EXO-17-009

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EXO-17-009

# Search for pair production of first-generation scalar leptoquarks at
$\sqrt{s}=13\TeV$

###### Abstract

A search for the pair production of first-generation scalar leptoquarks is
performed using proton-proton collision data recorded at 13center-of-mass
energy with the CMS detector at the LHC. The data correspond to an integrated
luminosity of 35.9. The leptoquarks are assumed to decay promptly to a quark
and either an electron or a neutrino, with branching fractions $\beta$ and
$1-\beta$, respectively. The search targets the decay final states comprising
two electrons, or one electron and large missing transverse momentum, along
with two quarks that are detected as hadronic jets. First-generation scalar
leptoquarks with masses below 1435 (1270)are excluded for
$\beta=\,1.0\,(0.5)$. These are the most stringent limits on the mass of
first-generation scalar leptoquarks to date. The data are also interpreted to
set exclusion limits in the context of an $R$-parity violating supersymmetric
model, predicting promptly decaying top squarks with a similar dielectron
final state.

##  0.1 Introduction

The quark and lepton sectors of the standard model (SM) [1, 2, 3] are similar:
both have the same number of generations composed of electroweak doublets.
This could indicate the existence of an additional fundamental symmetry
linking the two sectors, as proposed in many scenarios of physics beyond the
SM. These include grand unified theories with symmetry groups SU(4) of the
Pati–Salam model [4, 5], SU(5), SO(10), and SU(15) [6, 7, 8, 9, 10, 11];
technicolor [12, 13, 14]; superstring-inspired models [15]; and models
exhibiting quark and lepton substructures [16]. A common feature of these
models is the presence of a new class of bosons, called leptoquarks (LQs),
that carry both lepton ($L$) and baryon numbers ($B$). In general, LQs have
fractional electric charge and are color triplets under SU(3)${}_{\text{C}}$.
Their other properties, such as spin, weak isospin, and fermion number
($3B+L$), are model dependent.

Direct searches for LQs at colliders are usually interpreted in the context of
effective theories that impose constraints on their interactions. In order to
ensure renormalizability, these interactions are required to respect SM group
symmetries, restricting the couplings of the LQs to SM leptons and quarks
only. A detailed account of LQs and their interactions can be found in Ref.
[17]. Results from experiments sensitive to lepton number violation, flavor
changing neutral currents, and proton decay allow the existence of three
distinct generations of LQs with negligible intergenerational mixing for mass
scales accessible at the CERN LHC [18, 19]. Indirect searches for new physics
in rare meson decays [20, 21, 22, 23, 24] by LHCb and Belle suggest a possible
breakdown of lepton universality. These anomalies, if confirmed, could provide
additional support for LQ-based models [25]. A comprehensive review of LQ
phenomenology and experimental constraints on their properties is given in
Ref. [26].

We search for the pair production of first-generation scalar LQs that decay
promptly. The final state arising from each LQ decay comprises a quark that is
detected as a hadronic jet, and either an electron or a large missing
transverse momentum attributed to the presence of an undetected neutrino. For
light-quark final states, the quark flavors cannot be determined from the
observed jets. We assume the LQs decay only to $\Pe\,(\Pgne)$ and up or down
quarks. The branching fractions for the LQ decay are expressed in terms of a
free parameter $\beta$, where $\beta$ denotes the branching fraction to an
electron and a quark, and $1-\beta$ the branching fraction to a neutrino and a
quark. For pair production of LQs, we consider two decay modes. The first
arises when each LQ decays to an electron and a quark, having an overall
branching fraction of $\beta^{2}$. In the second mode one LQ decays to an
electron and a quark, and the other to a neutrino and a quark. This mode has a
branching fraction of $2\beta(1-\beta)$. We, therefore, utilize final states
with either two high transverse momentum () electrons and two high- jets,
denoted as $\Pe\Pe\text{jj}$, or one high- electron, large missing transverse
momentum, and two high- jets, denoted as $\Pe\Pgn\text{jj}$.

Previous experiments at the LEP [27], HERA [28, 29], and Tevatron [30, 31]
colliders have searched for LQ production and placed lower limits of several
hundreds of on allowed LQ masses ($m_{\text{LQ}}$) at 95% confidence level
(CL). The CMS experiment at the LHC has extended the limits on pair production
of first-generation scalar LQs using proton-proton () collision data recorded
during 2012 at a center-of-mass energy of $\sqrt{s}=8\TeV$. Based on a sample
corresponding to an integrated luminosity of 19.7, the lower limit obtained on
$m_{\text{LQ}}$ was 1010 (850)for $\beta=1.0\,(0.5)$ [32]. The CMS
Collaboration has also published results on a search for singly produced LQs
with the final states of either two electrons and one jet, or two muons and
one jet [33]. Recently, using a data set of 3.2collected at $\sqrt{s}=13\TeV$,
the ATLAS experiment has placed a lower limit on $m_{\text{LQ}}$ of 1100 [34]
for $\beta=1.0$.

This analysis is based on data recorded in collisions at $\sqrt{s}=13\TeV$
with the CMS detector, corresponding to an integrated luminosity of 35.9. At
LHC energies, the pair production of LQs would mainly proceed via gluon-gluon
fusion with a smaller contribution from quark-antiquark annihilation. The
corresponding Feynman diagrams are shown in Fig. 1. The production cross
section as a function of $m_{\text{LQ}}$ has been calculated at next-to-
leading order (NLO) in perturbation theory [35]. At the LHC, the LQ-lepton-
quark Yukawa coupling has negligible effect on the production rate for
promptly decaying LQs, which are the focus of our search.

Figure 1: Leading order Feynman diagrams for the scalar LQ pair production
channels at the LHC.

The paper is organized as follows. Section 0.2 introduces the CMS detector,
and Sec. 0.3 describes the data and simulated samples used in the search. The
core of the analysis in terms of event reconstruction and selection is
discussed in Sec. 0.4, while the background estimation is presented in Sec.
0.5. Section 0.6 deals with the systematic uncertainties affecting this
analysis. Sections 0.7 and 0.8 describe the results of the LQ search and its
interpretation in an exotic scenario of supersymmetry, respectively. We
conclude with a summary of the main results in Sec. 0.9.

##  0.2 The CMS detector

The key feature of the CMS apparatus is a superconducting solenoid of 6m
diameter, providing a magnetic field of 3.8T. Within the solenoid volume lie a
silicon pixel and microstrip tracker, a lead-tungstate crystal electromagnetic
calorimeter (ECAL), and a brass-scintillator hadron calorimeter (HCAL), each
composed of a barrel and two end-cap sections. Forward calorimeters extend the
pseudorapidity ($\eta$) coverage provided by the barrel and end-cap detectors.
Muons are detected in gas-ionization chambers embedded in the steel flux-
return yoke outside the solenoid. The first level of the trigger system [36],
composed of custom electronics, uses information from the calorimeters and
muon detectors to select the most interesting events in an interval of less
than 4$\mu$s. The high-level trigger processor farm further reduces the event
rate from around 100kHz to 1kHz, before data storage. A detailed description
of the CMS detector, along with a definition of the coordinate system used and
the relevant kinematic variables, can be found in Ref. [37].

##  0.3 Data and simulated samples

Events are selected using a combination of triggers requiring either a single
electron or a single photon. Electron candidates are required to have a
minimum of 27 (115)for the low (high) threshold trigger. Each of these
triggers examines clusters of energy deposited in the ECAL that are matched to
tracks reconstructed within a range $\abs{\eta}<2.5$. Cluster shape
requirements as well as calorimetric and track-based isolation (only for the
low threshold trigger) are also applied. By comparison, the photon trigger
requires $\pt>175\GeV$ without any requirements on track-cluster matching,
cluster shape, or isolation. The latter three criteria are applied to electron
triggers to reduce background rates and are not necessary at high . Therefore,
the single photon and electron triggers are combined to improve efficiency at
high electron . Events selected using other single-photon triggers with lower
thresholds are used for determining the multijet background.

Monte Carlo (MC) simulation samples of scalar LQ signals are generated using
version 8.212 [38] at leading order (LO) with the NNPDF2.3LO parton
distribution function (PDF) set [39]. Samples are generated for
$m_{\text{LQ}}$ ranging from 200 to 2000in 50steps. The LQ is assumed to have
quantum numbers corresponding to the combination of an electron ($L=1$) and an
up quark ($B=1/3$), implying it has an electric charge of $-1/3$. Possible
formation of hadrons containing LQs is not included in the simulation. The
cross sections are normalized to the values calculated at NLO [40, 35] using
the CTEQ6L1 PDF set [41].

The main backgrounds for searches in the $\Pe\Pe\text{jj}$ and
$\Pe\Pgn\text{jj}$ channels include Drell–Yan ($\cPZ/\PGg^{*}$) production
with jets, top quark pair production (), single top quark and diboson
($\text{VV}=\PW\PW$, , or ) production. Additional background contributions
arise from $\PW\text{+jets}$, $\PGg\text{+jets}$, and multijet production,
where jets are misidentified as electrons. The background in the
$\Pe\Pe\text{jj}$ channel as well as the multijet background in both channels
are estimated from data, while MC simulated events are used to calculate all
other backgrounds. The $\cPZ/\PGg^{*}\text{+jets}$, $\PW\text{+jets}$, and VV
samples are generated at next to leading order (NLO) with version 2.3.3 using
the FxFx merging method [42, 43]. Both and single top quark events are
generated at NLO using , and v2 complemented with MadSpin [44], except for
single top quark production in association with a boson, where events are
generated with v1 at NLO [45, 46, 47, 48, 49, 50], and $s$-channel single top
quark production, where at NLO is used. The $\PGg\text{+jets}$ events are
generated with at LO with MLM merging [51]. The NNPDF3.0 at NLO [52] PDF set
is used, except for $\PGg\text{+jets}$ events that are generated using the LO
PDF set.

The $\PW\text{+jets}$ and $\cPZ/\PGg^{*}\text{+jets}$ samples are normalized
to next-to-NLO (NNLO) inclusive cross sections calculated with versions 3.1
and 3.1.b2, respectively [53]. Single top quark samples are normalized to NLO
inclusive cross sections [54, 55], except for the $\PQt\PW$ production, where
the NNLO calculations of Refs. [56] are used. The calculations from Refs. [57,
58, 59, 60, 61, 62, 63] with Top++2.0 are used to normalize the sample at NNLO
in quantum chromodynamics (QCD) including resummation of the next-to-next-to-
leading-logarithmic soft gluon terms.

8.212 with the CUETP8M1 underlying event tune [64] is used for hadronization
and fragmentation in all simulated samples, with the exception of a dedicated
tune used for the sample [65]. All samples include an overlay of minimum bias
events (pileup), generated with an approximate distribution for the number of
additional $\Pp\Pp$ interactions expected within the same or nearby bunch
crossings, and reweighted to match the distribution observed in data. In all
cases, the software v.10.00.p02 [66, 67] is used to simulate the response of
the CMS detector.

##  0.4 Event reconstruction and selection

A particle-flow (PF) algorithm [68] aims to reconstruct and identify each
individual particle in a given event, by optimally combining information from
the various elements of the CMS detector. The energy of photons is directly
obtained from the ECAL measurement. On the other hand, the energy of electrons
is determined from a combination of their momentum at the primary interaction
vertex as determined by the tracker, the energy of the corresponding ECAL
clusters, and the energy sum of all bremsstrahlung photons spatially
compatible with originating from the associated track. The momentum of muons
is obtained from the curvature of the corresponding track. The energy of
charged hadrons is determined from a combination of their momentum measured in
the tracker and the matching ECAL and HCAL energy deposits, corrected for zero
suppression effects as well as for the response function of the calorimeters
to hadronic showers. Finally, the energy of neutral hadrons is obtained from
the corresponding corrected ECAL and HCAL energy.

Electrons are identified by spatially matching a reconstructed charged-
particle track to a cluster of energy deposits in the ECAL. The ECAL cluster
is required to have longitudinal and transverse profiles compatible with those
expected from an electromagnetic shower. Electrons used in this analysis are
required to have $\pt>50\GeV$ and $\abs{\eta}<2.5$, excluding the transition
regions between barrel and end-cap detectors $1.4442<\abs{\eta}<1.5660$.
Additional selection criteria are applied to electron candidates in order to
reduce backgrounds while maintaining high efficiency for identification of
electrons with large [69]. The absolute difference in $\eta$ between the ECAL
cluster seed and the matched track is required to be less than 0.004 (0.006)
in the barrel (end cap), and the corresponding quantity in the azimuthal
angle, $\phi$, must be less than 0.06rad. Leptons resulting from the decay of
LQs are expected to be isolated from hadronic activity in the event.
Requirements are, therefore, applied based on calorimeter energy deposits and
tracks in the vicinity of electron candidates. The scalar sum of associated
with calorimeter clusters in a cone of radius $\Delta
R=\sqrt{\smash[b]{(\Delta\eta)^{2}+(\Delta\phi)^{2}}}=0.3$ centered on the
electron candidate, excluding clusters associated to the candidate itself,
must be less than 3% of the electron . A correction to the isolation sum
accounts for contributions from pileup interactions. The track-based
isolation, calculated as the scalar sum of all tracks in the cone defined
above, must be less than 5to reduce misidentification of jets as electrons. At
most one layer of the pixel detector may have missing hits along the
trajectory of the matched track. The track must also be compatible with
originating from the primary interaction vertex, which is taken to be the
reconstructed vertex with the largest value of summed physics-object
$\pt^{2}$. Here the physics objects are the jets, reconstructed using the
algorithm [70, 71] with the tracks assigned to the vertex as inputs, and the
negative vector sum of the of those jets. To correct for the possible
difference of electron reconstruction and identification efficiencies between
collision and simulated data, appropriate corrections or scale factors are
applied to the simulated samples.

