B2G-16-026

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$Id:B2G-16-026.tex4524522018-03-2321:36:33Zalverson$

B2G-16-026

# Search for a massive resonance decaying to a pair of Higgs bosons in the
four b quark final state in proton-proton collisions at $\sqrt{s}=13$

###### Abstract

A search for a massive resonance decaying into a pair of standard model Higgs
bosons, in a final state consisting of two b quark-antiquark pairs, is
performed. A data sample of proton-proton collisions at a centre-of-mass
energy of 13is used, collected by the CMS experiment at the CERN LHC in 2016,
and corresponding to an integrated luminosity of 35.9. The Higgs bosons are
highly Lorentz-boosted and are each reconstructed as a single large-area jet.
The signal is characterized by a peak in the dijet invariant mass
distribution, above a background from the standard model multijet production.
The observations are consistent with the background expectations, and are
interpreted as upper limits on the products of the $s$-channel production
cross sections and branching fractions of narrow bulk gravitons and radions in
warped extra-dimensional models. The limits range from 126 to 1.4fb at 95%
confidence level for resonances with masses between 750 and 3000, and are the
most stringent to date, over the explored mass range.

##  0.1 Introduction

In the standard model (SM), the pair production of Higgs bosons ($\PH$) [1, 2,
3] in proton-proton ($\Pp\Pp$) collisions at $\sqrt{s}=13\TeV$ is a rare
process [4]. However, the existence of massive resonances decaying to Higgs
boson pairs ($\PH\PH$) in many new physics models may enhance this rate to a
level observable at the CERN LHC using the current data. For instance, models
with warped extra dimensions (WED) [5] contain new particles such as the
spin-0 radion [6, 7, 8] and the spin-2 first Kaluza–Klein (KK) excitation of
the graviton [9, 10, 11], which have sizeable branching fractions to $\PH\PH$.

The WED models have an extra spatial dimension compactified between two
branes, with the region between (called the bulk) warped via an exponential
metric ${\kappa l}$, $\kappa$ being the warp factor and $l$ the coordinate of
the extra spatial dimension [12]. The reduced Planck scale
($\overline{\Mpl}\equiv\Mpl/8\pi$, being the Planck scale) is considered a
fundamental scale. The free parameters of the model are
$\kappa/\overline{\Mpl}$ and the ultraviolet cutoff of the theory
$\Lambda_{\text{R}}\equiv\sqrt{6}\re^{-\kappa l}\overline{\Mpl}$ [6]. In
$\Pp\Pp$ collisions at the LHC, the graviton and the radion are produced
primarily through gluon-gluon fusion and are predicted to decay to $\PH\PH$
[13].

Other scenarios, such as the two-Higgs doublet models [14] (in particular, the
minimal supersymmetric model [15]) and the Georgi-Machacek model [16] predict
spin-0 resonances that are produced primarily through gluon-gluon fusion, and
decay to an $\PH\PH$ pair. These particles have the same Lorentz structure and
effective couplings to the gluons and, for narrow widths, result in the same
kinematic distributions as those for the bulk radion. Hence, the results of
this paper are also applicable to this class of models.

Searches for a new particle $\cmsSymbolFace{X}$ in the $\PH\PH$ decay channel
have been performed by the ATLAS [17, 18, 19] and CMS [20, 21, 22, 23, 24]
Collaborations in $\Pp\Pp$ collisions at $\sqrt{s}=7$ and 8. More recently,
the ATLAS Collaboration has published limits on the production of a KK bulk
graviton, decaying to $\PH\PH$, in the $\bbbar\bbbar$ final state, using
$\Pp\Pp$ collision data at $\sqrt{s}=13\TeV$, corresponding to an integrated
luminosity of 3.2 [25]. Because the longitudinal components of the $\PW$ and
$\PZ$ bosons couple to the Higgs field in the SM, a resonance decaying to
$\PH\PH$ potentially also decays into $\PW\PW$ and $\PZ\PZ$, with a comparable
branching fraction for $\cmsSymbolFace{X}\to\PZ\PZ$, and with a branching
fraction for $\cmsSymbolFace{X}\to\PW\PW$ that is twice as large. Searches for
$\cmsSymbolFace{X}\to\PW\PW$ and $\PZ\PZ$ have been performed by ATLAS and CMS
[26, 27, 28, 29, 30, 31, 32, 33, 34, 35].

This letter reports on the search for a massive resonance decaying to an
$\PH\PH$ pair, in the $\bbbar\bbbar$ final state (with a branching fraction
$\approx$33% [36]), performed using a data set corresponding to 35.9of
$\Pp\Pp$ collisions at $\sqrt{s}=13\TeV$. The search significantly improves
upon the CMS analysis performed using the LHC data collected at
$\sqrt{s}=8\TeV$ [24], and extends the searched mass range to 750–3000. This
search is conducted for both the radion and the graviton, whereas the earlier
search only considered the former.

