SUS-17-001

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$Id:SUS-17-001.tex4471872018-02-2113:12:15Zschoef$

SUS-17-001

# Search for top squarks and dark matter particles in opposite-charge dilepton
final states at $\sqrt{s}=13\TeV$

###### Abstract

A search for new physics is presented in final states with two oppositely
charged leptons (electrons or muons), jets identified as originating from
quarks, and missing transverse momentum (). The search uses proton-proton
collision data at $\sqrt{s}=13\TeV$ amounting to 35.9of integrated luminosity
collected using the CMS detector in 2016. Hypothetical signal events are
efficiently separated from the dominant background with requirements on and
transverse mass variables. No significant deviation is observed from the
expected background. Exclusion limits are set in the context of simplified
supersymmetric models with pair-produced top squarks. For top squarks,
decaying exclusively to a top quark and a neutralino, exclusion limits are
placed at 95% confidence level on the mass of the lightest top squark up to
800and on the lightest neutralino up to 360. These results, combined with
searches in the single-lepton and all-jet final states, raise the exclusion
limits up to 1050for the lightest top squark and up to 500for the lightest
neutralino. For top squarks undergoing a cascade decay through charginos and
sleptons, the mass limits reach up to 1300for top squarks and up to 800for the
lightest neutralino. The results are also interpreted in a simplified model
with a dark matter (DM) particle coupled to the top quark through a scalar or
pseudoscalar mediator. For light DM, mediator masses up to 100 (50)are
excluded for scalar (pseudoscalar) mediators. The result for the scalar
mediator achieves some of the most stringent limits to date in this model.

##  0.1 Introduction

The top quark couples to the Higgs boson more strongly than other fermions
because of its large mass. As a result, it plays a prominent role in the so-
called hierarchy problem [1, 2] of the standard model (SM) of particle
physics, since its dominant contribution in the loop corrections to the Higgs
boson mass exposes the theory to higher energy scales present in nature.
Supersymmetry (SUSY) [3, 4, 5, 6, 7, 8, 9, 10] is a well-motivated theory
beyond the SM that provides a solution to the hierarchy problem. In addition,
in $R$-parity conserving SUSY [11], the lightest SUSY particle (LSP) is stable
and can be a viable dark matter (DM) candidate, assuming it is neutral and
weakly interacting. Presently, the lighter SUSY particles may have masses in
the range and therefore could be produced in proton-proton ($\Pp\Pp$)
collisions at the CERN LHC. The scalar partners of the right- and left-handed
top quarks, the top squarks $\PSQt_{R}$ and $\PSQt_{L}$, can be among these
particles. These two states mix into the mass eigenstates $\PSQtDo$ and
$\PSQtDt$. The lighter one, $\PSQtDo$, could be within the LHC energy reach to
provide a natural solution to the hierarchy problem [12], which strongly
motivates searches for top squark production.

In this paper, we present a search for top squark pair production in a final
state with two leptons (electrons or muons), hadronic jets identified as
originating from quarks, and significant transverse momentum imbalance. The
search is performed using data from $\Pp\Pp$ collisions collected with the CMS
detector at the LHC during 2016 at a center-of-mass energy of 13,
corresponding to an integrated luminosity of 35.9. We employ an efficient
background reduction strategy that suppresses the large background from SM
$\ttbar$ events by several orders of magnitude through use of dedicated
transverse-mass variables [13, 14]. The predicted SM backgrounds in the
various search regions are validated in data control samples orthogonal in
selection to the signal regions in data.

The search is interpreted in simplified models [15, 16, 17] describing the
strong production of pairs of top squarks. We consider different decay modes,
following the naming convention in Ref. [18]. In the T2 model (Fig. 1, upper
left), each top squark decays into a top quark and the lightest neutralino ,
which is the LSP. Alternatively, we consider the T2 model (Fig. 1, upper
right), where both top squarks decay into a quark and an intermediate chargino
() which further decays into a boson and an LSP. In both models, leptonic
decays of the two W bosons provide a low-background final state with two
oppositely charged leptons, jets from quarks, and significant transverse
momentum imbalance due to undetected LSPs and neutrinos. The obtained results
are then combined with results from searches in the same dataset in the
single-lepton and all-jet final states [19, 20]. Finally, we consider for the
first time the $\text{T8}\PQb\PQb\ell\ell\PGn\PGn$ model (Fig. 1, lower left),
where both top squarks decay via charginos to sleptons and, subsequently, to
neutralinos leading to a final state with the same particle content as in the
T2 model. Here, sleptons are the SUSY partners of leptons, and the branching
fraction of the chargino is taken to be identical for all three flavors. In
this way, and contrary to the T2 and T2 models, the branching fraction to a
pair of oppositely charged leptons is 100% when decays to $\tau$ leptons are
included. Searches based on T2 and T2 models using 8 and 13$\Pp\Pp$ collision
data recorded before 2016 were published by the CMS [21, 22, 23] and the ATLAS
[24, 25, 26, 27, 28] experiments, with a $\PSQtDo$ mass excluded up to 700in
the T2 model.

As an alternative to the SUSY hypothesis, we also interpret the search in a
simplified model where a DM candidate $\PGc$ interacts with SM particles
through a scalar ($\phi$) or pseudoscalar () mediator [29, 30, 31, 32, 33].
Assuming minimal flavor violation [34, 35], the DM particles are dominantly
produced in pairs in association with a pair (Fig. 1, lower right). This model
predicts therefore the same final state as considered in SUSY phenomenology,
with the transverse momentum imbalance provided by the DM particles. Prior
searches for such direct DM production via scalar and pseudoscalar mediators
have been carried out at the LHC with 8data [36, 37], and more recently with
13data [38, 39, 40].

Figure 1: Diagrams for simplified SUSY models and for direct DM production:
strong production of top squark pairs $\PSQtDo\PASQt_{1}$, where each top
squark decays to a top quark and a (T2 model, upper left), or where each top
squark decays into a quark and an intermediate that further decays into a
boson and a (T2 model, upper right), or to a neutrino and an intermediate
slepton $\PGn\widetilde{\ell}^{\pm}$ that yield $\PGn\PSGczDo$ and an
$\ell^{\pm}$ from the virtual slepton decay
($\text{T8}\PQb\PQb\ell\ell\PGn\PGn$ model, lower left). Direct DM production
through scalar or pseudoscalar mediators in association with top quarks is
shown at the lower right.

##  0.2 The CMS detector

The central feature of the CMS detector is a superconducting solenoid of 6m
internal diameter, providing a magnetic field of 3.8T. A silicon pixel and a
silicon strip tracker, a lead tungstate crystal electromagnetic calorimeter
(ECAL), and a brass and scintillator hadron calorimeter, each comprising a
barrel and two end sections reside within the solenoid volume. Muons are
measured in gas-ionization detectors embedded in the magnet steel flux-return
yoke outside the solenoid. Extensive forward calorimetry complements the
coverage provided by the barrel and endcap detectors that improve the
measurement of the imbalance in transverse momentum. A more detailed
description of the CMS detector, together with a definition of the coordinate
system and the kinematic variables, can be found in Ref. [41].

##  0.3 Event samples

During data taking, events are selected for offline analysis by different
trigger algorithms that require the presence of one or two leptons (electrons
or muons). For the dilepton triggers, which accept the majority of events with
two leptons, the thresholds are 23on the leading lepton and 12(electron) or
8(muon) on the subleading lepton . Efficiencies of the dilepton triggers are
measured in data events that are selected independently of the leptons, based
on the presence of jets and requirements on the transverse momentum imbalance
(). Typical values range from 95 to 99%, depending on the momenta and
pseudorapidities ($\eta$) of the two leptons and are applied as scale factors
to simulated events.

The top quark antiquark pair production () and $t$-channel single top quark
background samples are simulated using the v2 [42, 43] event generator, and
are normalized to next-to-next-to-leading order (NNLO) cross sections [44, 45,
46, 47, 48, 49, 50, 44]. Events with single top quarks produced in association
with bosons ($\PQt\PW$) are simulated using v1 [51] and normalized to the NNLO
cross section. Drell–Yan and $\ttbar\cPZ$ events are generated with v2.2.2
[52] at leading order (LO) and next-to-leading order (NLO), respectively, and
their cross sections are computed at NNLO [53] and NLO [54], respectively. The
processes $\ttbar\PW$, $\PQt\Z\PQq$, $\ttbar\gamma$, and the triboson
processes are generated using at NLO, while $\PQt\PW\Z$ is generated at LO.
The diboson and $\ttbar\PH$ processes are generated using v2 at NLO. These
processes are normalized to the most precise available cross section,
corresponding to NLO accuracy in most cases.

Generated events are interfaced with v8.205 [55] using the CUETP8M1 tune [56,
57] or, for and $\ttbar\PH$ backgrounds, the CUETP8M2 tune, to simulate parton
showering, hadronization, and the underlying event. The NNPDF3.0 [58] parton
distribution functions (PDFs) at NLO and LO are used consistently with NLO and
LO event generators, respectively. The events are subsequently processed with
a -based simulation model [59] of the CMS detector.

Signal samples including top squark pairs are generated with at LO precision,
interfaced with . For the T2 and T2 models, the top squark mass is varied from
150 to 1200and the mass of the LSP is scanned from 1 to 650. The mass of the
chargino in the T2 model is assumed to be equal to the mean of the masses of
the top squark and the lightest neutralino. For the
$\text{T8}\PQb\PQb\ell\ell\PGn\PGn$ model, we vary the top squark mass between
200 to 1400and the mass of the LSP from 1 to 1000. The masses of the
intermediate chargino and slepton states in the
$\text{T8}\PQb\PQb\ell\ell\PGn\PGn$ model are chosen as follows: for the
chargino mass we assume $m_{\PSGcpDo}=(m_{\PSQtDo}+m_{\PSGczDo})/2$, while the
slepton masses are chosen by the three values $x=0.95$, 0.50, 0.05 in
$m_{\tilde{\ell}}=x\,(m_{\PSGcpDo}-m_{\PSGczDo})+m_{\PSGczDo}$. The signal
production cross sections are normalized to NLO plus next-to-leading
logarithmic (NLL) accuracy [60]. Simulation of the detector response is
performed using the CMS fast detector simulation [61].

For the simplified model of ${\rm t\bar{t}}$+DM production, is used at LO to
generate events with at most one additional parton from initial-state
radiation. We follow the recommendations from Ref. [33]: the DM particle is
taken to be a Dirac fermion, while the spin-0 mediator can have either scalar
or pseudoscalar couplings to both quarks and DM, ignoring mixing with the SM
Higgs boson in the scalar case. Yukawa couplings proportional to
$g_{\PQq}m_{\PQq}$ are assumed between the mediator and the quarks of mass
$m_{\PQq}$, where the coupling strength $g_{\PQq}$ is taken to be 1 and
assumed to be flavor universal. The coupling strength $g_{\mathrm{DM}}$ of the
mediator to the DM particles is also set to 1. The aforementioned -based
detector simulation is used for this signal.

All simulated samples include the simulation of so-called pileup from the
presence of additional $\Pp\Pp$ collisions in simultaneous or preceding bunch
crossings, and are reweighted according to the distribution of the true number
of interactions in the main collision’s bunch crossing.

##  0.4 Object selection

Offline event reconstruction uses the CMS particle-flow (PF) algorithm [62],
yielding a consistent set of electron [63], muon [64], charged and neutral
hadron, and photon candidates. These particles are defined with respect to the
primary $\Pp\Pp$ interaction vertex, chosen to have the largest value of
summed physics-object $\pt^{2}$, where these physics objects are reconstructed
by a jet finding algorithm [65, 66] applied to all charged tracks associated
with the vertex.

Electron candidates are reconstructed using tracking and ECAL information, by
combining the clusters of energy deposits in the ECAL with Gaussian sum filter
tracks [63]. The electron identification is performed using shower shape
variables, track-cluster matching variables, and track quality variables. The
selection is optimized to identify electrons from the decay of SM bosons with
a 70% efficiency while rejecting electron candidates originating from jets. To
reject electrons originating from photon conversion inside the detector,
electrons are required to have all possible hits in the innermost tracker
layers and to be incompatible with any conversion-like secondary vertices.
Identification of muon candidates is performed using the quality of the
geometrical matching between the measurements of the tracker and the muon
system [64].

All lepton candidates are required to satisfy $\pt>25(20)\GeV$ for the leading
(subleading) lepton and $\abs{\eta}<2.4$. Consistency of the lepton track with
the selected primary vertex is enforced by vetoing lepton candidates whose
tracks have a significance of the transverse impact parameter above 4. Here,
the impact parameter is the minimum three-dimensional distance between the
lepton trajectory and the primary vertex. Its significance is defined as the
ratio of the impact parameter to its uncertainty. The longitudinal
displacement from the primary collision vertex must also be less than
$0.1\cm$.

Lepton candidates are required to be isolated. For each candidate a cone with
radius $\Delta
R=\sqrt{\smash[b]{(\Delta\eta)}^{2}+\smash[b]{(\Delta\phi)}^{2}}=0.3$ (where
$\phi$ is azimuthal angle in radians) around the track direction at the event
vertex is constructed. The relative isolation ($I_{\textrm{rel, 0.3}}$) is
defined as the scalar sum, normalized to the lepton , of photons and neutral
and charged hadrons reconstructed by the PF algorithm within this cone. In
order to reduce dependence on the number of pileup interactions, charged
hadron candidates are included in the sum only if they are consistent with
originating from the selected primary vertex in the event. The contribution of
neutral particles from pileup events is estimated following the method
described in Ref. [63], and subtracted from the isolation sum. For a lepton
candidate to be isolated, $I_{\textrm{rel, 0.3}}$ has to be smaller than 0.12.

