This document provides an overview of dark matter searches using mono-X analyses, with a focus on new techniques. It begins with background on evidence for dark matter and the "WIMP miracle". It then discusses using effective field theories to model dark matter interactions without specifying an underlying theory. The document outlines various detection methods for dark matter including collider experiments looking for monojet, monophoton, mono-W/Z, and mono-b signatures. Example analyses from ATLAS and CMS applying these techniques are summarized. Limit plots are also shown comparing results to thermal relic targets and direct detection experiments.
An Improved Empirical Mode Decomposition Based On Particle Swarm OptimizationIJRES Journal
End effect is the main factor affecting the application of Empirical Mode Decomposition (EMD).
This paper presents an improve EMD for decomposing short signal. First, analyzing the frequency components
of signal to be decomposed, and construct the parameter equation with the amplitude and initial phase of signal
as unknowns. Second, employing particle swarm optimization (PSO) to estimate the unknown parameters, and
extending the inspected signal according to the obtained parameters. Thirdly, using EMD to decompose the
extended signal into a series of intrinsic mode functions (IMFs) and a residual. The IMFs of original signal are
extracted from these obtained IMFs. The correlation coefficients between the IMFs and the signal are calculated
to judge the pseudo-IMFs. The simulation result shows that the presented method is effective and extends the
application of EMD.
An Improved Empirical Mode Decomposition Based On Particle Swarm OptimizationIJRES Journal
End effect is the main factor affecting the application of Empirical Mode Decomposition (EMD).
This paper presents an improve EMD for decomposing short signal. First, analyzing the frequency components
of signal to be decomposed, and construct the parameter equation with the amplitude and initial phase of signal
as unknowns. Second, employing particle swarm optimization (PSO) to estimate the unknown parameters, and
extending the inspected signal according to the obtained parameters. Thirdly, using EMD to decompose the
extended signal into a series of intrinsic mode functions (IMFs) and a residual. The IMFs of original signal are
extracted from these obtained IMFs. The correlation coefficients between the IMFs and the signal are calculated
to judge the pseudo-IMFs. The simulation result shows that the presented method is effective and extends the
application of EMD.
A JOINT TIMING OFFSET AND CHANNEL ESTIMATION USING FRACTIONAL FOURIER TRANSFO...IJCNCJournal
This paper deals with symbol timing offset and channel estimation in OFDM (orthogonal frequency
division multiplexing) system in fast varying channel. Symbol timing offset (STO) estimation is a major task
in OFDM. Most of existing methods for estimating STO used cyclic prefix or training sequences. In this
paper, we consider a new system for STO estimation using constant amplitude zero autocorrelation
(CAZAC) sequences as pilot sequences in conjunction with fractional Fourier transform (FRFT). After STO
estimation is done, timing compensation is made. Thereafter, channel is estimated to well recover the
original transmitted signal. This method gives good results in terms of MSE in comparison with other
known techniques, it estimated well the channel and it is important for fast varying channel. MATLAB
Monte-Carlo simulations are used to evaluate the performance of the proposed estimator.
Optimization of Packet Length for MIMO systemsIJCNCJournal
In this article, a method to enhance the throughput for Multiple Input Multiple Output (MIMO) systems by optimizing packet length is proposed. Two adaptation algorithms are proposed. In the first algorithm, we use the Average Signal to Noise Ratio (ASNR) to choose the optimal packet length and Modulation and Coding Scheme (MCS) in order to maximize the throughput. In the second algorithm, packet length and MCS are adapted with respect to the Instantaneous received SNR (ISNR). This article concludes that the variable packet
length gives up to 1.8 dB gain with respect to the Fixed Packet Length (FPL).
Ensemble Empirical Mode Decomposition: An adaptive method for noise reduction IOSR Journals
Empirical mode decomposition (EMD), a data analysis technique, is used to denoise non-stationary
and non-linear processes. The method does not require any pre & post processing of signal and use of any
specified basis functions. But EMD suffers from a problem called mode mixing. So to overcome this problem a
new method known as Ensemble Empirical mode decomposition (EEMD) has been introduced. The presented
paper gives the detail of EEMD and its application in various fields. EEMD is a time–space analysis method, in
which the added white noise is averaged out with sufficient number of trials; and the averaging process results
in only the component of the signal (original data). EEMD is a truly noise-assisted data analysis (NADA)
method and represents a substantial improvement over the original EMD.
