B2G-17-003

$HeadURL:svn+ssh://svn.cern.ch/reps/tdr2/papers/B2G-17-003/trunk/B2G-17-003.tex$
$Id:B2G-17-003.tex4472712018-02-2117:03:21Zvorobiev$

B2G-17-003

# Search for pair production of vector-like quarks in the $\PQb\PW\PAQb\PW$
channel from proton-proton collisions at $\sqrt{s}=13\TeV$

###### Abstract

A search is presented for the production of vector-like quark pairs,
$\mathrm{T}\overline{\mathrm{T}}$ or $\mathrm{Y}\overline{\mathrm{Y}}$, with
electric charge of $2/3$ ($\mathrm{T}$) or $-4/3$ ($\mathrm{Y}$), in proton-
proton collisions at $\sqrt{s}=13\TeV$. The data were collected by the CMS
experiment at the LHC in 2016 and correspond to an integrated luminosity of
35.8. The $\mathrm{T}$ and $\mathrm{Y}$ quarks are assumed to decay
exclusively to a boson and a quark. The search is based on events with a
single isolated electron or muon, large missing transverse momentum, and at
least four jets with large transverse momenta. In the search, a kinematic
reconstruction of the final state observables is performed, which would permit
a signal to be detected as a narrow mass peak ($\approx$7% resolution). The
observed number of events is consistent with the standard model prediction.
Assuming strong pair production of the vector-like quarks and a 100% branching
fraction to $\PQb\PW$, a lower limit of 1295at 95% confidence level is set on
the $\mathrm{T}$ and $\mathrm{Y}$ quark masses.

##  0.1 Introduction

Vector-like quarks (VLQs) are hypothetical spin-1/2 fermions, whose left- and
right-handed components transform in the same way under the standard model
(SM) symmetries, and hence have vector couplings. Nonchiral VLQs appear in a
number of beyond-the-SM scenarios, such as “Randall–Sundrum” and other extra-
dimensional models [1, 2]; the beautiful mirrors [3], little Higgs [4, 5, 6,
7, 8], and composite Higgs [9] models; grand unified theories [10]; and also
other models that provide insights into the SM flavor structure [11]. These
models provide possible solutions to a number of problems, such as electroweak
symmetry breaking, a poor general fit to the precision electroweak data, the
origin of flavor patterns, and the hierarchy problem. In particular, the
hierarchy problem, namely the instability within the SM of the Higgs boson
mass parameter to quantum corrections, can be solved through the introduction
of VLQ contributions that cancel the contributions from the top quark.

In general, VLQs T, with charge $+$2/3, are expected to mix significantly only
with the top quark, leading to the dominant $\mathrm{T}$ quark decay
$\mathrm{T}\to\PQb\PW$ [12]. We consider the case in which this decay has a
branching fraction $\mathcal{B}(\mathrm{T}\to\PQb\PW)=100\%$. Also in some
models [13], a VLQ $\mathrm{Y}$ with an electric charge of $-$4/3 is
predicted, either with or without the presence of a $\mathrm{T}$ VLQ. The
$\mathrm{Y}$ quark is expected to decay with a 100% branching fraction via the
same $\PQb\PW$ channel. Since jets originating from the hadronization of
quarks and antiquarks are not distinguished in this analysis, the results
presented apply equally to the strong pair production of both $\mathrm{T}$ and
$\mathrm{Y}$ VLQs. We consider the case where either only $\mathrm{T}$ quarks
or only $\mathrm{Y}$ quarks are produced. This assumption produces a more
conservative estimation of the lower mass limit on VLQs. Throughout the rest
of this paper, we will use $\mathrm{T}$ to represent both the $\mathrm{T}$ and
$\mathrm{Y}$ VLQs.

In this paper, results are presented of a search for the strong pair
production of heavy VLQs and their subsequent decays through the signal
channel

$\mathrm{T}\overline{\mathrm{T}}\to\PQb\PW\PAQb\PW\to\PQb\ell\nu\PAQb\PQq\PAQq^{\prime}$

in proton-proton (pp) collisions at $\sqrt{s}=13$using the CMS detector at the
CERN LHC, where $\ell$ is an electron or muon from the leptonic decay of one
of the W bosons, and $\PQq$ and $\PAQq^{\prime}$ are the quark and antiquark
from the hadronic decay of the other W boson. The analyzed data set
corresponds to an integrated luminosity of 35.8. This analysis is an extension
to higher mass values of an earlier CMS search for the $\mathrm{T}$ quark at
$\sqrt{s}=8$. Both the previous analysis and the present one are based on a
kinematic reconstruction with a constrained fit to the $\PQb\PW\PAQb\PW$ final
state in the signal decay channel shown above. Kinematic reconstruction
enables detection of the signal as a narrow mass peak. The previous results
were combined with other CMS $\mathrm{T}$ quark searches in Ref. [14]. The
present observed lower mass limits for a $\mathrm{T}$ quark decaying 100% via
the bW channel are 920for CMS [14] at $\sqrt{s}=8$, and 770at 8 [15] and
1350at 13for ATLAS [16].

The search strategy requires that one of the $\PW$ bosons decays leptonically,
producing an electron or a muon accompanied by a neutrino, and the other
decays hadronically to a quark-antiquark pair. We select events with a single
isolated muon or electron, missing transverse momentum, and at least four jets
with high transverse momenta, arising from the hadronization of the quarks in
the final state. We classify such events as $\mu$+jets or e+jets.

We perform a constrained kinematic fit on each selected event for the signal
decay process shown above. The full kinematic quantities of the final state
are reconstructed, and the invariant mass of the $\mathrm{T}$ quark,
$m_{\text{reco}}$, is obtained. We consider also cases when W bosons decaying
hadronically at high Lorentz boosts are reconstructed as single jets. Such
merged jets are then resolved into two subjets by employing jet substructure
techniques based on the“soft drop” grooming algorithm [17]. These resolved
subjets are counted individually when selecting four-jet final states and
contribute separately in the kinematic fit (see Section 0.5). Events with
leptonically decaying W bosons include those decaying into a $\tau$ lepton (in
the decay sequence $\PW\to\tau+\nu,\,\tau\to\ell+2\nu)$. They are treated in
the same way as events with direct decays to muons or electrons.

##  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
superconducting solenoid volume are a silicon pixel and strip tracker, a lead
tungstate crystal electromagnetic calorimeter (ECAL) with preshower detector,
and a brass and scintillator hadron calorimeter (HCAL), each composed of a
barrel and two endcap sections. Forward calorimeters extend the pseudorapidity
[18] coverage provided by the barrel and endcap detectors. The detector is
nearly hermetic, allowing for momentum balance measurements in the plane
transverse to the beam direction. Muons are detected in gas-ionization
chambers embedded in the steel flux-return yoke outside the solenoid.

A more detailed description of the CMS detector, together with a definition of
the coordinate system used and the relevant kinematic variables, can be found
in Ref. [18].

##  0.3 Event samples

The analysis is based on integrated luminosities of 35.8in the muon channel
and 35.6in the electron channel. The trigger providing the muon data sample
requires the presence of at least one muon with $\pt>50$and pseudorapidity
$\abs{\eta}<2.5$. For the electron data sample, events are required to have a
single isolated electron with $\pt>32$and $\abs{\eta}<2.1$.

Simulated event samples are used to estimate the signal efficiencies and
background contributions. The following background production processes are
modeled: $\ttbar$+jets; W+jets and Z+jets (single boson production); single
top quark via the tW, $s$\- and $t$-channel processes; WW, WZ, and ZZ (diboson
production); and quantum chromodynamic (QCD) multijet production. The dominant
background is from $\ttbar$+jets production. All other background processes
are collectively referred to as non-$\ttbar$. The non-$\ttbar$ background
excluding multijets is called the electroweak background.

The $\ttbar+\text{jets}$ events are generated using the v2.0 [19, 20, 21, 22]
event generator. The diboson samples are produced using the 8.205 [23]
generator. The W+jets, Z+jets, and QCD multijet simulated events are produced
with the generator v2.2.2 [24]. Single top quark events are generated with and
.

The simulated $\mathrm{T}\overline{\mathrm{T}}$ signal events are generated
with at leading order for $\mathrm{T}$ quark masses from 800 to 1600in
100steps. The total $\mathrm{T}\overline{\mathrm{T}}$ inclusive cross section
($\Pg\Pg\to\mathrm{T}\overline{\mathrm{T}}+X$) is computed for each
$\mathrm{T}$ quark mass value at next-to-next-to-leading order, using a soft-
gluon resummation with next-to-next-to-leading-logarithmic accuracy [25].
Signal samples are produced in the narrow-width approximation in which the
width of the generated $\mathrm{T}$ quark mass distribution of 1is much less
than the mass resolution of the detector.

The generated events are processed through the CMS detector simulation based
on [26]. Additional minimum-bias events, generated with , are superimposed on
the hard-scattering events to simulate multiple inelastic pp collisions in the
same or nearby beam crossings (pileup). The simulated events are weighted to
reproduce the distribution of the number of pileup interactions observed in
data, with an average of 23 collisions per beam crossing. All samples have
been generated with the NNPDF 3.0 set [27] of parton distribution functions
(PDFs), using the tune CUETP8M1. is used to shower and hadronize all generated
partons.

##  0.4 Event reconstruction

Events are reconstructed using a particle-flow (PF) algorithm [28] that
combines information from all the subdetectors: tracks in the silicon tracker
and energy deposits in the ECAL and HCAL, as well as signals in the preshower
detector and the muon system. This procedure categorizes all particles into
five types: muons, electrons, photons, and charged and neutral hadrons. An
energy calibration is performed separately for each particle type.

Muon candidates are identified by multiple reconstruction algorithms based on
hits in the silicon tracker and signals in the muon system. The standalone-
muon algorithm uses only information from the muon chambers. The silicon
tracker muon algorithm starts from tracks found in the silicon tracker and
then associates them with matching signals in the muon detectors. In the
global-muon algorithm, for each standalone-muon track a matching tracker muon
is found by comparing parameters of the two tracks propagated onto a common
surface. A global-muon track is fitted by combining hits from the silicon
tracker muon and the standalone-muon track, using the Kalman-filter technique
[29]. The PF algorithm uses global muons.

Electron candidates are reconstructed from clusters of energy deposited in the
ECAL matched with tracks in the silicon tracker. Electron tracks are
reconstructed using a dedicated modeling of the electron energy loss and are
fitted with a Gaussian sum filter algorithm. Finally, electrons are further
distinguished from charged hadrons using a multivariate approach [30].

Charged leptons, originating from decays of heavy VLQs, are expected to be
isolated from nearby jets. Therefore, a relative isolation parameter
($I_{\text{rel}}$) is used, which is defined as the sum of the of charged
hadrons, neutral hadrons, and photons in a cone with distance parameter
$\Delta R=\sqrt{\smash[b]{(\Delta\phi)^{2}+(\Delta\eta)^{2}}}$ around the
lepton direction, where $\Delta\phi$ and $\Delta\eta$ are the azimuthal and
pseudorapidity differences, divided by the lepton . The isolation cone radius
is taken as $\Delta R=0.4$ for muons. Pileup corrections to $I_{\text{rel}}$
are computed using tracks from reconstructed vertices [29]. For electrons,
$\Delta R=0.3$ and pileup corrections are calculated using jet effective areas
[31, 32] separately for the barrel and endcap regions.

Particles found by the PF algorithm are clustered into jets using the PF jet
identification procedure [28]. Using the charged-hadron subtraction (CHS)
algorithm, charged hadrons associated with pileup vertices are not considered,
and particles that are identified as isolated leptons are removed from the jet
clustering procedure. In the analysis, two types of jets are used: jets
reconstructed using the anti-algorithm [33] with distance parameters of either
R = 0.4 (AK4) or 0.8 (AK8), as implemented in v3.0.1 [34, 35]. An event-by-
event jet area-based correction [36, 37, 31, 32] is applied to remove on a
statistical basis pileup contributions that are not already removed by the CHS
procedure.

