TOP-18-011

TOP-18-011

# Measurement of the $\ttbar\bbbar$ production cross section in the all-jet
final state in $\Pp\Pp$ collisions at $\sqrt{s}=13\TeV$

###### Abstract

A measurement of the production cross section of top quark pairs in
association with two $\PQb$ jets ($\ttbar\bbbar$) is presented using data
collected in proton-proton collisions at $\sqrt{s}=13\TeV$ by the CMS detector
at the LHC corresponding to an integrated luminosity of $35.9\fbinv$. The
cross section is measured in the all-jet decay channel of the top quark pair
by selecting events containing at least eight jets, of which at least two are
identified as originating from the hadronization of $\PQb$ quarks. A
combination of multivariate analysis techniques is used to reduce the large
background from multijet events not containing a top quark pair, and to help
discriminate between jets originating from top quark decays and other
additional jets. The cross section is determined for the total phase space to
be $5.5\pm 0.3\stat^{+1.6}_{-1.3}\syst\unit{pb}$ and also measured for two
fiducial $\ttbar\bbbar$ definitions. The measured cross sections are found to
be larger than theoretical predictions by a factor of 1.5–2.4, corresponding
to 1–2 standard deviations.

##  0.1 Introduction

At the CERN LHC, top quark pairs are produced with copious amounts of
additional jets, including those resulting from the hadronization of $\PQb$
quarks ($\PQb$ jets). Top quark pair production in association with a pair of
$\PQb$ jets, $\ttbar\bbbar$, is challenging to model because of the very
different energy scales for the $\PQb$ jets produced in association with the
$\ttbar$ system and that of $\ttbar$ system [1], and because of the small but
nonnegligible mass of the quark. Improving the accuracy and the precision of
perturbative calculations in quantum chromodynamics (QCD) for this process is
crucial, since it represents an important background for numerous searches or
other measurements at the LHC. In particular, $\ttbar$ production in
association with a Higgs boson ($\ttbar\PH$), where the Higgs boson decays to
$\bbbar$, suffers from an irreducible $\ttbar\bbbar$ background [2, 3, 4, 5,
6, 7]. Searches for four top quark production ($\ttbar\ttbar$) are also
affected by this background [8, 9, 10]. The two latter processes provide
direct access to the top quark Yukawa coupling, a crucial parameter of the
standard model [11, 12]. An improved understanding of the $\ttbar\bbbar$
process would help reduce the uncertainty in such measurements.

Calculations of the production cross section of in association with jets have
been performed at next-to-leading order (NLO) in QCD and matched with parton
showers for up to two additional massless partons in the matrix element [13,
14, 15]. The $\ttbar\bbbar$ cross section at NLO, matched with parton showers,
has also been calculated for massless $\PQb$ quarks (five-flavour scheme, 5FS)
[16], and has recently become available for massive $\PQb$ quarks (four-
flavour scheme, 4FS) [17, 18, 19]. A comparison of the measurements of the
$\ttbar\bbbar$ cross section with such calculations provides valuable guidance
to improve the different frameworks. The $\ttbar\bbbar$ cross section has been
measured previously at $\sqrt{s}=8$ and $13\TeV$ by the ATLAS and CMS
Collaborations, in events containing one or two charged leptons [20, 21, 22,
23, 24].

This Letter focuses on the all-jet final state of the system, where each top
quark decays into three jets, leading to a signature of four $\PQb$ jets and
four light-quark jets for the $\ttbar\bbbar$ system. This final state is
favoured by a large branching fraction and provides a complete reconstruction
of top quarks, as opposed to other decay channels of the top quark pairs.
Moreover, the main uncertainties affecting the sensitivity in this measurement
are different than those affecting final states containing leptons, therefore
providing complementary information. However, the all-jet channel also suffers
from a large background from multijet production, as well as from the
difficulty of identifying jets that originate from decaying top quarks.
Multivariate analysis techniques are developed and implemented to mitigate
these problems. The $\ttbar\bbbar$ cross section is measured using data
collected by the CMS detector in $\Pp\Pp$ collisions at $\sqrt{s}=13\TeV$,
corresponding to an integrated luminosity of $35.9\fbinv$ [25].

##  0.2 The CMS detector and event simulation

The central feature of the CMS apparatus is a superconducting solenoid of 6m
internal diameter, providing a magnetic field of 3.8T. A silicon pixel and
strip tracker, a lead tungstate crystal electromagnetic calorimeter (ECAL),
and a brass and scintillator hadron calorimeter (HCAL), each composed of a
barrel and two endcap sections reside within the solenoid field. Forward
calorimeters extend the pseudorapidity coverage provided by the barrel and end
detectors. Muons are detected in gas-ionization chambers embedded in the steel
flux-return yoke outside the solenoid. A more detailed description of the CMS
detector, together with a definition of its coordinate system and kinematic
variables, can be found in Ref. [26]. Samples of $\ttbar$ events are simulated
at NLO in QCD using (v2) [27, 28, 29, 30]. These samples include
$\ttbar\bbbar$ events, where the additional jets are generated by the parton
shower. Single top quark production in the $t$ channel or in association with
a $\PW$ boson, and $\ttbar\PH$ production are simulated at NLO with [31, 32,
33]. Production of $\PW$ or $\PZ$ bosons in association with jets
($\PV$+jets), as well as QCD multijet events, are simulated at leading order
(LO) with (v2.2.2) [14], and the MLM merging scheme [34]. The generator is
used at NLO for simulating associated production of top quark pairs with $\PW$
or $\PZ$ bosons ($\ttbar\PV$). Diboson processes ($\PW\PW$, $\PW\PZ$ and
$\PZ\PZ$) are simulated at LO using (v8.219) [35].

All simulated events are processed with for modelling of the parton showering,
hadronization, and underlying event (UE). The NNPDF 3.0 [36] parton
distribution functions (PDFs) are used throughout, at the same perturbative
order as used by the event generators. The CUETP8M1 UE tune [37] is used for
all processes except for the $\ttbar$, $\ttbar\PH$ and single top quark
processes. For these, an updated version of the tune is used (CUETP8M2T4), in
which an adjusted value of the strong coupling constant is used in the
description of initial-state radiation [38]. Simulation of the CMS detector
response is based on (v9.4) [39]. Additional $\Pp\Pp$ interactions in the same
or neighbouring bunch crossings (pileup) are simulated with and overlaid with
hard-scattering events according to the pileup distribution measured in data.

The various simulated processes are normalized to state-of-the-art predictions
for the production cross sections. The $\ttbar$, $\PV$+jets, single top quark,
and $\PW^{+}\PW^{-}$ samples are normalized to next-to-NLO (NNLO) precision in
QCD [40, 41, 42, 43], while remaining processes such as $\ttbar\PV$,
$\ttbar\PH$, and other diboson production are normalized to NLO in QCD [14,
44].

##  0.3 Definitions of fiducial phase space

The $\ttbar\bbbar$ production cross section is measured for three different
phase space definitions. Two definitions for $\ttbar\bbbar$ events in the
fiducial phase space, matching the detector acceptance, are considered: one
that is based exclusively on stable generated particles after hadronization
(parton-independent), and one that also uses parton-level information after
radiation emission (parton-based). The former facilitates comparisons with
predictions from event generators, while the latter is closer to the approach
taken by searches for $\ttbar\PH$ production to define the contribution from
the $\ttbar\bbbar$ process. The cross section is reported for the total phase
space by correcting the parton-based fiducial cross section by the
experimental acceptance.

Particle-level jets are defined by clustering stable generated final-state
particles, excluding neutrinos, using the anti-algorithm [45, 46] with a
distance parameter of 0.4. These jets are defined unambiguously as $\PQb$ or
$\PQc$ jets by rescaling the momenta of generated $\PQb$ and $\PQc$ hadrons to
a negligible value, while preserving their direction, and including them in
the clustering procedure [47]. A jet is labelled $\PQb$ jet if it is matched
to at least one $\PQb$ hadron, and labelled $\PQc$ jet if matched with at
least one $\PQc$ hadron and no $\PQb$ hadron.

Events in the generated $\ttbar$ sample are divided into exclusive categories
according to the flavour of the jets that do not originate from the decay of
top quarks, which we refer to as “additional” jets. The $\PQb$ or $\PQc$ jets
are considered to originate from a top quark if one of the clustered $\PQb$ or
$\PQc$ hadrons features a top quark in its simulation history. Additional jets
are required to have a transverse momentum $\pt>20\GeV$, and absolute
pseudorapidity $\abs{\eta}<2.4$. No explicit requirement on the $\PQb$ hadron
kinematic variables is used. Events are categorized as $\ttbar\bbbar$ if they
contain at least two additional $\PQb$ jets, which defines the total phase
space for which the $\ttbar\bbbar$ cross section is measured. Events with a
single additional $\PQb$ jet are categorized as $\ttbar\PQb$ ($\ttbar 2\PQb$)
if that $\PQb$ jet is matched with exactly one (at least two) $\PQb$
hadron(s). The $\ttbar\PQb$ events correspond to $\ttbar\bbbar$ events where
one of the additional $\PQb$ jets fails the above kinematic requirements,
while $\ttbar 2\PQb$ events arise from collinear gluon splittings. If no
$\PQb$ jets are present but at least one additional $\PQc$ jet is present the
event is referred to as $\ttbar\PQc\PAQc$; all remaining events are denoted
$\ttbar\cmsSymbolFace{jj}$.

For the parton-based definition of the $\ttbar\bbbar$ fiducial phase space, at
least eight jets with $\pt>20\GeV$ and $\abs{\eta}<2.4$ must be present, of
which at least six have $\pt>30\GeV$. At least four of these jets must be
$\PQb$ jets, and at least two of those must not originate from top quarks.
This last requirement is removed for the parton-independent fiducial
definition, in order to be independent of the origin of the $\PQb$ jets, and
thus of the simulated parton content. Some $\ttbar\bbbar$ events in the total
phase space failing the fiducial requirements may still be reconstructed and
selected because of resolution effects, and are referred to as out-of-
acceptance. They correspond to 16% of all reconstructed $\ttbar\bbbar$ events.

##  0.4 Event reconstruction and selection

The particle-flow algorithm [48] aims to reconstruct and identify each
particle in an event, with an optimized combination of information from the
various elements of the CMS detector. The primary $\Pp\Pp$ interaction vertex
is taken to be the reconstructed vertex with the largest sum of the $\pt^{2}$
of the objects associated to that vertex, where the considered objects are
those returned by a jet clustering algorithm [45, 46] applied to the tracks
assigned to the vertex, and the associated missing transverse momentum, taken
as the negative vector sum of the of those objects. The energy of photons is
obtained from the ECAL measurement. The energy of electrons is determined from
a combination of the electron momentum at the primary interaction vertex as
determined by the tracker, the energy of the corresponding ECAL cluster, and
the energy sum of all bremsstrahlung photons spatially compatible with
originating from the electron track. The of muons is obtained from the
curvature of the corresponding tracks. 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 and for the response function of the calorimeters to hadronic showers.
The energy of neutral hadrons is obtained from the corresponding corrected
ECAL and HCAL energies.

For each event, hadronic jets are clustered from the reconstructed particles
using the anti-algorithm with a distance parameter of 0.4. The jet momentum is
determined as the vectorial sum of all particle momenta in the jet, and is
found from simulation to be within 5 to 10% of the true momentum over the
whole spectrum and detector acceptance. Pileup interactions can contribute
additional tracks and calorimetric energy depositions to the jet momentum. To
mitigate this effect, tracks identified to be originating from pileup vertices
are discarded and an offset correction is applied to correct for remaining
contributions [47]. Jet energy corrections are derived from simulation to
bring the average measured response of a jet to that of a particle-level jet.
In situ measurements of the momentum balance in dijet, photon+jet, $\PZ$+jet,
and multijet events are used to account for any residual differences in jet
energy scale in data and simulation [49]. The data used for these measurements
are independent of those used for the present Letter.