In this search, the $\cmsSymbolFace{X}\to\PH\PH$ decay would result in highly
Lorentz-boosted and collimated decay products of $\PH\to\bbbar$, which are
referred to as $\PH$ jets. These are reconstructed using jet substructure and
jet flavour-tagging techniques [37, 38, 39]. The background consists mostly of
SM multijet events, and is estimated using several control regions defined in
the phase space of the masses and flavour-tagging discriminators of the two
$\PH$ jets, and the $\PH\PH$ dijet invariant mass, allowing the background to
be predicted over the entire range of $m_{\cmsSymbolFace{X}}$ explored. The
signal would appear as a peak in the $\PH\PH$ dijet invariant mass spectrum
above a smooth background distribution.

##  0.2 The CMS detector and event simulations

The CMS detector with its coordinate system and the relevant kinematic
variables is described in Ref. [40]. The central feature of the CMS apparatus
is a superconducting solenoid of 6m internal diameter, providing a magnetic
field of 3.8T. Within the field volume are silicon pixel and strip trackers, a
lead tungstate crystal electromagnetic calorimeter (ECAL), and a brass and
scintillator hadron calorimeter (HCAL), each composed of a barrel and two
endcap sections. The tracker covers a pseudorapidity $\eta$ range from $-2.5$
to 2.5 with the ECAL and the HCAL extending up to $\abs{\eta}=3$. Forward
calorimeters in the region up to $\abs{\eta}=5$ provide almost hermetic
detector coverage. Muons are detected in gas-ionization chambers embedded in
the steel flux-return yoke outside the solenoid, covering a region of
$\abs{\eta}<2.4$.

Events of interest are selected using a two-tiered trigger system [41]. The
first level (L1), composed of custom hardware processors, uses information
from the calorimeters and muon detectors to select events at a rate of around
100kHz. The second level, known as the high-level trigger (HLT), consists of a
farm of processors running a version of the full event reconstruction software
optimized for fast processing, and reduces the event rate to around 1kHz
before data storage. Events are selected at the trigger level by the presence
of jets of particles in the detector. The L1 trigger algorithms reconstruct
jets from energy deposits in the calorimeters. At the HLT, physics objects
(charged and neutral hadrons, electrons, muons, and photons) are reconstructed
using a particle-flow (PF) algorithm [42]. The anti-algorithm [43, 44] is used
to cluster these objects with a distance parameter of 0.8 (AK8 jets) or 0.4
(AK4 jets).

Bulk graviton and radion signal events are simulated at leading order using
the 2.3.3 [45] event generator for masses in the range 750–3000and widths of
1(narrow width approximation). The NNPDF3.0 leading order parton distribution
functions (PDFs) [46], taken from the LHAPDF6 PDF set [47, 48, 49, 50], with
the four-flavour scheme, is used. The showering and hadronization of partons
is simulated with 8.212 [51]. The 2.7.1 [52] generator is used for an
alternative model to evaluate the systematic uncertainty associated with the
parton shower and hadronization. The tune CUETP8M1-NNPDF2.3LO [53] is used for
8, while the EE5C tune [54] is used for .

The background is modelled entirely from data. However, simulated background
samples are used to develop and validate the background estimation techniques,
prior to being applied to the data. These are multijet events, generated at
leading order using , and +jets, generated at next-to-leading order using 2.0
[55, 56, 57]. Both these backgrounds are interfaced to 8 for simulating the
parton shower and hadronization. Studies using simulations established that
the multijet component is more than 99% of the background, with the rest
mostly from +jets production.

All generated samples were processed through a -based [58, 59] simulation of
the CMS detector. Multiple $\Pp\Pp$ collisions may occur in the same or
adjacent LHC bunch crossings (pileup) and contribute to the overall event
activity in the detector. This effect is included in the simulations, and the
samples are reweighted to match the number of $\Pp\Pp$ interactions observed
in the data, assuming a total inelastic $\Pp\Pp$ collision cross section of
69.2mb [60].

##  0.3 Event selection

Events were collected using several HLT algorithms. The first required the
scalar $\pt$ sum of all AK4 jets in the event ($\HT$) to be greater than 800
or 900, depending on the LHC beam instantaneous luminosity. A second trigger
criterion required $\HT\geq 650\GeV$, with a pair of AK4 jets with invariant
mass above 900and a pseudorapidity separation $|\Delta\eta|<1.5$. A third set
of triggers selected events with the scalar $\pt$ sum of all AK8 jets greater
than 650 or 700and the presence of an AK8 jet with a “trimmed mass” above 50,
the jet mass after removing remnants of soft radiation using jet trimming
technique [61]. The fourth triggering condition was based on the presence of
an AK8 jet with $\pt>360\GeV$ and trimmed mass greater than 30. The last
trigger selection accepted events containing two AK8 jets having $\pt>280$ and
$200\GeV$ with at least one having trimmed mass greater than 30, together with
an AK4 jet passing a loose $\PQb$-tagging criterion.

