SUS-19-011

SUS-19-011

# Search for top squark pair production using dilepton final states in
$\Pp\Pp$ collision data collected at $\sqrt{s}=13\TeV$

###### Abstract

A search is presented for supersymmetric partners of the top quark (top
squarks) in final states with two oppositely charged leptons (electrons or
muons), jets identified as originating from quarks, and missing transverse
momentum. The search uses data from proton-proton collisions at
$\sqrt{s}=13\TeV$ collected with the CMS detector, corresponding to an
integrated luminosity of 137. Hypothetical signal events are efficiently
separated from the dominant top quark pair production background with
requirements on the significance of the missing transverse momentum and on
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 lightest top squarks. For top squarks
decaying exclusively to a top quark and a lightest neutralino, lower limits
are placed at $95\%$ confidence level on the masses of the top squark and the
neutralino up to 925 and 450, respectively. If the decay proceeds via an
intermediate chargino, the corresponding lower limits on the mass of the
lightest top squark are set up to 850for neutralino masses below 420. For top
squarks undergoing a cascade decay through charginos and sleptons, the mass
limits reach up to 1.4and 900respectively for the top squark and the lightest
neutralino.

##  0.1 Introduction

The standard model (SM) of particle physics accurately describes the
overwhelming majority of observed particle physics phenomena. Nevertheless,
several open questions are not addressed by the SM, such as the hierarchy
problem, the need for fine tuning to reconcile the large difference between
the electroweak and the Planck scales in the presence of a fundamental scalar
[1, 2, 3, 4]. Moreover, there is a lack of an SM candidate particle that could
constitute the dark matter in cosmological and astrophysical observations [5,
6]. Supersymmetry (SUSY) [7, 8, 9, 10, 11, 12, 13, 14] is a well-motivated
extension of the SM that provides a solution to both of these problems,
through the introduction of a symmetry between bosons and fermions. In SUSY
models, large quantum loop corrections to the mass of the Higgs boson (),
mainly arising from the top quarks, are mostly canceled by those arising from
their SUSY partners, the top squarks, if the masses of the SM particles and
their SUSY partners are close in value. Similar cancellations occur for other
particles, resulting in a natural solution to the hierarchy problem [2, 15,
16]. Furthermore, SUSY introduces a new quantum number, R parity [17], that
distinguishes between SUSY and SM particles. If R parity is conserved, top
squarks are produced in pairs and the lightest SUSY particle (LSP) is stable.
If neutral, the LSP provides a good candidate for the dark matter. The lighter
top squark mass eigenstate is the lightest squark in many SUSY models and may
be within the energy reach of the CERN LHC if SUSY provides a natural solution
to the hierarchy problem [18]. This strongly motivates searches for top squark
production.

In this paper, we present a search for top squark pair production in data from
proton-proton ($\Pp\Pp$) collisions collected at a center-of-mass energy of
13, corresponding to an integrated luminosity of 137, with the CMS detector at
the LHC from 2016 to 2018. The search is performed in final states with two
leptons (electrons or muons), hadronic jets identified as originating from
quarks, and significant missing transverse momentum (). The large background
from the SM top quark-antiquark pair production () is reduced by several
orders of magnitude through the use of specially designed transverse-mass
variables [19, 20]. Simulations of residual SM backgrounds in the search
regions are validated in control regions orthogonal to the signal regions,
using observed data.

Simplified models [21, 22, 23] of strong top squark pair production and
different top squark decay modes are considered. Following the naming
convention in Ref. [24], top squark decays to top quarks and neutralinos (,
identified as LSPs) are described by the T2 model (Fig. 1, left). In the T2
model (Fig. 1, center), both top squarks decay via an intermediate chargino ()
into a bottom quark, a boson, and an LSP. In both models, the undetected LSPs
and the neutrinos from leptonic decays account for significant , and the
leptons provide a final state with low SM backgrounds. In the
$\text{T8}\PQb\PQb\ell\ell\PGn\PGn$ model (Fig. 1, right), both top squarks
decay via an intermediate chargino to a bottom quark, a slepton, and a
neutrino. The branching fraction of the chargino to sleptons is assumed to be
identical for the three slepton flavors. The subsequent decay of the sleptons
to neutralinos and leptons leads to a final state with the same particle
content as in the T2 model, albeit without the suppression of the dilepton
final state from the leptonic boson branching fraction.

Searches for top squark production have been performed by the ATLAS [25, 26,
27, 28, 29, 30, 31, 32] and CMS [33, 34, 35, 36, 37, 38, 39, 40]
Collaborations using 8 and 13$\Pp\Pp$ collision data. These searches disfavor
top squark masses below about 1.1–1.3in a wide variety of production and decay
scenarios. Here we present a search for top squark pair production in dilepton
final states. With respect to a previous search in this final state [38],
improved methods to suppress and estimate backgrounds from SM processes and a
factor of about four larger data set increase the expected sensitivity by
about 125in the mass. This search complements recent searches for top squark
production in other final states [39, 40], in particular in scenarios with a
compressed mass spectrum or final states with a single lepton.

Figure 1:  Diagrams for simplified SUSY models with strong production of top
squark pairs $\PSQtDo\PASQt_{1}$. In the T2 model (left), the top squark
decays to a top quark and a . In the T2 model (center), the top squark decays
into a bottom quark and an intermediate that further decays into a boson and a
. The decay of the intermediate , which yields a , plus a and a $\ell^{\pm}$
from the decay of an intermediate slepton $\widetilde{\ell}^{\pm}$, is
described by the $\text{T8}\PQb\PQb\ell\ell\PGn\PGn$ model (right).

##  0.2 The CMS detector

The central feature of the CMS apparatus is a superconducting solenoid of 6m
internal diameter, providing a magnetic field of 3.8T. Within the solenoid
volume are a silicon pixel and strip tracker, a lead tungstate crystal
electromagnetic calorimeter (ECAL), and a brass and scintillator hadron
calorimeter, each composed of a barrel and two endcap sections. Forward
calorimeters extend the pseudorapidity ($\eta$) coverage provided by the
barrel and endcap detectors that improve the measurement of the imbalance in
transverse momentum. Muons are detected in gas-ionization chambers embedded in
the steel flux-return yoke outside the solenoid.

Events of interest are selected using a two-tier trigger system. The first
level, composed of custom hardware processors, uses information from the
calorimeters and muon detectors to select events in a fixed time interval of
less than 4$\mu$s. The second level, called the high-level trigger, further
decreases the event rate from around 100kHz to less than 1kHz before data
storage [41]. A more detailed description of the CMS detector, together with a
definition of the coordinate system used and the relevant kinematic variables,
can be found in Ref. [42].

##  0.3 Event samples

The search is performed in a data set collected by the CMS experiment during
the 2016–2018 LHC running periods. Events are selected online by different
trigger algorithms that require the presence of one or two leptons (electrons
or muons). The majority of events are selected with dilepton triggers. The
thresholds of same-flavor (SF) dilepton triggers are 23(electron) or 17(muon)
on the transverse momentum () of the leading lepton, and 12(electron) or
8(muon) on the subleading lepton . Triggers for different-flavor (DF)
dileptons have thresholds of 23on the leading lepton , and 12(electron) or
8(muon) on the subleading lepton . Single lepton triggers with a 24threshold
for muons and with a 27threshold for electrons (32for electrons in the years
2017 and 2018) improve the selection efficiency. The efficiency of this online
selection is measured using observed events that are independently selected
based on the presence of jets and requirements on the . Typical efficiencies
range from 95 to 99%, depending on the and $\eta$ of the two leptons and are
accounted for by corrections applied to simulated events.

Event generator and orders of accuracy for each simulated background process.
Process Cross section Event generator Perturbative normalization order ,
single  NNLO+NNLL v2 NLO $\PQt\PW$ NNLO v1/v2 NLO $\ttbar\PH$ NLO+NLL v2 NLO
Drell–Yan NNLO LO $\ttbar\cPZ$, $\ttbar\PW$, $\cPqt\PZ\Pq$,
$\ttbar\Pgg^{(*)}$, NLO NLO $\PV\PV\PV$, $\PV\PV$ $\cPqt\PH\PW$, $\cPqt\PH\Pq$
NLO LO $\cPqt\PW\PZ$ LO LO

Simulated samples matching the varying conditions for each data taking period
are generated using Monte Carlo (MC) techniques. The production and $t$\- and
$s$-channel single-top-quark background processes are simulated at next-to-
leading order (NLO) with the v2 [43, 44, 45, 46, 47, 48, 49, 50] event
generator, and are normalized to next-to-next-to-leading-order (NNLO) cross
sections, including soft-gluon resummation at next-to-next-to-leading-
logarithmic (NNLL) accuracy [51]. Events with single top quarks produced in
association with bosons ($\PQt\PW$) are simulated with v1 [52] (2016) or v2
(2017–2018), and are normalized to the NNLO cross section [53, 54]. The
$\ttbar\PH$ process is generated with v2 at NLO [55]. Drell–Yan events are
generated with up to four extra partons in the matrix element calculations
with v2.3.3 (2016) and v2.4.2 (2017–2018) [56] at leading order (LO), and the
cross section is computed at NNLO [57]. The $\ttbar\cPZ$, $\ttbar\PW$,
$\cPqt\PZ\Pq$, $\ttbar\Pgg^{(*)}$, and triboson ($\PV\PV\PV$) processes are
generated with at NLO. The cross section of the $\ttbar\cPZ$ process is
computed at NLO in perturbative quantum chromodynamics (QCD) and electroweak
accuracy [58, 59]. The $\ttbar\PH$ process is normalized to a cross section
calculated at NLO+NLL accuracy [60]. The diboson ($\PV\PV$) processes are
simulated with up to one extra parton in the matrix element calculations,
using at NLO. The $\PQt\PW\PZ$, $\PQt\PH\PQq$, and $\PQt\PH\PW$ processes are
generated at LO with . These processes are normalized to the most precise
available cross sections, corresponding to NLO accuracy in most cases. A
summary of the event samples is provided in Table 0.3.

The event generators are interfaced with v8.226 (8.230) [61] using the
CUETP8M1 (CP5) tune [62, 63, 64] for 2016 (2017, 2018) samples to simulate the
fragmentation, parton shower, and hadronization of partons in the initial and
final states, along with the underlying event. The NNPDF parton distribution
functions (PDFs) at different perturbative orders in QCD are used in v3.0 [65]
and v3.1 [66] for 2016 and 2017–18 samples, respectively. Double counting of
the partons generated with and is removed using the MLM [67] and the FxFx [68]
matching schemes for LO and NLO samples, respectively. The events are
subsequently processed with a -based simulation model [69] of the CMS
detector.

The SUSY signal samples are generated with at LO precision, with up to two
extra partons in the matrix element calculations, interfaced with v8.226
(8.230) using the CUETP8M1 (CP2) tune for 2016 (2017, 2018). For the T2 and T2
models, the top squark mass is varied from 200 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, the top squark
mass is varied from 200 to 1600and the mass of the LSP is scanned from 1 to
1200. Similarly to the T2 model, the mass of the chargino is assumed to be
equal to the mean of the top squark and the LSP masses. For the slepton mass,
three values of $x=0.95$, 0.50, 0.05 are chosen in
$m_{\widetilde{\ell}}=x\,(m_{\PSGcpDo}-m_{\PSGczDo})+m_{\PSGczDo}$. The
production cross sections of signal samples are normalized to approximate
NNLO+NNLL accuracy with all other SUSY particles assumed to be heavy and
decoupled [70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82]. The simulation
of the detector response is performed using the CMS fast detector simulation
[83, 84].

All simulated samples include the effects of additional $\Pp\Pp$ collisions in
the same or adjacent bunch crossings (pileup), and are reweighted according to
the observed distribution of the number of interactions per bunch crossing. An
additional correction is applied to account for a mismatch of the simulated
samples and the observed distribution of primary vertices in the 2018 running
period.

##  0.4 Object and event selection

Event reconstruction uses the CMS particle-flow (PF) algorithm [85], which
provides an exclusive set of electron [86], muon [87], charged hadron, neutral
hadron, and photon candidates. These particles are defined with respect to the
primary $\Pp\Pp$ interaction vertex, which is the vertex with the largest
value of summed physics-object $\pt^{2}$. The physics objects are the jets,
clustered using the anti-algorithm [88, 89] with the tracks assigned to
candidate vertices as inputs, and the associated missing transverse momentum,
taken as the negative vector sum of the of those jets. Charged-hadron
candidates not originating from the selected primary vertex in the event are
discarded from the list of reconstructed particles.

Electron candidates are reconstructed using tracking and ECAL information, by
combining the clusters of energy deposits in the ECAL with charged tracks
[86]. 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 and bosons while
rejecting electron candidates originating from jets. To reject electrons
originating from photon conversions inside the detector, electrons are
required to have all possible measurements in the innermost tracker layers and
to be incompatible with any conversion-like secondary vertices. Reconstruction
of muon candidates is done by geometrically matching tracks from measurements
in the muon system and tracker, and fitting them to form a global muon track.
Muons are identified using the quality of the geometrical matching and the
quality of the tracks [87].

