TOP-17-012

$HeadURL$ $Id$

TOP-17-012

# Measurement of CKM matrix elements in single top quark $t$-channel
production in proton-proton collisions at $\sqrt{s}=13\TeV$

###### Abstract

The first direct, model-independent measurement is presented of the modulus of
the Cabibbo–Kobayashi–Maskawa (CKM) matrix elements $\abs{V_{\PQt\PQb}}$,
$\abs{V_{\PQt\PQd}}$, and $\abs{V_{\PQt\PQs}}$, in final states enriched in
single top quark $t$-channel events. The analysis uses proton-proton collision
data from the LHC, collected during 2016 by the CMS experiment, at a centre-
of-mass energy of 13, corresponding to an integrated luminosity of 35.9.
Processes directly sensitive to these matrix elements are considered at both
the production and decay vertices of the top quark. In the standard model
hypothesis of CKM unitarity, a lower limit of $\abs{V_{\PQt\PQb}}>0.970$ is
measured at the 95$\%$ confidence level. Several theories beyond the standard
model are considered, and by releasing all constraints among the involved
parameters, the values $\abs{V_{\PQt\PQb}}=0.988\pm 0.024$, and
$\abs{V_{\PQt\PQd}}^{2}+\abs{V_{\PQt\PQs}}^{2}=0.06\pm 0.06$, where the
uncertainties include both statistical and systematic components, are
measured.

##  0.1 Introduction

A distinctive feature of the electroweak sector of top quark physics is the
relative magnitude of the Cabibbo–Kobayashi–Maskawa (CKM) [1] matrix element
$V_{\PQt\PQb}$ with respect to $V_{\PQt\PQd}$ and $V_{\PQt\PQs}$, which leads
to a strong suppression of processes involving mixing between the third and
the first two quark families. This feature can be probed at the CERN LHC by
studying the couplings of top quarks to , , and quarks in electroweak charged-
current interactions, where such couplings play a role at either the
production or decay vertices of the top quark. In general, top quarks are
produced in proton-proton ($\Pp\Pp$) collisions through the strong
interaction, predominantly via gluon fusion, creating a top quark-antiquark ()
pair. Top quarks can also be singly produced via the electroweak interaction,
in which case the dominant mechanism involves an exchange of a boson in the
$t$ channel, a process which has been precisely measured at the LHC [2, 3, 4,
5, 6, 7, 8, 9, 10, 11]. The dominant decay process for a top quark is to a
boson and a quark via an electroweak charged-current interaction. All single
top quark processes therefore allow the direct probing of the $\PQt\PW\PQq$
vertex, with representing a , , or quark, both in production and decay of the
top quark. In the $t$ channel, a top quark is produced recoiling against a
light quark, henceforth referred to as $\PQq^{\prime}$. Figure 1 shows typical
Feynman diagrams at leading order (LO) for the different production and decay
modes considered in this analysis.

Figure 1:  Leading-order Feynman diagrams for single top quark production via
the $t$ channel featuring: (a) a $\PQt\PW\PQb$ vertex in production and decay,
(b) a $\PQt\PW\PQb$ vertex in production and a $\PQt\PW\PQq$ in decay, with
being an or quark, (c) a $\PQt\PW\PQq$ vertex in production and a
$\PQt\PW\PQb$ in decay, and (d) a process initiated by a quark and enhanced
due to contributions from these valence quarks. The $\ell$ refers to or
leptons.

The elements $V_{\PQt\PQb}$, $V_{\PQt\PQd}$, and $V_{\PQt\PQs}$ of the CKM
matrix can be indirectly constrained from measurements in the and meson
sectors [12], but those determinations rely crucially on model assumptions,
such as the existence of only three generations of quarks and the absence of
particles beyond the standard model (SM) [13]. This model dependence motivates
alternative inferences based on different sets of hypotheses. In particular,
given that these three CKM elements connect the top quark with down-type
quarks, it is natural to use events enriched in top quarks to set constraints
on them. Two complementary approaches have been pursued by the Tevatron and
LHC experiments to extract $\abs{V_{\PQt\PQb}}$: the first method measures the
branching fraction
$\mathcal{B}(\PQt\to\PW\PQb)=\abs{V_{\PQt\PQb}}^{2}/\bigl{(}\abs{V_{\PQt\PQd}}^{2}+\abs{V_{\PQt\PQs}}^{2}+\abs{V_{\PQt\PQb}}^{2}\bigr{)}$
in events [14, 15, 16, 17]. The $\mathcal{B}(\PQt\to\PW\PQb)$ measurement is
sensitive to the CKM elements of interest through the decay vertex of the top
quark, and can be turned into a measurement of the value of
$\abs{V_{\PQt\PQb}}$ only under the hypothesis of the unitarity of the
$3\times 3$ CKM matrix. The second method is based on the single top quark
production cross section and is sensitive in principle through both the
production and decay of the top quark. To disentangle the effects of the two
vertices in past measurements at the Tevatron [18, 19, 20, 21, 22, 23, 24, 25,
26, 27] and the LHC [5, 2, 3, 9, 6, 7, 8, 28, 29, 10], $\abs{V_{\PQt\PQb}}$
was extracted in the $t$ channel by assuming that the values of
$\abs{V_{\PQt\PQs}}$ and $\abs{V_{\PQt\PQd}}$ are negligible. Some theoretical
proposals have suggested the simultaneous extraction of the three CKM matrix
elements from a combination of measurements of $\mathcal{B}(\PQt\to\PW\PQb)$
and either inclusive [13, 30] or differential [31, 32] cross sections of
single top quark production in the $t$ channel. Other studies specifically
address the determination of $\abs{V_{\PQt\PQd}}$ [31, 33] through a reliance
on the reinterpretation of existing measurements, but they do not make use of
full experimental detector simulations and do not exploit the discriminating
power of multivariate analyses (see, for example, discussion in Ref. [34]).

The data used in this Letter come from $\Pp\Pp$ collisions at
$\sqrt{s}=13\TeV$, corresponding to an integrated luminosity of $35.9\fbinv$
and collected by the CMS experiment with triggers requiring either one muon or
electron in the final state. We present the first direct and model-independent
simultaneous measurement of $\abs{V_{\PQt\PQb}}$, $\abs{V_{\PQt\PQd}}$, and
$\abs{V_{\PQt\PQs}}$, by considering their respective contributions to the top
quark $t$-channel production and decay.

##  0.2 The CMS detector

The central feature of the CMS apparatus is a superconducting solenoid of 6m
internal diameter, providing a magnetic field of 3.8T. Within the solenoid
volume are a silicon pixel and strip tracker, a lead tungstate crystal
electromagnetic calorimeter, and a brass and scintillator hadron calorimeter,
each composed of a barrel and two endcap sections. Forward calorimeters extend
the pseudorapidity ($\eta$) [35] coverage provided by the barrel and endcap
detectors.

Events of interest are selected using a two-tiered trigger system [36]. The
first level, composed of custom hardware processors, uses information from the
calorimeters and muon detectors to select events. The second level, known as
the high-level trigger, consists of a farm of processors running a version of
the full event reconstruction software optimised for efficient processing. A
more detailed description of the CMS detector, together with a definition of
the coordinate system used and the relevant kinematic variables, can be found
in Ref. [35].

##  0.3 Simulated samples

Monte Carlo (MC) event generators are used to simulate signal and background
samples. Single top quark $t$-channel events are generated at next-to-leading-
order (NLO) in quantum chromodynamics (QCD) with 2.0 [37, 38, 39]. The four-
flavour scheme [40] is used for events with the $V_{\PQt\PQb}$ vertex in
production, while the five-flavour scheme [41] is used for events with one
$V_{\PQt\PQd}$ or $V_{\PQt\PQs}$ vertex in production. Top quark decays are
simulated with madspin [42]. The $\ttbar$ background process [43], as well as
double vector boson production [44, 45] (, where stands for either a or a
boson), are generated with 2.0. Associated top quark and boson production are
simulated with in the five-flavour scheme [46]. Single top quark $s$-channel
events (t, $s$-ch) are simulated with 2.2.2 [47] at NLO. The value of the top
quark mass used in the simulated samples is 172.5. For all samples 8.180 [48]
with tune CUETP8M1 [49] is used to simulate the parton shower, quark
hadronisation, and underlying event, except for $\ttbar$, where the tune
CUETPM2T4 is used [50]. Simulated event samples with and bosons in association
with jets ($\PW\text{+jets}$, $\PZ$+jets) are generated using 2.2.2. For these
processes, events with up to two additional partons emitted in the hard
scattering are simulated, and the FxFx merging scheme [51] is used to avoid
double counting with parton emissions generated in the parton showering.
Simulated QCD multijet events, generated at LO with 8.180, are used to
validate the estimation of this background with a technique based on control
samples in data.

The default parametrisation of the parton distribution functions (PDFs) used
in all simulations is NNPDF3.0 [52] at LO or NLO QCD, with the order matching
that of the matrix element calculation. All generated events undergo a full
simulation of the detector response according to the model of the CMS detector
within [53]. Additional $\Pp\Pp$ interactions within the same or nearby bunch
crossings (pileup) are included in the simulation with the same distribution
as observed in data. Except for the QCD multijet process, which is determined
from a fit to data, all simulated samples are normalised to the expected cross
sections.

##  0.4 Event selection and reconstruction

The signal event selection is based on final states where the top quark decays
to a , , or quark, and a boson, which then decays to a lepton-neutrino pair.
Events with exactly one muon or electron and at least two jets are considered
in this analysis, as was done in the latest CMS single top quark cross section
measurement [10]. The neutrino accompanying the lepton cannot be directly
detected, and manifests itself in the detector as a measured momentum
imbalance in the event. Depending on the CKM matrix element involved in the
decay, the final state may include a jet from the hadronisation of either a ,
, or quark. A jet recoiling against the top quark is present, and it is
produced usually at low angle with respect to the beam axis. A third jet can
stem from the second quark produced in the gluon splitting (as shown in Fig.
1(c)). The quark from gluon splitting generates a jet that usually has a
softer transverse momentum () spectrum than that of the jet from the top quark
decay products. Depending on the number of $\PQt\PW\PQb$ vertices in the event
process, one can have one jet coming from the hadronisation of a quark (jet)
if the $\PQt\PW\PQb$ vertex occurs in production or in decay but not in both,
or two jets if the $\PQt\PW\PQb$ vertex occurs both in production and decay.

Events are retained for the offline analysis if they were selected online by
requiring the presence of an isolated, high-$\pt$ lepton: either a muon with
$\pt>24\GeV$ or an electron with $\pt>32\GeV$. From the sample of triggered
events, only those with at least one primary vertex reconstructed from at
least four tracks, with a longitudinal distance of less than 24cm and a radial
distance of less then 2cm from the centre of the detector, are considered for
the analysis. The candidate vertex with the largest value of summed physics-
object $\pt^{2}$ is taken to be the primary $\Pp\Pp$ interaction vertex. The
physics objects are the jets, clustered using the jet-finding algorithm [54,
55] with the tracks assigned to candidate vertices as inputs, and the
associated missing (), taken as the magnitude of the negative vector sum of
the of those jets.

The particle-flow (PF) algorithm [56] is used to reconstruct and identify
individual particles in the event using combined information from the
subdetectors of the CMS experiment, allowing identification of muons,
electrons, photons, and charged and neutral hadrons. After triggering, muons
are considered for further analysis if they have $\pt>26\GeV$ and
$\abs{\eta}<2.4$, while electrons are required to have $\pt>35\GeV$ and
$\abs{\eta}<2.1$. Additional isolation requirements are used to discriminate
between prompt leptons and those coming from hadronic decays within jets, by
defining $I_{rel}$, as the scalar sum of the of charged hadrons, neutral
hadrons, and photons divided by the of lepton in a cone of $\Delta
R=\sqrt{\smash[b]{(\Delta\eta)^{2}+(\Delta\phi)^{2}}}=0.4$ around the muon and
0.3 around the electron, where $\phi$ is the azimuthal angle in radians. The
contribution of hadrons from pileup interactions is subtracted from the scalar
sum with the techniques detailed in Refs. [57, 58]. The parameter $I_{rel}$ is
required to be less than 6.0% for muons, 5.9% for barrel electrons, and 5.7%
for endcap electrons.