Analyse Performance of Fractional Fourier Transform on Timing and Carrier Fr...ijwmn
This paper deals with the performance of the use of fractional Fourier transform (FRFT) instead of
conventional Fourier transform (FFT) in either symbol timing offset (STO) and carrier frequency offset
(CFO) estimation. Orthogonal frequency division multiplexing is widely used in many systems due to
advantages of theses technique compared with mono-carrier systems. In spite of his advantages, OFDM
presents drawbacks such as sensitivity to timing and frequency offsets. Many techniques are used in the
literature to estimate these two parameters in order to compensate them (synchronization task). These
techniques used conventional Fourier transform. In this paper, we are interested in estimating STO and
CFO using fractional Fourier transform. Monte Carlo simulation demonstrates the performance of the use
of FRFT instead of FFT.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
A JOINT TIMING OFFSET AND CHANNEL ESTIMATION USING FRACTIONAL FOURIER TRANSFO...IJCNCJournal
This paper deals with symbol timing offset and channel estimation in OFDM (orthogonal frequency
division multiplexing) system in fast varying channel. Symbol timing offset (STO) estimation is a major task
in OFDM. Most of existing methods for estimating STO used cyclic prefix or training sequences. In this
paper, we consider a new system for STO estimation using constant amplitude zero autocorrelation
(CAZAC) sequences as pilot sequences in conjunction with fractional Fourier transform (FRFT). After STO
estimation is done, timing compensation is made. Thereafter, channel is estimated to well recover the
original transmitted signal. This method gives good results in terms of MSE in comparison with other
known techniques, it estimated well the channel and it is important for fast varying channel. MATLAB
Monte-Carlo simulations are used to evaluate the performance of the proposed estimator.
Optimization of Packet Length for MIMO systemsIJCNCJournal
In this article, a method to enhance the throughput for Multiple Input Multiple Output (MIMO) systems by optimizing packet length is proposed. Two adaptation algorithms are proposed. In the first algorithm, we use the Average Signal to Noise Ratio (ASNR) to choose the optimal packet length and Modulation and Coding Scheme (MCS) in order to maximize the throughput. In the second algorithm, packet length and MCS are adapted with respect to the Instantaneous received SNR (ISNR). This article concludes that the variable packet
length gives up to 1.8 dB gain with respect to the Fixed Packet Length (FPL).
Ensemble Empirical Mode Decomposition: An adaptive method for noise reduction IOSR Journals
Empirical mode decomposition (EMD), a data analysis technique, is used to denoise non-stationary
and non-linear processes. The method does not require any pre & post processing of signal and use of any
specified basis functions. But EMD suffers from a problem called mode mixing. So to overcome this problem a
new method known as Ensemble Empirical mode decomposition (EEMD) has been introduced. The presented
paper gives the detail of EEMD and its application in various fields. EEMD is a time–space analysis method, in
which the added white noise is averaged out with sufficient number of trials; and the averaging process results
in only the component of the signal (original data). EEMD is a truly noise-assisted data analysis (NADA)
method and represents a substantial improvement over the original EMD.
Analyse Performance of Fractional Fourier Transform on Timing and Carrier Fr...ijwmn
This paper deals with the performance of the use of fractional Fourier transform (FRFT) instead of
conventional Fourier transform (FFT) in either symbol timing offset (STO) and carrier frequency offset
(CFO) estimation. Orthogonal frequency division multiplexing is widely used in many systems due to
advantages of theses technique compared with mono-carrier systems. In spite of his advantages, OFDM
presents drawbacks such as sensitivity to timing and frequency offsets. Many techniques are used in the
literature to estimate these two parameters in order to compensate them (synchronization task). These
techniques used conventional Fourier transform. In this paper, we are interested in estimating STO and
CFO using fractional Fourier transform. Monte Carlo simulation demonstrates the performance of the use
of FRFT instead of FFT.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Computation of electromagnetic fields scattered from dielectric objects of un...Alexander Litvinenko
Computational tools for characterizing electromagnetic scattering from objects with uncertain shapes are needed in various applications ranging from remote sensing at microwave frequencies to Raman spectroscopy at optical frequencies. Often, such computational tools use the Monte Carlo (MC) method to sample a parametric space describing geometric uncertainties. For each sample, which corresponds to a realization of the geometry, a deterministic electromagnetic solver computes the scattered fields. However, for an accurate statistical characterization the number of MC samples has to be large. In this work, to address this challenge, the continuation multilevel Monte Carlo (\CMLMC) method is used together with a surface integral equation solver.