In all three running periods, the selected lepton candidates are required to
satisfy $\pt>30\,\allowbreak(20)$for the leading (subleading) lepton, and
$\abs{\eta}<2.4$, and to be isolated. To obtain a measure of isolation for
leptons with $\pt<50\GeV$, a cone with radius $\Delta
R=\sqrt{\smash[b]{(\Delta\eta)}^{2}+\smash[b]{(\Delta\phi)}^{2}}=0.2$ (where
$\phi$ is the azimuthal angle in radians) is constructed around the lepton at
the event vertex. For leptons with $\pt>50\GeV$ the radius is reduced to
$\Delta R=\mathrm{max}(0.05,10\GeV/\pt)$. A lepton is isolated if the scalar
sum of photons and neutral and charged hadrons reconstructed by the PF
algorithm within this cone is less than 20% of the lepton ,
$I_{\text{rel}}<0.2$. The contribution of neutral particles from pileup
interactions is estimated according to the method described in Ref. [86], and
subtracted from the isolation sum. The remaining selection criteria applied to
electrons, muons, and the reconstruction of jets and are described in Ref.
[38]. Jets are clustered from PF candidates using the anti-algorithm with a
distance parameter of $R=0.4$, and are required to satisfy $\pt>30\GeV$,
$\abs{\eta}<2.4$, and quality criteria. A multivariate tagging discriminator
algorithm, DeepCSV [90], is used to identify jets arising from quark
hadronization and decay (jets). The chosen working point has a mistag rate of
approximately 1% for light-flavor jets and a corresponding tagging efficiency
of approximately 70%, depending on jet and $\eta$.

Scale factors are applied to simulated events to take into account differences
between the observed and simulated lepton reconstruction, identification, and
isolation, and tagging efficiencies. Typical corrections are less than 1% per
lepton and less than 10% per -tagged jet.

##  0.5 Search strategy

We select events containing a pair of leptons with opposite charge. The
invariant mass of the lepton pair $m(\ell\ell)$ is required to be greater than
20to 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 $I_{\text{rel}}<0.4$ are rejected. Events with an SF lepton pair
that is consistent with the SM Drell–Yan production are removed by requiring
$\abs{m_{\PZ}-m(\ell\ell)}>15\GeV$, where $m_{\PZ}$ is the mass of the boson.
To further suppress Drell–Yan 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 -tagged jets ($N_{\PQb}$) to be at least one.

We use the significance, denoted as $\mathcal{S}$, to suppress events where
detector effects and misreconstruction of particles from pileup interactions
are the main source of reconstructed . In short, the $\mathcal{S}$ observable
offers an event-by-event assessment of the likelihood that the observed is
consistent with zero. Using a Gaussian parametrization of the resolutions of
the reconstructed objects in the event, the $\mathcal{S}$ observable follows a
$\chi^{2}$-distribution with two degrees of freedom for events with no genuine
[91, 92, 93]. Figure 2 shows the distribution of $\mathcal{S}$ in a
$\PZ\to\ell\ell$ sample, requiring events with two SF leptons with
$\abs{m_{\PZ}-m(\ell\ell)}<15\GeV$, $N_{\text{jets}}\geq 2$ and $N_{\PQb}=0$.
Events with no genuine , such as from the Drell–Yan process, follow a
$\chi^{2}$ distribution with two degrees of freedom. Processes with true such
as or production of two or more or bosons populate high values of the
$\mathcal{S}$ distribution. The algorithm is described in Ref. [93] and
provides stability of event selection efficiency as a function of the pileup
rate. We exploit this property by requiring $\mathcal{S}>12$ in order to
suppress the otherwise overwhelming Drell–Yan background in the SF channel. We
further reduce this background by placing a requirement on the azimuthal
angular separation of and the momentum of the leading (subleading) jet of
$\cos\Delta\phi(\ptmiss,\mathrm{j})<0.80~{}(0.96)$. These criteria reject a
small background of Drell–Yan events with significantly mismeasured jets.

The event preselection is summarized in Table 0.5. The resulting event sample
is dominated by events with top quark pairs that decay to the dilepton final
state.

Figure 2:  Distribution of significance $\mathcal{S}$ in a $\PZ\to\ell\ell$
selection, requiring an SF lepton pair. Points with error bars represent the
data, and the stacked histograms the SM backgrounds predicted as described in
Section 0.6, with uncertainty in the SM prediction indicated by the hatched
area. The red line represents a $\chi^{2}$ distribution with two degrees of
freedom. The last bin includes the overflow events. The lower panel gives the
ratio between the observation and the predicted SM backgrounds. The relative
uncertainty in the SM background prediction is shown as a hatched band.

Overview of the event preselection requirements.  Quantity Requirement
$N_{\mathrm{leptons}}$ $=$ 2 ( or $\mu$), oppositely charged $m(\ell\ell)$ $>$
20 $\abs{m_{\PZ}-m(\ell\ell)}$ $>$ 15, SF only $N_{\text{jets}}$ $\geq$ 2
$N_{\PQb}$ $\geq$ 1 $\mathcal{S}$ $>$ 12
$\cos\Delta\phi(\ptmiss,\mathrm{j}_{1})$ $<$ 0.80
$\cos\Delta\phi(\ptmiss,\mathrm{j}_{2})$ $<$ 0.96

The main search variable in this analysis is [20, 94]

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

where the choice $\ptvec^{\text{vis}1,2}=\ptvec^{\ell 1,2}$ corresponds to the
definition introduced in Ref. [95]. The alternative choice
$\ptvec^{\text{vis}1,2}=\ptvec^{\ell 1,2}+\ptvec^{\PQb 1,2}$ involves the
-tagged jets and defines $M_{\text{T2}}(\PQb\ell\PQb\ell)$. 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 calculation of
$M_{\text{T2}}(\ell\ell)$ and $M_{\text{T2}}(\PQb\ell\PQb\ell)$ is performed
through the algorithm discussed in Ref. [96], assuming vanishing mass for the
undetected particles, and follows the description in Ref. [38]. The key
feature of the $M_{\text{T2}}(\ell\ell)$ observable is that it retains a
kinematic endpoint at the boson mass for background events from the leptonic
decays of two bosons, produced directly or through top quark decay. Similarly,
the $M_{\text{T2}}(\PQb\ell\PQb\ell)$ observable is bound by the top quark
mass if the leptons, neutrinos and -tagged jets originate from the decay of
top quarks. In turn, signal events from the processes depicted in Fig. 1 do
not respect the endpoint and are expected to populate the tails of these
distributions.

Signal regions based on $M_{\text{T2}}(\ell\ell)$,
$M_{\text{T2}}(\PQb\ell\PQb\ell)$ and $\mathcal{S}$ are defined to enhance
sensitivity to different signal scenarios, and are listed in Table 0.5. The
regions are further divided into different categories based on SF or DF lepton
pairs, accounting for the different SM background composition. The signal
regions are defined so that there is no overlap between them, nor with the
background-enriched control regions.

Definition of the signal regions. The regions are further split into SF and DF
regions. The preselection in Table 0.5 is applied to all regions.
$M_{\text{T2}}(\PQb\ell\PQb\ell)$ () $\mathcal{S}$
$100<M_{\text{T2}}(\ell\ell)<140\GeV$ $140<M_{\text{T2}}(\ell\ell)<240\GeV$
$M_{\text{T2}}(\ell\ell)>240\GeV$ 0–100 12–50 SR0 SR6 SR12 $>$50 SR1 SR7
100–200 12–50 SR2 SR8 $>$50 SR3 SR9 $>$200 12–50 SR4 SR10 $>$50 SR5 SR11

##  0.6 Background predictions

Events with an opposite-charge lepton pair are abundantly produced by
Drell–Yan and processes. The event selection discussed in Section 0.4
efficiently rejects the vast majority of Drell–Yan events. Therefore, the
major backgrounds from SM processes in the search regions are /events that
pass the $M_{\text{T2}}(\ell\ell)$ threshold because of severely mismeasured
or a misidentified lepton. In signal regions with large
$M_{\text{T2}}(\ell\ell)$ and $\mathcal{S}$ requirements, $\ttbar\cPZ$ events
with $\PZ\to\cPgn\cPagn$ are the main SM background. Remaining Drell–Yan
events with large from mismeasurement, multiboson production and other /single
processes in association with a , a or a Higgs boson ($\ttbar\PW$,
$\PQt\PQq\cPZ$ or $\ttbar\PH$) are sources of smaller contributions. The
background estimation procedures and their corresponding control regions,
listed in Table 0.6, are discussed in the following.

Definition of the control regions. The preselection in Table 0.5 is applied to
all regions.  Name Definition TTCRSF $M_{\text{T2}}(\ell\ell)<100\GeV$, SF
leptons, $\abs{m(\ell\ell)-m_{\PZ}}>15\GeV$ TTCRDF
$M_{\text{T2}}(\ell\ell)<100\GeV$, DF leptons TTZ2j2b $N_{\text{jets}}=2$,
$N_{\PQb}\geq 2$ TTZ3j1b $N_{\ell}=3$, $\mathcal{S}\geq 0$, $\geq 1$ SF lepton
pair $N_{\text{jets}}=3$, $N_{\PQb}=1$ TTZ3j2b with
$\abs{m(\ell\ell)-m_{\PZ}}<10\GeV$ $N_{\text{jets}}=3$, $N_{\PQb}\geq 2$
TTZ4j1b $N_{\text{jets}}\geq 4$, $N_{\PQb}=1$ TTZ4j2b $N_{\text{jets}}\geq 4$,
$N_{\PQb}\geq 2$ CR0-CR12 Same as SR0-SR12 in Table 0.5 but requiring SF
leptons, $\abs{m(\ell\ell)-m_{\PZ}}<15\GeV$, $N_{\PQb}=0$, and without the
$\cos\Delta\phi(\ptmiss,\mathrm{j})$ requirements given in Table 0.5.

###  0.6.1 Top quark background

Events from the process are contained in the $M_{\text{T2}}(\ell\ell)<100\GeV$
region, as long as the jets and leptons in each event are identified and their
momenta are precisely measured. Three main sources are identified that promote
events into the tail of the $M_{\text{T2}}(\ell\ell)$ distribution. Firstly,
the jet momentum resolution is approximately Gaussian [97] and jet
mismeasurements propagate to , which subsequently leads to values of
$M_{\text{T2}}(\ell\ell)$ and $M_{\text{T2}}(\PQb\ell\PQb\ell)$ that do not
obey the endpoint at the mother particle mass. For events with
$M_{\text{T2}}(\ell\ell)\leq 140\GeV$, this component is dominant, while it
amounts to less than 10% for signal regions with
$M_{\text{T2}}(\ell\ell)>140\GeV$. Secondly, significant mismeasurements of
the momentum of jets can be caused by the loss of photons and neutral hadrons
showering in masked channels of the calorimeters, or neutrinos with high
within jets. For $M_{\text{T2}}(\ell\ell)>140\GeV$, up to 50% of the top quark
background falls into this category. The predicted rate and kinematic modeling
of these rare non-Gaussian effects in simulation are checked in a control
region requiring SF leptons satisfying $\abs{m(\ell\ell)-m_{\PZ}}<15\GeV$. A
30% uncertainty covers differences in the tails of the distribution observed
in this control region.

Finally, an electron or a muon may fail the identification requirements, or
the event may have a $\tau$ lepton produced in a boson decay. If there is a
nonprompt lepton from the hadronization of a bottom 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 W 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 the observed and simulated samples. Since the transverse
momentum balance is not significantly changed by the lepton misidentification,
the and $\mathcal{S}$ observables are not modified. Events with misidentified
electrons or muons from this category constitute up to 40% of the top quark
background prediction for $M_{\text{T2}}(\ell\ell)>140\GeV$. We see good
agreement between the observed and simulated kinematic distributions,
indicating that the simulation describes such backgrounds well. Based on the
statistical precision in the highest $M_{\text{T2}}(\ell\ell)$ regions, we
assign a 50% uncertainty to this contribution.

The normalization is measured in situ by including a signal-depleted control
region defined by $M_{\text{T2}}(\ell\ell)<100\GeV$ in the signal extraction
fit, yielding a scale factor for the prediction of $1.02\pm 0.04$. The region
is split into DF (TTCRDF) and SF channels (TTCRSF). Events with a boson
candidate are rejected in the latter.