Jets are clustered from PF candidates using the anti-algorithm [65] with a
distance parameter of $R=0.4$. The influence of pileup is mitigated using the
charged hadron subtraction technique, by subtracting the energy of charged
hadrons associated to vertices other than the primary vertex. Jet momenta are
then further calibrated, accounting for deposits from neutral pileup particles
and the imperfect detector response [67], and quality criteria are applied for
jets with $\pt>30\GeV$ and $\abs{\eta}<2.4$. To arbitrate between jets and
leptons, jets that are found within a cone with radius $\Delta R=0.4$ around
any isolated lepton are removed from the set of selected jets. The scalar sum
of the jets that pass this selection is denoted by $\HT$.

The vector is defined as the negative vector sum of all PF candidates
reconstructed in an event and is corrected to account for the jet energy
corrections. Its magnitude is denoted by . Events with possible contributions
from beam halo processes or anomalous noise in the calorimeter are rejected
using dedicated filters [68].

A multivariate tagging discriminator CSVv2 [69] is used to identify jets that
originate from a quark (b jets). The chosen “medium” working point has a
mistag rate of approximately 1% for light flavor jets and a corresponding
tagging efficiency of 55% to 65% depending on jet transverse momentum and
pseudorapidity [69].

Scale factors are applied in simulation to take into account the differences
of lepton reconstruction, identification and isolation as well as tagging
efficiencies in data and simulation. Typical corrections are less than 1% per
lepton and less than 10% per b-tagged jet.

##  0.5 Search strategy

We select events containing a pair of leptons with opposite charge, and we
require the invariant mass of the lepton pair to be greater than 20, to
suppress backgrounds with misidentified or nonprompt leptons from the
hadronization of (heavy flavor) jets in multijet events. Events with
additional leptons with $\pt>15\GeV$ and satisfying a looser isolation
criterion of $I_{\text{rel, 0.3}}<0.4$ are vetoed. In case of a same-flavor
(SF) lepton pair, we suppress contributions from SM Drell–Yan production with
a requirement on the dilepton mass, $\abs{m_{\PZ}-m(\ell\ell)}>15\GeV$, where
$m(\ell\ell)$ is the invariant mass of the dilepton system and $m_{\PZ}$ is
the mass of the boson. To further suppress this and other vector boson
backgrounds, we require the number of jets ($N_{\text{jets}}$) to be at least
two and, among them, the number of jets ($N_{\text{\PQb jets}}$) to be at
least one. After additionally requiring $\ptmiss>80\GeV$, a small background
remains from events with vector bosons and highly energetic jets that are
severely mismeasured. We further reduce this background by defining
$S=\ptmiss/\sqrt{\HT}$ and requiring $S>5\GeV^{1/2}$ and, furthermore, by
placing a requirement on the angular separation of and the momenta of the
leading ($j_{1}$) and subleading ($j_{2}$) jets in the azimuthal plane. The
selection above is summarized in Table 0.5 and defines the event sample, which
is dominated by events with top quark pairs that decay to a dilepton final
state.

Overview of the preselection requirements. ll Leptons & = 2 ( or $\mu$),
oppositely charged
$m(\ell\ell)$ $>$20
$\abs{m_{\Z}-m(\ell\ell)}$ $>$15, same flavor only
$N_{\text{jets}}$ $\geq$2
$N_{\text{\PQb jets}}$ $\geq$1
$\ptmiss$ $>$80
$S$$>$51/2
$\cos\Delta\phi(\ptmiss,j_{1})$ $<$0.80
$\cos\Delta\phi(\ptmiss,j_{2})$ $<$0.96

The main search variable in this analysis is

$M_{\text{T2}}(\ell\ell)=\min_{\ptvecmiss{}^{1}+\ptvecmiss{}^{2}=\ptvecmiss}\left(\max\left[M_{\text{T}}(\ptvec^{\text{vis}1},\ptvecmiss{}^{1}),M_{\text{T}}(\ptvec^{\text{vis}2},\ptvecmiss{}^{2})\right]\right),$
(1)

where the choice $\ptvec^{\text{vis}1,2}=\ptvec^{\ell 1,2}$ corresponds to the
definition introduced in Ref. [70] and used in Ref. [22]. The calculation of
$M_{\text{T2}}(\ell\ell)$ is performed through the algorithm discussed in Ref.
[71] assuming vanishing mass for the undetected particles. Under the
hypothesis of a well-reconstructed dileptonic or $\PW\PW$ event, the
minimization in Eq. 1 encompasses the correct neutrino momenta, and thus
$M_{\text{T2}}(\ell\ell)$ has an endpoint at the parent particle’s mass [14],
here $m_{\text{W}}$. When the azimuthal angle of falls within the smaller of
the two opening angles defined by the leptons in the transverse plane, it
follows that $M_{\text{T2}}(\ell\ell)$ vanishes because the minimization
procedure will find a partitioning where $\ptvecmiss{}^{1,2}$ and
$\ptvec^{\ell 1,2}$ are both parallel.

The key feature of this analysis is that the presence of additional invisible
particles, , the LSP $\PSGczDo$ or the DM particle $\PGc$, breaks the
correlation between the and the lepton transverse momenta that define the
$M_{\text{T2}}(\ell\ell)$ endpoint. Hence, we expect the events predicted by
the diagrams depicted in Fig. 1 to populate the tails of this distribution.
The distribution of $M_{\text{T2}}(\ell\ell)$ in simulation after the
preselection is shown in Fig. 2 (left) for $M_{\text{T2}}(\ell\ell)>100\GeV$
and including a T2 signal with a mass configuration with $m_{\PSQt}=750\GeV$
and $m_{\PSGczDo}=1\GeV$, as well as a more compressed signal scenario with
$m_{\PSQt}=600\GeV$ and $m_{\PSGczDo}=300\GeV$.

We refine the analysis by using two more observables to define signal regions,
$M_{\text{T2}}(\PQb\ell\PQb\ell)$ and . For $M_{\text{T2}}(\PQb\ell\PQb\ell)$,
we choose [70] $\ptvec^{\text{vis}1,2}=\ptvec^{\text{b}1,2}+\ptvec^{\ell
1,2}$, which requires two b-tagged jets. If only one tagged jet is found in
the event, the jet with the highest that does not pass the tagging selection
is taken instead. The ambiguity when pairing leptons with jets for
$M_{\text{T2}}(\PQb\ell\PQb\ell)$ is resolved by selecting the configuration
which minimizes the maximum invariant mass of the two lepton-jet pairs.
Similar to the procedure to obtain $M_{\text{T2}}(\ell\ell)$, we break up into
two parts and pair them with $\ptvec^{\text{vis}1,2}$ in order to define
$M_{\text{T}}$, and then compute $M_{\text{T2}}(\PQb\ell\PQb\ell)$ analogously
to Eq. (1). For dileptonic events, $M_{\text{T2}}(\PQb\ell\PQb\ell)$ has an
endpoint at the top quark mass. After a tight threshold of
$M_{\text{T2}}(\ell\ell)>100\GeV$, both $M_{\text{T2}}(\PQb\ell\PQb\ell)$ and
still exhibit significant discrimination power. This is shown in Fig. 2
(middle) for $M_{\text{T2}}(\PQb\ell\PQb\ell)$ and Fig. 2 (right) for .

Figure 2: Distributions of $M_{\text{T2}}(\ell\ell)$ (left),
$M_{\text{T2}}(\PQb\ell\PQb\ell)$ (center), and (right) in simulation after
preselection and requiring $M_{\text{T2}}(\ell\ell)>100\GeV$. A T2 signal is
shown with masses $m_{\PSQt}=750\GeV$ and $m_{\PSGczDo}=1\GeV$, as well as a
more compressed signal with $m_{\PSQt}=600\GeV$ and $m_{\PSGczDo}=300\GeV$.

Based on sensitivity studies for a wide range of signal scenarios, the signal
regions listed in Table 0.5 are chosen. These regions are further split
depending on the flavor of the leptons into different- and same-flavor signal
regions. There is no overlap among the signal regions themselves or with
background enriched regions (control regions) used in the following.

Definition of the signal regions. The regions are further split into
different- and same-flavor regions.  ccccc $M_{\text{T2}}(\PQb\ell\PQb\ell)$
() & $\ptmiss$ () $100<M_{\text{T2}}(\ell\ell)<140\GeV$
$140<M_{\text{T2}}(\ell\ell)<240\GeV$ $M_{\text{T2}}(\ell\ell)>240\GeV$
0–100 80–200 SR0 SR6  SR12
$>$200 SR1 SR7
100–200 80–200 SR2 SR8
$>$200 SR3 SR9
$>$200  80–200 SR4 SR10
$>$200 SR5 SR11

##  0.6 Background predictions

The major backgrounds from SM processes in the search regions after the event
selection are single top quark and top quark pair events with either severely
mismeasured or misidentified leptons. Smaller contributions come from the same
processes in association with a , , or an boson ($\ttbar\cPZ$, $\ttbar\PW$,
$\ttbar\PH$, $\PQt\PQq\cPZ$) and Drell–Yan and multiboson production
($\PW\PW$, $\PW\PZ$, $\PZ\PZ$, $\PW\PW\PW$, $\PW\PW\PZ$, $\PW\PZ\PZ$, and
$\PZ\PZ\PZ$). In the following, we discuss the estimation of these different
background components.

###  0.6.1 Top quark background

Events containing single or pair-produced top quarks populate low regions in
the distributions of the three analysis variables $M_{\text{T2}}(\ell\ell)$,
$M_{\text{T2}}(\PQb\ell\PQb\ell)$, and if the momenta in the events are well
measured. Studies based on simulation show two main sources of top quark
background in the signal regions. First, a severe mismeasurement of jet energy
caused by the loss of photons and neutral hadrons showering in masked channels
of the calorimeters can induce large mismeasurement and promote an otherwise
well-measured event to the signal regions. Additionally, neutrinos with high
within jets cause mismeasurements of the jet . A control region requiring
same-flavor leptons satisfying $\abs{m(\ell\ell)-m_{\PZ}}<15\GeV$ is used to
constrain any mismodeling of this rare effect by comparing the tail between
data and simulation. It is found that the simulation predicts well such
mismeasurements, and no sign of unaccounted effects in the measurement is
observed. Furthermore, the modeling of the tail of the analysis variable
distributions is validated in control regions that invert the requirement on
one or more of the following variables: with no requirement on $S$,
$N_{\text{\PQb jets}}$, and $N_{\text{jets}}$. As an example, Fig. 3 (left)
shows the $M_{\text{T2}}(\ell\ell)$ distribution in the different-flavor
channel with $N_{\text{\PQb jets}}\geq 1$, $N_{\text{jets}}\geq 2$,
$\ptmiss<80\GeV$, and no requirement on $S$. No significant sign of
mismodeling is found in any of the control regions over at least three orders
of magnitude in event yields. The uncertainties from experimental effects, as
described in Section 0.7, are shown with a hatched band.

Second, an electron or muon may fail the identification requirements, or the
event may have a $\PGt$ lepton produced in a boson decay. If there is a
nonprompt lepton from the hadronization of a quark or a charged hadron
misidentified as a lepton selected in the same event, the reconstructed value
for $M_{\text{T2}}(\ell\ell)$ is not bound by the mass. To validate the
modeling of this contribution, we select events with one additional lepton
satisfying loose isolation requirements on top of the selection in Table 0.5.
In order to mimic the lost prompt lepton background, we recompute
$M_{\text{T2}}(\ell\ell)$ by combining each of the isolated leptons with the
extra lepton in both data and simulation. Since the transverse momentum
balance is not significantly changed by lepton misidentification, the
observable is not modified. The resulting $M_{\text{T2}}(\ell\ell)$
distribution is shown in Fig. 3 (right) and serves as a validation of the
modeling of the lost lepton background. We observe overall good agreement
between simulation and data, indicating that simulation describes such
backgrounds well.

Figure 3: Left: distribution of $M_{\text{T2}}(\ell\ell)$ in a control region
enriched in events and defined by $N_{\text{jets}}\geq 2$, $N_{\text{\PQb
jets}}\geq 1$, and $\ptmiss<80\GeV$. The hatched band shows the uncertainties
from experimental effects, as described in Section 0.7. Right: distribution of
$M_{\text{T2}}(\ell\ell)$ after swapping an isolated lepton with an additional
non-isolated lepton, as described in the text. For both plots, simulated
yields are normalized to data using the yields in the
$M_{\text{T2}}(\ell\ell)<100\GeV$ region.

Top quark backgrounds are split into three categories in the signal regions
and uncertainties related to them are assigned based on the agreement of data
and simulation in the studies above. The first category consists of events
which are promoted to the $M_{\text{T2}}(\ell\ell)$ tail due to Gaussian jet
energy mismeasurements within approximately twice the jet energy resolution.
It comprises 25–55% of the top quark background, depending on the signal
region, and we assign a 15% uncertainty in the yield of this fraction. The
second category, 40–50% of the total top quark background yield, contains
events with jets with more severe energy mismeasurements. A 30% uncertainty,
based on studies in control regions, is assigned to the yield of events.
Events containing misidentified electrons or muons constitute 1–25% of the top
quark background, and based on studies on the modeling of the
misidentification rate, a 50% uncertainty is assigned. Finally, we proceed to
predict the background from single top and top quark pair production by
normalizing simulated distributions to the number of events in a data region
defined by the selection in Table 0.5 and an additional requirement of
$M_{\text{T2}}(\ell\ell)<100\GeV$. In this way, experimental uncertainties
affecting the overall normalization are largely reduced.

