HIG-17-006

$Revision:443592$
<EMAIL_ADDRESS>$Id:HIG-17-006.tex4435922018-01-3116:15:34Zobondu$

HIG-17-006

# Search for resonant and nonresonant Higgs boson pair production in the
$\bbbar\ell\nu\ell\nu$ final state in proton-proton collisions at
$\sqrt{s}=13\TeV$

###### Abstract

Searches for resonant and nonresonant pair-produced Higgs bosons ($\PH\PH$)
decaying respectively into $\ell\nu\ell\nu$, through either $\PW$ or $\Z$
bosons, and $\bbbar$ are presented. The analyses are based on a sample of
proton-proton collisions at $\sqrt{s}=13\TeV$, collected by the CMS experiment
at the LHC, corresponding to an integrated luminosity of 35.9. Data and
predictions from the standard model are in agreement within uncertainties. For
the standard model $\PH\PH$ hypothesis, the data exclude at 95% confidence
level a product of the production cross section and branching fraction larger
than 72fb, corresponding to 79 times the standard model prediction.
Constraints are placed on different scenarios considering anomalous couplings,
which could affect the rate and kinematics of $\PH\PH$ production. Upper
limits at 95% confidence level are set on the production cross section of
narrow-width spin-0 and spin-2 particles decaying to Higgs boson pairs, the
latter produced with minimal gravity-like coupling.

##  0.1 Introduction

The Brout–Englert–Higgs mechanism is a key element of the standard model (SM)
of elementary particles and their interactions, explaining the origin of mass
through spontaneous breaking of electroweak symmetry [1, 2, 3, 4, 5, 6]. The
discovery of a Higgs boson with a mass $m_{\PH}$ around 125by the ATLAS and
CMS experiments [7, 8, 9] fixes the value, in the SM, of the self-coupling
$\lambda$ in the scalar potential, whose shape is determined by the symmetries
of the SM and the requirement of renormalisability. Direct information on the
Higgs three- and four-point interactions will provide an indication of the
scalar potential structure.

Nonresonant Higgs boson pair production ($\PH\PH$) can be used to directly
study the Higgs boson self-coupling. At the CERN LHC, Higgs boson pairs are
predominantly produced through gluon-gluon fusion via two destructively
interfering diagrams, shown in Fig. 1. In the SM the destructive interference
between these two diagrams makes the observation of $\PH\PH$ production
extremely challenging, even in the most optimistic scenarios of energy and
integrated luminosity at the future High Luminosity LHC [10, 11]. The SM cross
section for $\PH\PH$ production in proton-proton collisions at
$\sqrt{s}=13$for a Higgs boson mass of 125is $\sigma^{\PH\PH}=33.5$fb at next-
to-next-to-leading order (NNLO) in quantum chromodynamics (QCD) for the gluon-
gluon fusion process [12, 13, 14, 15, 16, 17, 18, 19, 20, 21].

Indirect effects at the electroweak scale arising from beyond the standard
model (BSM) phenomena at a higher scale can be parameterised in an effective
field theory framework [22, 23, 24] by introducing coupling modifiers for the
SM parameters involved in $\PH\PH$ production, namely
$\kappa_{\lambda}=\lambda/\lambda_{\mathrm{SM}}$ for the Higgs boson self-
coupling $\lambda$ and $\kappa_{\PQt}=y_{\PQt}/y_{\PQt_{\mathrm{SM}}}$ for the
top quark Yukawa coupling $y_{\PQt}$. Such modifications of the Higgs boson
couplings could enhance Higgs boson pair production to rates observable with
the current dataset. The relevant part of the modified Lagrangian takes the
form:

${\cal
L}_{\PH}=\frac{1}{2}\partial_{\mu}\PH\,\partial^{\mu}\PH-\frac{1}{2}m_{\PH}^{2}\PH^{2}-{\kappa_{\lambda}}\,\lambda_{\mathrm{SM}}\,v\,\PH^{3}-\frac{m_{\PQt}}{v}(v+{\kappa_{\PQt}}\,\PH)\,({\PAQt}_{\text{L}}\PQt_{\mathrm{R}}+\text{h.c.}),$
(1)

where $\PH$ is the Higgs boson field, $v$ is the vacuum expectation value of
$\PH$, $m_{\PQt}$ is the top quark mass, $\bar{\PQt}_{\text{L}}$ and
$\PQt_{\mathrm{R}}$ are the left- and right-handed top quark fields, and h.c.
is the Hermitian conjugate. The appearance of new contact-like interactions,
not considered in this paper, could also result in an enhancement of $\PH\PH$
production.

Extensions of the scalar sector of the SM postulate the existence of
additional Higgs bosons. An explored scenario is the two-Higgs-doublet model
(2HDM) [25], where a second doublet of complex scalar fields is added to the
SM scalar sector Lagrangian. The generic 2HDM potential has a large number of
degrees of freedom, which can be reduced to six under specific assumptions. In
case the new CP-even state is massive enough (mass larger than $2m_{\PH}$) it
can decay to a pair of Higgs bosons. Models inspired by warped extra
dimensions [26] predict the existence of new heavy particles that can decay to
pairs of Higgs bosons. Examples of such particles are the radion (spin 0) [27,
28, 29, 30] or the first Kaluza–Klein (KK) excitation of the graviton (spin 2)
[31, 32]. In the following, we will use X to denote a generic state decaying
into pairs of Higgs bosons.

Searches for Higgs boson pair production have been performed by the ATLAS and
CMS experiments using LHC proton-proton collision data. These include searches
for BSM production as well as more targeted searches for production with SM-
like kinematics in $\sqrt{s}=8$ [33, 34, 35, 36, 37] and 13data [38, 39].

This paper reports on a search for Higgs boson pair production, $\PH\PH$, and
resonant Higgs boson pair production, $\text{X}\to\PH\PH$, where one of the
$\PH$ decays into $\bbbar$, and the other into $\PZ(\ell\ell)\PZ(\PGn\PGn)$ or
$\PW(\ell\PGn)\PW(\ell\PGn)$, where $\ell$ is either an electron, a muon, or a
tau lepton that decays leptonically. The search is based on LHC proton-proton
collision data at $\sqrt{s}=13$collected by the CMS experiment, corresponding
to an integrated luminosity of 35.9. The analysis focuses on the invariant
mass distribution of the b jet pairs, searching for a resonant-like excess
compatible with the Higgs boson mass, in combination with an artificial neural
network discriminator based on kinematic information. The dominant background
is production, with smaller contributions from Drell–Yan (DY) and single top
quark production.

Figure 1:  Feynman diagrams for Higgs boson pair production via gluon fusion
in the SM. The coupling modifiers for the Higgs boson self-coupling and the
top quark Yukawa coupling are denoted by $\kappa_{\lambda}$ and
$\kappa_{\PQt}$, respectively.