###  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, if the boson
decays to leptons or neutrinos. The $\PZ\to\cPgn\cPagn$ decay in the
$\ttbar\cPZ$ process provides genuine and is the dominant background component
at high values of $M_{\text{T2}}(\ell\ell)$. The decay mode
$\ttbar\cPZ\to(\cPqb\ell^{\pm}\cPgn)(\PQb\text{jj})(\ell^{\pm}\ell^{\mp})$ is
used to measure the normalization of this contribution. The leading,
subleading, and trailing lepton are required to satisfy thresholds of $40$,
$20$, and $20\GeV$, respectively. The invariant mass of two SF leptons with
opposite charge is required to satisfy the tightened requirement
$\abs{m(\ell\ell)-m_{\PZ}}<10\GeV$. The shape of the distribution of
$\pt(\PZ)$ has recently been measured in the 2016 and 2017 data sets [98] and
is well described by simulation. Five control regions requiring different
$N_{\text{jets}}$ and $N_{\PQb}$ combinations are defined in Table 0.6 and
labeled TTZ2j2b–TTZ4j2b. They are included in the signal extraction fit, in
which the simulated number of $\ttbar\cPZ$ events is found to be scaled up by
a factor of $1.22\pm 0.25$, consistent with the initial prediction.

###  0.6.3 Drell–Yan and multiboson backgrounds

In order to measure the small residual Drell–Yan contribution that passes the
event selection, we select dilepton events according to the criteria listed in
Table 0.5 except that we invert the boson veto, the jet requirements, and
remove the angular separation requirements on jets and . We expect from the
simulation that the selection is dominated by the Drell–Yan and multiboson
events. For each SF 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
$\mathcal{S}$. The regions are labeled CR0–CR12 in Table 0.6 and are included
in the signal extraction fit. The $M_{\text{T2}}(\PQb\ell\PQb\ell)$ observable
is calculated in these regions using the two highest jets. The scale factors
for the Drell–Yan and multiboson background components are found to be
$1.18\pm 0.28$ and $1.35\pm 0.32$, respectively.

The good modeling of the multiboson and processes, including potential sources
of anomalous , is demonstrated in a validation region requiring
$N_{\text{jets}}\geq 2$ and $N_{\PQb}=0$ and combining the SF and DF channels.
The observed distributions of the search variables are compared with the
simulated distributions in Fig. 3. The hatched band includes the experimental
systematic uncertainties and the uncertainties in the background
normalizations.

Figure 3:  The $M_{\text{T2}}(\ell\ell)$, $M_{\text{T2}}(\PQb\ell\PQb\ell)$,
and $\mathcal{S}$ distributions in the validation regions requiring
$N_{\text{jets}}\geq 2$ and $N_{\PQb}=0$, combining the SF and DF channels.
All other event selection requirements are applied. For the
$M_{\text{T2}}(\PQb\ell\PQb\ell)$ and $\mathcal{S}$ distributions,
$M_{\text{T2}}(\ell\ell)>100\GeV$ is required. The individual processes are
scaled using their measured respective scale factors, as described in the
text. The hatched band represents the experimental systematic uncertainties
and the uncertainties in the scale factors. The last bin in each distribution
includes the overflow events. The lower panel gives the ratio between the
observation and the predicted SM backgrounds. The relative uncertainty in the
SM background prediction is shown as a hatched band.

##  0.7 Systematic uncertainties

Several experimental uncertainties affect the signal and background yield
estimations. The efficiency of the trigger selection ranges from 95 to 99%
with uncertainties lower than 2.3% in all signal and control regions. Offline
lepton reconstruction and selection efficiencies are measured using
$\PZ\to\ell\ell$ events in bins of lepton and $\eta$. These measurements are
performed separately in the observed and simulated data sets, with efficiency
values ranging from 70 to 80%. Scale factors are used to correct the
efficiencies measured in simulated events to those in the observed data. The
uncertainties in these scale factors are less than 3% per lepton and less than
5% 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 4%, except in the lowest regions in
$M_{\text{T2}}(\ell\ell)$ close to the $m_{\PW}$ threshold where it can be as
high as 20%. 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 7%. The tagging efficiency in the simulation is
corrected using scale factors determined from the observed data [90], and
uncertainties are propagated to all simulated events. These contribute an
uncertainty of up to 7% in the predicted yields, depending on the , $\eta$ and
origin of the -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.

The uncertainties in the normalizations of the single top and , $\ttbar\cPZ$,
Drell–Yan, and multiboson backgrounds are discussed in Section 0.6. Finally,
the uncertainty in the integrated luminosity is 2.3–2.5% [99, 100, 101].

Additional systematic uncertainties affect the modeling in simulation of the
various processes, discussed in the following. 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 5% in the expected yields.

For the and $\ttbar\cPZ$ backgrounds, we determine the event yield changes
resulting from varying the renormalization scale ($\mu_{\mathrm{R}}$) and the
factorization scale ($\mu_{\mathrm{F}}$) up and down by a factor of two, while
keeping the overall normalization constant. The combinations of variations in
opposite directions are disregarded. We assign as the uncertainty the envelope
of the considered yield variations, treated as uncorrelated among 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—less than 4%—as a correlated uncertainty [102].

The contributions to the total uncertainty in the estimated backgrounds are
summarized in Table 0.7, which provides the maximum uncertainties over all
signal regions and the typical values, defined as the 90% quantile of the
uncertainty values in all signal regions.

Typical values (90% quantiles) and maximum values of the systematic
uncertainties in all signal regions.  Systematic uncertainty Typical (%) Max
(%) Integrated luminosity $2$ $2$ Pileup modeling $5$ $7$ Jet energy scale $4$
$20$ Jet energy resolution $3$ $4$ tagging efficiency $2$ $3$ tagging mistag
rate $1$ $7$ Trigger efficiency $1$ $2$ Lepton identification efficiency $3$
$5$ Modeling of unclustered energy $3$ $7$ Non-Gaussian jet mismeasurements
$6$ $6$ Misidentified or nonprompt leptons $5$ $5$ normalization $9$ $9$
$\ttbar\cPZ$ normalization $10$ $14$ Multiboson background normalization $4$
$8$ $\ttbar\PH$/background normalization $5$ $8$ Drell–Yan normalization $3$
$8$ Parton distribution functions $2$ $4$ $\mu_{\mathrm{R}}$ and
$\mu_{\mathrm{F}}$ choice $7$ $11$

For the small contribution from 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 generator scales and the PDFs.

Most of the sources of systematic uncertainty 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 $\mu_{\mathrm{R}}$ and $\mu_{\mathrm{F}}$ [103, 104,
105] and find that those uncertainties are below 10%. 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 based on the number of ISR jets ($N_{\mathrm{J}}^{\text{ISR}}$)
so as to make the predicted jet multiplicity distribution agree with that
observed. The comparison is performed in a sample of events requiring two
leptons and two -tagged jets. The reweighting procedure is applied to SUSY MC
events and factors vary between 0.92 and 0.51 for
$N_{\mathrm{J}}^{\text{ISR}}$ 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 is evaluated by comparing the reconstructed
with the obtained using generator-level information. This uncertainty ranges
up to 20% and only affects the SUSY signal samples. For these samples, the
scale factors and uncertainties for the tagging efficiency of jets and leptons
are evaluated separately. Typical uncertainties in the scale factors are below
2% for -tagged jets, and between 1 and 7% for leptons.

##  0.8 Results

Figure 4:  Distributions of $M_{\text{T2}}(\ell\ell)$ (left),
$M_{\text{T2}}(\PQb\ell\PQb\ell)$ (middle), and $\mathcal{S}$ (right) for all
lepton flavors for the preselection 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 $\mathcal{S}$ distributions. The last
bin in each distribution includes the overflow events. The lower panel gives
the ratio between the observation and the predicted SM backgrounds and the
relative uncertainty in the SM background prediction is shown as a hatched
band.

Good agreement between the SM-predicted and observed
$M_{\text{T2}}(\ell\ell)$, $M_{\text{T2}}(\PQb\ell\PQb\ell)$, and
$\mathcal{S}$ distributions is found, as shown in Fig. 4. No significant
deviation from the SM prediction is observed in any of the signal regions as
shown in Fig. 5. The observed excess events in SR10SF are found to be close to
the signal region selection thresholds. To perform the statistical
interpretations, a likelihood function is formed with Poisson probability
functions for all data regions. The control and signal regions as depicted in
Fig. 5 are included. The correlations of the uncertainties are taken into
account as described in Section 0.7. A profile likelihood ratio in the
asymptotic approximation [106] is used as the test statistic. Upper limits on
the production cross section are calculated at 95% confidence level (CL)
according to the asymptotic criterion [107, 108].

Figure 5:  Predicted and observed yields in the signal and control regions as
defined in Tables 0.5 and 0.6. The control regions TTCRSF and TTCRDF are
defined by $M_{\text{T2}}(\ell\ell)<100\GeV$ and are used to constrain the
normalization. The $\ttbar\cPZ$ control regions employ a 3 lepton requirement
in different $N_{\text{jets}}$ and $N_{\PQb}$ bins. The dilepton invariant
mass and $N_{\PQb}$ selections are inverted for CR0–CR12 in order to constrain
the Drell–Yan and multiboson normalizations, using only the SF channel. The
lower panel gives the ratio between the observation and the predicted SM
backgrounds. The hatched band reflects the post-fit systematic uncertainties.

The results shown in Fig. 5 are interpreted in the context of simplified SUSY
models of top squark production followed by a decay to top quarks and
neutralinos (T2), via an intermediate chargino (T2), and via an additional
intermediate slepton ($\text{T8}\PQb\PQb\ell\ell\PGn\PGn$). These
interpretations are presented on the $m_{\PSQtDo}$-$m_{\PSGczDo}$ plane in
Figs. 6 and 7. The color on the $z$ axis indicates the 95% CL upper limit on
the cross section 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 for the decays of the SUSY particles.
The thick dashed red lines indicate the expected limit at 95% CL, while the
region containing 68% of the distribution of limits expected under the
background-only hypothesis is bounded by thin dashed red lines. 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 450and $m_{\PSQtDo}$ up to 925, assuming that the top quarks are
unpolarized, thus improving by approximately 125in $m_{\PSQtDo}$ the results
presented on a partial data set in Ref. [38]. The observed upper limit on the
top squark cross section improved by approximately 50% for most mass
configurations. The result for the T2 model is shown in Fig. 6 (right) and the
results for $\text{T8}\PQb\PQb\ell\ell\PGn\PGn$ models are shown in Fig. 7. We
exclude mass configurations with $m_{\PSGczDo}$ up to 420and $m_{\PSQtDo}$ up
to 850in the T2 model, extending the exclusion limits set in Ref. [38] by
approximately 100in $m_{\PSQtDo}$. 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
$m_{\widetilde{\ell}}=x\,(m_{\PSGcpDo}-m_{\PSGczDo})+m_{\PSGczDo}$. In this
case, excluded masses reach up to 900for $m_{\PSGczDo}$ and 1.4for
$m_{\PSQtDo}$. These upper limits decrease to 750for $m_{\PSGczDo}$ and 1.3for
$m_{\PSQtDo}$ when $x=0.5$ and to 100for $m_{\PSGczDo}$ and 1.2for
$m_{\PSQtDo}$ when $x=0.05$. In this model, the improvement upon previous
results from Ref. [38] is approximately 100in $m_{\PSQtDo}$, and up to 100in
$m_{\PSGczDo}$.

Figure 6: 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 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 for the decays of the SUSY particles, 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 small white area on the diagonal in the left figure
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 7: Expected and observed limits for the
$\text{T8}\PQb\PQb\ell\ell\PGn\PGn$ model with
$\PSQtDo\to\PQb\PSGcpDo\to\PQb\PGn\widetilde{\ell}\to\PQb\PGn\ell\PSGczDo$
decays in the $m_{\PSQtDo}$-$m_{\PSGczDo}$ mass plane for three different mass
configurations defined by
$m_{\widetilde{\ell}}=x\,(m_{\PSGcpDo}-m_{\PSGczDo})+m_{\PSGczDo}$ with
$x=0.05$ (upper left), $x=0.50$ (upper right), and $x=0.95$ (lower). The
description of curves is the same as in the caption of Fig. 6.

##  0.9 Summary

A search for top squark pair production in final states with two opposite-
charge leptons, jets, and significant missing transverse momentum () is
presented. The data set of proton-proton collisions corresponds to an
integrated luminosity of 137and was collected with the CMS detector at a
center-of-mass energy of 13. Transverse mass variables and the significance of
are used to efficiently suppress backgrounds from standard model processes. No
evidence for a deviation from the expected background is observed. The results
are interpreted in several simplified models for supersymmetric top squark
pair production and decay.

In the T2 model with $\PSQtDo\to\PQt\PSGczDo$ decays, $\PSQtDo$ masses up to
925and $\PSGczDo$ masses up to 450are excluded. In the T2 model with
$\PSQtDo\to\PQb\PSGcpDo\to\PQb\PWp\PSGczDo$ decays, $\PSQtDo$ masses up to
850and $\PSGczDo$ masses up to 420are excluded, assuming the chargino mass to
be the mean of the $\PSQtDo$ and $\PSGczDo$ masses. In the
$\text{T8}\PQb\PQb\ell\ell\PGn\PGn$ model with decays
$\PSQtDo\to\PQb\PSGcpDo\to\PQb\PGn\widetilde{\ell}\to\PQb\PGn\ell\PSGczDo$,
therefore 100% branching fraction 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 $\PSGczDo$ masses, the strongest
exclusion is obtained if the slepton mass is close to the chargino mass. In
this case, excluded masses reach up to 1.4for $\PSQtDo$ and 900for $\PSGczDo$.
When the slepton mass is taken as the mean of the chargino and neutralino
masses, these numbers decrease to 1.3for $\PSQtDo$ and 750for $\PSGczDo$. A
further reduction to 1.2for $\PSQtDo$ and to 100for $\PSGczDo$ is observed
when the slepton mass is close to the neutralino mass.