The \CMLMC method optimally balances statistical errors due to sampling of
the parametric space, and numerical errors due to the discretization of the geometry using a hierarchy of discretizations, from coarse to fine.
The number of realizations of finer discretizations can be kept low, with most samples
computed on coarser discretizations to minimize computational cost.
Consequently, the total execution time is significantly reduced, in comparison to the standard MC scheme.
ANALYTICAL PERFORMANCE EVALUATION OF A MIMO FSO COMMUNICATION SYSTEM WITH DIR...optljjournal
MIMO FSO correspondence is examined as of late to build up a hearty correspondence connects within the sight of atmospheric turbulence. In this paper an analytical approach is developed to assess the impact of atmospheric turbulence on BER performance of a MIMO FSO communication system with Q-ary Pulse Position Modulation (QPPM). Examination is exhibited to discover flag to clamor proportion at the yield of an immediate location collector with optical power modulator under strong turbulent condition which is modeled as gamma-gamma distribution. The outcomes demonstrate that the BER performance is emphatically debased because of the impact of atmospheric turbulence. In any case, the execution can be enhanced by expanding the quantity of transmitters, beneficiaries and request of Q in PPM. Results demonstrate that the FSO MIMO framework with M=8, N=4 Q=4 gives the 22 dB improvement at BER of 10-9 .
Computation of electromagnetic fields scattered from dielectric objects of un...Alexander Litvinenko
We develop fast and efficient stochastic methods for characterizing scattering
from objects of uncertain shapes. This is highly needed in the
fields of electromagnetics, optics, and photonics.
The continuation multilevel Monte Carlo (CMLMC) method is
used together with a surface integral equation solver. The
CMLMC method optimally balances statistical errors due to
sampling of the parametric space, and numerical errors due
to the discretization of the geometry using a hierarchy of
discretizations, from coarse to fine. The number of realizations
of finer discretizations can be kept low, with most samples
computed on coarser discretizations to minimize computational
work. Consequently, the total execution time is significantly
reduced, in comparison to the standard MC scheme.
This Analog Communication Lab Manual is prepared for JNTU, Hyderabad (in a general way to be utilized for the maximum institutions) for R18 regulation.
Design Method of Directional GenLOT with Trend Vanishing MomentsShogo Muramatsu
Proc. of Proc. of Asia Pacific Signal and Information Proc. Assoc. Annual Summit and Conf. (APSIPA ASC), pp.692-701, Biopolis, Singapore, Dec. 14 – 17, 2010
Multi carrier equalization by restoration of redundanc y (merry) for adaptive...IJNSA Journal
This paper proposes a new blind adaptive channel shortening approach for multi-carrier systems. The
performance of the discrete Fourier transform-DMT (DFT-DMT) system is investigated with the proposed
DST-DMT system over the standard carrier serving area (CSA) loop1. Enhanced bit rates demonstrated
and less complexity also involved by the simulation of the DST-DMT system.
ANALYTICAL PERFORMANCE EVALUATION OF A MIMO FSO COMMUNICATION SYSTEM WITH DIR...optljjournal
MIMO FSO correspondence is examined as of late to build up a hearty correspondence connects within the
sight of atmospheric turbulence. In this paper an analytical approach is developed to assess the impact of
atmospheric turbulence on BER performance of a MIMO FSO communication system with Q-ary Pulse
Position Modulation (QPPM). Examination is exhibited to discover flag to clamor proportion at the yield
of an immediate location collector with optical power modulator under strong turbulent condition which is
modeled as gamma-gamma distribution. The outcomes demonstrate that the BER performance is
emphatically debased because of the impact of atmospheric turbulence
Ensemble Empirical Mode Decomposition: An adaptive method for noise reductionIOSR Journals
Abstract:Empirical mode decomposition (EMD), a data analysis technique, is used to denoise non-stationary and non-linear processes. The method does not require any pre & post processing of signal and use of any specified basis functions. But EMD suffers from a problem called mode mixing. So to overcome this problem a new method known as Ensemble Empirical mode decomposition (EEMD) has been introduced. The presented paper gives the detail of EEMD and its application in various fields. EEMD is a time–space analysis method, in which the added white noise is averaged out with sufficient number of trials; and the averaging process results in only the component of the signal (original data). EEMD is a truly noise-assisted data analysis (NADA) method and represents a substantial improvement over the original EMD. Keywords –Data analysis, Empirical mode decomposition, intrinsic mode function, mode mixing, NADA,
Empirical mode decomposition and normal shrink tresholding for speech denoisingijitjournal
In this paper a signal denoising scheme based on Empirical mode decomposition (EMD) is presented. the
noisy signal is decomposed in an adaptive manner by the EMD algorithm which allows to obtain intrinsic
oscillatory called Intrinsic mode functions (IMFs)component by a process called sifting process. The basic
principle of the method is to decompose a speech signal corrupted by additive white Gaussian random
noise into segments each frame is categorised as either signal-dominant or noise-dominant then
reconstruct the signal with IMFs signal dominant frame previously filtered or thresholded.It is shown, on
the basis of intensivesimulations that EMD improves the signal to noise ratio and address the problem of
signal degradation. The denoising method is applied to real signal with different noise levels and the
results compared to Winner and universal threshold of DONOHO and JOHNSTONE [11] with soft and
hard tresholding.Theeffect of level noise value on the performances of the proposed denoising is analysed.