Since most jet constituents are identified and reconstructed with close to a
correct energy by the PF algorithm, only a small residual energy correction
must be applied to each jet. These corrections were obtained as a function of
jet and $\eta$ from a comparison of -based CMS Monte Carlo (MC) simulation
[38] and collision data. Jet energy corrections (JEC) are applied to each jet
as a function of and $\eta$.

For the identification of jets originating from the hadronization of a $\PQb$
quark (-tagged jets) we use the combined secondary vertex (CSVv2) algorithm
[39]. This provides $\PQb$ tagging identification by combining information
about impact parameter significance, secondary vertex reconstruction, and jet
kinematic distributions. We use two operating points: medium (CSVM), with a
mistagging rate of 1%, and loose (CSVL), with a 10% mistagging rate, for which
the efficiencies of correctly tagging jets coming from quark hadronization are
66% and 82%, respectively [39]. The differences in the performance of the
tagging algorithm in data and MC simulation are accounted for by data/MC scale
factors (SFs).

The missing transverse momentum in an event, , is defined as the magnitude of
the missing transverse momentum vector, which is the projection on the plane
perpendicular to the beams of the negative vector sum of the momenta of all
reconstructed particles in the event. The vertex with the highest sum of
squared of all associated tracks is taken as the hard-scattering primary
vertex.

##  0.5 Event selection and mass reconstruction

Selected events are required to contain exactly one charged lepton (muon or
electron). Muon candidates are required to have $\pt>55$and $\abs{\eta}<2.4$.
The relative muon isolation parameter must satisfy $I_{\text{rel}}<0.15$.
Selected electrons should have $\abs{\eta}<2.1$. To ensure that the e+jets
channel covers a similar kinematic phase space to the $\mu$+jets channel,
electron candidates must satisfy the same $\pt>55\GeV$ requirement. Simulation
shows that lowering the threshold would not improve the signal significance.
Events with a second more loosely identified electron or muon, with
$\pt>20\GeV$ and $\abs{\eta}<2.5$ (2.4) for electrons (muons), are vetoed.

At the next step, we select a collection of jets that are used as input to the
kinematic fit. The collection includes AK4 jets that have $\pt>$ 30and
$\abs{\eta}<2.4$, and AK8 jets that satisfy $\pt>$ 200and $\abs{\eta}<2.4$. A
selected event must have either at least four AK4 jets, or at least three AK4
jets and at least one AK8 jet for the case where the AK8 jet overlaps an AK4
jet (see explanations below). This is needed to satisfy the requirement to
have at least four jets in the final jet collection used for the kinematic
fit.

As the mass of a heavy VLQ increases, the reconstructed topology of its decay
is modified by the overlapping and merging of jets owing to the high Lorentz
boosts its decay products receive. The quark pair from the hadronically
decaying W boson becomes increasingly collimated, producing overlapping
hadronic showers that cannot be resolved as separate jets. This precludes
performing constrained kinematic fits that use jets as proxies for the final-
state quarks in the signal decay process.

The AK8 jets are used to identify the merged hadronic W boson decays by
applying the “soft drop” (SD) grooming algorithm [17], with parameters
$z_{\text{cut}}=0.1$ and $\beta=0$. This procedure removes soft and wide-angle
radiation from jets and resolves the internal structure of the wide jet into
two distinct subjets, associated with the underlying W boson decay. The JECs
that are applied to the AK8 jets are propagated to the pair of subjets by
scaling them so that the sum of their four-momenta is equal to the parent AK8
jet four-momentum. The groomed jet mass, called the soft drop mass,
$m_{\mathrm{SD}}$, is taken as the invariant mass of the constituents of the
AK8 jet with the SD algorithm applied, and thus is equal to the invariant mass
of the two subjets. It is required to be within the W boson mass window
$60<m_{\mathrm{SD}}<100\GeV$, in which case the AK8 jet is labeled “W-tagged”.

For each W-tagged AK8 jet, representing an identified footprint of a highly
boosted, hadronically decaying W boson, we search for the corresponding
footprint of the same W boson decay in the AK4 jet collection. This is done by
trying to match a W-tagged AK8 jet to an AK4 jet or to the vector sum of a
pair of nearby AK4 jets for which $\DR\mathrm{(AK8,\,AK4)}<0.8$. Since the
opening angle of AK8 subjets, resolved by the SD algorithm, can go down up to
$\DR=0.15$, the system of the two subjets represents a more accurate
assignment of jet constituents to two separate subjets compared to the
clustering into two AK4 jets, with their more coarse threshold of $\DR=0.4$. A
match requires $\DR{(AK8,\,AK4)}=\DR_{\text{match}}<0.05$. Matching with a
pair of AK4 jets is preferred to a matching with only one AK4 jet, when the
$\DR_{\text{match}}$ value for that pair is smaller than the values for any of
the single jets in the pair. In this case matching with the pair (represented
by the vector sum of the two AK4 momenta) provides the best association of
AK4/AK8 jets.

A matched AK4 jet is replaced by the two subjets of the W-tagged AK8 jet, thus
using the full kinematic information obtained by the W tagging and including
that into a jet collection used for the kinematic fit. This procedure results
in a hybrid jet collection, consisting of AK4 jets left unmatched and subjets
of W-tagged AK8 jets, thus excluding the possibility of double counting the
jets later used as input to the kinematic fit.

Only the jets in the hybrid collection are used in the rest of the analysis. A
set of preselection requirements is now applied to the event:

  * •

The missing transverse momentum in the event must satisfy $\ptmiss>30\GeV$.
This requirement is designed to both select final states containing neutrino
and suppress QCD multijet background contribution.

  * •

Each of the jets must have $\pt>30$and $\abs{\eta}<2.4$ (these requirements
were not applied to the newly included W-tagged subjets).

  * •

Jets too close to the lepton direction are discarded by requiring
$\DR(\text{jet},\,\ell)>0.4$.

  * •

There must be at least 4 remaining jets in the event after the previous
criteria.

  * •

The two highest-jets must satisfy $\pt>100$ and 70 , respectively.

Events that pass all these requirements are used as input to the kinematic
fit, which is performed using the HitFit package [40]. This fitting program
was developed by the D0 experiment [41] for the measurement of the top quark
mass in the lepton+jets channel. It contains a fitting engine, which minimizes
a $\chi^{2}$ quantity subject to a set of constraints, and an interface.

The input to the fitting engine comprises the two-dimensional vector and the
measured three-dimensional momenta of the charged lepton and four jets. The
four quarks in the final state of the signal decay process manifest themselves
as jets whose measured three-momenta are used as estimates of the quark
momenta. The in the event is used as an estimate of the transverse momentum of
the neutrino. The unmeasured longitudinal component of the neutrino momentum
is calculated from one of the kinematic constraints shown in Eqs. (1) and (3)
below.

The fit is performed by minimizing a $\chi^{2}$ computed from the differences
between the measured momentum components and their fitted values, divided by
the corresponding uncertainties, summed over all the reconstructed objects in
the final state. The fit is subject to the following constraints:

$\displaystyle m(\ell\Pgn)$ $\displaystyle=m_{\PW},$ (1) $\displaystyle
m(\cPq\cPaq^{\prime})$ $\displaystyle=m_{\PW},$ (2) $\displaystyle
m(\ell\Pgn\cPqb)$ $\displaystyle=m(\cPq\cPaq^{\prime}\cPqb)=m_{\text{reco}},$
(3)

where $m_{\PW}$ is the $\PW$ boson mass [42], $\ell$ stands for electron or
muon, and $\ell$, $\Pgn$, $\cPqb$ can denote either a particle or
antiparticle. Equation (2) requires that the invariant mass of the quark-
antiquark pair equals the W boson mass. Equation (3) demands that the
reconstructed invariant masses $m_{\text{reco}}$ of the two produced
$\mathrm{T}$ quarks are equal. After one constraint is used for the
calculation of the longitudinal neutrino momentum, two constraints are left.
To check to what extent the assumed kinematic hypothesis is compatible with
the fitted momenta, a so-called “goodness-of-fit” is calculated, given by the
probability $P(\chi^{2}\geq\chi^{2}_{\text{min}})$ for the
$\chi^{2}_{\text{min}}$ value obtained after minimization.

For events with exactly 4 jets, all jet permutations in which jets are
assigned specific quark roles in the final state of the signal process are
prepared by the HitFit interface and entered in turn into the fitting engine.
If there are more than four jets in an event passing the jet requirements,
then the five jets with the highest are considered and all permutations of
four jets out of five are used as input to the fitter. The calculation of the
longitudinal component of the neutrino momentum has a two-fold ambiguity from
solving a quadratic equation. This doubles the number of fitted combinations,
based on the jet permutations. At the end of the fitting process, HitFit
delivers information about 24 (120) fitted permutations for the case of 4 (5)
jets.

After the event fitting is done, we have to decide which fitted combination
must be chosen to represent the final state of the signal process. To reduce
the number of accidental combinatoric assignments, we use information on
tagging and W tagging. Pairs of -tagged subjets (if available) are assigned to
the hadronic W boson decay. To identify the most likely lepton+4 jets
combination arising from the decay chain of the signal process, we inspect
each fitted combination in turn, proceeding as follows:

  * •

In each fit combination, two jets are taken to be the jets from the
$\mathrm{T}$ and $\overline{\mathrm{T}}$ decays. We call $\mathrm{b_{l}}$ the
jet accompanying the leptonic W boson decay, and $\mathrm{b_{h}}$ the jet
accompanying the hadronic W boson decay. Combinations in which neither of
these jets is b-tagged or only one has a CSVL tag are rejected.

  * •

The four jets in the fitted combination, designated in the order:
$\mathrm{b_{h}}$ jet, $\mathrm{b_{l}}$ jet, highest-jet in the hadronic W
boson decay, second-highest-jet in the hadronic W boson decay, must satisfy
the requirements $\pt>200,100,100$, and 30, respectively.

  * •

For each fitted jet combination a variable $S_{\mathrm{T}}$ is calculated,
defined as the scalar sum of and the transverse momenta of the lepton and the
four jets in that combination:
$S_{\mathrm{T}}=\ptmiss+\pt^{\ell}+\pt^{J_{1}}+\pt^{J_{2}}+\pt^{J_{3}}+\pt^{J_{4}}$,
where $J_{i}$ (with $i=$ 1 to 4) refers to the four jets and $S_{\mathrm{T}}$
is evaluated using the measured momenta. To select hard-scattering processes
resulting in the production of heavy objects, we require
$S_{\mathrm{T}}>1000\GeV$.

  * •

$S_{\mathrm{L}}^{\text{fit}}/S_{\mathrm{T}}^{\text{fit}}<1.5$, where
$S_{\mathrm{L}}^{\text{fit}}=p_{\mathrm{L}}^{\nu}+p_{\mathrm{L}}^{\ell}+p_{\mathrm{L}}^{J_{1}}+p_{\mathrm{L}}^{J_{2}}+p_{\mathrm{L}}^{J_{3}}+p_{\mathrm{L}}^{J_{4}}$,
and $p_{\mathrm{L}}$ is the longitudinal momentum of each of the corresponding
objects. Both $S_{\mathrm{L}}^{\text{fit}}$ and $S_{\mathrm{T}}^{\text{fit}}$
are calculated using the fitted momenta. This requirement relies on the fact
that the final-state objects from the signal process typically have both high-
and moderate-$p_{z}$ values.

  * •

The invariant mass of the two jets attributed to the W boson hadronic decay
must be in the range 60–100.

  * •

$P(\chi^{2})>0.1\%$ (corresponding to 3 standard deviations for a one-sided
Gaussian distribution).

The signal decay process contains two quarks, which manifest themselves as
b-tagged jets. The fit combinations passing the above selection are sorted
into four groups according to the tagging categories of the
{$\mathrm{b_{l},b_{h}}$} jet pair: two CSVM tags; one CSVM and one CSVL tag;
only one CSVM tag; and two CSVL tags. The combination with the largest
$P(\chi^{2})$ value from the group with the tightest tagging is selected for
the signal sample.

Combinations containing W-tagged subjets are considered first, if such exist
in the event. If no combination with W-tagged subjets passes the selection
criteria, then the other combinations are considered.