The $\Pp\Pp$ interaction vertex with the highest $\sum\pt^{2}$ of the
associated clusters of physics objects is considered to be the one associated
with the hard scattering interaction, the primary vertex. The physics objects
are the jets, clustered using the jet finding algorithm [43, 44] with the
tracks assigned to the vertex as inputs, and the associated missing transverse
momentum, taken as the negative vector sum of the $\pt$ of those jets. The
other interaction vertices are designated as pileup vertices.

To mitigate the effect of pileup, particles are assigned weights using the
pileup per particle identification (PUPPI) algorithm [62], with the weight
corresponding to its estimated probability to originate from a pileup
interaction. Charged particles from pileup vertices receive a weight of zero
while those from the primary vertex receive a weight of one. Neutral particles
are assigned a weight between zero and one, with higher values for those
likely to originate from the primary vertex. Particles are then clustered into
AK8 jets. The vector sum of the weighted momenta of all particles clustered in
the jet is taken to be the jet momentum. To account for detector response
nonlinearity, jet energy corrections are applied as a function of jet $\eta$
and $\pt$ [63, 64]. In each event, the leading and the subleading $\pt$ AK8
jets, j1 and j2, respectively, are required to have $\pt>300\GeV$ and
$\abs{\eta}<2.4$.

The removal of events containing isolated leptons (electrons or muons) with
$\pt>20\GeV$ and $\abs{\eta}<2.4$ helps suppress +jets and diboson
backgrounds. The isolation variable is defined as the scalar $\pt$ sum of the
charged and neutral hadrons, and photons in a cone of $\Delta R=0.3$ for an
electron or $\Delta R=0.4$ for a muon, where $\Delta
R\equiv\sqrt{\smash[b]{(\Delta\eta)^{2}+(\Delta\phi)^{2}}}$, $\phi$ being the
azimuthal angle in radians. The energy from pileup deposited in the isolation
cone, and the $\pt$ of the lepton itself, is subtracted [65, 66]. The
isolation requirement removes jets misidentified as leptons. Additional
quality criteria are applied to improve the purity of the isolated lepton
samples. Electrons passing combined isolation and quality criteria
corresponding to a selection efficiency of 90% (70%) are designated “loose”
(“medium”) electrons. For the “loose” (“medium”) muons, the total associated
efficiency is 100% (95%). The probability of a jet to be misidentified as an
electron or a muon is in the range 0.5–2%, depending on $\pt$, $\eta$, and the
choice of medium or loose selection criteria. Events containing one medium
lepton, or two loose leptons of the same flavour, but of opposite charge, are
rejected.

The $\PH\to\bbbar$ system is reconstructed as a single high-$\pt$ AK8 jet,
where the decay products have merged within the jet, and the two highest $\pt$
jets in the event are assumed to be the Higgs boson candidates. The jet is
groomed [67] to remove soft and wide-angle radiation using the soft-drop
algorithm [68, 69], with the soft radiation fraction parameter $z$ set to
$0.1$ and the angular exponent parameter $\beta$ set to 0. The groomed jet is
used to compute the soft-drop jet mass, which peaks at the Higgs boson mass
for signal events and reduces the mass of background quark- and gluon-
initiated jets. Dedicated mass corrections [70], derived from simulation and
data in a region enriched with $\ttbar$ events with merged $\PW\to\qqbar$
decays, are applied to the jet mass in order to remove residual dependence on
the jet $\pt$, and to match the jet mass scale and resolution observed in
data.

Figure 1: The soft-drop mass (upper left), the N-subjettiness $\tau_{21}$
(upper right), and the double- tagger discriminator (lower) distributions of
the selected AK8 jets. The multijet background components for the different
jet flavours are shown: jets having two B hadrons ($\bbbar$) or a single one
($\cPqb$), jets having a charm hadron ($\cPqc$), and all other jets (light).
Also plotted are the distributions for the simulated bulk graviton and radion
signals of masses 1400 and 2500. The number of signal and background events
correspond to an integrated luminosity of 35.9. A signal cross section
$\sigma(\Pp\Pp\to X\to\PH\PH\to\bbbar\bbbar)=20\unit{pb}$ is assumed for all
the mass hypotheses. The events are required to have passed the trigger
selection, lepton rejection, the AK8 jet kinematic selections $\pt>300\GeV$
and $\abs{\eta}<2.4$, and $\abs{\Delta\eta(\text{j}_{1},\text{j}_{2})}<1.3$.
The reduced dijet invariant mass $m_{\text{jj,red}}$ is required to be greater
than 750. The N-subjettiness requirement of $\tau_{21}<0.55$ is applied to the
upper left and lower figures. The soft-drop masses of the two jets are between
105–135for the upper right and lower figures.