Empirical mode decomposition and normal shrink tresholding for speech denoising
JamesDPearce_MonoX
1. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
“Dark matter searches” with a focus on new
techniques (Mono-X)
WIN2013: Natal, Brazil
James D Pearce,
On behalf of the ATLAS and CMS collaborations
Sept 16, 2013
1 / 28
2. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
OUTLINE
1. Dark Matter Background
Evidence for Dark Matter
The “WIMP Miracle”
2. Effective Field Theories
3. Detection Methods
4. Mono-X Analyses
Monojet (ATLAS)
Monophoton (CMS)
Mono-W/Z (ATLAS + CMS)
Mono-b
5. Summary
6. Auxiliary Material
2 / 28
3. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
EVIDENCE FOR DARK MATTER (I)
Galactic Rotation Curves Strong Gravitational Lensing
Galactic rotation curves show
stars orbit at the same speeds
This implies mass density of
galaxies is uniform.
Image of Abell 1689 cluster as
observed by the hubble
telescope
The mass of galaxies is not
enough to account for the
strong gravitational lensing.
3 / 28
4. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
EVIDENCE FOR DARK MATTER (II)
Weak Gravitational Lensing Cosmic Microwave Background
Two galaxy clusters colliding.
The pink shows the x-ray
emissions.
Blue shows unseen mass as
measured with weak
gravitational lensing
techniques.
Anisotropies in the CMB are
due to acoustic oscillations in
the early universe.
Angular scales of the
oscillations reveal the different
effects of baryonic matter and
DM. 4 / 28
5. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
RELIC ABUNDANCE AND THE “WIMP MIRACLE”
1. DM and SM particles are in
thermal (chemical) equilibrium.
2. Universe expands and cools;
DM production drops
exponentially (∼ e−mχ/T).
3. Energy drops below DM
production threshold; DM
abundance remains constant
(“Freeze out”).
We are left with a relic abundance of
DM:
Ωχ ∝ 1
σv ∼
m2
χ
gχ4
5 / 28
6. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
WHAT WE KNOW ABOUT DARK MATTER
1. It’s neutral under electric charge, since it does not produce photons,
2. It’s stable, or at least has a lifetime on cosmological scales,
3. It’s non-baryonic, to preserve the success of ΛCDM,
4. It has a relic abundance consistent with weak scale mass and
interactions.
These seem to all point us to some sort of weakly interacting massive
particle (WIMP). We can use an EFT to model what we know about DM,
without resorting to any one specific UV complete theory (eg. SUSY,
LED, etc.)
6 / 28
7. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
FROM UV COMPLETE TO EFT (I)
UV complete Theory Effective Theory
By Taylor expanding the SM-DM propagator around the momentum
transfer and only keeping the leading order we get an effective coupling
constant:
1
Q2
tr−M2 = − 1
M2 1 +
Q2
tr
M2 + O
Q4
tr
M4 ≈ − 1
M2
This approximation is only valid if Q2
tr M2 otherwise all other terms in
the expansion (UV complete theory) must be considered.
7 / 28
8. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
FROM UV COMPLETE TO EFT (II)
Once the mediator has been “integrated out” we no longer talk about the
parameter M, instead we replace it with M∗, which parameterizes the
energy scale of the EFT. M∗ is the most important parameter of the
theory, it’s related to the mediator mass and couplings, and tells us
where the EFT approach breaks down:
M∗ = M/
√
gχgq, where gχ and gq are the couplings of the mediator
to the DM and quark fields.