###  0.5.1 Results of the event selection

Table 0.5.1 presents the numbers of observed and predicted background events,
normalized to the integrated luminosity. Selection efficiencies for the
$\mathrm{T}\overline{\mathrm{T}}$ signal, including acceptance and branching
fractions of decays, and the number of expected signal events are given in
Table 0.5.1 as a function of the $\mathrm{T}$ quark mass.

The numbers of expected background events for each process in the $\mu$+jets
and e+jets channels, normalized to the integrated luminosity of the data, the
number of observed events, and the ratio of the observed to predicted events.
The uncertainties in the predicted numbers of background events are
statistical only.  $\mu$ \+ jets e + jets Background process +jets
$533\,\pm\,6$ $470\,\pm\,5$ Single top $115\,\pm\,5$ $100\,\pm\,4$ W+jets
$94\,\pm\,2$ $73\,\pm\,2$ Z+jets $10.7\,\pm\,0.3$ $9.4\,\pm\,0.3$ QCD multijet
$8.8\,\pm\,4.4$ $15\,\pm\,8$ Diboson $4.4\,\pm\,4.4$ $1.8\,\pm\,1.8$ V
$10.9\,\pm\,0.9$ $8.0\,\pm\,0.8$ Total background (MC) $777\,\pm\,10$
$678\,\pm\,11$ Total observed (Data) 768 684 Data/MC $0.99\,\pm\,0.04$
$1.01\,\pm\,0.04$

Selection efficiencies from MC simulation for the
$\mathrm{T}\overline{\mathrm{T}}$ signal as a function of the $\mathrm{T}$
quark mass assuming $\mathcal{B}(\mathrm{T}\to\PQb\PW)=100\%$, and the numbers
of expected signal events after the final selection for the integrated
luminosity of the data. The uncertainties are statistical only.  $\mu$ \+ jets
e + jets Mass [] Efficiency (%) Events Efficiency (%) Events 800
$2.37\,\pm\,0.05$ $166.1\,\pm\,3.7$ $2.20\,\pm\,0.05$ $153.5\,\pm\,3.5$ 900
$2.71\,\pm\,0.06$ $87.8\,\pm\,1.9$ $2.36\,\pm\,0.05$ $75.8\,\pm\,1.8$ 1000
$2.97\,\pm\,0.06$ $46.7\,\pm\,0.9$ $2.69\,\pm\,0.06$ $42.2\,\pm\,0.9$ 1100
$3.08\,\pm\,0.06$ $24.7\,\pm\,0.5$ $2.77\,\pm\,0.06$ $22.1\,\pm\,0.4$ 1200
$3.14\,\pm\,0.06$ $13.3\,\pm\,0.3$ $2.80\,\pm\,0.06$ $11.8\,\pm\,0.2$ 1300
$3.10\,\pm\,0.07$ $7.09\,\pm\,0.15$ $2.79\,\pm\,0.06$ $6.34\,\pm\,0.14$ 1400
$3.14\,\pm\,0.06$ $3.98\,\pm\,0.08$ $2.77\,\pm\,0.06$ $3.50\,\pm\,0.07$ 1500
$3.21\,\pm\,0.06$ $2.30\,\pm\,0.04$ $2.76\,\pm\,0.06$ $1.96\,\pm\,0.04$ 1600
$3.01\,\pm\,0.06$ $1.24\,\pm\,0.02$ $2.84\,\pm\,0.06$ $1.16\,\pm\,0.02$

Figure 1:  The $\mathrm{T}$ quark reconstructed mass spectra for the
$\mu$+jets (upper plot) and e+jets (lower plot) channels from data and from MC
simulations of signal and background processes. The MC prediction for pair
production of a $\mathrm{T}$ quark with a mass of 1300is shown by a dashed
line, enhanced by a factor of 20. The lower panels show the ratio of the data
to the background prediction. The uncertainties represented by the vertical
bars on the points are statistical only. The shaded regions show the total
statistical uncertainties in the background.

Figure 2:  The $\mathrm{T}$ quark reconstructed mass spectra for the sum of
$\mu$+jets and e+jets channels from data and from MC simulations of signal and
background processes. The lower plot has a logarithmic x-axis scale and the
bin size corresponds to 7% of the mass value in the middle of the bin. The MC
prediction for the pair production of a $\mathrm{T}$ quark with a mass of
1300is shown by a dashed line, enhanced by a factor of 20. The lower panels
show the ratio of the data to the background prediction. The uncertainties
represented by the vertical bars on the points are statistical only. The
shaded regions show the total statistical uncertainties in the background.

Figure 1 shows the distributions of the $\mathrm{T}$ quark reconstructed mass,
$m_{\text{reco}}$, obtained from the selected $\mu$+jets and e+jets events,
and Fig. 2 shows their sum. The integrated luminosity and cross sections of
the background processes are used for normalization of the background
contributions. Only the statistical uncertainties are shown for the estimated
background, since the systematic uncertainties enter the workflow later and
are not available at this point of the analysis. Nevertheless, it is evident
that the data distributions are well described by the predicted backgrounds
alone.

The resolution of the reconstructed mass was found to be proportional to the
value of the mass, with the Gaussian core of the $m_{\text{reco}}$ resolution
curves having a width-to-mass ratio of $\approx$7%. We make use of this
feature by employing variable bin widths equal to 7% of the bin-center values
when plotting $m_{\text{reco}}$ and using a logarithmic scale for the
horizontal axis. In this way, the bin widths appear to be of the same size,
equal to the local mass resolution. This helps smooth statistical fluctuations
causing peaks that are narrower than the local mass resolution, and avoid
wrong interpretations when searching for narrow structures in the observed
mass distribution. Figure 2 (lower plot) shows the resulting $m_{\text{reco}}$
spectrum plotted this way for the sum of the $\mu$+jets and e+jets channels.
The reconstructed top quark peak from the $\ttbar$+jets background process and
the predicted signal for a $\mathrm{T}$ quark with a mass of 1300, enhanced by
a factor of 20 for better visibility, appear in the figure as narrow peaks
with similar widths.

The analysis selection has been optimized to obtain the best signal
significance at high masses, and the mass reconstruction in the region of the
top quark has not received special attention. As a result, the bin width used
in Fig. 1 and the upper part of Fig. 2 is too coarse to reveal details of the
mass reconstruction in this region. Nonetheless, the top quark peak provides a
useful benchmark for checking the reconstructed mass scale and resolution in
data and Monte Carlo.

##  0.6 Systematic uncertainties

In this section, we describe the systematic uncertainties in the calculation
of the signal cross section. The uncertainties can be divided into two
categories: those that only impact the normalizations of the distributions,
and those that also affect the shapes of the distributions. Each systematic
uncertainty is included as a nuisance parameter in the likelihood fit
described in Section 0.7.

The uncertainties in the $\ttbar$+jets, electroweak, and QCD multijet cross
sections, the total integrated luminosity, and the lepton efficiencies affect
only the normalization.

The uncertainty in the cross section for $\ttbar$+jets production of 5.3% is
taken from a previous CMS measurement [43]. The integrated luminosity is known
to a precision of 2.5% [44]. A 10% uncertainty is assigned to the sum of the
non-backgrounds, which is dominated by the uncertainty in the W+jets and
single top quark backgrounds. This uncertainty is obtained from earlier CMS
measurements on single top quark production [45] and from a preliminary CMS
measurement on inclusive W production.

Trigger and lepton identification efficiencies and data/MC SFs are obtained
from data using decays of bosons to dileptons. The systematic uncertainty in
the lepton identification and trigger efficiencies is 2.5%.

Uncertainties that affect the shapes of the $m_{\text{reco}}$ distributions
include those in the jet energy scales (JES), jet energy resolution (JER),
$\PQb$ tagging efficiency, pileup, renormalization/factorization scale, and
PDFs. To model these uncertainties, we produce additional distributions,
called templates, by varying the nuisance parameter that characterizes each
systematic effect by one standard deviation up and down. To determine the
signal and background templates for any value of the nuisance parameter, we
interpolate the content of each bin between the varied and nominal templates.
This procedure is often referred to as vertical morphing [46].

The JES uncertainty affects the normalization and the shape of the
$m_{\text{reco}}$ distribution. This is taken into account by generating
$m_{\text{reco}}$ distributions for values of the jet energy scaled by one
standard deviation of the $\eta$\- and -dependent uncertainties.

The MC was found to underestimate the JER observed in the data, and as a
result the MC simulated jets are smeared to describe the data. To this end,
the difference between the reconstructed jet and the generated jet is scaled
by $\eta$-dependent SFs (the so-called “nominal” variation). To estimate the
uncertainty in this rescaling, the analysis is repeated twice, each time
applying additional sets of SFs that correspond to varying the nominal ones up
and down by one standard deviation. Both AK4 and AK8 jets are subject to JER
systematic variations. The JES and JER systematic variations are applied
before the AK8 jet splitting. Systematic variations of each subjet are done
with the same relative variation as the entire AK8 jet, so that their sum is
equal to the modified AK8 four-momentum. The resulting jet momentum changes in
the AK4 jet collection are propagated to .

The systematic uncertainty related to the $\PQb$ tagging efficiency is
estimated by varying the tagging SFs for both the medium and loose operating
points by one standard deviation separately for heavy-flavor and light-flavor
jets .

The pileup uncertainty is evaluated by varying the minimum-bias cross section
used to calculate the pileup distribution in data by $\pm$4.6%, and adjusting
the number of pileup interactions in the simulation to these distributions.
This variation is taken from the uncertainty in a preliminary CMS measurement
of the minimum-bias cross section.

The uncertainties due to variations in the renormalization and factorization
scales are evaluated using per-event weights, corresponding to
renormalization/factorization scale variations by a factor of two up and down.
The combinations of scales corresponding to unphysical anti-correlated
variations are not considered. The envelope of the observed variations in the
$m_{\text{reco}}$ spectrum is taken as an estimate of the uncertainty.

For evaluating the uncertainty related to the PDFs, we use 100 MC replicas,
generated with the NNPDF3.0 PDF set and their corresponding weights, to sample
the $m_{\text{reco}}$ distribution. The per-bin RMS in the $m_{\text{reco}}$
distribution is taken as a measure of the PDF uncertainty in the corresponding
templates. The PDF uncertainty is applied both to the background and the
signal MC replicas. In the case of the signal, the uncertainty affects both
the shape and yield, though the latter is only due to the signal acceptance,
not to the signal cross section.

It is known that the top quark distribution in the $\ttbar$+jets background
process is not well modeled by the MC simulation [47]. Therefore, a
reweighting of the top quark MC distribution is applied. An event weight is
calculated, based on the generator-level top quark . The systematic
uncertainty related to the top quark distribution reweighting is determined
from the difference between applying and not applying the reweighting, and by
applying the reweighting twice.

For the W+jets background modeling, we use -binned MC samples, for which the
generator-level distribution was found to deviate from the same distribution
in the inclusive W+jets simulation. The variable is defined as the scalar sum
of the transverse momenta of all partons in a simulated event that originate
from the hard-scattering process. In each -binned sample, events are simulated
in a certain range of (200 to 400, 400 to 600, etc.). To improve the modeling,
we implement an event-weighting technique in which each simulated W+jets event
is weighted depending on its value. The weight is based on a parametrization
obtained from a fit to the ratio of the generator-level distributions of
inclusive and -binned samples. The systematic uncertainty related to the event
weighting is estimated from the difference between applying and not applying
the weighting, and by applying the weighting twice.

To estimate the systematic uncertainties related to the $\DR_{\text{match}}$
requirement used to associate W-tagged AK8 jets with AK4 jets in the jet-
splitting procedure, two templates with $\pm$20% variation in the maximum
allowed $\DR_{\text{match}}$ value were prepared.

Table 0.6 shows the influence of the shape systematic uncertainties on the
signal, for a $\mathrm{T}$ mass of 1200, and background yields. Other sources
of systematic uncertainties have a negligible impact on the analysis.