Muons are used in defining a control region to estimate the background
contribution. They are identified as tracks in the central tracker consistent
with either a track or several hits in the muon system [72]. These muon
candidates must have $\pt>35\GeV$ and $\abs{\eta}<2.4$, and are required to
pass a series of identification criteria designed for high-muons as follows.
Segments in at least two muon stations must be geometrically matched to a
track in the central tracker, with at least one hit from a muon chamber
included in the muon track fit. In order to reject muons from decays in flight
and increase momentum measurement precision, at least five tracker layers must
have hits associated with the muon, and there must be at least one hit in the
pixel detector. Isolation is imposed by requiring the sum of tracks in a cone
of $\Delta R=0.3$ (excluding the muon itself) divided by the muon to be less
than 0.1. For rejection of cosmic ray muons, the transverse impact parameter
of the muon track with respect to the primary vertex must be less than 2 mm
and the longitudinal distance of the track formed from tracker system only to
the primary vertex must be less than 5mm. Finally, the relative uncertainty on
the measurement from the muon track must be less than 30%.

Jets are reconstructed using the anti-algorithm [70, 71] with a distance
parameter of 0.4. Their momentum is determined as the vectorial sum of all
particle momenta in the jet, and is found in simulation to be within 5–10% of
the true momentum [73] over the entire spectrum and detector acceptance.
Pileup interactions can contribute spurious tracks and calorimeter energy
deposits to the jet momentum. To mitigate this effect, tracks identified to be
originating from pileup vertices are discarded, while a correction [74] is
applied to compensate for the remaining contributions. Jet energy corrections
are extracted from simulation to compensate for differences between the true
and reconstructed momenta of jets. In situ measurements of the momentum
balance in dijet, $\PGg\text{+jets}$, $\cPZ/\PGg^{*}\text{+jets}$, and
multijet events are used to estimate and correct for any residual differences
in jet energy scale between data and simulation [74]. Additional selection
criteria are applied to all jets to remove those potentially affected by
spurious energy deposits originating from instrumental effects or
reconstruction failures [75]. Jets must have $\pt>50\GeV$ and
$\abs{\eta}<2.4$, and only jets separated from electrons or muons by $\Delta
R>0.3$ are retained.

The missing transverse momentum () is given by the negative vector sum of of
all PF candidates in the event. The magnitude of is referred to as .

To identify $\cPqb$ jets arising from top quark decays in the determination of
the $\Pe\Pgn\text{jj}$ background control regions, the combined secondary
vertex algorithm is used with the loose working point of Ref. [76]. Based on
simulation, the corresponding $\cPqb$-jet identification efficiency is above
80% with a probability of 10% of misidentifying a light-flavor jet.

###  0.4.1 The $\Pe\Pe\text{jj}$ channel

For the $\Pe\Pe\text{jj}$ analysis, we select events with at least two
electrons and at least two jets passing the criteria described above. No
charge requirements are imposed on the electrons. When additional objects
satisfy these requirements, the two highest electrons and jets are considered.
Further, there should not be any muon fulfilling the requirements mentioned
earlier in this section. The dielectron invariant mass $m_{\Pe\Pe}$ is
required to be greater than 50. The of the dielectron system must be greater
than 70. The scalar sum over the electrons and two jets,
$S_{\mathrm{T}}=\pt(\Pe_{1})+\pt(\Pe_{2})+\pt(\text{j}_{1})+\pt(\text{j}_{2})$,
must be at least 300. This initial selection is used for the determination of
backgrounds in control regions, as explained in Section 0.5.

Final selections are then optimized by maximizing the Punzi criterion for
observation of a signal at a significance of five standard deviations [77].
These selections are determined by examining three variables: $m_{\Pe\Pe}$,
$S_{\mathrm{T}}$, and $m_{\Pe\text{j}}^{\text{min}}$. The electron-jet pairing
is chosen to minimize the difference in the invariant mass of the LQ
candidates, and the quantity $m_{\Pe\text{j}}^{\text{min}}$ is defined as the
smaller of the two masses. Thresholds for the three observables are varied
independently, and the Punzi criterion is then calculated at each set of
thresholds as well as for each $m_{\text{LQ}}$ hypothesis. The optimized
thresholds as a function of $m_{\text{LQ}}$ are shown in Fig. 2 (left). For
the $m_{\text{LQ}}$ hypotheses above 1050, the statistical uncertainty in the
background prediction becomes large, making an optimization for these masses
impossible, and thus the thresholds for the 1050hypothesis are applied.

Figure 2:  Optimized threshold values applied for the selection variables in
the $\Pe\Pe\text{jj}$ (left) and $\Pe\Pgn\text{jj}$ (right) channels as a
function of $m_{\text{LQ}}$.

###  0.4.2 The $\Pe\Pgn\text{jj}$ channel

In the $\Pe\Pgn\text{jj}$ channel, we select events containing exactly one
electron, at least two jets, and $\ptmiss>100\GeV$. The electron and jets must
pass the aforementioned identification criteria. Events with isolated muons
are rejected, applying the same criteria as for the $\Pe\Pe\text{jj}$ channel.
The absolute difference in the angle between the and the leading jet,
$\Delta\phi(\ptvecmiss,\text{j}_{1})$, is required to be larger than 0.5rad.
This helps reject events with arising primarily from instrumental effects. The
$\Delta\phi(\ptvecmiss,\Pe)$ must be greater than 0.8rad for similar reasons.
The and transverse mass of the -electron system must be greater than 70 and
50, respectively. Here and later, the transverse mass of a two-object system
is given by $\mT=\sqrt{\smash[b]{2p_{{\rm T},1}p_{{\rm
T},2}(1-\cos\Delta\phi)}}$, with $\Delta\phi$ being the angle between the
vectors of two objects, namely , electron and jet. The criterion helps
suppress the $\PW\text{+jets}$ contribution. Finally, selected events must
have $S_{\mathrm{T}}>300\GeV$, where
$S_{\mathrm{T}}=\pt(\Pe)+\ptmiss+\pt(\text{j}_{1})+\pt(\text{j}_{2})$. This
initial selection is used for the determination of backgrounds in control
regions, similarly to the $\Pe\Pe\text{jj}$ channel.

The selection criteria are then optimized in a similar fashion as for the
$\Pe\Pe\text{jj}$ channel, except that four observables are considered for
final selections at each $m_{\text{LQ}}$ hypothesis: $S_{\mathrm{T}}$, of the
-electron system, , and the electron-jet invariant mass $m_{\Pe\text{j}}$. The
-jet and electron-jet pairing is chosen to minimize the difference in between
the two LQ candidates. The optimized thresholds as a function of
$m_{\text{LQ}}$ are shown in Fig. 2 (right). As with the $\Pe\Pe\text{jj}$
channel, for the $m_{\text{LQ}}$ hypotheses above 1200, the thresholds for the
1200hypothesis are used.

##  0.5 Background estimation

The SM processes that produce electrons and jets can have final states similar
to those of an LQ signal and are, therefore, considered as backgrounds for
this search. These include dilepton events from $\cPZ/\PGg^{*}\text{+jets}$, ,
and VV; single top quark production; and $\PW\text{+jets}$. Another background
arises from multijet production in which at least one jet is misidentified as
an electron.

The major backgrounds in the $\Pe\Pe\text{jj}$ channel are
$\cPZ/\PGg^{*}\text{+jets}$ and production. The $\cPZ/\PGg^{*}\text{+jets}$
background is estimated from simulation and normalized to the data in a
control region that comprises the initial selection plus a window of
$80<m_{\Pe\Pe}<100\GeV$ around the nominal boson mass; the latter criterion is
applied to enrich the sample with $\cPZ/\PGg^{*}\text{+jets}$ events. The
$m_{\Pe\Pe}$ distribution is corrected for the presence of
non-$\cPZ/\PGg^{*}\text{+jets}$ events in the data control region using
simulation. The resulting normalization factor applied to the
$\cPZ/\PGg^{*}\text{+jets}$ simulated events is $R_{\PZ}=0.97\pm 0.01\stat$.

The contribution from events containing two electrons is estimated using a
control region in data, which consists of events containing one electron and
one muon, to which all applicable $\Pe\Pe\text{jj}$ selection criteria are
applied. Residual backgrounds from other processes are subtracted using
simulated event samples. Corrections for the branching fractions between the
two states as well as for the differences in electron/muon identification and
isolation efficiencies and acceptances are determined using simulation. The
difference in the trigger efficiency between the one- and two-electron final
states is corrected by reweighting each event in the sample with the
calculated efficiencies for the single electron final state.

After application of event selection requirements, the background contribution
to the $\Pe\Pe\text{jj}$ channel arising from single top quark production,
$\PW\text{+jets}$, and VV is found to be small and is estimated from
simulations.

The multijet background in the $\Pe\Pe\text{jj}$ channel is estimated using
control samples in data. The electron identification requirements for the
calorimeter shower profile and track-cluster matching are relaxed to define a
loose selection. We measure the probability that an electron candidate that
passes the loose selection requirements also satisfies the electron
identification and isolation criteria used in the analysis. This probability
is obtained as a function of the candidate and $\eta$. The events are required
to have exactly one loose electron, at least two jets, and low ($<100\gev$).
Contributions from electrons satisfying the full identification requirements
are removed. The number of such electrons is calculated by comparing the
number of candidates that pass the tight selection criteria minus the track-
isolation requirement, with those that satisfy the track-isolation requirement
but fail one of the other selection criteria. This sample is dominated by QCD
multijet events. The distribution of multijet events in the $\Pe\Pe\text{jj}$
channel following final selections is obtained by applying the measured
probability twice to an event sample with two electrons passing loose electron
requirements, and two or more jets that satisfy all the requirements of the
signal selection. The normalization is obtained by scaling the weighted
multijet sample to an orthogonal control region defined by inverting track-
isolation requirement for electrons.

Distributions of kinematic variables for the $\Pe\Pe\text{jj}$ channel in
data, including those used in the final selections, have been studied at the
initial selection level, and are found to agree with the background models
within background estimation uncertainties. The distributions of
$S_{\mathrm{T}}$, $m_{\Pe\text{j}}^{\text{min}}$, and $m_{\Pe\Pe}$ are shown
in Fig. 3.

Figure 3: Data and background comparison for events passing the initial
selection requirements for the $\Pe\Pe\text{jj}$ channel, shown for the
variables used for final selection optimization: $m_{\Pe\Pe}$ (upper),
$m_{\Pe\text{j}}^{\text{min}}$ (lower left), and $S_{\mathrm{T}}$ (lower
right). “Other background” includes diboson, single top quark, and
$\PW\text{+jets}$. Signal predictions for $m_{\text{LQ}}=650$ and
1200hypotheses are overlaid on the plots. The last bin includes all events
beyond the upper $x$-axis boundary.

The largest background in the $\Pe\Pgn\text{jj}$ channel comes from
$\PW\text{+jets}$ and production. Single top quark, VV, and
$\cPZ/\PGg^{*}\text{+jets}$ backgrounds have small contributions and are
estimated from simulations. The QCD multijet background is estimated from
control samples in data using the same probability for jets to be
misidentified as electrons as is used in the background estimation for the
$\Pe\Pe\text{jj}$ channel. The number of multijet events at the final
selection is obtained by selecting events having exactly one loose electron,
large , and at least two jets satisfying the signal selection criteria, and
weighting these with the probability of a jet being misidentified as an
electron.

The background contributions from $\PW\text{+jets}$ and are estimated from
simulation, and normalized to the data in a control region defined by
requiring $50<\mT<110\GeV$ after the initial selection. Then -tagging
information is used to distinguish $\PW\text{+jets}$ from in the control
region. The $\PW\text{+jets}$ contribution is enhanced by requiring zero
-tagged jets in the event, while the control region is defined by requiring at
least one -tagged jet in the event. These regions each have a purity of about
75%. The normalization factors for the two backgrounds are determined from
these control regions using

$\displaystyle
N_{1}=R_{\ttbar}N_{1,\ttbar}+R_{\PW}N_{1,{\PW}}+N_{1,\mathrm{O}}$ (1)
$\displaystyle
N_{2}=R_{\ttbar}N_{2,\ttbar}+R_{\PW}N_{2,{\PW}}+N_{2,\mathrm{O}},$

where $N_{1\,(2)}$ is the number of events in the ($\PW\text{+jets}$) control
region in data. The terms $N_{i,\ttbar}$ and $N_{i,{\PW}}$ are the numbers of
and $\PW\text{+jets}$ events in the simulated samples, while
$N_{i,\mathrm{O}}$ is the number of events arising from other background
sources, namely diboson, single top quark, $\cPZ/\PGg^{*}\text{+jets}$ and
multijet. The subscript $i=1,2$ refers to the two control regions described
above. The background normalization factors $R_{\ttbar}=0.92\pm 0.01\stat$ and
$R_{\PW}=0.87\pm 0.01\stat$ are then determined by solving Eq. (1).

The observed distributions of kinematic variables for the $\Pe\Pgn\text{jj}$
channel following the initial selection are found to agree with the background
prediction within estimation uncertainties. The distributions of ,
$m_{\Pe\text{j}}$, $S_{\mathrm{T}}$, and are shown in Fig. 4.

Figure 4: Data and background for events passing the initial selection
requirements in the $\Pe\Pgn\text{jj}$ channel, shown for the variables used
for final selection optimization: (upper left), $m_{\Pe\text{j}}$ (upper
right), $S_{\mathrm{T}}$ (lower left), and (lower right). “Other background”
includes diboson, single top quark, and $\cPZ/\PGg^{*}\text{+jets}$. Signal
predictions for $m_{\text{LQ}}=650$ and 1200hypotheses are overlaid on the
plots. The last bin includes all events beyond the upper $x$-axis boundary.