##  0.2 The CMS detector

The central feature of the CMS apparatus is a superconducting solenoid of 6m
internal diameter, providing a magnetic field of 3.8T. Within the solenoid
volume are a silicon pixel and strip tracker, a lead tungstate crystal
electromagnetic calorimeter (ECAL), and a brass and scintillator hadron
calorimeter, each composed of a barrel and two endcap sections. Forward
calorimeters extend the pseudorapidity coverage provided by the barrel and
endcap detectors. Muons are detected in gas-ionisation 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. [40].

##  0.3 Event simulation

The main background processes, in decreasing order of importance, are , DY,
and single top quark production. Diboson, triboson, V and SM single Higgs
boson production are also considered. Other contributions, such as +jets or
QCD multijet events with jets misidentified as leptons, are negligible due to
the dilepton selection described in the next section. The dominant
contribution, especially in the $\Pepm\mu^{\mp}$ channel, arises from $\ttbar$
production yielding the same final state as the signal process (two b quark
jets, two leptons, and two neutrinos) when both bosons from top quark decays
further decay leptonically.

Background simulation samples have been generated at next-to-leading order
(NLO) in QCD using 2 [41, 42, 43, 44, 45], and versions 2.2.2.0 and 2.3.2.2
[46] with FxFx merging [47] and MadSpin [48]. The signal samples of gluon
fusion production of two Higgs bosons, and of spin-0 or spin-2 narrow
resonances decaying into two Higgs bosons, have been generated at leading
order (LO) in QCD using version 2.2.2.0. The spin-2 narrow resonance is
produced as a KK-graviton with minimal coupling [49], leading to spin
projection $\pm$2 on the beam axis. The mass of the Higgs boson has been fixed
to 125 [50], and its branching fractions to those in the SM. One of the Higgs
bosons is required to decay into a pair of b quarks, while the second one is
required to decay to final states containing two leptons and two neutrinos of
any flavour. This implies that the signal samples contain both
$\PH\to\PZ(\ell\ell)\PZ(\PGn\PGn)$ and $\PH\to\PW(\ell\PGn)\PW(\ell\PGn)$
decay chains, leading to a total branching fraction
$\mathcal{B}(\PH\PH\to\bbbar\mathrm{V}\mathrm{V}\to\bbbar\ell\PGn\ell\PGn)$ of
2.7% [12]. The event generators used for both signal and background samples
are interfaced with 8.212 [51, 52] for simulation of the parton showering,
hadronisation, and underlying event using the CUETP8M1 tune [53]. The NNPDF
3.0 [54] LO and NLO Parton Distribution Functions (PDF) are used.

For all processes, the detector response is simulated using a detailed
description of the CMS apparatus, based on the package [55]. Additional
$\Pp\Pp$ interactions in the same and in the neighbouring bunch crossings
(pileup) are generated with and overlapped with the simulated events of
interest to reproduce the pileup measured in data.

All background processes are normalised to their most accurate theoretical
cross sections. The , DY, single top quark and $\PW^{+}\PW^{-}$ samples are
normalised to NNLO precision in QCD [56, 57, 58, 59], while remaining diboson,
triboson and $\ttbar\mathrm{V}$ processes are normalised to NLO precision in
QCD [60, 46]. The single Higgs boson production cross section is computed at
the NNLO precision of QCD corrections and NLO precision of electroweak
corrections [12].

##  0.4 Event selection and background predictions

Data are collected with a set of dilepton triggers. The $\pt$ thresholds
applied by the triggers are asymmetric and channel-dependent, and vary from 17
to 23for the leading leptons and from 8 to 12for the subleading leptons.
Trigger efficiencies are measured with a “tag-and-probe” technique [61] as a
function of lepton $\pt$ and $\eta$ in a data control region consisting of
$\PZ\to\ell\ell$ events.

Events with two oppositely charged leptons (, , $\mu^{\mp}$) are selected
using asymmetric $\pt$ requirements, chosen to be above the corresponding
trigger thresholds, for leading and subleading leptons of 25and 15for $\Pe\Pe$
and $\PGm\Pe$ events, 20and 10for $\PGm\PGm$ events, and 25and 10for $\Pe\PGm$
events. Electrons in the pseudorapidity range $\abs{\eta}<2.5$ and muons in
the range $\abs{\eta}<2.4$ are considered.

Electrons, reconstructed by associating tracks with ECAL clusters, are
identified by a sequential selection using information on the cluster shape in
the ECAL, track quality, and the matching between the track and the ECAL
cluster. Additionally, electrons from photon conversions are rejected [62].
Muons are reconstructed from tracks found in the muon system, associated with
tracks in the silicon tracking detectors. They are identified based on the
quality of the track fit and the number of associated hits in the different
tracking detectors [63]. The lepton isolation, defined as the scalar $\pt$ sum
of all particle candidates in a cone around the lepton, excluding the lepton
itself, divided by the lepton $\pt$, is required to be $<$0.04 for electrons
(with a cone of radius $\Delta
R=\sqrt{\smash[b]{(\Delta\phi)^{2}+(\Delta\eta)^{2}}}=0.3$) and $<$0.15 for
muons (with a cone of radius $\Delta R=0.4$). Lepton identification and
isolation efficiencies in the simulation are corrected for residual
differences with respect to data. These corrections are measured in a data
sample, enriched in $\PZ\to\ell\ell$ events, using a “tag-and-probe” method
and are parameterised as a function of lepton $\pt$ and $\eta$.

Jets are reconstructed using a particle flow (PF) technique [64]. PF
candidates are clustered to form jets using the anti-clustering algorithm [65]
with a distance parameter of 0.4, implemented in the package [66]. Jet
energies are corrected for residual nonuniformity and nonlinearity of the
detector response [67]. Jets are required to have $\pt>20$, $\abs{\eta}<2.4$,
and be separated from identified leptons by a distance of $\Delta R>0.3$. The
missing transverse momentum vector, defined as the projection onto the
transverse plane relative to the beam axis, of the negative vector sum of the
momenta of all PF candidates, is referred to as $\ptvecmiss$ [68, 69]. Its
magnitude is denoted by $\ptmiss$. Corrections to the jet energies are
propagated to $\ptvecmiss$.

The reconstructed vertex with the largest value of summed object $\pt^{2}$ is
taken to be the primary $\Pp\Pp$ interaction vertex, considering the objects
returned by a clustering algorithm applied to all charged tracks associated
with the vertex, plus the corresponding associated $\ptvecmiss$.

The combined multivariate algorithm [70, 71] is used to identify jets
originating from b quarks. Jets are considered as b tagged if they pass the
medium working point of the algorithm, which provides around 70% efficiency
with a mistag rate less than 1%. Correction factors are applied in the
simulation to the selected jets to account for the different response of the
combined multivariate algorithm between data and simulation [71]. Among all
possible dijet combinations fulfilling the previous criteria, we select the
two jets with the highest combined multivariate algorithm outputs.