Figure 2: The jet separation $\abs{\Delta\eta(\text{j}_{1},\text{j}_{2})}$
(left) and the reduced dijet invariant mass $m_{\text{jj,red}}$ (right)
distributions. The multijet background components for the different jet
flavours are shown: events containing at least one jet with two B hadrons
($\bbbar$) or a single one ($\cPqb$), events containing a jet having a charm
hadron ($\cPqc$), and all other events (light). Also plotted are the
distributions for the simulated bulk graviton and radion signals of masses
1400 and 2500. The numbers of signal and background events correspond to an
integrated luminosity of 35.9. The signal cross section $\sigma(\Pp\Pp\to
X\to\PH\PH\to\bbbar\bbbar)$ is assumed to be 20pb for all the mass hypotheses.
The events are required to have passed the online selection, lepton rejection,
the AK8 jet kinematic selections $\pt>300\GeV$, $\abs{\eta}<2.4$. The soft-
drop masses of the two jets are between 105 and 135, and the N-subjettiness
requirement of $\tau_{21}<0.55$ and $m_{\text{jj,red}}>750\GeV$ are applied.
The $m_{\text{jj,red}}$ distributions (right) require
$\abs{\Delta\eta(\text{j}_{1},\text{j}_{2})}<1.3$.

The soft-drop masses of j1 and j2 are required to be within the range 105–135,
with an efficiency of about 60–70%, for jets arising from a signal of mass
$m_{\cmsSymbolFace{X}}$ in the range 750–3000. The “N-subjettiness” algorithm
is used to determine the consistency of the jet with two subjets from a two-
pronged $\PH\to\bbbar$ decay, by computing the inclusive jet shape variables
$\tau_{1}$ and $\tau_{2}$ [71]. The ratio $\tau_{21}\equiv\tau_{2}/\tau_{1}$
with a value much less than one indicates a jet with two subjets. The
selection $\tau_{21}<0.55$ is used, having a jet $\pt$-dependent efficiency of
50–70%, before applying the soft-drop mass requirement.

For background events, j1 and j2 are often well separated in $\eta$,
especially at high invariant mass ($m_{\text{jj}}$) of j1 and j2. In contrast,
signal events that contain a heavy resonance decaying to two energetic $\PH$
jets are characterized by a small separation of the two jets in $\eta$. Events
are therefore required to have a pseudorapidity separation
$\abs{\Delta\eta(\text{j}_{1},\text{j}_{2})}<1.3$.

The efficiency of the trigger combination is measured in a sample of multijet
events, collected with a control trigger requiring a single AK4 jet with
$\pt>260\GeV$, and with the leading and the subleading $\pt$ AK8 jets, j1 and
j2, respectively, passing the above selections on $\pt$, $\eta$, and the soft-
drop mass. The efficiency is greater than 99% for $m_{\text{jj}}\geq
1100\GeV$, and in the range 40–99% for $750<m_{\text{jj}}<1100\GeV$. The
trigger efficiency of the simulated samples is corrected using a scale factor
to match the observed efficiency in the data. This scale factor is applied as
a function of $\abs{\Delta\eta(\text{j}_{1},\text{j}_{2})}$ because it has a
mild dependence on this variable.

The main method to suppress the multijet background is $\PQb$ tagging: since a
true $\PH\to\bbbar$ jet contains two $\PQb$ hadrons, the $\PH$ jet candidates
are identified using the dedicated “double- tagger” algorithm [72]. The
double- tagger exploits the presence of two hadronized $\PQb$ quarks inside
the jet, and uses variables related to $\PQb$ hadron lifetime and mass to
distinguish between jets and the background from multijet production; it also
exploits the fact that the $\PQb$ hadron flight directions are strongly
correlated with the axes used to calculate the N-subjettiness observables. The
double- tagger is a multivariate discriminator with output between $-1$ and 1,
with a higher value indicating a greater probability for the jet to contain a
$\bbbar$ pair. The double- tagger discriminator thresholds of 0.3 and 0.8
correspond to $\PH$ jet tagging efficiencies of 80 and 30% and are referred to
as “loose” (L) and “tight” (T) requirements, respectively. Events must have
the two leading $\pt$ AK8 jets satisfying the loose double- tagger
requirement. The data-to-simulation scale factor for the double- tagger
efficiency is measured in an event sample enriched in $\bbbar$ pairs from
gluon splitting [72], and applied to the signals to obtain the correct signal
yields.