4-momentum conservation requires mχ < M/2
Perturbation theory requires gχgq < (4π)2
Therefore our EFT is valid for mχ < 2πM∗
This EFT language allows us to relate different experimental signatures
in a model-independent way. As we’ll see the relic abundance, direct
detection signal, and collider predictions depend only on M∗.
8 / 28
9. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
FROM UV COMPLETE TO EFT (III)
Name Operator Coefficient
D1 ¯χχ¯qq mq/M3
∗
D2 ¯χγ5χ¯qq imq/M3
∗
D3 ¯χχ¯qγ5q imq/M3
∗
D4 ¯χγ5χ¯qγ5q mq/M3
∗
D5 ¯χγµχ¯qγµq 1/M2
∗
D6 ¯χγµγ5χ¯qγµq 1/M2
∗
D7 ¯χγµχ¯qγµγ5q 1/M2
∗
D8 ¯χγµγ5χ¯qγµγ5q 1/M2
∗
D9 ¯χσµνχ¯qσµνq 1/M2
∗
D10 ¯χσµνγ5χ¯qσαβq i/M2
∗
D11 ¯χχGµνGµν αs/4M3
∗
D12 ¯χγ5χGµνGµν iαs/4M3
∗
D13 ¯χχGµν
˜Gµν iαs/4M3
∗
D14 ¯χγ5χGµν
˜Gµν αs/4M3
∗
arXiv:1008.1783
The theory is then
characterized by an effective
Lagrangian Leff :
Leff = ciOi
Where ci ∼ 1
M∗
d−4 and Oi is an
effective operator which is
some Lorentz invariant
combination of the SM and
DM (χ) fields.
Place limits on a
representative set: D1 (scalar),
D5 (vector), D8 (axial-vector),
D9 (tensor) and D11 (couples
to gluons)
9 / 28
11. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
MONOJET ANALYSIS (ATLAS/CMS)
Main Backgrounds:
Z(→ νν)+ jet(s) (50-70%)
W(→ linvν) + jet(s) (46-29%)
Z(→ linvlinv) + jet(s) (4-0%)
EW background estimate (ATLAS):
Nest
SR = (NData
CR −N
bkg
CR )×(1−FEW)×TF
where 1 − FEW =
NMC
CR
All EW
NMC
CR
and TF =
NMC
SR
NMC
CR
MC EW background estimate (CMS):
Z+ jets, W+ jets, t¯t and single top:
MadGraph → Phythia6: Z2Star tune
with CTEQ6L1 pdf
CMS-PAS-EXO-12-048 ATLAS-CONF-2012-147
11 / 28
12. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
MONOJET ANALYSIS (CMS)
[GeV]T
miss
E
200 300 400 500 600 700 800 900 1000
Events/25GeV
1
10
2
10
3
10
4
10
5
10
6
10
7
10 νν→Z
νl→W
tt
t
QCD
-
l
+
l→Z
= 3δ= 2 TeV,D
ADD M
= 1 GeVχ
= 892 GeV, MΛDM
= 2 TeVU
Λ=1.7,
U
Unparticles d
Data
CMS Preliminary
= 8 TeVs
-1
L dt = 19.5 fb∫
[GeV]T
miss
E
200 300 400 500 600 700 800 900 1000
Data/MC
0
0.5
1
1.5
2
Selection
Trigger: Emiss
T > 80 GeV
Lead jet: pT > 110 GeV,
|η| < 2.4
lepton veto: e, µ, τ
∆φ(jet1, jet2) < 2.5
jet veto: Njet ≤ 2
Scan in Emiss
T
Blue dashed line indicates
hypothetical DM signal
12 / 28
13. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
ENERGY SCALE LIMITS
[GeV]WIMP mass m
2
10
3
10
[GeV]
*
SuppressionscaleM
100
150
200
250
300
350
400
450
500 , SR3, 90%CLOperator D11
)exp
2±1±Expected limit (
)theory
1±Observed limit (
Thermal relic
PreliminaryATLAS
=8 TeVs
-1
Ldt = 10.5 fb
not valid
effective theory
]2
[GeV/cχM
1 10
2
10
3
10
[GeV]Λ
300
1000
CMS 2012 Vector
CMS 2011 Vector
CMS Preliminary
= 8 TeVs
-1
L dt = 19.5 fb∫
Green line indicates the M∗ values at which WIMPs of a given mass
would result in the required relic abundance.
M∗ limits above the thermal relic line means exclusion or negative
interference or additional annihilation (e.g. to leptons)
The light-grey region indicates where the EFT breaks down.