###  0.6.2 Top quark + X background

Top quarks produced in association with a boson ($\ttbar\cPZ$, $\ttbar\PW$,
$\ttbar\PH$, $\PQt\PQq\cPZ$) form an irreducible background in decay channels
where the bosons decay to leptons or neutrinos. Among these, the $\ttbar\cPZ$
background, with $\Z\to\PGn\PAGn$ providing extra genuine , is the dominant
one. The overall normalization of this contribution is measured in the decay
mode

$\ttbar\cPZ\to(\PQt\to\cPqb\ell^{\pm}\cPgn)(\PQt\to\PQb\cmsSymbolFace{jj})(\PZ\to\ell^{\pm}\ell^{\mp})$

in control regions with exactly three leptons ($\mu\mu\mu$, $\mu\mu\Pe$,
$\mu\Pe\Pe$ and $\Pe\Pe\Pe$), where the leading, subleading, and trailing
lepton transverse momentum are required to satisfy thresholds of 40, 20, and
10, respectively. All pairs of same-flavor leptons with opposite charge are
required to satisfy $\abs{m(\ell\ell)-m_{\PZ}<10\GeV}$. Five control regions
requiring different $N_{\text{jets}}$ and $N_{\text{\PQb jets}}$ combinations
are defined. The simulated number of $\ttbar\cPZ$ events is fitted to the
number of observed events in these regions. The normalizations of other
background components are allowed to vary within their uncertainties, and the
values returned by the fit are consistent with the initial ones. The number of
events in the control regions in simulation and data is shown in Fig. 4 before
(left) and after (right) the fit. Including systematic uncertainties, the fit
yields a scale factor of $1.09\pm 0.15$, which is then used to normalize the
$\ttbar\cPZ$ background in the signal regions. The scale factor uncertainty is
fully accounted for in the background prediction.

Figure 4: Expected and observed yields in the five $\ttbar\cPZ$ control
regions, which are defined by different requirements on the number of
reconstructed jets and jets, before (left) and after the fit (right). The
hatched band contains all uncertainties discussed in the text.

Furthermore, we constrain a potential mismodeling of the
$M_{\text{T2}}(\ell\ell)$ and distributions for the $\ttbar\cPZ$ (with
$\Z\to\PGn\PAGn$) background in a data control sample dominated by
$\ttbar\gamma$ events, using the photon as a proxy for the boson and adding
its momentum to the . To mitigate the difference between the massive boson and
the massless photon, the simulated photon momentum is reweighted to match the
distribution of the boson momentum. After this procedure, we find good
agreement between the simulated $\ttbar\gamma$ and $\ttbar\cPZ$ distributions.
Repeating the exercise on data, we find agreement within the statistical
precision and assign a conservative additional uncertainty of 20%.

###  0.6.3 Drell–Yan and multiboson backgrounds

Drell–Yan events constitute only a small background component after the
analysis selection. In order to measure the residual contribution, we select
dilepton events where we invert the boson veto, the jet requirements, and the
angular separation requirements on jets and . From simulation, this selection
is expected to retain about 85% Drell–Yan events, while the subleading
contribution comes from multiboson events. For each same-flavor signal region,
we define a corresponding control region with the selections above and the
signal region requirements on $M_{\text{T2}}(\ell\ell)$,
$M_{\text{T2}}(\PQb\ell\PQb\ell)$, and .

Including systematic uncertainties, we perform a likelihood fit of the
predicted yields in these control regions and extract simulation-to-data scale
factors that amount to $1.31\pm 0.19$ for the Drell–Yan background and
$1.19\pm 0.17$ for the multiboson background component. The
$M_{\text{T2}}(\ell\ell)$ distribution with this selection is presented in
Fig. 5 (left) after applying the overall scale factors. The fit procedure is
sensitive to the Drell–Yan and multiboson contributions separately, because
their $M_{\text{T2}}(\PQb\ell\PQb\ell)$ and distributions differ
substantially, as shown in Fig. 5 (middle) and (right), respectively. Good
agreement between the prediction and observation of both Drell–Yan and
multiboson contributions is observed, and the result in all 13 control regions
is shown in Fig. 6.

Figure 5: Distributions of $M_{\text{T2}}(\ell\ell)$ (left),
$M_{\text{T2}}(\PQb\ell\PQb\ell)$ (center), and (right) for SF events falling
within the boson mass window ($\abs{m(\ell\ell)-m_{\PZ}}<15\GeV$), with at
least two jets and $N_{\text{\PQb jets}}=0$, $\ptmiss>80\GeV$, and
$M_{\text{T2}}(\ell\ell)>100\GeV$. The hatched band shows the uncertainties
from experimental effects, as described in Section 0.7. Figure 6: Event yields
in the 13 Drell–Yan and multiboson control regions for events with SF leptons
falling within the boson mass window ($\abs{m(\ell\ell)-m_{\PZ}}<15\GeV$) and
$N_{\text{\PQb jets}}=0$, after renormalizing with the scale factors obtained
from the fit procedure described in the text. The hatched band shows the
uncertainties from the fit including the uncertainties from the experimental
effects, as described in Section 0.7.

##  0.7 Systematic uncertainties and signal acceptance

Several experimental uncertainties affect the various signal and background
yield estimations. Efficiencies of the dilepton triggers, as mentioned
previously, range from 95 to 99%. The uncertainties in these efficiencies are
about 1%. Offline lepton reconstruction and selection efficiencies are
measured using $\PZ\to\ell\ell$ events in bins of lepton and pseudorapidity,
and as a function of the total hadronic activity in the vicinity of the
lepton. These measurements are performed separately in data and in simulation.
Typical efficiency values range from 70 to 80%, and scale factors are used to
correct the differences between data and simulation. The uncertainties in
these scale factors are less than 3% per lepton in most of the search and
control regions.

Uncertainties in the event yields resulting from the calibration of the jet
energy scale are estimated by shifting the jet momenta in the simulation up
and down by one standard deviation of the jet energy corrections. Depending on
the jet and $\eta$, the resulting uncertainty in the simulated yields from the
jet energy scale is typically 1–5%, except in the lowest regions in
$M_{\text{T2}}(\ell\ell)$ where it can be as high as 12%. In addition, the
energy scale of deposits from soft particles that are not clustered in jets
are varied within their uncertainties and the resulting uncertainty reaches
3.5%, with an increase up to 25% in the lowest $M_{\text{T2}}(\ell\ell)$
region. The tagging efficiency in the simulation is corrected using scale
factors determined from data [69], and uncertainties are propagated to all
simulated events. These contribute an uncertainty of about 1–6% in the
predicted yields depending on the transverse momentum and pseudorapidity of
the b-tagged jet.

The effect of all the experimental uncertainties described above is evaluated
for each of the simulated processes in all signal regions, and is considered
correlated across the analysis bins and simulated processes.

Further experimental uncertainties arise from the normalization of the single
top and top quark pair, Drell–Yan, and multiboson backgrounds in their
respective control regions, for which uncertainties in the scale factors
derived in Section 0.6 are taken into account. Finally, the uncertainty in the
integrated luminosity is 2.5% [72].

Several additional systematic uncertainties affect the modeling in simulation
of the various processes. Firstly, all simulated samples are reweighted
according to the distribution of the true number of interactions at each bunch
crossing. The uncertainty in the total inelastic $\Pp\Pp$ cross section leads
to uncertainties of 1–6% in the expected yields.

For the and $\ttbar\cPZ$ backgrounds, we determine the event yield changes
resulting from varying the renormalization and factorization scales by a
factor of two, while keeping the overall normalization from the control region
in data constant. We assign as uncertainty the envelope of the considered
yield variations, treated uncorrelated between the background processes.
Uncertainties in the PDFs can have a further effect on the simulated
$M_{\text{T2}}(\ell\ell)$ shape. We determine the change of acceptance in the
signal regions using the PDF variations and assign the envelope of these
variations—between 1 and 6%—as a correlated uncertainty [73].

Measurements of the top quark in events at $\sqrt{s}=8$ and 13show a potential
mismodeling in simulation [74, 75]. To evaluate the impact of this effect, we
reweight the top quark in the simulated sample to match that in data, keeping
the overall normalization constant. The difference relative to the unweighted
sample is assigned as a systematic uncertainty, which typically contributes an
uncertainty of about 1–2% in the predicted yields.

For the small contribution from top quark pair production in association with
a or a Higgs boson, we take an uncertainty of 20% in the cross section based
on the variations of the renormalization and factorization scales and the
PDFs.

Finally, the statistical uncertainties due to the finite number of simulated
events are treated as fully uncorrelated. These maximally amount to 27% on the
rare backgrounds, with little impact on the analysis sensitivity.

A summary of the systematic uncertainties in the background prediction is
presented in Table 0.7.

Most of the sources of systematic uncertainties in the background estimates
affect the prediction of the signal as well, and these are evaluated
separately for each mass configuration of the considered simplified models. We
further estimate the effect of missing higher-order corrections for the signal
acceptance by varying the renormalization and factorization scales [76, 77]
and find that uncertainties are between 1 and 19%. The modeling of initial-
state radiation (ISR) is relevant for the SUSY signal simulation in cases
where the mass difference between the top squark and the LSP is small. The ISR
reweighting is obtained in an inclusive data control region requiring an
opposite-charge electron-muon pair and exactly two b jets, and is based on the
number of ISR jets ($N_{J}^{\mathrm{ISR}}$) not tagged as b jets, so as to
make the jet multiplicity agree with data. The reweighting procedure is
applied to SUSY Monte Carlo events and factors vary between 0.92 and 0.51 for
$N_{J}^{\mathrm{ISR}}$ between 1 and 6. We take one half of the deviation from
unity as the systematic uncertainty in these reweighting factors, correlated
across search regions. It is generally found to have a small effect, but can
reach 30% for compressed mass configurations. An uncertainty from potential
differences of the modeling of in the fast simulation of the CMS detector with
respect to data is evaluated by comparing the reconstructed with the obtained
using generator-level information. This uncertainty ranges up to 20% and only
affects the considered SUSY signal samples. For these samples, the scale
factors and uncertainties for the tagging efficiency of jets and leptons as
well as the uncertainty on the modeling of pileup are evaluated separately.
For DM signal models, the uncertainty in the signal acceptance due to
variations of the PDFs is considered, while for the SUSY signal models, this
uncertainty was found to be redundant with the ISR uncertainty and thus not
included.

Relative systematic uncertainties in the background yields in the signal
regions. Where given, ranges represent the minimal and maximal changes in
yield across all signal regions. lw Source of systematic uncertainty Change in
signal region yields (%)
Trigger efficiency 1
Lepton scale factors 1,5
Jet energy scale 1,12
Modeling of unclustered energy 1,25
tagging 1,6
Top quark background normalization 3,20
$\ttbar\cPZ$ background normalization 1,14
Multiboson background normalization 1,8
Drell-Yan background normalization 1,7
Integrated luminosity 2.5
Pileup modeling 1,6
Factorization/renormalization scales 1,19
PDFs 1,6
Top quark modeling 1,2
$\ttbar X$ (excl. $\ttbar\cPZ$) background normalization 1,6
Simulated sample event count 2,27

##  0.8 Results

No significant deviation from the SM prediction is observed in any of the
signal regions. Good agreement between the predicted and observed
$M_{\text{T2}}(\ell\ell)$, $M_{\text{T2}}(\PQb\ell\PQb\ell)$, and
distributions is observed, as shown in Figs. 7 and 8, respectively. A summary
of the predicted and observed event yields for each signal region is shown in
Figs. 9 and 10 and in Table 0.8.

Figure 7: Distributions of $M_{\text{T2}}(\ell\ell)$ for observed events in
the $\mu\mu$ (left), $\Pe\Pe$ (middle), and $\Pe\mu$ (right) channels compared
to the predicted SM backgrounds for the selection defined in Table 0.5. The
hatched band shows the uncertainties discussed in the text.

Figure 8: Distributions of $M_{\text{T2}}(\ell\ell)$ (left),
$M_{\text{T2}}(\PQb\ell\PQb\ell)$ (middle), and (right) for all lepton flavors
for the selection defined in Table 0.5. Additionally,
$M_{\text{T2}}(\ell\ell)>100\GeV$ is required for the
$M_{\text{T2}}(\PQb\ell\PQb\ell)$ and distributions. The hatched band shows
the uncertainties discussed in the text.

Figure 9: Predicted backgrounds and observed yields in the $\Pe\Pe$ and
$\mu\mu$ search regions (left) and the $\Pe\mu$ search regions (right). The
hatched band shows the uncertainties discussed in the text.  Figure 10:
Predicted backgrounds and observed yields in the $\Pe\Pe$, $\mu\mu$, and
$\Pe\mu$ search regions combined. The hatched band shows the uncertainties
discussed in the text.

Total expected background and event yields in data in each of the signal
regions for same-flavor ($\Pep\Pem/\PGmp\PGmm$), different-flavor
($\Pepm\PGm^{\mp}$), and all channels combined with all the systematic
uncertainties included as described in Section 0.7. lzrc@ zrc@ zr Signal
region Same flavor Different flavor All
Expected Observed Expected Observed Expected Observed
0 131,30 112 139,32 141 271,61 253
1 4.1,1.1 7 4.0,1.1 6 8.1,2.0 13
2 60 ,13 69 70 ,17 67 130,29 136
3 4.8,1.2 1 3.9,1.0 5 8.7,2.0 6
4 0.5,0.2 0 0.7,0.2 1 1.2,0.4 1
5 1.9,0.5 2 2.1,0.5 1 4.0,0.8 3
6 1.1,0.6 2 0.5,0.2 1 1.5,0.7 3
7 0.6,0.3 2 0.3,0.2 0 0.8,0.3 2
8 2.1,0.7 1 0.8,0.2 1 2.9,0.7 2
9 1.6,0.4 1 0.9,0.3 0 2.5,0.5 1
10 0.3,0.1 0 0.1,0.1 0 0.4,0.2 0
11 1.7,0.4 2 1.2,0.3 1 2.9,0.6 3
12 0.7,0.3 1 0.5,0.2 0 1.1,0.4 1

We interpret the results in the context of simplified SUSY models and combine
with complementary results from the searches in the all-hadronic [20] and the
single-lepton [19] final states for the T2 and T2 models. Moreover, we also
interpret the results in a model with DM particle pair production via a scalar
or pseudoscalar mediator.

To perform the statistical interpretations, a likelihood function is formed
containing Poisson probability functions for all data regions, where the same-
flavor and different-flavor signal regions are considered separately. The
control regions for the $\ttbar\cPZ$ background and for the Drell–Yan and
multiboson backgrounds, as depicted in Figs. 4 and 6, respectively, are
included as well. The correlations of the uncertainties are taken into account
as described in Section 0.7. A profile likelihood ratio in the asymptotic
approximation [78] is used as the test statistic. Upper limits on the
production cross section are then calculated at 95% confidence level (CL)
using the asymptotic $\text{CL}_{\text{s}}$ criterion [79, 80].