###### 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: BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq,
CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST,
and NSFC (China); COLCIENCIAS (Colombia); MSES and CSF (Croatia); RIF
(Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, PUT and ERDF (Estonia); Academy
of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG,
and HGF (Germany); GSRT (Greece); NKFIA (Hungary); DAE and DST (India); IPM
(Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES
(Latvia); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT,
LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC
(Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom,
RAS, RFBR, and NRC KI (Russia); MESTD (Serbia); SEIDI, CPAN, PCTI, and FEDER
(Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST
(Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK
(Turkey); NASU (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 Nos. 675440,
752730, and 765710 (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 F.R.S.-FNRS and FWO (Belgium)
under the “Excellence of Science – EOS” – be.h project n. 30820817; the
Beijing Municipal Science & Technology Commission, No. Z191100007219010; the
Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the
Deutsche Forschungsgemeinschaft (DFG) under Germany’s Excellence Strategy –
EXC 2121 “Quantum Universe” – 390833306; the Lendület (“Momentum”) Program and
the János Bolyai Research Scholarship of the Hungarian Academy of Sciences,
the New National Excellence Program ÚNKP, the NKFIA research grants 123842,
123959, 124845, 124850, 125105, 128713, 128786, and 129058 (Hungary); 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 Ministry of Science and
Higher Education, project no. 02.a03.21.0005 (Russia); the Programa Estatal de
Fomento de la Investigación Científica y Técnica de Excelencia María de
Maeztu, grant MDM-2015-0509 and 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 Kavli Foundation; the Nvidia Corporation;
the SuperMicro Corporation; 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${}^{\textrm{\textdagger}}$, A. Tumasyan Institut für
Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, T. Bergauer, M. Dragicevic, J. Erö, A. Escalante Del
Valle, R. Frühwirth1, M. Jeitler1, N. Krammer, L. Lechner, D. Liko, T.
Madlener, I. Mikulec, F.M. Pitters, N. Rad, J. Schieck1, R. Schöfbeck, M.
Spanring, S. Templ, W. Waltenberger, C.-E. Wulz1, M. Zarucki Institute for
Nuclear Problems, Minsk, Belarus
V. Chekhovsky, A. Litomin, V. Makarenko, J. Suarez Gonzalez Universiteit
Antwerpen, Antwerpen, Belgium
M.R. Darwish2, E.A. De Wolf, D. Di Croce, X. Janssen, T. Kello3, A. Lelek, M.
Pieters, H. Rejeb Sfar, H. Van Haevermaet, P. Van Mechelen, S. Van Putte, N.
Van Remortel Vrije Universiteit Brussel, Brussel, Belgium
F. Blekman, E.S. Bols, S.S. Chhibra, J. D’Hondt, J. De Clercq, D. Lontkovskyi,
S. Lowette, I. Marchesini, S. Moortgat, A. Morton, Q. Python, S. Tavernier, W.
Van Doninck, P. Van Mulders Université Libre de Bruxelles, Bruxelles, Belgium
D. Beghin, B. Bilin, B. Clerbaux, G. De Lentdecker, B. Dorney, L. Favart, A.
Grebenyuk, A.K. Kalsi, I. Makarenko, L. Moureaux, L. Pétré, A. Popov, N.
Postiau, E. Starling, L. Thomas, C. Vander Velde, P. Vanlaer, D. Vannerom, L.
Wezenbeek Ghent University, Ghent, Belgium
T. Cornelis, D. Dobur, M. Gruchala, I. Khvastunov4, M. Niedziela, C. Roskas,
K. Skovpen, M. Tytgat, W. Verbeke, B. Vermassen, M. Vit Université Catholique
de Louvain, Louvain-la-Neuve, Belgium
G. Bruno, F. Bury, C. Caputo, P. David, C. Delaere, M. Delcourt, I.S.
Donertas, A. Giammanco, V. Lemaitre, K. Mondal, J. Prisciandaro, A. Taliercio,
M. Teklishyn, P. Vischia, S. Wuyckens, J. Zobec Centro Brasileiro de Pesquisas
Fisicas, Rio de Janeiro, Brazil
G.A. Alves, G. Correia Silva, C. Hensel, A. Moraes Universidade do Estado do
Rio de Janeiro, Rio de Janeiro, Brazil
W.L. Aldá Júnior, E. Belchior Batista Das Chagas, H. BRANDAO MALBOUISSON, W.
Carvalho, J. Chinellato5, E. Coelho, E.M. Da Costa, G.G. Da Silveira6, D. De
Jesus Damiao, S. Fonseca De Souza, J. Martins7, D. Matos Figueiredo, M. Medina
Jaime8, M. Melo De Almeida, C. Mora Herrera, L. Mundim, H. Nogima, P. Rebello
Teles, L.J. Sanchez Rosas, A. Santoro, S.M. Silva Do Amaral, A. Sznajder, M.
Thiel, E.J. Tonelli Manganote5, F. Torres Da Silva De Araujo, A. Vilela
Pereira Universidade Estadual Paulista a, Universidade Federal do ABC b, São
Paulo, Brazil
C.A. Bernardesa, L. Calligarisa, T.R. Fernandez Perez Tomeia, E.M. Gregoresb,
D.S. Lemosa, P.G. Mercadanteb, S.F. Novaesa, Sandra S. Padulaa Institute for
Nuclear Research and Nuclear Energy, Bulgarian Academy of Sciences, Sofia,
Bulgaria
A. Aleksandrov, G. Antchev, I. Atanasov, R. Hadjiiska, P. Iaydjiev, M.
Misheva, M. Rodozov, M. Shopova, G. Sultanov University of Sofia, Sofia,
Bulgaria
M. Bonchev, A. Dimitrov, T. Ivanov, L. Litov, B. Pavlov, P. Petkov, A. Petrov
Beihang University, Beijing, China
W. Fang3, Q. Guo, H. Wang, L. Yuan Department of Physics, Tsinghua University,
Beijing, China
M. Ahmad, Z. Hu, Y. Wang Institute of High Energy Physics, Beijing, China
E. Chapon, G.M. Chen9, H.S. Chen9, M. Chen, A. Kapoor, D. Leggat, H. Liao, Z.
Liu, R. Sharma, A. Spiezia, J. Tao, J. Thomas-wilsker, J. Wang, H. Zhang, S.
Zhang9, J. Zhao State Key Laboratory of Nuclear Physics and Technology, Peking
University, Beijing, China
A. Agapitos, Y. Ban, C. Chen, Q. Huang, A. Levin, Q. Li, M. Lu, X. Lyu, Y.
Mao, S.J. Qian, D. Wang, Q. Wang, J. Xiao Sun Yat-Sen University, Guangzhou,
China
Z. You Institute of Modern Physics and Key Laboratory of Nuclear Physics and
Ion-beam Application (MOE) - Fudan University, Shanghai, China
X. Gao3 Zhejiang University, Hangzhou, China
M. Xiao Universidad de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, C. Florez, J. Fraga, A. Sarkar, M.A. Segura Delgado
Universidad de Antioquia, Medellin, Colombia
J. Jaramillo, J. Mejia Guisao, F. Ramirez, J.D. Ruiz Alvarez, C.A. Salazar
González, N. Vanegas Arbelaez University of Split, Faculty of Electrical
Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia
D. Giljanovic, N. Godinovic, D. Lelas, I. Puljak, T. Sculac University of
Split, Faculty of Science, Split, Croatia
Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia
V. Brigljevic, D. Ferencek, D. Majumder, M. Roguljic, A. Starodumov10, T. Susa
University of Cyprus, Nicosia, Cyprus
M.W. Ather, A. Attikis, E. Erodotou, A. Ioannou, G. Kole, M. Kolosova, S.
Konstantinou, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A.
Razis, H. Rykaczewski, H. Saka, D. Tsiakkouri Charles University, Prague,
Czech Republic
M. Finger11, M. Finger Jr.11, A. Kveton, J. Tomsa Escuela Politecnica
Nacional, Quito, Ecuador
E. Ayala 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
H. Abdalla12, Y. Assran13,14, S. Khalil15 Center for High Energy Physics
(CHEP-FU), Fayoum University, El-Fayoum, Egypt
M.A. Mahmoud, Y. Mohammed16 National Institute of Chemical Physics and
Biophysics, Tallinn, Estonia
S. Bhowmik, A. Carvalho Antunes De Oliveira, R.K. Dewanjee, K. Ehataht, M.
Kadastik, M. Raidal, C. Veelken Department of Physics, University of Helsinki,
Helsinki, Finland
P. Eerola, L. Forthomme, H. Kirschenmann, K. Osterberg, M. Voutilainen
Helsinki Institute of Physics, Helsinki, Finland
E. Brücken, F. Garcia, J. Havukainen, V. Karimäki, M.S. Kim, R. Kinnunen, T.
Lampén, K. Lassila-Perini, S. Laurila, S. Lehti, T. Lindén, H. Siikonen, E.
Tuominen, J. Tuominiemi Lappeenranta University of Technology, Lappeenranta,
Finland
P. Luukka, T. Tuuva IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
C. Amendola, M. Besancon, F. Couderc, M. Dejardin, D. Denegri, J.L. Faure, F.
Ferri, S. Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry,
B. Lenzi, E. Locci, J. Malcles, J. Rander, A. Rosowsky, M.Ö. Sahin, A. Savoy-
Navarro17, M. Titov, G.B. Yu Laboratoire Leprince-Ringuet, CNRS/IN2P3, Ecole
Polytechnique, Institut Polytechnique de Paris, Paris, France
S. Ahuja, F. Beaudette, M. Bonanomi, A. Buchot Perraguin, P. Busson, C.
Charlot, O. Davignon, B. Diab, G. Falmagne, R. Granier de Cassagnac, A.
Hakimi, I. Kucher, A. Lobanov, C. Martin Perez, M. Nguyen, C. Ochando, P.
Paganini, J. Rembser, R. Salerno, J.B. Sauvan, Y. Sirois, A. Zabi, A. Zghiche
Université de Strasbourg, CNRS, IPHC UMR 7178, Strasbourg, France
J.-L. Agram18, J. Andrea, D. Bloch, G. Bourgatte, J.-M. Brom, E.C. Chabert, C.
Collard, J.-C. Fontaine18, D. Gelé, U. Goerlach, C. Grimault, A.-C. Le Bihan,
P. Van Hove Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3,
Institut de Physique Nucléaire de Lyon, Villeurbanne, France
E. Asilar, S. Beauceron, C. Bernet, G. Boudoul, C. Camen, A. Carle, N. Chanon,
D. Contardo, P. Depasse, H. El Mamouni, J. Fay, S. Gascon, M. Gouzevitch, B.
Ille, Sa. Jain, I.B. Laktineh, H. Lattaud, A. Lesauvage, M. Lethuillier, L.
Mirabito, L. Torterotot, G. Touquet, M. Vander Donckt, S. Viret Georgian
Technical University, Tbilisi, Georgia
I. Bagaturia19, Z. Tsamalaidze11 RWTH Aachen University, I. Physikalisches
Institut, Aachen, Germany
L. Feld, K. Klein, M. Lipinski, D. Meuser, A. Pauls, M. Preuten, M.P. Rauch,
J. Schulz, M. Teroerde RWTH Aachen University, III. Physikalisches Institut A,
Aachen, Germany
D. Eliseev, M. Erdmann, P. Fackeldey, B. Fischer, S. Ghosh, T. Hebbeker, K.
Hoepfner, H. Keller, L. Mastrolorenzo, M. Merschmeyer, A. Meyer, P. Millet, G.
Mocellin, S. Mondal, S. Mukherjee, D. Noll, A. Novak, T. Pook, A. Pozdnyakov,
T. Quast, M. Radziej, Y. Rath, H. Reithler, J. Roemer, A. Schmidt, S.C.
Schuler, A. Sharma, S. Wiedenbeck, S. Zaleski RWTH Aachen University, III.
Physikalisches Institut B, Aachen, Germany