Jets are reconstructed using the anti-clustering algorithm described in Refs.
[54, 55] with a distance parameter of 0.4 on the collection of PF candidates.
To be included, charged particle candidates must be closer along the z axis to
the primary vertex than to any other vertex.

A correction to account for pileup interactions is estimated on an event-by-
event basis using the jet area method described in Ref. [58], and is applied
to the reconstructed jet . Further jet energy corrections [59], derived from
the study of dijet events and photon plus jet events in data, are applied. Two
types of jets are defined: high-jets are defined by requiring $\abs{\eta}<4.7$
and $\pt>40~{}\GeV$, and low-jets are defined by requiring $\abs{\eta}<4.7$
and $20<\pt<40~{}\GeV$.

Once the jets have been selected according to the above criteria, they can be
further categorised using a tagging discriminator variable in order to
distinguish between jets stemming from the hadronisation of quarks and those
from the hadronisation of light partons. A multivariate (MVA) discriminator
algorithm uses track-based lifetime information, together with secondary
vertices inside the jet, to provide a MVA discriminator for jet identification
[60, 61]. For values of the discriminator above the chosen threshold, the
efficiency of the tagging algorithm to correctly find jets is about 45%, with
a rate of 0.1% for mistagging light-parton jets [60, 61].

Events are divided into mutually exclusive “categories” according to the
number of selected high-jets and -tagged high-jets. In the following,
categories are labelled as “$n$j$m$t”, referring to events with exactly $n$
high-jets, $m$ of which are tagged as jets, regardless of the number of low-
jets. The threshold on the jet momentum for high-jets lessens the impact on
the categorisation of additional jets coming from initial- or final-state
radiation, which is fully simulated and taken into account in the modelling
systematic uncertainties.

To reject events from QCD multijet background processes, a requirement on the
transverse mass of the boson of $\mT^{\PW}>50\GeV$ is imposed, where

$\mT^{\PW}=\sqrt{\left(p_{\mathrm{T},\ell}+\ptmiss\right)^{2}-\left(p_{x,\ell}+p_{x}^{\text{miss}}\right)^{2}-\left(p_{y,\ell}+p_{y}^{\text{miss}}\right)^{2}}.$
(1)

Here, $\ptmiss$ is defined as the magnitude of $\ptvecmiss$, which is the
negative of the vectorial sum of all the PF particles. The
$p_{x}^{\text{miss}}$ and $p_{y}^{\text{miss}}$ quantities are the
$\ptvecmiss$ components along the $x$ and $y$ axes, respectively, and
$p_{\mathrm{T},\ell}$, $p_{x,\ell}$, and $p_{y,\ell}$ are the corresponding
lepton momentum components in the transverse, $x$, and $y$ directions.

To analyse the kinematics of single top quark production, the four-momentum of
a top quark candidate is reconstructed from the decay products: leptons,
neutrinos, and jet candidates. The of the neutrino can be inferred from . The
longitudinal momentum of the neutrino, $p_{z,\PGn}$, is calculated assuming
energy-momentum conservation at the $\PW\ell\PGn$ vertex and constraining the
boson mass to $m_{\mathrm{W}}=80.4\GeV$ [12]:

$p_{z,\PGn}^{\pm}=\frac{\Lambda
p_{z,\ell}}{p_{\mathrm{T},\ell}^{2}}\pm\frac{1}{p_{\mathrm{T},\ell}^{2}}\sqrt{\Lambda^{2}p_{z,\ell}^{2}-p_{\mathrm{T},\ell}^{2}(p_{\ell}^{2}p_{\mathrm{T},\PGn}^{2}-\Lambda^{2})},$
(2)

where

$\Lambda=\frac{m_{\PW}^{2}}{2}+\vec{p}_{\mathrm{T},\ell}\cdot\ptvecmiss,$ (3)

and $p_{\ell}^{2}=p_{\mathrm{T},\ell}^{2}+p_{z,\ell}^{2}$ denotes the square
of the lepton momentum. In most of the cases, this leads to two real solutions
for $p_{z,\PGn}$ and the solution with the smallest absolute value is chosen
[23, 21]. For some events, the discriminant in Eq. (2) becomes negative,
leading to complex solutions for $p_{z,\PGn}$. In this case, the imaginary
component is eliminated by modification of $p_{x,\PGn}$ and $p_{y,\PGn}$ so
that $\mT^{\PW}=m_{\PW}$, while still respecting the $m_{\PW}$ constraint.
This is achieved by requiring the determinant, and thus the square-root term
in Eq. (2), to equal zero. This condition gives a quadratic relation between
$p_{x,\PGn}$ and $p_{y,\PGn}$ with two possible solutions and one remaining
degree of freedom. The solution is chosen by finding the
$\vec{p}_{\mathrm{T},\PGn}$ that has the minimum vectorial distance from in
the $p_{x}^{\text{miss}}-p_{y}^{\text{miss}}$ plane.

A reconstructed top quark candidate is defined by associating one jet with an
accompanying boson, and the respective top quark four-momentum is evaluated as
described above. For each of the signal categories selected, multiple top
quark candidates can be defined in the same category, depending on the
hypothesis for the origin of the jet in the event.

##  0.5 Signal description and event categorisation

The predicted branching fractions of top quarks to , , and quarks can be
written as a function of the overall magnitude of
$\mathcal{B}(\PQt\to\PW\PQq)=\abs{V_{\PQt\PQq}}^{2}/\bigl{(}\abs{V_{\PQt\PQd}}^{2}+\abs{V_{\PQt\PQs}}^{2}+\abs{V_{\PQt\PQb}}^{2}\bigr{)}$.
The values of $\abs{V_{\PQt\PQq}}$ and $\mathcal{B}(\PQt\to\PW\PQq)$ used to
derive the initial normalisation of signal processes are taken from Ref. [12],
and shown in Table 0.5.

Values of the third-row elements of the CKM matrix inferred from low-energy
measurements, taken from Ref. [12], with the respective values of the top
quark decay branching fractions. The in $\abs{V_{\PQt\PQq}}$ and
$\mathcal{B}(\PQt\to\PW\PQq)$ in the first column refers to , , and quarks,
according to the quark label shown in the header row.  Quark
$\abs{V_{\PQt\PQq}}$ $0.999119^{\,+0.000024}_{\,-0.000012}$
$0.04108^{\,+0.00030}_{\,-0.00057}$ $0.008575^{\,+0.000076}_{\,-0.000098}$
$\mathcal{B}(\PQt\to\PW\PQq)$ $0.998239^{\,+0.000048}_{\,-0.000024}$
$0.0016876^{\,+0.0000025}_{\,-0.0000047}$
$0.000074^{\,+0.000013}_{\,-0.000017}$

The quantities reported in Table 0.5 come from low-energy measurements that
assume unitarity in the CKM matrix and no new loops in the relevant Feynman
diagrams. This analysis will relax such assumptions and present different
scenarios for interpretation of the provided results.

The signatures for $t$-channel processes involving $V_{\PQt\PQb}$,
$V_{\PQt\PQd}$, and $V_{\PQt\PQs}$ either in production or decay differ in
three aspects: the number of reconstructed -tagged jets, the features of the
jet involved in the reconstruction of the correct top quark candidate, and the
kinematic features of the events as a result of different PDF contributions to
production modes involving a , , or quark. Henceforth, the $t$-channel process
involving $V_{\PQt\PQb}$ in both production and decay will be referred to as
$ST_{\PQb,\PQb}$, while $t$-channel processes involving $V_{\PQt\PQb}$ in only
production or decay will be referred to as $ST_{\PQb,\PQq}$ and
$ST_{\PQq,\PQb}$, respectively. The signal channels and their corresponding
cross sections times branching fractions from simulation are reported in Table
0.5.

For each of the production and decay vertices, the cross section times
branching fraction for the corresponding signal process from simulation. The
uncertainties shown include those from the factorisation and renormalisation
scales, the PDFs, and any experimental uncertainties, where appropriate.
Production Decay Cross section $\times$ branching fraction (pb) $\PQt\PW\PQb$
$\PQt\PW\PQb$ $217.0\pm 8.4$ $\PQt\PW\PQb$ ($\PQt\PW\PQs+\PQt\PW\PQd$)
$0.41\pm 0.05$ $\PQt\PW\PQd$ $\PQt\PW\PQb$ $0.102\pm 0.015$ $\PQt\PW\PQs$
$\PQt\PW\PQb$ $0.92\pm 0.11$

The cross sections are evaluated at NLO in the five-flavour scheme using for
$\sigma_{t\text{-ch,}\PQd}$, $\sigma_{t\text{-ch},\PQs}$, and with HATHOR [62]
for $\sigma_{t\text{-ch,}\PQb}$.

Multiple categories are defined in order to extract the contribution of the
different $t$-channel processes, while at the same time discriminating against
the background processes, mainly and $\PW\text{+jets}$ production. The
majority of $t$-channel events populate categories with 2 or 3 jets, as
defined above. The main backgrounds arise from (all categories),
$\PW\text{+jets}$ (in the 2j1t and 3j1t categories), and QCD multijet (in the
2j1t category) processes. The signal processes taken into consideration give
different contributions to the three categories, and it is possible to
identify the most sensitive categories with respect to each process based on
the respective signatures, as summarised in Table 0.5. The physics motivations
leading to this strategy are described below.

Events from strong interaction production, where one top quark decays through
the $\PQt\PW\PQd$ or $\PQt\PW\PQs$ vertex ($\ttbar_{\PQb,\PQq}$), populate the
2j1t and 3j1t categories. Their small contribution to the yield in such
categories is covered by the -tagging uncertainty. Their signature in those
categories is also found to be indistinguishable, within systematic
uncertainties, from that of when each top quark decays through the
$\PQt\PW\PQb$ vertex and one jet does not pass either the kinematic or tagging
requirements. For those reasons, all top quark decay modes of pairs are
treated as a single background source.

For each category, the corresponding signal process, the cross section times
branching fraction expression, and the specific Feynman diagram from Fig. 1
are shown.  Category Enriched in Cross section $\times$ branching fraction
Feynman diagram 2j1t $ST_{\PQb,\PQb}$
$\sigma_{t\text{-ch,}\PQb}\mathcal{B}(\PQt\to\PW\PQb)$ 1a 3j1t
$ST_{\PQb,\PQq}$, $ST_{\PQq,\PQb}$
$\sigma_{t\text{-ch,}\PQb}\mathcal{B}(\PQt\to\PW\PQq)$,
$\sigma_{t\text{-ch,}\PQq}\mathcal{B}(\PQt\to\PW\PQb)$ 1b, 1c, 1d 3j2t
$ST_{\PQb,\PQb}$ $\sigma_{t\text{-ch,}\PQb}\mathcal{B}(\PQt\to\PW\PQb)$ 1a

The discrimination between the three signals $ST_{\PQb,\PQq}$,
$ST_{\PQq,\PQb}$, and $ST_{\PQb,\PQb}$ is based on three characteristics.
First, for $ST_{\PQb,\PQq}$ events, only a single quark is present in the
final state stemming from gluon splitting, thus resulting in a low-energy
-tagged jet, while the jet coming from the top quark decay is usually not
tagged. For $ST_{\PQq,\PQb}$ events, a single -tagged jet is produced in the
top quark decay, and additional jets from gluon splitting are usually not
tagged. Both $ST_{\PQq,\PQb}$ and $ST_{\PQb,\PQq}$ processes therefore differ
from $ST_{\PQb,\PQb}$ by having a single quark in the final state, as opposed
to two for the latter process. However, this feature can only be exploited
when the jet from gluon splitting is energetic enough to be reconstructed.
Second, further discrimination is achieved by exploiting the features of the
reconstructed top quark candidates. The kinematic and angular properties of
the decay products exhibit significant differences depending on whether the
correct jet is chosen, or if the jet that originated from the quark produced
in the gluon splitting is used. For $ST_{\PQb,\PQq}$ events, the top quark
reconstructed with the correct jet assignment usually does not use the -tagged
jet in the event, while for $ST_{\PQb,\PQb}$ and $ST_{\PQq,\PQb}$, the top
quark candidate is reconstructed by using the -tagged jet in the majority of
cases. It is therefore possible to differentiate between the $ST_{\PQb,\PQb}$
and $ST_{\PQb,\PQq}$ processes by comparing the features of top quark
candidates reconstructed with or without -tagged jets. Finally, different PDFs
are involved in $ST_{\PQb,\PQb}$ and $ST_{\PQq,\PQb}$ processes, the latter
drawing contributions from valence quarks as well. Therefore, the kinematic
properties of final-state particles may differ from the other channels. The
second characteristic, related to the correctness of the top quark
reconstruction hypothesis, proves to be the strongest amongst the three
mentioned criteria. While the $ST_{\PQb,\PQq}$ and the $ST_{\PQb,\PQb}$
processes can be differentiated by using this characteristic, the
$ST_{\PQq,\PQb}$ and the $ST_{\PQb,\PQb}$ productions cannot, because their
final-state signatures exhibit the same features.