The SUSY interpretations are given in the $m_{\PSQtDo}$–$m_{\PSGczDo}$ plane
in Figs. 11 and 12. The color on the z axis indicates the 95% CL upper limit
on the cross section times the square of the branching fraction at each point
in the $m_{\PSQtDo}$–$m_{\PSGczDo}$ plane. The area below the thick black
curve represents the observed exclusion region at 95% CL assuming 100%
branching fraction, while the dashed red lines indicate the expected limit at
95% CL and the region containing 68% of the distribution of limits expected
under the background-only hypothesis. The thin black lines show the effect of
the theoretical uncertainties in the signal cross section. In the T2 model we
exclude mass configurations with $m_{\PSGczDo}$ up to 360and $m_{\PSQtDo}$ up
to 800, assuming that the top quarks are unpolarized. Because this choice may
have a significant impact on the kinematic properties of the final state
particles [81], we also check that for purely right-handed polarization, the
limit increases by about 50in both $m_{\PSQtDo}$ and $m_{\PSGczDo}$, while for
purely left-handed polarization, the limit decreases by about 50in
$m_{\PSQtDo}$ and by 70in $m_{\PSGczDo}$.

The results for the T2 and $\text{T8}\PQb\PQb\ell\ell\PGn\PGn$ models are
shown in Figs. 11 (right) and 12. We exclude mass configurations with
$m_{\PSGczDo}$ up to 320and $m_{\PSQtDo}$ up to 750in the T2 model. The
sensitivity in the $\text{T8}\PQb\PQb\ell\ell\PGn\PGn$ model strongly depends
on the intermediate slepton mass and is largest when $x=0.95$ in
$m_{\tilde{\ell}}=x\,(m_{\PSGcpDo}-m_{\PSGczDo})+m_{\PSGczDo}$. In this case,
excluded masses reach up to 800for $m_{\PSGczDo}$ and 1300for $m_{\PSQtDo}$.
These numbers reduce to 660for $m_{\PSGczDo}$ and 1200for $m_{\PSQtDo}$ when
$x=0.5$ and to 50for $m_{\PSGczDo}$ and 1000for $m_{\PSQtDo}$ when $x=0.05$.

Figure 11: Expected and observed limits for the T2 model with
$\PSQtDo\to\PQt\PSGczDo$ decays (left) and for the T2 model with
$\PSQtDo\to\PQb\PSGcpDo\to\PQb\PWp\PSGczDo$ decays (right) in the
$m_{\PSQtDo}$–$m_{\PSGczDo}$ mass plane. The color indicates the 95% CL upper
limit on the cross section times the square of the branching fraction at each
point in the plane. The area below the thick black curve represents the
observed exclusion region at 95% CL assuming 100% branching fraction, while
the dashed red lines indicate the expected limits at 95% CL and the region
containing 68% of the distribution of limits expected under the background-
only hypothesis. The thin black lines show the effect of the theoretical
uncertainties in the signal cross section.

Figure 12: Expected and observed limits for the
$\text{T8}\PQb\PQb\ell\ell\PGn\PGn$ model with
$\PSQtDo\to\PQb\PSGcpDo\to\PQb\PGn\tilde{\ell}\to\PQb\PGn\ell\PSGczDo$ decays
in the $m_{\PSQtDo}$–$m_{\PSGczDo}$ mass plane for three different mass
configurations defined by
$m_{\tilde{\ell}}=x\,(m_{\PSGcpDo}-m_{\PSGczDo})+m_{\PSGczDo}$ with $x=0.05$
(upper left), $x=0.5$ (upper right), and $x=0.95$ (lower). The description of
curves is the same as in the caption of Fig. 11.

Besides the dilepton search described in this paper, searches for direct top
squark pair production were also performed in final states with a single
lepton [19] and without leptons [20]. The signal and control regions for these
two searches and the dilepton search are mutually exclusive. A statistical
combination of the results of the three searches is performed in the context
of the T2 and T2 scenarios of top squark pair production, taking into account
correlations in both signal and expected background yields in the different
analyses. Figure 13 shows the combination of the results of the three searches
for direct top squark pair production for the T2 model with
$\PSQtDo\to\PQt\PSGczDo$ decays. The combined result excludes a top squark
mass of 1050for a massless LSP, and an LSP mass of 500for a top squark mass of
900. The combination is driven primarily by the all-jet search, except in the
region of small mass splitting between the top squark and the LSP where
searches in the zero- and one-lepton channels have similar sensitivity. Figure
14 shows the equivalent limits for direct top squark pair production for the
T2 model with $\PSQtDo\to\PQb\PSGcpDo$, $\PSGcpDo\to\PWp\PSGczDo$ decays. The
combined result for this scenario excludes a top squark mass of 1000for a
massless LSP and an LSP mass of 450for a top squark mass of 900. The
combination extends the sensitivity to both top squark and LSP masses by about
50compared to the most sensitive individual result coming from the one-lepton
channel.

Figure 13: Expected and observed limits for the T2 model with
$\PSQtDo\to\PQt\PSGczDo$ decays in the $m_{\PSQtDo}$–$m_{\PSGczDo}$ mass plane
combining the dilepton final state with the single-lepton [19] and the all-
hadronic [20] final states as described in the text. The color indicates the
95% CL upper limit on the cross section times the square of the branching
fraction at each point in the plane. The area below the thick black curve
represents the observed exclusion region at 95% CL assuming 100% branching
fraction, while the dashed red lines indicate the expected limits at 95% CL
and the region containing 68% of the distribution of limits expected under the
background-only hypothesis. The thin black lines show the effect of the
theoretical uncertainties in the signal cross section. The green short-dashed,
blue dotted, and long-short-dashed orange curves show the expected individual
limits for the all-hadronic, single-lepton, and dilepton analyses,
respectively. The whited out area on the diagonal corresponds to
configurations where the mass difference between and is very close to the top
quark mass. In this region the signal acceptance strongly depends on the mass
and is therefore hard to model.

Figure 14: Expected and observed limits for the T2 model with
$\PSQtDo\to\PQb\PSGcpDo\to\PQb\PWp\PSGczDo$ decays in the
$m_{\PSQtDo}$–$m_{\PSGczDo}$ mass plane combining the dilepton final state
with the all-hadronic [20] and the single-lepton [19] final states as
described in the text. The mass of the chargino is chosen to be
$(m_{\PSQtDo}+m_{\PSGczDo})/2$. The description of curves is the same as in
the caption of Fig. 13.

Limits on the production of DM particle pairs in association with top quark
pairs via a scalar or pseudoscalar mediator are listed in Table 0.8, assuming
$g_{\PQq}=g_{\mathrm{DM}}=1$. The results are presented as ratios
$\mu=\sigma/\sigma_{\text{theory}}$ of the 95% CL expected and observed upper
limits on the cross section $\sigma$ with respect to the simplified model
cross section expectations $\sigma_{\rm theory}$. Results are shown for
different DM particle and mediator masses, and for both scalar and
pseudoscalar mediators. Figure 15 shows expected and observed limits as a
function of the mediator mass for DM particles $\PGc$ with a mass of 1. We
exclude scalar mediators with masses up to 100and pseudoscalar mediators with
masses up to 50.

Ratios $\mu=\sigma/\sigma_{\text{theory}}$ of the 95% CL expected and observed
limits to simplified model expectations for different DM particle masses and
mediator masses and for scalar ($\phi$) and pseudoscalar ($\mathrm{a}$)
mediators under the assumption $g_{\PQq}=g_{\mathrm{DM}}=1$. The uncertainties
reflect the 68% band of the expected limits. rrcccccc@ cc $m_{\PGc}$
$m_{\phi/\Pa}$ Scalar Pseudoscalar
() () $\sigma_{\text{theory}}$ (fb) Expected Observed $\sigma_{\text{theory}}$
(fb) Expected Observed
1 10 21357 $0.54^{+0.25}_{-0.16}$ 0.70 451 $1.01^{+0.49}_{-0.32}$ 0.81
1 20 10954 $0.56^{+0.26}_{-0.17}$ 0.53 411 $1.02^{+0.49}_{-0.32}$ 0.81
1 50 3086 $0.67^{+0.32}_{-0.21}$ 0.59 308 $1.14^{+0.55}_{-0.36}$ 0.91
1 100 720 $1.04^{+0.48}_{-0.32}$ 0.90 193 $1.33^{+0.65}_{-0.42}$ 1.08
1 200 101 $2.30^{+1.11}_{-0.72}$ 1.87 87.8 $2.02^{+1.01}_{-0.64}$ 1.64
1 300 30.5 $4.8^{+2.3}_{-1.5}$ 3.8 39.5 $3.7^{+1.8}_{-1.2}$ 2.9
1 500 4.95 $21.6^{+10.9}_{-6.9}$ 17.4 5.14 $21.0^{+10.4}_{-6.7}$ 16.9
10 10 101 $18.8^{+8.8}_{-5.8}$ 16.6 15.2 $19.3^{+9.3}_{-6.1}$ 15.3
10 15 127 $17.0^{+8.0}_{-5.2}$ 13.8 19.5 $15.8^{+7.6}_{-5.0}$ 12.7
10 50 3096 $0.72^{+0.33}_{-0.22}$ 0.69 310 $1.08^{+0.52}_{-0.34}$ 0.86
10 100 742 $1.03^{+0.48}_{-0.32}$ 0.84 197 $1.25^{+0.61}_{-0.39}$ 0.98
50 10 2.10 $125^{+61}_{-39}$ 102 2.38 $72^{+36}_{-23}$ 58
50 50 2.57 $104^{+50}_{-33}$ 84 2.95 $62^{+30}_{-19}$ 49
50 95 7.24 $52^{+25}_{-16}$ 43 10.8 $20.3^{+10.0}_{-6.4}$ 16.2
50 200 100 $2.32^{+1.14}_{-0.73}$ 1.86 84.8 $2.05^{+1.02}_{-0.64}$ 1.64
50 300 30.5 $4.7^{+2.3}_{-1.5}$ 3.8 38.5 $3.7^{+1.9}_{-1.2}$ 3.0

Figure 15: The 95% CL expected (dashed line) and observed limits (solid line)
on $\mu=\sigma/\sigma_{\text{theory}}$ for a fermionic DM particle with
$m_{\PGc}=1\GeV$ assuming different scalar (left) and pseudoscalar (right)
mediator masses. The green and yellow bands represent the regions containing
68 and 95%, respectively, of the distribution of limits expected under the
background-only hypothesis. The horizontal red line indicates $\mu=1$. The
mediator couplings are set to $g_{\PQq}=g_{\mathrm{DM}}=1$. The gray hashed
band around the observed limit corresponds to a 30% theory uncertainty in the
inclusive signal cross section.

Expected and observed event yields, summed over all lepton flavors, in the
aggregate signal regions defined by the selection requirements in the table.
crcyr Signal region $\ptmiss$ () $M_{\text{T2}}(\ell\ell)$ () Expected
Observed
A0 $>$200 100–140 20.8, 4.4 22
A1 $>$200 140–240 6.2,1.0 6
A2 $>$80 $>$240 1.1,0.4 1

Covariance (left) and correlation matrix (right) for the background prediction
in the aggregate signal regions described in Table 0.8. cccc Covariance
A0 A1 A2
A0 13.3 1.8 0.5
A1 0.9 0.2
A2 0.1
cccc Correlation
A0 A1 A2
A0 1 0.51 0.38
A1 1 0.49
A2 1

In order to facilitate the reinterpretation of these results, we construct
three aggregate signal regions. The preselection in Table 0.5 is applied, but
in contrast to the main analysis, there is no separation of events according
to lepton flavor. Regions A0 and A1 are defined as $100\leq
M_{\text{T2}}(\ell\ell)<140\GeV$ and $140\leq
M_{\text{T2}}(\ell\ell)<240\GeV$, with an additional requirement of
$\ptmiss>200\GeV$ for both. Region A2 is defined by
$M_{\text{T2}}(\ell\ell)>240\GeV$ and $\ptmiss>80\GeV$. Expected and observed
yields in the aggregate regions are shown in Table 0.8. The covariance and
correlation matrices [82] for the background predictions in the aggregate
regions are given in Table 0.8.

##  0.9 Summary

A search was presented for top squark pair production and dark matter in final
states with two leptons, jets, and large missing transverse momentum in data
corresponding to an integrated luminosity of 35.9in $\Pp\Pp$ collisions
collected at a center-of-mass energy of 13in the CMS detector at the LHC. An
efficient background reduction using dedicated kinematic variables was
achieved, suppressing by several orders of magnitude the large background from
standard model dilepton $\ttbar$ events. With no evidence observed for a
deviation from the expected background from the standard model, results were
interpreted in several simplified models for supersymmetric top squark pair
production as well as through the production of a spin-0 dark matter mediator
in association with a $\ttbar$ pair.

In the T2 model with $\PSQtDo\to\PQt\PSGczDo$ decays, $\PSQtDo$ masses
$<$800and $\PSGczDo$ masses $<$360are excluded. In the T2 model with
$\PSQtDo\to\PQb\PSGcpDo\to\PQb\PWp\PSGczDo$ decays, $\PSQtDo$ masses $<$750and
$\PSGczDo$ masses $<$320are excluded, assuming the chargino mass to be the
mean of the $\PSQtDo$ and the $\PSGczDo$ masses. In the newly considered
$\text{T8}\PQb\PQb\ell\ell\PGn\PGn$ model with decays
$\PSQtDo\to\PQb\PSGcpDo\to\PQb\PGn\tilde{\ell}\to\PQb\PGn\ell\PSGczDo$, and
therefore 100% branching to dilepton final states, the sensitivity depends on
the intermediate particle masses. With the chargino mass again taken as the
mean of the $\PSQtDo$ and the $\PSGczDo$ masses, the strongest exclusion is
obtained if the slepton mass is close to the chargino mass. In this case,
excluded masses reach up to 1.3for $\PSQtDo$ and 800for $\PSGczDo$.