Variations in percent on the yield of the selected MC events due to shape
systematic uncertainties for a signal with a $\mathrm{T}$ quark mass of
1200and background.  Signal (%) Background (%) JES $+$0.2, $-$2.5 17 JER
$+$0.02, $-$0.3 0.03 b tag heavy flavor 2.5 $+$2.8, $-$1.4 b tag light flavor
0.2 0.8 Renorm./fact. scales 1.1 $+$18, $-$14 Pileup 0.05 0.2 PDF 0.3 2.0 Top
quark reweighting — 11 W+jets reweighting — $+$4.9, $-$3.3
$\DR_{\text{match}}$ $+$0, $-$0.8 $+$0, $-$1.9

##  0.7 Cross section and mass limits

Since the observed distributions are consistent with the expected background,
we use the results to set limits on the $\mathrm{T}\overline{\mathrm{T}}$
production cross section and on the $\mathrm{T}$ quark mass.

As discussed in Section 0.5, there are two types of selected events: those
with W-tagged jets (labeled as “W-tagged”), and those without (labeled as “no
W tag”). The $m_{\text{reco}}$ invariant mass distributions for these two
categories of events are shown separately in Fig. 3 for data and simulated
background, combining the $\mu$+jets and e+jets contributions. The no W tag
category is more sensitive to lower-mass $\mathrm{T}\overline{\mathrm{T}}$
signal events, as shown in the upper plot of Fig. 3 by the clear top quark
mass peak. At high masses this category of events gives a very small
contribution to the signal. Conversely, the W-tagged category is more
sensitive to high-mass signal events, as can be seen in Fig. 3 from the
predicted distributions for a $\mathrm{T}\overline{\mathrm{T}}$ signal with a
$\mathrm{T}$ mass of 1300for the two categories. We therefore use the data
$m_{\text{reco}}$ distribution from the W-tagged events in setting a lower
limit on the $\mathrm{T}$ quark mass. We checked that using the no W tag
category together with the W-tagged category did not improve the sensitivity
at high masses.

Figure 3: The $\mathrm{T}$ quark reconstructed mass spectra for the sum of the
$\mu$+jets and e+jets channels for the “no W tag” category of events (upper
plot), and for the “W-tagged” category (lower plot) from data and from MC
simulations of the background processes. The MC prediction for
$\mathrm{T}\overline{\mathrm{T}}$ production of a $\mathrm{T}$ quark with a
mass of 1300is shown by a dashed line, enhanced by a factor of 100 (upper) and
10 (lower). The lower panels show the ratio of the data to the background
prediction. The uncertainties represented by the vertical bars on the data
points are statistical only.

The distribution shown in Fig. 3 (lower plot) is used for the limit
calculations. For the MC background distribution we require that the relative
statistical uncertainty in each bin is not worse than 20%. For masses above
1200 GeV the bins are merged to meet this requirement. The final binning can
be seen on the post-fit distribution shown in Fig. 4 (lower plot).

The 95% confidence level (CL) upper limits on the production cross section of
$\mathrm{T}\overline{\mathrm{T}}$ are computed within the Theta framework [48]
using a Bayesian interpretation [49], in which the systematic uncertainties
are taken into account as nuisance parameters. The binned maximum-likelihood
fit to the data distribution is performed with a combination of the background
contributions plus a signal. The main backgrounds are $\ttbar$+jets, single
top quark, and W+jets production. Other smaller backgrounds, including
electroweak and QCD multijet processes, are summed up with the single top
quark and W+jets contributions and are called non-$\ttbar$ background (see
Table 0.5.1). Distributions of possible $\mathrm{T}\overline{\mathrm{T}}$
signals are considered for $\mathrm{T}$ masses from 800 to 1600(Table 0.5.1).

The likelihood function is marginalized with respect to the nuisance
parameters representing the systematic uncertainties in the shape and
normalization. Thirteen nuisance parameters are employed in the likelihood
fit: $\ttbar$+jets cross section uncertainty of 5.3%, normalization of the
non-$\ttbar$ contribution of 10%, the integrated luminosity uncertainty of
2.5%, lepton identification and trigger uncertainty of 2.5%; other
uncertainties are the shape uncertainties that include the JES, JER, the tag
SFs for light- and heavy-flavor jets, the renormalization and factorization
scales, pileup, PDFs, top quark reweighting, and W+jets background
reweighting. Shapes of the SM background and signal templates are changed
(“morphed”) in the limit-setting procedure according to the varying values of
the shape nuisance parameters. Contributions from the SM processes are allowed
to vary independently within their systematic uncertainties, using log-normal
priors [50, 51]. The nuisance parameters describing the shape uncertainties
are constrained using Gaussian priors. A flat prior probability density
function on the total signal yield is assumed. The MC statistical
uncertainties in the simulated samples are also included in this calculation.

Figure 4 (upper plot) shows the observed and expected 95% CL upper limits on
the $\mathrm{T}\overline{\mathrm{T}}$ cross section as a function of the T
quark mass.

Figure 4: Upper plot: Observed and expected Bayesian upper limits at 95% CL on
the product of the $\mathrm{T}\overline{\mathrm{T}}$ or
$\mathrm{Y}\overline{\mathrm{Y}}$ production cross section and the branching
fraction to $\PQb\PW$ using only the W-tagged events. The inner and outer
bands show the 1 and 2 standard deviation uncertainty ranges in the expected
limits, respectively. The dashed-dotted line shows the prediction of the
theory. Lower plot: The post-fit distribution of the reconstructed
$\mathrm{T}$ quark mass, $m_{\text{reco}}$. Horizontal bars on the data points
show bin size. The shaded band on the histogram and on the ratio plot shows
the quadrature sum of the statistical and systematic uncertainties. The MC
prediction for heavy quark production with a mass of 1300is shown by a dashed
line, enhanced by a factor of 10.

Figure 4 (lower plot) shows the post-fit distribution of the reconstructed
mass. From the upper cross section limits we set lower limits on the
$\mathrm{T}$ quark mass. The 95% CL lower limit on the $\mathrm{T}$ mass is
given by the value at which the 95% CL upper limit curve for the
$\mathrm{T}\overline{\mathrm{T}}$ cross section intersects the theory curve,
as shown in Fig. 4. In the $\PQb\PW\PAQb\PW$ channel with an assumed branching
fraction $\mathcal{B}(\mathrm{T}\to\PQb\PW)$ = 100%, the observed (expected)
lower limit on the $\mathrm{T}$ quark mass is 1295 (1275).

##  0.8 Summary

The results of a search for vector-like quarks, either $\mathrm{T}$ or
$\mathrm{Y}$, with electric charge of 2/3 and $-$4/3, respectively, that are
pair produced in pp interactions at $\sqrt{s}=13$and decay exclusively via the
$\PQb\PW$ channel have been presented. Events are selected requiring that one
$\PW$ boson decays to a lepton and neutrino, and the other to a quark-
antiquark pair. The selection requires a muon or electron, significant missing
transverse momentum, and at least four jets. A kinematic fit assuming
$\mathrm{T}\overline{\mathrm{T}}$ or $\mathrm{Y}\overline{\mathrm{Y}}$
production is performed and for every event a candidate
$\mathrm{T}/\mathrm{Y}$ quark mass $m_{\text{reco}}$ is reconstructed. The
analysis provides a high-resolution (7%) mass scan of the $\PQb\PW$ spectrum
in the range from the top quark mass up to $\approx$2, in which the signal
from pair production of equal mass objects decaying to $\PQb\PW$ would show up
in a model-independent way as a narrow peak. A binned maximum-likelihood fit
to the $m_{\text{reco}}$ distribution is made and no significant deviations
from the standard model expectations are found. Upper limits are set on the
$\mathrm{T}\overline{\mathrm{T}}$ and $\mathrm{Y}\overline{\mathrm{Y}}$ pair
production cross sections as a function of their mass. By comparing these
limits with the predicted theoretical cross section of the pair production,
the production of $\mathrm{T}$ and $\mathrm{Y}$ quarks is excluded at 95%
confidence level for masses below 1295 (1275expected). More generally, the
results set upper limits on the product of the production cross section and
branching fraction to $\PQb\PW$ for any new heavy quark decaying to this
channel.

###### Acknowledgements.

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

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##  .9 The CMS Collaboration