The 2j1t category is populated by events that depend on $V_{\PQt\PQb}$ in both
production and decay, where the single reconstructed jet comes in the majority
of cases (85%) from top quark decays, and for the remaining cases from the
second jet from gluon splitting. This means that the jet from the second quark
fails either the jet $\pt$ requirement or the tag requirement, or both. Events
coming from a process for which $V_{\PQt\PQd}$ or $V_{\PQt\PQs}$ are involved,
either in production or in decay, populate this category as well, with either
the -tagged jet coming from top quark decay or the secondary quark from gluon
splitting.

For $t$-channel signal events from all four processes in Fig. 1, the most
distinctive features that allow the discrimination against backgrounds in the
2j1t category rely on the fact that the second jet stems from the recoiling
quark. For this reason the non--tagged jet is not used for the top quark
reconstruction. This category is the one where the highest discrimination
power for $ST_{\PQb,\PQb}$ against backgrounds is achieved by making use of
the features of the top quark decay products, such as the reconstructed top
quark mass and $\mT^{\PW}$, and of the recoiling jet. However, the
discrimination power with respect to other $t$-channel mechanisms is poor
since jets from gluon splitting are typically not energetic enough to pass the
threshold, making it impossible to reconstruct two different top quark
candidates.

The 3j1t category is also populated by all $t$-channel processes of interest,
but it differs from 2j1t in the fact that it accommodates events in which the
jet from gluon splitting has a higher on average. For both the 2j1t and 3j1t
categories, when the top quark decays through $\PQt\PW\PQd$,vertices, the jet
coming from the top quark usually does not pass the tagging requirement since
it stems from the hadronisation of a light quark. In all other cases, this jet
passes the tagging requirement, given the efficiency of the tagging algorithm.

The 3j1t category is enriched in $t$-channel events by requiring
$\abs{\eta_{\text{j}^{\prime}}}>2.5$, where $\eta_{\text{j}^{\prime}}$ is the
pseudorapidity of the most forward jet. The two jets other than the most
forward one are used to reconstruct the two top quark candidates. If the event
is from the $ST_{\PQb,\PQq}$ process, the -tagged jet in the 3j1t category
will stem from gluon splitting, and the additional jet will have a higher
chance of being the one coming from the top quark decay to an or quark.
Variables of interest in this case are constructed by making use of the jet
and the least forward jet of the remaining two, referred to as the extra jet.
Such variables include the invariant mass of the lepton plus jet system
(either the jet or the extra jet), and several top quark kinematic variables
constructed using a combination of the extra jet, the lepton, and .

In both the 2j1t and the 3j1t categories, $\mT^{\PW}$ is also used to
discriminate between the QCD multijet background and other processes. An event
category depleted of QCD multijet background is defined by adding the
requirement $\mT^{\PW}>50\GeV$. Figure 2 shows the $\mT^{\PW}$ distribution
from data and simulations in the 2j1t and 3j1t categories for the muon (upper
plots) and electron (lower plots) channels, where the QCD multijet background
is normalised to the result of the fit.

Figure 2:  The $\mT^{\PW}$ distribution from data (points) and simulation
(shaded histograms) in the 2j1t (left) and 3j1t (right) categories for the
muon (upper) and electron (lower) channels. The vertical lines on the points
and the hatched bands show the experimental and MC statistical uncertainties,
respectively. The expected distribution from the
$ST_{\PQq,\PQb}+ST_{\PQb,\PQq}$ processes (multiplied by a factor of 1000) is
shown by the solid blue line. The lower panels show the ratio of the data to
the MC prediction.

In the 3j2t category, there are two jets, one produced from the top quark
decay and another from gluon splitting. Both jets are used to reconstruct a
top quark candidate and its corresponding variables. In this case, the
$\mT^{\PW}>50\GeV$ requirement is unnecessary since the
$\mathrm{QCD}~{}\text{multijet}$ contamination is negligible and the dominant
background process is $\ttbar$. No requirement on $\eta_{\text{j}^{\prime}}$
is needed either since the category is dominated by the $ST_{\PQb,\PQb}$
process and the combinatorial top quark background is small.

Multivariate analyses are then performed by using boosted decision trees (BDT)
in order to obtain appropriate discriminating variables, henceforth referred
to as BDT discriminators, in the three categories, for both muons and
electrons. The processes used as signal or background in the training are the
following:

  * •

In the 2j1t category, the single top quark $ST_{\PQb,\PQb}$ process is
considered as signal and and $\PW\text{+jets}$ processes as background.

  * •

In the 3j1t category, the single top quark $ST_{\PQq,\PQb}$ process is
considered as signal and the $ST_{\PQb,\PQb}$, , and $\PW\text{+jets}$
processes as background.

  * •

In the 3j2t category, the single top quark $ST_{\PQb,\PQb}$ process is
considered as signal and as background.

The variables used in the 2j1t category training are: the $\abs{\eta}$ of the
non--tagged jet, the reconstructed top quark mass, the cosine of the angle
between the boson momentum in the top quark rest frame and the momentum of the
lepton in the boson rest frame, the cosine of the polarisation angle defined
as the angle between the direction of the lepton and the light-quark momenta
in the top quark rest frame, the invariant mass of the lepton and -tagged jet
system, and the invariant mass of the lepton and forward jet system.

The variables used in the 3j1t category training are: the $\abs{\eta}$ of the
most forward non--tagged jet, the mass of the top quark when it is
reconstructed with the -tagged jet (-top quark), the cosine of the angle
between the boson momentum in the -top quark rest frame and the momentum of
the lepton in the boson rest frame, the cosine of the polarisation angle
defined as the angle between the direction of the lepton and the light-quark
momenta in the -top quark rest frame, , $\mT^{\PW}$, the invariant mass of the
lepton and -tagged jet system, the invariant mass of the lepton and extra jet
system, the invariant mass of the lepton and forward jet system, the number of
low-jets, the mass of the top quark when it is reconstructed with the non--
tagged jet (non--top quark), the cosine of the angle between the boson
momentum in the non--top quark rest frame and the momentum of the lepton in
the boson rest frame, the cosine of the polarisation angle defined as the
angle between the direction of the lepton and the light-quark momenta in the
non--top quark rest frame, and the value of the MVA tagger discriminator when
applied to the non--tagged jet.

The variables used in the 3j2t category training are: the $\abs{\eta}$ of the
non--tagged jet, the mass of the top quark when it is reconstructed with the
highest--tagged jet (leading top quark), the cosine of the angle between the
boson momentum in the leading top quark rest frame and the momentum of the
lepton in the boson rest frame, the cosine of the polarisation angle defined
as the angle between the direction of the lepton and the light-quark momenta
in the leading top quark rest frame, , $\mT^{\PW}$, the invariant mass of the
lepton and the highest--tagged jet system, the invariant mass of the lepton
and lower--tagged jet system, the invariant mass of the lepton and light-jet
system, the number of low-jets, the mass of the top quark when it is
reconstructed with the lower--tagged jet (non-leading top quark), the cosine
of the angle between the boson momentum in the non-leading top quark rest
frame and the momentum of the lepton in the boson rest frame, the cosine of
the polarisation angle defined as the angle between the direction of the
lepton and the light-quark momenta in the non-leading top quark rest frame,
and the difference in $\eta$ between the two -tagged jets.

Figures 3–5 show the distributions of the most discriminating variables in the
2j1t, 3j1t, and 3j2t categories, respectively.

Figure 3:  Distributions of the two most discriminating variables from data
(points) and simulation (shaded histograms) in the 2j1t category: the
$\abs{\eta}$ of the non--tagged jet $\eta_{\text{j}^{\prime}}$ (left) and the
invariant mass of lepton and jet momenta system (right), shown for the muon
(upper) and electron (lower) channels, respectively. The vertical lines on the
points and the hatched bands show the experimental and MC statistical
uncertainties, respectively. The expected distribution from the
$ST_{\PQq,\PQb}+ST_{\PQb,\PQq}$ processes (multiplied by a factor of 1000) is
shown by the solid blue line. The lower panels show the ratio of the data to
the MC prediction.

Figure 4:  Distributions of the two most discriminating variables from data
(points) and simulation (shaded histograms) in the 3j1t category: the in the
transverse plane (left) and the value of the MVA tagger discriminator when
applied to the extra jet (right) are shown for the muon (upper) and electron
(lower) channels, respectively. The vertical lines on the points and the
hatched bands show the experimental and MC statistical uncertainties,
respectively. The expected distribution from the
$ST_{\PQq,\PQb}+ST_{\PQb,\PQq}$ processes (multiplied by a factor of 1000) is
shown by the solid blue line. The lower panels show the ratio of the data to
the MC prediction.

Figure 5:  Distributions of the two most discriminating variables from data
(points) and simulation (shaded histograms) in the 3j2t category: the
$\abs{\eta}$ of the non--tagged jet $\eta_{\text{j}^{\prime}}$ (left) and the
invariant mass of lepton and non--tagged jet system (right) are shown for the
muon (upper) and electron (lower) channels, respectively. The vertical lines
on the points and the hatched bands show the experimental and MC statistical
uncertainties, respectively. The expected distribution from the
$ST_{\PQq,\PQb}+ST_{\PQb,\PQq}$ processes (multiplied by a factor of 1000) is
shown by the solid blue line. The lower panels show the ratio of the data to
the MC prediction.

##  0.6 Systematic uncertainties

Several sources of systematic uncertainties are considered in the analysis,
divided in two groups depending on the treatment: uncertainties labelled as
“profiled” are treated as nuisance parameters and profiled in the fit
procedure described in Section 0.7, while those labelled as “nonprofiled” are
estimated as the difference between the result of the fit procedure by varying
the systematic scenario. These latter uncertainties include the sources
related to the modelling of the signal process, which cannot be constrained
from the measurement since they apply to the full phase space and not only to
the region in which the measurement is performed. Also included are the jet
energy scale and resolution uncertainties, which play a major role in events
featuring hadronic activity in the high-pseudorapidity region of the detector.
They are also intertwined with the uncertainties in the modelling of the
hadronisation and cause a larger uncertainty in the signal acceptance, which
was not the case for previous measurements [10, 11]. For these reasons, a more
conservative approach is preferred and these uncertainties are not profiled in
the fit.

The impact of nonprofiled uncertainties is determined by repeating the
analysis using varied templates according to the systematic uncertainty
sources under study in the fit, instead of the nominal templates. The
uncertainty due to a certain source is then taken as half the difference
between the results for up and down variations of the effect. In the
following, the different uncertainty sources that are considered in the
analysis are briefly described. For the sake of simplicity and better
readability, they are grouped into profiled and nonprofiled uncertainties.