After the final object selection consisting of two opposite sign leptons and
two b-tagged jets, a requirement of $12<m_{\ell\ell}<m_{\PZ}-15$is applied to
suppress quarkonia resonances and jets misidentified as leptons, and to remove
the large background at the boson peak as well as the high-$m_{\ell\ell}$ tail
of the DY and $\ttbar$ processes. This requirement has a negligible impact on
signal events where one $\PH$ decays as $\PH\to\PW(\ell\PGn)\PW(\ell\PGn)$,
and removes only the portion of $\PH\to\PZ(\ell\ell)\PZ(\PGn\PGn)$ decays with
on-shell $\PZ(\ell\ell)$ legs. Figure 2 shows the dijet for data and simulated
events after requiring the selection criteria described in this section.

Figure 2:  The dijet distributions in data and simulated events after
requiring two leptons, two b-tagged jets, and $12<m_{\ell\ell}<m_{\PZ}-15$,
for $\Pep\Pem$ (top left), $\Pepm{}\mu^{\mp}$ (top right), and $\PGmp{}\PGmm$
(bottom) events. The various signal hypotheses displayed have been scaled to a
cross section of 5pb for display purposes. Error bars indicate statistical
uncertainties, while shaded bands show post-fit systematic uncertainties.

All the background processes are estimated from simulation, with the exception
of DY production in the $\Pep\Pem$ and $\PGmp\PGmm$ channels. The DY
contribution in the $\Pepm\mu^{\mp}$ channels is almost negligible, and is
taken from simulation.

The contribution of the DY process in the analysis selection is estimated from
a data sample enriched in DY plus jets events. The estimate is performed by
requiring all the selection criteria described above, except for the b tagging
requirements. The resulting dataset is corrected with weights to represent the
DY contribution in the full selection. The weights are a function of kinematic
variables and are tuned to reproduce the effect of applying the b tagging
requirements on the DY process. They account for the following features:

  * •

The b tagging efficiencies are not constant and depend on jet kinematics.
Moreover, this dependency is different for $\PQb$-, $\PQc$\- or light-flavour
jets.

  * •

The relative contributions of DY plus two jets of flavours $k$ and $l$, where
$k,l=\PQb,\PQc,\text{or light-flavour}$, to the DY plus two jets process are
not constant throughout the phase-space. Modelling the effect of b tagging
requires to parameterise the fractions $F_{kl}$ of jets with flavours $k$ and
$l$ as a function of event kinematics.

We compute the weights as:

$W_{\text{sim}}=\sum_{k,l=\PQb,\PQc,\text{light-
flavour}}\,F_{kl}(\mathrm{BDT})\,\epsilon_{k}(\pt^{\cmsSymbolFace{j}_{1}},\eta^{\cmsSymbolFace{j}_{1}})\,\epsilon_{l}(\pt^{\cmsSymbolFace{j}_{2}},\eta^{\cmsSymbolFace{j}_{2}})\text{,}$
(2)

where $\epsilon_{k}$ and $\epsilon_{l}$ are the b tagging efficiencies for
$k$\- and $l$-flavour jets calculated from simulation as a function of and
$\eta$ of the jets and corrected for differences between data and simulation,
and $\cmsSymbolFace{j}_{1}$ and $\cmsSymbolFace{j}_{2}$ denote the two
$\pt$-ordered jets selected according to the above requirements. The expected
fractions of jets with flavours $k$ and $l$ in the dataset are denoted by
$F_{kl}$ and are parameterised as a function of the output value of a Boosted
Decision Tree (BDT) [72]. The indices $k$ and $l$ refer to the assumed flavour
of $\cmsSymbolFace{j}_{1}$ and $\cmsSymbolFace{j}_{2}$, respectively. The
flavour fractions $F_{kl}$ are estimated from a simulated DY sample. Their
dependency on the BDT output value accounts for the different kinematical
behaviours of heavy- or light-flavour associated DY processes, effectively
reducing the dimensionality of the phase-space to a single variable. The BDT
is trained to discriminate DY+$\PQb\PAQb,\PQc\PAQc$ from other DY associated
production processes using the following input variables:
$\pt^{\cmsSymbolFace{j}_{1}}$, $\pt^{\cmsSymbolFace{j}_{2}}$,
$\eta^{\cmsSymbolFace{j}_{1}}$, $\eta^{\cmsSymbolFace{j}_{2}}$,
$\pt^{\cmsSymbolFace{j}\cmsSymbolFace{j}}$, $\pt^{\ell\ell}$,
$\eta^{\ell\ell}$, $\Delta\phi(\ell\ell,\ptvecmiss)$ (defined as the
$\Delta\phi$ between the dilepton system and $\ptvecmiss$), number of jets,
and $H_{\mathrm{T}}$ defined as the scalar sum of the transverse momentum of
all selected leptons and jets.

Beside DY, the data sample without b tagging requirements contains small
contributions from other backgrounds such as $\ttbar$, single top quark and
diboson production. Hence, the same reweighting procedure is applied to
simulated samples for these processes, and the result is subtracted from the
weighted data to define the estimate of the DY background in the analysis
region.

The method is validated both in simulation and in two data control regions
requiring either $m_{\ell\ell}>m_{\PZ}-15$or $\abs{m_{\ell\ell}-m_{\PZ}}<15$.
The predicted DY distributions are in agreement with data and simulation
within the uncertainties of the method, described in section 0.6.

##  0.5 Parameterised multivariate discriminators for signal extraction

Deep neural network (DNN) discriminators, based on the Keras library [73], are
used to improve the signal-to-background separation. As the dominant
background process ($\ttbar$ production) is irreducible, the DNNs rely on
information related to event kinematics. The variables provided as input to
the DNNs exploit the presence in the signal of two Higgs bosons decaying into
two b jets on the one hand, and two leptons and two neutrinos on the other
hand, which results in different kinematics for the dilepton and dijet systems
between signal and background processes. The variables used as input are:
$m_{\ell\ell}$, $\Delta R_{\ell\ell}$, $\Delta
R_{\cmsSymbolFace{j}\cmsSymbolFace{j}}$,
$\Delta\phi(\ell\ell,\cmsSymbolFace{j}\cmsSymbolFace{j})$ (defined as the
$\Delta\phi$ between the dijet and the dilepton systems), $\pt^{\ell\ell}$,
$\pt^{\cmsSymbolFace{j}\cmsSymbolFace{j}}$, min$\left(\Delta
R_{\cmsSymbolFace{j}\ell}\right)$, and
$m_{\text{T}}=\sqrt{\smash[b]{2\pt^{\ell\ell}\ptmiss[1-\cos\Delta\phi(\ell\ell,\ptvecmiss)]}}$.