A combined secondary vertex $\PQb$ tagging algorithm (CSVv2) is used to
identify jets originating from the hadronization of $\PQb$ quarks [50], with
an efficiency for identifying $\PQb$ jets in simulated events of about 65%.
The misidentification probability is about 10 and 1% for $\PQc$ and light-
flavour jets, respectively, where the latter refers to jets originating from
the hadronization of $\PQu$, $\PQd$, $\PQs$ quarks or gluons. The distribution
of the discriminator score for $\PQb$ and light-flavour jets in the simulation
is calibrated to match the distribution measured in control samples of events
with exactly two leptons (electrons or muons) and two jets, and $\PZ$ bosons
produced in association with jets where the $\PZ$ bosons decay to pairs of
electrons or muons. The calibration is achieved by reweighting events using
scale factors that are parameterized by the jet flavour, $\pt$, $\abs{\eta}$,
and $\PQb$ tagging discriminator score [50].

Data are collected using two triggers [51], both requiring at least six jets
with $\abs{\eta}<2.4$. The first (second) trigger considers jets with $\pt>40$
($30$) , and requires that the jet scalar sum, , exceeds $450$ ($400$) and
that at least one (two) of the jets is (are) $\PQb$ tagged. The efficiency of
these triggers is measured in simulation, as well as in a data control sample
collected using independent single-muon triggers. The trigger efficiency in
simulation is corrected to match the efficiency observed in the data by
reweighting events using scale factors defined as the ratio between the
efficiencies in the data and simulation. For events satisfying the
preselection criteria detailed below, the trigger efficiency is above 95%.

An offline preselection is applied to data and simulated events, by requiring
the presence of at least six jets with $\pt>40\GeV$ and $\abs{\eta}<2.4$, of
which at least two are $\PQb$ tagged, and $\HT>500\GeV$. Additional jets in
the events are considered if they satisfy the requirements $\pt>30\GeV$ and
$\abs{\eta}<2.4$. Events are vetoed if they contain electrons or muons with
$\pt>15\GeV$ and $\abs{\eta}<2.4$ that satisfy highly efficient identification
criteria [52, 53] and are isolated from hadronic activity. About 20% of the
$\ttbar\bbbar$ events in the fiducial phase space pass the offline selection.

##  0.5 Multivariate analysis

The final state considered in this analysis suffers from a large background
from multijet production, as well as from the difficulty to identify which
jets do not stem from top quark decays. To address these challenges and
improve the sensitivity to the $\ttbar\bbbar$ signal, several multivariate
analysis tools have been employed.

The multijet background can be discriminated from production by observing that
the latter is expected to contain four light-quark jets from $\PW$ boson
decays per event, whereas the former is enriched in gluon jets. Gluon and
quark jets are separated using a quark-gluon likelihood (QGL) variable, based
on jet substructure observables [54, 55]. Using the individual jet QGL values,
the likelihood of an event to contain $N_{\PQq}$ light-quark jets and
$N_{\Pg}$ gluon jets is defined as

$L(N_{\PQq},N_{\Pg})=\sum_{\text{perm}}\left(\prod_{k={i_{1}}}^{i_{N_{\PQq}}}f_{\PQq}(\zeta_{k})\right)\left(\prod_{m={i_{N_{\PQq}+1}}}^{i_{N_{\PQq}+N_{\Pg}}}f_{\Pg}(\zeta_{m})\right),$
(1)

where the sums run over all possible assignments of $N_{\PQq}$ jets to quarks
(indices $k$) and $N_{\Pg}$ jets to gluons (indices $m$), $\zeta_{i}$ is the
QGL discriminant of the $i^{\text{th}}$ jet, and $f_{\PQq}$ and $f_{\Pg}$ are
the probability densities for $\zeta_{i}$ under the hypothesis of ($\PQu$,
$\PQd$, $\PQs$, or $\PQc$) quark or gluon origin, respectively. When computing
$L(N_{\PQq},N_{\Pg})$, $\PQb$-tagged jets are not considered. Based on the
event likelihoods with $N_{\PQq}=4$ and $N_{\Pg}=0$, as well as $N_{\PQq}=0$
and $N_{\Pg}=4$, the QGL ratio (QGLR) is defined as
$\text{QGLR}=L(4,0)/(L(4,0)+L(0,4)).$ Other values for $N_{\PQq}$ and
$N_{\Pg}$ have been tried but led to reduced discrimination between multijet
and production. We correct the modelling of the QGL in the simulation by
reweighting each event based on the quark or gluon origin and the QGL value of
all jets in the event, where the weights are measured using data samples
enriched in $\PZ$+jets and dijet events [55]. After applying this correction,
a good agreement is found between data and simulation.

To address the large combinatorial ambiguity in identifying the additional
jets in the events, we have trained a boosted decision tree (BDT) using the
TMVA package [56], henceforth referred to as the “permutation BDT”. In events
with eight reconstructed jets, there are 28 ways to select six of those as
originating from the all-jet decay of a top quark pair, and there are 90 ways
to match those six jets to the six partons from the top quark decay chains.
Some permutations are indistinguishable and are not considered, permutations
of two jets assigned to a $\PW$ boson decay are not considered, and neither
are the permutations of three jets assigned to a $\PQt$ or $\PAQt$ decay. To
reduce the large number of permutations, the least favoured ones are rejected
using a $\chi^{2}$ variable quantifying the compatibility of the invariant
masses of the different jet pairings with those of the particles they should
come from, defined as

$\chi^{2}=(m_{\mathrm{j}_{1},\mathrm{j}_{3},\mathrm{j}_{4}}-m_{\PQt})^{2}/\sigma_{\PQt}^{2}+(m_{\mathrm{j}_{3},\mathrm{j}_{4}}-m_{\PW})^{2}/\sigma_{\PW}^{2}+(m_{\mathrm{j}_{2},\mathrm{j}_{5},\mathrm{j}_{6}}-m_{\PQt})^{2}/\sigma_{\PQt}^{2}+(m_{\mathrm{j}_{5},\mathrm{j}_{6}}-m_{\PW})^{2}/\sigma_{\PW}^{2},$

where $m_{(\dots)}$ denotes the invariant mass of the given jets, and
$\sigma_{\PW}=10.9\GeV$ and $\sigma_{\PQt}=17.8\GeV$ are the experimental
resolutions in the two- and three-jet invariant masses, respectively. The
masses entering the equation are $m_{\PQt}=172.3\GeV$ and $m_{\PW}=80.2\GeV$,
measured from the generated system after reconstruction. The BDT is trained
using simulated events after applying the above preselection criteria,
requiring the presence of at least seven jets, and reducing the number of
permutations by requiring that $\chi^{2}<33.38$, corresponding to a p-value
$P(\chi^{2})$ of $10^{-6}$ for a $\chi^{2}$ distribution with four degrees of
freedom. Events for which no permutation satisfies this requirement are
rejected. The correct jet-parton assignment is considered as a signal in the
training, while all other distinguishable combinations are treated as
background. Input variables used for the BDT include jet $\PQb$ tagging
discriminator scores and kinematic quantities, such as invariant masses of
pairs and triplets of jets, angular openings between jets, and the transverse
momenta of jets. For each permutation, only quantities pertaining to the six
jets assumed to originate from the top quarks are used in the training. The
permutation yielding the highest BDT score is used for the rest of the
analysis. For events with eight jets where all six jets from the top quark
decays have been selected, the permutation BDT identifies the correct
permutation with about 60% efficiency.

As a further handle to reduce the multijet background, we have trained a
second BDT to discriminate this background from inclusive $\ttbar$+jets
production. While supervised training of multivariate classifiers relies on
samples of simulated events, the poor modelling of multijet production and the
insufficient size of the available simulated samples limit the achievable
discrimination power. A proposed method to alleviate these shortcomings is a
classification without labels (CWoLa) [57]. In this weakly supervised
approach, the classifier is trained using data, whereby one region in the data
is treated as background and another independent region is treated as signal.
In the limit of large training sample the resulting classifier converges to
the optimal classifier to distinguish between signal and background, provided
the two following conditions are fulfilled [57]. First, the relative rates of
the actual signal and background processes should be different in the two
regions. Second, the distributions of the variables entering the CWoLa
classifier should be independent of the quantity used to define the two
regions, for both the signal and background processes. The CWoLa BDT is
trained using a sample of data with exactly seven jets, where two independent
regions are defined by requiring that the QGLR is below or above $0.95$. The
first and second regions are expected to contain about 10 and 20% of $\ttbar$
events, respectively. Variables used for constructing the CWoLa BDT are
kinematic quantities similar to those used in the permutation BDT, the output
value of the permutation BDT, and the tagging discriminator scores of the two
jets identified by the permutation BDT as the $\PQb$ jets originating from the
top quark decays. Only the six jets identified by the permutation BDT as
coming from the top quark decays are used to define the CWoLa BDT input
variables. The performance of the resulting classifier, measured in the region
with at least eight jets, is found to be comparable to that of a supervised
classifier trained using simulated samples.

##  0.6 Cross sections

To measure the $\ttbar\bbbar$ cross section we require, in addition to the
preselection criteria, the presence of at least eight jets, and
$P(\chi^{2})>10^{-6}$. The distributions in the QGLR and of the CWoLa BDT
discriminants for selected events are shown in Fig. 1. The cross section is
extracted from a binned maximum likelihood fit to a two-dimensional
distribution (referred to as 2DCSV) constructed using the largest and second-
largest $\PQb$ tagging discriminator scores among the jets determined to be
additional jets by the permutation BDT. In order to increase the signal purity
and the precision in the measurement, we define a signal region (SR) by
requiring that the CWoLa BDT score be above 0.5, and the QGLR be above 0.8.
These thresholds are optimized to obtain the best expected precision in the
cross section. About 20% of the $\ttbar\bbbar$ signal that passes the offline
preselection is selected into the SR.

Figure 1: Distributions in the QGLR (left) and the CWoLa BDT discriminants
(right). Both are after preselection, requiring $P(\chi^{2})>10^{-6}$ and at
least eight selected jets. All the contributions are based on simulation. The
multijet contribution is scaled to match the total yields in data, after the
other processes including the $\ttbar\bbbar$ signal have been normalized to
their corresponding theoretical cross sections. This choice takes into account
only the effect of the shape variation from the multijet background. The small
backgrounds include $\ttbar\PV$, $\ttbar\PH$, single top quark, $\PV$+jets,
and diboson production. The lower panels show the ratio between the observed
data and the predictions. The dashed lines indicate the boundaries between the
signal and control regions defined in Section 0.6. Hatched bands indicate the
statistical uncertainty in the predictions without considering the systematic
sources, dominated by the uncertainties in the simulated multijet background.
Underflow and overflow events were added to the first and last bins,
respectively.