C. Dziwok, G. Flügge, W. Haj Ahmad20, O. Hlushchenko, T. Kress, A. Nowack, C.
Pistone, O. Pooth, D. Roy, H. Sert, A. Stahl21, T. Ziemons Deutsches
Elektronen-Synchrotron, Hamburg, Germany
H. Aarup Petersen, M. Aldaya Martin, P. Asmuss, I. Babounikau, S. Baxter, O.
Behnke, A. Bermúdez Martínez, A.A. Bin Anuar, K. Borras22, V. Botta, D.
Brunner, A. Campbell, A. Cardini, P. Connor, S. Consuegra Rodríguez, V.
Danilov, A. De Wit, M.M. Defranchis, L. Didukh, D. Domínguez Damiani, G.
Eckerlin, D. Eckstein, T. Eichhorn, L.I. Estevez Banos, E. Gallo23, A. Geiser,
A. Giraldi, A. Grohsjean, M. Guthoff, A. Harb, A. Jafari24, N.Z. Jomhari, H.
Jung, A. Kasem22, M. Kasemann, H. Kaveh, C. Kleinwort, J. Knolle, D. Krücker,
W. Lange, T. Lenz, J. Lidrych, K. Lipka, W. Lohmann25, R. Mankel, I.-A.
Melzer-Pellmann, J. Metwally, A.B. Meyer, M. Meyer, M. Missiroli, J. Mnich, A.
Mussgiller, V. Myronenko, Y. Otarid, D. Pérez Adán, S.K. Pflitsch, D. Pitzl,
A. Raspereza, A. Saggio, A. Saibel, M. Savitskyi, V. Scheurer, P. Schütze, C.
Schwanenberger, A. Singh, R.E. Sosa Ricardo, N. Tonon, O. Turkot, A.
Vagnerini, M. Van De Klundert, R. Walsh, D. Walter, Y. Wen, K. Wichmann, C.
Wissing, S. Wuchterl, O. Zenaiev, R. Zlebcik University of Hamburg, Hamburg,
Germany
R. Aggleton, S. Bein, L. Benato, A. Benecke, K. De Leo, T. Dreyer, A.
Ebrahimi, M. Eich, F. Feindt, A. Fröhlich, C. Garbers, E. Garutti, P.
Gunnellini, J. Haller, A. Hinzmann, A. Karavdina, G. Kasieczka, R. Klanner, R.
Kogler, V. Kutzner, J. Lange, T. Lange, A. Malara, C.E.N. Niemeyer, A.
Nigamova, K.J. Pena Rodriguez, O. Rieger, P. Schleper, S. Schumann, J.
Schwandt, D. Schwarz, J. Sonneveld, H. Stadie, G. Steinbrück, B. Vormwald, I.
Zoi Karlsruher Institut fuer Technologie, Karlsruhe, Germany
M. Baselga, S. Baur, J. Bechtel, T. Berger, E. Butz, R. Caspart, T. Chwalek,
W. De Boer, A. Dierlamm, A. Droll, K. El Morabit, N. Faltermann, K. Flöh, M.
Giffels, A. Gottmann, F. Hartmann21, C. Heidecker, U. Husemann, M.A. Iqbal, I.
Katkov26, P. Keicher, R. Koppenhöfer, S. Maier, M. Metzler, S. Mitra, D.
Müller, Th. Müller, M. Musich, G. Quast, K. Rabbertz, J. Rauser, D. Savoiu, D.
Schäfer, M. Schnepf, M. Schröder, D. Seith, I. Shvetsov, H.J. Simonis, R.
Ulrich, M. Wassmer, M. Weber, R. Wolf, S. Wozniewski Institute of Nuclear and
Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece
G. Anagnostou, P. Asenov, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas,
G. Paspalaki, A. Stakia National and Kapodistrian University of Athens,
Athens, Greece
M. Diamantopoulou, D. Karasavvas, G. Karathanasis, P. Kontaxakis, C.K. Koraka,
A. Manousakis-katsikakis, A. Panagiotou, I. Papavergou, N. Saoulidou, K.
Theofilatos, K. Vellidis, E. Vourliotis National Technical University of
Athens, Athens, Greece
G. Bakas, K. Kousouris, I. Papakrivopoulos, G. Tsipolitis, A. Zacharopoulou
University of Ioánnina, Ioánnina, Greece
I. Evangelou, C. Foudas, P. Gianneios, P. Katsoulis, P. Kokkas, S. Mallios, K.
Manitara, N. Manthos, I. Papadopoulos, J. Strologas MTA-ELTE Lendület CMS
Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest,
Hungary
M. Bartók27, R. Chudasama, M. Csanad, M.M.A. Gadallah28, S. Lökös29, P. Major,
K. Mandal, A. Mehta, G. Pasztor, O. Surányi, G.I. Veres Wigner Research Centre
for Physics, Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath30, F. Sikler, V. Veszpremi, G.
Vesztergombi${}^{\textrm{\textdagger}}$ Institute of Nuclear Research ATOMKI,
Debrecen, Hungary
S. Czellar, J. Karancsi27, J. Molnar, Z. Szillasi, D. Teyssier Institute of
Physics, University of Debrecen, Debrecen, Hungary
P. Raics, Z.L. Trocsanyi, G. Zilizi Eszterhazy Karoly University, Karoly
Robert Campus, Gyongyos, Hungary
T. Csorgo, F. Nemes, T. Novak Indian Institute of Science (IISc), Bangalore,
India
S. Choudhury, J.R. Komaragiri, D. Kumar, L. Panwar, P.C. Tiwari National
Institute of Science Education and Research, HBNI, Bhubaneswar, India
S. Bahinipati31, D. Dash, C. Kar, P. Mal, T. Mishra, V.K. Muraleedharan Nair
Bindhu, A. Nayak32, D.K. Sahoo31, N. Sur, S.K. Swain Panjab University,
Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, S. Chauhan, N. Dhingra33, R. Gupta, A.
Kaur, S. Kaur, P. Kumari, M. Lohan, M. Meena, K. Sandeep, S. Sharma, J.B.
Singh, A.K. Virdi University of Delhi, Delhi, India
A. Ahmed, A. Bhardwaj, B.C. Choudhary, R.B. Garg, M. Gola, S. Keshri, A.
Kumar, M. Naimuddin, P. Priyanka, K. Ranjan, A. Shah Saha Institute of Nuclear
Physics, HBNI, Kolkata, India
M. Bharti34, R. Bhattacharya, S. Bhattacharya, D. Bhowmik, S. Dutta, S. Ghosh,
B. Gomber35, M. Maity36, S. Nandan, P. Palit, A. Purohit, P.K. Rout, G. Saha,
S. Sarkar, M. Sharan, B. Singh34, S. Thakur34 Indian Institute of Technology
Madras, Madras, India
P.K. Behera, S.C. Behera, P. Kalbhor, A. Muhammad, R. Pradhan, P.R. Pujahari,
A. Sharma, A.K. Sikdar Bhabha Atomic Research Centre, Mumbai, India
D. Dutta, V. Kumar, K. Naskar37, P.K. Netrakanti, L.M. Pant, P. Shukla Tata
Institute of Fundamental Research-A, Mumbai, India
T. Aziz, M.A. Bhat, S. Dugad, R. Kumar Verma, G.B. Mohanty, U. Sarkar Tata
Institute of Fundamental Research-B, Mumbai, India
S. Banerjee, S. Bhattacharya, S. Chatterjee, M. Guchait, S. Karmakar, S.
Kumar, G. Majumder, K. Mazumdar, S. Mukherjee, D. Roy, N. Sahoo Indian
Institute of Science Education and Research (IISER), Pune, India
S. Dube, B. Kansal, K. Kothekar, S. Pandey, A. Rane, A. Rastogi, S. Sharma
Department of Physics, Isfahan University of Technology, Isfahan, Iran
H. Bakhshiansohi38 Institute for Research in Fundamental Sciences (IPM),
Tehran, Iran
S. Chenarani39, S.M. Etesami, M. Khakzad, M. Mohammadi Najafabadi 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, R. Alya,b,40, C. Arutaa,b, A. Colaleoa, D. Creanzaa,c, N. De
Filippisa,c, M. De Palmaa,b, A. Di Florioa,b, A. Di Pilatoa,b, W.
Elmetenaweea,b, L. Fiorea, A. Gelmia,b, M. Gula, G. Iasellia,c, M. Incea,b, S.
Lezkia,b, G. Maggia,c, M. Maggia, I. Margjekaa,b, V. Mastrapasquaa,b, J.A.
Merlina, S. Mya,b, S. Nuzzoa,b, A. Pompilia,b, G. Pugliesea,c, A. Ranieria, G.
Selvaggia,b, L. Silvestrisa, F.M. Simonea,b, 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,
M. Cuffiania,b, G.M. Dallavallea, T. Diotalevia,b, F. Fabbria, A. Fanfania,b,
E. Fontanesia,b, P. Giacomellia, L. Giommia,b, C. Grandia, L. Guiduccia,b, F.
Iemmia,b, S. Lo Meoa,41, S. Marcellinia, G. Masettia, F.L. Navarriaa,b, A.
Perrottaa, F. Primaveraa,b, 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,42, S. Costaa,b, A. Di Mattiaa, R. Potenzaa,b, A. Tricomia,b,42,
C. Tuvea,b INFN Sezione di Firenze a, Università di Firenze b, Firenze, Italy
G. Barbaglia, A. Cassesea, R. Ceccarellia,b, V. Ciullia,b, C. Civininia, R.
D’Alessandroa,b, F. Fioria, E. Focardia,b, G. Latinoa,b, P. Lenzia,b, M.
Lizzoa,b, M. Meschinia, S. Paolettia, R. Seiditaa,b, G. Sguazzonia, L.
Viliania INFN Laboratori Nazionali di Frascati, Frascati, Italy
L. Benussi, S. Bianco, D. Piccolo INFN Sezione di Genova a, Università di
Genova b, Genova, Italy
M. Bozzoa,b, F. Ferroa, R. Mulargiaa,b, E. Robuttia, S. Tosia,b INFN Sezione
di Milano-Bicocca a, Università di Milano-Bicocca b, Milano, Italy
A. Benagliaa, A. Beschia,b, F. Brivioa,b, F. Cetorellia,b, V. Cirioloa,b,21,
F. De Guioa,b, M.E. Dinardoa,b, P. Dinia, S. Gennaia, A. Ghezzia,b, P.
Govonia,b, L. Guzzia,b, M. Malbertia, S. Malvezzia, D. Menascea, F. Montia,b,
L. Moronia, M. Paganonia,b, D. Pedrinia, S. Ragazzia,b, T. Tabarelli de
Fatisa,b, D. Valsecchia,b,21, D. Zuoloa,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, A. De Iorioa,b, F. Fabozzia,c, F. Fiengaa,
A.O.M. Iorioa,b, L. Listaa,b, S. Meolaa,d,21, P. Paoluccia,21, B. Rossia, C.
Sciaccaa,b, E. Voevodinaa,b INFN Sezione di Padova a, Università di Padova b,
Padova, Italy, Università di Trento c, Trento, Italy
P. Azzia, N. Bacchettaa, D. Biselloa,b, A. Bolettia,b, A. Bragagnoloa,b, R.
Carlina,b, P. Checchiaa, P. De Castro Manzanoa, T. Dorigoa, F. Gasparinia,b,
U. Gasparinia,b, S.Y. Hoha,b, L. Layera, M. Margonia,b, A.T. Meneguzzoa,b, M.
Presillab, P. Ronchesea,b, R. Rossina,b, F. Simonettoa,b, G. Strong, A. Tikoa,
M. Tosia,b, H. YARARa,b, M. Zanettia,b, P. Zottoa,b, A. Zucchettaa,b, G.
Zumerlea,b INFN Sezione di Pavia a, Università di Pavia b, Pavia, Italy
C. Aime‘a,b, A. Braghieria, S. Calzaferria,b, D. Fiorinaa,b, P. Montagnaa,b,
S.P. Rattia,b, V. Rea, M. Ressegottia,b, C. Riccardia,b, P. Salvinia, I. Vaia,
P. Vituloa,b INFN Sezione di Perugia a, Università di Perugia b, Perugia,
Italy
M. Biasinia,b, G.M. Bileia, D. Ciangottinia,b, L. Fanòa,b, P. Laricciaa,b, G.
Mantovania,b, V. Mariania,b, M. Menichellia, F. Moscatellia, A. Piccinellia,b,
A. Rossia,b, A. Santocchiaa,b, D. Spigaa, T. Tedeschia,b INFN Sezione di Pisa
a, Università di Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy
K. Androsova, P. Azzurria, G. Bagliesia, V. Bertacchia,c, L. Bianchinia, T.
Boccalia, R. Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, M.R. Di Domenicoa,b, S.
Donatoa, L. Gianninia,c, A. Giassia, M.T. Grippoa, F. Ligabuea,c, E. Mancaa,c,
G. Mandorlia,c, A. Messineoa,b, F. Pallaa, G. Ramirez-Sancheza,c, A. Rizzia,b,
G. Rolandia,c, S. Roy Chowdhurya,c, A. Scribanoa, N. Shafieia,b, P. Spagnoloa,
R. Tenchinia, G. Tonellia,b, N. Turinia, A. Venturia, P.G. Verdinia INFN
Sezione di Roma a, Sapienza Università di Roma b, Rome, Italy
F. Cavallaria, M. Cipriania,b, D. Del Rea,b, E. Di Marcoa, M. Diemoza, E.
Longoa,b, P. Meridiania, G. Organtinia,b, F. Pandolfia, R. Paramattia,b, C.
Quarantaa,b, S. Rahatloua,b, C. Rovellia, F. Santanastasioa,b, L. Soffia,b, R.
Tramontanoa,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, A. Belloraa,b, C. Biinoa, A. Cappatia,b, N. Cartigliaa, S.