The DNNs utilise a parameterised machine learning technique [74] in order to
ensure optimal sensitivity on the full range of signal hypotheses considered
in these searches. In this approach, one or more physics parameters describing
the wider scope of the problem, as for example the mass of the resonance in
the resonant search case, are provided as input to the DNNs, in addition to
reconstructed quantities. The parameterised network is able to perform as well
as individual networks trained on specific hypotheses (parameter values) while
requiring only a single training, and provides a smooth interpolation to cases
not seen during the training phase, as shown by Fig. 3. Two parameterised DNNs
are trained: one for the resonant and one for the nonresonant search. In the
first case, the set of parameters are the masses of the resonance, providing
13 values for the network training ($m_{\text{X}}=260$, 270, 300, 350, 400,
450, 500, 550, 600, 650, 750, 800, 900), and a discrete variable indicating
the dilepton flavour channel: same flavour ($\Pep\Pem$ and $\PGmp\PGmm$) or
different flavour ($\Pepm\mu^{\mp}$). In the second case, the parameters are
$\kappa_{\lambda}$ and $\kappa_{\PQt}$, providing 32 combinations of those for
the network training ($\kappa_{\lambda}=-20$, -5, 0, 1, 2.4, 3.8, 5, 20 and
$\kappa_{\PQt}=0.5$, 1, 1.75, 2.5), and the dilepton flavour channel variable
as in the resonant case.

Figure 3:  Performance of the parameterised DNN for the resonant search, shown
as the selection efficiency for the $m_{\text{X}}=$ 650 GeV signal as a
function of the selection efficiency for the background (ROC curve), for the
combined $\Pep\Pem$, $\PGmp\PGmm$ and $\Pepm\mu^{\mp}$ channels. The dashed
line corresponds to the DNN used in the analysis, trained on all available
signal samples, and evaluated at $m_{\text{X}}=$ 650 GeV. The dotted line
shows an alternative DNN trained using all signal samples except for
$m_{\text{X}}=$ 650 GeV, and evaluated at $m_{\text{X}}=$ 650 GeV. Both curves
overlap, indicating that the parameterised DNN is able to generalise to cases
not seen during the training phase by interpolating the signal behaviour from
nearby $m_{\text{X}}$ points.

The $m_{\cmsSymbolFace{j}\cmsSymbolFace{j}}$ distributions, and resonant and
nonresonant DNN discriminators after selection requirements, are shown in
Figs. 4 and 5, respectively. Given their discrimination power between signal
and background, both variables are used to enhance the sensitivity of the
analysis. We define three regions in $m_{\cmsSymbolFace{j}\cmsSymbolFace{j}}$:
two of them enriched in background,
$m_{\cmsSymbolFace{j}\cmsSymbolFace{j}}<75$and
$m_{\cmsSymbolFace{j}\cmsSymbolFace{j}}\geq 140$, and the other enriched in
signal, $m_{\cmsSymbolFace{j}\cmsSymbolFace{j}}\in\left[\,75,140\,\right)$. In
each region, we use the DNN output as our final discriminant, as shown in Fig.
6, where the three $m_{\cmsSymbolFace{j}\cmsSymbolFace{j}}$ regions are
represented in a single distribution.

Figure 4:  The $m_{\cmsSymbolFace{j}\cmsSymbolFace{j}}$ distribution in data
and simulated events after requiring all selection criteria in the $\Pep\Pem$
(top left), $\Pepm{}\mu^{\mp}$ (top right), and $\PGmp{}\PGmm$ (bottom)
channels. The various signal hypotheses displayed have been scaled to a cross
section of 5pb for display purposes. Error bars indicate statistical
uncertainties, while shaded bands show post-fit systematic uncertainties.

Figure 5:  The DNN output distributions in data and simulated events after
requiring all selection criteria, in the $\Pep\Pem$ (top), $\Pepm{}\mu^{\mp}$
(middle), and $\PGmp\PGmm$ (bottom) channels. Output values towards 0 are
background-like, while output values towards 1 are signal-like. The
parameterised resonant DNN output (left) is evaluated at $m_{\text{X}}=400$and
the parameterised nonresonant DNN output (right) is evaluated at
$\kappa_{\lambda}=1$, $\kappa_{\PQt}=1$. The two signal hypotheses displayed
have been scaled to a cross section of 5pb for display purposes. Error bars
indicate statistical uncertainties, while shaded bands show post-fit
systematic uncertainties.

Figure 6:  The DNN output distributions in data and simulated events, for the
$\Pep\Pem$ (top), $\Pepm{}\mu^{\mp}$ (middle), and $\PGmp\PGmm$ (bottom)
channels, in three different $m_{\cmsSymbolFace{j}\cmsSymbolFace{j}}$ regions:
$m_{\cmsSymbolFace{j}\cmsSymbolFace{j}}<75$,
$m_{\cmsSymbolFace{j}\cmsSymbolFace{j}}\in\left[\,75,140\,\right)$, and
$m_{\cmsSymbolFace{j}\cmsSymbolFace{j}}\geq 140$. The parameterised resonant
DNN output (left) is evaluated at $m_{\text{X}}=400$and the parameterised
nonresonant DNN output (right) is evaluated at $\kappa_{\lambda}=1$,
$\kappa_{\PQt}=1$. The two signal hypotheses displayed have been scaled to a
cross section of 5pb for display purposes. Error bars indicate statistical
uncertainties, while shaded bands show post-fit systematic uncertainties.

##  0.6 Systematic uncertainties

We investigate sources of systematic uncertainties and their impact on the
statistical interpretation of the results by considering both uncertainties in
the normalisation of the various processes in the analysis, as well as those
affecting the shapes of the distributions.

Theoretical uncertainties in the cross sections of backgrounds estimated using
simulation are considered as systematic uncertainties in the yield
predictions. The uncertainty in the total integrated luminosity is determined
to be 2.5% [75].

The following sources of systematic uncertainties that affect the
normalisation and shape of the templates used in the statistical evaluation
are considered:

  * •

Trigger efficiency, lepton identification and isolation: uncertainties in the
measurement, using a “tag-and-probe” technique, of trigger efficiencies as
well as electron and muon isolation and identification efficiencies, are
considered as sources of systematic uncertainties. These are evaluated as a
function of lepton $\pt$ and $\eta$, and their effect on the analysis is
estimated by varying the corrections to the efficiencies by $\pm$1 standard
deviation.

  * •

Jet energy scale and resolution: uncertainties in the jet energy scale are of
the order of a few percent and are computed as a function of jet $\pt$ and
$\eta$ [67]. A difference in the jet energy resolution of about 10% between
data and simulation is accounted for by worsening the jet energy resolution in
simulation by $\eta$-dependent factors. The uncertainty due to these
corrections is estimated by a variation of the factors applied by $\pm$1
standard deviation. Variations of jet energies are propagated to $\ptvecmiss$.