The multijet background is also estimated from data. Three independent control
regions (CRs), orthogonal to the SR, are defined by inverting the requirements
on the CWoLa BDT and the QGLR: the CR1 ($\text{BDT}>0.5$, $\text{QGLR}<0.8$),
the CR2 ($\text{BDT}<0.5$, $\text{QGLR}<0.8$), and the CR3 ($\text{BDT}<0.5$,
$\text{QGLR}>0.8$). For multijet production, the CWoLa BDT score and the QGLR
are nearly independent, so that in each bin $i$ of the 2DCSV distribution the
number of multijet events in the SR, $N^{\text{SR}}_{i}$, can be estimated
from the number of multijet events in the CRs as

$N^{\text{SR}}_{i}=N^{\text{CR3}}_{i}\,\frac{N^{\text{CR1}}_{i}}{N^{\text{CR2}}_{i}}.$
(2)

This relationship is a consequence of the choice of variables entering the
CWoLa BDT, which were required to be independent of the QGLR in order to
satisfy the hypotheses of the CWoLa method. In order to properly take into
account the small but non-negligible signal contribution in the CRs, the fit
to extract the cross section is performed in all four regions, with the
multijet rates $N^{\text{CR1}}_{i}$, $N^{\text{CR2}}_{i}$, and
$N^{\text{CR3}}_{i}$ free to vary in the fit. The assumption of Eq. (2) on
which this estimation relies is confirmed using the simulation. In addition,
we verify that Eq. (2) is also satisfied in the data for kinematic
distributions, such as the invariant mass of the reconstructed $\PW$ bosons
and top quarks, where for each bin of these distributions the multijet yields
are estimated by taking the difference between the observed yields in data and
the predicted yields of all simulated processes. Finally, we validate Eq. (2)
using alternative definitions of the four regions in the plane formed by the
QGLR and the CWoLa BDT, excluding the SR as defined above. The outcome of
goodness-of-fit tests of the 2DCSV distribution was also positive for each of
the alternative region definitions.

The data are fitted using a profiled maximum likelihood technique, where the
likelihood is built as a product of independent Poisson likelihoods, defined
for each bin $i$ of the 2DCSV distributions in the four event regions using
the following expression for the number of events in bin $i$:

$\mathcal{N}_{i}=\mu\,\mathcal{T}_{i}^{\text{sig}}(\vec{\theta})+\sum_{k\text{
in sim bkg}}\mathcal{T}_{i}^{k}(\vec{\theta})+N_{i},$ (3)

where $\mu$ is a signal strength parameter, defined by the ratio of observed
to expected signal, $\mathcal{T}_{i}^{k}$ is the expected yield for process
$k$ in bin $i$, “sig” includes the contributions from $\ttbar\bbbar$, $\ttbar
2\PQb$, and $\ttbar\PQb$, and $\vec{\theta}$ is a vector of nuisance
parameters affecting the predicted yields of the various processes introduced
to model the systematic uncertainties described in the next section. The
parameters $N_{i}$ are used to estimate the multijet background from the
combined fit of the four regions; they are free parameters in the CRs and are
given by Eq. (2) in the SR. The likelihood also features constraint terms for
each of the nuisance parameters considered in the fit. Different templates are
constructed from $\ttbar\bbbar$ events matching the fiducial requirements and
from events failing these requirements. For the fiducial $\ttbar\bbbar$
templates, the effect of nuisance parameters corresponding to theoretical
uncertainties is normalized such that the $\ttbar\bbbar$ cross section in the
fiducial phase space is preserved, i.e. only shape variations within that
phase space and their impact on the reconstruction efficiency are taken into
account. No such requirement is made for the other templates. The uncertainty
in the measured cross section is obtained by profiling the nuisance
parameters. As described in the next section, some uncertainties are not
profiled and are added in quadrature with the uncertainty obtained from the
fit. The fit is repeated for each of the two fiducial phase-space definitions
for $\ttbar\bbbar$ events described in Section 0.3, leading to different in-
and out-of-acceptance $\ttbar\bbbar$ templates. The total $\ttbar\bbbar$ cross
section is obtained by dividing the cross section for the parton-based
fiducial phase space by the acceptance, estimated using + to be $(29.4\pm
1.8)\%$. Uncertainties affecting this acceptance correction are detailed in
the next section.

##  0.7 Systematic uncertainties

Several sources of systematic uncertainties affecting the predictions for the
signal and background processes entering the analysis are considered. These
uncertainties may affect the normalization of the templates entering the fit,
or may alter both their shape and their normalization. The migration of events
between the four regions is taken into account when relevant. Experimental
sources of uncertainties are taken to be fully correlated for all signal and
background distributions estimated using the simulation, while only a subset
of theoretical uncertainties are correlated among the $\ttbar$+jets
components.

The modelling of the shape of the $\PQb$ tagging discriminator in the
simulation represents an important source of systematic uncertainty. Several
uncertainties in the calibration of the $\PQb$ tagging discriminator
distribution are propagated independently to the shape and normalization of
the 2DCSV templates. These are related to the uncertainty in the contamination
by light- (heavy-) flavour jets in the control samples used for the
measurement of heavy- (light-) jet correction factors, as well as to the
statistical uncertainty in these measurements [50]. Since no dedicated
measurement is performed for $\PQc$ jets, the uncertainty in the shape of the
$\PQb$ tagging discriminator distribution for $\PQc$ jets is conservatively
taken to be twice the relative uncertainty considered for $\PQb$ jets. In
total, six different nuisance parameters are introduced to estimate the
uncertainty arising from $\PQb$ tagging.

We evaluate the effect of the uncertainty in the jet energy scale (JES) and
jet energy resolution (JER) by shifting the jet four-momenta using correction
factors that depend on jet and $\abs{\eta}$ for the JES, and jet $\abs{\eta}$
for the JER [49]. The calibration of the JES is affected by several sources of
uncertainty, which are propagated independently to the measurement. The
uncertainty in the JES is also propagated to the $\PQb$ tagging calibration,
and the resulting effect on the distribution of the $\PQb$ tagging
discriminators is taken to be correlated with the effect on the jet momenta.

Uncertainties pertaining to the QGL are estimated conservatively by removing
or doubling the scale factors applied to correct the distribution of the QGL
in the simulation [55]. The uncertainty in the integrated luminosity is
evaluated to be 2.5% [25]. Uncertainties in the trigger efficiency are
estimated by varying the trigger scale factors by their uncertainty, as
determined from the efficiency measurements in data and simulation. The
uncertainty in the modelling of pileup is estimated by reweighting simulated
events to yield different distributions of the expected number of pileup
interactions, obtained by varying the total inelastic $\Pp\Pp$ cross section
by 4.6% [58]. We take into account the limited size of the simulated samples
by varying independently the predicted yields in every bin by their
statistical uncertainties.

Theoretical uncertainties in the modelling of the $\ttbar$+jets process enter
this analysis both through the efficiency to reconstruct and select
$\ttbar\bbbar$ events, and through the contamination from $\ttbar\PQc\PAQc$
and $\ttbar\cmsSymbolFace{jj}$ backgrounds. The uncertainties in the
renormalization and factorization scales ($\mu_{\mathrm{R}}$ and
$\mu_{\mathrm{F}}$, respectively) are estimated by varying both scales
independently by a factor of two up or down in the event generation, omitting
the two cases where the scales are varied in opposite directions, and taking
the envelope of the six resulting variations. Likewise, the uncertainties
related to the choice of the scale in the parton shower is evaluated by
varying the scale in the initial-state shower by factors of 0.5 and 2, and the
scale in the final-state shower by factors of $\sqrt{2}$ and $1/\sqrt{2}$.
Propagation of the uncertainties associated with the PDFs, as well as with the
value of the strong coupling in the PDFs, has been achieved by reweighting
generated events using variations of the NNPDF 3.0 set [36]. The impact of the
choice of the matching scale $h_{\text{damp}}=1.58m_{\PQt}$ between the
matrix-element generator and the parton shower in is evaluated using simulated
samples generated with different choices of $h_{\text{damp}}=m_{\PQt}$ and
$2.24m_{\PQt}$ [38]. We evaluate the uncertainty related to the UE tune by
varying the tune parameters according to their uncertainties. The uncertainty
from the modelling of colour reconnection in the final state is evaluated by
considering four alternatives to the default, which is based on multiple-
parton interactions (MPI) with early resonance decays (ERD) switched off.
These alternatives are an MPI-based scheme with ERD switched on, a QCD-
inspired scheme [59], and a gluon-move scheme with ERD either off or on [60].
All the alternative models were tuned to LHC data [61]. It has been verified
that the selection efficiency obtained from the nominal $\ttbar$ simulation,
in which additional jets are generated by the parton shower, is in agreement
within estimated modelling uncertainties with that obtained using a sample of
$\ttbar\bbbar$ events generated at NLO in QCD with massive quarks (4FS) [19].
Since the spectrum of the top quark $\pt$ is known to be softer in the data
than in the simulation, we evaluate the effect of this mismodelling by
reweighting the generated events to match the top quark $\pt$ distribution
measured in data [62]. The latter two uncertainties are not evaluated using
profiled nuisance parameters, but by repeating the measurement using varied
signal and background predictions. The differences in the measured cross
sections are taken as the corresponding uncertainties and are added in
quadrature with the uncertainty obtained from the profile likelihood.
Uncertainties related to the $\mu_{\mathrm{R}}$ and $\mu_{\mathrm{F}}$ scales,
the parton shower scale, and the $h_{\text{damp}}$ choice are taken to be
uncorrelated for the $\ttbar\bbbar$, $\ttbar\PQb$, $\ttbar 2\PQb$,
$\ttbar\PQc\PAQc$ and $\ttbar\cmsSymbolFace{jj}$ templates, while the other
modelling uncertainties are taken to be correlated for all events. In addition
to the aforementioned modelling uncertainties, we assign an uncertainty of 50%
to the normalization of the $\ttbar\PQc\PAQc$ background to cover the lack of
precise measurements of this process. The results are stable when doubling
that uncertainty.

Compared to $\ttbar$+jets and multijet production, the contribution of other
background processes such as $\ttbar\PV$, $\ttbar\PH$, $\PV$+jets, diboson,
and single top quark production is small. We assign uncertainties to their
predicted rates based on the PDF and $\mu_{\mathrm{R}}$/$\mu_{\mathrm{F}}$
scale uncertainties in their theoretical cross sections.

Table 0.7 summarizes the contributions of the various sources of systematic
uncertainties to the total uncertainty in the cross sections measured in the
fiducial phase space. The theoretical uncertainty in the acceptance from the
various sources listed above is estimated to be 6%, and is added in quadrature
with the uncertainty in the parton-based fiducial cross section to yield the
systematic uncertainty in the total $\ttbar\bbbar$ cross section.

The considered sources of systematic uncertainties and their respective
contributions to the total systematic uncertainty in the measured
$\ttbar\bbbar$ cross section for the two defined $\ttbar\bbbar$ fiducial phase
spaces. The upper (lower) portion of the table lists uncertainties related to
the experimental conditions (theoretical modelling). The numbers are obtained
by taking the difference in quadrature of the profile likelihood width when
fixing nuisance parameters corresponding to a given source of uncertainty and
leaving the others free to vary.