Comettia, M. Costaa,b, R. Covarellia,b, N. Demariaa, B. Kiania,b, F. Leggera,
C. Mariottia, S. Masellia, E. Migliorea,b, V. Monacoa,b, E. Monteila,b, M.
Montenoa, M.M. Obertinoa,b, G. Ortonaa, L. Pachera,b, N. Pastronea, M.
Pelliccionia, G.L. Pinna Angionia,b, M. Ruspaa,c, R. Salvaticoa,b, F.
Sivieroa,b, V. Solaa, A. Solanoa,b, D. Soldia,b, A. Staianoa, D. Trocinoa,b
INFN Sezione di Trieste a, Università di Trieste b, Trieste, Italy
S. Belfortea, V. Candelisea,b, M. Casarsaa, F. Cossuttia, A. Da Rolda,b, G.
Della Riccaa,b, F. Vazzolera,b Kyungpook National University, Daegu, Korea
S. Dogra, C. Huh, B. Kim, D.H. Kim, G.N. Kim, J. Lee, S.W. Lee, C.S. Moon,
Y.D. Oh, S.I. Pak, B.C. Radburn-Smith, S. Sekmen, Y.C. Yang Chonnam National
University, Institute for Universe and Elementary Particles, Kwangju, Korea
H. Kim, D.H. Moon Hanyang University, Seoul, Korea
B. Francois, T.J. Kim, J. Park Korea University, Seoul, Korea
S. Cho, S. Choi, Y. Go, S. Ha, B. Hong, K. Lee, K.S. Lee, J. Lim, J. Park,
S.K. Park, J. Yoo Kyung Hee University, Department of Physics, Seoul, Republic
of Korea
J. Goh, A. Gurtu Sejong University, Seoul, Korea
H.S. Kim, Y. Kim Seoul National University, Seoul, Korea
J. Almond, J.H. Bhyun, J. Choi, S. Jeon, J. Kim, J.S. Kim, S. Ko, H. Kwon, H.
Lee, K. Lee, S. Lee, K. Nam, B.H. Oh, M. Oh, S.B. Oh, H. Seo, U.K. Yang, I.
Yoon University of Seoul, Seoul, Korea
D. Jeon, J.H. Kim, B. Ko, J.S.H. Lee, I.C. Park, Y. Roh, D. Song, I.J. Watson
Yonsei University, Department of Physics, Seoul, Korea
H.D. Yoo Sungkyunkwan University, Suwon, Korea
Y. Choi, C. Hwang, Y. Jeong, H. Lee, Y. Lee, I. Yu Riga Technical University,
Riga, Latvia
V. Veckalns43 Vilnius University, Vilnius, Lithuania
A. Juodagalvis, A. Rinkevicius, G. Tamulaitis National Centre for Particle
Physics, Universiti Malaya, Kuala Lumpur, Malaysia
W.A.T. Wan Abdullah, M.N. Yusli, Z. Zolkapli Universidad de Sonora (UNISON),
Hermosillo, Mexico
J.F. Benitez, A. Castaneda Hernandez, J.A. Murillo Quijada, L. Valencia Palomo
Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico
G. Ayala, H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz44,
R. Lopez-Fernandez, D.A. Perez Navarro, A. Sanchez-Hernandez Universidad
Iberoamericana, Mexico City, Mexico
S. Carrillo Moreno, C. Oropeza Barrera, M. Ramirez-Garcia, F. Vazquez Valencia
Benemerita Universidad Autonoma de Puebla, Puebla, Mexico
J. Eysermans, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad
Autónoma de San Luis Potosí, San Luis Potosí, Mexico
A. Morelos Pineda University of Montenegro, Podgorica, Montenegro
J. Mijuskovic4, N. Raicevic University of Auckland, Auckland, New Zealand
D. Krofcheck University of Canterbury, Christchurch, New Zealand
S. Bheesette, P.H. Butler National Centre for Physics, Quaid-I-Azam
University, Islamabad, Pakistan
A. Ahmad, M.I. Asghar, M.I.M. Awan, H.R. Hoorani, W.A. Khan, M.A. Shah, M.
Shoaib, M. Waqas AGH University of Science and Technology Faculty of Computer
Science, Electronics and Telecommunications, Krakow, Poland
V. Avati, L. Grzanka, M. Malawski National Centre for Nuclear Research,
Swierk, Poland
H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Górski, M. Kazana, M.
Szleper, P. Traczyk, P. Zalewski Institute of Experimental Physics, Faculty of
Physics, University of Warsaw, Warsaw, Poland
K. Bunkowski, A. Byszuk45, K. Doroba, A. Kalinowski, M. Konecki, J.
Krolikowski, M. Olszewski, M. Walczak Laboratório de Instrumentação e Física
Experimental de Partículas, Lisboa, Portugal
M. Araujo, P. Bargassa, D. Bastos, P. Faccioli, M. Gallinaro, J. Hollar, N.
Leonardo, T. Niknejad, J. Seixas, K. Shchelina, O. Toldaiev, J. Varela Joint
Institute for Nuclear Research, Dubna, Russia
S. Afanasiev, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev,
V. Karjavine, A. Lanev, A. Malakhov, V. Matveev46,47, P. Moisenz, V. Palichik,
V. Perelygin, M. Savina, D. Seitova, V. Shalaev, S. Shmatov, S. Shulha, V.
Smirnov, O. Teryaev, N. Voytishin, A. Zarubin, I. Zhizhin Petersburg Nuclear
Physics Institute, Gatchina (St. Petersburg), Russia
G. Gavrilov, V. Golovtcov, Y. Ivanov, V. Kim48, E. Kuznetsova49, V. Murzin, V.
Oreshkin, I. Smirnov, D. Sosnov, V. Sulimov, L. Uvarov, S. Volkov, A. Vorobyev
Institute for Nuclear Research, Moscow, Russia
Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov,
N. Krasnikov, A. Pashenkov, G. Pivovarov, D.
Tlisov${}^{\textrm{\textdagger}}$, A. Toropin Institute for Theoretical and
Experimental Physics named by A.I. Alikhanov of NRC ‘Kurchatov Institute’,
Moscow, Russia
V. Epshteyn, V. Gavrilov, N. Lychkovskaya, A. Nikitenko50, V. Popov, G.
Safronov, A. Spiridonov, A. Stepennov, M. Toms, E. Vlasov, A. Zhokin Moscow
Institute of Physics and Technology, Moscow, Russia
T. Aushev National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
O. Bychkova, M. Danilov51, D. Philippov, E. Popova, V. Rusinov P.N. Lebedev
Physical Institute, Moscow, Russia
V. Andreev, M. Azarkin, I. Dremin, M. Kirakosyan, A. Terkulov Skobeltsyn
Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow,
Russia
A. Belyaev, E. Boos, V. Bunichev, M. Dubinin52, L. Dudko, A. Ershov, A.
Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, S. Obraztsov, M. Perfilov, V.
Savrin Novosibirsk State University (NSU), Novosibirsk, Russia
V. Blinov53, T. Dimova53, L. Kardapoltsev53, I. Ovtin53, Y. Skovpen53
Institute for High Energy Physics of National Research Centre ‘Kurchatov
Institute’, Protvino, Russia
I. Azhgirey, I. Bayshev, V. Kachanov, A. Kalinin, D. Konstantinov, V. Petrov,
R. Ryutin, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov National
Research Tomsk Polytechnic University, Tomsk, Russia
A. Babaev, A. Iuzhakov, V. Okhotnikov, L. Sukhikh Tomsk State University,
Tomsk, Russia
V. Borchsh, V. Ivanchenko, E. Tcherniaev University of Belgrade: Faculty of
Physics and VINCA Institute of Nuclear Sciences, Belgrade, Serbia
P. Adzic54, P. Cirkovic, M. Dordevic, P. Milenovic, J. Milosevic Centro de
Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid,
Spain
M. Aguilar-Benitez, J. Alcaraz Maestre, A. Álvarez Fernández, I. Bachiller, M.
Barrio Luna, Cristina F. Bedoya, J.A. Brochero Cifuentes, C.A. Carrillo
Montoya, M. Cepeda, M. Cerrada, N. Colino, B. De La Cruz, A. Delgado Peris,
J.P. Fernández Ramos, J. Flix, M.C. Fouz, A. García Alonso, O. Gonzalez Lopez,
S. Goy Lopez, J.M. Hernandez, M.I. Josa, J. León Holgado, D. Moran, Á. Navarro
Tobar, A. Pérez-Calero Yzquierdo, J. Puerta Pelayo, I. Redondo, L. Romero, S.
Sánchez Navas, M.S. Soares, A. Triossi, L. Urda Gómez, C. Willmott Universidad
Autónoma de Madrid, Madrid, Spain
C. Albajar, J.F. de Trocóniz, R. Reyes-Almanza Universidad de Oviedo,
Instituto Universitario de Ciencias y Tecnologías Espaciales de Asturias
(ICTEA), Oviedo, Spain
B. Alvarez Gonzalez, J. Cuevas, C. Erice, J. Fernandez Menendez, S. Folgueras,
I. Gonzalez Caballero, E. Palencia Cortezon, C. Ramón Álvarez, J. Ripoll Sau,
V. Rodríguez Bouza, S. Sanchez Cruz, A. Trapote Instituto de Física de
Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain
I.J. Cabrillo, A. Calderon, B. Chazin Quero, J. Duarte Campderros, M.
Fernandez, P.J. Fernández Manteca, G. Gomez, C. Martinez Rivero, P. Martinez
Ruiz del Arbol, F. Matorras, J. Piedra Gomez, C. Prieels, F. Ricci-Tam, T.
Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, I. Vila, J.M. Vizan Garcia University
of Colombo, Colombo, Sri Lanka
MK Jayananda, B. Kailasapathy55, D.U.J. Sonnadara, DDC Wickramarathna
University of Ruhuna, Department of Physics, Matara, Sri Lanka
W.G.D. Dharmaratna, K. Liyanage, N. Perera, N. Wickramage CERN, European
Organization for Nuclear Research, Geneva, Switzerland
T.K. Aarrestad, D. Abbaneo, B. Akgun, E. Auffray, G. Auzinger, J. Baechler, P.
Baillon, A.H. Ball, D. Barney, J. Bendavid, N. Beni, M. Bianco, A. Bocci, P.
Bortignon, E. Bossini, E. Brondolin, T. Camporesi, G. Cerminara, L. Cristella,
D. d’Enterria, A. Dabrowski, N. Daci, V. Daponte, A. David, A. De Roeck, M.
Deile, R. Di Maria, M. Dobson, M. Dünser, N. Dupont, A. Elliott-Peisert, N.
Emriskova, F. Fallavollita56, D. Fasanella, S. Fiorendi, A. Florent, G.
Franzoni, J. Fulcher, W. Funk, S. Giani, D. Gigi, K. Gill, F. Glege, L.
Gouskos, M. Guilbaud, D. Gulhan, M. Haranko, J. Hegeman, Y. Iiyama, V.
Innocente, T. James, P. Janot, J. Kaspar, J. Kieseler, M. Komm, N. Kratochwil,
C. Lange, P. Lecoq, K. Long, C. Lourenço, L. Malgeri, M. Mannelli, A.
Massironi, F. Meijers, S. Mersi, E. Meschi, F. Moortgat, M. Mulders, J.
Ngadiuba, J. Niedziela, S. Orfanelli, L. Orsini, F. Pantaleo21, L. Pape, E.
Perez, M. Peruzzi, A. Petrilli, G. Petrucciani, A. Pfeiffer, M. Pierini, D.
Rabady, A. Racz, M. Rieger, M. Rovere, H. Sakulin, J. Salfeld-Nebgen, S.
Scarfi, C. Schäfer, C. Schwick, M. Selvaggi, A. Sharma, P. Silva, W. Snoeys,
P. Sphicas57, J. Steggemann, S. Summers, V.R. Tavolaro, D. Treille, A. Tsirou,
G.P. Van Onsem, A. Vartak, M. Verzetti, K.A. Wozniak, W.D. Zeuner Paul
Scherrer Institut, Villigen, Switzerland
L. Caminada58, W. Erdmann, R. Horisberger, Q. Ingram, H.C. Kaestli, D.
Kotlinski, U. Langenegger, T. Rohe ETH Zurich - Institute for Particle Physics
and Astrophysics (IPA), Zurich, Switzerland
M. Backhaus, P. Berger, A. Calandri, N. Chernyavskaya, A. De Cosa, G.
Dissertori, M. Dittmar, M. Donegà, C. Dorfer, T. Gadek, T.A. Gómez Espinosa,
C. Grab, D. Hits, W. Lustermann, A.-M. Lyon, R.A. Manzoni, M.T. Meinhard, F.
Micheli, F. Nessi-Tedaldi, F. Pauss, V. Perovic, G. Perrin, L. Perrozzi, S.
Pigazzini, M.G. Ratti, M. Reichmann, C. Reissel, T. Reitenspiess, B. Ristic,
D. Ruini, D.A. Sanz Becerra, M. Schönenberger, V. Stampf, M.L. Vesterbacka
Olsson, R. Wallny, D.H. Zhu Universität Zürich, Zurich, Switzerland