The main variable used in the search for a $\PH\PH$ resonance is the “reduced
dijet invariant mass” $m_{\text{jj,red}}\equiv
m_{\text{jj}}-(m_{\text{j}_{1}}-m_{\PH})-(m_{\text{j}_{2}}-m_{\PH})$, where
$m_{\text{j}_{1}}$ and $m_{\text{j}_{2}}$ are the soft-drop masses of the
leading and subleading $\PH$-tagged jets in the event, and
$m_{\PH}=125.09\GeV$ [73, 74] is the Higgs boson mass. The quantity
$m_{\text{jj,red}}$ is used rather than $m_{\text{jj}}$ since by subtracting
the soft-drop masses of the two $\PH$-tagged jets and adding back the exact
Higgs boson mass $m_{\PH}$, fluctuations in $m_{\text{j}_{1}}$ and
$m_{\text{j}_{2}}$ due to the jet mass resolution are corrected, leading to
8–10% improvement in the dijet mass resolution. A requirement of
$m_{\text{jj,red}}>750\GeV$ is applied for selecting signal-like events.

The soft-drop mass, $\tau_{21}$, and double- tagger discriminator
distributions of the two leading $\pt$ jets are shown in Fig. 1 for simulated
events after passing the online selection, lepton rejection, kinematic
selection, and the requirement $m_{\text{jj,red}}>750\GeV$. Also, the
N-subjettiness requirement of $\tau_{21}<0.55$ is applied for the soft-drop
mass and the double- tagger distributions, while the soft-drop mass
requirement is applied to the $\tau_{21}$, and double- tagger discriminator
distributions. Since some of the triggers impose a trimmed jet mass
requirement, this affects the shape of the offline soft-drop jet mass,
resulting in a steep rise above $\sim$20\. The distributions of the
$\abs{\Delta\eta(\text{j}_{1},\text{j}_{2})}$ and the $m_{\text{jj,red}}$
variables are shown in Fig. 2. In these figures, the multijet background is
shown for different jet flavour categories: jets having two B hadrons
($\bbbar$) or a single one ($\cPqb$), jets having a charm hadron ($\cPqc$),
and all other jets (light).

The double- tagger discriminator of the two leading AK8 jets must exceed the
loose threshold. In addition, if both discriminator values also exceed the
tight threshold, events are classified in the “TT” category. Otherwise, they
are classified in the “LL” category, which contains events with both j1 and j2
failing the tight threshold as well as events with either j1 or j2 passing the
tight threshold while the other passes the loose threshold only.

Figure 3: The signal selection efficiencies for the bulk graviton and radion
models for different mass hypotheses of the resonances, shown for the LL and
the TT signal event categories. Owing to the large sample sizes of the
simulated events, the statistical uncertainties are small.

The backgrounds are estimated separately for each category, and the
combination of the likelihoods for the TT and LL categories gives the optimal
signal sensitivity over a wide range of resonance masses, according to studies
performed using simulated signal and multijet samples. The TT category has a
good background rejection for $m_{\cmsSymbolFace{X}}$ up to 2000. At higher
resonance masses, where the background is small, the LL category provides
better signal sensitivity. The full event selection efficiencies for bulk
gravitons and radions of different assumed masses are shown in Fig. 3. The
radion has a smaller efficiency than the bulk graviton because its
$\abs{\Delta\eta(\text{j}_{1},\text{j}_{2})}$ distribution is considerably
wider than that of a bulk graviton of the same mass, as shown in Fig. 2
(left).

##  0.4 Signal and background modelling

The method chosen for the background modelling depends on whether the
resonance mass $m_{\cmsSymbolFace{X}}$ is below or above 1200, since at low
masses the background does not fall smoothly as a function of
$m_{\text{jj,red}}$, because of the trigger requirements, while above 1200it
does. The background estimation relies on a set of control regions to predict
the total background shape and normalization in the signal regions. The entire
range of the $m_{\text{jj,red}}$ distribution above 750is used for the
prediction.

Figure 4: The bulk graviton signal $m_{\text{jj,red}}$ distribution for the LL
category, modelled using the sum of Gaussian and Crystal Ball functions. This
modelling is performed for signals in the range
$1100<m_{\text{jj,red}}<3000\GeV$, where the background distribution falls
smoothly. No events are observed with $m_{\text{jj,red}}$ greater than 3000.