Source |  Fiducial, parton-independent (%) |  Fiducial, parton-based (%)
---|---|---
Simulated sample size | ${}^{+15}_{-11}$ | ${}^{+15}_{-11}$
Quark-gluon likelihood | ${}^{+13}_{-8}$ | ${}^{+13}_{-8}$
tagging of quark | $\pm 10$ | $\pm 10$
JES and JER | ${}^{+5.1}_{-5.2}$ | ${}^{+5.0}_{-5.4}$
Integrated luminosity | ${}^{+2.8}_{-2.2}$ | ${}^{+2.4}_{-2.2}$
Trigger efficiency | ${}^{+2.6}_{-2.1}$ | ${}^{+2.5}_{-2.2}$
Pileup | ${}^{+2.3}_{-2.0}$ | ${}^{+2.2}_{-1.9}$
$\mu_{\mathrm{R}}$ and $\mu_{\mathrm{F}}$ scales | ${}^{+13}_{-9}$ | ${}^{+13}_{-9}$
Parton shower scale | ${}^{+11}_{-8}$ | ${}^{+11}_{-8}$
UE tune | ${}^{+9.0}_{-5.3}$ | ${}^{+9.0}_{-5.2}$
Colour reconnection | $\pm 7.2$ | $\pm 7.1$
Shower matching ($h_{\text{damp}}$) | ${}^{+4.3}_{-2.8}$ | ${}^{+3.8}_{-2.7}$
$\ttbar\PQc\PAQc$ normalization | ${}^{+3.2}_{-4.4}$ | ${}^{+2.9}_{-4.5}$
Modelling of of top quark | $\pm 2.5$ | $\pm 2.4$
PDFs | ${}^{+2.2}_{-2.0}$ | ${}^{+2.2}_{-2.0}$
Total | ${}^{+28}_{-23}$ | ${}^{+28}_{-23}$

##  0.8 Results

Figure 2:  Distribution in the 2DCSV in the SR (upper left), CR1 (upper
right), CR2 (lower right), and CR3 (lower left) regions. For clarity, the two-
dimensional distribution with largest and next-to-largest tagging discriminant
scores for the additional jets have been unrolled to one dimension, and the
resulting bins ordered according to increasing values of the ratio between
expected signal and background yields in each bin of the SR. The small
backgrounds include $\ttbar\PV$, $\ttbar\PH$, single top quark, $\PV$+jets,
and diboson production. Hatched bands correspond to uncertainties. The bottom
panels show the pull distribution. The pull is defined as the bin by bin
difference between data and predicted yields after the fit, divided by the
uncertainties accounted for correlations between data and predictions after
the fit.

The result of the maximum likelihood fit described in Section 0.6 is shown in
Fig. 2 for the 2DCSV distributions in the four analysis regions. The
contribution from multijet production nearly matches the differences between
the yields in data and from the other processes in the CR1, CR2, and CR3
because it is estimated from the data in the four regions according to the
method described in the previous section. The measured cross section for the
two $\ttbar\bbbar$ definitions in the fiducial phase space, as well as for the
total phase space introduced in Section 0.3, are given in Table 0.8. The
measurement uncertainty is dominated by the systematic effects from the
simulation sample sizes, QGL corrections, and $\mu_{\mathrm{R}}$ and
$\mu_{\mathrm{F}}$ dependences on changes in scale.

Because of the large overlap between the two definitions of the $\ttbar\bbbar$
fiducial phase space, the measured cross sections are numerically equal at the
quoted precision. The measurements are compared with NLO predictions from for
inclusive production interfaced with either or (v2.7.1) [63], using the EE5C
UE tune [64] for the latter. Predictions from at NLO interfaced with for
production with up to two extra massless partons (5FS) merged using the FxFx
scheme [15], and for $\ttbar\bbbar$ production with massive $\PQb$ quarks
(4FS), are also compared with the measurements. The predicted cross sections
are not rescaled by any NLO to NNLO K-factor, which for inclusive production
amounts to 1.1–1.15 [40]. Measured and predicted cross sections are shown in
Fig. 3. The predictions underestimate the measured cross section by a factor
of 1.5–2.4, corresponding to differences of 1–2 standard deviations. This is
consistent with the results from Refs. [20, 21, 22, 23, 24].

Measured and predicted cross sections for the different definitions of the
$\ttbar\bbbar$ phase space considered in this analysis. For measurements, the
first uncertainty is statistical, while the second one is from the systematic
sources. The uncertainties in the predicted cross sections include the
statistical uncertainty, the PDF uncertainties, and the $\mu_{\mathrm{R}}$ and
$\mu_{\mathrm{F}}$ dependences on changes in scale. The uncertainties in scale
for parton showers are not included, and amount to about 15% for +. Unless
specified otherwise, is used for the modelling the parton shower,
hadronization, and the underlying event.

|  Fiducial, parton-independent (pb) |  Fiducial, parton-based (pb) | Total (pb)
---|---|---|---
Measurement | $1.6\pm 0.1^{+0.5}_{-0.4}$ | $1.6\pm 0.1^{+0.5}_{-0.4}$ | $5.5\pm 0.3^{+1.6}_{-1.3}$
() | $1.1\pm 0.2$ | $1.0\pm 0.2$ | $3.5\pm 0.6$
() +  | $0.8\pm 0.2$ | $0.8\pm 0.2$ | $3.0\pm 0.5$
(4FS $\ttbar\bbbar$) | $0.8\pm 0.2$ | $0.8\pm 0.2$ | $2.3\pm 0.7$
(5FS $\ttbar$+jets, FxFx) | $1.0\pm 0.1$ | $1.0\pm 0.1$ | $3.6\pm 0.3$

Figure 3:  Comparison of the measured $\ttbar\bbbar$ production cross sections
(vertical lines) with predictions from several Monte Carlo generators
(squares), for three definitions of our $\ttbar\bbbar$ regions of phase space:
fiducial parton-independent (left), fiducial parton-based (middle), total
(right). The dark (light) shaded bands show the statistical (total)
uncertainties in the measured value. Uncertainty intervals in the theoretical
cross sections include the statistical uncertainty as well as the
uncertainties in the PDFs and the $\mu_{\mathrm{R}}$ and $\mu_{\mathrm{F}}$
scales.

##  0.9 Summary

The first measurement of the $\ttbar\bbbar$ cross section in the all-jet final
state was presented, using $35.9\fbinv$ of data collected in $\Pp\Pp$
collisions at $\sqrt{s}=13\TeV$. The cross section is first measured in a
fiducial region of particle-level phase space by defining two categories of
$\ttbar\bbbar$ events, and subsequently this result is corrected to the total
phase space. One of the defined fiducial regions corresponds to ignoring
parton-level information, while the other uses parton-level information to
identify the particle-level jets that do not originate from the decay of top
quarks. For both definitions, the cross section is measured to be $1.6\pm
0.1\stat^{+0.5}_{-0.4}\syst\unit{pb}$. The cross section in the total phase
space is obtained by correcting this measurement for the experimental
acceptance on the jets originating from the top quarks, which yields $5.5\pm
0.3\stat^{+1.6}_{-1.3}\syst\unit{pb}$. This measurement provides valuable
input to studies of the $\ttbar\PH$ process, where the Higgs boson decays into
a pair of quarks, and for which the normalization and modelling of the
$\ttbar\bbbar$ process represent a leading source of systematic uncertainty.
Furthermore, these results represent a stringent test of perturbative quantum
chromodynamics at the LHC. Predictions from several generators are compared
with measurements and found to be smaller than the measured values by a factor
of 1.5–2.4, corresponding to 1–2 standard deviations. This is consistent with
previous results for the $\ttbar\bbbar$ cross section and calls for further
experimental and theoretical studies of the associated production of top quark
pairs and jets.

###### 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, PUT and ERDF (Estonia); Academy
of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG,
and HGF (Germany); GSRT (Greece); NKFIA (Hungary); DAE and DST (India); IPM
(Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES
(Latvia); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT,
LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC
(Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom,
RAS, RFBR, and NRC KI (Russia); MESTD (Serbia); SEIDI, CPAN, PCTI, and FEDER
(Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST
(Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK
(Turkey); NASU 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 Nos. 675440,
752730, and 765710 (European Union); the Leventis Foundation; the A.P. Sloan
Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science
Policy Office; the Fonds pour la Formation à la Recherche dans l’Industrie et
dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door
Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium)
under the “Excellence of Science – EOS” – be.h project n. 30820817; the
Beijing Municipal Science & Technology Commission, No. Z181100004218003; 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, 125105, 128713, 128786,
and 129058 (Hungary); the Council of Science and Industrial Research, India;
the HOMING PLUS program of the Foundation for Polish Science, cofinanced from
European Union, Regional Development Fund, the Mobility Plus program of the
Ministry of Science and Higher Education, the National Science Center
(Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543,
2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406;
the National Priorities Research Program by Qatar National Research Fund; the
Ministry of Science and Education, grant no. 3.2989.2017 (Russia); the
Programa Estatal de Fomento de la Investigación Científica y Técnica de
Excelencia María de Maeztu, grant MDM-2015-0509 and the Programa Severo Ochoa
del Principado de Asturias; the Thalis and Aristeia programs cofinanced by EU-
ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral
Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its
2nd Century Project Advancement Project (Thailand); the Nvidia Corporation;
the Welch Foundation, contract C-1845; and the Weston Havens Foundation (USA).

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##  .10 The CMS Collaboration