##  0.6 Systematic uncertainties

The sources of systematic uncertainties considered in this analysis are listed
in Table 0.6. Uncertainties in the reconstruction of electrons, jets and
affect the selected sample of events used in the analysis. The uncertainty due
to the electron energy scale is obtained by shifting the electron energy up
and down by 2%. The uncertainty in the electron energy resolution is measured
by smearing the electron energy by $\pm$10% [78]. The uncertainties due to
electron reconstruction and identification efficiencies are obtained by
varying the corresponding scale factors applied to simulated events by $\pm 1$
standard deviation with respect to their nominal values. The trigger
efficiency for electrons is measured by utilizing the tag-and-probe method
[79] in data, and parametrized as a function of electron and $\eta$. The
corresponding uncertainty depends on the number of data events and is almost
entirely statistical in origin for the kinematic range studied in this
analysis.

The uncertainty due to the jet energy scale is obtained by varying the nominal
scale correction by $\pm$1 standard deviation and taking the maximum
difference with respect to the nominal event yield. The jet energy resolution
models the variation between the reconstructed and generated jets. The
corresponding uncertainty is obtained by modifying the parametrization of this
difference [74].

To determine uncertainties in , we consider up and down shifts in the jet
energy scale and resolution, electron energy correction, and the scale
corrections applied to the energy not associated with any PF candidates. For
each variation, a new vector is computed for each event. The uncertainties
corresponding to different variations in the quantities are then added in
quadrature to determine the variation in , and the maximum difference of the
event yield with respect to nominal is taken as the uncertainty.

Variations in the shape of the $\cPZ/\PGg^{*}\text{+jets}$ ($\Pe\Pe\text{jj}$
channel only), $\PW\text{+jets}$ and ($\Pe\Pgn\text{jj}$ channel only), and
diboson (both channels) backgrounds are determined using simulated samples
with renormalization and factorization scales independently varied up and down
in the matrix element by a factor of two, yielding eight different
combinations. The event yields are then calculated for each of these
variations and the maximum variation with respect to nominal is taken as the
systematic uncertainty. The corresponding normalization uncertainties are
evaluated from the statistical uncertainties in the scale factors obtained
while normalizing these backgrounds to data in the control regions. In the
$\Pe\Pgn\text{jj}$ channel, an additional uncertainty of 10% is included to
account for the observed differences associated with the choice of the range,
defining the control region used to calculate the normalization scale factors.
As described above, -tagging is used to define the control region for
$\PW\text{+jets}$ and normalization in the $\Pe\Pgn\text{jj}$ channel;
therefore the uncertainty in the -tagging efficiency (3%) is taken into
account.

The uncertainty in the QCD multijet background is assessed by using an
independent data sample. This sample is required to have exactly two electron
candidates satisfying loosened criteria applied to the track-cluster matching,
the isolation (both track-based and calorimetric), and the shower profile. We
compare the number of events in this sample, where one candidate satisfies the
electron selection requirements, to that predicted by the multijet background
method. This test is repeated on a subsample of the data after applying an
$S_{\mathrm{T}}$ threshold of 320, which corresponds to the optimized final
selection for an LQ mass of 200. The relative difference of 25% observed
between the results of the two tests is taken as the systematic uncertainty in
the probability for a jet to be misidentified as an electron and applied in
the $\Pe\Pgn\text{jj}$ channel. For the $\Pe\Pe\text{jj}$ case, we assume full
correlation between the two electrons and take 50% as the uncertainty.

The uncertainty in the integrated luminosity is 2.5% [80]. An uncertainty in
the modeling of pileup is evaluated by reweighting the simulated events after
varying the inelastic $\Pp\Pp$ cross section by $\pm$4.6% [81]. The acceptance
for both signal and backgrounds, and the expected background cross sections
are affected by PDF uncertainties. We estimate this effect by evaluating the
complete set of NNPDF 3.0 PDF eigenvectors, following the PDF4LHC prescription
[82, 83, 84, 85, 52].

Systematic uncertainties for the $\Pe\Pe\text{jj}$ and $\Pe\Pgn\text{jj}$
channels. The values shown are calculated for the selections used in the
$m_{\text{LQ}}=1000\GeV$ search hypothesis and reflect the variations in the
event yields due to each source. Major backgrounds, namely
$\cPZ/\PGg^{*}\text{+jets}$ ($\Pe\Pe\text{jj}$), $\PW\text{+jets}$ and
($\Pe\Pgn\text{jj}$), are normalized at the initial selection level when
calculating the effect of shifts for various systematics. lrrrrr &
$\Pe\Pe\text{jj}$ $\Pe\Pgn\text{jj}$
Source of the uncertainty Signal (%) Background (%) Signal (%) Background (%)
Electron energy scale 1.5 2.5 1.9 6.9
Electron energy resolution 0.2 5.3 0.1 4.9
Electron reconstr. efficiency 3.0 3.0 0.6 0.8
Electron identif. efficiency 1.3 0.3 0.6 0.1
Trigger 1.1 1.4 9.5 7.6
Jet energy scale 0.5 0.9 0.5 2.3
Jet energy resolution 0.1 1.7 0.1 2.4
— — 0.8 13.1
$\cPZ/\PGg^{*}\text{+jets}$ shape — 5.6 — —
$\cPZ/\PGg^{*}\text{+jets}$ normalization — 1.0 — —
$\PW\text{+jets}$ shape — — — 7.1
$\PW\text{+jets}$ normalization — — — 1.1
$\PW\text{+jets}$ sideband selection — — — 10.0
$\PW\text{+jets}$ tagging — — — 3.0
shape — — — 10.4
normalization — 1.0 — 1.0
tagging — — — 3.0
Diboson shape — 3.4 — 3.2
QCD multijet — $<$0.1 — 2.6
Integrated luminosity 2.5 0.6 2.5 0.5
Pileup 0.2 1.0 0.4 1.4
PDF 2.8 3.0 2.9 4.7

##  0.7 Results of the leptoquark search

After applying the final selection criteria shown in Fig. 2, the data are
compared to SM background expectations for both channels and each
$m_{\text{LQ}}$ hypothesis. Distributions of $m_{\Pe\text{j}}^{\text{min}}$
and $S_{\mathrm{T}}$ are shown in Fig. 5 for the $\Pe\Pe\text{jj}$ channel
with the selections applied for the 650 and 1200$m_{\text{LQ}}$ hypotheses.
Figure 6 shows the corresponding distributions of $m_{\Pe\text{j}}$ and
$S_{\mathrm{T}}$ for the $\Pe\Pgn\text{jj}$ channel for the same mass
hypotheses.

Figure 7 shows background, data, and expected signal for each LQ mass point
after applying the final selection criteria. Signal efficiency times
acceptance, along with tables listing event yields for signal, background, and
data are provided in Appendix .10. The data are found to be in agreement with
SM background expectations in both channels. We set upper limits on the
product of the cross section and branching fraction for scalar LQs as a
function of $m_{\text{LQ}}$ and $\beta$. The limits are calculated using the
asymptotic approximation [86] of the modified frequentist approach [87, 88,
89]. Systematic uncertainties described in Sec. 0.6 are modeled with log-
normal probability density functions, while statistical uncertainties are
modeled with gamma functions whose widths are calculated from the number of
events in the control regions or simulated samples.

Figure 5: $m_{\Pe\text{j}}^{\text{min}}$ (left) and $S_{\mathrm{T}}$ (right)
distributions for events passing the $\Pe\Pe\text{jj}$ final selection for LQs
of mass 650 (upper) and 1200 (lower). The predicted signal model distributions
are shown, along with major backgrounds and “other background” which consists
of the sum of the $\PW\text{+jets}$, diboson, single top quark, and
$\PGg\text{+jets}$ contributions. The background contributions are stacked,
while the signal distributions are plotted unstacked. The dark shaded region
indicates the statistical and systematic uncertainty in the total background.
The last bin includes all events beyond the upper $x$-axis boundary.

Figure 6: $m_{\Pe\text{j}}$ (left) and $S_{\mathrm{T}}$ (right) distributions
for events passing the $\Pe\Pgn\text{jj}$ final selection for LQs of mass 650
(upper) and 1200 (lower). The predicted signal model distributions are shown,
along with major backgrounds and “other background” which consists of the sum
of $\cPZ/\PGg^{*}\text{+jets}$, diboson, single top quark, and
$\PGg\text{+jets}$ contributions. The background contributions are stacked,
while the signal distributions are plotted unstacked. The dark shaded region
indicates the statistical and systematic uncertainty in the total background.
The last bin includes all events beyond the upper $x$-axis boundary.

Figure 7:  Data, background, and expected signal yields after applying the
final selection criteria for the $\Pe\Pe\text{jj}$ (left) and
$\Pe\Pgn\text{jj}$ (right) channels. “Other background” includes diboson,
single top quark, and $\PW\text{+jets}$ (for the $\Pe\Pe\text{jj}$ channel) or
$\cPZ/\PGg^{*}\text{+jets}$ (for the $\Pe\Pgn\text{jj}$ channel). The bin
contents are correlated, because events selected for higher-mass LQ searches
are a subset of those selected for lower mass searches.

We set upper limits on the production cross section multiplied by the
branching fraction $\beta^{2}$ or $2\beta(1-\beta)$ at 95% CL as a function of
$m_{\text{LQ}}$. The expected and observed limits are shown with NLO
predictions for the scalar LQ pair production cross section in Fig. 8 for both
$\Pe\Pe\text{jj}$ and $\Pe\Pgn\text{jj}$ channels. The observed limits are
within two standard deviations of expectations from the background-only
hypothesis. The uncertainty in the theoretical prediction for the LQ pair
production cross section is calculated as the quadrature sum of the PDF
uncertainty in the signal cross section and the uncertainty due to the choice
of renormalization and factorization scales. The latter is estimated by
independently varying the scales up and down by a factor of two.

Figure 8:  Observed upper limits for scalar LQ pair-production cross section
times $\beta^{2}$ (left) and $\beta(1-\beta)$ (right) at 95% CL obtained with
the $\Pe\Pe\text{jj}$ (left) and $\Pe\Pgn\text{jj}$ (right) analysis. The
median (dashed line), 68% (inner green band) and 95% (outer yellow band)
confidence-interval expected limits are also shown.

Under the assumption $\beta=1.0$, where only the $\Pe\Pe\text{jj}$ channel
contributes, first-generation scalar LQs with masses less than 1435are
excluded at 95% CL compared to a median expected limit of 1465. For
$\beta=0.5$, using the $\Pe\Pgn\text{jj}$ channel alone, LQ masses are
excluded below 1195with the corresponding expected limit being 1210. As both
$\Pe\Pe\text{jj}$ and $\Pe\Pgn\text{jj}$ decays contribute at $\beta$ values
smaller than 1, the LQ mass limit is improved using the combination of the two
channels. In this combination, systematic uncertainties are considered to be
fully correlated between the channels, while statistical uncertainties are
treated as fully uncorrelated. Limits for a range of $\beta$ values from 0 to
1 are set at 95% CL for both $\Pe\Pe\text{jj}$ and $\Pe\Pgn\text{jj}$
channels, as well as for their combination, as shown in Fig. 9. In the
$\beta=0.5$ case, the combination excludes first-generation scalar LQs with
masses less than 1270, compared to a median expected value of 1285.

Figure 9:  Expected and observed exclusion limits at 95% CL for pair
production of first-generation scalar LQ shown in the $\beta$ versus
$m_{\text{LQ}}$ plane for the individual $\Pe\Pe\text{jj}$ and
$\Pe\Pgn\text{jj}$ channels and their combination. The inner green and outer
yellow bands represent the 68% and 95% confidence intervals on the expected
limits.

##  0.8 $R$-parity violating supersymmetry interpretation

Many new physics models predict the existence of particles with couplings of
the type expected for LQs. One such model is $R$-parity violating
supersymmetry (RPV SUSY) [90, 91], where the superpartners of quarks or
‘squarks’ can decay into LQ-like final states. For example, the top squark ()
can decay to a bottom quark and an electron. The topology of the resulting
events is similar to an LQ decay and hence these events will pass our nominal
selection for the $\Pe\Pe\text{jj}$ channel.

The analysis is recast in terms of the possible production of prompt top-
squark pairs ($c\tau=0\unit{cm}$), with each subsequently decaying to a bottom
quark and an electron. Limits on the production cross section for pairs are
calculated from the $\Pe\Pe\text{jj}$ data, accounting for the difference in
branching fractions of LQ and decays to electrons.

Figure 10 shows the expected and observed 95% CL upper limits on the RPV SUSY
pair production cross section as a function of the squark mass ($m_{\PSQt}$).
The observed exclusion limit is 1100for $c\tau=0$cm.

Figure 10: Expected and observed upper limits at 95% CL on the RPV SUSY squark
pair production cross section as a function of $M_{\PSQt}$ for $c\tau=0$cm.
The expected limits represent the median values, while the inner green and
outer yellow bands are the 68% and 95% confidence intervals, respectively.

##  0.9 Summary

A search has been performed for the pair production of first-generation scalar
leptoquarks in final states consisting of two high-momentum electrons and two
jets, or one electron, large missing transverse momentum and two jets. The
data sample used in the study corresponds to an integrated luminosity of
35.9recorded by the CMS experiment at $\sqrt{s}=13\TeV$. The data are found to
be in agreement with standard model background expectations and a lower limit
at 95% confidence level is set on the scalar leptoquark mass at 1435 (1270)for
$\beta=$ 1.0 (0.5), where $\beta$ is the branching fraction of the leptoquark
decay to an electron and a quark. These results constitute the most stringent
limits on the mass of first-generation scalar leptoquarks to date. The data
are also interpreted in the context of an $R$-parity violating supersymmetric
model with promptly decaying top squarks, which can decay into leptoquark-like
final states. Top squarks are excluded for masses below 1100.