The T2 and T2 results were combined with complementary searches in the all-jet
and single-lepton channels, providing exclusions in the T2 model of $\PSQtDo$
mass $<$1050for a massless $\PSGczDo$, and a $\PSGczDo$ mass of $<$500for a
$\PSQtDo$ mass of 900. In the same way, the T2 model is excluded for $\PSQtDo$
mass $<$1000for a massless $\PSGczDo$, and a $\PSGczDo$ mass of $<$450for a
$\PSQtDo$ mass of 900

The combination extends the sensitivity by $\approx$50in the masses of both
$\PSQtDo$ and $\PSGczDo$ in the T2 model, and by similar values in the T2
model, when the difference between these masses is $\approx$200\. Aggregate
search regions were presented that can be used to reinterpret the results in a
wider range of theoretical models of new physics that give rise to the chosen
final state.

In addition, the results were interpreted in a simplified model with a dark
matter candidate particle coupled to the top quark via a scalar or a
pseudoscalar mediator. Within the assumptions of the model, a scalar mediator
with a mass up to 100and a pseudoscalar mediator with a mass up to 50are
excluded for a dark matter candidate mass of 1. The result for the scalar
mediator achieves some of the most stringent limits to date in this model.

###### Acknowledgements.

We congratulate our colleagues in the CERN accelerator departments for the
excellent performance of the LHC and thank the technical and administrative
staffs at CERN and at other CMS institutes for their contributions to the
success of the CMS effort. In addition, we gratefully acknowledge the
computing centers and personnel of the Worldwide LHC Computing Grid for
delivering so effectively the computing infrastructure essential to our
analyses. Finally, we acknowledge the enduring support for the construction
and operation of the LHC and the CMS detector provided by the following
funding agencies: BMWFW and FWF (Austria); FNRS and FWO (Belgium); CNPq,
CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC
(China); COLCIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus);
SENESCYT (Ecuador); MoER, ERC IUT, and ERDF (Estonia); Academy of Finland,
MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF
(Germany); GSRT (Greece); OTKA and NIH (Hungary); DAE and DST (India); IPM
(Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); LAS
(Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and
UASLP-FAI (Mexico); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC
(Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS, RFBR and RAEP
(Russia); MESTD (Serbia); SEIDI, CPAN, PCTI and FEDER (Spain); Swiss Funding
Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA
(Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United
Kingdom); DOE and NSF (USA). Individuals have received support from the Marie-
Curie program and the European Research Council and Horizon 2020 Grant,
contract No. 675440 (European Union); the Leventis Foundation; the A. P. Sloan
Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science
Policy Office; the Fonds pour la Formation à la Recherche dans l’Industrie et
dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door
Wetenschap en Technologie (IWT-Belgium); the Ministry of Education, Youth and
Sports (MEYS) of the Czech Republic; the Council of Science and Industrial
Research, India; the HOMING PLUS program of the Foundation for Polish Science,
cofinanced from European Union, Regional Development Fund, the Mobility Plus
program of the Ministry of Science and Higher Education, the National Science
Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus
2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis
2012/07/E/ST2/01406; the National Priorities Research Program by Qatar
National Research Fund; the Programa Severo Ochoa del Principado de Asturias;
the Thalis and Aristeia programs cofinanced by EU-ESF and the Greek NSRF; the
Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University
and the Chulalongkorn Academic into Its 2nd Century Project Advancement
Project (Thailand); the Welch Foundation, contract C-1845; and the Weston
Havens Foundation (USA).

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##  .10 The CMS Collaboration