Yerevan Physics Institute, Yerevan, Armenia
A.M. Sirunyan${}^{\textrm{\textdagger}}$, A. Tumasyan Institut für
Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, T. Bergauer, J. Brandstetter, M. Dragicevic, J. Erö, A.
Escalante Del Valle, M. Flechl, R. Frühwirth1, M. Jeitler1, N. Krammer, I.
Krätschmer, D. Liko, T. Madlener, I. Mikulec, N. Rad, J. Schieck1, R.
Schöfbeck, M. Spanring, D. Spitzbart, W. Waltenberger, C.-E. Wulz1, M. Zarucki
Institute for Nuclear Problems, Minsk, Belarus
V. Drugakov, V. Mossolov, J. Suarez Gonzalez Universiteit Antwerpen,
Antwerpen, Belgium
M.R. Darwish, E.A. De Wolf, D. Di Croce, X. Janssen, A. Lelek, M. Pieters, H.
Rejeb Sfar, H. Van Haevermaet, P. Van Mechelen, S. Van Putte, N. Van Remortel
Vrije Universiteit Brussel, Brussel, Belgium
F. Blekman, E.S. Bols, S.S. Chhibra, J. D’Hondt, J. De Clercq, D. Lontkovskyi,
S. Lowette, I. Marchesini, S. Moortgat, Q. Python, K. Skovpen, S. Tavernier,
W. Van Doninck, P. Van Mulders Université Libre de Bruxelles, Bruxelles,
Belgium
D. Beghin, B. Bilin, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, B.
Dorney, L. Favart, A. Grebenyuk, A.K. Kalsi, A. Popov, N. Postiau, E.
Starling, L. Thomas, C. Vander Velde, P. Vanlaer, D. Vannerom Ghent
University, Ghent, Belgium
T. Cornelis, D. Dobur, I. Khvastunov2, M. Niedziela, C. Roskas, D. Trocino, M.
Tytgat, W. Verbeke, B. Vermassen, M. Vit, N. Zaganidis Université Catholique
de Louvain, Louvain-la-Neuve, Belgium
O. Bondu, G. Bruno, C. Caputo, P. David, C. Delaere, M. Delcourt, A.
Giammanco, V. Lemaitre, A. Magitteri, J. Prisciandaro, A. Saggio, M. Vidal
Marono, P. Vischia, J. Zobec Centro Brasileiro de Pesquisas Fisicas, Rio de
Janeiro, Brazil
F.L. Alves, G.A. Alves, G. Correia Silva, C. Hensel, A. Moraes, 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, L.M. Huertas Guativa, H. Malbouisson, J. Martins5, D. Matos
Figueiredo, M. Medina Jaime6, 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
C.A. Bernardesa, L. Calligarisa, T.R. Fernandez Perez Tomeia, E.M. Gregoresb,
D.S. Lemos, P.G. Mercadanteb, S.F. Novaesa, SandraS. Padulaa Institute for
Nuclear Research and Nuclear Energy, Bulgarian Academy of Sciences, Sofia,
Bulgaria
A. Aleksandrov, G. Antchev, R. Hadjiiska, P. Iaydjiev, M. Misheva, M. Rodozov,
M. Shopova, G. Sultanov University of Sofia, Sofia, Bulgaria
M. Bonchev, A. Dimitrov, T. Ivanov, L. Litov, B. Pavlov, P. Petkov Beihang
University, Beijing, China
W. Fang7, X. Gao7, L. Yuan Institute of High Energy Physics, Beijing, China
M. Ahmad, G.M. Chen, H.S. Chen, M. Chen, C.H. Jiang, D. Leggat, H. Liao, Z.
Liu, S.M. Shaheen8, A. Spiezia, J. Tao, E. Yazgan, H. Zhang, S. Zhang8, J.
Zhao State Key Laboratory of Nuclear Physics and Technology, Peking
University, Beijing, China
A. Agapitos, Y. Ban, G. Chen, A. Levin, J. Li, L. Li, Q. Li, Y. Mao, S.J.
Qian, D. Wang, Q. Wang Tsinghua University, Beijing, China
Z. Hu, Y. Wang Zhejiang University, Hangzhou, China
M. Xiao Universidad de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, C. Florez, C.F. González Hernández, M.A. Segura Delgado
Universidad de Antioquia, Medellin, Colombia
J. Mejia Guisao, J.D. Ruiz Alvarez, C.A. Salazar González, N. Vanegas Arbelaez
University of Split, Faculty of Electrical Engineering, Mechanical Engineering
and Naval Architecture, Split, Croatia
D. Giljanović, 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, S. Ceci, D. Ferencek, K. Kadija, B. Mesic, M. Roguljic, A.
Starodumov9, T. Susa University of Cyprus, Nicosia, Cyprus
M.W. Ather, A. Attikis, E. Erodotou, A. Ioannou, M. Kolosova, S. Konstantinou,
G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H.
Rykaczewski, D. Tsiakkouri Charles University, Prague, Czech Republic
M. Finger10, M. Finger Jr.10, A. Kveton, J. Tomsa Escuela Politecnica
Nacional, Quito, Ecuador
E. Ayala Universidad San Francisco de Quito, Quito, Ecuador
E. Carrera Jarrin Academy of Scientific Research and Technology of the Arab
Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt
H. Abdalla11, E. Salama12,13 National Institute of Chemical Physics and
Biophysics, Tallinn, Estonia
S. Bhowmik, A. Carvalho Antunes De Oliveira, R.K. Dewanjee, K. Ehataht, M.
Kadastik, M. Raidal, C. Veelken Department of Physics, University of Helsinki,
Helsinki, Finland
P. Eerola, L. Forthomme, H. Kirschenmann, K. Osterberg, M. Voutilainen
Helsinki Institute of Physics, Helsinki, Finland
F. Garcia, J. Havukainen, J.K. Heikkilä, T. Järvinen, V. Karimäki, M.S. Kim,
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, B. Fabbro, J.L. Faure, F.
Ferri, S. Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry,
C. Leloup, E. Locci, J. Malcles, J. Rander, A. Rosowsky, M.Ö. Sahin, A. Savoy-
Navarro14, M. Titov Laboratoire Leprince-Ringuet, CNRS/IN2P3, Ecole
Polytechnique, Institut Polytechnique de Paris
S. Ahuja, C. Amendola, F. Beaudette, P. Busson, C. Charlot, B. Diab, G.
Falmagne, R. Granier de Cassagnac, I. Kucher, A. Lobanov, C. Martin Perez, M.
Nguyen, C. Ochando, P. Paganini, J. Rembser, R. Salerno, J.B. Sauvan, Y.
Sirois, A. Zabi, A. Zghiche Université de Strasbourg, CNRS, IPHC UMR 7178,
Strasbourg, France
J.-L. Agram15, J. Andrea, D. Bloch, G. Bourgatte, J.-M. Brom, E.C. Chabert, C.
Collard, E. Conte15, J.-C. Fontaine15, 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, C. Camen, A. Carle, N. Chanon, R.
Chierici, D. Contardo, P. Depasse, H. El Mamouni, J. Fay, S. Gascon, M.
Gouzevitch, B. Ille, Sa. Jain, F. Lagarde, I.B. Laktineh, H. Lattaud, A.
Lesauvage, M. Lethuillier, L. Mirabito, S. Perries, V. Sordini, L. Torterotot,
G. Touquet, M. Vander Donckt, S. Viret Georgian Technical University, Tbilisi,
Georgia
G. Adamov Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze10 RWTH Aachen University, I. Physikalisches Institut, Aachen,
Germany
C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, D. Meuser, A.
Pauls, M. Preuten, M.P. Rauch, C. Schomakers, J. Schulz, M. Teroerde, B.
Wittmer RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
A. Albert, M. Erdmann, B. Fischer, S. Ghosh, T. Hebbeker, K. Hoepfner, H.
Keller, L. Mastrolorenzo, M. Merschmeyer, A. Meyer, P. Millet, G. Mocellin, S.
Mondal, S. Mukherjee, D. Noll, A. Novak, T. Pook, A. Pozdnyakov, T. Quast, M.
Radziej, Y. Rath, H. Reithler, M. Rieger, J. Roemer, A. Schmidt, S.C. Schuler,
A. Sharma, S. Wiedenbeck, S. Zaleski RWTH Aachen University, III.
Physikalisches Institut B, Aachen, Germany
G. Flügge, W. Haj Ahmad16, O. Hlushchenko, T. Kress, T. Müller, A. Nehrkorn,
A. Nowack, C. Pistone, O. Pooth, D. Roy, H. Sert, A. Stahl17 Deutsches
Elektronen-Synchrotron, Hamburg, Germany
M. Aldaya Martin, P. Asmuss, I. Babounikau, H. Bakhshiansohi, K. Beernaert, O.
Behnke, A. Bermúdez Martínez, D. Bertsche, A.A. Bin Anuar, K. Borras18, V.
Botta, A. Campbell, A. Cardini, P. Connor, S. Consuegra Rodríguez, C.
Contreras-Campana, V. Danilov, A. De Wit, M.M. Defranchis, C. Diez Pardos, D.
Domínguez Damiani, G. Eckerlin, D. Eckstein, T. Eichhorn, A. Elwood, E. Eren,
E. Gallo19, A. Geiser, A. Grohsjean, M. Guthoff, M. Haranko, A. Harb, A.
Jafari, N.Z. Jomhari, H. Jung, A. Kasem18, M. Kasemann, H. Kaveh, J. Keaveney,
C. Kleinwort, J. Knolle, D. Krücker, W. Lange, T. Lenz, J. Leonard, J.
Lidrych, K. Lipka, W. Lohmann20, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer,
M. Meyer, M. Missiroli, G. Mittag, J. Mnich, A. Mussgiller, V. Myronenko, D.
Pérez Adán, S.K. Pflitsch, D. Pitzl, A. Raspereza, A. Saibel, M. Savitskyi, V.
Scheurer, P. Schütze, C. Schwanenberger, R. Shevchenko, A. Singh, H. Tholen,
O. Turkot, A. Vagnerini, M. Van De Klundert, G.P. Van Onsem, R. Walsh, Y. Wen,
K. Wichmann, C. Wissing, O. Zenaiev, R. Zlebcik University of Hamburg,
Hamburg, Germany
R. Aggleton, S. Bein, L. Benato, A. Benecke, V. Blobel, T. Dreyer, A.
Ebrahimi, F. Feindt, A. Fröhlich, C. Garbers, 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, T. Lange, A. Malara, J.
Multhaup, C.E.N. Niemeyer, 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, B. Vormwald, I. Zoi Karlsruher Institut fuer
Technologie, Karlsruhe, Germany
M. Akbiyik, C. Barth, M. Baselga, S. Baur, T. Berger, E. Butz, R. Caspart, T.
Chwalek, W. De Boer, A. Dierlamm, K. El Morabit, N. Faltermann, M. Giffels, P.
Goldenzweig, A. Gottmann, M.A. Harrendorf, F. Hartmann17, U. Husemann, S.
Kudella, S. Mitra, M.U. Mozer, D. Müller, Th. Müller, M. Musich, A. Nürnberg,
G. Quast, K. Rabbertz, M. Schröder, I. Shvetsov, H.J. Simonis, R. Ulrich, M.
Wassmer, M. Weber, C. Wöhrmann, R. Wolf Institute of Nuclear and Particle
Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece
G. Anagnostou, P. Asenov, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas,
G. Paspalaki National and Kapodistrian University of Athens, Athens, Greece
M. Diamantopoulou, G. Karathanasis, P. Kontaxakis, A. Manousakis-katsikakis,
A. Panagiotou, I. Papavergou, N. Saoulidou, A. Stakia, K. Theofilatos, K.
Vellidis, E. Vourliotis National Technical University of Athens, Athens,
Greece
G. Bakas, K. Kousouris, I. Papakrivopoulos, G. Tsipolitis University of
Ioánnina, Ioánnina, Greece
I. Evangelou, C. Foudas, P. Gianneios, P. Katsoulis, P. Kokkas, S. Mallios, K.
Manitara, N. Manthos, I. Papadopoulos, J. Strologas, F.A. Triantis, D.
Tsitsonis MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
M. Bartók21, R. Chudasama, M. Csanad, P. Major, K. Mandal, A. Mehta, M.I.
Nagy, G. Pasztor, O. Surányi, G.I. Veres Wigner Research Centre for Physics,
Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath22, F. Sikler, T.Á. Vámi, V. Veszpremi, G.
Vesztergombi${}^{\textrm{\textdagger}}$ Institute of Nuclear Research ATOMKI,
Debrecen, Hungary
N. Beni, S. Czellar, J. Karancsi21, A. Makovec, J. Molnar, Z. Szillasi
Institute of Physics, University of Debrecen, Debrecen, Hungary