Yerevan Physics Institute, Yerevan, Armenia
A.M. Sirunyan, A. Tumasyan Institut für Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, E. Brondolin, M.
Dragicevic, J. Erö, M. Flechl, M. Friedl, R. Frühwirth1, V.M. Ghete, J.
Grossmann, J. Hrubec, M. Jeitler1, A. König, N. Krammer, I. Krätschmer, D.
Liko, T. Madlener, I. Mikulec, E. Pree, D. Rabady, N. Rad, H. Rohringer, J.
Schieck1, R. Schöfbeck, M. Spanring, D. Spitzbart, W. Waltenberger, J.
Wittmann, C.-E. Wulz1, M. Zarucki Institute for Nuclear Problems, Minsk,
Belarus
V. Chekhovsky, V. Mossolov, J. Suarez Gonzalez Universiteit Antwerpen,
Antwerpen, Belgium
E.A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, M. Van De Klundert, H. Van
Haevermaet, P. Van Mechelen, N. Van Remortel Vrije Universiteit Brussel,
Brussel, Belgium
S. Abu Zeid, F. Blekman, J. D’Hondt, I. De Bruyn, J. De Clercq, K. Deroover,
G. Flouris, D. Lontkovskyi, S. Lowette, S. Moortgat, L. Moreels, Q. Python, K.
Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders, I. Van Parijs
Université Libre de Bruxelles, Bruxelles, Belgium
H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, G. Fasanella, L. Favart,
R. Goldouzian, A. Grebenyuk, G. Karapostoli, T. Lenzi, J. Luetic, T.
Maerschalk, A. Marinov, A. Randle-conde, T. Seva, C. Vander Velde, P. Vanlaer,
D. Vannerom, R. Yonamine, F. Zenoni, F. Zhang2 Ghent University, Ghent,
Belgium
A. Cimmino, T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov, D. Poyraz,
C. Roskas, S. Salva, M. Tytgat, W. Verbeke, N. Zaganidis Université Catholique
de Louvain, Louvain-la-Neuve, Belgium
H. Bakhshiansohi, O. Bondu, S. Brochet, G. Bruno, C. Caputo, A. Caudron, S. De
Visscher, C. Delaere, M. Delcourt, B. Francois, A. Giammanco, A. Jafari, M.
Komm, G. Krintiras, V. Lemaitre, A. Magitteri, A. Mertens, M. Musich, K.
Piotrzkowski, L. Quertenmont, M. Vidal Marono, S. Wertz Université de Mons,
Mons, Belgium
N. Beliy Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil
W.L. Aldá Júnior, F.L. Alves, G.A. Alves, L. Brito, M. Correa Martins Junior,
C. Hensel, A. Moraes, M.E. Pol, P. Rebello Teles Universidade do Estado do Rio
de Janeiro, Rio de Janeiro, Brazil
E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato3, A. Custódio, E.M.
Da Costa, G.G. Da Silveira4, D. De Jesus Damiao, S. Fonseca De Souza, L.M.
Huertas Guativa, H. Malbouisson, M. Melo De Almeida, C. Mora Herrera, L.
Mundim, H. Nogima, A. Santoro, A. Sznajder, E.J. Tonelli Manganote3, F. Torres
Da Silva De Araujo, A. Vilela Pereira Universidade Estadual Paulista a,
Universidade Federal do ABC b, São Paulo, Brazil
S. Ahujaa, C.A. Bernardesa, T.R. Fernandez Perez Tomeia, E.M. Gregoresb, P.G.
Mercadanteb, S.F. Novaesa, Sandra S. Padulaa, D. Romero Abadb, J.C. Ruiz
Vargasa Institute for Nuclear Research and Nuclear Energy of Bulgaria Academy
of Sciences
A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Misheva, M. Rodozov, M. Shopova,
S. Stoykova, G. Sultanov University of Sofia, Sofia, Bulgaria
A. Dimitrov, I. Glushkov, L. Litov, B. Pavlov, P. Petkov Beihang University,
Beijing, China
W. Fang5, X. Gao5 Institute of High Energy Physics, Beijing, China
M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D.
Leggat, H. Liao, Z. Liu, F. Romeo, S.M. Shaheen, A. Spiezia, J. Tao, C. Wang,
Z. Wang, E. Yazgan, H. Zhang, S. Zhang, J. Zhao State Key Laboratory of
Nuclear Physics and Technology, Peking University, Beijing, China
Y. Ban, G. Chen, Q. Li, S. Liu, Y. Mao, S.J. Qian, D. Wang, Z. Xu Universidad
de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, L.F. Chaparro Sierra, C. Florez, C.F. González
Hernández, J.D. Ruiz Alvarez University of Split, Faculty of Electrical
Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia
B. Courbon, N. Godinovic, D. Lelas, I. Puljak, P.M. Ribeiro Cipriano, T.
Sculac University of Split, Faculty of Science, Split, Croatia
Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia
V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, A. Starodumov6, T. Susa
University of Cyprus, Nicosia, Cyprus
M.W. Ather, A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos,
P.A. Razis, H. Rykaczewski Charles University, Prague, Czech Republic
M. Finger7, M. Finger Jr.7 Universidad San Francisco de Quito, Quito, Ecuador
E. Carrera Jarrin Academy of Scientific Research and Technology of the Arab
Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt
E. El-khateeb8, S. Elgammal9, A. Ellithi Kamel10 National Institute of
Chemical Physics and Biophysics, Tallinn, Estonia
R.K. Dewanjee, M. Kadastik, L. Perrini, M. Raidal, A. Tiko, C. Veelken
Department of Physics, University of Helsinki, Helsinki, Finland
P. Eerola, J. Pekkanen, M. Voutilainen Helsinki Institute of Physics,
Helsinki, Finland
J. Härkönen, T. Järvinen, V. Karimäki, R. Kinnunen, T. Lampén, K. Lassila-
Perini, S. Lehti, T. Lindén, P. Luukka, E. Tuominen, J. Tuominiemi, E.
Tuovinen Lappeenranta University of Technology, Lappeenranta, Finland
J. Talvitie, T. Tuuva IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette,
France
M. Besancon, F. Couderc, M. Dejardin, D. Denegri, J.L. Faure, F. Ferri, S.
Ganjour, S. Ghosh, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry,
I. Kucher, E. Locci, M. Machet, J. Malcles, G. Negro, J. Rander, A. Rosowsky,
M.Ö. Sahin, M. Titov Laboratoire Leprince-Ringuet, Ecole polytechnique,
CNRS/IN2P3, Université Paris-Saclay, Palaiseau, France
A. Abdulsalam, I. Antropov, S. Baffioni, F. Beaudette, P. Busson, L. Cadamuro,
C. Charlot, R. Granier de Cassagnac, M. Jo, S. Lisniak, A. Lobanov, J. Martin
Blanco, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P. Pigard, R. Salerno,
J.B. Sauvan, Y. Sirois, A.G. Stahl Leiton, T. Strebler, Y. Yilmaz, A. Zabi, A.
Zghiche Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg,
France
J.-L. Agram11, J. Andrea, D. Bloch, J.-M. Brom, M. Buttignol, E.C. Chabert, N.
Chanon, C. Collard, E. Conte11, X. Coubez, J.-C. Fontaine11, D. Gelé, U.
Goerlach, M. Jansová, A.-C. Le Bihan, N. Tonon, P. Van Hove Centre de Calcul
de l’Institut National de Physique Nucleaire et de Physique des Particules,
CNRS/IN2P3, Villeurbanne, France
S. Gadrat Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3,
Institut de Physique Nucléaire de Lyon, Villeurbanne, France
S. Beauceron, C. Bernet, G. Boudoul, R. Chierici, D. Contardo, P. Depasse, H.
El Mamouni, J. Fay, L. Finco, S. Gascon, M. Gouzevitch, G. Grenier, B. Ille,
F. Lagarde, I.B. Laktineh, M. Lethuillier, L. Mirabito, A.L. Pequegnot, S.
Perries, A. Popov12, V. Sordini, M. Vander Donckt, S. Viret Georgian Technical
University, Tbilisi, Georgia
A. Khvedelidze7 Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze7 RWTH Aachen University, I. Physikalisches Institut, Aachen,
Germany
C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, C.
Schomakers, J. Schulz, T. Verlage, V. Zhukov12 RWTH Aachen University, III.
Physikalisches Institut A, Aachen, Germany
A. Albert, E. Dietz-Laursonn, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg,
T. Esch, R. Fischer, A. Güth, M. Hamer, T. Hebbeker, C. Heidemann, K.
Hoepfner, S. Knutzen, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, T.
Pook, M. Radziej, H. Reithler, M. Rieger, F. Scheuch, D. Teyssier, S. Thüer
RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany
G. Flügge, B. Kargoll, T. Kress, A. Künsken, J. Lingemann, T. Müller, A.
Nehrkorn, A. Nowack, C. Pistone, O. Pooth, A. Stahl13 Deutsches Elektronen-
Synchrotron, Hamburg, Germany
M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, K. Beernaert, O. Behnke, U.
Behrens, A. Bermúdez Martínez, A.A. Bin Anuar, K. Borras14, V. Botta, A.
Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G.
Eckerlin, D. Eckstein, T. Eichhorn, E. Eren, E. Gallo15, J. Garay Garcia, A.
Geiser, A. Gizhko, J.M. Grados Luyando, A. Grohsjean, P. Gunnellini, M.
Guthoff, A. Harb, J. Hauk, M. Hempel16, H. Jung, A. Kalogeropoulos, M.
Kasemann, J. Keaveney, C. Kleinwort, I. Korol, D. Krücker, W. Lange, A. Lelek,
T. Lenz, J. Leonard, K. Lipka, W. Lohmann16, R. Mankel, I.-A. Melzer-Pellmann,
A.B. Meyer, G. Mittag, J. Mnich, A. Mussgiller, E. Ntomari, D. Pitzl, A.
Raspereza, B. Roland, M. Savitskyi, P. Saxena, R. Shevchenko, S. Spannagel, N.
Stefaniuk, G.P. Van Onsem, R. Walsh, Y. Wen, K. Wichmann, C. Wissing, O.
Zenaiev University of Hamburg, Hamburg, Germany
S. Bein, V. Blobel, M. Centis Vignali, T. Dreyer, E. Garutti, D. Gonzalez, J.
Haller, A. Hinzmann, M. Hoffmann, A. Karavdina, R. Klanner, R. Kogler, N.
Kovalchuk, S. Kurz, T. Lapsien, I. Marchesini, D. Marconi, M. Meyer, M.
Niedziela, D. Nowatschin, F. Pantaleo13, T. Peiffer, A. Perieanu, C. Scharf,
P. Schleper, A. Schmidt, S. Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G.
Steinbrück, F.M. Stober, M. Stöver, H. Tholen, D. Troendle, E. Usai, L.
Vanelderen, A. Vanhoefer, B. Vormwald Institut für Experimentelle Kernphysik,
Karlsruhe, Germany
M. Akbiyik, C. Barth, S. Baur, E. Butz, R. Caspart, T. Chwalek, F. Colombo, W.
De Boer, A. Dierlamm, B. Freund, R. Friese, M. Giffels, A. Gilbert, D. Haitz,
F. Hartmann13, S.M. Heindl, U. Husemann, F. Kassel13, S. Kudella, H. Mildner,
M.U. Mozer, Th. Müller, M. Plagge, G. Quast, K. Rabbertz, M. Schröder, I.
Shvetsov, G. Sieber, H.J. Simonis, R. Ulrich, S. Wayand, M. Weber, T. Weiler,
S. Williamson, C. Wöhrmann, R. Wolf Institute of Nuclear and Particle Physics
(INPP), NCSR Demokritos, Aghia Paraskevi, Greece
G. Anagnostou, G. Daskalakis, T. Geralis, V.A. Giakoumopoulou, A. Kyriakis, D.
Loukas, I. Topsis-Giotis National and Kapodistrian University of Athens,
Athens, Greece
G. Karathanasis, S. Kesisoglou, A. Panagiotou, N. Saoulidou National Technical
University of Athens, Athens, Greece
K. Kousouris University of Ioánnina, Ioánnina, Greece
I. Evangelou, C. Foudas, P. Kokkas, S. Mallios, N. Manthos, I. Papadopoulos,
E. Paradas, J. Strologas, F.A. Triantis MTA-ELTE Lendület CMS Particle and
Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary
M. Csanad, N. Filipovic, G. Pasztor, G.I. Veres17 Wigner Research Centre for
Physics, Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath18, Á. Hunyadi, F. Sikler, V. Veszpremi, A.J.
Zsigmond Institute of Nuclear Research ATOMKI, Debrecen, Hungary
N. Beni, S. Czellar, J. Karancsi19, A. Makovec, J. Molnar, Z. Szillasi
Institute of Physics, University of Debrecen, Debrecen, Hungary
M. Bartók17, P. Raics, Z.L. Trocsanyi, B. Ujvari Indian Institute of Science
(IISc), Bangalore, India
S. Choudhury, J.R. Komaragiri National Institute of Science Education and
Research, Bhubaneswar, India
S. Bahinipati20, S. Bhowmik, P. Mal, K. Mandal, A. Nayak21, D.K. Sahoo20, N.