For signals with $m_{\cmsSymbolFace{X}}\geq 1200\GeV$, the underlying
background distribution falls monotonically with $m_{\text{jj,red}}$, thus
allowing the background shape to be modelled by a smooth function, above which
a localized signal is searched for. This smooth background modelling helps to
reduce uncertainties in the background estimation from local statistical
fluctuations in $m_{\text{jj,red}}$, thereby improving the signal search
sensitivity. The parameters of the function and its total normalization are
constrained by a simultaneous fit of the signal and background models to the
data in the control and the signal regions. For $m_{\cmsSymbolFace{X}}\geq
1200\GeV$, the $m_{\text{jj,red}}$ distributions for the signal are modelled
using the sum of a Gaussian and a Crystal Ball function [75], as shown in Fig.
4 for one signal category. The same modelling is used for the other signal
categories, with different parameters for the Gaussian and the Crystal Ball
functions.

Definition of the signal, the antitag, and the sideband regions used for the
background estimation. The regions are defined in terms of the soft-drop
masses of the leading $\pt$ (j1) and the subleading $\pt$ (j2) AK8 jets, and
their double- tagger discriminator values.  Event Jet Soft-drop Double- tagger
category mass () discriminator Signal (LL) j1 105–135 $>$0.3, but j2 not both
$>$0.8 Signal (TT) j1 $>$0.8 j2 Antitag (LL) j1 105–135 $<$0.3 j2 0.3–0.8
Antitag (TT) j1 $<$0.3 j2 $>$0.8 Sideband j1 $<$105 or $>$135 $>$0.3, but (LL,
passing) j2 105–135 not both $>$0.8 Sideband j1 $<$105 or $>$135 $>$0.8 (TT,
passing) j2 105–135 Sideband j1 $<$105 or $>$135 $<$0.3 (LL, failing) j2
105–135 0.3–0.8 Sideband j1 $<$105 or $>$135 $<$0.3 (TT, failing) j2 105–135
$>$0.8

Figure 5: The pass-fail ratio $R_{\text{p/f}}$ of the leading $\pt$ jet for
the LL (left) and TT (right) signal region categories as a function of the
difference between the soft-drop mass of the leading jet and the Higgs boson
mass, $m_{\text{j}_{1}}$\- $m_{\PH}$. The measured ratio in different bins of
$m_{\text{j}_{1}}-m_{\PH}$ is used in the fit (red solid line), except in the
region around $m_{\text{j}_{1}}-m_{\PH}=0$, which corresponds to the signal
region (blue triangular markers). The fitted function is interpolated to
obtain $R_{\text{p/f}}$ in the signal region. The horizontal bars on the data
points indicate the bin widths.

Figure 6: The reduced mass distributions $m_{\text{jj,red}}$ for the LL (left)
and TT (right) signal region categories. The points with bars show the data,
the histogram with shaded band shows the estimated background and associated
uncertainty. The $m_{\text{jj,red}}$ spectrum for the background is obtained
by weighting the $m_{\text{jj,red}}$ spectrum in the antitag region by the
ratio $R_{\text{p/f}}$ of Fig. 5. The signal predictions for a bulk graviton
of mass 1000, are overlaid for comparison, assuming a cross section
$\sigma(\Pp\Pp\to X\to\PH\PH\to\bbbar\bbbar)$ of 10fb. The last bins of the
distributions contain all events with $m_{\text{jj,red}}>3000\GeV$. The
differences between the data and the predicted background, divided by the data
statistical uncertainty (data unc.) as given by the Garwood interval [76], are
shown in the lower panels.

Figure 7: The reduced mass $m_{\text{jj,red}}$ distributions in the antitag
region for the LL (left) and TT (right) categories. The black markers are the
data while the curves show the pre-fit and post-fit background shapes. The
differences between the data and the pre-fit background distribution, divided
by the statistical uncertainty in the data (data unc.) as given by the Garwood
interval [76], are shown in the lower panels.

Figure 8: The reduced mass $m_{\text{jj,red}}$ distributions in the signal
region for the LL (left) and the TT (right) categories. The black markers are
the data while the curves show the pre-fit and post-fit background shapes. The
contribution of bulk gravitons of masses 1600 and 2500in the signal region are
shown assuming a cross section $\sigma(\Pp\Pp\to X\to\PH\PH\to\bbbar\bbbar)$
of 10fb. The differences between the data and the pre-fit background
distribution, divided by the statistical uncertainty in the data (data unc.)
as given by the Garwood interval [76], are shown in the lower panels.

The signal and control regions are defined by two variables related to the
leading $\pt$ jet j1: (i) its soft-drop mass $m_{\text{j}_{1}}$ and (ii) the
value of the discriminator of the double- tagger. The background is estimated
in bins of the $m_{\text{jj,red}}$ distribution. Considering these two
variables, several regions are defined.