Yerevan Physics Institute, Yerevan, Armenia
A.M. Sirunyan, A. Tumasyan Institut für Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, E. Brondolin, M.
Dragicevic, J. Erö, M. Flechl, M. Friedl, R. Frühwirth1, V.M. Ghete, J.
Grossmann, J. Hrubec, M. Jeitler1, A. König, N. Krammer, I. Krätschmer, D.
Liko, T. Madlener, I. Mikulec, E. Pree, N. Rad, H. Rohringer, J. Schieck1, R.
Schöfbeck, M. Spanring, D. Spitzbart, W. Waltenberger, J. Wittmann, C.-E.
Wulz1, M. Zarucki Institute for Nuclear Problems, Minsk, Belarus
V. Chekhovsky, V. Mossolov, J. Suarez Gonzalez Universiteit Antwerpen,
Antwerpen, Belgium
E.A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, M. Van De Klundert, H. Van
Haevermaet, P. Van Mechelen, N. Van Remortel Vrije Universiteit Brussel,
Brussel, Belgium
S. Abu Zeid, F. Blekman, J. D’Hondt, I. De Bruyn, J. De Clercq, K. Deroover,
G. Flouris, D. Lontkovskyi, S. Lowette, I. Marchesini, S. Moortgat, L.
Moreels, Q. Python, K. Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders,
I. Van Parijs Université Libre de Bruxelles, Bruxelles, Belgium
D. Beghin, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, B. Dorney, G.
Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk, T. Lenzi, J. Luetic, T.
Maerschalk, A. Marinov, T. Seva, E. Starling, C. Vander Velde, P. Vanlaer, D.
Vannerom, R. Yonamine, F. Zenoni, F. Zhang2 Ghent University, Ghent, Belgium
A. Cimmino, T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov3, D.
Poyraz, C. Roskas, S. Salva, M. Tytgat, W. Verbeke, N. Zaganidis Université
Catholique de Louvain, Louvain-la-Neuve, Belgium
H. Bakhshiansohi, O. Bondu, S. Brochet, G. Bruno, C. Caputo, A. Caudron, P.
David, S. De Visscher, C. Delaere, M. Delcourt, B. Francois, A. Giammanco, M.
Komm, G. Krintiras, V. Lemaitre, A. Magitteri, A. Mertens, M. Musich, K.
Piotrzkowski, L. Quertenmont, A. Saggio, M. Vidal Marono, S. Wertz, J. Zobec
Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil
W.L. Aldá Júnior, F.L. Alves, G.A. Alves, L. Brito, M. Correa Martins Junior,
C. Hensel, A. Moraes, M.E. Pol, P. Rebello Teles Universidade do Estado do Rio
de Janeiro, Rio de Janeiro, Brazil
E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato4, E. Coelho, E.M.
Da Costa, G.G. Da Silveira5, D. De Jesus Damiao, S. Fonseca De Souza, L.M.
Huertas Guativa, H. Malbouisson, M. Melo De Almeida, C. Mora Herrera, L.
Mundim, H. Nogima, L.J. Sanchez Rosas, A. Santoro, A. Sznajder, M. Thiel, E.J.
Tonelli Manganote4, F. Torres Da Silva De Araujo, A. Vilela Pereira
Universidade Estadual Paulista a, Universidade Federal do ABC b, São Paulo,
Brazil
S. Ahujaa, C.A. Bernardesa, T.R. Fernandez Perez Tomeia, E.M. Gregoresb, P.G.
Mercadanteb, S.F. Novaesa, Sandra S. Padulaa, D. Romero Abadb, J.C. Ruiz
Vargasa Institute for Nuclear Research and Nuclear Energy, Bulgarian Academy
of Sciences, Sofia, Bulgaria
A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Misheva, M. Rodozov, M. Shopova,
G. Sultanov University of Sofia, Sofia, Bulgaria
A. Dimitrov, L. Litov, B. Pavlov, P. Petkov Beihang University, Beijing, China
W. Fang6, X. Gao6, L. Yuan Institute of High Energy Physics, Beijing, China
M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D.
Leggat, H. Liao, Z. Liu, F. Romeo, S.M. Shaheen, A. Spiezia, J. Tao, C. Wang,
Z. Wang, E. Yazgan, H. Zhang, S. Zhang, J. Zhao State Key Laboratory of
Nuclear Physics and Technology, Peking University, Beijing, China
Y. Ban, G. Chen, Q. Li, S. Liu, Y. Mao, S.J. Qian, D. Wang, Z. Xu Universidad
de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, L.F. Chaparro Sierra, C. Florez, C.F. González
Hernández, J.D. Ruiz Alvarez, M.A. Segura Delgado University of Split, Faculty
of Electrical Engineering, Mechanical Engineering and Naval Architecture,
Split, Croatia
B. Courbon, N. Godinovic, D. Lelas, I. Puljak, P.M. Ribeiro Cipriano, T.
Sculac University of Split, Faculty of Science, Split, Croatia
Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia
V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, A. Starodumov7, T. Susa
University of Cyprus, Nicosia, Cyprus
M.W. Ather, A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos,
P.A. Razis, H. Rykaczewski Charles University, Prague, Czech Republic
M. Finger8, M. Finger Jr.8 Universidad San Francisco de Quito, Quito, Ecuador
E. Carrera Jarrin Academy of Scientific Research and Technology of the Arab
Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt
E. El-khateeb9, S. Elgammal10, A. Mohamed11 National Institute of Chemical
Physics and Biophysics, Tallinn, Estonia
R.K. Dewanjee, M. Kadastik, L. Perrini, M. Raidal, A. Tiko, C. Veelken
Department of Physics, University of Helsinki, Helsinki, Finland
P. Eerola, H. Kirschenmann, J. Pekkanen, M. Voutilainen Helsinki Institute of
Physics, Helsinki, Finland
J. Havukainen, J.K. Heikkilä, T. Järvinen, V. Karimäki, R. Kinnunen, T.
Lampén, K. Lassila-Perini, S. Laurila, S. Lehti, T. Lindén, P. Luukka, H.
Siikonen, E. Tuominen, J. Tuominiemi Lappeenranta University of Technology,
Lappeenranta, Finland
T. Tuuva IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
M. Besancon, F. Couderc, M. Dejardin, D. Denegri, J.L. Faure, F. Ferri, S.
Ganjour, S. Ghosh, P. Gras, G. Hamel de Monchenault, P. Jarry, I. Kucher, C.
Leloup, E. Locci, M. Machet, J. Malcles, G. Negro, J. Rander, A. Rosowsky,
M.Ö. Sahin, M. Titov Laboratoire Leprince-Ringuet, Ecole polytechnique,
CNRS/IN2P3, Université Paris-Saclay, Palaiseau, France
A. Abdulsalam, C. Amendola, I. Antropov, S. Baffioni, F. Beaudette, P. Busson,
L. Cadamuro, C. Charlot, R. Granier de Cassagnac, M. Jo, S. Lisniak, A.
Lobanov, J. Martin Blanco, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P.
Pigard, R. Salerno, J.B. Sauvan, Y. Sirois, A.G. Stahl Leiton, T. Strebler, Y.
Yilmaz, A. Zabi, A. Zghiche Université de Strasbourg, CNRS, IPHC UMR 7178,
F-67000 Strasbourg, France
J.-L. Agram12, J. Andrea, D. Bloch, J.-M. Brom, M. Buttignol, E.C. Chabert, N.
Chanon, C. Collard, E. Conte12, X. Coubez, J.-C. Fontaine12, D. Gelé, U.
Goerlach, M. Jansová, A.-C. Le Bihan, N. Tonon, P. Van Hove Centre de Calcul
de l’Institut National de Physique Nucleaire et de Physique des Particules,
CNRS/IN2P3, Villeurbanne, France
S. Gadrat Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3,
Institut de Physique Nucléaire de Lyon, Villeurbanne, France
S. Beauceron, C. Bernet, G. Boudoul, R. Chierici, D. Contardo, P. Depasse, H.
El Mamouni, J. Fay, L. Finco, S. Gascon, M. Gouzevitch, G. Grenier, B. Ille,
F. Lagarde, I.B. Laktineh, M. Lethuillier, L. Mirabito, A.L. Pequegnot, S.
Perries, A. Popov13, V. Sordini, M. Vander Donckt, S. Viret Georgian Technical
University, Tbilisi, Georgia
A. Khvedelidze8 Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze8 RWTH Aachen University, I. Physikalisches Institut, Aachen,
Germany
C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, C.
Schomakers, J. Schulz, V. Zhukov13 RWTH Aachen University, III. Physikalisches
Institut A, Aachen, Germany
A. Albert, E. Dietz-Laursonn, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg,
T. Esch, R. Fischer, A. Güth, M. Hamer, T. Hebbeker, C. Heidemann, K.
Hoepfner, S. Knutzen, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, T.
Pook, M. Radziej, H. Reithler, M. Rieger, F. Scheuch, D. Teyssier, S. Thüer
RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany
G. Flügge, B. Kargoll, T. Kress, A. Künsken, T. Müller, A. Nehrkorn, A.
Nowack, C. Pistone, O. Pooth, A. Stahl14 Deutsches Elektronen-Synchrotron,
Hamburg, Germany
M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, K. Beernaert, O. Behnke, U.
Behrens, A. Bermúdez Martínez, A.A. Bin Anuar, K. Borras15, V. Botta, A.
Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G.
Eckerlin, D. Eckstein, T. Eichhorn, E. Eren, E. Gallo16, J. Garay Garcia, A.
Geiser, J.M. Grados Luyando, A. Grohsjean, P. Gunnellini, M. Guthoff, A. Harb,
J. Hauk, M. Hempel17, H. Jung, M. Kasemann, J. Keaveney, C. Kleinwort, I.
Korol, D. Krücker, W. Lange, A. Lelek, T. Lenz, J. Leonard, K. Lipka, W.
Lohmann17, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, G. Mittag, J. Mnich,
A. Mussgiller, E. Ntomari, D. Pitzl, A. Raspereza, M. Savitskyi, P. Saxena, R.
Shevchenko, S. Spannagel, N. Stefaniuk, G.P. Van Onsem, R. Walsh, Y. Wen, K.
Wichmann, C. Wissing, O. Zenaiev University of Hamburg, Hamburg, Germany
R. Aggleton, S. Bein, V. Blobel, M. Centis Vignali, T. Dreyer, E. Garutti, D.
Gonzalez, J. Haller, A. Hinzmann, M. Hoffmann, A. Karavdina, R. Klanner, R.
Kogler, N. Kovalchuk, S. Kurz, T. Lapsien, D. Marconi, M. Meyer, M. Niedziela,
D. Nowatschin, F. Pantaleo14, T. Peiffer, A. Perieanu, C. Scharf, P. Schleper,
A. Schmidt, S. Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G. Steinbrück,
F.M. Stober, M. Stöver, H. Tholen, D. Troendle, E. Usai, A. Vanhoefer, B.
Vormwald Institut für Experimentelle Kernphysik, Karlsruhe, Germany
M. Akbiyik, C. Barth, M. Baselga, S. Baur, E. Butz, R. Caspart, T. Chwalek, F.
Colombo, W. De Boer, A. Dierlamm, N. Faltermann, B. Freund, R. Friese, M.
Giffels, M.A. Harrendorf, F. Hartmann14, S.M. Heindl, U. Husemann, F.
Kassel14, S. Kudella, H. Mildner, M.U. Mozer, Th. Müller, M. Plagge, G. Quast,
K. Rabbertz, M. Schröder, I. Shvetsov, G. Sieber, H.J. Simonis, R. Ulrich, S.
Wayand, M. Weber, T. Weiler, S. Williamson, C. Wöhrmann, R. Wolf Institute of
Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece
G. Anagnostou, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas, I. Topsis-
Giotis National and Kapodistrian University of Athens, Athens, Greece
G. Karathanasis, S. Kesisoglou, A. Panagiotou, N. Saoulidou National Technical
University of Athens, Athens, Greece
K. Kousouris University of Ioánnina, Ioánnina, Greece
I. Evangelou, C. Foudas, P. Kokkas, S. Mallios, N. Manthos, I. Papadopoulos,
E. Paradas, J. Strologas, F.A. Triantis MTA-ELTE Lendület CMS Particle and
Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary
M. Csanad, N. Filipovic, G. Pasztor, O. Surányi, G.I. Veres18 Wigner Research
Centre for Physics, Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath19, Á. Hunyadi, F. Sikler, V. Veszpremi
Institute of Nuclear Research ATOMKI, Debrecen, Hungary
N. Beni, S. Czellar, J. Karancsi20, A. Makovec, J. Molnar, Z. Szillasi
Institute of Physics, University of Debrecen, Debrecen, Hungary
M. Bartók18, P. Raics, Z.L. Trocsanyi, B. Ujvari Indian Institute of Science
(IISc), Bangalore, India
S. Choudhury, J.R. Komaragiri National Institute of Science Education and
Research, Bhubaneswar, India
S. Bahinipati21, S. Bhowmik, P. Mal, K. Mandal, A. Nayak22, D.K. Sahoo21, N.
Sahoo, S.K. Swain Panjab University, Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, N. Dhingra, A.K. Kalsi, A.
Kaur, M. Kaur, S. Kaur, R. Kumar, P. Kumari, A. Mehta, J.B. Singh, G. Walia
University of Delhi, Delhi, India
Ashok Kumar, Aashaq Shah, A. Bhardwaj, S. Chauhan, B.C. Choudhary, R.B. Garg,
S. Keshri, A. Kumar, S. Malhotra, M. Naimuddin, K. Ranjan, R. Sharma Saha
Institute of Nuclear Physics, HBNI, Kolkata, India
R. Bhardwaj, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep, S. Dey, S. Dutt,
S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S.
Nandan, A. Purohit, A. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur
Indian Institute of Technology Madras, Madras, India
P.K. Behera Bhabha Atomic Research Centre, Mumbai, India
R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty14, P.K. Netrakanti,
L.M. Pant, P. Shukla, A. Topkar Tata Institute of Fundamental Research-A,
Mumbai, India
T. Aziz, S. Dugad, B. Mahakud, S. Mitra, G.B. Mohanty, N. Sur, B. Sutar Tata
Institute of Fundamental Research-B, Mumbai, India
S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, Sa. Jain, S.
Kumar, M. Maity23, G. Majumder, K. Mazumdar, T. Sarkar23, N. Wickramage24
Indian Institute of Science Education and Research (IISER), Pune, India
S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, S.
Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
S. Chenarani25, E. Eskandari Tadavani, S.M. Etesami25, M. Khakzad, M.
Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi26, F. Rezaei
Hosseinabadi, B. Safarzadeh27, M. Zeinali University College Dublin, Dublin,
Ireland
M. Felcini, M. Grunewald INFN Sezione di Bari a, Università di Bari b,
Politecnico di Bari c, Bari, Italy
M. Abbresciaa,b, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L. Cristellaa,b,
N. De Filippisa,c, M. De Palmaa,b, F. Erricoa,b, L. Fiorea, G. Iasellia,c, S.
Lezkia,b, G. Maggia,c, M. Maggia, G. Minielloa,b, S. Mya,b, S. Nuzzoa,b, A.
Pompilia,b, G. Pugliesea,c, R. Radognaa, A. Ranieria, G. Selvaggia,b, A.
Sharmaa, L. Silvestrisa,14, R. Vendittia, P. Verwilligena INFN Sezione di
Bologna a, Università di Bologna b, Bologna, Italy
G. Abbiendia, C. Battilanaa,b, D. Bonacorsia,b, L. Borgonovia,b, S. Braibant-
Giacomellia,b, R. Campaninia,b, P. Capiluppia,b, A. Castroa,b, F.R. Cavalloa,
S.S. Chhibraa, G. Codispotia,b, M. Cuffiania,b, G.M. Dallavallea, F. Fabbria,
A. Fanfania,b, D. Fasanellaa,b, P. Giacomellia, C. Grandia, L. Guiduccia,b, S.
Marcellinia, G. Masettia, A. Montanaria, F.L. Navarriaa,b, A. Perrottaa, A.M.
Rossia,b, T. Rovellia,b, G.P. Sirolia,b, N. Tosia INFN Sezione di Catania a,
Università di Catania b, Catania, Italy
S. Albergoa,b, S. Costaa,b, A. Di Mattiaa, F. Giordanoa,b, R. Potenzaa,b, A.
Tricomia,b, C. Tuvea,b INFN Sezione di Firenze a, Università di Firenze b,
Firenze, Italy
G. Barbaglia, K. Chatterjeea,b, V. Ciullia,b, C. Civininia, R.
D’Alessandroa,b, E. Focardia,b, P. Lenzia,b, M. Meschinia, S. Paolettia, L.
Russoa,28, G. Sguazzonia, D. Stroma, L. Viliania,b,14 INFN Laboratori
Nazionali di Frascati, Frascati, Italy
L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera14 INFN Sezione di
Genova a, Università di Genova b, Genova, Italy
V. Calvellia,b, F. Ferroa, E. Robuttia, S. Tosia,b INFN Sezione di Milano-
Bicocca a, Università di Milano-Bicocca b, Milano, Italy
A. Benagliaa, A. Beschib, L. Brianzaa,b, F. Brivioa,b, V. Cirioloa,b,14, M.E.
Dinardoa,b, S. Fiorendia,b, S. Gennaia, A. Ghezzia,b, P. Govonia,b, M.
Malbertia,b, S. Malvezzia, R.A. Manzonia,b, D. Menascea, L. Moronia, M.
Paganonia,b, K. Pauwelsa,b, D. Pedrinia, S. Pigazzinia,b,29, S. Ragazzia,b, T.
Tabarelli de Fatisa,b INFN Sezione di Napoli a, Università di Napoli ’Federico