  * •

b tagging: b tagging efficiency and light-flavour mistag rate corrections and
associated uncertainties are determined as a function of the jet $\pt$ [71].
Their effect on the analysis is estimated by varying these corrections by
$\pm$1 standard deviation.

  * •

Pileup: the measured total inelastic cross section is varied by $\pm$5% [76]
to produce different expected pileup distributions.

  * •

Renormalisation and factorisation scale uncertainty: this uncertainty is
estimated by varying the renormalisation ($\mu_{\mathrm{R}}$) and the
factorisation ($\mu_{\mathrm{F}}$) scales used during the generation of the
simulated samples independently by factors of 0.5, 1, or 2. Unphysical cases,
where the two scales are at opposite extremes, are not considered. An envelope
is built from the 6 possible combinations by keeping maximum and minimum
variations for each bin of the distributions, and is used as an estimate of
the scale uncertainties for all the background and signal samples.

  * •

PDF uncertainty: the magnitudes of the uncertainties related to the PDFs and
the variation of the strong coupling constant for each simulated background
and signal process are obtained using variations of the NNPDF 3.0 set [54],
following the PDF4LHC prescriptions [77, 78].

  * •

Simulated sample size: the finite nature of simulated samples is considered as
an additional source of systematic uncertainty. For each bin of the
distributions, one additional uncertainty is added, where only the considered
bin is altered by $\pm$1 standard deviation, keeping the others at their
nominal value.

  * •

DY background estimate from data: the systematic uncertainties listed above,
which affect the simulation samples, are propagated to $\epsilon_{k}$ and
$F_{kl}$, both computed from simulation. These uncertainties are then
propagated to the weights $W_{\text{sim}}$ and to the normalisation and shape
of the estimated DY background contribution. The uncertainty due to the finite
size of the simulation samples used for the determination of $\epsilon_{k}$
and $F_{kl}$ is also taken into account. Since previous measurements [79, 80]
have shown that the flavour composition of DY events with associated jets in
data is compatible with the simulation within scale uncertainties, no extra
source of theoretical uncertainty has been considered for $F_{kl}$. To account
for residual differences between the $\Pep\Pem$ and $\PGmp\PGmm$ channels not
taken into account by $F_{kl}$, due to the different requirements on lepton
$\pt$, a 5% uncertainty in the normalisation of the DY background estimate is
added in both channels.

The effects of these uncertainties on the total yields in the analysis
selection are summarised in Table 0.6.

Summary of the systematic uncertainties and their impact on total background
yields and on the SM and $m_{\text{X}}=400$signal hypotheses in the signal
region.  Source Background yield variation Signal yield variation Electron
identification and isolation 2.0–3.2% 1.9–2.9% Jet b tagging (heavy-flavour
jets) 2.5% 2.5–2.7% Integrated luminosity 2.5% 2.5% Trigger efficiency
0.5–1.4% 0.4–1.4% Pileup 0.3–1.4% 0.3–1.5% Muon identification 0.4–0.8%
0.4–0.7% PDFs 0.6–0.7% 1.0–1.4% Jet b tagging (light-flavour jets) 0.3%
0.3–0.4% Muon isolation 0.2–0.3% 0.1–0.2% Jet energy scale $<$0.1–0.3%
0.7–1.0% Jet energy resolution 0.1% $<$0.1% Affecting only $\ttbar$
(85.1–95.7% of the total bkg.) $\mu_{\mathrm{R}}$ and $\mu_{\mathrm{F}}$
scales 12.8–12.9% $\ttbar$ cross section 5.2% Simulated sample size $<$0.1%
Affecting only DY in $\Pepm{}\mu^{\mp}$ channel (0.9% of the total bkg.)
$\mu_{\mathrm{R}}$ and $\mu_{\mathrm{F}}$ scales 24.6–24.7% Simulated sample
size 7.7–11.6% DY cross section 4.9% Affecting only DY estimate from data in
same-flavour events (7.1–10.7% of the total bkg.) Simulated sample size
18.8–19.0% Normalisation 5.0% Affecting only single top quark (2.5–2.9% of the
total bkg.) Single $\PQt$ cross section 7.0% Simulated sample size $<$0.1–1.0%
$\mu_{\mathrm{R}}$ and $\mu_{\mathrm{F}}$ scales $<$0.1–0.2% Affecting only
signal SM signal $m_{\text{X}}=400\GeV$ $\mu_{\mathrm{R}}$ and
$\mu_{\mathrm{F}}$ scales 24.2% 4.6–4.7% Simulated sample size $<$0.1% $<$0.1%

##  0.7 Results

A binned maximum likelihood fit is performed in order to extract best fit
signal cross sections. The fit is performed using templates built from the DNN
output distributions in the three $m_{\cmsSymbolFace{j}\cmsSymbolFace{j}}$
regions, as shown in Fig. 6, and in the three channels ($\Pep\Pem$,
$\PGmp\PGmm$, and $\Pepm\mu^{\mp}$). The likelihood function is the product of
the Poisson likelihoods over all bins of the templates and is given by

$L(\beta_{\text{signal}},\beta_{k}|\text{data})=\prod_{i=1}^{N_{\text{bins}}}\frac{\mu_{i}^{n_{i}}\,\re^{-\mu_{i}}}{n_{i}!},$

where $n_{i}$ is the number of observed events in bin $i$ and the Poisson mean
for bin $i$ is given by

$\mu_{i}=\beta_{\text{signal}}\,S_{i}+\sum_{k}\beta_{k}\,T_{k,i},$

where $k$ denotes all of the considered background processes, $T_{k,i}$ is the
bin content of bin $i$ of the template for process $k$, and $S_{i}$ is the bin
content of bin $i$ of the signal template. The parameter $\beta_{k}$ is the
nuisance parameter for the normalisation of the process $k$, constrained by
theoretical uncertainties with a log-normal prior, and $\beta_{\text{signal}}$
is the signal strength, unconstrained. For each systematic uncertainty
affecting the shape (normalisation) of the templates, a nuisance parameter is
introduced with a Gaussian (log-normal) prior.

The best-fit values for all the nuisance parameters, as well as the
corresponding post-fit uncertainties, are extracted by performing a binned
maximum likelihood fit, in the background-only hypothesis, of the
$m_{\cmsSymbolFace{j}\cmsSymbolFace{j}}$ vs. DNN output distributions (such as
Fig. 6 left) to the data. Only nuisance parameters affecting the backgrounds
are considered.