###### 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); RPF
(Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, and ERDF (Estonia); Academy of
Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and
HGF (Germany); GSRT (Greece); 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 and SFFR (Ukraine); STFC (United Kingdom); DOE and NSF (USA).
Individuals have received support from the Marie-Curie program and the
European Research Council and Horizon 2020 Grant, contract No. 675440
(European Union); the Leventis Foundation; the A. P. Sloan Foundation; the
Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office;
the Fonds pour la Formation à la Recherche dans l’Industrie et dans
l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en
Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the
“Excellence of Science - EOS” - be.h project n. 30820817; the Ministry of
Education, Youth and Sports (MEYS) of the Czech Republic; 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 and 125105 (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 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 Welch Foundation, contract C-1845; and the
Weston Havens Foundation (USA).

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##  .10 Efficiencies and event yields

In Fig. 11 the product of signal acceptance and efficiency is shown after
final optimized selections as a function of $m_{\text{LQ}}$ for the
$\Pe\Pe\text{jj}$ (left) and $\Pe\Pgn\text{jj}$ (right) channels. Tables .10
and .10 list the number of events passing the final selection criteria in data
and the various background components as a function of $m_{\text{LQ}}$ for the
$\Pe\Pe\text{jj}$ and $\Pe\Pgn\text{jj}$ channels, respectively.

Figure 11:  The product of signal acceptance and efficiency after final
optimized selections, as a function of $m_{\text{LQ}}$ for the
$\Pe\Pe\text{jj}$ (left) and $\Pe\Pgn\text{jj}$ (right) channels.

Event yields after the optimized $\Pe\Pe\text{jj}$ selections. Uncertainties
are statistical except for the total background, where both statistical and
systematic uncertainties are shown. An entry of $0.0$ quoted for the
uncertainty indicates that its value is negligibly small. LQ masses are given
in units of and init. sel. refers to initial selection.  cccccccc LQ mass
Signal $\cPZ/\PGg^{*}\text{+jets}$ Multijet VV, , single , $\PGg\text{+jets}$
Total background Data
init. sel. — $41600\pm 49$ $7100\pm 68$ $26\pm 0.1$ $2400\pm 36$ $51100\pm
91\pm 2700$ $50585$
200 $311500\pm 3300$ $1900\pm 16$ $2300\pm 39$ $15\pm 0.1$ $630\pm 18$
$4800\pm 46\pm 120$ $4709$
250 $137400\pm 1200$ $910\pm 11$ $1200\pm 29$ $9.1\pm 0.1$ $380\pm 14$
$2500\pm 34\pm 69$ $2426$
300 $63160\pm 510$ $470\pm 4.2$ $630\pm 22$ $4.8\pm 0.0$ $220^{+10}_{-9.5}$
$1300^{+24}_{-24}\pm 24$ $1278$
350 $30150\pm 230$ $250\pm 2.7$ $310\pm 15$ $2.5\pm 0.0$ $140^{+9.5}_{-8.6}$
$700^{+18}_{-18}\pm 27$ $652$
400 $15440\pm 110$ $140\pm 1.8$ $150\pm 11$ $1.0\pm 0.0$ $89^{+7.2}_{-6.2}$
$380^{+13}_{-13}\pm 11$ $376$
450 $8260\pm 60$ $85\pm 1.5$ $79\pm 7.7$ $0.6\pm 0.0$ $49^{+2.3}_{-2.3}$
$210^{+8.2}_{-8.1}\pm 5.3$ $209$
500 $4700\pm 33$ $54\pm 1.1$ $36\pm 5.5$ $0.3\pm 0.0$ $30^{+2.0}_{-1.9}$
$120^{+6.0}_{-5.9}\pm 4.4$ $128$
550 $2830\pm 19$ $33\pm 0.8$ $15\pm 4.0$ $0.2\pm 0.0$ $22^{+1.8}_{-1.8}$
$70^{+4.5}_{-4.5}\pm 2.6$ $84$
600 $1750\pm 12$ $21\pm 0.6$ $9.6\pm 3.3$ $0.1\pm 0.0$ $16^{+1.6}_{-1.6}$
$47^{+3.7}_{-3.7}\pm 1.9$ $58$
650 $1110\pm 7.2$ $15\pm 0.6$ $7.7\pm 2.9$ $0.1\pm 0.0$ $11^{+1.4}_{-1.3}$
$34^{+3.2}_{-3.2}\pm 1.3$ $37$
700 $718\pm 4.5$ $12\pm 0.5$ $3.7\pm 2.2$ $0.1\pm 0.0$ $7.3^{+1.2}_{-1.2}$
$23^{+2.6}_{-2.6}\pm 1.0$ $28$
750 $470\pm 2.9$ $7.8\pm 0.3$ $2.0\pm 1.9$ $0.0\pm 0.0$ $5.5^{+1.1}_{-1.1}$
$15^{+2.2}_{-2.2}\pm 0.6$ $17$
800 $320\pm 1.9$ $6.4\pm 0.4$ $1.1^{+0.5}_{-0.4}$ $0.0\pm 0.0$
$3.5^{+1.1}_{-0.9}$ $11^{+1.2}_{-1.1}\pm 0.6$ $13$
850 $220\pm 1.3$ $4.9\pm 0.3$ $1.5^{+0.7}_{-0.5}$ $0.0\pm 0.0$
$2.8^{+1.0}_{-0.6}$ $9.2^{+1.3}_{-0.8}\pm 0.5$ $10$
900 $150\pm 0.9$ $4.0\pm 0.3$ $0.0^{+1.2}_{-0.0}$ $0.0\pm 0.0$
$2.6^{+0.8}_{-0.5}$ $6.6^{+1.4}_{-0.6}\pm 0.4$ $8$
950 $110\pm 0.6$ $3.6\pm 0.5$ $0.0^{+0.9}_{-0.0}$ $0.0\pm 0.0$
$2.1^{+0.7}_{-0.5}$ $5.7^{+1.3}_{-0.7}\pm 0.3$ $5$
1000 $77\pm 0.4$ $2.2\pm 0.1$ $0.0^{+0.7}_{-0.0}$ $0.0\pm 0.0$
$1.9^{+0.7}_{-0.4}$ $4.1^{+1.0}_{-0.5}\pm 0.2$ $5$
1050 $55\pm 0.3$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1100 $41\pm 0.2$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1150 $31\pm 0.2$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1200 $23\pm 0.1$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1250 $17\pm 0.1$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1300 $13\pm 0.1$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1350 $9.8\pm 0.0$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1400 $7.4\pm 0.0$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1450 $5.6\pm 0.0$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1500 $4.2\pm 0.0$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1550 $3.2\pm 0.0$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1600 $2.4\pm 0.0$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1650 $1.8\pm 0.0$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1700 $1.4\pm 0.0$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1750 $1.1\pm 0.0$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1800 $0.8\pm 0.0$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1850 $0.6\pm 0.0$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1900 $0.5\pm 0.0$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
1950 $0.4\pm 0.0$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$
2000 $0.3\pm 0.0$ $1.8\pm 0.1$ $0.0^{+0.3}_{-0.0}$ $0.0\pm 0.0$
$1.4^{+0.6}_{-0.4}$ $3.2^{+0.7}_{-0.4}\pm 0.2$ $4$

Event yields after the optimized $\Pe\Pgn\text{jj}$ selections. Uncertainties
are statistical except for the total background, where both statistical and
systematic uncertainties are shown. An entry of $0.0$ quoted for the
uncertainty indicates that its value is negligibly small. LQ masses are given
in units of and init. sel. refers to initial selection.  cccccccc LQ mass
Signal $\PW\text{+jets}$ Multijet VV, , single , $\PGg\text{+jets}$ Total
background Data
init. sel. — $47900\pm 160$ $66900\pm 110$ $2800\pm 15$ $11300\pm 72$
$128900\pm 210\pm 8800$ $125076$
200 $130800\pm 1600$ $40100\pm 150$ $52800\pm 94$ $2100\pm 11$ $9600\pm 57$
$104500\pm 190\pm 7300$ $101618$
250 $44200\pm 520$ $1800\pm 25$ $3800\pm 25$ $300\pm 2.3$ $1300\pm 38$
$7100\pm 52\pm 430$ $7151$
300 $19800\pm 220$ $800\pm 15$ $1400\pm 16$ $120\pm 1.4$ $660\pm 37$ $3000\pm
43\pm 170$ $3164$
350 $9800\pm 100$ $410\pm 13$ $610\pm 10$ $62\pm 1.0$ $330\pm 11$ $1400\pm
20\pm 88$ $1539$
400 $5100\pm 51$ $230\pm 8.9$ $300\pm 7.2$ $37\pm 0.8$ $200\pm 10$ $760\pm
15\pm 74$ $847$
450 $2900\pm 27$ $150\pm 6.0$ $160\pm 5.2$ $28\pm 0.8$ $120\pm 9.6$ $460\pm
12\pm 31$ $496$
500 $1700\pm 15$ $90\pm 4.1$ $88\pm 3.9$ $21\pm 0.8$ $75^{+3.9}_{-3.3}$
$270^{+6.9}_{-6.6}\pm 21$ $298$
550 $990\pm 8.8$ $59\pm 5.2$ $49\pm 2.9$ $9.1\pm 0.4$ $53^{+3.5}_{-2.9}$
$170^{+6.9}_{-6.6}\pm 13$ $195$
600 $620\pm 5.3$ $45\pm 5.1$ $32\pm 2.3$ $6.1\pm 0.4$ $36^{+2.8}_{-2.2}$
$120^{+6.3}_{-6.0}\pm 12$ $132$
650 $400\pm 3.3$ $34\pm 5.0$ $20\pm 1.8$ $5.0\pm 0.4$ $26^{+2.5}_{-1.9}$
$84^{+5.9}_{-5.7}\pm 8.1$ $94$
700 $270\pm 2.1$ $22\pm 1.2$ $12\pm 1.5$ $4.2\pm 0.5$ $18^{+2.1}_{-1.5}$
$56^{+2.9}_{-2.5}\pm 6.1$ $71$
750 $180\pm 1.4$ $15\pm 0.9$ $10\pm 1.3$ $3.7\pm 0.5$ $13^{+2.1}_{-1.3}$
$42^{+2.7}_{-2.1}\pm 4.9$ $49$
800 $130\pm 0.9$ $13\pm 1.0$ $6.3\pm 1.0$ $3.4\pm 0.6$ $9.8^{+2.0}_{-1.1}$
$32^{+2.5}_{-1.9}\pm 4.6$ $38$
850 $86\pm 0.6$ $13\pm 1.1$ $5.2\pm 0.9$ $3.2\pm 0.7$ $7.0^{+2.0}_{-1.2}$
$28^{+2.6}_{-2.0}\pm 4.8$ $28$
900 $61\pm 0.4$ $11\pm 1.2$ $3.8\pm 0.8$ $3.0\pm 0.7$ $6.3^{+2.0}_{-1.1}$
$24^{+2.6}_{-2.0}\pm 4.1$ $21$
950 $44\pm 0.3$ $8.4\pm 1.0$ $3.0\pm 0.7$ $0.7\pm 0.1$ $5.7^{+2.0}_{-1.1}$
$18^{+2.3}_{-1.6}\pm 3.3$ $20$
1000 $31\pm 0.2$ $7.9\pm 0.9$ $2.2\pm 0.6$ $0.6\pm 0.1$ $4.8^{+2.0}_{-1.1}$
$16^{+2.3}_{-1.5}\pm 2.8$ $15$
1050 $23\pm 0.2$ $7.1\pm 0.9$ $1.4^{+0.7}_{-0.5}$ $0.5\pm 0.1$
$4.4^{+2.0}_{-1.1}$ $13^{+2.3}_{-1.4}\pm 2.5$ $14$
1100 $17\pm 0.1$ $5.9\pm 0.8$ $1.2^{+0.6}_{-0.4}$ $0.5\pm 0.1$
$4.0^{+2.0}_{-1.0}$ $12^{+2.3}_{-1.4}\pm 2.1$ $12$
1150 $12\pm 0.1$ $5.4\pm 0.9$ $0.9^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.3^{+2.0}_{-1.0}$ $10^{+2.3}_{-1.4}\pm 1.7$ $12$
1200 $9.1\pm 0.1$ $5.2\pm 1.1$ $0.7^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.2^{+2.0}_{-1.0}$ $9.5^{+2.3}_{-1.5}\pm 1.6$ $10$
1250 $7.1\pm 0.0$ $5.0\pm 1.1$ $0.7^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.0^{+2.0}_{-1.0}$ $9.1^{+2.3}_{-1.5}\pm 1.5$ $9$
1300 $5.4\pm 0.0$ $5.0\pm 1.1$ $0.7^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.0^{+2.0}_{-1.0}$ $9.1^{+2.3}_{-1.5}\pm 1.5$ $9$
1350 $4.1\pm 0.0$ $5.0\pm 1.1$ $0.7^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.0^{+2.0}_{-1.0}$ $9.1^{+2.3}_{-1.5}\pm 1.5$ $9$
1400 $3.1\pm 0.0$ $5.0\pm 1.1$ $0.7^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.0^{+2.0}_{-1.0}$ $9.1^{+2.3}_{-1.5}\pm 1.5$ $9$
1450 $2.4\pm 0.0$ $5.0\pm 1.1$ $0.7^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.0^{+2.0}_{-1.0}$ $9.1^{+2.3}_{-1.5}\pm 1.5$ $9$
1500 $1.9\pm 0.0$ $5.0\pm 1.1$ $0.7^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.0^{+2.0}_{-1.0}$ $9.1^{+2.3}_{-1.5}\pm 1.5$ $9$
1550 $1.4\pm 0.0$ $5.0\pm 1.1$ $0.7^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.0^{+2.0}_{-1.0}$ $9.1^{+2.3}_{-1.5}\pm 1.5$ $9$
1600 $1.1\pm 0.0$ $5.0\pm 1.1$ $0.7^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.0^{+2.0}_{-1.0}$ $9.1^{+2.3}_{-1.5}\pm 1.5$ $9$
1650 $0.8\pm 0.0$ $5.0\pm 1.1$ $0.7^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.0^{+2.0}_{-1.0}$ $9.1^{+2.3}_{-1.5}\pm 1.5$ $9$
1700 $0.6\pm 0.0$ $5.0\pm 1.1$ $0.7^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.0^{+2.0}_{-1.0}$ $9.1^{+2.3}_{-1.5}\pm 1.5$ $9$
1750 $0.5\pm 0.0$ $5.0\pm 1.1$ $0.7^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.0^{+2.0}_{-1.0}$ $9.1^{+2.3}_{-1.5}\pm 1.5$ $9$
1800 $0.4\pm 0.0$ $5.0\pm 1.1$ $0.7^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.0^{+2.0}_{-1.0}$ $9.1^{+2.3}_{-1.5}\pm 1.5$ $9$
1850 $0.3\pm 0.0$ $5.0\pm 1.1$ $0.7^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.0^{+2.0}_{-1.0}$ $9.1^{+2.3}_{-1.5}\pm 1.5$ $9$
1900 $0.2\pm 0.0$ $5.0\pm 1.1$ $0.7^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.0^{+2.0}_{-1.0}$ $9.1^{+2.3}_{-1.5}\pm 1.5$ $9$
1950 $0.2\pm 0.0$ $5.0\pm 1.1$ $0.7^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.0^{+2.0}_{-1.0}$ $9.1^{+2.3}_{-1.5}\pm 1.5$ $9$
2000 $0.1\pm 0.0$ $5.0\pm 1.1$ $0.7^{+0.6}_{-0.4}$ $0.4\pm 0.1$
$3.0^{+2.0}_{-1.0}$ $9.1^{+2.3}_{-1.5}\pm 1.5$ $9$