P. Raics, D. Teyssier, Z.L. Trocsanyi, B. Ujvari Eszterhazy Karoly University,
Karoly Robert Campus, Gyongyos, Hungary
T. Csorgo, W.J. Metzger, F. Nemes, T. Novak 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. Bahinipati24, C. Kar, G. Kole, P. Mal, V.K. Muraleedharan Nair Bindhu, A.
Nayak25, D.K. Sahoo24, 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, M. Meena, 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. Bhardwaj26, M. Bharti26, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep26,
D. Bhowmik, S. Dutta, S. Ghosh, M. Maity27, K. Mondal, S. Nandan, A. Purohit,
P.K. Rout, G. Saha, S. Sarkar, T. Sarkar27, M. Sharan, B. Singh26, S. Thakur26
Indian Institute of Technology Madras, Madras, India
P.K. Behera, P. Kalbhor, A. Muhammad, P.R. Pujahari, A. Sharma, A.K. Sikdar
Bhabha Atomic Research Centre, Mumbai, India
D. Dutta, V. Jha, V. Kumar, D.K. Mishra, 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, RavindraKumar Verma Tata
Institute of Fundamental Research-B, Mumbai, India
S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, S. Karmakar,
S. Kumar, G. Majumder, K. Mazumdar, N. Sahoo, S. Sawant Indian Institute of
Science Education and Research (IISER), Pune, India
S. Chauhan, S. Dube, V. Hegde, B. Kansal, A. Kapoor, K. Kothekar, S. Pandey,
A. Rane, A. Rastogi, S. Sharma Institute for Research in Fundamental Sciences
(IPM), Tehran, Iran
S. Chenarani28, E. Eskandari Tadavani, S.M. Etesami28, M. Khakzad, M.
Mohammadi Najafabadi, M. Naseri, F. Rezaei Hosseinabadi University College
Dublin, Dublin, Ireland
M. Felcini, M. Grunewald INFN Sezione di Bari a, Università di Bari b,
Politecnico di Bari c, Bari, Italy
M. Abbresciaa,b, R. Alya,b,29, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L.
Cristellaa,b, N. De Filippisa,c, M. De Palmaa,b, A. Di Florioa,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, L. Silvestrisa, R. Vendittia, P.
Verwilligena INFN Sezione di Bologna a, Università di Bologna b, Bologna,
Italy
G. Abbiendia, C. Battilanaa,b, D. Bonacorsia,b, L. Borgonovia,b, S. Braibant-
Giacomellia,b, R. Campaninia,b, P. Capiluppia,b, A. Castroa,b, F.R. Cavalloa,
C. Cioccaa, G. Codispotia,b, M. Cuffiania,b, G.M. Dallavallea, F. Fabbria, A.
Fanfania,b, E. Fontanesia,b, P. Giacomellia, C. Grandia, L. Guiduccia,b, F.
Iemmia,b, S. Lo Meoa,30, S. Marcellinia, G. Masettia, F.L. Navarriaa,b, A.
Perrottaa, F. Primaveraa,b, A.M. Rossia,b, T. Rovellia,b, G.P. Sirolia,b, N.
Tosia INFN Sezione di Catania a, Università di Catania b, Catania, Italy
S. Albergoa,b,31, S. Costaa,b, A. Di Mattiaa, R. Potenzaa,b, A. Tricomia,b,31,
C. Tuvea,b INFN Sezione di Firenze a, Università di Firenze b, Firenze, Italy
G. Barbaglia, A. Cassese, R. Ceccarelli, K. Chatterjeea,b, V. Ciullia,b, C.
Civininia, R. D’Alessandroa,b, E. Focardia,b, G. Latinoa,b, P. Lenzia,b, M.
Meschinia, S. Paolettia, G. Sguazzonia, L. Viliania INFN Laboratori Nazionali
di Frascati, Frascati, Italy
L. Benussi, S. Bianco, D. Piccolo INFN Sezione di Genova a, Università di
Genova b, Genova, Italy
M. Bozzoa,b, F. Ferroa, R. Mulargiaa,b, E. Robuttia, S. Tosia,b INFN Sezione
di Milano-Bicocca a, Università di Milano-Bicocca b, Milano, Italy
A. Benagliaa, A. Beschia,b, F. Brivioa,b, V. Cirioloa,b,17, S. Di Guidaa,b,17,
M.E. Dinardoa,b, P. Dinia, S. Gennaia, A. Ghezzia,b, P. Govonia,b, L.
Guzzia,b, M. Malbertia, S. Malvezzia, D. Menascea, F. Montia,b, L. Moronia, G.
Ortonaa,b, 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, L. Listaa,b, S.
Meolaa,d,17, P. Paoluccia,17, B. Rossia, C. Sciaccaa,b, E. Voevodinaa,b INFN
Sezione di Padova a, Università di Padova b, Padova, Italy, Università di
Trento c, Trento, Italy
P. Azzia, N. Bacchettaa, D. Biselloa,b, A. Bolettia,b, A. Bragagnoloa,b, R.
Carlina,b, P. Checchiaa, P. De Castro Manzanoa, T. Dorigoa, U. Dossellia, F.
Gasparinia,b, U. Gasparinia,b, A. Gozzelinoa, S.Y. Hoha,b, P. Lujana, M.
Margonia,b, A.T. Meneguzzoa,b, J. Pazzinia,b, M. Presillab, P. Ronchesea,b, R.
Rossina,b, F. Simonettoa,b, A. Tikoa, 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, D. Fiorinaa,b, 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, D. Ciangottinia,b, L. Fanòa,b, P. Laricciaa,b, R.
Leonardia,b, 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, V. Bertacchia,c, L. Bianchinia, T.
Boccalia, R. Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, G. Fedia, 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. Rolandi32, S. Roy
Chowdhury, A. Scribanoa, P. Spagnoloa, R. Tenchinia, G. Tonellia,b, N. Turini,
A. Venturia, P.G. Verdinia INFN Sezione di Roma a, Sapienza Università di Roma
b, Rome, Italy
F. Cavallaria, M. Cipriania,b, D. Del Rea,b, E. Di Marcoa,b, M. Diemoza, E.
Longoa,b, B. Marzocchia,b, P. Meridiania, G. Organtinia,b, F. Pandolfia, R.
Paramattia,b, C. Quarantaa,b, S. Rahatloua,b, C. Rovellia, F.
Santanastasioa,b, L. Soffia,b INFN Sezione di Torino a, Università di Torino
b, Torino, Italy, Università del Piemonte Orientale c, Novara, Italy
N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, N. Bartosika,
R. Bellana,b, A. Bellora, C. Biinoa, A. Cappatia,b, N. Cartigliaa, 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. Salvaticoa,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
B. Kim, D.H. Kim, G.N. Kim, J. 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, T.J. Kim, J. Park Korea University, Seoul, Korea
S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, K. Lee, K.S. Lee, J. Lim, J.
Park, S.K. Park, Y. Roh, J. Yoo Kyung Hee University, Department of Physics
J. Goh Sejong University, Seoul, Korea
H.S. Kim Seoul National University, Seoul, Korea
J. Almond, J.H. Bhyun, J. Choi, S. Jeon, J. Kim, J.S. Kim, H. Lee, K. Lee, S.
Lee, K. Nam, M. Oh, S.B. Oh, B.C. Radburn-Smith, U.K. Yang, H.D. Yoo, I. Yoon,
G.B. Yu University of Seoul, Seoul, Korea
D. Jeon, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park, I.J Watson Sungkyunkwan
University, Suwon, Korea
Y. Choi, C. Hwang, Y. Jeong, J. Lee, Y. Lee, I. Yu Riga Technical University,
Riga, Latvia
V. Veckalns33 Vilnius University, Vilnius, Lithuania
V. Dudenas, A. Juodagalvis, G. Tamulaitis, J. Vaitkus National Centre for
Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia
Z.A. Ibrahim, F. Mohamad Idris34, W.A.T. Wan Abdullah, M.N. Yusli, Z. Zolkapli
Universidad de Sonora (UNISON), Hermosillo, Mexico
J.F. Benitez, A. Castaneda Hernandez, J.A. Murillo Quijada, L. Valencia Palomo
Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico
H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz35, R. Lopez-
Fernandez, A. Sanchez-Hernandez Universidad Iberoamericana, Mexico City,
Mexico
S. Carrillo Moreno, C. Oropeza Barrera, M. Ramirez-Garcia, F. Vazquez Valencia
Benemerita Universidad Autonoma de Puebla, Puebla, Mexico
J. Eysermans, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad
Autónoma de San Luis Potosí, San Luis Potosí, Mexico
A. Morelos Pineda University of Montenegro, Podgorica, Montenegro
J. Mijuskovic, N. Raicevic University of Auckland, Auckland, New Zealand
D. Krofcheck University of Canterbury, Christchurch, New Zealand
S. Bheesette, P.H. Butler National Centre for Physics, Quaid-I-Azam
University, Islamabad, Pakistan
A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, W.A. Khan, M.A. Shah, M. Shoaib,
M. Waqas AGH University of Science and Technology Faculty of Computer Science,
Electronics and Telecommunications, Krakow, Poland
V. Avati, L. Grzanka, M. Malawski National Centre for Nuclear Research,
Swierk, Poland
H. Bialkowska, M. Bluj, B. Boimska, M. Górski, M. Kazana, M. Szleper, P.
Zalewski Institute of Experimental Physics, Faculty of Physics, University of
Warsaw, Warsaw, Poland
K. Bunkowski, A. Byszuk36, K. Doroba, A. Kalinowski, M. Konecki, J.
Krolikowski, M. Misiura, M. Olszewski, M. Walczak Laboratório de
Instrumentação e Física Experimental de Partículas, Lisboa, Portugal
M. Araujo, P. Bargassa, D. Bastos, A. Di Francesco, P. Faccioli, B. Galinhas,
M. Gallinaro, J. Hollar, N. Leonardo, J. Seixas, K. Shchelina, G. Strong, O.
Toldaiev, J. Varela Joint Institute for Nuclear Research, Dubna, Russia
V. Alexakhin, P. Bunin, Y. Ershov, I. Golutvin, A. Kamenev, V. Karjavine, I.
Kashunin, G. Kozlov, A. Lanev, A. Malakhov, V. Matveev37,38, V.V. Mitsyn, P.
Moisenz, V. Palichik, V. Perelygin, S. Shmatov, O. Teryaev, N. Voytishin, B.S.
Yuldashev39, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St.
Petersburg), Russia
L. Chtchipounov, V. Golovtcov, Y. Ivanov, V. Kim40, E. Kuznetsova41, P.
Levchenko, V. Murzin, V. Oreshkin, I. Smirnov, D. Sosnov, V. Sulimov, L.
Uvarov, 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 named by A.I. Alikhanov of NRC ‘Kurchatov Institute’,
Moscow, Russia
V. Epshteyn, V. Gavrilov, N. Lychkovskaya, A. Nikitenko42, V. Popov, I.
Pozdnyakov, G. Safronov, A. Spiridonov, A. Stepennov, M. Toms, E. Vlasov, A.
Zhokin Moscow Institute of Physics and Technology, Moscow, Russia
T. Aushev National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
O. Bychkova, R. Chistov43, M. Danilov43, S. Polikarpov43, E. Tarkovskii P.N.
Lebedev Physical Institute, Moscow, Russia
V. Andreev, M. Azarkin, I. Dremin, M. Kirakosyan, A. Terkulov Skobeltsyn
Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow,
Russia
A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin44, L. Dudko, V.
Klyukhin, N. Korneeva, I. Lokhtin, S. Obraztsov, M. Perfilov, V. Savrin, P.
Volkov Novosibirsk State University (NSU), Novosibirsk, Russia
A. Barnyakov45, V. Blinov45, T. Dimova45, L. Kardapoltsev45, Y. Skovpen45
Institute for High Energy Physics of National Research Centre ‘Kurchatov
Institute’, Protvino, Russia
I. Azhgirey, I. Bayshev, S. Bitioukov, V. Kachanov, 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, A. Iuzhakov, V. Okhotnikov Tomsk State University, Tomsk, Russia