Profiled uncertainties

  * •

Limited size of simulated event samples: The statistical uncertainty due to
the limited size of the simulated event samples is evaluated for each bin with
the Barlow–Beeston “light” method [63, 64].

  * •

Lepton trigger and reconstruction: Single-muon and single-electron trigger and
reconstruction efficiencies are estimated with a “tag-and-probe” method [65]
from Drell–Yan events with the dilepton invariant mass in the boson peak.

  * •

Pileup: The uncertainty in the average expected number of pileup interactions
is propagated as a source of systematic uncertainty by varying the total
$\Pp\Pp$ inelastic cross section by $\pm 4.6\%$ [66].

  * •

modelling: The following uncertainty sources cover potential mismodelling of
the process. Their effect is considered on both the acceptance and the cross
section.

    * –

renormalisation and factorisation scale uncertainties
($\mu_{\mathrm{R}}/\mu_{\mathrm{F}}$): The uncertainties caused by variations
in the renormalisation and factorisation scales are considered by reweighting
the BDT response distributions with different combinations of doubled/halved
renormalisation and factorisation scales with respect to the nominal value of
172.5.

    * –

Matching of matrix element and parton shower (ME-PS matching): The parameter
that controls the matching between the matrix element level calculation and
the parton shower, and that regulates the high-radiation in the simulation is
varied within its uncertainties.

    * –

Initial- and final-state radiation: The impact of variations in the initial-
state and final-state radiation is studied by comparing the nominal sample
with dedicated samples.

    * –

Underlying event: The effect of uncertainties in the modelling of the
underlying event is studied by comparing the nominal sample with dedicated
samples.

  * •

QCD multijet background process normalisation: The QCD multijet background
yield is assigned a $50\%$ uncertainty, which is chosen conservatively to be
much larger than the uncertainty from the $\mT^{\PW}$ fit.

  * •

$\PW\text{+jets}$ composition: A separate uncertainty is dedicated to the
fraction of $\PW\text{+jets}$ events where the forward jet is generated by the
parton showering.

  * •

Other backgrounds $\mu_{\mathrm{R}}/\mu_{\mathrm{F}}$: In addition to , the
uncertainties due to variations in the renormalisation and factorisation
scales are studied for the $\PQt\PW$ and $\PW\text{+jets}$ processes by
reweighting the distributions with weights corresponding to different
combinations of halved or doubled factorisation and renormalisation scales.
The effect is estimated for each process separately.

  * •

PDF for background processes: The uncertainty due to the choice of PDF is
estimated using reweighted histograms derived from all PDF sets of NNPDF 3.0
[67].

  * •

tagging: The uncertainties in the tagging and mistagging efficiency
measurements are split into different components and propagated to the
efficiency of tagging jets.

Nonprofiled uncertainties

  * •

Luminosity: The integrated luminosity is known with a relative uncertainty of
$\pm 2.6\%$ [68].

  * •

Jet energy scale (JES): All reconstructed jet four-momenta in simulated events
are simultaneously varied according to the $\eta$\- and $\pt$-dependent
uncertainties in the JES [59]. This variation in jet four-momenta is also
propagated to $\ptmiss$.

  * •

Jet energy resolution (JER): A smearing is applied to account for the
difference in the JER between simulation and data [59], and its uncertainty is
estimated by increasing or decreasing the resolutions by their uncertainties.

  * •

Signal modelling: The following uncertainty sources cover potential
mismodelling of the single top quark $t$-channel signal processes. The effect
of those uncertainties on the acceptance, and not on the cross section, is
considered. In the fit procedure, the uncertainties are not considered as
nuisance parameters in the fit but evaluated by repeating the full analysis
using samples of simulated signal events that feature variations in the
modelling parameters covering the systematic uncertainty sources under study.

    * –

Signal $\mu_{\mathrm{R}}/\mu_{\mathrm{F}}$: The uncertainties caused by
variations in the renormalisation and factorisation scales are considered by
reweighting the BDT response distributions according to weights corresponding
to doubling/halving the nominal values of the scales [40, 41].

    * –

Matching of matrix element and parton shower (ME-PS matching): The parameter
that controls the matching between the matrix element level calculation and
the parton shower, and that regulates the high-radiation in the simulation is
varied within its uncertainties.

    * –

Parton shower factorisation scale: The renormalisation scales of the initial-
and final-state parton shower are varied by factors of two and one half with
respect to the nominal value of 172.5.

    * –

PDF for signal process: The uncertainty due to the choice of PDF is estimated
using reweighted histograms derived from all PDF sets of NNPDF 3.0. The
measurements in the following report only the experimental uncertainties,
while the uncertainties on the predicted cross sections are reported in Table
0.5. Effects on the fit due to correlation between PDFs are considered
negligible.

##  0.7 Fit procedure

The three CKM matrix elements are extracted by measuring the production cross
sections and branching fractions of single top quark $t$-channel processes
that depend on $V_{\PQt\PQb}$, $V_{\PQt\PQd}$, and $V_{\PQt\PQs}$ in
production and decay. The vast majority of single top quark $t$-channel events
come from the $ST_{\PQb,\PQb}$ process, while $ST_{\PQb,\PQq}$ and
$ST_{\PQq,\PQb}$ constitute subdominant production mechanisms. The
$\ttbar_{\PQb,\PQq}$ contribution is taken into account in the background
estimation.

The fit procedure is divided into two steps. In the first step, a maximum
likelihood (ML) fit to the $\mT^{\PW}$ distribution is performed separately
for the 2j1t and 3j1t categories in order to extract the QCD multijet
contribution. The QCD multijet normalisation and the relative uncertainty are
extrapolated to the QCD multijet depleted categories and used as an input to
the second step. In the second step, in order to discriminate between
$ST_{\PQb,\PQb}$, $ST_{\PQq,\PQb}$, and $ST_{\PQb,\PQq}$, the multivariate
discriminators described in Section 0.5 are used in a simultaneous ML fit to
the three event categories, while the QCD multijet prior uncertainty and
central value are taken from the first step.

The $t$-channel single top quark signals are parametrised with a flat prior
representing the coupling strength, and all systematic uncertainties are
treated as described in Section 0.6. The smaller background yields are allowed
to vary in the fit, along with the respective scale uncertainties. The QCD
multijet background is fitted with a flat prior nuisance, while $\ttbar$ and
$\PW\text{+jets}$ backgrounds are left floating within the respective
systematic uncertainties. The $t$-channel $ST_{\PQb,\PQq}$ and
$\ttbar_{\PQb,\PQq}$ processes do not distinguish between topologies depending
on $V_{\PQt\PQd}$ or $V_{\PQt\PQs}$ in the decay, while $ST_{\PQq,\PQb}$ is
sensitive to the different PDFs contributing to the processes. Figure 6 shows
the distributions after the fit procedure has been applied for the muon (left)
and the electron (right) channels.

Figure 6:  Distribution of the multivariate discriminators, comparing data to
simulation normalised after the fit procedure, for the muon channel on the
left and for the electron channel on the right, for 2j1t (upper), 3j1t
(middle), and 3j2t (lower). The vertical lines on the points and the hatched
bands show the experimental and fit uncertainties, respectively. The expected
distribution from the $ST_{\PQq,\PQb}+ST_{\PQb,\PQq}$ processes (multiplied by
a factor of 1000) is shown by the solid blue line. The lower panels show the
ratio of the data to the fit.

The partial and total contributions of the profiled and nonprofiled
uncertainties are given in Table 0.7.

The sources and relative values in percent of the systematic uncertainty in
the measurement of the $ST_{\PQb,\PQb}$cross section. The uncertainties are
broken up into profiled and nonprofiled sources.  Treatment Uncertainty
$\Delta\sigma_{ST_{\PQb,\PQb}}/\sigma$ (%) Profiled Lepton trigger and
reconstruction 0.50 Limited size of simulated event samples 3.13 modelling
0.66 Pileup 0.35 QCD background normalisation 0.08 $\PW\text{+jets}$
composition 0.13 Other backgrounds $\mu_{\mathrm{R}}/\mu_{\mathrm{F}}$ 0.44
PDF for background processes 0.42 tagging 0.73 Total profiled 3.4 Nonprofiled
Integrated luminosity 2.5 JER 2.8 JES 8.0 PDF for signal process 3.8 Signal
$\mu_{\mathrm{R}}/\mu_{\mathrm{F}}$ 2.4 ME-PS matching 3.7 Parton shower scale
6.1 Total nonprofiled 11.5 Total uncertainty 12.0

##  0.8 Results and interpretation

The contributions of each of the three CKM matrix elements to the different
$ST_{\PQb,\PQb}$, $ST_{\PQb,\PQq}$, and $ST_{\PQq,\PQb}$ cross sections,
extracted from the fit procedure, are considered. In the SM, top quarks only
decay to bosons plus , , or quarks, and their branching fractions are
proportional to the magnitude squared of the respective matrix element, as
given in Table 0.5. The fit results are given in terms of two signal strength
parameters: the first, $\mu_{\PQb}$, refers to the $ST_{\PQb,\PQb}$ process,
and the second, $\mu_{\PQs\PQd}$, to the sum of the $ST_{\PQq,\PQb}$ and
$ST_{\PQb,\PQq}$ contributions.

By neglecting terms proportional to $\abs{V_{\PQt\PQd}}^{4}$,
$\abs{V_{\PQt\PQs}}^{4}$, the $ST_{\PQq,\PQb}$ term can be written as
proportional to $\abs{V_{\PQt\PQd}}^{2}+\abs{V_{\PQt\PQs}}^{2}$, with a
contribution of order 5% that depends on
$\abs{V_{\PQt\PQd}}^{2}/\abs{V_{\PQt\PQs}}^{2}$. We consider variations on the
latter contribution as negligible in the analysis. These assumptions can be
justified because of the hierarchy observed in the first two rows of the CKM
matrix. The signal strengths thus become:

$\displaystyle\mu_{\PQb}$
$\displaystyle=\frac{\sigma_{t\text{-ch,}\PQb}^{\text{obs}}\mathcal{B}(\PQt\to\PW\PQb)^{\text{obs}}}{\sigma_{t\text{-ch,}\PQb}\mathcal{B}(\PQt\to\PW\PQb)}$
(4) $\displaystyle\mu_{\PQs\PQd}$
$\displaystyle=\frac{\sigma_{t\text{-ch,}\PQb}^{\text{obs}}\mathcal{B}(\PQt\to\PW\PQs,\PQd)^{\text{obs}}+\sigma_{t\text{-ch},\PQs,\PQd}^{\text{obs}}\mathcal{B}(\PQt\to\PW\PQb)^{\text{obs}}}{\sigma_{t\text{-ch,}\PQb}\mathcal{B}(\PQt\to\PW\PQs,\PQd)+\sigma_{t\text{-ch},\PQs,\PQd}\mathcal{B}(\PQt\to\PW\PQb)},$

where $\mathcal{B}(\PQt\to\PW\PQs,\PQd)$ is the branching fraction for a top
quark to decay to a boson and either an or quark. Henceforth, the “obs” label
will refer to the measured value of a quantity, and the absence of this label
will mean the expected value. Equation (4) shows that the signal strengths are
the ratios of the measured value of a quantity to the expected value.