##  .11 The CMS Collaboration

Yerevan Physics Institute, Yerevan, Armenia
A.M. Sirunyan, A. Tumasyan Institut für Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, M. Dragicevic,
J. Erö, A. Escalante Del Valle, M. Flechl, R. Frühwirth1, V.M. Ghete, J.
Hrubec, M. Jeitler1, N. Krammer, I. Krätschmer, D. Liko, T. Madlener, I.
Mikulec, N. Rad, H. Rohringer, J. Schieck1, R. Schöfbeck, M. Spanring, D.
Spitzbart, A. Taurok, W. Waltenberger, J. Wittmann, C.-E. Wulz1, M. Zarucki
Institute for Nuclear Problems, Minsk, Belarus
V. Chekhovsky, V. Mossolov, J. Suarez Gonzalez Universiteit Antwerpen,
Antwerpen, Belgium
E.A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, M. Pieters, H. Van
Haevermaet, P. Van Mechelen, N. Van Remortel Vrije Universiteit Brussel,
Brussel, Belgium
S. Abu Zeid, F. Blekman, J. D’Hondt, J. De Clercq, K. Deroover, G. Flouris, D.
Lontkovskyi, S. Lowette, I. Marchesini, S. Moortgat, L. Moreels, Q. Python, K.
Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders, I. Van Parijs
Université Libre de Bruxelles, Bruxelles, Belgium
D. Beghin, B. Bilin, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, B.
Dorney, G. Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk, A.K. Kalsi, T.
Lenzi, J. Luetic, N. Postiau, E. Starling, L. Thomas, C. Vander Velde, P.
Vanlaer, D. Vannerom, Q. Wang Ghent University, Ghent, Belgium
T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov2, D. Poyraz, C. Roskas,
D. Trocino, M. Tytgat, W. Verbeke, B. Vermassen, M. Vit, N. Zaganidis
Université Catholique de Louvain, Louvain-la-Neuve, Belgium
H. Bakhshiansohi, O. Bondu, S. Brochet, G. Bruno, C. Caputo, P. David, C.
Delaere, M. Delcourt, A. Giammanco, G. Krintiras, V. Lemaitre, A. Magitteri,
K. Piotrzkowski, A. Saggio, M. Vidal Marono, S. Wertz, J. Zobec Centro
Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil
F.L. Alves, G.A. Alves, M. Correa Martins Junior, G. Correia Silva, C. Hensel,
A. Moraes, M.E. Pol, P. Rebello Teles Universidade do Estado do Rio de
Janeiro, Rio de Janeiro, Brazil
E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato3, E. Coelho, E.M.
Da Costa, G.G. Da Silveira4, D. De Jesus Damiao, C. De Oliveira Martins, S.
Fonseca De Souza, H. Malbouisson, D. Matos Figueiredo, M. Melo De Almeida, C.
Mora Herrera, L. Mundim, H. Nogima, W.L. Prado Da Silva, L.J. Sanchez Rosas,
A. Santoro, A. Sznajder, M. Thiel, E.J. Tonelli Manganote3, F. Torres Da Silva
De Araujo, A. Vilela Pereira Universidade Estadual Paulista a, Universidade
Federal do ABC b, São Paulo, Brazil
S. Ahujaa, C.A. Bernardesa, L. Calligarisa, T.R. Fernandez Perez Tomeia, E.M.
Gregoresb, P.G. Mercadanteb, S.F. Novaesa, SandraS. Padulaa Institute for
Nuclear Research and Nuclear Energy, Bulgarian Academy of Sciences, Sofia,
Bulgaria
A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, A. Marinov, M. Misheva, M. Rodozov,
M. Shopova, G. Sultanov University of Sofia, Sofia, Bulgaria
A. Dimitrov, L. Litov, B. Pavlov, P. Petkov Beihang University, Beijing, China
W. Fang5, X. Gao5, L. Yuan Institute of High Energy Physics, Beijing, China
M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D.
Leggat, H. Liao, Z. Liu, F. Romeo, S.M. Shaheen6, A. Spiezia, J. Tao, Z. Wang,
E. Yazgan, H. Zhang, S. Zhang6, J. Zhao State Key Laboratory of Nuclear
Physics and Technology, Peking University, Beijing, China
Y. Ban, G. Chen, A. Levin, J. Li, L. Li, Q. Li, Y. Mao, S.J. Qian, D. Wang
Tsinghua University, Beijing, China
Y. Wang Universidad de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, C.A. Carrillo Montoya, L.F. Chaparro Sierra, C. Florez,
C.F. González Hernández, M.A. Segura Delgado University of Split, Faculty of
Electrical Engineering, Mechanical Engineering and Naval Architecture, Split,
Croatia
B. Courbon, N. Godinovic, D. Lelas, I. Puljak, T. Sculac University of Split,
Faculty of Science, Split, Croatia
Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia
V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, A. Starodumov7, T. Susa
University of Cyprus, Nicosia, Cyprus
M.W. Ather, A. Attikis, M. Kolosova, G. Mavromanolakis, J. Mousa, C. Nicolaou,
F. Ptochos, P.A. Razis, H. Rykaczewski Charles University, Prague, Czech
Republic
M. Finger8, M. Finger Jr.8 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
Y. Assran9,10, S. Elgammal10, S. Khalil11 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, H. Kirschenmann, J. Pekkanen, M. Voutilainen Helsinki Institute of
Physics, Helsinki, Finland
J. Havukainen, J.K. Heikkilä, T. Järvinen, V. Karimäki, R. Kinnunen, T.
Lampén, K. Lassila-Perini, S. Laurila, S. Lehti, T. Lindén, P. Luukka, T.
Mäenpää, H. Siikonen, E. Tuominen, J. Tuominiemi Lappeenranta University of
Technology, Lappeenranta, Finland
T. Tuuva IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
M. Besancon, F. Couderc, M. Dejardin, D. Denegri, J.L. Faure, F. Ferri, S.
Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, C. Leloup,
E. Locci, J. Malcles, G. Negro, J. Rander, A. Rosowsky, M.Ö. Sahin, M. Titov
Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Université
Paris-Saclay, Palaiseau, France
A. Abdulsalam12, C. Amendola, I. Antropov, F. Beaudette, P. Busson, C.
Charlot, R. Granier de Cassagnac, I. Kucher, A. Lobanov, J. Martin Blanco, C.
Martin Perez, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P. Pigard, J.
Rembser, R. Salerno, J.B. Sauvan, Y. Sirois, A.G. Stahl Leiton, A. Zabi, A.
Zghiche Université de Strasbourg, CNRS, IPHC UMR 7178, Strasbourg, France
J.-L. Agram13, J. Andrea, D. Bloch, J.-M. Brom, E.C. Chabert, V. Cherepanov,
C. Collard, E. Conte13, J.-C. Fontaine13, D. Gelé, U. Goerlach, M. Jansová,
A.-C. Le Bihan, N. Tonon, P. Van Hove Centre de Calcul de l’Institut National
de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne,
France
S. Gadrat Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3,
Institut de Physique Nucléaire de Lyon, Villeurbanne, France
S. Beauceron, C. Bernet, G. Boudoul, N. Chanon, R. Chierici, D. Contardo, P.
Depasse, H. El Mamouni, J. Fay, L. Finco, S. Gascon, M. Gouzevitch, G.
Grenier, B. Ille, F. Lagarde, I.B. Laktineh, H. Lattaud, M. Lethuillier, L.
Mirabito, S. Perries, A. Popov14, V. Sordini, G. Touquet, M. Vander Donckt, S.
Viret Georgian Technical University, Tbilisi, Georgia
T. Toriashvili15 Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze8 RWTH Aachen University, I. Physikalisches Institut, Aachen,
Germany
C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, M.P.
Rauch, C. Schomakers, J. Schulz, M. Teroerde, B. Wittmer RWTH Aachen
University, III. Physikalisches Institut A, Aachen, Germany
A. Albert, D. Duchardt, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, S. Ghosh,
A. Güth, T. Hebbeker, C. Heidemann, K. Hoepfner, H. Keller, L. Mastrolorenzo,
M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, T. Pook, M. Radziej, H.
Reithler, M. Rieger, A. Schmidt, D. Teyssier, S. Thüer RWTH Aachen University,
III. Physikalisches Institut B, Aachen, Germany
G. Flügge, O. Hlushchenko, T. Kress, T. Müller, A. Nehrkorn, A. Nowack, C.
Pistone, O. Pooth, D. Roy, H. Sert, A. Stahl16 Deutsches Elektronen-
Synchrotron, Hamburg, Germany
M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, I. Babounikau, K.
Beernaert, O. Behnke, U. Behrens, A. Bermúdez Martínez, D. Bertsche, A.A. Bin
Anuar, K. Borras17, V. Botta, A. Campbell, P. Connor, C. Contreras-Campana, V.
Danilov, A. De Wit, M.M. Defranchis, C. Diez Pardos, D. Domínguez Damiani, G.
Eckerlin, T. Eichhorn, A. Elwood, E. Eren, E. Gallo18, A. Geiser, J.M. Grados
Luyando, A. Grohsjean, M. Guthoff, M. Haranko, A. Harb, J. Hauk, H. Jung, M.
Kasemann, J. Keaveney, C. Kleinwort, J. Knolle, D. Krücker, W. Lange, A.
Lelek, T. Lenz, J. Leonard, K. Lipka, W. Lohmann19, R. Mankel, I.-A. Melzer-
Pellmann, A.B. Meyer, M. Meyer, M. Missiroli, G. Mittag, J. Mnich, V.
Myronenko, S.K. Pflitsch, D. Pitzl, A. Raspereza, M. Savitskyi, P. Saxena, P.
Schütze, C. Schwanenberger, R. Shevchenko, A. Singh, H. Tholen, O. Turkot, A.
Vagnerini, G.P. Van Onsem, R. Walsh, Y. Wen, K. Wichmann, C. Wissing, O.
Zenaiev University of Hamburg, Hamburg, Germany
R. Aggleton, S. Bein, L. Benato, A. Benecke, V. Blobel, T. Dreyer, A.
Ebrahimi, E. Garutti, D. Gonzalez, P. Gunnellini, J. Haller, A. Hinzmann, A.
Karavdina, G. Kasieczka, R. Klanner, R. Kogler, N. Kovalchuk, S. Kurz, V.
Kutzner, J. Lange, D. Marconi, J. Multhaup, M. Niedziela, C.E.N. Niemeyer, D.
Nowatschin, A. Perieanu, A. Reimers, O. Rieger, C. Scharf, P. Schleper, S.
Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G. Steinbrück, F.M. Stober, M.
Stöver, A. Vanhoefer, B. Vormwald, I. Zoi Karlsruher Institut fuer
Technologie, Karlsruhe, Germany
M. Akbiyik, C. Barth, M. Baselga, S. Baur, E. Butz, R. Caspart, T. Chwalek, F.
Colombo, W. De Boer, A. Dierlamm, K. El Morabit, N. Faltermann, B. Freund, M.
Giffels, M.A. Harrendorf, F. Hartmann16, S.M. Heindl, U. Husemann, I.
Katkov14, S. Kudella, S. Mitra, M.U. Mozer, Th. Müller, M. Musich, M. Plagge,
G. Quast, K. Rabbertz, M. Schröder, I. Shvetsov, H.J. Simonis, R. Ulrich, S.
Wayand, M. Weber, T. Weiler, C. Wöhrmann, R. Wolf Institute of Nuclear and
Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece
G. Anagnostou, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas, G. Paspalaki
National and Kapodistrian University of Athens, Athens, Greece
G. Karathanasis, P. Kontaxakis, A. Panagiotou, I. Papavergou, N. Saoulidou, E.
Tziaferi, K. Vellidis National Technical University of Athens, Athens, Greece
K. Kousouris, I. Papakrivopoulos, G. Tsipolitis University of Ioánnina,
Ioánnina, Greece
I. Evangelou, C. Foudas, P. Gianneios, P. Katsoulis, P. Kokkas, S. Mallios, N.
Manthos, I. Papadopoulos, E. Paradas, J. Strologas, F.A. Triantis, D.
Tsitsonis MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
M. Bartók20, M. Csanad, N. Filipovic, P. Major, M.I. Nagy, G. Pasztor, O.
Surányi, G.I. Veres Wigner Research Centre for Physics, Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath21, Á. Hunyadi, F. Sikler, T.Á. Vámi, V.
Veszpremi, G. Vesztergombi${}^{\textrm{\textdagger}}$ Institute of Nuclear
Research ATOMKI, Debrecen, Hungary
N. Beni, S. Czellar, J. Karancsi20, A. Makovec, J. Molnar, Z. Szillasi
Institute of Physics, University of Debrecen, Debrecen, Hungary
P. Raics, Z.L. Trocsanyi, B. Ujvari Indian Institute of Science (IISc),
Bangalore, India
S. Choudhury, J.R. Komaragiri, P.C. Tiwari National Institute of Science
Education and Research, HBNI, Bhubaneswar, India
S. Bahinipati23, C. Kar, P. Mal, K. Mandal, A. Nayak24, D.K. Sahoo23, S.K.