II’ b, Napoli, Italy, Università della Basilicata c, Potenza, Italy,
Università G. Marconi d, Roma, Italy
S. Buontempoa, N. Cavalloa,c, S. Di Guidaa,d,14, F. Fabozzia,c, F. Fiengaa,b,
A.O.M. Iorioa,b, W.A. Khana, L. Listaa, S. Meolaa,d,14, P. Paoluccia,14, C.
Sciaccaa,b, F. Thyssena INFN Sezione di Padova a, Università di Padova b,
Padova, Italy, Università di Trento c, Trento, Italy
P. Azzia, N. Bacchettaa, L. Benatoa,b, D. Biselloa,b, A. Bolettia,b, R.
Carlina,b, A. Carvalho Antunes De Oliveiraa,b, P. Checchiaa, M. Dall’Ossoa,b,
P. De Castro Manzanoa, T. Dorigoa, U. Dossellia, F. Gasparinia,b, U.
Gasparinia,b, S. Lacapraraa, P. Lujan, A.T. Meneguzzoa,b, D. Pantanoa, N.
Pozzobona,b, P. Ronchesea,b, R. Rossina,b, F. Simonettoa,b, E. Torassaa, M.
Zanettia,b, P. Zottoa,b, G. Zumerlea,b INFN Sezione di Pavia a, Università di
Pavia b, Pavia, Italy
A. Braghieria, A. Magnania, P. Montagnaa,b, S.P. Rattia,b, V. Rea, M.
Ressegottia,b, C. Riccardia,b, P. Salvinia, I. Vaia,b, P. Vituloa,b INFN
Sezione di Perugia a, Università di Perugia b, Perugia, Italy
L. Alunni Solestizia,b, M. Biasinia,b, G.M. Bileia, C. Cecchia,b, D.
Ciangottinia,b, L. Fanòa,b, P. Laricciaa,b, R. Leonardia,b, E. Manonia, G.
Mantovania,b, V. Mariania,b, M. Menichellia, A. Rossia,b, A. Santocchiaa,b, D.
Spigaa INFN Sezione di Pisa a, Università di Pisa b, Scuola Normale Superiore
di Pisa c, Pisa, Italy
K. Androsova, P. Azzurria,14, G. Bagliesia, T. Boccalia, L. Borrello, R.
Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, G. Fedia, L. Gianninia,c, A.
Giassia, M.T. Grippoa,28, F. Ligabuea,c, T. Lomtadzea, E. Mancaa,c, G.
Mandorlia,c, A. Messineoa,b, F. Pallaa, A. Rizzia,b, A. Savoy-Navarroa,30, P.
Spagnoloa, R. Tenchinia, G. Tonellia,b, A. Venturia, P.G. Verdinia INFN
Sezione di Roma a, Sapienza Università di Roma b, Rome, Italy
L. Baronea,b, F. Cavallaria, M. Cipriania,b, N. Dacia, D. Del Rea,b,14, E. Di
Marcoa,b, M. Diemoza, S. Gellia,b, E. Longoa,b, F. Margarolia,b, B.
Marzocchia,b, P. Meridiania, G. Organtinia,b, R. Paramattia,b, F. Preiatoa,b,
S. Rahatloua,b, C. Rovellia, F. Santanastasioa,b INFN Sezione di Torino a,
Università di Torino b, Torino, Italy, Università del Piemonte Orientale c,
Novara, Italy
N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, N. Bartosika,
R. Bellana,b, C. Biinoa, N. Cartigliaa, F. Cennaa,b, M. Costaa,b, R.
Covarellia,b, A. Deganoa,b, N. Demariaa, B. Kiania,b, C. Mariottia, S.
Masellia, E. Migliorea,b, V. Monacoa,b, E. Monteila,b, M. Montenoa, M.M.
Obertinoa,b, L. Pachera,b, N. Pastronea, M. Pelliccionia, G.L. Pinna
Angionia,b, F. Raveraa,b, A. Romeroa,b, M. Ruspaa,c, R. Sacchia,b, K.
Shchelinaa,b, V. Solaa, A. Solanoa,b, A. Staianoa, P. Traczyka,b INFN Sezione
di Trieste a, Università di Trieste b, Trieste, Italy
S. Belfortea, M. Casarsaa, F. Cossuttia, G. Della Riccaa,b, A. Zanettia
Kyungpook National University, Daegu, Korea
D.H. Kim, G.N. Kim, M.S. Kim, J. Lee, S. Lee, S.W. Lee, C.S. Moon, Y.D. Oh, S.
Sekmen, D.C. Son, Y.C. Yang Chonbuk National University, Jeonju, Korea
A. Lee Chonnam National University, Institute for Universe and Elementary
Particles, Kwangju, Korea
H. Kim, D.H. Moon, G. Oh Hanyang University, Seoul, Korea
J.A. Brochero Cifuentes, J. Goh, T.J. Kim Korea University, Seoul, Korea
S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, Y. Kim, K. Lee, K.S.
Lee, S. Lee, J. Lim, S.K. Park, Y. Roh Seoul National University, Seoul, Korea
J. Almond, J. Kim, J.S. Kim, H. Lee, K. Lee, K. Nam, S.B. Oh, B.C. Radburn-
Smith, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu University of Seoul, Seoul,
Korea
H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park Sungkyunkwan University, Suwon, Korea
Y. Choi, C. Hwang, J. Lee, I. Yu Vilnius University, Vilnius, Lithuania
V. Dudenas, A. Juodagalvis, J. Vaitkus National Centre for Particle Physics,
Universiti Malaya, Kuala Lumpur, Malaysia
I. Ahmed, Z.A. Ibrahim, M.A.B. Md Ali31, F. Mohamad Idris32, W.A.T. Wan
Abdullah, M.N. Yusli, Z. Zolkapli Centro de Investigacion y de Estudios
Avanzados del IPN, Mexico City, Mexico
Reyes-Almanza, R, Ramirez-Sanchez, G., Duran-Osuna, M. C., H. Castilla-Valdez,
E. De La Cruz-Burelo, I. Heredia-De La Cruz33, Rabadan-Trejo, R. I., R. Lopez-
Fernandez, J. Mejia Guisao, A. Sanchez-Hernandez Universidad Iberoamericana,
Mexico City, Mexico
S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita
Universidad Autonoma de Puebla, Puebla, Mexico
I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad Autónoma de
San Luis Potosí, San Luis Potosí, Mexico
A. Morelos Pineda University of Auckland, Auckland, New Zealand
D. Krofcheck University of Canterbury, Christchurch, New Zealand
P.H. Butler National Centre for Physics, Quaid-I-Azam University, Islamabad,
Pakistan
A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, A. Saddique, M.A. Shah, M.
Shoaib, M. Waqas National Centre for Nuclear Research, Swierk, Poland
H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Górski, M. Kazana, K.
Nawrocki, M. Szleper, P. Zalewski Institute of Experimental Physics, Faculty
of Physics, University of Warsaw, Warsaw, Poland
K. Bunkowski, A. Byszuk34, K. Doroba, A. Kalinowski, M. Konecki, J.
Krolikowski, M. Misiura, M. Olszewski, A. Pyskir, M. Walczak Laboratório de
Instrumentação e Física Experimental de Partículas, Lisboa, Portugal
P. Bargassa, C. Beirão Da Cruz E Silva, A. Di Francesco, P. Faccioli, B.
Galinhas, M. Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias, M.V.
Nemallapudi, J. Seixas, G. Strong, O. Toldaiev, D. Vadruccio, J. Varela Joint
Institute for Nuclear Research, Dubna, Russia
V. Alexakhin, A. Golunov, I. Golutvin, N. Gorbounov, I. Gorbunov, A. Kamenev,
V. Karjavin, A. Lanev, A. Malakhov, V. Matveev35,36, V. Palichik, V.
Perelygin, M. Savina, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, A.
Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg),
Russia
Y. Ivanov, V. Kim37, E. Kuznetsova38, P. Levchenko, V. Murzin, V. Oreshkin, I.
Smirnov, V. Sulimov, L. Uvarov, S. Vavilov, A. Vorobyev Institute for Nuclear
Research, Moscow, Russia
Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov,
N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical
and Experimental Physics, Moscow, Russia
V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G.
Safronov, A. Spiridonov, A. Stepennov, M. Toms, E. Vlasov, A. Zhokin Moscow
Institute of Physics and Technology, Moscow, Russia
T. Aushev, A. Bylinkin36 National Research Nuclear University ’Moscow
Engineering Physics Institute’ (MEPhI), Moscow, Russia
R. Chistov39, M. Danilov39, P. Parygin, D. Philippov, S. Polikarpov, E.
Tarkovskii P.N. Lebedev Physical Institute, Moscow, Russia
V. Andreev, M. Azarkin36, I. Dremin36, M. Kirakosyan36, A. Terkulov Skobeltsyn
Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow,
Russia
A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin40, L. Dudko, A.
Ershov, A. Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S.
Obraztsov, S. Petrushanko, V. Savrin Novosibirsk State University (NSU),
Novosibirsk, Russia
V. Blinov41, Y.Skovpen41, D. Shtol41 State Research Center of Russian
Federation, Institute for High Energy Physics, Protvino, Russia
I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, V. Kachanov, A. Kalinin,
D. Konstantinov, P. Mandrik, V. Petrov, R. Ryutin, A. Sobol, S. Troshin, N.
Tyurin, A. Uzunian, A. Volkov University of Belgrade, Faculty of Physics and
Vinca Institute of Nuclear Sciences, Belgrade, Serbia
P. Adzic42, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic
Centro de Investigaciones Energéticas Medioambientales y Tecnológicas
(CIEMAT), Madrid, Spain
J. Alcaraz Maestre, M. Barrio Luna, M. Cerrada, N. Colino, B. De La Cruz, A.
Delgado Peris, A. Escalante Del Valle, C. Fernandez Bedoya, J.P. Fernández
Ramos, J. Flix, M.C. Fouz, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez,
M.I. Josa, D. Moran, A. Pérez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario
Olmeda, I. Redondo, L. Romero, M.S. Soares, A. Álvarez Fernández Universidad
Autónoma de Madrid, Madrid, Spain
C. Albajar, J.F. de Trocóniz, M. Missiroli Universidad de Oviedo, Oviedo,
Spain
J. Cuevas, C. Erice, J. Fernandez Menendez, I. Gonzalez Caballero, J.R.
González Fernández, E. Palencia Cortezon, S. Sanchez Cruz, P. Vischia, J.M.
Vizan Garcia Instituto de Física de Cantabria (IFCA), CSIC-Universidad de
Cantabria, Santander, Spain
I.J. Cabrillo, A. Calderon, B. Chazin Quero, E. Curras, J. Duarte Campderros,
M. Fernandez, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto, J. Marco, C.
Martinez Rivero, P. Martinez Ruiz del Arbol, F. Matorras, J. Piedra Gomez, T.
Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar
Cortabitarte CERN, European Organization for Nuclear Research, Geneva,
Switzerland
D. Abbaneo, B. Akgun, E. Auffray, P. Baillon, A.H. Ball, D. Barney, J.
Bendavid, M. Bianco, P. Bloch, A. Bocci, C. Botta, T. Camporesi, R. Castello,
M. Cepeda, G. Cerminara, E. Chapon, Y. Chen, D. d’Enterria, A. Dabrowski, V.
Daponte, A. David, M. De Gruttola, A. De Roeck, N. Deelen, M. Dobson, T. du
Pree, M. Dünser, N. Dupont, A. Elliott-Peisert, P. Everaerts, F. Fallavollita,
G. Franzoni, J. Fulcher, W. Funk, D. Gigi, A. Gilbert, K. Gill, F. Glege, D.
Gulhan, P. Harris, J. Hegeman, V. Innocente, A. Jafari, P. Janot, O.
Karacheban17, J. Kieseler, V. Knünz, A. Kornmayer, M.J. Kortelainen, M.
Krammer1, C. Lange, P. Lecoq, C. Lourenço, M.T. Lucchini, L. Malgeri, M.
Mannelli, A. Martelli, F. Meijers, J.A. Merlin, S. Mersi, E. Meschi, P.
Milenovic43, F. Moortgat, M. Mulders, H. Neugebauer, J. Ngadiuba, S.
Orfanelli, L. Orsini, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G.
Petrucciani, A. Pfeiffer, M. Pierini, D. Rabady, A. Racz, T. Reis, G.
Rolandi44, M. Rovere, H. Sakulin, C. Schäfer, C. Schwick, M. Seidel, M.
Selvaggi, A. Sharma, P. Silva, P. Sphicas45, A. Stakia, J. Steggemann, M.
Stoye, M. Tosi, D. Treille, A. Triossi, A. Tsirou, V. Veckalns46, M. Verweij,
W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland
W. Bertl${}^{\textrm{\textdagger}}$, L. Caminada47, K. Deiters, W. Erdmann, R.
Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe,
S.A. Wiederkehr ETH Zurich - Institute for Particle Physics and Astrophysics
(IPA), Zurich, Switzerland
M. Backhaus, L. Bäni, P. Berger, L. Bianchini, B. Casal, G. Dissertori, M.
Dittmar, M. Donegà, C. Dorfer, C. Grab, C. Heidegger, D. Hits, J. Hoss, G.
Kasieczka, T. Klijnsma, W. Lustermann, B. Mangano, M. Marionneau, M.T.
Meinhard, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandolfi,
J. Pata, F. Pauss, G. Perrin, L. Perrozzi, M. Quittnat, M. Reichmann, D.A.
Sanz Becerra, M. Schönenberger, L. Shchutska, V.R. Tavolaro, K. Theofilatos,
M.L. Vesterbacka Olsson, R. Wallny, D.H. Zhu Universität Zürich, Zurich,
Switzerland
T.K. Aarrestad, C. Amsler48, M.F. Canelli, A. De Cosa, R. Del Burgo, S.
Donato, C. Galloni, T. Hreus, B. Kilminster, D. Pinna, G. Rauco, P. Robmann,
D. Salerno, K. Schweiger, C. Seitz, Y. Takahashi, A. Zucchetta National
Central University, Chung-Li, Taiwan
V. Candelise, T.H. Doan, Sh. Jain, R. Khurana, C.M. Kuo, W. Lin, A.
Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan
Arun Kumar, P. Chang, Y. Chao, K.F. Chen, P.H. Chen, F. Fiori, W.-S. Hou, Y.
Hsiung, Y.F. Liu, R.-S. Lu, E. Paganis, A. Psallidas, A. Steen, J.f. Tsai
Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok,
Thailand
B. Asavapibhop, K. Kovitanggoon, G. Singh, N. Srimanobhas Çukurova University,
Physics Department, Science and Art Faculty, Adana, Turkey
M.N. Bakirci49, A. Bat, F. Boran, S. Cerci50, S. Damarseckin, Z.S. Demiroglu,
C. Dozen, S. Girgis, G. Gokbulut, Y. Guler, I. Hos51, E.E. Kangal52, O. Kara,
U. Kiminsu, M. Oglakci, G. Onengut53, K. Ozdemir54, S. Ozturk49, A. Polatoz,
U.G. Tok, H. Topakli49, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East
Technical University, Physics Department, Ankara, Turkey
B. Bilin, G. Karapinar55, K. Ocalan56, M. Yalvac, M. Zeyrek Bogazici
University, Istanbul, Turkey
E. Gülmez, M. Kaya57, O. Kaya58, S. Tekten, E.A. Yetkin59 Istanbul Technical
University, Istanbul, Turkey
M.N. Agaras, S. Atay, A. Cakir, K. Cankocak, I. Köseoglu Institute for
Scintillation Materials of National Academy of Science of Ukraine, Kharkov,
Ukraine
B. Grynyov National Scientific Center, Kharkov Institute of Physics and
Technology, Kharkov, Ukraine
L. Levchuk University of Bristol, Bristol, United Kingdom
F. Ball, L. Beck, J.J. Brooke, D. Burns, E. Clement, D. Cussans, O. Davignon,
H. Flacher, J. Goldstein, G.P. Heath, H.F. Heath, L. Kreczko, D.M. Newbold60,
S. Paramesvaran, T. Sakuma, S. Seif El Nasr-storey, D. Smith, V.J. Smith
Rutherford Appleton Laboratory, Didcot, United Kingdom
K.W. Bell, A. Belyaev61, C. Brew, R.M. Brown, L. Calligaris, D. Cieri, D.J.A.
Cockerill, J.A. Coughlan, K. Harder, S. Harper, J. Linacre, E. Olaiya, D.
Petyt, C.H. Shepherd-Themistocleous, A. Thea, I.R. Tomalin, T. Williams
Imperial College, London, United Kingdom
G. Auzinger, R. Bainbridge, J. Borg, S. Breeze, O. Buchmuller, A. Bundock, S.
Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies, A. De Wit, M.
Della Negra, R. Di Maria, A. Elwood, Y. Haddad, G. Hall, G. Iles, T. James, R.
Lane, C. Laner, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, T.
Matsushita, J. Nash, A. Nikitenko7, V. Palladino, M. Pesaresi, D.M. Raymond,
A. Richards, A. Rose, E. Scott, C. Seez, A. Shtipliyski, S. Summers, A.
Tapper, K. Uchida, M. Vazquez Acosta62, T. Virdee14, N. Wardle, D.
Winterbottom, J. Wright, S.C. Zenz Brunel University, Uxbridge, United Kingdom
J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, I.D. Reid, L. Teodorescu, M.
Turner, S. Zahid Baylor University, Waco, USA
A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika, C. Smith
Catholic University of America, Washington DC, USA
R. Bartek, A. Dominguez The University of Alabama, Tuscaloosa, USA
A. Buccilli, S.I. Cooper, C. Henderson, P. Rumerio, C. West Boston University,
Boston, USA
D. Arcaro, A. Avetisyan, T. Bose, D. Gastler, D. Rankin, C. Richardson, J.
Rohlf, L. Sulak, D. Zou Brown University, Providence, USA
G. Benelli, D. Cutts, A. Garabedian, M. Hadley, J. Hakala, U. Heintz, J.M.
Hogan, K.H.M. Kwok, E. Laird, G. Landsberg, J. Lee, Z. Mao, M. Narain, J.
Pazzini, S. Piperov, S. Sagir, R. Syarif, D. Yu University of California,
Davis, Davis, USA