The pre-tag region includes events fulfilling the selection requirements in
Sections 0.2–0.3 apart from those on $m_{\text{j}_{1}}$ and on the j1 double-
tagger discriminator. The signal region is the subset of pre-tag events where
$m_{\text{j}_{1}}$ is inside the $\PH$ jet mass window of 105–135, and with
the j1 double- tagger discriminator greater than 0.3 or 0.8, for the LL and TT
regions, respectively. The antitag regions require the j1 double- tagger
discriminator to be less than 0.3, with the requirement on j2 being the same
as that for the corresponding LL or TT signal regions. The $m_{\text{j}_{1}}$
sideband region consists of events in the pre-tag region, where
$m_{\text{j}_{1}}$ lies outside the $\PH$ jet mass window. Based on whether j1
passes or fails the double- tagger discriminator threshold, the sideband
region is divided into either “passing” or “failing”, respectively. The
antitag regions are dominated by the multijet background, and have identical
kinematic distributions to the multijet background events in the signal
region, according to studies using simulations. The definitions of the signal,
the antitag, and the sideband regions are given in Table 0.4.

In the absence of a correlation between $m_{\text{j}_{1}}$ and the double-
tagger discriminator values, one could measure in the $m_{\text{j}_{1}}$
sideband the ratio of the number of events passing and failing the double-
tagger selection, $R_{\text{p/f}}\equiv N_{\text{pass}}/N_{\text{fail}}$, the
“pass-fail ratio”. The yield in the antitag region (in each
$m_{\text{jj,red}}$ bin) could then be scaled by $R_{\text{p/f}}$ to obtain an
estimate of the background normalization in the signal region. However, there
is a small correlation between the double- tagger discriminator and
$m_{\text{j}_{1}}$, which is taken into account by measuring the pass-fail
ratio $R_{\text{p/f}}$ as a function of $m_{\text{j}_{1}}$. The signal
fraction was found to be less than $10^{-3}$ in the sideband regions used to
evaluate $R_{\text{p/f}}$, assuming a signal cross section $\sigma(\Pp\Pp\to
X\to\PH\PH\to\bbbar\bbbar)$ of $10\unit{fb}$.

The $R_{\text{p/f}}$ for the LL signal region is measured using ratio of the
number of events in the “LL, passing” and “LL, failing” sideband regions, as
defined in Table 0.4. Likewise, the $R_{\text{p/f}}$ for the TT signal region
uses the ratio of the number of events in the “TT, passing” to the “TT,
failing” sideband regions. The variation of $R_{\text{p/f}}$ as a function of
$m_{\text{j}_{1}}$ in each $m_{\text{j}_{1}}$ sideband is fitted with a
quadratic function. The fit to the pass-fail ratio is interpolated to the
region where $m_{\text{j}_{1}}$ lies within the $\PH$ jet mass window of
105–135. An alternative fit using a third order polynomial was found to give
the same interpolated value of $R_{\text{p/f}}$ in the Higgs jet mass window.
Every event in the antitag region is scaled by the pass-fail ratio evaluated
for the $m_{\text{j}_{1}}$ of that event, to obtain the background prediction
in the signal region.

Figure 5 shows the quadratic fit in the $m_{\text{j}_{1}}$ sidebands of the
pass-fail ratio $R_{\text{p/f}}$ as a function of $m_{\text{j}_{1}}$, as
obtained in the data. The background prediction using this method, along with
the number of observed events in the signal region is shown in Fig. 6.

For resonance masses of 1200and above, the background estimation is improved
by simultaneously fitting a parametric model for the background and signal to
the data in the signal and the antitag regions for $m_{\text{jj,red}}\geq
1100\GeV$. In the fit, the ratio $R_{\text{p/f}}$ obtained from the sidebands
is used to constrain the relative number of background events in the two
regions. To account for possible $R_{\text{p/f}}$ dependence on
$m_{\text{jj,red}}$ at high $m_{\text{jj,red}}$ values, the $R_{\text{p/f}}$
obtained from the fits shown in Fig. 5 is also parametrized as a linear
function of $m_{\text{jj,red}}$. The signal normalization is unconstrained in
the fit, while the uncertainties in the parameters of the functions used to
model the background and $R_{\text{p/f}}$ are treated as nuisance parameters.
For the background modelling, a choice among an exponential function
$N\re^{-a\,m_{\text{jj,red}}}$, a “levelled exponential” function
$N\re^{-a\,m_{\text{jj,red}}/(1+a\,b\,m_{\text{jj,red}})}$, and a “quadratic
levelled exponential function”
$N\re^{[{-a\,m_{\text{jj,red}}}/(1+a\,b\,m_{\text{jj,red}})]-[{-c\,m_{\text{jj,red}}^{2}}/(1+b\,c\,m_{\text{jj,red}}^{2})]}$
was made, using a Fisher F-test [77]. At a confidence level of 95%, the
levelled exponential function was found to be optimal. Since the background
shapes in the signal regions, as predicted using the antitag regions, were
found to be similar (Fig. 6), the parametric background modelling was tested
using the antitag region in the data before applying it to the signal region.