One can write Eq. (4) more generally in terms of the top quark decay
amplitudes or partial widths. We factorise out the modulus of the matrix
element from the partial width for each quark. Thus, the top quark partial
width to $\PW\PQq$ can be written as
$\Gamma_{\PQq}=\widetilde{\Gamma}_{\PQq}\abs{V_{\PQt\PQq}}^{2}$, where
$\widetilde{\Gamma}_{\PQq}$ is the top quark partial width for
$\abs{V_{\PQt\PQq}}=1$. We further assume that
$\widetilde{\Gamma}_{\PQq}=\widetilde{\Gamma}_{\PQb}$, that any differences
other than the CKM elements are negligible. Using this and the total width
$\Gamma_{\PQt}$ of the top quark, we can write Eq. (4) as:

$\displaystyle\mu_{\PQb}$
$\displaystyle=\frac{\abs{V_{\PQt\PQb}}^{4}_{\text{obs}}\widetilde{\Gamma}_{\PQq}^{\text{obs}}\Gamma_{\PQt}}{\abs{V_{\PQt\PQb}}^{4}\widetilde{\Gamma}_{\PQq}\Gamma_{\PQt}^{\text{obs}}}$
(5) $\displaystyle\mu_{\PQs\PQd}$
$\displaystyle=\frac{\abs{V_{\PQt\PQb}}^{2}_{\text{obs}}\bigl{(}\abs{V_{\PQt\PQs}}^{2}_{\text{obs}}+\abs{V_{\PQt\PQd}}^{2}_{\text{obs}}\bigr{)}\widetilde{\Gamma}_{\PQq}^{\text{obs}}\Gamma_{\PQt}}{\abs{V_{\PQt\PQb}}^{2}\bigl{(}\abs{V_{\PQt\PQs}}^{2}+\abs{V_{\PQt\PQd}}^{2}\bigr{)}\widetilde{\Gamma}_{\PQq}\Gamma_{\PQt}^{\text{obs}}}.$

The first fit extracts the signal strengths $\mu_{\PQb}$ and $\mu_{\PQs\PQd}$,
whose values can be interpreted under different model assumptions. The signal
strengths obtained are:

$\displaystyle\mu_{\PQb}$ $\displaystyle=0.99\pm 0.03\,(\text{stat+prof})\pm
0.12\,(\text{nonprof})$ (6) $\displaystyle\mu_{\PQs\PQd}$ $\displaystyle<87\
\text{at 95\% confidence level (CL),}$

with a correlation factor of $\rho_{\mu_{\PQb},\mu_{\PQs\PQd}}=-0.25$. The
first uncertainty on $\mu_{\PQb}$ is the combination of the statistical and
profiled systematic uncertainties, while the second is due to the nonprofiled
systematic components. The upper limit on $\mu_{\PQs\PQd}$ takes into account
both profiled and nonprofiled systematic uncertainties.

In the following, we describe the signal extraction using the values of the
CKM elements directly as parameters in the fit and applying constraints from
the SM scenario and then two possible beyond-the-SM (BSM) extensions.

###  0.8.1 Measurement in the SM scenario

One can simplify Eq. (4) by assuming the SM unitarity constraint
$\abs{V_{\PQt\PQb}}^{2}+\abs{V_{\PQt\PQd}}^{2}+\abs{V_{\PQt\PQs}}^{2}=1$. The
fit is repeated, taking $\abs{V_{\PQt\PQb}}$ as the single free parameter and
replacing $\abs{V_{\PQt\PQd}}^{2}+\abs{V_{\PQt\PQs}}^{2}$ with
$1-\abs{V_{\PQt\PQb}}^{2}$. In this case, Eq. (4) becomes:

$\displaystyle\mu_{\PQb}$
$\displaystyle=\frac{\abs{V_{\PQt\PQb}}^{4}_{\text{obs}}}{\abs{V_{\PQt\PQb}}^{4}}$
(7) $\displaystyle\mu_{\PQs\PQd}$
$\displaystyle=\frac{\abs{V_{\PQt\PQb}}^{2}_{\text{obs}}\bigl{(}1-\abs{V_{\PQt\PQb}}^{2}_{\text{obs}}\bigr{)}}{\abs{V_{\PQt\PQb}}^{2}\bigl{(}1-\abs{V_{\PQt\PQb}}^{2}\bigr{)}}.$

The fit is only allowed to return values of $\abs{V_{\PQt\PQb}}\,\leq\,1$, and
the constraint
$\abs{V_{\PQt\PQd}}^{2}+\abs{V_{\PQt\PQs}}^{2}=1-\abs{V_{\PQt\PQb}}^{2}$ is
imposed. Because of these constraints, Gaussian behaviour of the uncertainties
cannot be assumed. Instead, pseudo-experiments are generated to evaluate the
impact of nonprofiled uncertainties on the measurement, and the following
confidence intervals are measured at 95% CL:

$\displaystyle\abs{V_{\PQt\PQb}}\,>0.970$ (8)
$\displaystyle\abs{V_{\PQt\PQd}}^{2}+\abs{V_{\PQt\PQs}}^{2}<0.057.$

This measurement is comparable with the previous most precise estimate using
events from Ref. [17], and with the result of the combination of single top
quark measurements in Ref. [29].

###  0.8.2 Measurements for two BSM scenarios

Any BSM contribution potentially enhancing $\abs{V_{\PQt\PQb}}^{2}$,
$\abs{V_{\PQt\PQs}}^{2}$, or $\abs{V_{\PQt\PQd}}^{2}$ can affect top quark
production, decay, or both. Some BSM scenarios predict the presence of
additional quark families. In this case, the CKM matrix is extended due to the
mixing between the SM quarks and the new hypothesised ones. This would imply
that the CKM matrix elements $\abs{V_{\PQt\PQb}}$, $\abs{V_{\PQt\PQs}}$, and
$\abs{V_{\PQt\PQd}}$ would not necessarily satisfy the unitarity constraint of
$\abs{V_{\PQt\PQb}}^{2}+\abs{V_{\PQt\PQs}}^{2}+\abs{V_{\PQt\PQd}}^{2}=1$. If
these BSM quarks are heavier than the top quark, they would alter the CKM
matrix elements without appearing as top quark decay products. They would thus
not contribute directly to the top quark decay width $\Gamma_{\PQt}$, but only
indirectly because of the reduction in the absolute values of the
corresponding SM CKM matrix elements.

For the first BSM scenario, we assume the top quark decays through the same
channels as in the SM case, and that the partial width of each decay only
varies because of a modified CKM matrix element. In this case, by writing
$\Gamma_{\PQt}$ and $\widetilde{\Gamma}_{\PQq}$ as a function of
$\abs{V_{\PQt\PQb}}^{2}$ and $\abs{V_{\PQt\PQd}}^{2}+\abs{V_{\PQt\PQs}}^{2}$,
Eq. (5) becomes:

$\displaystyle\mu_{\PQb}$
$\displaystyle=\frac{\abs{V_{\PQt\PQb}}^{4}_{\text{obs}}}{\abs{V_{\PQt\PQb}}^{4}\bigl{(}\abs{V_{\PQt\PQb}}^{2}_{\text{obs}}+\abs{V_{\PQt\PQs}}^{2}_{\text{obs}}+\abs{V_{\PQt\PQd}}^{2}_{\text{obs}}\bigr{)}}$
(9) $\displaystyle\mu_{\PQs\PQd}$
$\displaystyle=\frac{\abs{V_{\PQt\PQb}}^{2}_{\text{obs}}\bigl{(}\abs{V_{\PQt\PQs}}^{2}_{\text{obs}}+\abs{V_{\PQt\PQd}}^{2}_{\text{obs}}\bigr{)}}{\bigl{(}\abs{V_{\PQt\PQs}}^{2}+\abs{V_{\PQt\PQd}}^{2}\bigr{)}\bigl{(}\abs{V_{\PQt\PQb}}^{2}_{\text{obs}}+\abs{V_{\PQt\PQs}}^{2}_{\text{obs}}+\abs{V_{\PQt\PQd}}^{2}_{\text{obs}}\bigr{)}}.$

In this scenario, the measurement is performed leaving $\abs{V_{\PQt\PQb}}$
and $\abs{V_{\PQt\PQd}}^{2}$ +$\abs{V_{\PQt\PQs}}^{2}$ as free parameters in
the fit, resulting in:

$\displaystyle\abs{V_{\PQt\PQb}}=0.988\pm 0.027\,(\text{stat+prof})\pm
0.043\,(\text{nonprof})$ (10)
$\displaystyle\abs{V_{\PQt\PQd}}^{2}+\abs{V_{\PQt\PQs}}^{2}=0.06\pm
0.05\,(\text{stat+prof})\,^{+0.04}_{-0.03}\,(\text{nonprof}).$

In the second BSM scenario, the top quark partial width is unchanged, but the
total width increases due to additional, undetected decays. In the fit, the
partial widths for decays to known quarks are fixed, and the total width is a
free parameter and allowed to vary. The effects on $\Gamma_{\PQt}$ due to
variations in $\abs{V_{\PQt\PQb}}^{2}$, $\abs{V_{\PQt\PQd}}^{2}$, and
$\abs{V_{\PQt\PQs}}^{2}$ are neglected.

In this scenario, Eq. (5) is modified to:

$\displaystyle\mu_{\PQb}$
$\displaystyle=\frac{\abs{V_{\PQt\PQb}}^{4}_{\text{obs}}\Gamma_{\PQt}}{\abs{V_{\PQt\PQb}}^{4}\Gamma_{\PQt}^{\text{obs}}}$
(11) $\displaystyle\mu_{\PQs\PQd}$
$\displaystyle=\frac{\abs{V_{\PQt\PQb}}^{2}_{\text{obs}}\bigl{(}\abs{V_{\PQt\PQs}}^{2}_{\text{obs}}+\abs{V_{\PQt\PQd}}^{2}_{\text{obs}}\bigr{)}\Gamma_{\PQt}}{\abs{V_{\PQt\PQb}}^{2}\bigl{(}\abs{V_{\PQt\PQs}}^{2}+\abs{V_{\PQt\PQd}}^{2}\bigr{)}\Gamma_{\PQt}^{\text{obs}}}.$

Using $\abs{V_{\PQt\PQb}}^{2}$,
$\abs{V_{\PQt\PQd}}^{2}+\abs{V_{\PQt\PQs}}^{2}$, and
$R_{\Gamma}=\Gamma_{\PQt}^{\text{obs}}/\Gamma_{\PQt}$ as the free parameters
in the fit, we obtain:

$\displaystyle\abs{V_{\PQt\PQb}}=0.988\pm 0.011\,(\text{stat+prof})\pm
0.021\,(\text{nonprof})$ (12)
$\displaystyle\abs{V_{\PQt\PQd}}^{2}+\abs{V_{\PQt\PQs}}^{2}=0.06\pm
0.05\,(\text{stat+prof})\pm 0.04\,(\text{nonprof})$ $\displaystyle
R_{\Gamma}=0.99\pm 0.42\,(\text{stat+prof})\pm 0.03\,(\text{nonprof}).$

The measured correlation factors between the three parameters are
$\rho_{\abs{V_{\PQt\PQb}},\abs{V_{\PQt\PQd}}^{2}}=-0.19$,
$\rho_{\abs{V_{\PQt\PQb}},R_{\Gamma}}=-0.78$, and
$\rho_{R_{\Gamma},\abs{V_{\PQt\PQd}}^{2}}=-0.21$. This measurement is in good
agreement with the other measurements from Refs. [69, 17, 70, 29], which
however make use of the SM assumptions. The results for the second BSM
scenario have a higher statistical precision than those for the first scenario
because of the weaker dependence of the signal strength on
$\abs{V_{\PQt\PQb}}$ for the first scenario.

As mentioned in Section 0.1, constraints on $\abs{V_{\PQt\PQd}}$ and
$\abs{V_{\PQt\PQs}}$ from precision low-energy measurements do not necessarily
hold when BSM particles are present in the relevant Feynman diagram loops.
Theoretical studies have shown that values of $\abs{V_{\PQt\PQs}}$ up to about
$0.2$ are possible in some BSM scenarios [13]. The measurements presented here
establish a model-independent upper limit on $\abs{V_{\PQt\PQd}}$ and
$\abs{V_{\PQt\PQs}}$ by removing any assumed theoretical hypotheses. This will
now allow new interpretations for possible mixing of SM and BSM processes.

Alternative approaches interpret the available single top quark measurements
in terms of different scenarios for modifying the CKM matrix elements (see,
for example, Ref. [32]), obtaining results that are comparable with the
measurements presented in this Letter. Such approaches, however, do not allow
changes in the decay vertex of the top quark, and do not consider possible
similarities in the features of the $ST_{\PQb,\PQq}$ signal and background
processes.