C. Amsler59, C. Botta, D. Brzhechko, M.F. Canelli, R. Del Burgo, J.K.
Heikkilä, M. Huwiler, A. Jofrehei, B. Kilminster, S. Leontsinis, A. Macchiolo,
P. Meiring, V.M. Mikuni, U. Molinatti, I. Neutelings, G. Rauco, A. Reimers, P.
Robmann, K. Schweiger, Y. Takahashi, S. Wertz National Central University,
Chung-Li, Taiwan
C. Adloff60, C.M. Kuo, W. Lin, A. Roy, T. Sarkar36, S.S. Yu National Taiwan
University (NTU), Taipei, Taiwan
L. Ceard, P. Chang, Y. Chao, K.F. Chen, P.H. Chen, W.-S. Hou, Y.y. Li, R.-S.
Lu, E. Paganis, A. Psallidas, A. Steen, E. Yazgan Chulalongkorn University,
Faculty of Science, Department of Physics, Bangkok, Thailand
B. Asavapibhop, C. Asawatangtrakuldee, N. Srimanobhas Çukurova University,
Physics Department, Science and Art Faculty, Adana, Turkey
F. Boran, S. Damarseckin61, Z.S. Demiroglu, F. Dolek, C. Dozen62, I.
Dumanoglu63, E. Eskut, G. Gokbulut, Y. Guler, E. Gurpinar Guler64, I. Hos65,
C. Isik, E.E. Kangal66, O. Kara, A. Kayis Topaksu, U. Kiminsu, G. Onengut, K.
Ozdemir67, A. Polatoz, A.E. Simsek, B. Tali68, U.G. Tok, S. Turkcapar, I.S.
Zorbakir, C. Zorbilmez Middle East Technical University, Physics Department,
Ankara, Turkey
B. Isildak69, G. Karapinar70, K. Ocalan71, M. Yalvac72 Bogazici University,
Istanbul, Turkey
I.O. Atakisi, E. Gülmez, M. Kaya73, O. Kaya74, Ö. Özçelik, S. Tekten75, E.A.
Yetkin76 Istanbul Technical University, Istanbul, Turkey
A. Cakir, K. Cankocak63, Y. Komurcu, S. Sen77 Istanbul University, Istanbul,
Turkey
F. Aydogmus Sen, S. Cerci68, B. Kaynak, S. Ozkorucuklu, D. Sunar Cerci68
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
E. Bhal, S. Bologna, J.J. Brooke, E. Clement, D. Cussans, H. Flacher, J.
Goldstein, G.P. Heath, H.F. Heath, L. Kreczko, B. Krikler, S. Paramesvaran, T.
Sakuma, S. Seif El Nasr-Storey, V.J. Smith, J. Taylor, A. Titterton Rutherford
Appleton Laboratory, Didcot, United Kingdom
K.W. Bell, A. Belyaev78, C. Brew, R.M. Brown, D.J.A. Cockerill, K.V. Ellis, K.
Harder, S. Harper, J. Linacre, K. Manolopoulos, D.M. Newbold, E. Olaiya, D.
Petyt, T. Reis, T. Schuh, C.H. Shepherd-Themistocleous, A. Thea, I.R. Tomalin,
T. Williams Imperial College, London, United Kingdom
R. Bainbridge, P. Bloch, S. Bonomally, J. Borg, S. Breeze, O. Buchmuller, A.
Bundock, V. Cepaitis, G.S. Chahal79, D. Colling, P. Dauncey, G. Davies, M.
Della Negra, G. Fedi, G. Hall, G. Iles, J. Langford, L. Lyons, A.-M. Magnan,
S. Malik, A. Martelli, V. Milosevic, J. Nash80, V. Palladino, M. Pesaresi,
D.M. Raymond, A. Richards, A. Rose, E. Scott, C. Seez, A. Shtipliyski, M.
Stoye, A. Tapper, K. Uchida, T. Virdee21, N. Wardle, S.N. Webb, D.
Winterbottom, A.G. Zecchinelli Brunel University, Uxbridge, United Kingdom
J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, C.K. Mackay, I.D. Reid, L.
Teodorescu, S. Zahid Baylor University, Waco, USA
A. Brinkerhoff, K. Call, B. Caraway, J. Dittmann, K. Hatakeyama, A.R.
Kanuganti, C. Madrid, B. McMaster, N. Pastika, S. Sawant, C. Smith, J. Wilson
Catholic University of America, Washington, DC, USA
R. Bartek, A. Dominguez, R. Uniyal, A.M. Vargas Hernandez The University of
Alabama, Tuscaloosa, USA
A. Buccilli, O. Charaf, S.I. Cooper, S.V. Gleyzer, C. Henderson, P. Rumerio,
C. West Boston University, Boston, USA
A. Akpinar, A. Albert, D. Arcaro, C. Cosby, Z. Demiragli, D. Gastler, C.
Richardson, J. Rohlf, K. Salyer, D. Sperka, D. Spitzbart, I. Suarez, S. Yuan,
D. Zou Brown University, Providence, USA
G. Benelli, B. Burkle, X. Coubez22, D. Cutts, Y.t. Duh, M. Hadley, U. Heintz,
J.M. Hogan81, K.H.M. Kwok, E. Laird, G. Landsberg, K.T. Lau, J. Lee, M.
Narain, S. Sagir82, R. Syarif, E. Usai, W.Y. Wong, D. Yu, W. Zhang University
of California, Davis, Davis, USA
R. Band, C. Brainerd, R. Breedon, M. Calderon De La Barca Sanchez, M. Chertok,
J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, F. Jensen, W.
Ko${}^{\textrm{\textdagger}}$, O. Kukral, R. Lander, M. Mulhearn, D. Pellett,
J. Pilot, M. Shi, D. Taylor, K. Tos, M. Tripathi, Y. Yao, F. Zhang University
of California, Los Angeles, USA
M. Bachtis, R. Cousins, A. Dasgupta, D. Hamilton, J. Hauser, M. Ignatenko, T.
Lam, N. Mccoll, W.A. Nash, S. Regnard, D. Saltzberg, C. Schnaible, B. Stone,
V. Valuev University of California, Riverside, Riverside, USA
K. Burt, Y. Chen, R. Clare, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, G.
Karapostoli, O.R. Long, N. Manganelli, M. Olmedo Negrete, M.I. Paneva, W. Si,
S. Wimpenny, Y. Zhang University of California, San Diego, La Jolla, USA
J.G. Branson, P. Chang, S. Cittolin, S. Cooperstein, N. Deelen, M. Derdzinski,
J. Duarte, R. Gerosa, D. Gilbert, B. Hashemi, V. Krutelyov, J. Letts, M.
Masciovecchio, S. May, S. Padhi, M. Pieri, V. Sharma, M. Tadel, F. Würthwein,
A. Yagil University of California, Santa Barbara - Department of Physics,
Santa Barbara, USA
N. Amin, C. Campagnari, M. Citron, A. Dorsett, V. Dutta, J. Incandela, B.
Marsh, H. Mei, A. Ovcharova, H. Qu, M. Quinnan, J. Richman, U. Sarica, D.
Stuart, S. Wang California Institute of Technology, Pasadena, USA
D. Anderson, A. Bornheim, O. Cerri, I. Dutta, J.M. Lawhorn, N. Lu, J. Mao,
H.B. Newman, T.Q. Nguyen, J. Pata, M. Spiropulu, J.R. Vlimant, S. Xie, Z.
Zhang, R.Y. Zhu Carnegie Mellon University, Pittsburgh, USA
J. Alison, M.B. Andrews, T. Ferguson, T. Mudholkar, M. Paulini, M. Sun, I.
Vorobiev University of Colorado Boulder, Boulder, USA
J.P. Cumalat, W.T. Ford, E. MacDonald, T. Mulholland, R. Patel, A. Perloff, K.
Stenson, K.A. Ulmer, S.R. Wagner Cornell University, Ithaca, USA
J. Alexander, Y. Cheng, J. Chu, D.J. Cranshaw, A. Datta, A. Frankenthal, K.
Mcdermott, J. Monroy, J.R. Patterson, D. Quach, A. Ryd, W. Sun, S.M. Tan, Z.
Tao, J. Thom, 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, D. Berry, J. Berryhill, P.C. Bhat, K.
Burkett, J.N. Butler, A. Canepa, G.B. Cerati, H.W.K. Cheung, F. Chlebana, M.
Cremonesi, V.D. Elvira, J. Freeman, Z. Gecse, E. Gottschalk, L. Gray, D.
Green, S. Grünendahl, O. Gutsche, R.M. Harris, S. Hasegawa, R. Heller, T.C.
Herwig, J. Hirschauer, B. Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, P.
Klabbers, T. Klijnsma, B. Klima, M.J. Kortelainen, S. Lammel, D. Lincoln, R.
Lipton, M. Liu, T. Liu, J. Lykken, K. Maeshima, D. Mason, P. McBride, P.
Merkel, S. Mrenna, S. Nahn, V. O’Dell, V. Papadimitriou, K. Pedro, C. Pena52,
O. Prokofyev, F. Ravera, A. Reinsvold Hall, L. Ristori, B. Schneider, E.
Sexton-Kennedy, N. Smith, A. Soha, W.J. Spalding, L. Spiegel, S. Stoynev, J.
Strait, L. Taylor, S. Tkaczyk, N.V. Tran, L. Uplegger, E.W. Vaandering, H.A.
Weber, A. Woodard University of Florida, Gainesville, USA
D. Acosta, P. Avery, D. Bourilkov, L. Cadamuro, V. Cherepanov, F. Errico, R.D.
Field, D. Guerrero, B.M. Joshi, M. Kim, J. Konigsberg, A. Korytov, K.H. Lo, K.
Matchev, N. Menendez, G. Mitselmakher, D. Rosenzweig, K. Shi, J. Wang, S.
Wang, X. Zuo Florida State University, Tallahassee, USA
T. Adams, A. Askew, D. Diaz, R. Habibullah, S. Hagopian, V. Hagopian, K.F.
Johnson, R. Khurana, T. Kolberg, G. Martinez, H. Prosper, C. Schiber, R.
Yohay, J. Zhang Florida Institute of Technology, Melbourne, USA
M.M. Baarmand, S. Butalla, T. Elkafrawy83, M. Hohlmann, D. Noonan, M. Rahmani,
M. Saunders, F. Yumiceva University of Illinois at Chicago (UIC), Chicago, USA
M.R. Adams, L. Apanasevich, H. Becerril Gonzalez, R. Cavanaugh, X. Chen, S.
Dittmer, O. Evdokimov, C.E. Gerber, D.A. Hangal, D.J. Hofman, C. Mills, G. Oh,
T. Roy, M.B. Tonjes, N. Varelas, J. Viinikainen, X. Wang, Z. Wu The University
of Iowa, Iowa City, USA
M. Alhusseini, K. Dilsiz84, S. Durgut, R.P. Gandrajula, M. Haytmyradov, V.
Khristenko, O.K. Köseyan, J.-P. Merlo, A. Mestvirishvili85, A. Moeller, J.
Nachtman, H. Ogul86, Y. Onel, F. Ozok87, A. Penzo, C. Snyder, E. Tiras, J.
Wetzel, K. Yi88 Johns Hopkins University, Baltimore, USA
O. Amram, B. Blumenfeld, L. Corcodilos, M. Eminizer, A.V. Gritsan, S.
Kyriacou, P. Maksimovic, C. Mantilla, J. Roskes, M. Swartz, T.Á. Vámi The
University of Kansas, Lawrence, USA
C. Baldenegro Barrera, P. Baringer, A. Bean, A. Bylinkin, T. Isidori, S.
Khalil, J. King, G. Krintiras, A. Kropivnitskaya, C. Lindsey, N. Minafra, M.
Murray, C. Rogan, C. Royon, S. Sanders, E. Schmitz, J.D. Tapia Takaki, Q.
Wang, J. Williams, G. Wilson Kansas State University, Manhattan, USA
S. Duric, A. Ivanov, K. Kaadze, D. Kim, Y. Maravin, T. Mitchell, A. Modak, A.
Mohammadi Lawrence Livermore National Laboratory, Livermore, USA
F. Rebassoo, D. Wright University of Maryland, College Park, USA
E. Adams, A. Baden, O. Baron, A. Belloni, S.C. Eno, Y. Feng, N.J. Hadley, S.
Jabeen, G.Y. Jeng, R.G. Kellogg, T. Koeth, A.C. Mignerey, S. Nabili, M.
Seidel, A. Skuja, S.C. Tonwar, L. Wang, K. Wong Massachusetts Institute of
Technology, Cambridge, USA
D. Abercrombie, B. Allen, R. Bi, S. Brandt, W. Busza, I.A. Cali, Y. Chen, M.
D’Alfonso, G. Gomez Ceballos, M. Goncharov, P. Harris, D. Hsu, M. Hu, M.
Klute, D. Kovalskyi, J. Krupa, Y.-J. Lee, P.D. Luckey, B. Maier, A.C. Marini,
C. Mcginn, C. Mironov, S. Narayanan, X. Niu, C. Paus, D. Rankin, C. Roland, G.
Roland, Z. Shi, G.S.F. Stephans, K. Sumorok, K. Tatar, D. Velicanu, J. Wang,
T.W. Wang, Z. Wang, B. Wyslouch University of Minnesota, Minneapolis, USA
R.M. Chatterjee, A. Evans, S. Guts${}^{\textrm{\textdagger}}$, P. Hansen, J.
Hiltbrand, Sh. Jain, M. Krohn, Y. Kubota, Z. Lesko, J. Mans, M. Revering, R.
Rusack, R. Saradhy, N. Schroeder, N. Strobbe, M.A. Wadud University of
Mississippi, Oxford, USA
J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA
K. Bloom, S. Chauhan, D.R. Claes, C. Fangmeier, L. Finco, F. Golf, J.R.
González Fernández, I. Kravchenko, J.E. Siado, G.R.
Snow${}^{\textrm{\textdagger}}$, B. Stieger, W. Tabb, F. Yan State University