###  0.7.1 Resonant production

The fit results in signal cross sections compatible with zero; no significant
excess above background predictions is observed for X particle mass hypotheses
between 260 and 900. We set upper limits at 95% confidence level (CL) on the
product of the production cross section for X and branching fraction for
$\text{X}\to\PH\PH\to\bbbar\mathrm{V}\mathrm{V}\to\bbbar\ell\PGn\ell\PGn$
using the asymptotic modified frequentist method (asymptotic
$\mathrm{CL_{s}}$) [81, 82, 83] as a function of the X mass hypothesis. The
limits are shown in Fig. 7. The observed upper limits on the product of the
production cross section and branching fraction for a narrow-width spin-0
resonance range from 430 to 17fb, in agreement with expected upper limits of
$340^{+140}_{-100}$ to $14^{+6}_{-4}$fb. For narrow-width spin-2 particles
produced in gluon fusion with minimal gravity-like coupling, the observed
upper limits range from 450 to 14fb, in agreement with expected upper limits
of $360^{+140}_{-100}$ to $13^{+6}_{-4}$fb.

The left plot of Fig. 7 shows possible cross sections for the production of a
radion, for the parameters $\Lambda_{\mathrm{R}}=1\TeV$ (mass scale) and
$\text{kL}=35$ (size of the extra dimension). The right plot of Fig. 7 shows
possible cross sections for the production of a Kaluza–Klein graviton, for the
parameters $\text{k}/\overline{\text{M}_{\text{Pl}}}=0.1$ (curvature) and
$\text{kL}=35$. These cross sections are taken from [49], assuming absence of
mixing with the Higgs boson.

Figure 7:  Expected (dashed) and observed (continuous) 95% CL upper limits on
the product of the production cross section for X and branching fraction for
$\text{X}\to\PH\PH\to\bbbar\mathrm{V}\mathrm{V}\to\bbbar\ell\PGn\ell\PGn$, as
a function of $m_{\text{X}}$. The inner (green) band and the outer (yellow)
band indicate the regions containing 68 and 95%, respectively, of the
distribution of limits expected under the background-only hypothesis. These
limits are computed using the asymptotic $\mathrm{CL_{s}}$ method, combining
the $\Pep\Pem$, $\PGmp\PGmm$ and $\Pe^{\pm}\PGm^{\mp}$ channels, for spin-0
(left) and spin-2 (right) hypotheses. The solid circles represent fully-
simulated mass points. The dashed red lines represent possible cross sections
for the production of a radion (left) or a Kaluza–Klein graviton (right),
assuming absence of mixing with the Higgs boson [49]. Parameters used to
compute these cross sections can be found in the legend.

###  0.7.2 Nonresonant production

Likewise for the nonresonant case, the fit results in signal cross sections
compatible with zero; no significant excess above background predictions is
seen. We set upper limits at 95% CL on the product of the Higgs boson pair
production cross section and branching fraction for
$\PH\PH\to\bbbar\mathrm{V}\mathrm{V}\to\bbbar\ell\PGn\ell\PGn$ using the
asymptotic $\mathrm{CL_{s}}$, combining the $\Pep\Pem$, $\PGmp\PGmm$ and
$\Pepm\mu^{\mp}$ channels. The observed upper limit on the SM
$\PH\PH\to\bbbar\mathrm{V}\mathrm{V}\to\bbbar\ell\PGn\ell\PGn$ cross section
is found to be 72fb, in agreement with an expected upper limit of
$81^{+42}_{-25}$fb. Including theoretical uncertainties in the SM signal cross
section, this observed upper limit amounts to 79 times the SM prediction, in
agreement with an expected upper limit of $89^{+47}_{-28}$ times the SM
prediction.

In the BSM hypothesis, upper limits are set as a function of
$\kappa_{\lambda}/\kappa_{\PQt}$, as shown in Fig. 8 (left panel), since the
signal kinematics depend only on this ratio of couplings. Red lines show the
theoretical cross sections, along with their uncertainties, for
$\kappa_{\PQt}=1$ (SM) and $\kappa_{\PQt}=2$. The theoretical signal cross
section is minimal for $\kappa_{\lambda}/\kappa_{\PQt}=2.45$ [84],
corresponding to a maximal interference between the diagrams shown on Fig. 1.

Excluded regions in the $\kappa_{\PQt}$ vs. $\kappa_{\lambda}$ plane are shown
in Fig. 8 (right panel). The signal cross sections and kinematics are
invariant under a
$(\kappa_{\lambda},\kappa_{\PQt})\leftrightarrow(-\kappa_{\lambda},-\kappa_{\PQt})$
transformation, hence the expected and observed limits on the production cross
section, as well as the constraints on the $\kappa_{\lambda}$ and
$\kappa_{\PQt}$ parameters respect the same symmetry. The red region in the
panel corresponds to parameters excluded at 95% CL with the observed data,
whereas the dashed black line and the blue areas correspond to the expected
exclusions and the 68 and 95% bands. Isolines of the product of the
theoretical cross section and branching fraction for
$\PH\PH\to\bbbar\mathrm{V}\mathrm{V}\to\bbbar\ell\PGn\ell\PGn$ are shown as
dashed-dotted lines.

Figure 8:  Left: expected (dashed) and observed (continuous) 95% CL upper
limits on the product of the Higgs boson pair production cross section and
branching fraction for
$\PH\PH\to\bbbar\mathrm{V}\mathrm{V}\to\bbbar\ell\PGn\ell\PGn$ as a function
of $\kappa_{\lambda}/\kappa_{\PQt}$. The inner (green) band and the outer
(yellow) band indicate the regions containing 68 and 95%, respectively, of the
distribution of limits expected under the background-only hypothesis. Red
lines show the theoretical cross sections, along with their uncertainties, for
$\kappa_{\PQt}=1$ (SM) and $\kappa_{\PQt}=2$. Right: exclusions in the
($\kappa_{\lambda}$, $\kappa_{\PQt}$) plane. The red region corresponds to
parameters excluded at 95% CL with the observed data, whereas the dashed black
line and the blue areas correspond to the expected exclusions and the 68 and
95% bands (light and dark respectively). Isolines of the product of the
theoretical cross section and branching fraction for
$\PH\PH\to\bbbar\mathrm{V}\mathrm{V}\to\bbbar\ell\PGn\ell\PGn$ are shown as
dashed-dotted lines. The diamond marker indicates the prediction of the SM.
All theoretical predictions are extracted from Refs. [12, 13, 14, 15, 16, 17,
84].

##  0.8 Summary

A search for resonant and nonresonant Higgs boson pair production ($\PH\PH$)
is presented, where one of the Higgs bosons decays to $\bbbar$, and the other
to $\mathrm{V}\mathrm{V}\to\ell\PGn\ell\PGn$, where $\mathrm{V}$ is either a
$\PW$ or a $\PZ$ boson. The LHC proton-proton collision data at
$\sqrt{s}=13$collected by the CMS experiment corresponding to an integrated
luminosity of 35.9are used. Masses are considered in the range between 260 and
900for the resonant search, while anomalous Higgs boson self-coupling and
coupling to the top quark are considered in addition to the standard model
case for the nonresonant search.