The current analysis improves the precision on $\abs{V_{\PQt\PQb}}$ by 50%
with respect to previous studies [10] by exploiting the $\PQt\PW\PQb$ vertex
in the top quark decay, and is more precise than the combined ATLAS and CMS
measurement using data at $\sqrt{s}=7$ and 8 [29].

##  0.9 Summary

A measurement of the Cabibbo–Kobayashi–Maskawa (CKM) matrix elements
$\abs{V_{\PQt\PQb}}$, $\abs{V_{\PQt\PQd}}$, and $\abs{V_{\PQt\PQs}}$ has been
performed in an event sample enriched in $t$-channel single top quark events,
featuring one muon or electron and jets in the final state. The data are from
proton-proton collisions at $\sqrt{s}=13\TeV$, acquired at the LHC by the CMS
experiment and correspond to an integrated luminosity of $35.9\fbinv$. The
contributions from single top quark processes featuring all three matrix
elements in the production vertex have been considered as separate signal
processes, as well as contributions from decays of single top quarks involving
all three quark families. The yields of the signal processes have been
extracted through a simultaneous fit to data in different selected event
categories, and the values of the CKM matrix elements have been inferred from
the signal strengths, which are the ratios of the measured top quark
$t$-channel cross sections times branching ratios to the expected values. The
signal strengths obtained from the fit are $\mu_{\PQb}=0.99\pm 0.12$, where
the uncertainty includes both the statistical and systematic components, and
$\mu_{\PQs\PQd}<87\ \mathrm{at}\ 95\%$ confidence level (CL).

Under the standard model assumption of CKM unitarity, the values are found to
be $\abs{V_{\PQt\PQb}}>0.970$ and
$\abs{V_{\PQt\PQd}}^{2}+\abs{V_{\PQt\PQs}}^{2}<0.057$, both at $95\%$ CL.

Fits were also performed under two different beyond-the-standard-model
scenarios. In the first, we assume the presence of additional quark families
that are heavier than the top quark. The unitarity constraint for the three
CKM matrix elements no longer holds, but the top quark decays through the same
channels as in the standard model. We assume the partial width of each top
quark decay only varies because of a modified CKM matrix element. The fit
gives:

$\displaystyle\abs{V_{\PQt\PQb}}=0.988\pm 0.051$
$\displaystyle\abs{V_{\PQt\PQd}}^{2}+\abs{V_{\PQt\PQs}}^{2}=0.06\pm 0.06,$

where the uncertainties include both the statistical and systematic
components.

In the second scenario, the top quark width is left unconstrained under the
assumption that the contributions to the total width from the mixing of the
three families are negligible. The corresponding measured values are:

$\displaystyle\abs{V_{\PQt\PQb}}=0.988\pm 0.024,$
$\displaystyle\abs{V_{\PQt\PQd}}^{2}+\abs{V_{\PQt\PQs}}^{2}=0.06\pm 0.06,$
$\displaystyle\frac{\Gamma^{\text{obs}}_{\mathrm{t}}}{\Gamma_{\PQt}}=0.99\pm
0.42,$

where again, both the statistical and systematic uncertainties are included.
The differences among the uncertainties in the presented scenarios are driven
by the difference in the functional dependence of the observed event yields
from the CKM matrix elements. This results in smaller uncertainties in
$\abs{V_{\PQt\PQb}}$ for the case where a fourth–power dependence is
considered with respect to the second–power dependence case.

All results are consistent with each other, and show no deviation with respect
to extrapolations of low-energy measurements. These results are the first
direct, model-independent measurements of the CKM matrix elements for the
third-generation quarks, and provide the best determination of these
fundamental SM parameters via single top quark measurements.

###### 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 centres 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 (Ukraine); STFC (United Kingdom); DOE and NSF (USA).
Individuals have received support from the Marie-Curie programme and the
European Research Council and Horizon 2020 Grant, contract Nos. 675440,
752730, and 765710 (European Union); the Leventis Foundation; the A.P. Sloan
Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science
Policy Office; the Fonds pour la Formation à la Recherche dans l’Industrie et
dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door
Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium)
under the “Excellence of Science – EOS” – be.h project n. 30820817; the
Beijing Municipal Science & Technology Commission, No. Z191100007219010; the
Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the
Deutsche Forschungsgemeinschaft (DFG) under Germany’s Excellence Strategy –
EXC 2121 “Quantum Universe” – 390833306; the Lendület (“Momentum”) Programme
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
programme of the Foundation for Polish Science, cofinanced from European
Union, Regional Development Fund, the Mobility Plus programme 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. 14.W03.31.0026 (Russia); the
Tomsk Polytechnic University Competitiveness Enhancement Program and “Nauka”
Project FSWW-2020-0008 (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 programmes cofinanced by EU-ESF and the Greek NSRF; the
Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University
and the Chulalongkorn Academic into Its 2nd Century Project Advancement
Project (Thailand); the Kavli Foundation; the Nvidia Corporation; the
SuperMicro Corporation; the Welch Foundation, contract C-1845; and the Weston
Havens Foundation (USA).

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##  .10 The CMS Collaboration