of New York at Buffalo, Buffalo, USA
G. Agarwal, H. Bandyopadhyay, C. Harrington, L. Hay, I. Iashvili, A.
Kharchilava, C. McLean, D. Nguyen, J. Pekkanen, S. Rappoccio, B. Roozbahani
Northeastern University, Boston, USA
G. Alverson, E. Barberis, C. Freer, Y. Haddad, A. Hortiangtham, J. Li, G.
Madigan, B. Marzocchi, D.M. Morse, V. Nguyen, T. Orimoto, A. Parker, L.
Skinnari, A. Tishelman-Charny, T. Wamorkar, B. Wang, A. Wisecarver, D. Wood
Northwestern University, Evanston, USA
S. Bhattacharya, J. Bueghly, Z. Chen, A. Gilbert, T. Gunter, K.A. Hahn, N.
Odell, M.H. Schmitt, K. Sung, M. Velasco University of Notre Dame, Notre Dame,
USA
R. Bucci, N. Dev, R. Goldouzian, M. Hildreth, K. Hurtado Anampa, C. Jessop,
D.J. Karmgard, K. Lannon, W. Li, N. Loukas, N. Marinelli, I. Mcalister, F.
Meng, K. Mohrman, Y. Musienko46, R. Ruchti, P. Siddireddy, S. Taroni, M.
Wayne, A. Wightman, M. Wolf, L. Zygala The Ohio State University, Columbus,
USA
J. Alimena, B. Bylsma, B. Cardwell, L.S. Durkin, B. Francis, C. Hill, A.
Lefeld, B.L. Winer, B.R. Yates Princeton University, Princeton, USA
P. Das, G. Dezoort, P. Elmer, B. Greenberg, N. Haubrich, S. Higginbotham, A.
Kalogeropoulos, G. Kopp, S. Kwan, D. Lange, M.T. Lucchini, 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
V.E. Barnes, R. Chawla, S. Das, L. Gutay, M. Jones, A.W. Jung, B. Mahakud, G.
Negro, N. Neumeister, C.C. Peng, S. Piperov, H. Qiu, J.F. Schulte, M.
Stojanovic17, N. Trevisani, F. Wang, R. Xiao, W. Xie Purdue University
Northwest, Hammond, USA
T. Cheng, J. Dolen, N. Parashar Rice University, Houston, USA
A. Baty, S. Dildick, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Kilpatrick, A.
Kumar, W. Li, B.P. Padley, R. Redjimi, J. Roberts${}^{\textrm{\textdagger}}$,
J. Rorie, W. Shi, A.G. Stahl Leiton University of Rochester, Rochester, USA
A. Bodek, P. de Barbaro, R. Demina, J.L. Dulemba, C. Fallon, T. Ferbel, M.
Galanti, A. Garcia-Bellido, O. Hindrichs, A. Khukhunaishvili, E. Ranken, R.
Taus Rutgers, The State University of New Jersey, Piscataway, USA
B. Chiarito, J.P. Chou, A. Gandrakota, Y. Gershtein, E. Halkiadakis, A. Hart,
M. Heindl, E. Hughes, S. Kaplan, O. Karacheban25, I. Laflotte, A. Lath, R.
Montalvo, K. Nash, M. Osherson, S. Salur, S. Schnetzer, S. Somalwar, R. Stone,
S.A. Thayil, S. Thomas, H. Wang University of Tennessee, Knoxville, USA
H. Acharya, A.G. Delannoy, S. Spanier Texas A&M University, College Station,
USA
O. Bouhali89, M. Dalchenko, A. Delgado, R. Eusebi, J. Gilmore, T. Huang, T.
Kamon90, H. Kim, S. Luo, S. Malhotra, R. Mueller, D. Overton, L. Perniè, D.
Rathjens, A. Safonov, J. Sturdy Texas Tech University, Lubbock, USA
N. Akchurin, J. Damgov, V. Hegde, S. Kunori, K. Lamichhane, S.W. Lee, T.
Mengke, S. Muthumuni, T. Peltola, S. Undleeb, I. Volobouev, Z. Wang, A.
Whitbeck Vanderbilt University, Nashville, USA
E. Appelt, S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H.
Ni, K. Padeken, F. Romeo, P. Sheldon, S. Tuo, J. Velkovska, M. Verweij
University of Virginia, Charlottesville, USA
M.W. Arenton, B. Cox, G. Cummings, J. Hakala, R. Hirosky, M. Joyce, A.
Ledovskoy, A. Li, C. Neu, B. Tannenwald, Y. Wang, E. Wolfe, F. Xia Wayne State
University, Detroit, USA
P.E. Karchin, N. Poudyal, P. Thapa University of Wisconsin - Madison, Madison,
WI, USA
K. Black, T. Bose, J. Buchanan, C. Caillol, S. Dasu, I. De Bruyn, P.
Everaerts, C. Galloni, H. He, M. Herndon, A. Hervé, U. Hussain, A. Lanaro, A.
Loeliger, R. Loveless, J. Madhusudanan Sreekala, A. Mallampalli, D. Pinna, T.
Ruggles, A. Savin, V. Shang, V. Sharma, W.H. Smith, D. Teague, S. Trembath-
reichert, W. Vetens †: Deceased
1: Also at Vienna University of Technology, Vienna, Austria
2: Also at Department of Basic and Applied Sciences, Faculty of Engineering,
Arab Academy for Science, Technology and Maritime Transport, Alexandria, Egypt
3: Also at Université Libre de Bruxelles, Bruxelles, Belgium
4: Also at IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
5: Also at Universidade Estadual de Campinas, Campinas, Brazil
6: Also at Federal University of Rio Grande do Sul, Porto Alegre, Brazil
7: Also at UFMS, Nova Andradina, Brazil
8: Also at Universidade Federal de Pelotas, Pelotas, Brazil
9: Also at University of Chinese Academy of Sciences, Beijing, China
10: Also at Institute for Theoretical and Experimental Physics named by A.I.
Alikhanov of NRC ‘Kurchatov Institute’, Moscow, Russia
11: Also at Joint Institute for Nuclear Research, Dubna, Russia
12: Also at Cairo University, Cairo, Egypt
13: Also at Suez University, Suez, Egypt
14: Now at British University in Egypt, Cairo, Egypt
15: Also at Zewail City of Science and Technology, Zewail, Egypt
16: Now at Fayoum University, El-Fayoum, Egypt
17: Also at Purdue University, West Lafayette, USA
18: Also at Université de Haute Alsace, Mulhouse, France
19: Also at Ilia State University, Tbilisi, Georgia
20: Also at Erzincan Binali Yildirim University, Erzincan, Turkey
21: Also at CERN, European Organization for Nuclear Research, Geneva,
Switzerland
22: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
23: Also at University of Hamburg, Hamburg, Germany
24: Also at Department of Physics, Isfahan University of Technology, Isfahan,
Iran, Isfahan, Iran
25: Also at Brandenburg University of Technology, Cottbus, Germany
26: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State
University, Moscow, Russia
27: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary,
Debrecen, Hungary
28: Also at Physics Department, Faculty of Science, Assiut University, Assiut,
Egypt
29: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary, Budapest, Hungary
30: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
31: Also at IIT Bhubaneswar, Bhubaneswar, India, Bhubaneswar, India
32: Also at Institute of Physics, Bhubaneswar, India
33: Also at G.H.G. Khalsa College, Punjab, India
34: Also at Shoolini University, Solan, India
35: Also at University of Hyderabad, Hyderabad, India
36: Also at University of Visva-Bharati, Santiniketan, India
37: Also at Indian Institute of Technology (IIT), Mumbai, India
38: Also at Deutsches Elektronen-Synchrotron, Hamburg, Germany
39: Also at Department of Physics, University of Science and Technology of
Mazandaran, Behshahr, Iran
40: Now at INFN Sezione di Bari a, Università di Bari b, Politecnico di Bari
c, Bari, Italy
41: Also at Italian National Agency for New Technologies, Energy and
Sustainable Economic Development, Bologna, Italy
42: Also at Centro Siciliano di Fisica Nucleare e di Struttura Della Materia,
Catania, Italy
43: Also at Riga Technical University, Riga, Latvia, Riga, Latvia
44: Also at Consejo Nacional de Ciencia y Tecnología, Mexico City, Mexico
45: Also at Warsaw University of Technology, Institute of Electronic Systems,
Warsaw, Poland
46: Also at Institute for Nuclear Research, Moscow, Russia
47: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
48: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
49: Also at University of Florida, Gainesville, USA
50: Also at Imperial College, London, United Kingdom
51: Also at P.N. Lebedev Physical Institute, Moscow, Russia
52: Also at California Institute of Technology, Pasadena, USA
53: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
54: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
55: Also at Trincomalee Campus, Eastern University, Sri Lanka, Nilaveli, Sri
Lanka
56: Also at INFN Sezione di Pavia a, Università di Pavia b, Pavia, Italy,
Pavia, Italy
57: Also at National and Kapodistrian University of Athens, Athens, Greece
58: Also at Universität Zürich, Zurich, Switzerland
59: Also at Stefan Meyer Institute for Subatomic Physics, Vienna, Austria,
Vienna, Austria
60: Also at Laboratoire d’Annecy-le-Vieux de Physique des Particules,
IN2P3-CNRS, Annecy-le-Vieux, France
61: Also at Şırnak University, Sirnak, Turkey
62: Also at Department of Physics, Tsinghua University, Beijing, China,
Beijing, China
63: Also at Near East University, Research Center of Experimental Health
Science, Nicosia, Turkey
64: Also at Beykent University, Istanbul, Turkey, Istanbul, Turkey
65: Also at Istanbul Aydin University, Application and Research Center for
Advanced Studies (App. & Res. Cent. for Advanced Studies), Istanbul, Turkey
66: Also at Mersin University, Mersin, Turkey
67: Also at Piri Reis University, Istanbul, Turkey
68: Also at Adiyaman University, Adiyaman, Turkey
69: Also at Ozyegin University, Istanbul, Turkey
70: Also at Izmir Institute of Technology, Izmir, Turkey
71: Also at Necmettin Erbakan University, Konya, Turkey
72: Also at Bozok Universitetesi Rektörlügü, Yozgat, Turkey
73: Also at Marmara University, Istanbul, Turkey
74: Also at Milli Savunma University, Istanbul, Turkey
75: Also at Kafkas University, Kars, Turkey
76: Also at Istanbul Bilgi University, Istanbul, Turkey
77: Also at Hacettepe University, Ankara, Turkey
78: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
79: Also at IPPP Durham University, Durham, United Kingdom
80: Also at Monash University, Faculty of Science, Clayton, Australia
81: Also at Bethel University, St. Paul, Minneapolis, USA, St. Paul, USA
82: Also at Karamanoğlu Mehmetbey University, Karaman, Turkey
83: Also at Ain Shams University, Cairo, Egypt
84: Also at Bingol University, Bingol, Turkey
85: Also at Georgian Technical University, Tbilisi, Georgia
86: Also at Sinop University, Sinop, Turkey
87: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey
88: Also at Nanjing Normal University Department of Physics, Nanjing, China
89: Also at Texas A&M University at Qatar, Doha, Qatar
90: Also at Kyungpook National University, Daegu, Korea, Daegu, Korea