Sahoo, S.K. Swain Panjab University, Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, N. Dhingra, A.K. Kalsi, A.
Kaur, M. Kaur, R. Kumar, P. Kumari, A. Mehta, J.B. Singh, G. Walia University
of Delhi, Delhi, India
Ashok Kumar, Aashaq Shah, A. Bhardwaj, S. Chauhan, B.C. Choudhary, R.B. Garg,
S. Keshri, A. Kumar, S. Malhotra, M. Naimuddin, K. Ranjan, R. Sharma Saha
Institute of Nuclear Physics, HBNI, Kolkata, India
R. Bhardwaj, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep, S. Dey, S. Dutt,
S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S.
Nandan, A. Purohit, A. Roy, D. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S.
Thakur Indian Institute of Technology Madras, Madras, India
P.K. Behera Bhabha Atomic Research Centre, Mumbai, India
R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty13, P.K. Netrakanti,
L.M. Pant, P. Shukla, A. Topkar Tata Institute of Fundamental Research-A,
Mumbai, India
T. Aziz, S. Dugad, B. Mahakud, S. Mitra, G.B. Mohanty, N. Sur, B. Sutar Tata
Institute of Fundamental Research-B, Mumbai, India
S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, Sa. Jain, S.
Kumar, M. Maity22, G. Majumder, K. Mazumdar, T. Sarkar22, N. Wickramage23
Indian Institute of Science Education and Research (IISER), Pune, India
S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, S.
Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
S. Chenarani24, E. Eskandari Tadavani, S.M. Etesami24, M. Khakzad, M.
Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi25, F. Rezaei
Hosseinabadi, B. Safarzadeh26, M. Zeinali University College Dublin, Dublin,
Ireland
M. Felcini, M. Grunewald INFN Sezione di Bari a, Università di Bari b,
Politecnico di Bari c, Bari, Italy
M. Abbresciaa,b, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L. Cristellaa,b,
N. De Filippisa,c, M. De Palmaa,b, F. Erricoa,b, L. Fiorea, G. Iasellia,c, S.
Lezkia,b, G. Maggia,c, M. Maggia, G. Minielloa,b, S. Mya,b, S. Nuzzoa,b, A.
Pompilia,b, G. Pugliesea,c, R. Radognaa, A. Ranieria, G. Selvaggia,b, A.
Sharmaa, L. Silvestrisa,13, R. Vendittia, P. Verwilligena INFN Sezione di
Bologna a, Università di Bologna b, Bologna, Italy
G. Abbiendia, C. Battilanaa,b, D. Bonacorsia,b, S. Braibant-Giacomellia,b, R.
Campaninia,b, P. Capiluppia,b, A. Castroa,b, F.R. Cavalloa, S.S. Chhibraa, G.
Codispotia,b, M. Cuffiania,b, G.M. Dallavallea, F. Fabbria, A. Fanfania,b, D.
Fasanellaa,b, P. Giacomellia, C. Grandia, L. Guiduccia,b, S. Marcellinia, G.
Masettia, A. Montanaria, F.L. Navarriaa,b, A. Perrottaa, A.M. Rossia,b, T.
Rovellia,b, G.P. Sirolia,b, N. Tosia INFN Sezione di Catania a, Università di
Catania b, Catania, Italy
S. Albergoa,b, S. Costaa,b, A. Di Mattiaa, F. Giordanoa,b, R. Potenzaa,b, A.
Tricomia,b, C. Tuvea,b INFN Sezione di Firenze a, Università di Firenze b,
Firenze, Italy
G. Barbaglia, K. Chatterjeea,b, V. Ciullia,b, C. Civininia, R.
D’Alessandroa,b, E. Focardia,b, P. Lenzia,b, M. Meschinia, S. Paolettia, L.
Russoa,27, G. Sguazzonia, D. Stroma, L. Viliania,b,13 INFN Laboratori
Nazionali di Frascati, Frascati, Italy
L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera13 INFN Sezione di
Genova a, Università di Genova b, Genova, Italy
V. Calvellia,b, F. Ferroa, E. Robuttia, S. Tosia,b INFN Sezione di Milano-
Bicocca a, Università di Milano-Bicocca b, Milano, Italy
A. Benagliaa, L. Brianzaa,b, F. Brivioa,b, V. Cirioloa,b, M.E. Dinardoa,b, S.
Fiorendia,b, S. Gennaia, A. Ghezzia,b, P. Govonia,b, M. Malbertia,b, S.
Malvezzia, R.A. Manzonia,b, D. Menascea, L. Moronia, M. Paganonia,b, K.
Pauwelsa,b, D. Pedrinia, S. Pigazzinia,b,28, S. Ragazzia,b, N. Redaellia, T.
Tabarelli de Fatisa,b INFN Sezione di Napoli a, Università di Napoli ’Federico
II’ b, Napoli, Italy, Università della Basilicata c, Potenza, Italy,
Università G. Marconi d, Roma, Italy
S. Buontempoa, N. Cavalloa,c, S. Di Guidaa,d,13, F. Fabozzia,c, F. Fiengaa,b,
A.O.M. Iorioa,b, W.A. Khana, L. Listaa, S. Meolaa,d,13, P. Paoluccia,13, C.
Sciaccaa,b, F. Thyssena INFN Sezione di Padova a, Università di Padova b,
Padova, Italy, Università di Trento c, Trento, Italy
P. Azzia, N. Bacchettaa, L. Benatoa,b, D. Biselloa,b, A. Bolettia,b, R.
Carlina,b, A. Carvalho Antunes De Oliveiraa,b, P. Checchiaa, M. Dall’Ossoa,b,
P. De Castro Manzanoa, T. Dorigoa, F. Gasparinia,b, U. Gasparinia,b, A.
Gozzelinoa, S. Lacapraraa, P. Lujan, A.T. Meneguzzoa,b, N. Pozzobona,b, P.
Ronchesea,b, R. Rossina,b, F. Simonettoa,b, E. Torassaa, S. Venturaa, M.
Zanettia,b, P. Zottoa,b, G. Zumerlea,b INFN Sezione di Pavia a, Università di
Pavia b, Pavia, Italy
A. Braghieria, A. Magnania, P. Montagnaa,b, S.P. Rattia,b, V. Rea, M.
Ressegottia,b, C. Riccardia,b, P. Salvinia, I. Vaia,b, P. Vituloa,b INFN
Sezione di Perugia a, Università di Perugia b, Perugia, Italy
L. Alunni Solestizia,b, M. Biasinia,b, G.M. Bileia, C. Cecchia,b, D.
Ciangottinia,b, L. Fanòa,b, P. Laricciaa,b, R. Leonardia,b, E. Manonia, G.
Mantovania,b, V. Mariania,b, M. Menichellia, A. Rossia,b, A. Santocchiaa,b, D.
Spigaa INFN Sezione di Pisa a, Università di Pisa b, Scuola Normale Superiore
di Pisa c, Pisa, Italy
K. Androsova, P. Azzurria,13, G. Bagliesia, T. Boccalia, L. Borrello, R.
Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, G. Fedia, L. Gianninia,c, A.
Giassia, M.T. Grippoa,27, F. Ligabuea,c, T. Lomtadzea, E. Mancaa,c, G.
Mandorlia,c, L. Martinia,b, A. Messineoa,b, F. Pallaa, A. Rizzia,b, A. Savoy-
Navarroa,29, P. Spagnoloa, R. Tenchinia, G. Tonellia,b, A. Venturia, P.G.
Verdinia INFN Sezione di Roma a, Sapienza Università di Roma b, Rome, Italy
L. Baronea,b, F. Cavallaria, M. Cipriania,b, N. Dacia, D. Del Rea,b,13, E. Di
Marcoa,b, M. Diemoza, S. Gellia,b, E. Longoa,b, F. Margarolia,b, B.
Marzocchia,b, P. Meridiania, G. Organtinia,b, R. Paramattia,b, F. Preiatoa,b,
S. Rahatloua,b, C. Rovellia, F. Santanastasioa,b INFN Sezione di Torino a,
Università di Torino b, Torino, Italy, Università del Piemonte Orientale c,
Novara, Italy
N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, N. Bartosika,
R. Bellana,b, C. Biinoa, N. Cartigliaa, F. Cennaa,b, M. Costaa,b, R.
Covarellia,b, A. Deganoa,b, N. Demariaa, B. Kiania,b, C. Mariottia, S.
Masellia, E. Migliorea,b, V. Monacoa,b, E. Monteila,b, M. Montenoa, M.M.
Obertinoa,b, L. Pachera,b, N. Pastronea, M. Pelliccionia, G.L. Pinna
Angionia,b, F. Raveraa,b, A. Romeroa,b, M. Ruspaa,c, R. Sacchia,b, K.
Shchelinaa,b, V. Solaa, A. Solanoa,b, A. Staianoa, P. Traczyka,b INFN Sezione
di Trieste a, Università di Trieste b, Trieste, Italy
S. Belfortea, M. Casarsaa, F. Cossuttia, G. Della Riccaa,b, A. Zanettia
Kyungpook National University, Daegu, Korea
D.H. Kim, G.N. Kim, M.S. Kim, J. Lee, S. Lee, S.W. Lee, C.S. Moon, Y.D. Oh, S.
Sekmen, D.C. Son, Y.C. Yang Chonbuk National University, Jeonju, Korea
A. Lee Chonnam National University, Institute for Universe and Elementary
Particles, Kwangju, Korea
H. Kim, D.H. Moon, G. Oh Hanyang University, Seoul, Korea
J.A. Brochero Cifuentes, J. Goh, T.J. Kim Korea University, Seoul, Korea
S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, Y. Kim, K. Lee, K.S.
Lee, S. Lee, J. Lim, S.K. Park, Y. Roh Seoul National University, Seoul, Korea
J. Almond, J. Kim, J.S. Kim, H. Lee, K. Lee, K. Nam, S.B. Oh, B.C. Radburn-
Smith, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu University of Seoul, Seoul,
Korea
M. Choi, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park Sungkyunkwan University,
Suwon, Korea
Y. Choi, C. Hwang, J. Lee, I. Yu Vilnius University, Vilnius, Lithuania
V. Dudenas, A. Juodagalvis, J. Vaitkus National Centre for Particle Physics,
Universiti Malaya, Kuala Lumpur, Malaysia
I. Ahmed, Z.A. Ibrahim, M.A.B. Md Ali30, F. Mohamad Idris31, W.A.T. Wan
Abdullah, M.N. Yusli, Z. Zolkapli Centro de Investigacion y de Estudios
Avanzados del IPN, Mexico City, Mexico
Reyes-Almanza, R, Ramirez-Sanchez, G., Duran-Osuna, M. C., H. Castilla-Valdez,
E. De La Cruz-Burelo, I. Heredia-De La Cruz32, Rabadan-Trejo, R. I., R. Lopez-
Fernandez, J. Mejia Guisao, A. Sanchez-Hernandez Universidad Iberoamericana,
Mexico City, Mexico
S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita
Universidad Autonoma de Puebla, Puebla, Mexico
I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad Autónoma de
San Luis Potosí, San Luis Potosí, Mexico
A. Morelos Pineda University of Auckland, Auckland, New Zealand
D. Krofcheck University of Canterbury, Christchurch, New Zealand
P.H. Butler National Centre for Physics, Quaid-I-Azam University, Islamabad,
Pakistan
A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, A. Saddique, M.A. Shah, M.
Shoaib, M. Waqas National Centre for Nuclear Research, Swierk, Poland
H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Górski, M. Kazana, K.
Nawrocki, M. Szleper, P. Zalewski Institute of Experimental Physics, Faculty
of Physics, University of Warsaw, Warsaw, Poland
K. Bunkowski, A. Byszuk33, K. Doroba, A. Kalinowski, M. Konecki, J.
Krolikowski, M. Misiura, M. Olszewski, A. Pyskir, M. Walczak Laboratório de
Instrumentação e Física Experimental de Partículas, Lisboa, Portugal
P. Bargassa, C. Beirão Da Cruz E Silva, A. Di Francesco, P. Faccioli, B.
Galinhas, M. Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias, M.V.
Nemallapudi, J. Seixas, G. Strong, O. Toldaiev, D. Vadruccio, J. Varela Joint
Institute for Nuclear Research, Dubna, Russia
S. Afanasiev, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev,
V. Karjavin, A. Lanev, A. Malakhov, V. Matveev34,35, V. Palichik, V.
Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin, A.
Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg),
Russia
Y. Ivanov, V. Kim36, E. Kuznetsova37, P. Levchenko, V. Murzin, V. Oreshkin, I.
Smirnov, V. Sulimov, L. Uvarov, S. Vavilov, A. Vorobyev Institute for Nuclear
Research, Moscow, Russia
Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov,
N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical
and Experimental Physics, Moscow, Russia
V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G.
Safronov, A. Spiridonov, A. Stepennov, M. Toms, E. Vlasov, A. Zhokin Moscow
Institute of Physics and Technology, Moscow, Russia
T. Aushev, A. Bylinkin35 National Research Nuclear University ’Moscow
Engineering Physics Institute’ (MEPhI), Moscow, Russia
R. Chistov38, M. Danilov38, P. Parygin, D. Philippov, S. Polikarpov, E.
Tarkovskii P.N. Lebedev Physical Institute, Moscow, Russia
V. Andreev, M. Azarkin35, I. Dremin35, M. Kirakosyan35, A. Terkulov Skobeltsyn
Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow,
Russia
A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin39, L. Dudko, A.
Ershov, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, M.