Swain Panjab University, Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, S. Chauhan, R. Chawla, N. Dhingra, R.
Gupta, A. Kaur, M. Kaur, S. Kaur, P. Kumari, M. Lohan, A. Mehta, K. Sandeep,
S. Sharma, J.B. Singh, A.K. Virdi, G. Walia University of Delhi, Delhi, India
A. Bhardwaj, B.C. Choudhary, R.B. Garg, M. Gola, S. Keshri, Ashok Kumar, S.
Malhotra, M. Naimuddin, P. Priyanka, K. Ranjan, Aashaq Shah, R. Sharma Saha
Institute of Nuclear Physics, HBNI, Kolkata, India
R. Bhardwaj25, M. Bharti25, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep25,
D. Bhowmik, S. Dey, S. Dutt25, S. Dutta, S. Ghosh, K. Mondal, S. Nandan, A.
Purohit, P.K. Rout, A. Roy, S. Roy Chowdhury, G. Saha, S. Sarkar, M. Sharan,
B. Singh25, S. Thakur25 Indian Institute of Technology Madras, Madras, India
P.K. Behera Bhabha Atomic Research Centre, Mumbai, India
R. Chudasama, D. Dutta, V. Jha, V. Kumar, P.K. Netrakanti, L.M. Pant, P.
Shukla Tata Institute of Fundamental Research-A, Mumbai, India
T. Aziz, M.A. Bhat, S. Dugad, G.B. Mohanty, N. Sur, B. Sutar, RavindraKumar
Verma Tata Institute of Fundamental Research-B, Mumbai, India
S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, Sa. Jain, S.
Karmakar, S. Kumar, M. Maity26, G. Majumder, K. Mazumdar, N. Sahoo, T.
Sarkar26 Indian Institute of Science Education and Research (IISER), Pune,
India
S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, A.
Rastogi, S. Sharma Institute for Research in Fundamental Sciences (IPM),
Tehran, Iran
S. Chenarani27, E. Eskandari Tadavani, S.M. Etesami27, M. Khakzad, M.
Mohammadi Najafabadi, M. Naseri, F. Rezaei Hosseinabadi, B. Safarzadeh28, M.
Zeinali University College Dublin, Dublin, Ireland
M. Felcini, M. Grunewald INFN Sezione di Bari a, Università di Bari b,
Politecnico di Bari c, Bari, Italy
M. Abbresciaa,b, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L. Cristellaa,b,
N. De Filippisa,c, M. De Palmaa,b, A. Di Florioa,b, F. Erricoa,b, L. Fiorea,
A. Gelmia,b, G. Iasellia,c, M. Incea,b, S. Lezkia,b, G. Maggia,c, M. Maggia,
G. Minielloa,b, S. Mya,b, S. Nuzzoa,b, A. Pompilia,b, G. Pugliesea,c, R.
Radognaa, A. Ranieria, G. Selvaggia,b, A. Sharmaa, L. Silvestrisa, R.
Vendittia, P. Verwilligena, G. Zitoa INFN Sezione di Bologna a, Università di
Bologna b, Bologna, Italy
G. Abbiendia, C. Battilanaa,b, D. Bonacorsia,b, L. Borgonovia,b, S. Braibant-
Giacomellia,b, R. Campaninia,b, P. Capiluppia,b, A. Castroa,b, F.R. Cavalloa,
S.S. Chhibraa,b, C. Cioccaa, G. Codispotia,b, M. Cuffiania,b, G.M.
Dallavallea, F. Fabbria, A. Fanfania,b, E. Fontanesi, P. Giacomellia, C.
Grandia, L. Guiduccia,b, S. Lo Meoa, S. Marcellinia, G. Masettia, A.
Montanaria, F.L. Navarriaa,b, A. Perrottaa, F. Primaveraa,b,16, 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, A. Di Mattiaa, R. Potenzaa,b, A. Tricomia,b, C. Tuvea,b INFN
Sezione di Firenze a, Università di Firenze b, Firenze, Italy
G. Barbaglia, K. Chatterjeea,b, V. Ciullia,b, C. Civininia, R.
D’Alessandroa,b, E. Focardia,b, G. Latino, P. Lenzia,b, M. Meschinia, S.
Paolettia, L. Russoa,29, G. Sguazzonia, D. Stroma, L. Viliania INFN Laboratori
Nazionali di Frascati, Frascati, Italy
L. Benussi, S. Bianco, F. Fabbri, D. Piccolo INFN Sezione di Genova a,
Università di Genova b, Genova, Italy
F. Ferroa, R. Mulargiaa,b, F. Raveraa,b, E. Robuttia, S. Tosia,b INFN Sezione
di Milano-Bicocca a, Università di Milano-Bicocca b, Milano, Italy
A. Benagliaa, A. Beschib, F. Brivioa,b, V. Cirioloa,b,16, S. Di Guidaa,d,16,
M.E. Dinardoa,b, S. Fiorendia,b, S. Gennaia, A. Ghezzia,b, P. Govonia,b, M.
Malbertia,b, S. Malvezzia, A. Massironia,b, D. Menascea, F. Monti, L. Moronia,
M. Paganonia,b, D. Pedrinia, S. Ragazzia,b, T. Tabarelli de Fatisa,b, 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, A. Di Crescenzoa,b, F.
Fabozzia,c, F. Fiengaa, G. Galatia, A.O.M. Iorioa,b, W.A. Khana, L. Listaa, S.
Meolaa,d,16, P. Paoluccia,16, 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. Bragagnolo, R.
Carlina,b, P. Checchiaa, M. Dall’Ossoa,b, P. De Castro Manzanoa, T. Dorigoa,
U. Dossellia, F. Gasparinia,b, U. Gasparinia,b, A. Gozzelinoa, S.Y. Hoh, S.
Lacapraraa, P. Lujan, M. Margonia,b, A.T. Meneguzzoa,b, J. Pazzinia,b, P.
Ronchesea,b, R. Rossina,b, F. Simonettoa,b, A. Tiko, E. Torassaa, M. Tosia,b,
M. Zanettia,b, P. Zottoa,b, G. Zumerlea,b INFN Sezione di Pavia a, Università
di Pavia b, Pavia, Italy
A. Braghieria, A. Magnania, P. Montagnaa,b, S.P. Rattia,b, V. Rea, M.
Ressegottia,b, C. Riccardia,b, P. Salvinia, I. Vaia,b, P. Vituloa,b INFN
Sezione di Perugia a, Università di Perugia b, Perugia, Italy
M. Biasinia,b, G.M. Bileia, C. Cecchia,b, D. Ciangottinia,b, L. Fanòa,b, P.
Laricciaa,b, R. Leonardia,b, E. Manonia, G. Mantovania,b, V. Mariania,b, M.
Menichellia, A. Rossia,b, A. Santocchiaa,b, D. Spigaa INFN Sezione di Pisa a,
Università di Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy
K. Androsova, P. Azzurria, G. Bagliesia, L. Bianchinia, T. Boccalia, L.
Borrello, R. Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, G. Fedia, F. Fioria,c,
L. Gianninia,c, A. Giassia, M.T. Grippoa, F. Ligabuea,c, E. Mancaa,c, G.
Mandorlia,c, A. Messineoa,b, F. Pallaa, A. Rizzia,b, G. Rolandi30, P.
Spagnoloa, R. Tenchinia, G. Tonellia,b, A. Venturia, P.G. Verdinia INFN
Sezione di Roma a, Sapienza Università di Roma b, Rome, Italy
L. Baronea,b, F. Cavallaria, M. Cipriania,b, D. Del Rea,b, E. Di Marcoa,b, M.
Diemoza, S. Gellia,b, E. Longoa,b, B. Marzocchia,b, P. Meridiania, G.
Organtinia,b, F. Pandolfia, R. Paramattia,b, F. Preiatoa,b, S. Rahatloua,b, C.
Rovellia, F. Santanastasioa,b INFN Sezione di Torino a, Università di Torino
b, Torino, Italy, Università del Piemonte Orientale c, Novara, Italy
N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, N. Bartosika,
R. Bellana,b, C. Biinoa, A. Cappatia,b, N. Cartigliaa, F. Cennaa,b, S.
Comettia, M. Costaa,b, R. Covarellia,b, N. Demariaa, B. Kiania,b, C.
Mariottia, S. Masellia, E. Migliorea,b, V. Monacoa,b, E. Monteila,b, M.
Montenoa, M.M. Obertinoa,b, L. Pachera,b, N. Pastronea, M. Pelliccionia, G.L.
Pinna Angionia,b, A. Romeroa,b, M. Ruspaa,c, R. Sacchia,b, R. Salvaticoa,b, K.
Shchelinaa,b, V. Solaa, A. Solanoa,b, D. Soldia,b, A. Staianoa 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, A. Zanettia Kyungpook National University,
Daegu, Korea
D.H. Kim, G.N. Kim, M.S. Kim, J. Lee, S. Lee, S.W. Lee, C.S. Moon, Y.D. Oh,
S.I. Pak, S. Sekmen, D.C. Son, Y.C. Yang Chonnam National University,
Institute for Universe and Elementary Particles, Kwangju, Korea
H. Kim, D.H. Moon, G. Oh Hanyang University, Seoul, Korea
B. Francois, J. Goh31, T.J. Kim Korea University, Seoul, Korea
S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, K. Lee, K.S. Lee, S.
Lee, J. Lim, S.K. Park, Y. Roh Sejong University, Seoul, Korea
H.S. Kim Seoul National University, Seoul, Korea
J. Almond, J. Kim, J.S. Kim, H. Lee, K. Lee, K. Nam, S.B. Oh, B.C. Radburn-
Smith, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu University of Seoul, Seoul,
Korea
D. Jeon, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park Sungkyunkwan University,
Suwon, Korea
Y. Choi, C. Hwang, J. Lee, I. Yu Vilnius University, Vilnius, Lithuania
V. Dudenas, A. Juodagalvis, J. Vaitkus National Centre for Particle Physics,
Universiti Malaya, Kuala Lumpur, Malaysia
I. Ahmed, Z.A. Ibrahim, M.A.B. Md Ali32, F. Mohamad Idris33, 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 Centro de
Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico
H. Castilla-Valdez, E. De La Cruz-Burelo, M.C. Duran-Osuna, I. Heredia-De La
Cruz34, R. Lopez-Fernandez, J. Mejia Guisao, R.I. Rabadan-Trejo, M. Ramirez-
Garcia, G. Ramirez-Sanchez, R. Reyes-Almanza, A. Sanchez-Hernandez Universidad
Iberoamericana, Mexico City, Mexico
S. Carrillo Moreno, C. Oropeza Barrera, 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 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. Ahmad, M.I. Asghar, Q. Hassan, H.R. Hoorani, A. Saddique, M.A.
Shah, M. Shoaib, M. Waqas National Centre for Nuclear Research, Swierk, Poland
H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Górski, M. Kazana, M.
Szleper, P. Traczyk, P. Zalewski Institute of Experimental Physics, Faculty of
Physics, University of Warsaw, Warsaw, Poland
K. Bunkowski, A. Byszuk35, K. Doroba, A. Kalinowski, M. Konecki, J.
Krolikowski, M. Misiura, M. Olszewski, A. Pyskir, M. Walczak Laboratório de
Instrumentação e Física Experimental de Partículas, Lisboa, Portugal
M. Araujo, P. Bargassa, C. Beirão Da Cruz E Silva, A. Di Francesco, P.
Faccioli, B. Galinhas, M. Gallinaro, J. Hollar, N. Leonardo, J. Seixas, G.
Strong, 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. Matveev36,37, P. Moisenz, V. Palichik,
V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin,
A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg),
Russia
V. Golovtsov, Y. Ivanov, V. Kim38, E. Kuznetsova39, P. Levchenko, V. Murzin,
V. Oreshkin, I. Smirnov, D. Sosnov, V. Sulimov, L. Uvarov, S. Vavilov, A.
Vorobyev Institute for Nuclear Research, Moscow, Russia
Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov,
N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical
and Experimental Physics, Moscow, Russia
V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G.
Safronov, A. Spiridonov, A. Stepennov, V. Stolin, 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
R. Chistov40, M. Danilov40, P. Parygin, D. Philippov, S. Polikarpov40, E.
Tarkovskii P.N. Lebedev Physical Institute, Moscow, Russia
V. Andreev, M. Azarkin, I. Dremin37, M. Kirakosyan, A. Terkulov Skobeltsyn
Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow,
Russia
A. Baskakov, A. Belyaev, E. Boos, M. Dubinin41, L. Dudko, A. Ershov, A.
Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, S.
Petrushanko, V. Savrin, A. Snigirev Novosibirsk State University (NSU),
Novosibirsk, Russia
A. Barnyakov42, V. Blinov42, T. Dimova42, L. Kardapoltsev42, Y. Skovpen42
Institute for High Energy Physics of National Research Centre ’Kurchatov
Institute’, Protvino, Russia
I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, A. Godizov, V. Kachanov,
A. Kalinin, D. Konstantinov, P. Mandrik, V. Petrov, R. Ryutin, S.
Slabospitskii, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov National
Research Tomsk Polytechnic University, Tomsk, Russia
A. Babaev, S. Baidali, V. Okhotnikov University of Belgrade, Faculty of
Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia
P. Adzic43, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic Centro de
Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid,
Spain
J. Alcaraz Maestre, A. Álvarez Fernández, I. Bachiller, M. Barrio Luna, J.A.