The results obtained are in agreement, within uncertainties, with the
predictions of the standard model. For the resonant search, the data exclude a
product of the production cross section and branching fraction of narrow-width
spin-0 particles from 430 to 17fb, in agreement with the expectations of
$340^{+140}_{-100}$ to $14^{+6}_{-4}$fb, and narrow-width spin-2 particles
produced with minimal gravity-like coupling from 450 to 14fb, in agreement
with the expectations of $360^{+140}_{-100}$ to $13^{+6}_{-4}$fb. For the
standard model $\PH\PH$ hypothesis, the data exclude a product of the
production cross section and branching fraction of 72fb, corresponding to 79
times the SM cross section. The expected exclusion is $81^{+42}_{-25}$fb,
corresponding to $89^{+47}_{-28}$ times the SM cross section.

###### Acknowledgements.

We congratulate our colleagues in the CERN accelerator departments for the
excellent performance of the LHC and thank the technical and administrative
staffs at CERN and at other CMS institutes for their contributions to the
success of the CMS effort. In addition, we gratefully acknowledge the
computing centres and personnel of the Worldwide LHC Computing Grid for
delivering so effectively the computing infrastructure essential to our
analyses. Finally, we acknowledge the enduring support for the construction
and operation of the LHC and the CMS detector provided by the following
funding agencies: 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 programme 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 programme of the Foundation for Polish
Science, cofinanced from European Union, Regional Development Fund, the
Mobility Plus programme of the Ministry of Science and Higher Education, the
National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus
2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis
2012/07/E/ST2/01406; the National Priorities Research Program by Qatar
National Research Fund; the Programa Clarín-COFUND del Principado de Asturias;
the Thalis and Aristeia programmes cofinanced by EU-ESF and the Greek NSRF;
the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn
University and the Chulalongkorn Academic into Its 2nd Century Project
Advancement Project (Thailand); and the Welch Foundation, contract C-1845.