V. Borchsh, V. Ivanchenko, E. Tcherniaev University of Belgrade: Faculty of
Physics and VINCA Institute of Nuclear Sciences
P. Adzic46, P. Cirkovic, D. Devetak, M. Dordevic, P. Milenovic, J. Milosevic,
M. Stojanovic Centro de Investigaciones Energéticas Medioambientales y
Tecnológicas (CIEMAT), Madrid, Spain
M. Aguilar-Benitez, J. Alcaraz Maestre, A. Álvarez Fernández, I. Bachiller, M.
Barrio Luna, J.A. Brochero Cifuentes, C.A. Carrillo Montoya, M. Cepeda, 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, Á. Navarro Tobar, A. Pérez-Calero Yzquierdo,
J. Puerta Pelayo, I. Redondo, L. Romero, S. Sánchez Navas, M.S. Soares, A.
Triossi, C. Willmott Universidad Autónoma de Madrid, Madrid, Spain
C. Albajar, J.F. de Trocóniz, R. Reyes-Almanza Universidad de Oviedo,
Instituto Universitario de Ciencias y Tecnologías Espaciales de Asturias
(ICTEA), Oviedo, Spain
B. Alvarez Gonzalez, J. Cuevas, C. Erice, J. Fernandez Menendez, S. Folgueras,
I. Gonzalez Caballero, J.R. González Fernández, E. Palencia Cortezon, V.
Rodríguez Bouza, S. Sanchez Cruz 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, G. Gomez, C. Martinez
Rivero, P. Martinez Ruiz del Arbol, F. Matorras, J. Piedra Gomez, C. Prieels,
T. Rodrigo, A. Ruiz-Jimeno, L. Russo47, L. Scodellaro, N. Trevisani, I. Vila,
J.M. Vizan Garcia University of Colombo, Colombo, Sri Lanka
K. Malagalage University of Ruhuna, Department of Physics, Matara, Sri Lanka
W.G.D. Dharmaratna, N. Wickramage CERN, European Organization for Nuclear
Research, Geneva, Switzerland
D. Abbaneo, B. Akgun, E. Auffray, G. Auzinger, J. Baechler, P. Baillon, A.H.
Ball, D. Barney, J. Bendavid, M. Bianco, A. Bocci, P. Bortignon, E. Bossini,
C. Botta, E. Brondolin, T. Camporesi, A. Caratelli, G. Cerminara, E. Chapon,
G. Cucciati, D. d’Enterria, A. Dabrowski, N. Daci, V. Daponte, A. David, O.
Davignon, A. De Roeck, N. Deelen, M. Deile, M. Dobson, M. Dünser, N. Dupont,
A. Elliott-Peisert, N. Emriskova, F. Fallavollita48, D. Fasanella, S.
Fiorendi, G. Franzoni, J. Fulcher, W. Funk, S. Giani, D. Gigi, A. Gilbert, K.
Gill, F. Glege, M. Gruchala, M. Guilbaud, D. Gulhan, J. Hegeman, C. Heidegger,
Y. Iiyama, V. Innocente, P. Janot, O. Karacheban20, J. Kaspar, J. Kieseler, M.
Krammer1, N. Kratochwil, C. Lange, P. Lecoq, C. Lourenço, L. Malgeri, M.
Mannelli, A. Massironi, F. Meijers, J.A. Merlin, S. Mersi, E. Meschi, F.
Moortgat, M. Mulders, J. Ngadiuba, J. Niedziela, S. Nourbakhsh, S. Orfanelli,
L. Orsini, F. Pantaleo17, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G.
Petrucciani, A. Pfeiffer, M. Pierini, F.M. Pitters, D. Rabady, A. Racz, M.
Rovere, H. Sakulin, C. Schäfer, C. Schwick, M. Selvaggi, A. Sharma, P. Silva,
W. Snoeys, P. Sphicas49, J. Steggemann, S. Summers, V.R. Tavolaro, D. Treille,
A. Tsirou, A. Vartak, M. Verzetti, W.D. Zeuner Paul Scherrer Institut,
Villigen, Switzerland
L. Caminada50, 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, 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, F. Pauss, G. Perrin, L. Perrozzi, S. Pigazzini,
M.G. Ratti, M. Reichmann, C. Reissel, T. Reitenspiess, D. Ruini, D.A. Sanz
Becerra, M. Schönenberger, L. Shchutska, M.L. Vesterbacka Olsson, R. Wallny,
D.H. Zhu Universität Zürich, Zurich, Switzerland
T.K. Aarrestad, C. Amsler51, D. Brzhechko, M.F. Canelli, A. De Cosa, R. Del
Burgo, S. Donato, B. Kilminster, S. Leontsinis, V.M. Mikuni, I. Neutelings, G.
Rauco, P. Robmann, D. Salerno, K. Schweiger, C. Seitz, Y. Takahashi, S. Wertz,
A. Zucchetta National Central University, Chung-Li, Taiwan
T.H. Doan, C.M. Kuo, W. Lin, A. Roy, S.S. Yu National Taiwan University (NTU),
Taipei, Taiwan
P. Chang, Y. Chao, K.F. Chen, P.H. Chen, W.-S. Hou, Y.y. Li, R.-S. Lu, E.
Paganis, A. Psallidas, A. Steen Chulalongkorn University, Faculty of Science,
Department of Physics, Bangkok, Thailand
B. Asavapibhop, C. Asawatangtrakuldee, N. Srimanobhas, N. Suwonjandee Çukurova
University, Physics Department, Science and Art Faculty, Adana, Turkey
A. Bat, F. Boran, A. Celik52, S. Damarseckin53, Z.S. Demiroglu, F. Dolek, C.
Dozen, I. Dumanoglu, E. Eskut, G. Gokbulut, EmineGurpinar Guler54, Y. Guler,
I. Hos55, C. Isik, E.E. Kangal56, O. Kara, A. Kayis Topaksu, U. Kiminsu, M.
Oglakci, G. Onengut, K. Ozdemir57, S. Ozturk58, A.E. Simsek, D. Sunar Cerci59,
U.G. Tok, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical
University, Physics Department, Ankara, Turkey
B. Isildak60, G. Karapinar61, M. Yalvac Bogazici University, Istanbul, Turkey
I.O. Atakisi, E. Gülmez, M. Kaya62, O. Kaya63, Ö. Özçelik, S. Tekten, E.A.
Yetkin64 Istanbul Technical University, Istanbul, Turkey
A. Cakir, K. Cankocak, Y. Komurcu, S. Sen65 Istanbul University, Istanbul,
Turkey
B. Kaynak, S. Ozkorucuklu 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, E. Bhal, S. Bologna, J.J. Brooke, D. Burns66, E. Clement, D. Cussans,
H. Flacher, J. Goldstein, G.P. Heath, H.F. Heath, L. Kreczko, S. Paramesvaran,
B. Penning, T. Sakuma, S. Seif El Nasr-Storey, V.J. Smith, J. Taylor, A.
Titterton Rutherford Appleton Laboratory, Didcot, United Kingdom
K.W. Bell, A. Belyaev67, C. Brew, R.M. Brown, D. Cieri, D.J.A. Cockerill, J.A.
Coughlan, K. Harder, S. Harper, J. Linacre, K. Manolopoulos, D.M. Newbold, E.
Olaiya, D. Petyt, T. Reis, T. Schuh, C.H. Shepherd-Themistocleous, A. Thea,
I.R. Tomalin, T. Williams, W.J. Womersley Imperial College, London, United
Kingdom
R. Bainbridge, P. Bloch, J. Borg, S. Breeze, O. Buchmuller, A. Bundock,
GurpreetSingh CHAHAL68, D. Colling, P. Dauncey, G. Davies, M. Della Negra, R.
Di Maria, P. Everaerts, G. Hall, G. Iles, T. James, M. Komm, C. Laner, L.
Lyons, A.-M. Magnan, S. Malik, A. Martelli, V. Milosevic, J. Nash69, V.
Palladino, M. Pesaresi, D.M. Raymond, A. Richards, A. Rose, E. Scott, C. Seez,
A. Shtipliyski, M. Stoye, T. Strebler, A. Tapper, K. Uchida, T. Virdee17, N.
Wardle, D. Winterbottom, J. Wright, A.G. Zecchinelli, 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, B. Caraway, J. Dittmann, K. Hatakeyama, C. Madrid, B. McMaster, N.
Pastika, C. Smith Catholic University of America, Washington, DC, USA
R. Bartek, A. Dominguez, R. Uniyal, A.M. Vargas Hernandez The University of
Alabama, Tuscaloosa, USA
A. Buccilli, S.I. Cooper, C. Henderson, P. Rumerio, C. West Boston University,
Boston, USA
D. Arcaro, Z. Demiragli, D. Gastler, S. Girgis, D. Pinna, C. Richardson, J.
Rohlf, D. Sperka, I. Suarez, L. Sulak, D. Zou Brown University, Providence,
USA
G. Benelli, B. Burkle, X. Coubez18, D. Cutts, Y.t. Duh, M. Hadley, J. Hakala,
U. Heintz, J.M. Hogan70, K.H.M. Kwok, E. Laird, G. Landsberg, J. Lee, Z. Mao,
M. Narain, S. Sagir71, R. Syarif, E. Usai, D. Yu, W. Zhang University of
California, Davis, Davis, USA
R. Band, C. Brainerd, R. Breedon, M. Calderon De La Barca Sanchez, M. Chertok,
J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, F. Jensen, W.
Ko, O. Kukral, R. Lander, M. Mulhearn, D. Pellett, J. Pilot, M. Shi, 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, W.A. Nash, S. Regnard, D. Saltzberg, C. Schnaible, B.
Stone, V. Valuev University of California, Riverside, Riverside, USA
K. Burt, Y. Chen, R. Clare, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, G.
Karapostoli, E. Kennedy, O.R. Long, M. Olmedo Negrete, M.I. Paneva, W. Si, L.
Wang, S. Wimpenny, B.R. Yates, Y. Zhang University of California, San Diego,
La Jolla, USA
J.G. Branson, P. Chang, S. Cittolin, M. Derdzinski, R. Gerosa, D. Gilbert, B.
Hashemi, D. Klein, V. Krutelyov, J. Letts, M. Masciovecchio, S. May, S. Padhi,
M. Pieri, V. Sharma, M. Tadel, 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, J. Incandela, B. Marsh, H. Mei, A. Ovcharova, H. Qu, J. Richman,
U. Sarica, D. Stuart, S. Wang California Institute of Technology, Pasadena,
USA
D. Anderson, A. Bornheim, O. Cerri, I. Dutta, J.M. Lawhorn, N. Lu, J. Mao,
H.B. Newman, T.Q. Nguyen, J. Pata, M. Spiropulu, J.R. Vlimant, S. Xie, Z.
Zhang, R.Y. Zhu Carnegie Mellon University, Pittsburgh, USA
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, 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, A. Frankenthal, K.
Mcdermott, J.R. Patterson, D. Quach, A. Rinkevicius72, A. Ryd, S.M. Tan, Z.
Tao, J. Thom, P. Wittich, M. Zientek Fermi National Accelerator Laboratory,
Batavia, USA
S. Abdullin, M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, A. Apyan, S.
Banerjee, L.A.T. Bauerdick, A. Beretvas, 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, AllisonReinsvold Hall, J. Hanlon, R.M.
Harris, S. Hasegawa, R. Heller, J. Hirschauer, B. Jayatilaka, S. Jindariani,
M. Johnson, U. Joshi, B. Klima, M.J. Kortelainen, B. Kreis, S. Lammel, J.
Lewis, 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, V.
Papadimitriou, K. Pedro, C. Pena, G. Rakness, F. Ravera, L. Ristori, B.
Schneider, E. Sexton-Kennedy, N. Smith, 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, R. Vidal, M. Wang, H.A. Weber University of
Florida, Gainesville, USA
D. Acosta, P. Avery, D. Bourilkov, A. Brinkerhoff, L. Cadamuro, A. Carnes, V.
Cherepanov, D. Curry, F. Errico, R.D. Field, S.V. Gleyzer, B.M. Joshi, M. Kim,
J. Konigsberg, A. Korytov, K.H. Lo, P. Ma, K. Matchev, N. Menendez, G.
Mitselmakher, D. Rosenzweig, K. Shi, J. Wang, S. Wang, X. Zuo Florida
International University, Miami, USA
Y.R. Joshi Florida State University, Tallahassee, USA
T. Adams, A. Askew, S. Hagopian, V. Hagopian, K.F. Johnson, R. Khurana, T.
Kolberg, G. Martinez, T. Perry, H. Prosper, C. Schiber, R. Yohay, J. Zhang
Florida Institute of Technology, Melbourne, USA
M.M. Baarmand, M. Hohlmann, D. Noonan, M. Rahmani, M. Saunders, 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, C.
Mills, T. Roy, M.B. Tonjes, N. Varelas, J. Viinikainen, H. Wang, X. Wang, Z.
