCERTAINTIES Standard Model
Predictions (II)
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- 11 Use theory & simulations to estimate production rate and
model detector effects on probability to select events Systematic
uncertainty from approximation and inaccuracy in modeling of:
Theoretical calculation Modeling of strong interaction effects at
large distance Modeling of detector effects Number of collisions
registered Monte Carlo-based estimates
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- 12 Reduce systematic uncertainty by replacing MC distribution
with well understood data distribution similar to the process of
interest to avoid bias Stat error only Simulation Data e-e- e+e+
Data-driven techniques 101 (I)
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- 13 To produce a data-driven predictions, we can: 1- Reverse one
(few) signal selection(s) Avoid signal contamination X: Z X 2-
Count the number of events in the Y Z (Z X) sample 3- Use ratios to
compute mapping factors for the final prediction All events from a
dataset Event cut 1 Event cut 2 Event cut N-1 Event cut N Set of
selections defining signal (eg: monojet) Signal events Selections
to reverse Y: All other selections X Y Data model of the signal If
X is unbiased with respect to Y, then Y Z provides a good model for
Y X Data-driven techniques 101 (II)
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- Data-driven in monojet events 14 Jets observables present
similar distributions e e Met Z ee + 1-jet Z + 1-jet E T miss can
similarly be obtained after removing the two charged leptons with
corrections Must now use ratio to normalize and correct for shape
distortion
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- Results and interpretation 15
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- Various signal regions 16 We dont know the kinematic region in
which new physics will get revealed Expectations vary with models
Model-independence: dont select the kinematic region based on the
indications of a particular model Or do a kinematic scan Lowest
kinematic region determined by trigger requirement Statistics is a
limitation for data-driven estimate in high kinematic regions ETET
Jet 1 E T 0 120 220 350 500
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- Background systematics uncertainties When taking all effects
and all background into account: For the high stats low kinematic
region 17 QCD prediction uncertainty is not the dominant background
and is kept at a low level This estimate is a very conservative,
essentially only reflecting the small statistics of the sample used
to get the estimate. Recent studies suggest a factor of 3 to 5
smaller uncertainty on QCD effects
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- The Results (I) 18 Results are consistent with SM regardless of
the jet P T and E T miss selections Outstanding precision of
- Conclusion Dark matter is an empirical fact established by
astrophysics Most popular explanation: a new particle (WIMPs)
Escape detections => jets + E T miss events Background
predictions to monojet events typically suffer from large
systematic uncertainties Use data-driven background estimate ATLAS
performed the search and found no evidence for new physics in
monojet events Constraints are set on generic effective dark matter
scenario Complementary to direct and indirect dark matter searches
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- Back-up slides 29
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- LED: Model assumptions Limits assume extra dimensions are flat
and compactified on n-dimensional torus SM fields attached to a
3-brane o Brane deformation ignored Continuous KK-spectrum is
assumed, even for n=6 o Universal couplings of each modes o Assumed
the spectrum stops at M D Fundamental to effective scale
relationship: Prediction from minimal graviton emission model of
GRW Valid: E 7 M D
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- LED: Experimental signatures Direct graviton production in
association with partons or photons Graviton interaction with
detector suppressed by M Pl -2 Missing transverse energy Signature
at the LHC Monojet o More jets due to QCD radiation Monophoton
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- LED: Limits Typical efficiency for jets and Met selection: ~83%
Similar for Zvv, and ADD and general dark matter model Set 95% C.L.
limits on M D Truncation: quantify UV effects not modeled by L eff
o = 0% (n=2), 6% (n=3), 20% (n=4), 45% (n=5), 60% (n=6) model does
not make non-ambiguous predictions with SR4 o Limits of SR1 to SR3
are 35%, 15%, 5% worse, but less UV sensitive
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- Electroweak background estimate (II) Data-driven prediction for
Z +jets background is obtained from: Number of Z ll+jets events in
each control regions E T miss bin (N i cand,CR ) Ratio of signal
region to control region observable distribution The ratio mapping
factor accounts for lepton acceptance and efficiency different
cross section and branching ratios distortion of the measured
observable due to the charged lepton in the CR Similar exercise can
be done to estimate the reducible W+jets background Direct use of
the R jets measurement The ratio is also corrected for the
probability that the event survive the veto W+jets control region
events are also used to estimate Z +jets 33
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- QCD multijets background estimate 34 Sources of QCD
contribution: 2-jets and 3-jets events for which one of the jets is
lost (dominate) 3-jets events for which two jets are lost (smaller)
obtained from MC To estimate the 2-jets contribution: 1- Select
2/3-jets events with E T miss vector toward one jet 2- Extrapolate
this jet E T below energy threshold (loose a jet) 3- Background
prediction = area under the fit in the extrapolated region MC
correction 2-jets events Extrapolated region * Jet threshold
lowered to 15 GeV to verify the extrapolation
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- Results (IV) Preliminary studies with 10 fb -1 of 2012 8 TeV
data yields very similar results than the 7 TeV 2011 results.
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