R. Band, C. Brainerd, R. Breedon, D. Burns, M. Calderon De La Barca Sanchez,
M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk,
W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout,
M. Shi, J. Smith, D. Stolp, K. Tos, M. Tripathi, Z. Wang University of
California, Los Angeles, USA
M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M.
Ignatenko, N. Mccoll, S. Regnard, D. Saltzberg, C. Schnaible, V. Valuev
University of California, Riverside, Riverside, USA
E. Bouvier, K. Burt, R. Clare, J. Ellison, J.W. Gary, S.M.A. Ghiasi Shirazi,
G. Hanson, J. Heilman, G. Karapostoli, E. Kennedy, F. Lacroix, O.R. Long, M.
Olmedo Negrete, M.I. Paneva, W. Si, L. Wang, H. Wei, S. Wimpenny, B. R. Yates
University of California, San Diego, La Jolla, USA
J.G. Branson, S. Cittolin, M. Derdzinski, R. Gerosa, D. Gilbert, B. Hashemi,
A. Holzner, D. Klein, G. Kole, V. Krutelyov, J. Letts, I. Macneill, M.
Masciovecchio, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon,
M. Tadel, A. Vartak, S. Wasserbaech63, J. Wood, F. Würthwein, A. Yagil, G.
Zevi Della Porta University of California, Santa Barbara - Department of
Physics, Santa Barbara, USA
N. Amin, R. Bhandari, J. Bradmiller-Feld, C. Campagnari, A. Dishaw, V. Dutta,
M. Franco Sevilla, F. Golf, L. Gouskos, R. Heller, J. Incandela, A. Ovcharova,
H. Qu, J. Richman, D. Stuart, I. Suarez, J. Yoo California Institute of
Technology, Pasadena, USA
D. Anderson, A. Bornheim, J.M. Lawhorn, H.B. Newman, T. Nguyen, C. Pena, M.
Spiropulu, J.R. Vlimant, S. Xie, Z. Zhang, R.Y. Zhu Carnegie Mellon
University, Pittsburgh, USA
M.B. Andrews, T. Ferguson, T. Mudholkar, M. Paulini, J. Russ, M. Sun, H.
Vogel, I. Vorobiev, M. Weinberg University of Colorado Boulder, Boulder, USA
J.P. Cumalat, W.T. Ford, F. Jensen, A. Johnson, M. Krohn, S. Leontsinis, T.
Mulholland, K. Stenson, S.R. Wagner Cornell University, Ithaca, USA
J. Alexander, J. Chaves, J. Chu, S. Dittmer, K. Mcdermott, N. Mirman, J.R.
Patterson, D. Quach, A. Rinkevicius, A. Ryd, L. Skinnari, L. Soffi, S.M. Tan,
Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek Fermi National Accelerator
Laboratory, Batavia, USA
S. Abdullin, M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, A. Apyan, S.
Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, G.
Bolla${}^{\textrm{\textdagger}}$, K. Burkett, J.N. Butler, A. Canepa, G.B.
Cerati, H.W.K. Cheung, F. Chlebana, M. Cremonesi, J. Duarte, V.D. Elvira, J.
Freeman, Z. Gecse, E. Gottschalk, L. Gray, D. Green, S. Grünendahl, O.
Gutsche, R.M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, B. Jayatilaka, S.
Jindariani, M. Johnson, U. Joshi, B. Klima, B. Kreis, S. Lammel, D. Lincoln,
R. Lipton, M. Liu, T. Liu, R. Lopes De Sá, J. Lykken, K. Maeshima, N. Magini,
J.M. Marraffino, D. Mason, P. McBride, P. Merkel, S. Mrenna, S. Nahn, V.
O’Dell, K. Pedro, O. Prokofyev, G. Rakness, L. Ristori, B. Schneider, E.
Sexton-Kennedy, A. Soha, W.J. Spalding, L. Spiegel, S. Stoynev, J. Strait, N.
Strobbe, L. Taylor, S. Tkaczyk, N.V. Tran, L. Uplegger, E.W. Vaandering, C.
Vernieri, M. Verzocchi, R. Vidal, M. Wang, H.A. Weber, A. Whitbeck University
of Florida, Gainesville, USA
D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerhoff, A. Carnes, M.
Carver, D. Curry, R.D. Field, I.K. Furic, S.V. Gleyzer, B.M. Joshi, J.
Konigsberg, A. Korytov, K. Kotov, P. Ma, K. Matchev, H. Mei, G. Mitselmakher,
D. Rank, K. Shi, D. Sperka, N. Terentyev, L. Thomas, J. Wang, S. Wang, J.
Yelton Florida International University, Miami, USA
Y.R. Joshi, S. Linn, P. Markowitz, J.L. Rodriguez Florida State University,
Tallahassee, USA
A. Ackert, T. Adams, A. Askew, S. Hagopian, V. Hagopian, K.F. Johnson, T.
Kolberg, G. Martinez, T. Perry, H. Prosper, A. Saha, A. Santra, V. Sharma, R.
Yohay Florida Institute of Technology, Melbourne, USA
M.M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, T.
Roy, F. Yumiceva University of Illinois at Chicago (UIC), Chicago, USA
M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, R. Cavanaugh, X. Chen, O.
Evdokimov, C.E. Gerber, D.A. Hangal, D.J. Hofman, K. Jung, J. Kamin, I.D.
Sandoval Gonzalez, M.B. Tonjes, H. Trauger, N. Varelas, H. Wang, Z. Wu, J.
Zhang The University of Iowa, Iowa City, USA
B. Bilki64, W. Clarida, K. Dilsiz65, S. Durgut, R.P. Gandrajula, M.
Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya66, A. Mestvirishvili,
A. Moeller, J. Nachtman, H. Ogul67, Y. Onel, F. Ozok68, A. Penzo, C. Snyder,
E. Tiras, J. Wetzel, K. Yi Johns Hopkins University, Baltimore, USA
B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan, P.
Maksimovic, J. Roskes, U. Sarica, M. Swartz, M. Xiao, C. You The University of
Kansas, Lawrence, USA
A. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, J. Castle, S.
Khalil, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, C. Royon, S.
Sanders, E. Schmitz, J.D. Tapia Takaki, Q. Wang Kansas State University,
Manhattan, USA
A. Ivanov, K. Kaadze, Y. Maravin, A. Mohammadi, L.K. Saini, N. Skhirtladze, S.
Toda Lawrence Livermore National Laboratory, Livermore, USA
F. Rebassoo, D. Wright University of Maryland, College Park, USA
C. Anelli, A. Baden, O. Baron, A. Belloni, S.C. Eno, Y. Feng, C. Ferraioli,
N.J. Hadley, S. Jabeen, G.Y. Jeng, R.G. Kellogg, J. Kunkle, A.C. Mignerey, F.
Ricci-Tam, Y.H. Shin, A. Skuja, S.C. Tonwar Massachusetts Institute of
Technology, Cambridge, USA
D. Abercrombie, B. Allen, V. Azzolini, R. Barbieri, A. Baty, R. Bi, S. Brandt,
W. Busza, I.A. Cali, M. D’Alfonso, Z. Demiragli, G. Gomez Ceballos, M.
Goncharov, D. Hsu, M. Hu, Y. Iiyama, G.M. Innocenti, M. Klute, D. Kovalskyi,
Y.S. Lai, Y.-J. Lee, A. Levin, P.D. Luckey, B. Maier, A.C. Marini, C. Mcginn,
C. Mironov, S. Narayanan, X. Niu, C. Paus, C. Roland, G. Roland, J. Salfeld-
Nebgen, G.S.F. Stephans, K. Tatar, D. Velicanu, J. Wang, T.W. Wang, B.
Wyslouch University of Minnesota, Minneapolis, USA
A.C. Benvenuti, R.M. Chatterjee, A. Evans, P. Hansen, J. Hiltbrand, S.
Kalafut, Y. Kubota, Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack,
J. Turkewitz, M.A. Wadud University of Mississippi, Oxford, USA
J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA
E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, R. Gonzalez Suarez, R.
Kamalieddin, I. Kravchenko, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger State
University of New York at Buffalo, Buffalo, USA
J. Dolen, A. Godshalk, C. Harrington, I. Iashvili, D. Nguyen, A. Parker, S.
Rappoccio, B. Roozbahani Northeastern University, Boston, USA
G. Alverson, E. Barberis, A. Hortiangtham, A. Massironi, D.M. Morse, T.
Orimoto, R. Teixeira De Lima, D. Trocino, D. Wood Northwestern University,
Evanston, USA
S. Bhattacharya, O. Charaf, K.A. Hahn, N. Mucia, N. Odell, B. Pollack, M.H.
Schmitt, K. Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame,
USA
N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N. Kellams,
K. Lannon, W. Li, N. Loukas, N. Marinelli, F. Meng, C. Mueller, Y. Musienko35,
M. Planer, A. Reinsvold, R. Ruchti, P. Siddireddy, G. Smith, S. Taroni, M.
Wayne, A. Wightman, M. Wolf, A. Woodard The Ohio State University, Columbus,
USA
J. Alimena, L. Antonelli, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, A.
Hart, C. Hill, W. Ji, B. Liu, W. Luo, B.L. Winer, H.W. Wulsin Princeton
University, Princeton, USA
S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, S. Higginbotham,
A. Kalogeropoulos, D. Lange, J. Luo, D. Marlow, K. Mei, I. Ojalvo, J. Olsen,
C. Palmer, P. Piroué, D. Stickland, C. Tully University of Puerto Rico,
Mayaguez, USA
S. Malik, S. Norberg Purdue University, West Lafayette, USA
A. Barker, V.E. Barnes, S. Das, S. Folgueras, L. Gutay, M.K. Jha, M. Jones,
A.W. Jung, A. Khatiwada, D.H. Miller, N. Neumeister, C.C. Peng, H. Qiu, J.F.
Schulte, J. Sun, F. Wang, W. Xie Purdue University Northwest, Hammond, USA
T. Cheng, N. Parashar, J. Stupak Rice University, Houston, USA
A. Adair, Z. Chen, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Guilbaud, M.
Kilpatrick, W. Li, B. Michlin, M. Northup, B.P. Padley, J. Roberts, J. Rorie,
W. Shi, Z. Tu, J. Zabel, A. Zhang University of Rochester, Rochester, USA
A. Bodek, P. de Barbaro, R. Demina, Y.t. Duh, T. Ferbel, M. Galanti, A.
Garcia-Bellido, J. Han, O. Hindrichs, A. Khukhunaishvili, K.H. Lo, P. Tan, M.
Verzetti The Rockefeller University, New York, USA
R. Ciesielski, K. Goulianos, C. Mesropian Rutgers, The State University of New
Jersey, Piscataway, USA
A. Agapitos, J.P. Chou, Y. Gershtein, T.A. Gómez Espinosa, E. Halkiadakis, M.
Heindl, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath,
R. Montalvo, K. Nash, M. Osherson, H. Saka, S. Salur, S. Schnetzer, D.
Sheffield, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker
University of Tennessee, Knoxville, USA
A.G. Delannoy, M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K.
Thapa Texas A&M University, College Station, USA
O. Bouhali69, A. Castaneda Hernandez69, A. Celik, M. Dalchenko, M. De Mattia,
A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, T. Kamon70, R.
Mueller, Y. Pakhotin, R. Patel, A. Perloff, L. Perniè, D. Rathjens, A.
Safonov, A. Tatarinov, K.A. Ulmer Texas Tech University, Lubbock, USA
N. Akchurin, J. Damgov, F. De Guio, P.R. Dudero, J. Faulkner, E. Gurpinar, S.
Kunori, K. Lamichhane, S.W. Lee, T. Libeiro, T. Mengke, S. Muthumuni, T.
Peltola, S. Undleeb, I. Volobouev, Z. Wang Vanderbilt University, Nashville,
USA
S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K.
Padeken, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu University of Virginia,
Charlottesville, USA
M.W. Arenton, P. Barria, B. Cox, R. Hirosky, M. Joyce, A. Ledovskoy, H. Li, C.
Neu, T. Sinthuprasith, Y. Wang, E. Wolfe, F. Xia Wayne State University,
Detroit, USA
R. Harr, P.E. Karchin, N. Poudyal, J. Sturdy, P. Thapa, S. Zaleski University
of Wisconsin - Madison, Madison, WI, USA
M. Brodski, J. Buchanan, C. Caillol, S. Dasu, L. Dodd, S. Duric, B. Gomber, M.
Grothe, M. Herndon, A. Hervé, U. Hussain, P. Klabbers, A. Lanaro, A. Levine,
K. Long, R. Loveless, T. Ruggles, A. Savin, N. Smith, W.H. Smith, D. Taylor,
N. Woods †: Deceased
1: Also at Vienna University of Technology, Vienna, Austria
2: Also at State Key Laboratory of Nuclear Physics and Technology, Peking
University, Beijing, China
3: Also at IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
4: Also at Universidade Estadual de Campinas, Campinas, Brazil
5: Also at Universidade Federal de Pelotas, Pelotas, Brazil
6: Also at Université Libre de Bruxelles, Bruxelles, Belgium
7: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia
8: Also at Joint Institute for Nuclear Research, Dubna, Russia
9: Now at Ain Shams University, Cairo, Egypt
10: Now at British University in Egypt, Cairo, Egypt
11: Also at Zewail City of Science and Technology, Zewail, Egypt
12: Also at Université de Haute Alsace, Mulhouse, France
13: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State
University, Moscow, Russia
14: Also at CERN, European Organization for Nuclear Research, Geneva,
Switzerland
15: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
16: Also at University of Hamburg, Hamburg, Germany
17: Also at Brandenburg University of Technology, Cottbus, Germany
18: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
19: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
20: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary
21: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India
22: Also at Institute of Physics, Bhubaneswar, India
23: Also at University of Visva-Bharati, Santiniketan, India
24: Also at University of Ruhuna, Matara, Sri Lanka
25: Also at Isfahan University of Technology, Isfahan, Iran
26: Also at Yazd University, Yazd, Iran
27: Also at Plasma Physics Research Center, Science and Research Branch,
Islamic Azad University, Tehran, Iran
28: Also at Università degli Studi di Siena, Siena, Italy
29: Also at INFN Sezione di Milano-Bicocca; Università di Milano-Bicocca,
Milano, Italy
30: Also at Purdue University, West Lafayette, USA
31: Also at International Islamic University of Malaysia, Kuala Lumpur,
Malaysia
32: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia
33: Also at Consejo Nacional de Ciencia y Tecnología, Mexico city, Mexico
34: Also at Warsaw University of Technology, Institute of Electronic Systems,
Warsaw, Poland
35: Also at Institute for Nuclear Research, Moscow, Russia
36: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
37: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
38: Also at University of Florida, Gainesville, USA
39: Also at P.N. Lebedev Physical Institute, Moscow, Russia
40: Also at California Institute of Technology, Pasadena, USA
41: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
42: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
43: Also at University of Belgrade, Faculty of Physics and Vinca Institute of
Nuclear Sciences, Belgrade, Serbia
44: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy
45: Also at National and Kapodistrian University of Athens, Athens, Greece
46: Also at Riga Technical University, Riga, Latvia
47: Also at Universität Zürich, Zurich, Switzerland
48: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna,
Austria
49: Also at Gaziosmanpasa University, Tokat, Turkey
50: Also at Adiyaman University, Adiyaman, Turkey
51: Also at Istanbul Aydin University, Istanbul, Turkey
52: Also at Mersin University, Mersin, Turkey
53: Also at Cag University, Mersin, Turkey
54: Also at Piri Reis University, Istanbul, Turkey
55: Also at Izmir Institute of Technology, Izmir, Turkey
56: Also at Necmettin Erbakan University, Konya, Turkey
57: Also at Marmara University, Istanbul, Turkey
58: Also at Kafkas University, Kars, Turkey
59: Also at Istanbul Bilgi University, Istanbul, Turkey
60: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom
61: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
62: Also at Instituto de Astrofísica de Canarias, La Laguna, Spain
63: Also at Utah Valley University, Orem, USA
64: Also at Beykent University, Istanbul, Turkey
65: Also at Bingol University, Bingol, Turkey
66: Also at Erzincan University, Erzincan, Turkey
67: Also at Sinop University, Sinop, Turkey
68: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey
69: Also at Texas A&M University at Qatar, Doha, Qatar
70: Also at Kyungpook National University, Daegu, Korea