Wu The University of Iowa, Iowa City, USA
M. Alhusseini, B. Bilki54, W. Clarida, K. Dilsiz73, S. Durgut, R.P.
Gandrajula, M. Haytmyradov, V. Khristenko, O.K. Köseyan, J.-P. Merlo, A.
Mestvirishvili74, A. Moeller, J. Nachtman, H. Ogul75, Y. Onel, F. Ozok76, 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, M. Swartz The University of Kansas,
Lawrence, USA
C. Baldenegro Barrera, P. Baringer, A. Bean, S. Boren, J. Bowen, A. Bylinkin,
T. Isidori, S. Khalil, J. King, G. Krintiras, A. Kropivnitskaya, C. Lindsey,
D. Majumder, W. Mcbrayer, N. Minafra, M. Murray, C. Rogan, C. Royon, S.
Sanders, E. Schmitz, J.D. Tapia Takaki, Q. Wang, J. Williams, G. Wilson Kansas
State University, Manhattan, USA
S. Duric, A. Ivanov, K. Kaadze, D. Kim, Y. Maravin, D.R. Mendis, T. Mitchell,
A. Modak, A. Mohammadi 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, N.J. Hadley, S. Jabeen,
G.Y. Jeng, R.G. Kellogg, J. Kunkle, A.C. Mignerey, S. Nabili, F. Ricci-Tam, M.
Seidel, Y.H. Shin, A. Skuja, S.C. Tonwar, K. Wong Massachusetts Institute of
Technology, Cambridge, USA
D. Abercrombie, B. Allen, A. Baty, R. Bi, S. Brandt, W. Busza, I.A. Cali, M.
D’Alfonso, G. Gomez Ceballos, M. Goncharov, P. Harris, D. Hsu, M. Hu, 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, D. Rankin, 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, S. Guts,
P. Hansen, J. Hiltbrand, Y. Kubota, Z. Lesko, J. Mans, R. Rusack, M.A. Wadud
University of Mississippi, Oxford, USA
J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA
K. Bloom, D.R. Claes, C. Fangmeier, L. Finco, F. Golf, R. Gonzalez Suarez, R.
Kamalieddin, I. Kravchenko, J.E. Siado, G.R. Snow${}^{\textrm{\textdagger}}$,
B. Stieger, W. Tabb State University of New York at Buffalo, Buffalo, USA
G. Agarwal, C. Harrington, I. Iashvili, A. Kharchilava, C. McLean, D. Nguyen,
A. Parker, J. Pekkanen, S. Rappoccio, B. Roozbahani Northeastern University,
Boston, USA
G. Alverson, E. Barberis, C. Freer, Y. Haddad, A. Hortiangtham, G. Madigan,
D.M. Morse, T. Orimoto, L. Skinnari, A. Tishelman-Charny, T. Wamorkar, B.
Wang, A. Wisecarver, D. Wood Northwestern University, Evanston, USA
S. Bhattacharya, J. Bueghly, T. Gunter, K.A. Hahn, N. Odell, M.H. Schmitt, K.
Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, USA
R. Bucci, N. Dev, R. Goldouzian, M. Hildreth, K. Hurtado Anampa, C. Jessop,
D.J. Karmgard, K. Lannon, W. Li, N. Loukas, N. Marinelli, I. Mcalister, F.
Meng, C. Mueller, Y. Musienko37, M. Planer, R. Ruchti, P. Siddireddy, G.
Smith, S. Taroni, M. Wayne, A. Wightman, M. Wolf, A. Woodard The Ohio State
University, Columbus, USA
J. Alimena, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, C. Hill, W. Ji, A.
Lefeld, T.Y. Ling, B.L. Winer Princeton University, Princeton, USA
S. Cooperstein, G. Dezoort, P. Elmer, J. Hardenbrook, N. Haubrich, S.
Higginbotham, A. Kalogeropoulos, S. Kwan, 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, G. Negro, 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
U. Behrens, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Kilpatrick, Arun Kumar,
W. Li, B.P. Padley, R. Redjimi, J. Roberts, J. Rorie, W. Shi, A.G. Stahl
Leiton, Z. Tu, A. Zhang University of Rochester, Rochester, USA
A. Bodek, P. de Barbaro, R. Demina, J.L. Dulemba, C. Fallon, T. Ferbel, M.
Galanti, A. Garcia-Bellido, O. Hindrichs, A. Khukhunaishvili, E. Ranken, P.
Tan, R. Taus Rutgers, The State University of New Jersey, Piscataway, USA
B. Chiarito, J.P. Chou, A. Gandrakota, Y. Gershtein, E. Halkiadakis, A. Hart,
M. Heindl, E. Hughes, S. Kaplan, S. Kyriacou, I. Laflotte, A. Lath, R.
Montalvo, K. Nash, M. Osherson, H. Saka, S. Salur, S. Schnetzer, S. Somalwar,
R. Stone, S. Thomas University of Tennessee, Knoxville, USA
H. Acharya, A.G. Delannoy, G. Riley, S. Spanier Texas A&M University, College
Station, USA
O. Bouhali77, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi,
J. Gilmore, T. Huang, T. Kamon78, S. Luo, D. Marley, R. Mueller, D. Overton,
L. Perniè, D. Rathjens, A. Safonov Texas Tech University, Lubbock, USA
N. Akchurin, J. Damgov, F. De Guio, S. Kunori, K. Lamichhane, S.W. Lee, T.
Mengke, S. Muthumuni, T. Peltola, S. Undleeb, I. Volobouev, Z. Wang, A.
Whitbeck Vanderbilt University, Nashville, USA
S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K.
Padeken, F. Romeo, P. Sheldon, S. Tuo, J. Velkovska, M. Verweij University of
Virginia, Charlottesville, USA
M.W. Arenton, P. Barria, B. Cox, G. Cummings, R. Hirosky, M. Joyce, A.
Ledovskoy, C. Neu, B. Tannenwald, Y. Wang, E. Wolfe, F. Xia Wayne State
University, Detroit, USA
R. Harr, P.E. Karchin, N. Poudyal, J. Sturdy, P. Thapa University of Wisconsin
- Madison, Madison, WI, USA
T. Bose, J. Buchanan, C. Caillol, D. Carlsmith, S. Dasu, I. De Bruyn, L. Dodd,
F. Fiori, C. Galloni, B. Gomber79, H. He, M. Herndon, A. Hervé, U. Hussain, P.
Klabbers, A. Lanaro, A. Loeliger, K. Long, R. Loveless, J. Madhusudanan
Sreekala, T. Ruggles, A. Savin, V. Sharma, W.H. Smith, D. Teague, S. Trembath-
reichert, 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 UFMS, Nova Andradina, Brazil
6: Also at Universidade Federal de Pelotas, Pelotas, Brazil
7: Also at Université Libre de Bruxelles, Bruxelles, Belgium
8: Also at University of Chinese Academy of Sciences, Beijing, China
9: Also at Institute for Theoretical and Experimental Physics named by A.I.
Alikhanov of NRC ‘Kurchatov Institute’, Moscow, Russia
10: Also at Joint Institute for Nuclear Research, Dubna, Russia
11: Also at Cairo University, Cairo, Egypt
12: Also at British University in Egypt, Cairo, Egypt
13: Now at Ain Shams University, Cairo, Egypt
14: Also at Purdue University, West Lafayette, USA
15: Also at Université de Haute Alsace, Mulhouse, France
16: Also at Erzincan Binali Yildirim University, Erzincan, Turkey
17: Also at CERN, European Organization for Nuclear Research, Geneva,
Switzerland
18: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
19: Also at University of Hamburg, Hamburg, Germany
20: Also at Brandenburg University of Technology, Cottbus, Germany
21: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary,
Debrecen, Hungary
22: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
23: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary, Budapest, Hungary
24: Also at IIT Bhubaneswar, Bhubaneswar, India, Bhubaneswar, India
25: Also at Institute of Physics, Bhubaneswar, India
26: Also at Shoolini University, Solan, India
27: Also at University of Visva-Bharati, Santiniketan, India
28: Also at Isfahan University of Technology, Isfahan, Iran
29: Now at INFN Sezione di Bari a, Università di Bari b, Politecnico di Bari
c, Bari, Italy
30: Also at Italian National Agency for New Technologies, Energy and
Sustainable Economic Development, Bologna, Italy
31: Also at Centro Siciliano di Fisica Nucleare e di Struttura Della Materia,
Catania, Italy
32: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy
33: Also at Riga Technical University, Riga, Latvia, Riga, Latvia
34: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia
35: Also at Consejo Nacional de Ciencia y Tecnología, Mexico City, Mexico
36: Also at Warsaw University of Technology, Institute of Electronic Systems,
Warsaw, Poland
37: Also at Institute for Nuclear Research, Moscow, Russia
38: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
39: Also at Institute of Nuclear Physics of the Uzbekistan Academy of
Sciences, Tashkent, Uzbekistan
40: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
41: Also at University of Florida, Gainesville, USA
42: Also at Imperial College, London, United Kingdom
43: Also at P.N. Lebedev Physical Institute, Moscow, Russia
44: Also at California Institute of Technology, Pasadena, USA
45: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
46: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
47: Also at Università degli Studi di Siena, Siena, Italy
48: Also at INFN Sezione di Pavia a, Università di Pavia b, Pavia, Italy,
Pavia, Italy
49: Also at National and Kapodistrian University of Athens, Athens, Greece
50: Also at Universität Zürich, Zurich, Switzerland
51: Also at Stefan Meyer Institute for Subatomic Physics, Vienna, Austria,
Vienna, Austria
52: Also at Burdur Mehmet Akif Ersoy University, BURDUR, Turkey
53: Also at Şırnak University, Sirnak, Turkey
54: Also at Beykent University, Istanbul, Turkey, Istanbul, Turkey
55: Also at Istanbul Aydin University, Istanbul, Turkey
56: Also at Mersin University, Mersin, Turkey
57: Also at Piri Reis University, Istanbul, Turkey
58: Also at Gaziosmanpasa University, Tokat, Turkey
59: Also at Adiyaman University, Adiyaman, Turkey
60: Also at Ozyegin University, Istanbul, Turkey
61: Also at Izmir Institute of Technology, Izmir, Turkey
62: Also at Marmara University, Istanbul, Turkey
63: Also at Kafkas University, Kars, Turkey
64: Also at Istanbul Bilgi University, Istanbul, Turkey
65: Also at Hacettepe University, Ankara, Turkey
66: Also at Vrije Universiteit Brussel, Brussel, Belgium
67: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
68: Also at IPPP Durham University, Durham, United Kingdom
69: Also at Monash University, Faculty of Science, Clayton, Australia
70: Also at Bethel University, St. Paul, Minneapolis, USA, St. Paul, USA
71: Also at Karamanoğlu Mehmetbey University, Karaman, Turkey
72: Also at Vilnius University, Vilnius, Lithuania
73: Also at Bingol University, Bingol, Turkey
74: Also at Georgian Technical University, Tbilisi, Georgia
75: Also at Sinop University, Sinop, Turkey
76: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey
77: Also at Texas A&M University at Qatar, Doha, Qatar
78: Also at Kyungpook National University, Daegu, Korea, Daegu, Korea
79: Also at University of Hyderabad, Hyderabad, India