Perfilov, V. Savrin, A. Snigirev Novosibirsk State University (NSU),
Novosibirsk, Russia
V. Blinov40, Y.Skovpen40, D. Shtol40 State Research Center of Russian
Federation, Institute for High Energy Physics, Protvino, Russia
I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, V. Kachanov, A. Kalinin,
D. Konstantinov, V. Petrov, R. Ryutin, A. Sobol, S. Troshin, N. Tyurin, A.
Uzunian, A. Volkov University of Belgrade, Faculty of Physics and Vinca
Institute of Nuclear Sciences, Belgrade, Serbia
P. Adzic41, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic
Centro de Investigaciones Energéticas Medioambientales y Tecnológicas
(CIEMAT), Madrid, Spain
J. Alcaraz Maestre, M. Barrio Luna, M. Cerrada, N. Colino, B. De La Cruz, A.
Delgado Peris, A. Escalante Del Valle, C. Fernandez Bedoya, J.P. Fernández
Ramos, J. Flix, M.C. Fouz, P. Garcia-Abia, O. Gonzalez Lopez, S. Goy Lopez,
J.M. Hernandez, M.I. Josa, D. Moran, A. Pérez-Calero Yzquierdo, J. Puerta
Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, M.S. Soares, A. Álvarez
Fernández Universidad Autónoma de Madrid, Madrid, Spain
C. Albajar, J.F. de Trocóniz, M. Missiroli Universidad de Oviedo, Oviedo,
Spain
J. Cuevas, C. Erice, J. Fernandez Menendez, I. Gonzalez Caballero, J.R.
González Fernández, E. Palencia Cortezon, S. Sanchez Cruz, P. Vischia, J.M.
Vizan Garcia Instituto de Física de Cantabria (IFCA), CSIC-Universidad de
Cantabria, Santander, Spain
I.J. Cabrillo, A. Calderon, B. Chazin Quero, E. Curras, J. Duarte Campderros,
M. Fernandez, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto, J. Marco, C.
Martinez Rivero, P. Martinez Ruiz del Arbol, F. Matorras, J. Piedra Gomez, T.
Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar
Cortabitarte CERN, European Organization for Nuclear Research, Geneva,
Switzerland
D. Abbaneo, E. Auffray, P. Baillon, A.H. Ball, D. Barney, M. Bianco, P. Bloch,
A. Bocci, C. Botta, T. Camporesi, R. Castello, M. Cepeda, G. Cerminara, E.
Chapon, Y. Chen, D. d’Enterria, A. Dabrowski, V. Daponte, A. David, M. De
Gruttola, A. De Roeck, M. Dobson, B. Dorney, T. du Pree, M. Dünser, N. Dupont,
A. Elliott-Peisert, P. Everaerts, F. Fallavollita, G. Franzoni, J. Fulcher, W.
Funk, D. Gigi, K. Gill, F. Glege, D. Gulhan, P. Harris, J. Hegeman, V.
Innocente, P. Janot, O. Karacheban16, J. Kieseler, H. Kirschenmann, V. Knünz,
A. Kornmayer13, M.J. Kortelainen, M. Krammer1, C. Lange, P. Lecoq, C.
Lourenço, M.T. Lucchini, L. Malgeri, M. Mannelli, A. Martelli, F. Meijers,
J.A. Merlin, S. Mersi, E. Meschi, P. Milenovic42, F. Moortgat, M. Mulders, H.
Neugebauer, J. Ngadiuba, S. Orfanelli, L. Orsini, L. Pape, E. Perez, M.
Peruzzi, A. Petrilli, G. Petrucciani, A. Pfeiffer, M. Pierini, A. Racz, T.
Reis, G. Rolandi43, M. Rovere, H. Sakulin, C. Schäfer, C. Schwick, M. Seidel,
M. Selvaggi, A. Sharma, P. Silva, P. Sphicas44, A. Stakia, J. Steggemann, M.
Stoye, M. Tosi, D. Treille, A. Triossi, A. Tsirou, V. Veckalns45, M. Verweij,
W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland
W. Bertl${}^{\textrm{\textdagger}}$, L. Caminada46, K. Deiters, W. Erdmann, R.
Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe,
S.A. Wiederkehr ETH Zurich - Institute for Particle Physics and Astrophysics
(IPA), Zurich, Switzerland
F. Bachmair, L. Bäni, P. Berger, L. Bianchini, B. Casal, G. Dissertori, M.
Dittmar, M. Donegà, C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, T.
Klijnsma, W. Lustermann, B. Mangano, M. Marionneau, M.T. Meinhard, D. Meister,
F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandolfi, J. Pata, F. Pauss, G.
Perrin, L. Perrozzi, M. Quittnat, M. Reichmann, M. Schönenberger, L.
Shchutska, V.R. Tavolaro, K. Theofilatos, M.L. Vesterbacka Olsson, R. Wallny,
D.H. Zhu Universität Zürich, Zurich, Switzerland
T.K. Aarrestad, C. Amsler47, M.F. Canelli, A. De Cosa, R. Del Burgo, S.
Donato, C. Galloni, T. Hreus, B. Kilminster, D. Pinna, G. Rauco, P. Robmann,
D. Salerno, C. Seitz, Y. Takahashi, A. Zucchetta National Central University,
Chung-Li, Taiwan
V. Candelise, T.H. Doan, Sh. Jain, R. Khurana, C.M. Kuo, W. Lin, A.
Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan
Arun Kumar, P. Chang, Y. Chao, K.F. Chen, P.H. Chen, F. Fiori, W.-S. Hou, Y.
Hsiung, Y.F. Liu, R.-S. Lu, E. Paganis, A. Psallidas, A. Steen, J.f. Tsai
Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok,
Thailand
B. Asavapibhop, K. Kovitanggoon, G. Singh, N. Srimanobhas Çukurova University,
Physics Department, Science and Art Faculty, Adana, Turkey
M.N. Bakirci48, F. Boran, S. Damarseckin, Z.S. Demiroglu, C. Dozen, E. Eskut,
S. Girgis, G. Gokbulut, Y. Guler, I. Hos49, E.E. Kangal50, O. Kara, U.
Kiminsu, M. Oglakci, G. Onengut51, K. Ozdemir52, S. Ozturk48, A. Polatoz, B.
Tali53, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical
University, Physics Department, Ankara, Turkey
B. Bilin, G. Karapinar54, K. Ocalan55, M. Yalvac, M. Zeyrek Bogazici
University, Istanbul, Turkey
E. Gülmez, M. Kaya56, O. Kaya57, S. Tekten, E.A. Yetkin58 Istanbul Technical
University, Istanbul, Turkey
M.N. Agaras, S. Atay, A. Cakir, K. Cankocak 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
R. Aggleton, F. Ball, L. Beck, J.J. Brooke, D. Burns, E. Clement, D. Cussans,
O. Davignon, H. Flacher, J. Goldstein, M. Grimes, G.P. Heath, H.F. Heath, J.
Jacob, L. Kreczko, C. Lucas, D.M. Newbold59, S. Paramesvaran, A. Poll, T.
Sakuma, S. Seif El Nasr-storey, D. Smith, V.J. Smith Rutherford Appleton
Laboratory, Didcot, United Kingdom
K.W. Bell, A. Belyaev60, C. Brew, R.M. Brown, L. Calligaris, D. Cieri, D.J.A.
Cockerill, J.A. Coughlan, K. Harder, S. Harper, E. Olaiya, D. Petyt, C.H.
Shepherd-Themistocleous, A. Thea, I.R. Tomalin, T. Williams Imperial College,
London, United Kingdom
G. Auzinger, R. Bainbridge, S. Breeze, O. Buchmuller, A. Bundock, S. Casasso,
M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies, A. De Wit, M. Della
Negra, R. Di Maria, A. Elwood, Y. Haddad, G. Hall, G. Iles, T. James, R. Lane,
C. Laner, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, T. Matsushita,
J. Nash, A. Nikitenko6, V. Palladino, M. Pesaresi, D.M. Raymond, A. Richards,
A. Rose, E. Scott, C. Seez, A. Shtipliyski, S. Summers, A. Tapper, K. Uchida,
M. Vazquez Acosta61, T. Virdee13, N. Wardle, D. Winterbottom, J. Wright, S.C.
Zenz Brunel University, Uxbridge, United Kingdom
J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, I.D. Reid, P. Symonds, L.
Teodorescu, M. Turner Baylor University, Waco, USA
A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika, C. Smith
Catholic University of America, Washington DC, USA
R. Bartek, A. Dominguez The University of Alabama, Tuscaloosa, USA
A. Buccilli, S.I. Cooper, C. Henderson, P. Rumerio, C. West Boston University,
Boston, USA
D. Arcaro, A. Avetisyan, T. Bose, D. Gastler, D. Rankin, C. Richardson, J.
Rohlf, L. Sulak, D. Zou Brown University, Providence, USA
G. Benelli, D. Cutts, A. Garabedian, J. Hakala, U. Heintz, J.M. Hogan, K.H.M.
Kwok, E. Laird, G. Landsberg, Z. Mao, M. Narain, J. Pazzini, S. Piperov, S.
Sagir, R. Syarif, D. Yu University of California, Davis, Davis, USA
R. Band, C. Brainerd, D. Burns, M. Calderon De La Barca Sanchez, M. Chertok,
J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, M. Gardner,
W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout,
M. Shi, J. Smith, D. Stolp, K. Tos, M. Tripathi, Z. Wang University of
California, Los Angeles, USA
M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M.
Ignatenko, N. Mccoll, S. Regnard, D. Saltzberg, C. Schnaible, V. Valuev
University of California, Riverside, Riverside, USA
E. Bouvier, K. Burt, R. Clare, J. Ellison, J.W. Gary, S.M.A. Ghiasi Shirazi,
G. Hanson, J. Heilman, P. Jandir, E. Kennedy, F. Lacroix, O.R. Long, M. Olmedo
Negrete, M.I. Paneva, A. Shrinivas, W. Si, L. Wang, H. Wei, S. Wimpenny, B. R.
Yates University of California, San Diego, La Jolla, USA
J.G. Branson, S. Cittolin, M. Derdzinski, R. Gerosa, B. Hashemi, A. Holzner,
D. Klein, G. Kole, V. Krutelyov, J. Letts, I. Macneill, M. Masciovecchio, D.
Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A.
Vartak, S. Wasserbaech62, J. Wood, F. Würthwein, A. Yagil, G. Zevi Della Porta
University of California, Santa Barbara - Department of Physics, Santa
Barbara, USA
N. Amin, R. Bhandari, J. Bradmiller-Feld, C. Campagnari, A. Dishaw, V. Dutta,
M. Franco Sevilla, C. George, F. Golf, L. Gouskos, J. Gran, R. Heller, J.
Incandela, S.D. Mullin, A. Ovcharova, H. Qu, J. Richman, D. Stuart, I. Suarez,
J. Yoo California Institute of Technology, Pasadena, USA
D. Anderson, J. Bendavid, A. Bornheim, J.M. Lawhorn, H.B. Newman, T. Nguyen,
C. Pena, M. Spiropulu, J.R. Vlimant, S. Xie, Z. Zhang, R.Y. Zhu Carnegie
Mellon University, Pittsburgh, USA
M.B. Andrews, T. Ferguson, T. Mudholkar, M. Paulini, J. Russ, M. Sun, H.
Vogel, I. Vorobiev, M. Weinberg University of Colorado Boulder, Boulder, USA
J.P. Cumalat, W.T. Ford, F. Jensen, A. Johnson, M. Krohn, S. Leontsinis, T.
Mulholland, K. Stenson, S.R. Wagner Cornell University, Ithaca, USA
J. Alexander, J. Chaves, J. Chu, S. Dittmer, K. Mcdermott, N. Mirman, J.R.
Patterson, A. Rinkevicius, A. Ryd, L. Skinnari, L. Soffi, S.M. Tan, Z. Tao, J.
Thom, J. Tucker, P. Wittich, M. Zientek Fermi National Accelerator Laboratory,
Batavia, USA
S. Abdullin, M. Albrow, G. Apollinari, A. Apresyan, A. Apyan, S. Banerjee,
L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, G.
Bolla${}^{\textrm{\textdagger}}$, K. Burkett, J.N. Butler, A. Canepa, G.B.
Cerati, H.W.K. Cheung, F. Chlebana, M. Cremonesi, J. Duarte, V.D. Elvira, J.
Freeman, Z. Gecse, E. Gottschalk, L. Gray, D. Green, S. Grünendahl, O.
Gutsche, R.M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, B. Jayatilaka, S.
Jindariani, M. Johnson, U. Joshi, B. Klima, B. Kreis, S. Lammel, D. Lincoln,
R. Lipton, M. Liu, T. Liu, R. Lopes De Sá, J. Lykken, K. Maeshima, N. Magini,
J.M. Marraffino, S. Maruyama, D. Mason, P. McBride, P. Merkel, S. Mrenna, S.
Nahn, V. O’Dell, K. Pedro, O. Prokofyev, G. Rakness, L. Ristori, B. Schneider,
E. Sexton-Kennedy, A. Soha, W.J. Spalding, L. Spiegel, S. Stoynev, J. Strait,
N. Strobbe, L. Taylor, S. Tkaczyk, N.V. Tran, L. Uplegger, E.W. Vaandering, C.
Vernieri, M. Verzocchi, R. Vidal, M. Wang, H.A. Weber, A. Whitbeck University
of Florida, Gainesville, USA
D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerhoff, A. Carnes, M.
Carver, D. Curry, R.D. Field, I.K. Furic, J. Konigsberg, A. Korytov, K. Kotov,
P. Ma, K. Matchev, H. Mei, G. Mitselmakher, D. Rank, D. Sperka, N. Terentyev,
L. Thomas, J. Wang, S. Wang, J. Yelton Florida International University,
Miami, USA