Brochero Cifuentes, M. Cerrada, N. Colino, B. De La Cruz, A. Delgado Peris, C.
Fernandez Bedoya, J.P. Fernández Ramos, J. Flix, M.C. Fouz, O. Gonzalez Lopez,
S. Goy Lopez, J.M. Hernandez, M.I. Josa, D. Moran, A. Pérez-Calero Yzquierdo,
J. Puerta Pelayo, I. Redondo, L. Romero, M.S. Soares, A. Triossi Universidad
Autónoma de Madrid, Madrid, Spain
C. Albajar, J.F. de Trocóniz Universidad de Oviedo, Oviedo, Spain
J. Cuevas, C. Erice, J. Fernandez Menendez, S. Folgueras, I. Gonzalez
Caballero, J.R. González Fernández, E. Palencia Cortezon, V. Rodríguez Bouza,
S. Sanchez Cruz, P. Vischia, J.M. Vizan Garcia Instituto de Física de
Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain
I.J. Cabrillo, A. Calderon, B. Chazin Quero, J. Duarte Campderros, M.
Fernandez, P.J. Fernández Manteca, A. García Alonso, J. Garcia-Ferrero, G.
Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, P. Martinez Ruiz del
Arbol, F. Matorras, J. Piedra Gomez, C. Prieels, T. Rodrigo, A. Ruiz-Jimeno,
L. Scodellaro, N. Trevisani, I. Vila, R. Vilar Cortabitarte University of
Ruhuna, Department of Physics, Matara, Sri Lanka
N. Wickramage CERN, European Organization for Nuclear Research, Geneva,
Switzerland
D. Abbaneo, B. Akgun, E. Auffray, G. Auzinger, P. Baillon, A.H. Ball, D.
Barney, J. Bendavid, M. Bianco, A. Bocci, C. Botta, E. Brondolin, T.
Camporesi, M. Cepeda, G. Cerminara, E. Chapon, Y. Chen, G. Cucciati, D.
d’Enterria, A. Dabrowski, N. Daci, V. Daponte, A. David, A. De Roeck, N.
Deelen, M. Dobson, M. Dünser, N. Dupont, A. Elliott-Peisert, P. Everaerts, F.
Fallavollita44, D. Fasanella, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, A.
Gilbert, K. Gill, F. Glege, M. Gruchala, M. Guilbaud, D. Gulhan, J. Hegeman,
C. Heidegger, V. Innocente, A. Jafari, P. Janot, O. Karacheban19, J. Kieseler,
A. Kornmayer, M. Krammer1, C. Lange, P. Lecoq, C. Lourenço, L. Malgeri, M.
Mannelli, F. Meijers, J.A. Merlin, S. Mersi, E. Meschi, P. Milenovic45, F.
Moortgat, M. Mulders, J. Ngadiuba, S. Nourbakhsh, S. Orfanelli, L. Orsini, F.
Pantaleo16, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G. Petrucciani, A.
Pfeiffer, M. Pierini, F.M. Pitters, D. Rabady, A. Racz, T. Reis, M. Rovere, H.
Sakulin, C. Schäfer, C. Schwick, M. Seidel, M. Selvaggi, A. Sharma, P. Silva,
P. Sphicas46, A. Stakia, J. Steggemann, D. Treille, A. Tsirou, V. Veckalns47,
M. Verzetti, W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland
L. Caminada48, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C.
Kaestli, D. Kotlinski, U. Langenegger, T. Rohe, S.A. Wiederkehr ETH Zurich -
Institute for Particle Physics and Astrophysics (IPA), Zurich, Switzerland
M. Backhaus, L. Bäni, P. Berger, N. Chernyavskaya, G. Dissertori, M. Dittmar,
M. Donegà, C. Dorfer, T.A. Gómez Espinosa, C. Grab, D. Hits, T. Klijnsma, W.
Lustermann, R.A. Manzoni, M. Marionneau, M.T. Meinhard, F. Micheli, P.
Musella, F. Nessi-Tedaldi, J. Pata, F. Pauss, G. Perrin, L. Perrozzi, S.
Pigazzini, M. Quittnat, C. Reissel, D. Ruini, D.A. Sanz Becerra, M.
Schönenberger, L. Shchutska, V.R. Tavolaro, K. Theofilatos, M.L. Vesterbacka
Olsson, R. Wallny, D.H. Zhu Universität Zürich, Zurich, Switzerland
T.K. Aarrestad, C. Amsler49, D. Brzhechko, M.F. Canelli, A. De Cosa, R. Del
Burgo, S. Donato, C. Galloni, T. Hreus, B. Kilminster, S. Leontsinis, I.
Neutelings, G. Rauco, P. Robmann, D. Salerno, K. Schweiger, C. Seitz, Y.
Takahashi, A. Zucchetta National Central University, Chung-Li, Taiwan
T.H. Doan, R. Khurana, C.M. Kuo, W. Lin, A. Pozdnyakov, S.S. Yu National
Taiwan University (NTU), Taipei, Taiwan
P. Chang, Y. Chao, K.F. Chen, P.H. Chen, W.-S. Hou, Arun Kumar, Y.F. Liu,
R.-S. Lu, E. Paganis, A. Psallidas, A. Steen Chulalongkorn University, Faculty
of Science, Department of Physics, Bangkok, Thailand
B. Asavapibhop, N. Srimanobhas, N. Suwonjandee Çukurova University, Physics
Department, Science and Art Faculty, Adana, Turkey
M.N. Bakirci50, A. Bat, F. Boran, S. Damarseckin, Z.S. Demiroglu, F. Dolek, C.
Dozen, E. Eskut, S. Girgis, G. Gokbulut, Y. Guler, E. Gurpinar, I. Hos51, C.
Isik, E.E. Kangal52, O. Kara, U. Kiminsu, M. Oglakci, G. Onengut, K.
Ozdemir53, A. Polatoz, D. Sunar Cerci54, B. Tali54, U.G. Tok, H. Topakli50, S.
Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University,
Physics Department, Ankara, Turkey
B. Isildak55, G. Karapinar56, M. Yalvac, M. Zeyrek Bogazici University,
Istanbul, Turkey
I.O. Atakisi, E. Gülmez, M. Kaya57, O. Kaya58, S. Ozkorucuklu59, S. Tekten,
E.A. Yetkin60 Istanbul Technical University, Istanbul, Turkey
M.N. Agaras, A. Cakir, K. Cankocak, Y. Komurcu, S. Sen61 Institute for
Scintillation Materials of National Academy of Science of Ukraine, Kharkov,
Ukraine
B. Grynyov National Scientific Center, Kharkov Institute of Physics and
Technology, Kharkov, Ukraine
L. Levchuk University of Bristol, Bristol, United Kingdom
F. Ball, J.J. Brooke, D. Burns, E. Clement, D. Cussans, O. Davignon, H.
Flacher, J. Goldstein, G.P. Heath, H.F. Heath, L. Kreczko, D.M. Newbold62, S.
Paramesvaran, B. Penning, T. Sakuma, D. Smith, V.J. Smith, J. Taylor, A.
Titterton Rutherford Appleton Laboratory, Didcot, United Kingdom
K.W. Bell, A. Belyaev63, C. Brew, R.M. Brown, D. Cieri, D.J.A. Cockerill, J.A.
Coughlan, K. Harder, S. Harper, J. Linacre, E. Olaiya, D. Petyt, C.H.
Shepherd-Themistocleous, A. Thea, I.R. Tomalin, T. Williams, W.J. Womersley
Imperial College, London, United Kingdom
R. Bainbridge, P. Bloch, J. Borg, S. Breeze, O. Buchmuller, A. Bundock, D.
Colling, P. Dauncey, G. Davies, M. Della Negra, R. Di Maria, G. Hall, G. Iles,
T. James, M. Komm, C. Laner, L. Lyons, A.-M. Magnan, S. Malik, A. Martelli, J.
Nash64, A. Nikitenko7, V. Palladino, M. Pesaresi, D.M. Raymond, A. Richards,
A. Rose, E. Scott, C. Seez, A. Shtipliyski, G. Singh, M. Stoye, T. Strebler,
S. Summers, A. Tapper, K. Uchida, T. Virdee16, N. Wardle, D. Winterbottom, J.
Wright, S.C. Zenz Brunel University, Uxbridge, United Kingdom
J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, C.K. Mackay, A. Morton, I.D. Reid,
L. Teodorescu, S. Zahid Baylor University, Waco, USA
K. Call, J. Dittmann, K. Hatakeyama, H. Liu, C. Madrid, B. McMaster, N.
Pastika, C. Smith Catholic University of America, Washington DC, USA
R. Bartek, A. Dominguez The University of Alabama, Tuscaloosa, USA
A. Buccilli, S.I. Cooper, C. Henderson, P. Rumerio, C. West Boston University,
Boston, USA
D. Arcaro, T. Bose, D. Gastler, D. Pinna, D. Rankin, C. Richardson, J. Rohlf,
L. Sulak, D. Zou Brown University, Providence, USA
G. Benelli, X. Coubez, D. Cutts, M. Hadley, J. Hakala, U. Heintz, J.M.
Hogan65, K.H.M. Kwok, E. Laird, G. Landsberg, J. Lee, Z. Mao, M. Narain, S.
Sagir66, R. Syarif, E. Usai, D. Yu University of California, Davis, Davis, USA
R. Band, C. Brainerd, R. Breedon, D. Burns, M. Calderon De La Barca Sanchez,
M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk,
W. Ko, O. Kukral, R. Lander, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout,
M. Shi, D. Stolp, D. Taylor, K. Tos, M. Tripathi, Z. Wang, F. Zhang University
of California, Los Angeles, USA
M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M.
Ignatenko, N. Mccoll, S. Regnard, D. Saltzberg, C. Schnaible, V. Valuev
University of California, Riverside, Riverside, USA
E. Bouvier, K. Burt, R. Clare, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, G.
Karapostoli, E. Kennedy, F. Lacroix, O.R. Long, M. Olmedo Negrete, M.I.
Paneva, W. Si, L. Wang, H. Wei, S. Wimpenny, B.R. Yates University of
California, San Diego, La Jolla, USA
J.G. Branson, P. Chang, S. Cittolin, M. Derdzinski, R. Gerosa, D. Gilbert, B.
Hashemi, A. Holzner, D. Klein, G. Kole, V. Krutelyov, J. Letts, M.
Masciovecchio, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon,
M. Tadel, A. Vartak, S. Wasserbaech67, J. Wood, F. Würthwein, A. Yagil, G.
Zevi Della Porta University of California, Santa Barbara - Department of
Physics, Santa Barbara, USA
N. Amin, R. Bhandari, C. Campagnari, M. Citron, V. Dutta, M. Franco Sevilla,
L. Gouskos, R. Heller, J. Incandela, A. Ovcharova, H. Qu, J. Richman, D.
Stuart, I. Suarez, S. Wang, J. Yoo California Institute of Technology,
Pasadena, USA
D. Anderson, A. Bornheim, J.M. Lawhorn, N. Lu, H.B. Newman, T.Q. Nguyen, M.
Spiropulu, J.R. Vlimant, R. Wilkinson, S. Xie, Z. Zhang, R.Y. Zhu Carnegie
Mellon University, Pittsburgh, USA
M.B. Andrews, T. Ferguson, T. Mudholkar, M. Paulini, M. Sun, I. Vorobiev, M.
Weinberg University of Colorado Boulder, Boulder, USA
J.P. Cumalat, W.T. Ford, F. Jensen, A. Johnson, E. MacDonald, T. Mulholland,
R. Patel, A. Perloff, K. Stenson, K.A. Ulmer, S.R. Wagner Cornell University,
Ithaca, USA
J. Alexander, J. Chaves, Y. Cheng, J. Chu, A. Datta, K. Mcdermott, N. Mirman,
J.R. Patterson, D. Quach, A. Rinkevicius, A. Ryd, L. Skinnari, L. Soffi, S.M.
Tan, Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek Fermi National
Accelerator Laboratory, Batavia, USA
S. Abdullin, M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, A. Apyan, S.
Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, K. Burkett,
J.N. Butler, A. Canepa, G.B. Cerati, H.W.K. Cheung, F. Chlebana, M. Cremonesi,
J. Duarte, V.D. Elvira, J. Freeman, Z. Gecse, E. Gottschalk, L. Gray, D.
Green, S. Grünendahl, O. Gutsche, J. Hanlon, R.M. Harris, S. Hasegawa, J.
Hirschauer, Z. Hu, B. Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, B.
Klima, M.J. Kortelainen, B. Kreis, S. Lammel, D. Lincoln, R. Lipton, M. Liu,
T. Liu, J. Lykken, K. Maeshima, J.M. Marraffino, D. Mason, P. McBride, P.
Merkel, S. Mrenna, S. Nahn, V. O’Dell, K. Pedro, C. Pena, O. Prokofyev, G.
Rakness, L. Ristori, A. Savoy-Navarro68, B. Schneider, E. Sexton-Kennedy, A.
Soha, W.J. Spalding, L. Spiegel, S. Stoynev, J. Strait, N. Strobbe, L. Taylor,
S. Tkaczyk, N.V. Tran, L. Uplegger, E.W. Vaandering, C. Vernieri, M.
Verzocchi, R. Vidal, M. Wang, H.A. Weber, A. Whitbeck University of Florida,
Gainesville, USA
D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerhoff, L. Cadamuro,
A. Carnes, D. Curry, R.D. Field, S.V. Gleyzer, B.M. Joshi, J. Konigsberg, A.
Korytov, K.H. Lo, P. Ma, K. Matchev, H. Mei, G. Mitselmakher, D. Rosenzweig,
K. Shi, D. Sperka, J. Wang, S. Wang, X. Zuo Florida International University,
Miami, USA
Y.R. Joshi, S. Linn Florida State University, Tallahassee, USA
A. Ackert, T. Adams, A. Askew, S. Hagopian, V. Hagopian, K.F. Johnson, T.
Kolberg, G. Martinez, T. Perry, H. Prosper, A. Saha, C. Schiber, R. Yohay
Florida Institute of Technology, Melbourne, USA
M.M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, M.
Rahmani, T. Roy, F. Yumiceva University of Illinois at Chicago (UIC), Chicago,