Yerevan Physics Institute, Yerevan, Armenia
A.M. Sirunyan${}^{\textrm{\textdagger}}$, A. Tumasyan Institut für
Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, T. Bergauer, M. Dragicevic, J. Erö, A. Escalante Del
Valle, M. Flechl, R. Frühwirth1, M. Jeitler1, N. Krammer, I. Krätschmer, D.
Liko, T. Madlener, I. Mikulec, N. Rad, J. Schieck1, R. Schöfbeck, M. Spanring,
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, T. Kello2, 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, S. Tavernier, W. Van
Doninck, P. Van Mulders Université Libre de Bruxelles, Bruxelles, Belgium
D. Beghin, B. Bilin, B. Clerbaux, G. De Lentdecker, H. Delannoy, B. Dorney, L.
Favart, A. Grebenyuk, A.K. Kalsi, L. Moureaux, A. Popov, N. Postiau, E.
Starling, L. Thomas, C. Vander Velde, P. Vanlaer, D. Vannerom Ghent
University, Ghent, Belgium
T. Cornelis, D. Dobur, I. Khvastunov3, M. Niedziela, C. Roskas, K. Skovpen, M.
Tytgat, W. Verbeke, B. Vermassen, M. Vit Université Catholique de Louvain,
Louvain-la-Neuve, Belgium
G. Bruno, C. Caputo, P. David, C. Delaere, M. Delcourt, A. Giammanco, V.
Lemaitre, J. Prisciandaro, A. Saggio, P. Vischia, J. Zobec Centro Brasileiro
de Pesquisas Fisicas, Rio de Janeiro, Brazil
G.A. Alves, G. Correia Silva, C. Hensel, A. Moraes Universidade do Estado do
Rio de Janeiro, Rio de Janeiro, Brazil
E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato4, E. Coelho, E.M.
Da Costa, G.G. Da Silveira5, D. De Jesus Damiao, C. De Oliveira Martins, S.
Fonseca De Souza, H. Malbouisson, J. Martins6, D. Matos Figueiredo, M. Medina
Jaime7, M. Melo De Almeida, C. Mora Herrera, L. Mundim, H. Nogima, W.L. Prado
Da Silva, P. Rebello Teles, L.J. Sanchez Rosas, A. Santoro, A. Sznajder, M.
Thiel, E.J. Tonelli Manganote4, F. Torres Da Silva De Araujo, A. Vilela
Pereira Universidade Estadual Paulista a, Universidade Federal do ABC b, São
Paulo, Brazil
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, A. Petrov
Beihang University, Beijing, China
W. Fang2, X. Gao2, L. Yuan Department of Physics, Tsinghua University,
Beijing, China
M. Ahmad, Z. Hu, Y. Wang Institute of High Energy Physics, Beijing, China
G.M. Chen8, H.S. Chen8, M. Chen, C.H. Jiang, D. Leggat, H. Liao, Z. Liu, 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 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, 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, H. Saka, 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
A.A. Abdelalim11,12, S. Abu Zeid 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, V. Karimäki, M.S. Kim, R. Kinnunen,
T. Lampén, K. Lassila-Perini, S. Laurila, S. Lehti, T. Lindén, H. Siikonen, E.
Tuominen, J. Tuominiemi Lappeenranta University of Technology, Lappeenranta,
Finland
P. Luukka, T. Tuuva IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
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, B. Lenzi, E. Locci, J. Malcles, J. Rander, A. Rosowsky, M.Ö. Sahin,
A. Savoy-Navarro13, M. Titov, G.B. Yu Laboratoire Leprince-Ringuet,
CNRS/IN2P3, Ecole Polytechnique, Institut Polytechnique de Paris
S. Ahuja, C. Amendola, F. Beaudette, M. Bonanomi, 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. Agram14, J. Andrea, D. Bloch, G. Bourgatte, J.-M. Brom, E.C. Chabert, C.
Collard, E. Conte14, J.-C. Fontaine14, D. Gelé, U. Goerlach, C. Grimault,
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, 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
T. Toriashvili15 Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze10 RWTH Aachen University, I. Physikalisches Institut, Aachen,
Germany
C. Autermann, L. Feld, K. Klein, M. Lipinski, D. Meuser, A. Pauls, M. Preuten,
M.P. Rauch, J. Schulz, M. Teroerde RWTH Aachen University, III. Physikalisches
Institut A, Aachen, Germany
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, 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. 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, 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, L.I. Estevez Banos,
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. Lidrych, K. Lipka,
W. Lohmann20, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, M. Meyer, M.
Missiroli, 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, R.E. Sosa Ricardo, H.
Tholen, O. Turkot, A. Vagnerini, M. Van De Klundert, 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, 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. Reimers, O. Rieger, P. Schleper, S. Schumann, J. Schwandt,
J. Sonneveld, H. Stadie, G. Steinbrück, B. Vormwald, I. Zoi Karlsruher
Institut fuer Technologie, Karlsruhe, Germany
M. Akbiyik, M. Baselga, S. Baur, T. Berger, E. Butz, R. Caspart, T. Chwalek,
W. De Boer, A. Dierlamm, K. El Morabit, N. Faltermann, M. Giffels, A.
Gottmann, F. Hartmann17, C. Heidecker, U. Husemann, M.A. Iqbal, S. Kudella, S.
Maier, S. Mitra, M.U. Mozer, D. Müller, Th. Müller, M. Musich, A. Nürnberg, G.
Quast, K. Rabbertz, D. Savoiu, D. Schäfer, M. Schnepf, M. Schröder, I.
Shvetsov, H.J. Simonis, R. Ulrich, M. Wassmer, M. Weber, C. Wöhrmann, R. Wolf,
S. Wozniewski Institute of Nuclear and Particle Physics (INPP), NCSR
Demokritos, Aghia Paraskevi, Greece
G. Anagnostou, P. Asenov, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas,
G. Paspalaki, A. Stakia National and Kapodistrian University of Athens,
Athens, Greece
M. Diamantopoulou, G. Karathanasis, P. Kontaxakis, A. Manousakis-katsikakis,
A. Panagiotou, I. Papavergou, N. Saoulidou, K. Theofilatos, K. Vellidis, E.
Vourliotis National Technical University of Athens, Athens, Greece
G. Bakas, K. Kousouris, I. Papakrivopoulos, G. Tsipolitis, A. Zacharopoulou
University of Ioánnina, Ioánnina, Greece
I. Evangelou, C. Foudas, P. Gianneios, P. Katsoulis, P. Kokkas, S. Mallios, K.
Manitara, N. Manthos, I. Papadopoulos, J. Strologas, 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, G.
Pasztor, O. Surányi, G.I. Veres Wigner Research Centre for Physics, Budapest,
Hungary
G. Bencze, C. Hajdu, D. Horvath22, F. Sikler, V. Veszpremi, G.
Vesztergombi${}^{\textrm{\textdagger}}$ Institute of Nuclear Research ATOMKI,
Debrecen, Hungary
N. Beni, S. Czellar, J. Karancsi21, 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, N. Dhingra26, R. Gupta, A.
Kaur, M. Kaur, S. Kaur, P. Kumari, M. Lohan, M. Meena, K. Sandeep, S. Sharma,
J.B. Singh, A.K. Virdi University of Delhi, Delhi, India
A. Bhardwaj, B.C. Choudhary, R.B. Garg, M. Gola, S. Keshri, Ashok Kumar, M.
Naimuddin, P. Priyanka, K. Ranjan, Aashaq Shah, R. Sharma Saha Institute of
Nuclear Physics, HBNI, Kolkata, India
R. Bhardwaj27, M. Bharti27, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep27,
D. Bhowmik, S. Dutta, S. Ghosh, B. Gomber28, M. Maity29, K. Mondal, S. Nandan,
A. Purohit, P.K. Rout, G. Saha, S. Sarkar, M. Sharan, B. Singh27, S. Thakur27
Indian Institute of Technology Madras, Madras, India
P.K. Behera, S.C. Behera, P. Kalbhor, A. Muhammad, P.R. Pujahari, A. Sharma,
A.K. Sikdar Bhabha Atomic Research Centre, Mumbai, India
D. Dutta, V. Jha, 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. Dube, B. Kansal, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, A. Rastogi, S.
Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
S. Chenarani, S.M. Etesami, 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,30, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L.
Cristellaa,b, N. De Filippisa,c, M. De Palmaa,b, A. Di Florioa,b, W.
Elmetenaweea,b, L. Fiorea, A. Gelmia,b, G. Iasellia,c, M. Incea,b, S.
Lezkia,b, G. Maggia,c, M. Maggia, J.A. Merlina, G. Minielloa,b, S. Mya,b, S.
Nuzzoa,b, A. Pompilia,b, G. Pugliesea,c, R. Radognaa, A. Ranieria, G.
Selvaggia,b, L. Silvestrisa, F.M. Simonea,b, R. Vendittia, P. Verwilligena
INFN Sezione di Bologna a, Università di Bologna b, Bologna, Italy
G. Abbiendia, C. Battilanaa,b, D. Bonacorsia,b, L. Borgonovia,b, S. Braibant-
Giacomellia,b, R. Campaninia,b, P. Capiluppia,b, A. Castroa,b, F.R. Cavalloa,
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,31, 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,32, S. Costaa,b, A. Di Mattiaa, R. Potenzaa,b, A. Tricomia,b,32,
C. Tuvea,b INFN Sezione di Firenze a, Università di Firenze b, Firenze, Italy
G. Barbaglia, A. Cassesea, R. Ceccarellia,b, V. Ciullia,b, C. Civininia, R.
D’Alessandroa,b, F. Fioria,c, E. Focardia,b, G. Latinoa,b, P. Lenzia,b, M.
Lizzoa,b, M. Meschinia, S. Paolettia, R. Seiditaa,b, G. Sguazzonia, L.
Viliania INFN Laboratori Nazionali di Frascati, Frascati, Italy
L. Benussi, S. Bianco, D. Piccolo INFN Sezione di Genova a, Università di
Genova b, Genova, Italy
M. Bozzoa,b, F. Ferroa, R. Mulargiaa,b, E. Robuttia, S. Tosia,b INFN Sezione
di Milano-Bicocca a, Università di Milano-Bicocca b, Milano, Italy
A. Benagliaa, A. Beschia,b, F. Brivioa,b, V. Cirioloa,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, M. Paganonia,b, D.
Pedrinia, S. Ragazzia,b, T. Tabarelli de Fatisa,b, D. Valsecchia,b,17, 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. Layera,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, 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, A.
Zucchettaa,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, 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, E. Manonia, G. Mantovania,b, V. Mariania,b, M. Menichellia, A.
Rossia,b, A. Santocchiaa,b, D. Spigaa INFN Sezione di Pisa a, Università di
Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy
K. Androsova, P. Azzurria, G. Bagliesia, V. Bertacchia,c, L. Bianchinia, T.
Boccalia, R. Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, S. Donatoa, 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. Rolandia,c, S. Roy
Chowdhurya,c, A. Scribanoa, P. Spagnoloa, R. Tenchinia, G. Tonellia,b, N.
Turinia, A. Venturia, P.G. Verdinia INFN Sezione di Roma a, Sapienza
Università di Roma b, Rome, Italy
F. Cavallaria, M. Cipriania,b, D. Del Rea,b, E. Di Marcoa, M. Diemoza, E.
Longoa,b, P. Meridiania, G. Organtinia,b, F. Pandolfia, R. Paramattia,b, C.
Quarantaa,b, S. Rahatloua,b, C. Rovellia, F. Santanastasioa,b, L. Soffia,b, R.
Tramontanoa,b INFN Sezione di Torino a, Università di Torino b, Torino, Italy,
Università del Piemonte Orientale c, Novara, Italy
N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, N. Bartosika,
R. Bellana,b, A. Belloraa,b, C. Biinoa, A. Cappatia,b, N. Cartigliaa, S.
Comettia, M. Costaa,b, R. Covarellia,b, N. Demariaa, J.R. González Fernándeza,
B. Kiania,b, F. Leggera, C. Mariottia, S. Masellia, E. Migliorea,b, V.
Monacoa,b, E. Monteila,b, M. Montenoa, M.M. Obertinoa,b, G. Ortonaa, L.
Pachera,b, N. Pastronea, M. Pelliccionia, G.L. Pinna Angionia,b, A. Romeroa,b,
M. Ruspaa,c, R. Salvaticoa,b, V. Solaa, A. Solanoa,b, D. Soldia,b, A.
Staianoa, D. Trocinoa,b INFN Sezione di Trieste a, Università di Trieste b,
Trieste, Italy
S. Belfortea, V. Candelisea,b, M. Casarsaa, F. Cossuttia, A. Da Rolda,b, G.
Della Riccaa,b, F. Vazzolera,b, 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 Hanyang University, Seoul, Korea
B. Francois, T.J. Kim, J. Park Korea University, Seoul, Korea
S. Cho, S. Choi, Y. Go, S. Ha, B. Hong, K. Lee, K.S. Lee, J. Lim, J. Park,
S.K. Park, 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
University of Seoul, Seoul, Korea
D. Jeon, 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, A. Rinkevicius, G. Tamulaitis, J. Vaitkus National
Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia
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. Mijuskovic3, N. Raicevic University of Auckland, Auckland, New Zealand
D. Krofcheck University of Canterbury, Christchurch, New Zealand
S. Bheesette, P.H. Butler, P. Lujan National Centre for Physics, Quaid-I-Azam
University, Islamabad, Pakistan
A. Ahmad, M. Ahmad, M.I.M. Awan, 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. 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, T. Niknejad, 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, N. Gorbounov, I. Gorbunov, A.
Kamenev, V. Karjavine, A. Lanev, A. Malakhov, V. Matveev37,38, P. Moisenz, V.
Palichik, V. Perelygin, M. Savina, S. Shmatov, N. Skatchkov, V. Smirnov, 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, 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, CristinaF. Bedoya, J.A. Brochero Cifuentes, C.A. Carrillo
Montoya, M. Cepeda, M. Cerrada, N. Colino, B. De La Cruz, A. Delgado Peris,
J.P. Fernández Ramos, J. Flix, M.C. Fouz, 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, E. Palencia Cortezon, C. Ramón Álvarez, 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,
F. Ricci-Tam, T. Rodrigo, A. Ruiz-Jimeno, L. Russo47, L. Scodellaro, I. Vila,
J.M. Vizan Garcia University of Colombo, Colombo, Sri Lanka
D.U.J. Sonnadara University of Ruhuna, Department of Physics, Matara, Sri
Lanka
W.G.D. Dharmaratna, N. Wickramage CERN, European Organization for Nuclear
Research, Geneva, Switzerland
T.K. Aarrestad, D. Abbaneo, B. Akgun, E. Auffray, G. Auzinger, J. Baechler, P.
Baillon, A.H. Ball, D. Barney, J. Bendavid, M. Bianco, A. Bocci, P. Bortignon,
E. Bossini, 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, M. Deile, R. Di Maria, 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, K. Gill, F.