13 / 28
15. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
WIMP ANNIHILATION LIMITS
[ GeV ]WIMP mass m
1 10 2
10 3
10
/s]3
qq[cmv>forAnnihilationrate<
-29
10
-28
10
-27
10
-26
10
-25
10
-24
10
-23
10
-22
10
-21
10
-20
10
-19
10
Thermal relic value
)bb
Majorana
)( Fermi-LAT dSphs (×2
Dirac
)(qD5: q
Dirac
)(qD8: q
theory
-1
ATLAS , 95%CL-1
= 7 TeV, 4.7 fbs
Comparison with FERMI-LAT
is possible through our EFT
The results can also be
interpreted in terms of limits
on WIMPs annihilating to
light quarks
All limits shown here assume
100% branching fractions of
WIMPs annihilating to quarks
Below 10 GeV for D5 and 70
GeV for D8 the ATLAS limits
are below the values needed
for WIMPs to make up the
DM relic abundance
15 / 28
16. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
MONOPHOTON ANALYSIS (CMS)
Main Backgrounds:
Zγ → νν + γ (60%)
Wγ → linvν + γ, di-γ and
γ+ jet (5%)
Fake photons (20%)
Background Estimates
All backgrounds estimated with
MC
Z/γ(NLO), di-γ and γ+ jet ←
Pythia6 with CTEQ6L1
Wγ(NLO) ← MadGraph5
CMS-EXO-11-096 CERN-PH-EP-2012-209 16 / 28
19. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
MONO-W/Z ANALYSES (ATLAS/CMS)
Two possible diagrams lead to
interference:
1. ξ = −1: signal enhanced
leads to stronger signal
than monojet!
2. ξ = +1: signal suppressed
Two different strategies:
1. ATLAS: look for a single fat-jet
with internal structure
(mono-W/Z)
Same backgrounds as monojet
analysis
Similar data-driven
background estimate
2. CMS: look for single lepton
(mono-W)
W → lν, t¯t, single top,
Drell-Yan, diboson
Background estimated from
MC
CMS-EXO-12-060 ATLAS-CONF-2013-073
19 / 28
20. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
MONO-W/Z A.K.A. MONO-FATJET (ATLAS)
[GeV]jetm
50 60 70 80 90 100 110 120
Events/10GeV
0
5
10
15
20
25
30
35
40
45
Data
)+jetννZ(
)+jetτ/µW/Z(e/
Top
Diboson
uncertainty
D5(u=d) x20
D5(u=-d) x0.2
ATLAS Preliminary
= 8 TeVs
-1
L dt = 20.3 fb∫
> 500 GeV
miss
TSR: E
Selection:
Trigger: Emiss
T > 80 GeV
Fat jet: Cambridge-Aachen
algorithm, R = 1.2, first two
sub-jets balanced (
√
y > 0.4),
pT > 250 GeV, |η| < 1.2,
mjet = 50 − 120 GeV
Veto leptons (e, µ) and photons
t¯t supression: veto if
>= 2 AntiKt4 jets with
∆R(jetFat, jetAntiKt4) > 0.9 OR
∆φ(Emiss
T , jet) < 0.4 for any
AntiKt4 jets.
SR: Emiss
T > {350, 500} GeV
20 / 28
23. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
MONO-b
b
g b
X
X
Motivation:
D1 is proportional to the initial
quark mass (D1 ∼
mq
M3
∗
)
By approximate QCD flavour
symmetry the outgoing quark
will be a b
Analysis for 2012 data is
currently underway (ATLAS)
Despite the kinematic and PDF
suppression for producing third
generation quarks
improvement on limits is up to
3 orders of magnitude!
100
101
102
103
mX [GeV]
10−46
10−45
10−44
10−43
10−42
10−41
10−40
10−39
10−38
10−37
10−36
10−35
σn[cm2
]
ATLAS 7 TeV, 4.7 fb−1
XENON 100
Limits from mono-b search
14 TeV, 300 fb−1
, pileup 50
14 TeV, 3000 fb−1
, pileup 140
33 TeV, 3000 fb−1
, pileup 140
arXiv:1307.7834
23 / 28
24. INTRO BACKGROUND EFT’S DETECTION MONOJET MONOPHOTON MONO-W/Z MONO-b SUMMARY
SUMMARY
WIMPs are well motivated by what we know about Dark Matter and
the observed relic abundance.
EFT’s allow us to search for WIMPs in a model-independent way as
well as compare results from different experiments and signatures.
Mono-X searches at the LHC are competitive and complementary to
direct and indirect detection experiments.
24 / 28