Y.R. Joshi, S. Linn, P. Markowitz, J.L. Rodriguez Florida State University,
Tallahassee, USA
A. Ackert, T. Adams, A. Askew, S. Hagopian, V. Hagopian, K.F. Johnson, T.
Kolberg, G. Martinez, T. Perry, H. Prosper, A. Saha, A. Santra, V. Sharma, R.
Yohay Florida Institute of Technology, Melbourne, USA
M.M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, T.
Roy, F. Yumiceva University of Illinois at Chicago (UIC), Chicago, USA
M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, R. Cavanaugh, X. Chen, O.
Evdokimov, C.E. Gerber, D.A. Hangal, D.J. Hofman, K. Jung, J. Kamin, I.D.
Sandoval Gonzalez, M.B. Tonjes, H. Trauger, N. Varelas, H. Wang, Z. Wu, J.
Zhang The University of Iowa, Iowa City, USA
B. Bilki63, W. Clarida, K. Dilsiz64, S. Durgut, R.P. Gandrajula, M.
Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya65, A. Mestvirishvili,
A. Moeller, J. Nachtman, H. Ogul66, Y. Onel, F. Ozok67, A. Penzo, C. Snyder,
E. Tiras, J. Wetzel, K. Yi Johns Hopkins University, Baltimore, USA
B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan, P.
Maksimovic, J. Roskes, U. Sarica, M. Swartz, M. Xiao, C. You The University of
Kansas, Lawrence, USA
A. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, J. Castle, S.
Khalil, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, C. Royon, S.
Sanders, E. Schmitz, J.D. Tapia Takaki, Q. Wang Kansas State University,
Manhattan, USA
A. Ivanov, K. Kaadze, Y. Maravin, A. Mohammadi, L.K. Saini, N. Skhirtladze, S.
Toda Lawrence Livermore National Laboratory, Livermore, USA
F. Rebassoo, D. Wright University of Maryland, College Park, USA
C. Anelli, A. Baden, O. Baron, A. Belloni, B. Calvert, S.C. Eno, C. Ferraioli,
N.J. Hadley, S. Jabeen, G.Y. Jeng, R.G. Kellogg, J. Kunkle, A.C. Mignerey, F.
Ricci-Tam, Y.H. Shin, A. Skuja, S.C. Tonwar Massachusetts Institute of
Technology, Cambridge, USA
D. Abercrombie, B. Allen, V. Azzolini, R. Barbieri, A. Baty, R. Bi, S. Brandt,
W. Busza, I.A. Cali, M. D’Alfonso, Z. Demiragli, G. Gomez Ceballos, M.
Goncharov, D. Hsu, Y. Iiyama, G.M. Innocenti, M. Klute, D. Kovalskyi, Y.S.
Lai, Y.-J. Lee, A. Levin, P.D. Luckey, B. Maier, A.C. Marini, C. Mcginn, C.
Mironov, S. Narayanan, X. Niu, C. Paus, C. Roland, G. Roland, J. Salfeld-
Nebgen, G.S.F. Stephans, K. Tatar, D. Velicanu, J. Wang, T.W. Wang, B.
Wyslouch University of Minnesota, Minneapolis, USA
A.C. Benvenuti, R.M. Chatterjee, A. Evans, P. Hansen, S. Kalafut, Y. Kubota,
Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack, J. Turkewitz
University of Mississippi, Oxford, USA
J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA
E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, R. Gonzalez Suarez, R.
Kamalieddin, I. Kravchenko, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger State
University of New York at Buffalo, Buffalo, USA
M. Alyari, J. Dolen, A. Godshalk, C. Harrington, I. Iashvili, D. Nguyen, A.
Parker, S. Rappoccio, B. Roozbahani Northeastern University, Boston, USA
G. Alverson, E. Barberis, A. Hortiangtham, A. Massironi, D.M. Morse, D. Nash,
T. Orimoto, R. Teixeira De Lima, D. Trocino, D. Wood Northwestern University,
Evanston, USA
S. Bhattacharya, O. Charaf, K.A. Hahn, N. Mucia, N. Odell, B. Pollack, M.H.
Schmitt, K. Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame,
USA
N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N. Kellams,
K. Lannon, N. Loukas, N. Marinelli, F. Meng, C. Mueller, Y. Musienko34, M.
Planer, A. Reinsvold, R. Ruchti, G. Smith, S. Taroni, M. Wayne, M. Wolf, A.
Woodard The Ohio State University, Columbus, USA
J. Alimena, L. Antonelli, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, A.
Hart, C. Hill, W. Ji, B. Liu, W. Luo, D. Puigh, B.L. Winer, H.W. Wulsin
Princeton University, Princeton, USA
S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, S. Higginbotham,
D. Lange, J. Luo, D. Marlow, K. Mei, I. Ojalvo, J. Olsen, C. Palmer, P.
Piroué, D. Stickland, C. Tully University of Puerto Rico, Mayaguez, USA
S. Malik, S. Norberg Purdue University, West Lafayette, USA
A. Barker, V.E. Barnes, S. Das, S. Folgueras, L. Gutay, M.K. Jha, M. Jones,
A.W. Jung, A. Khatiwada, D.H. Miller, N. Neumeister, C.C. Peng, J.F. Schulte,
J. Sun, F. Wang, W. Xie Purdue University Northwest, Hammond, USA
T. Cheng, N. Parashar, J. Stupak Rice University, Houston, USA
A. Adair, B. Akgun, Z. Chen, K.M. Ecklund, F.J.M. Geurts, M. Guilbaud, W. Li,
B. Michlin, M. Northup, B.P. Padley, J. Roberts, J. Rorie, Z. Tu, J. Zabel
University of Rochester, Rochester, USA
A. Bodek, P. de Barbaro, R. Demina, Y.t. Duh, T. Ferbel, M. Galanti, A.
Garcia-Bellido, J. Han, O. Hindrichs, A. Khukhunaishvili, K.H. Lo, P. Tan, M.
Verzetti The Rockefeller University, New York, USA
R. Ciesielski, K. Goulianos, C. Mesropian Rutgers, The State University of New
Jersey, Piscataway, USA
A. Agapitos, J.P. Chou, Y. Gershtein, T.A. Gómez Espinosa, E. Halkiadakis, M.
Heindl, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath,
R. Montalvo, K. Nash, M. Osherson, H. Saka, S. Salur, S. Schnetzer, D.
Sheffield, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker
University of Tennessee, Knoxville, USA
A.G. Delannoy, M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K.
Thapa Texas A&M University, College Station, USA
O. Bouhali68, A. Castaneda Hernandez68, A. Celik, M. Dalchenko, M. De Mattia,
A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, T. Kamon69, R.
Mueller, Y. Pakhotin, R. Patel, A. Perloff, L. Perniè, D. Rathjens, A.
Safonov, A. Tatarinov, K.A. Ulmer Texas Tech University, Lubbock, USA
N. Akchurin, J. Damgov, F. De Guio, P.R. Dudero, J. Faulkner, E. Gurpinar, S.
Kunori, K. Lamichhane, S.W. Lee, T. Libeiro, T. Peltola, S. Undleeb, I.
Volobouev, Z. Wang Vanderbilt University, Nashville, USA
S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K.
Padeken, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu University of Virginia,
Charlottesville, USA
M.W. Arenton, P. Barria, B. Cox, R. Hirosky, M. Joyce, A. Ledovskoy, H. Li, C.
Neu, T. Sinthuprasith, Y. Wang, E. Wolfe, F. Xia Wayne State University,
Detroit, USA
R. Harr, P.E. Karchin, J. Sturdy, S. Zaleski University of Wisconsin -
Madison, Madison, WI, USA
M. Brodski, J. Buchanan, C. Caillol, S. Dasu, L. Dodd, S. Duric, B. Gomber, M.
Grothe, M. Herndon, A. Hervé, U. Hussain, P. Klabbers, A. Lanaro, A. Levine,
K. Long, R. Loveless, G.A. Pierro, G. Polese, T. Ruggles, A. Savin, N. Smith,
W.H. Smith, D. Taylor, N. Woods †: Deceased
1: Also at Vienna University of Technology, Vienna, Austria
2: Also at State Key Laboratory of Nuclear Physics and Technology, Peking
University, Beijing, China
3: Also at Universidade Estadual de Campinas, Campinas, Brazil
4: Also at Universidade Federal de Pelotas, Pelotas, Brazil
5: Also at Université Libre de Bruxelles, Bruxelles, Belgium
6: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia
7: Also at Joint Institute for Nuclear Research, Dubna, Russia
8: Now at Ain Shams University, Cairo, Egypt
9: Now at British University in Egypt, Cairo, Egypt
10: Now at Cairo University, Cairo, Egypt
11: Also at Université de Haute Alsace, Mulhouse, France
12: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State
University, Moscow, Russia
13: Also at CERN, European Organization for Nuclear Research, Geneva,
Switzerland
14: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
15: Also at University of Hamburg, Hamburg, Germany
16: Also at Brandenburg University of Technology, Cottbus, Germany
17: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
18: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
19: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary
20: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India
21: Also at Institute of Physics, Bhubaneswar, India
22: Also at University of Visva-Bharati, Santiniketan, India
23: Also at University of Ruhuna, Matara, Sri Lanka
24: Also at Isfahan University of Technology, Isfahan, Iran
25: Also at Yazd University, Yazd, Iran
26: Also at Plasma Physics Research Center, Science and Research Branch,
Islamic Azad University, Tehran, Iran
27: Also at Università degli Studi di Siena, Siena, Italy
28: Also at INFN Sezione di Milano-Bicocca; Università di Milano-Bicocca,
Milano, Italy
29: Also at Purdue University, West Lafayette, USA
30: Also at International Islamic University of Malaysia, Kuala Lumpur,
Malaysia
31: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia
32: Also at Consejo Nacional de Ciencia y Tecnología, Mexico city, Mexico
33: Also at Warsaw University of Technology, Institute of Electronic Systems,
Warsaw, Poland
34: Also at Institute for Nuclear Research, Moscow, Russia
35: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
36: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
37: Also at University of Florida, Gainesville, USA
38: Also at P.N. Lebedev Physical Institute, Moscow, Russia
39: Also at California Institute of Technology, Pasadena, USA
40: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
41: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
42: Also at University of Belgrade, Faculty of Physics and Vinca Institute of
Nuclear Sciences, Belgrade, Serbia
43: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy
44: Also at National and Kapodistrian University of Athens, Athens, Greece
45: Also at Riga Technical University, Riga, Latvia
46: Also at Universität Zürich, Zurich, Switzerland
47: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna,
Austria
48: Also at Gaziosmanpasa University, Tokat, Turkey
49: Also at Istanbul Aydin University, Istanbul, Turkey
50: Also at Mersin University, Mersin, Turkey
51: Also at Cag University, Mersin, Turkey
52: Also at Piri Reis University, Istanbul, Turkey
53: Also at Adiyaman University, Adiyaman, Turkey
54: Also at Izmir Institute of Technology, Izmir, Turkey
55: Also at Necmettin Erbakan University, Konya, Turkey
56: Also at Marmara University, Istanbul, Turkey
57: Also at Kafkas University, Kars, Turkey
58: Also at Istanbul Bilgi University, Istanbul, Turkey
59: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom
60: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
61: Also at Instituto de Astrofísica de Canarias, La Laguna, Spain
62: Also at Utah Valley University, Orem, USA
63: Also at Beykent University, Istanbul, Turkey
64: Also at Bingol University, Bingol, Turkey
65: Also at Erzincan University, Erzincan, Turkey
66: Also at Sinop University, Sinop, Turkey
67: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey
68: Also at Texas A&M University at Qatar, Doha, Qatar
69: Also at Kyungpook National University, Daegu, Korea