Glege, L. Gouskos, M. Gruchala, M. Guilbaud, D. Gulhan, J. Hegeman, C.
Heidegger, Y. Iiyama, V. Innocente, T. James, P. Janot, O. Karacheban20, J.
Kaspar, J. Kieseler, M. Krammer1, N. Kratochwil, C. Lange, P. Lecoq, K. Long,
C. Lourenço, L. Malgeri, M. Mannelli, A. Massironi, F. Meijers, S. Mersi, E.
Meschi, F. Moortgat, M. Mulders, J. Ngadiuba, J. Niedziela, S. 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. Rieger, M. Rovere, H. Sakulin, J. Salfeld-Nebgen, S. Scarfi, 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,
G.P. Van Onsem, A. Vartak, M. Verzetti, K.A. Wozniak, 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 ETH Zurich - Institute for
Particle Physics and Astrophysics (IPA), Zurich, Switzerland
M. Backhaus, P. Berger, A. Calandri, N. Chernyavskaya, G. Dissertori, M.
Dittmar, M. Donegà, C. Dorfer, T.A. Gómez Espinosa, C. Grab, D. Hits, W.
Lustermann, R.A. Manzoni, M.T. Meinhard, F. Micheli, P. Musella, F. Nessi-
Tedaldi, F. Pauss, V. Perovic, G. Perrin, L. Perrozzi, S. Pigazzini, M.G.
Ratti, M. Reichmann, C. Reissel, T. Reitenspiess, B. Ristic, D. Ruini, D.A.
Sanz Becerra, M. Schönenberger, L. Shchutska, M.L. Vesterbacka Olsson, R.
Wallny, D.H. Zhu Universität Zürich, Zurich, Switzerland
C. Amsler51, C. Botta, D. Brzhechko, M.F. Canelli, A. De Cosa, R. Del Burgo,
B. Kilminster, S. Leontsinis, V.M. Mikuni, I. Neutelings, G. Rauco, P.
Robmann, K. Schweiger, Y. Takahashi, S. Wertz National Central University,
Chung-Li, Taiwan
C.M. Kuo, W. Lin, A. Roy, T. Sarkar29, 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.
Dozen54, I. Dumanoglu55, G. Gokbulut, EmineGurpinar Guler56, Y. Guler, I.
Hos57, C. Isik, E.E. Kangal58, O. Kara, A. Kayis Topaksu, U. Kiminsu, G.
Onengut, K. Ozdemir59, A.E. Simsek, U.G. Tok, S. Turkcapar, I.S. Zorbakir, C.
Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey
B. Isildak60, G. Karapinar61, M. Yalvac62 Bogazici University, Istanbul,
Turkey
I.O. Atakisi, E. Gülmez, M. Kaya63, O. Kaya64, Ö. Özçelik, S. Tekten65, E.A.
Yetkin66 Istanbul Technical University, Istanbul, Turkey
A. Cakir, K. Cankocak55, Y. Komurcu, S. Sen67 Istanbul University, Istanbul,
Turkey
S. Cerci68, B. Kaynak, S. Ozkorucuklu, D. Sunar Cerci68 Institute for
Scintillation Materials of National Academy of Science of Ukraine, Kharkov,
Ukraine
B. Grynyov National Scientific Center, Kharkov Institute of Physics and
Technology, Kharkov, Ukraine
L. Levchuk University of Bristol, Bristol, United Kingdom
E. Bhal, S. Bologna, J.J. Brooke, D. Burns69, E. Clement, D. Cussans, H.
Flacher, J. Goldstein, G.P. Heath, H.F. Heath, L. Kreczko, B. Krikler, S.
Paramesvaran, T. Sakuma, S. Seif El Nasr-Storey, V.J. Smith, J. Taylor, A.
Titterton Rutherford Appleton Laboratory, Didcot, United Kingdom
K.W. Bell, A. Belyaev70, C. Brew, R.M. Brown, 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 Imperial College, London, United Kingdom
R. Bainbridge, P. Bloch, S. Bonomally, J. Borg, S. Breeze, O. Buchmuller, A.
Bundock, GurpreetSingh CHAHAL71, D. Colling, P. Dauncey, G. Davies, M. Della
Negra, P. Everaerts, G. Hall, G. Iles, M. Komm, J. Langford, L. Lyons, A.-M.
Magnan, S. Malik, A. Martelli, V. Milosevic, A. Morton, J. Nash72, 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, S.N. Webb, D. Winterbottom, A.G. Zecchinelli, S.C. Zenz Brunel
University, Uxbridge, United Kingdom
J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, C.K. Mackay, I.D. Reid, L.
Teodorescu, S. Zahid Baylor University, Waco, USA
A. Brinkerhoff, K. Call, B. Caraway, J. Dittmann, K. Hatakeyama, 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, S.V. Gleyzer, C. Henderson, P. Rumerio, C. West
Boston University, Boston, USA
A. Albert, D. Arcaro, Z. Demiragli, D. Gastler, C. Richardson, J. Rohlf, D.
Sperka, D. Spitzbart, I. Suarez, L. Sulak, D. Zou Brown University,
Providence, USA
G. Benelli, B. Burkle, X. Coubez18, D. Cutts, Y.t. Duh, M. Hadley, U. Heintz,
J.M. Hogan73, K.H.M. Kwok, E. Laird, G. Landsberg, K.T. Lau, J. Lee, M.
Narain, S. Sagir74, R. Syarif, E. Usai, W.Y. Wong, D. Yu, W. Zhang University
of California, Davis, Davis, USA
R. Band, C. Brainerd, R. Breedon, M. Calderon De La Barca Sanchez, M. Chertok,
J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, F. Jensen, W.
Ko${}^{\textrm{\textdagger}}$, O. Kukral, R. Lander, M. Mulhearn, D. Pellett,
J. Pilot, M. Shi, D. Taylor, K. Tos, M. Tripathi, 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, O.R. Long, N. Manganelli, M. Olmedo Negrete, M.I. Paneva, W. Si,
S. Wimpenny, B.R. Yates, Y. Zhang University of California, San Diego, La
Jolla, USA
J.G. Branson, P. Chang, S. Cittolin, S. Cooperstein, N. Deelen, M. Derdzinski,
J. Duarte, R. Gerosa, D. Gilbert, B. Hashemi, 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, 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
J. Alison, 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, E. MacDonald, T. Mulholland, R. Patel, A. Perloff, K.
Stenson, K.A. Ulmer, S.R. Wagner Cornell University, Ithaca, USA
J. Alexander, Y. Cheng, J. Chu, A. Datta, A. Frankenthal, K. Mcdermott, J.R.
Patterson, D. Quach, 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, D. Berry, J. Berryhill, P.C. Bhat, K.
Burkett, J.N. Butler, A. Canepa, G.B. Cerati, H.W.K. Cheung, F. Chlebana, M.
Cremonesi, V.D. Elvira, J. Freeman, Z. Gecse, E. Gottschalk, L. Gray, D.
Green, S. Grünendahl, O. Gutsche, J. Hanlon, R.M. Harris, S. Hasegawa, R.
Heller, J. Hirschauer, B. Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, T.
Klijnsma, 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. Pena44, F. Ravera, A. Reinsvold Hall, L. Ristori,
B. Schneider, E. Sexton-Kennedy, N. Smith, A. Soha, W.J. Spalding, L. Spiegel,
S. Stoynev, J. Strait, L. Taylor, S. Tkaczyk, N.V. Tran, L. Uplegger, E.W.
Vaandering, R. Vidal, M. Wang, H.A. Weber, A. Woodard University of Florida,
Gainesville, USA
D. Acosta, P. Avery, D. Bourilkov, L. Cadamuro, V. Cherepanov, F. Errico, R.D.
Field, D. Guerrero, B.M. Joshi, M. Kim, J. Konigsberg, A. Korytov, K.H. Lo, K.
Matchev, N. Menendez, G. Mitselmakher, D. Rosenzweig, K. Shi, J. Wang, S.
Wang, X. Zuo Florida 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, R.R. Betts, R. Cavanaugh, X. Chen, S. Dittmer, O.
Evdokimov, C.E. Gerber, D.A. Hangal, D.J. Hofman, V. Kumar, C. Mills, G. Oh,
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. Bilki56, K. Dilsiz75, S. Durgut, R.P. Gandrajula, M.
Haytmyradov, V. Khristenko, O.K. Köseyan, J.-P. Merlo, A. Mestvirishvili76, A.
Moeller, J. Nachtman, H. Ogul77, Y. Onel, F. Ozok78, A. Penzo, C. Snyder, E.
Tiras, J. Wetzel, K. Yi79 Johns Hopkins University, Baltimore, USA
B. Blumenfeld, A. Cocoros, N. Eminizer, A.V. Gritsan, W.T. Hung, S. Kyriacou,
P. Maksimovic, C. Mantilla, J. Roskes, M. Swartz, T.Á. Vámi The University of
Kansas, Lawrence, USA
C. Baldenegro Barrera, P. Baringer, A. Bean, S. Boren, 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, A.C. Mignerey, S. Nabili, M. Seidel, A. Skuja, S.C.
Tonwar, L. Wang, K. Wong Massachusetts Institute of Technology, Cambridge, USA
D. Abercrombie, B. Allen, R. Bi, S. Brandt, W. Busza, I.A. Cali, 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
R.M. Chatterjee, A. Evans, S. Guts${}^{\textrm{\textdagger}}$, P. Hansen, J.
Hiltbrand, Sh. Jain, Y. Kubota, Z. Lesko, J. Mans, M. Revering, R. Rusack, R.
Saradhy, N. Schroeder, N. Strobbe, M.A. Wadud University of Mississippi,
Oxford, USA
J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA
K. Bloom, S. Chauhan, D.R. Claes, C. Fangmeier, L. Finco, F. Golf, 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, B.
Marzocchi, D.M. Morse, V. Nguyen, T. Orimoto, L. Skinnari, A. Tishelman-
Charny, T. Wamorkar, B. Wang, A. Wisecarver, D. Wood Northwestern University,
Evanston, USA
S. Bhattacharya, J. Bueghly, G. Fedi, A. Gilbert, T. Gunter, K.A. Hahn, N.
Odell, M.H. Schmitt, K. Sung, M. Velasco University of Notre Dame, Notre Dame,
USA
R. Bucci, N. Dev, R. Goldouzian, M. Hildreth, K. Hurtado Anampa, C. Jessop,
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Meng, Y. Musienko37, R. Ruchti, P. Siddireddy, G. Smith, S. Taroni, M. Wayne,
A. Wightman, M. Wolf The Ohio State University, Columbus, USA
J. Alimena, B. Bylsma, B. Cardwell, L.S. Durkin, B. Francis, C. Hill, W. Ji,
A. Lefeld, T.Y. Ling, B.L. Winer Princeton University, Princeton, USA
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, D. Stickland, C. Tully University
of Puerto Rico, Mayaguez, USA
S. Malik, S. Norberg Purdue University, West Lafayette, USA
A. Barker, V.E. Barnes, R. Chawla, S. Das, L. Gutay, M. Jones, A.W. Jung, B.
Mahakud, D.H. Miller, G. Negro, N. Neumeister, C.C. Peng, S. Piperov, H. Qiu,
J.F. Schulte, N. Trevisani, F. Wang, R. Xiao, W. Xie Purdue University
Northwest, Hammond, USA
T. Cheng, J. Dolen, N. Parashar Rice University, Houston, USA
A. Baty, U. Behrens, S. Dildick, 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, 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, I. Laflotte, A. Lath, R. Montalvo, K. Nash,
M. Osherson, S. Salur, S. Schnetzer, S. Somalwar, R. Stone, S. Thomas
University of Tennessee, Knoxville, USA
H. Acharya, A.G. Delannoy, S. Spanier Texas A&M University, College Station,
USA
O. Bouhali80, M. Dalchenko, A. Delgado, R. Eusebi, J. Gilmore, T. Huang, T.
Kamon81, H. Kim, S. Luo, S. Malhotra, D. Marley, R. Mueller, D. Overton, L.
Perniè, D. Rathjens, A. Safonov Texas Tech University, Lubbock, USA
N. Akchurin, J. Damgov, F. De Guio, V. Hegde, S. Kunori, K. Lamichhane, S.W.
Lee, T. Mengke, S. Muthumuni, T. Peltola, S. Undleeb, I. Volobouev, Z. Wang,
A. Whitbeck Vanderbilt University, Nashville, USA
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, J. Hakala, 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
K. Black, T. Bose, J. Buchanan, C. Caillol, D. Carlsmith, S. Dasu, I. De
Bruyn, L. Dodd, C. Galloni, H. He, M. Herndon, A. Hervé, U. Hussain, A.
Lanaro, A. Loeliger, R. Loveless, J. Madhusudanan Sreekala, A. Mallampalli, D.
Pinna, T. Ruggles, A. Savin, V. Sharma, W.H. Smith, D. Teague, S. Trembath-
reichert †: Deceased
1: Also at Vienna University of Technology, Vienna, Austria
2: Also at Université Libre de Bruxelles, Bruxelles, Belgium
3: Also at IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
4: Also at Universidade Estadual de Campinas, Campinas, Brazil
5: Also at Federal University of Rio Grande do Sul, Porto Alegre, Brazil
6: Also at UFMS, Nova Andradina, Brazil
7: Also at Universidade Federal de Pelotas, Pelotas, Brazil
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 Helwan University, Cairo, Egypt
12: Now at Zewail City of Science and Technology, Zewail, Egypt
13: Also at Purdue University, West Lafayette, USA
14: Also at Université de Haute Alsace, Mulhouse, France
15: Also at Tbilisi State University, Tbilisi, Georgia
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 G.H.G. Khalsa College, Punjab, India
27: Also at Shoolini University, Solan, India
28: Also at University of Hyderabad, Hyderabad, India
29: Also at University of Visva-Bharati, Santiniketan, India
30: Now at INFN Sezione di Bari a, Università di Bari b, Politecnico di Bari
c, Bari, Italy
31: Also at Italian National Agency for New Technologies, Energy and
Sustainable Economic Development, Bologna, Italy
32: Also at Centro Siciliano di Fisica Nucleare e di Struttura Della Materia,
Catania, 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 Department of Physics, Tsinghua University, Beijing, China,
Beijing, China
55: Also at Near East University, Research Center of Experimental Health
Science, Nicosia, Turkey
56: Also at Beykent University, Istanbul, Turkey, Istanbul, Turkey
57: Also at Istanbul Aydin University, Application and Research Center for
Advanced Studies (App. & Res. Cent. for Advanced Studies), Istanbul, Turkey
58: Also at Mersin University, Mersin, Turkey
59: Also at Piri Reis University, Istanbul, Turkey
60: Also at Ozyegin University, Istanbul, Turkey
61: Also at Izmir Institute of Technology, Izmir, Turkey
62: Also at Bozok Universitetesi Rektörlügü, Yozgat, Turkey
63: Also at Marmara University, Istanbul, Turkey
64: Also at Milli Savunma University, Istanbul, Turkey
65: Also at Kafkas University, Kars, Turkey
66: Also at Istanbul Bilgi University, Istanbul, Turkey
67: Also at Hacettepe University, Ankara, Turkey
68: Also at Adiyaman University, Adiyaman, Turkey
69: Also at Vrije Universiteit Brussel, Brussel, Belgium
70: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
71: Also at IPPP Durham University, Durham, United Kingdom
72: Also at Monash University, Faculty of Science, Clayton, Australia
73: Also at Bethel University, St. Paul, Minneapolis, USA, St. Paul, USA
74: Also at Karamanoğlu Mehmetbey University, Karaman, Turkey
75: Also at Bingol University, Bingol, Turkey
76: Also at Georgian Technical University, Tbilisi, Georgia
77: Also at Sinop University, Sinop, Turkey
78: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey
79: Also at Nanjing Normal University Department of Physics, Nanjing, China
80: Also at Texas A&M University at Qatar, Doha, Qatar
81: Also at Kyungpook National University, Daegu, Korea, Daegu, Korea