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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, 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, 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, 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
Y. Assran8,9, S. Elgammal9, A. Mahrous10 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, S. Regnard,
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
T. Toriashvili13 Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze7 RWTH Aachen University, I. Physikalisches Institut, Aachen,
Germany
C. Autermann, S. Beranek, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M.
Preuten, C. Schomakers, J. Schulz, T. Verlage 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, M.
Olschewski, K. Padeken, 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. Stahl14 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. Borras15, V. Botta, A.
Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G.
Eckerlin, D. Eckstein, T. Eichhorn, E. Eren, E. Gallo16, J. Garay Garcia, A.
Geiser, A. Gizhko, J.M. Grados Luyando, A. Grohsjean, P. Gunnellini, M.
Guthoff, A. Harb, J. Hauk, M. Hempel17, 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. Lohmann17, 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. Pantaleo14, 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. Hartmann14, S.M. Heindl, U. Husemann, F. Kassel14, 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 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. Veres18 Wigner Research Centre for
Physics, Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath19, Á. Hunyadi, F. Sikler, V. Veszpremi, G.
Vesztergombi18, A.J. Zsigmond Institute of Nuclear Research ATOMKI, Debrecen,
Hungary
N. Beni, S. Czellar, J. Karancsi20, A. Makovec, J. Molnar, Z. Szillasi
Institute of Physics, University of Debrecen, Debrecen, Hungary
M. Bartók18, 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. Bahinipati21, S. Bhowmik, P. Mal, K. Mandal, A. Nayak22, D.K. Sahoo21, 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, V.
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. Mohanty14, 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. Maity23, G. Majumder, K. Mazumdar, T. Sarkar23, N. Wickramage24
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. Chenarani25, E. Eskandari Tadavani, S.M. Etesami25, M. Khakzad, M.
Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi26, F. Rezaei
Hosseinabadi, B. Safarzadeh27, 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, C. Caputoa,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,b, A. Ranieria, G.
Selvaggia,b, A. Sharmaa, L. Silvestrisa,14, 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,28, G. Sguazzonia, D. Stroma, L. Viliania,b,14 INFN Laboratori
Nazionali di Frascati, Frascati, Italy
L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera14 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
L. Brianzaa,b, F. Brivioa,b, V. Cirioloa,b, M.E. Dinardoa,b, S. Fiorendia,b,
S. Gennaia, A. Ghezzia,b, P. Govonia,b, S. Gundacker, M. Malbertia,b, S.
Malvezzia, R.A. Manzonia,b, D. Menascea, L. Moronia, M. Paganonia,b, K.
Pauwelsa,b, D. Pedrinia, S. Pigazzinia,b,29, S. Ragazzia,b, 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,14, F. Fabozzia,c, F. Fiengaa,b,
A.O.M. Iorioa,b, W.A. Khana, L. Listaa, S. Meolaa,d,14, P. Paoluccia,14, C.
Sciaccaa,b, F. Thyssena INFN Sezione di Padova a, Università di Padova b,
Padova, Italy, Università di Trento c, Trento, Italy
P. Azzia,14, 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, U. Dossellia, F. Gasparinia,b, U.
Gasparinia,b, A. Gozzelinoa, S. Lacapraraa, P. Lujan, M. Margonia,b, A.T.
Meneguzzoa,b, N. Pozzobona,b, P. Ronchesea,b, R. Rossina,b, F. Simonettoa,b,
E. Torassaa, P. Zottoa,b, G. Zumerlea,b INFN Sezione di Pavia a, Università di
Pavia b, Pavia, Italy
A. Braghieria, A. Magnania,b, P. Montagnaa,b, S.P. Rattia,b, V. Rea, M.
Ressegotti, 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,14, G. Bagliesia, J. Bernardinia, T. Boccalia, L.
Borrello, R. Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, G. Fedia, L.
Gianninia,c, A. Giassia, M.T. Grippoa,28, 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,30, P. Spagnoloa, R. Tenchinia, G. Tonellia,b, A.
Venturia, P.G. Verdinia INFN Sezione di Roma a, Sapienza Università di Roma b,
Rome, Italy
L. Baronea,b, F. Cavallaria, M. Cipriania,b, D. Del Rea,b,14, E. Di
Marcoa,b,31, 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 Ali32, F. Mohamad Idris33, 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 Cruz34, 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. Byszuk35, K. Doroba, A. Kalinowski, M. Konecki, J.
Krolikowski, M. Misiura, M. Olszewski, A. Pyskir, M. Walczak Laboratório de
Instrumentação e Física Experimental de Partículas, Lisboa, Portugal
P. Bargassa, C. Beirão Da Cruz E Silva, A. Di Francesco, P. Faccioli, M.
Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias, M.V. Nemallapudi, J.
Seixas, 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. Matveev36,37, 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. Kim38, E. Kuznetsova39, 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. Bylinkin37 National Research Nuclear University ’Moscow
Engineering Physics Institute’ (MEPhI), Moscow, Russia
R. Chistov40, M. Danilov40, P. Parygin, D. Philippov, S. Polikarpov, E.
Tarkovskii P.N. Lebedev Physical Institute, Moscow, Russia
V. Andreev, M. Azarkin37, I. Dremin37, M. Kirakosyan37, A. Terkulov Skobeltsyn
Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow,
Russia
A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin41, L. Dudko, A.
Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, S.
Petrushanko, V. Savrin, A. Snigirev Novosibirsk State University (NSU),
Novosibirsk, Russia
V. Blinov42, Y.Skovpen42, D. Shtol42 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. Krychkine, 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. Adzic43, 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, 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
J.F. de Trocóniz, M. Missiroli, D. Moran 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, I. Suárez Andrés,
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. Karacheban17, J. Kieseler, H. Kirschenmann, V. Knünz,
A. Kornmayer14, 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. Milenovic44, F. Moortgat, M. Mulders, H.
Neugebauer, S. Orfanelli, L. Orsini, L. Pape, E. Perez, M. Peruzzi, A.
Petrilli, G. Petrucciani, A. Pfeiffer, M. Pierini, A. Racz, T. Reis, G.
Rolandi45, M. Rovere, H. Sakulin, C. Schäfer, C. Schwick, M. Seidel, M.
Selvaggi, A. Sharma, P. Silva, P. Sphicas46, A. Stakia, J. Steggemann, M.
Stoye, M. Tosi, D. Treille, A. Triossi, A. Tsirou, V. Veckalns47, M. Verweij,
W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland
W. Bertl${}^{\textrm{\textdagger}}$, L. Caminada48, K. Deiters, W. Erdmann, R.
Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe,
S.A. Wiederkehr Institute for Particle Physics, ETH Zurich, 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. Amsler49, M.F. Canelli, A. De Cosa, R. Del Burgo, S.
Donato, C. Galloni, T. Hreus, B. Kilminster, J. Ngadiuba, 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
A. Adiguzel50, F. Boran, S. Cerci51, S. Damarseckin, Z.S. Demiroglu, C. Dozen,
I. Dumanoglu, S. Girgis, G. Gokbulut, Y. Guler, I. Hos52, E.E. Kangal53, O.
Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G. Onengut54, K. Ozdemir55, D.
Sunar Cerci51, B. Tali51, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle
East Technical University, Physics Department, Ankara, Turkey
B. Bilin, G. Karapinar56, K. Ocalan57, M. Yalvac, M. Zeyrek Bogazici
University, Istanbul, Turkey
E. Gülmez, M. Kaya58, O. Kaya59, S. Tekten, E.A. Yetkin60 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, P. Sorokin 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. Newbold61, 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. Belyaev62, 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 Acosta63, T. Virdee14, 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, M. Squires, 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, 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, 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.
Wasserbaech64, 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, 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, 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. Bilki65, W. Clarida, K. Dilsiz66, S. Durgut, R.P. Gandrajula, M.
Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya67, A. Mestvirishvili,
A. Moeller, J. Nachtman, H. Ogul68, Y. Onel, F. Ozok69, 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, R. Stringer, 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. Musienko36, 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
A. Benaglia, 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. Bouhali70, A. Castaneda Hernandez70, A. Celik, M. Dalchenko, M. De Mattia,
A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, T. Kamon71, 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, P.
Sheldon, S. Tuo, J. Velkovska, Q. Xu University of Virginia, Charlottesville,
USA
M.W. Arenton, P. Barria, B. Cox, R. Hirosky, A. Ledovskoy, H. Li, C. Neu, T.
Sinthuprasith, X. Sun, 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: Also at Suez University, Suez, Egypt
9: Now at British University in Egypt, Cairo, Egypt
10: Now at Helwan 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 Tbilisi State University, Tbilisi, Georgia
14: Also at CERN, European Organization for Nuclear Research, Geneva,
Switzerland
15: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
16: Also at University of Hamburg, Hamburg, Germany
17: Also at Brandenburg University of Technology, Cottbus, Germany
18: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
19: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
20: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary
21: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India
22: Also at Institute of Physics, Bhubaneswar, India
23: Also at University of Visva-Bharati, Santiniketan, India
24: Also at University of Ruhuna, Matara, Sri Lanka
25: Also at Isfahan University of Technology, Isfahan, Iran
26: Also at Yazd University, Yazd, Iran
27: Also at Plasma Physics Research Center, Science and Research Branch,
Islamic Azad University, Tehran, Iran
28: Also at Università degli Studi di Siena, Siena, Italy
29: Also at INFN Sezione di Milano-Bicocca; Università di Milano-Bicocca,
Milano, Italy
30: Also at Purdue University, West Lafayette, USA
31: Also at INFN Sezione di Roma; Sapienza Università di Roma, Rome, Italy
32: Also at International Islamic University of Malaysia, Kuala Lumpur,
Malaysia
33: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia
34: Also at Consejo Nacional de Ciencia y Tecnología, Mexico city, Mexico
35: Also at Warsaw University of Technology, Institute of Electronic Systems,
Warsaw, Poland
36: Also at Institute for Nuclear Research, Moscow, Russia
37: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
38: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
39: Also at University of Florida, Gainesville, USA
40: Also at P.N. Lebedev Physical Institute, Moscow, Russia
41: Also at California Institute of Technology, Pasadena, USA
42: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
43: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
44: Also at University of Belgrade, Faculty of Physics and Vinca Institute of
Nuclear Sciences, Belgrade, Serbia
45: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy
46: Also at National and Kapodistrian University of Athens, Athens, Greece
47: Also at Riga Technical University, Riga, Latvia
48: Also at Universität Zürich, Zurich, Switzerland
49: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna,
Austria
50: Also at Istanbul University, Faculty of Science, Istanbul, Turkey
51: Also at Adiyaman University, Adiyaman, Turkey
52: Also at Istanbul Aydin University, Istanbul, Turkey
53: Also at Mersin University, Mersin, Turkey
54: Also at Cag University, Mersin, Turkey
55: Also at Piri Reis University, Istanbul, Turkey
56: Also at Izmir Institute of Technology, Izmir, Turkey
57: Also at Necmettin Erbakan University, Konya, Turkey
58: Also at Marmara University, Istanbul, Turkey
59: Also at Kafkas University, Kars, Turkey
60: Also at Istanbul Bilgi University, Istanbul, Turkey
61: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom
62: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
63: Also at Instituto de Astrofísica de Canarias, La Laguna, Spain
64: Also at Utah Valley University, Orem, USA
65: Also at Beykent University, Istanbul, Turkey
66: Also at Bingol University, Bingol, Turkey
67: Also at Erzincan University, Erzincan, Turkey
68: Also at Sinop University, Sinop, Turkey
69: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey
70: Also at Texas A&M University at Qatar, Doha, Qatar
71: Also at Kyungpook National University, Daegu, Korea