USA
M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, R. Cavanaugh, X. Chen, S.
Dittmer, O. Evdokimov, C.E. Gerber, D.A. Hangal, D.J. Hofman, K. Jung, J.
Kamin, C. Mills, I.D. Sandoval Gonzalez, M.B. Tonjes, H. Trauger, N. Varelas,
H. Wang, X. Wang, Z. Wu, J. Zhang The University of Iowa, Iowa City, USA
M. Alhusseini, B. Bilki69, W. Clarida, K. Dilsiz70, S. Durgut, R.P.
Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, A. Mestvirishvili, A.
Moeller, J. Nachtman, H. Ogul71, Y. Onel, F. Ozok72, A. Penzo, C. Snyder, E.
Tiras, J. Wetzel Johns Hopkins University, Baltimore, USA
B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan,
W.T. Hung, P. Maksimovic, J. Roskes, U. Sarica, M. Swartz, M. Xiao, C. You The
University of Kansas, Lawrence, USA
A. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, A. Bylinkin, J.
Castle, S. Khalil, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, C.
Rogan, S. Sanders, E. Schmitz, J.D. Tapia Takaki, Q. Wang Kansas State
University, Manhattan, USA
S. Duric, A. Ivanov, K. Kaadze, D. Kim, Y. Maravin, D.R. Mendis, T. Mitchell,
A. Modak, A. Mohammadi, L.K. Saini Lawrence Livermore National Laboratory,
Livermore, USA
F. Rebassoo, D. Wright University of Maryland, College Park, USA
A. Baden, O. Baron, A. Belloni, S.C. Eno, Y. Feng, C. Ferraioli, N.J. Hadley,
S. Jabeen, G.Y. Jeng, R.G. Kellogg, J. Kunkle, A.C. Mignerey, S. Nabili, F.
Ricci-Tam, Y.H. Shin, A. Skuja, S.C. Tonwar, K. Wong Massachusetts Institute
of Technology, Cambridge, USA
D. Abercrombie, B. Allen, V. Azzolini, A. Baty, G. Bauer, R. Bi, S. Brandt, W.
Busza, I.A. Cali, M. D’Alfonso, Z. Demiragli, G. Gomez Ceballos, M. Goncharov,
P. Harris, D. Hsu, M. Hu, Y. Iiyama, G.M. Innocenti, M. Klute, D. Kovalskyi,
Y.-J. Lee, P.D. Luckey, B. Maier, A.C. Marini, C. Mcginn, C. Mironov, S.
Narayanan, X. Niu, C. Paus, C. Roland, G. Roland, Z. Shi, G.S.F. Stephans, K.
Sumorok, K. Tatar, D. Velicanu, J. Wang, T.W. Wang, B. Wyslouch University of
Minnesota, Minneapolis, USA
A.C. Benvenuti${}^{\textrm{\textdagger}}$, R.M. Chatterjee, A. Evans, P.
Hansen, J. Hiltbrand, Sh. Jain, S. Kalafut, M. Krohn, Y. Kubota, Z. Lesko, J.
Mans, N. Ruckstuhl, R. Rusack, M.A. Wadud University of Mississippi, Oxford,
USA
J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA
E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, F. Golf, R. Gonzalez Suarez,
R. Kamalieddin, I. Kravchenko, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger
State University of New York at Buffalo, Buffalo, USA
A. Godshalk, C. Harrington, I. Iashvili, A. Kharchilava, C. Mclean, D. Nguyen,
A. Parker, S. Rappoccio, B. Roozbahani Northeastern University, Boston, USA
G. Alverson, E. Barberis, C. Freer, Y. Haddad, A. Hortiangtham, D.M. Morse, T.
Orimoto, R. Teixeira De Lima, T. Wamorkar, B. Wang, A. Wisecarver, D. Wood
Northwestern University, Evanston, USA
S. Bhattacharya, J. Bueghly, O. Charaf, K.A. Hahn, N. Mucia, N. Odell, M.H.
Schmitt, K. Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame,
USA
R. Bucci, N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N.
Kellams, K. Lannon, W. Li, N. Loukas, N. Marinelli, F. Meng, C. Mueller, Y.
Musienko36, M. Planer, A. Reinsvold, R. Ruchti, P. Siddireddy, G. Smith, S.
Taroni, M. Wayne, A. Wightman, M. Wolf, A. Woodard The Ohio State University,
Columbus, USA
J. Alimena, L. Antonelli, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, C.
Hill, W. Ji, T.Y. Ling, W. Luo, B.L. Winer Princeton University, Princeton,
USA
S. Cooperstein, P. Elmer, J. Hardenbrook, S. Higginbotham, A. Kalogeropoulos,
D. Lange, M.T. Lucchini, J. Luo, D. Marlow, K. Mei, I. Ojalvo, J. Olsen, C.
Palmer, P. Piroué, J. Salfeld-Nebgen, D. Stickland, C. Tully, Z. Wang
University of Puerto Rico, Mayaguez, USA
S. Malik, S. Norberg Purdue University, West Lafayette, USA
A. Barker, V.E. Barnes, S. Das, L. Gutay, M. Jones, A.W. Jung, A. Khatiwada,
B. Mahakud, D.H. Miller, N. Neumeister, C.C. Peng, S. Piperov, H. Qiu, J.F.
Schulte, J. Sun, F. Wang, R. Xiao, W. Xie Purdue University Northwest,
Hammond, USA
T. Cheng, J. Dolen, N. Parashar Rice University, Houston, USA
Z. Chen, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Kilpatrick, W. Li, B.P.
Padley, R. Redjimi, J. Roberts, J. Rorie, W. Shi, Z. Tu, A. Zhang University
of Rochester, Rochester, USA
A. Bodek, P. de Barbaro, R. Demina, Y.t. Duh, J.L. Dulemba, C. Fallon, T.
Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs, A.
Khukhunaishvili, E. Ranken, P. Tan, R. Taus Rutgers, The State University of
New Jersey, Piscataway, USA
A. Agapitos, J.P. Chou, Y. Gershtein, E. Halkiadakis, A. Hart, M. Heindl, E.
Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath, R.
Montalvo, K. Nash, M. Osherson, H. Saka, S. Salur, S. Schnetzer, D. Sheffield,
S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker University of
Tennessee, Knoxville, USA
A.G. Delannoy, J. Heideman, G. Riley, S. Spanier Texas A&M University, College
Station, USA
O. Bouhali73, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R.
Eusebi, J. Gilmore, T. Huang, T. Kamon74, S. Luo, R. Mueller, D. Overton, L.
Perniè, D. Rathjens, A. Safonov Texas Tech University, Lubbock, USA
N. Akchurin, J. Damgov, F. De Guio, P.R. Dudero, S. Kunori, K. Lamichhane,
S.W. Lee, T. Mengke, S. Muthumuni, T. Peltola, S. Undleeb, I. Volobouev, Z.
Wang Vanderbilt University, Nashville, USA
S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K.
Padeken, J.D. Ruiz Alvarez, P. Sheldon, S. Tuo, J. Velkovska, M. Verweij, Q.
Xu University of Virginia, Charlottesville, USA
M.W. Arenton, P. Barria, B. Cox, R. Hirosky, M. Joyce, A. Ledovskoy, H. Li, C.
Neu, T. Sinthuprasith, Y. Wang, E. Wolfe, F. Xia Wayne State University,
Detroit, USA
R. Harr, P.E. Karchin, N. Poudyal, J. Sturdy, P. Thapa, S. Zaleski University
of Wisconsin - Madison, Madison, WI, USA
M. Brodski, J. Buchanan, C. Caillol, D. Carlsmith, S. Dasu, I. De Bruyn, L.
Dodd, B. Gomber, M. Grothe, M. Herndon, A. Hervé, U. Hussain, P. Klabbers, A.
Lanaro, K. Long, R. Loveless, T. Ruggles, A. Savin, V. Sharma, N. Smith, W.H.
Smith, N. Woods †: Deceased
1: Also at Vienna University of Technology, Vienna, Austria
2: Also at IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
3: Also at Universidade Estadual de Campinas, Campinas, Brazil
4: Also at Federal University of Rio Grande do Sul, Porto Alegre, Brazil
5: Also at Université Libre de Bruxelles, Bruxelles, Belgium
6: Also at University of Chinese Academy of Sciences, Beijing, China
7: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia
8: Also at Joint Institute for Nuclear Research, Dubna, Russia
9: Also at Suez University, Suez, Egypt
10: Now at British University in Egypt, Cairo, Egypt
11: Also at Zewail City of Science and Technology, Zewail, Egypt
12: Also at Department of Physics, King Abdulaziz University, Jeddah, Saudi
Arabia
13: Also at Université de Haute Alsace, Mulhouse, France
14: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State
University, Moscow, Russia
15: Also at Tbilisi State University, Tbilisi, Georgia
16: Also at CERN, European Organization for Nuclear Research, Geneva,
Switzerland
17: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
18: Also at University of Hamburg, Hamburg, Germany
19: Also at Brandenburg University of Technology, Cottbus, Germany
20: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary
21: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
22: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
23: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India
24: Also at Institute of Physics, Bhubaneswar, India
25: Also at Shoolini University, Solan, India
26: Also at University of Visva-Bharati, Santiniketan, India
27: Also at Isfahan University of Technology, Isfahan, Iran
28: Also at Plasma Physics Research Center, Science and Research Branch,
Islamic Azad University, Tehran, Iran
29: Also at Università degli Studi di Siena, Siena, Italy
30: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy
31: Also at Kyunghee University, Seoul, Korea
32: Also at International Islamic University of Malaysia, Kuala Lumpur,
Malaysia
33: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia
34: Also at Consejo Nacional de Ciencia y Tecnología, Mexico city, Mexico
35: Also at Warsaw University of Technology, Institute of Electronic Systems,
Warsaw, Poland
36: Also at Institute for Nuclear Research, Moscow, Russia
37: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
38: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
39: Also at University of Florida, Gainesville, USA
40: Also at P.N. Lebedev Physical Institute, Moscow, Russia
41: Also at California Institute of Technology, Pasadena, USA
42: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
43: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
44: Also at INFN Sezione di Pavia a, Università di Pavia b, Pavia, Italy
45: Also at University of Belgrade, Faculty of Physics and Vinca Institute of
Nuclear Sciences, Belgrade, Serbia
46: Also at National and Kapodistrian University of Athens, Athens, Greece
47: Also at Riga Technical University, Riga, Latvia
48: Also at Universität Zürich, Zurich, Switzerland
49: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna,
Austria
50: Also at Gaziosmanpasa University, Tokat, Turkey
51: Also at Istanbul Aydin University, Istanbul, Turkey
52: Also at Mersin University, Mersin, Turkey
53: Also at Piri Reis University, Istanbul, Turkey
54: Also at Adiyaman University, Adiyaman, Turkey
55: Also at Ozyegin University, Istanbul, Turkey
56: Also at Izmir Institute of Technology, Izmir, Turkey
57: Also at Marmara University, Istanbul, Turkey
58: Also at Kafkas University, Kars, Turkey
59: Also at Istanbul University, Faculty of Science, Istanbul, Turkey
60: Also at Istanbul Bilgi University, Istanbul, Turkey
61: Also at Hacettepe University, Ankara, Turkey
62: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom
63: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
64: Also at Monash University, Faculty of Science, Clayton, Australia
65: Also at Bethel University, St. Paul, USA
66: Also at Karamanoğlu Mehmetbey University, Karaman, Turkey
67: Also at Utah Valley University, Orem, USA
68: Also at Purdue University, West Lafayette, USA
69: Also at Beykent University, Istanbul, Turkey
70: Also at Bingol University, Bingol, Turkey
71: Also at Sinop University, Sinop, Turkey
72: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey
73: Also at Texas A&M University at Qatar, Doha, Qatar
74: Also at Kyungpook National University, Daegu, Korea