The simultaneous fits to the antitag and the signal regions are shown in Figs.
7 and 8, respectively, using the background model only. These are labelled as
“post-fit” curves with the signal region background yields constrained to be
$R_{\text{p/f}}$ times the background yields from the antitag regions. The
“pre-fit” curves, obtained by fitting the antitag and the signal regions
separately to the background-only model, with the background event yields
unconstrained, are also shown for comparison. In the post-fit results, the
$R_{\text{p/f}}$ dependence on $m_{\text{jj,red}}$ was found to be negligible.

Among the four fitted regions, corresponding to the antitag and the signal
regions in the LL and TT categories, the events with the highest value of
$m_{\text{jj,red}}$ occur in the antitag region of the LL category, at around
$m_{\text{jj,red}}=2850\GeV$. As the parametric background model is only
reliable within the range of observed events, the likelihood is only evaluated
up to $m_{\text{jj,red}}=3000\GeV$. This results in a truncation of the signal
distribution for resonances having $m_{\cmsSymbolFace{X}}$ of 2800and above,
with signal efficiency losses increasing to 30% for
$m_{\cmsSymbolFace{X}}=3000\GeV$, as shown in Fig. 4.

Closure tests of the background estimation methods were performed using
simulated multijet samples with signals of various cross sections. The tests
indicated a good consistency between the expected and the assumed signal
strengths.

##  0.5 Systematic uncertainties

The following sources of systematic uncertainty affect the expected signal
yields. None of these lead to a significant change in the signal shape.

Trigger response modelling uncertainties are particularly important for
$m_{\text{jj,red}}<1200\GeV$, where the trigger efficiency drops below 99%. A
scale factor is applied to correct for the difference in efficiency observed
between the data and simulation. The control trigger used to measure this
scale factor requires a single AK4 jet with $\pt>260\GeV$, and it too is
subject to some inefficiency when $m_{\text{jj,red}}$ is close to 750, because
of a difference between the jet energy scale used in the trigger and that used
in the offline reconstruction. This inefficiency is measured using
simulations, and has an associated total uncertainty of between 1% and 15%.

Summary of systematic uncertainties in the signal and background yields.
Source Uncertainty (%) Signal yield Trigger efficiency 1–15 $\PH$ jet energy
scale and resolution 1 $\PH$ jet mass scale and resolution 2 $\PH$ jet
$\tau_{21}$ selection $+$30 /$-$26 $\PH$-tagging correction factor 7–20
Double- tagger discriminator 2–5 Pileup modelling 2 PDF and scales 0.1-2
Luminosity 2.5 Background yield $R_{\text{p/f}}$ fit 2.6 (LL category) 6.8 (TT
category)

The jet energy scale and resolution uncertainty is about 1% [63, 64]. The jet
mass scale and resolution, and $\tau_{21}$ selection efficiency data-to-
simulation scale factor are measured using a sample of merged $\PW$ jets in
semileptonic $\ttbar$ events. The corresponding uncertainties are extrapolated
to a higher $\pt$ range than that associated with $\ttbar$ events, using
simulations. A correction factor is applied to account for the difference in
the jet shower profile of $\PW\to{\qqbar^{\prime}}$ and $\PH\to\bbbar$ decays,
by comparing the ratio of the efficiency of $\PH$ and $\PW$ jets using the 8
and shower generators. The jet mass scale and resolution has a 2% effect on
the signal yields because of a change in the mean of the $\PH$ jet mass
distribution. The $\tau_{21}$ selection efficiency uncertainty amounts to a
${+}30{/}{-}26\%$ change in the signal yields. The uncertainty in the $\PH$
tagging correction factor is in the range 7–20% depending on the resonance
mass $m_{\cmsSymbolFace{X}}$. The double- tagger efficiency scale factor
uncertainty is about 2–5%, depending on the double- tagger requirement
threshold and jet , and is propagated to the total uncertainty in the signal
yield.

The impact of the PDFs and the theoretical scale uncertainties are estimated
to be 0.1–2%, using the PDF4LHC procedure [50], and affect the product of the
signal acceptance and the efficiency. The PDF and scale uncertainties have
negligible impact on the signal $m_{\text{jj,red}}$ distributions. Additional
systematic uncertainties associated with the pileup modelling (2%) and the
integrated luminosity determination (2.5%) [78], are applied to the signal
yield.

The main source of uncertainty for the multijet background in the region
$m_{\text{jj,red}}<1200\GeV$ is due to the statistical uncertainty in the fit
to the $R_{\text{p/f}}$ ratio performed in the $\PH$ jet mass sidebands. This
uncertainty, amounting to 2.6% for the LL, and 6.8% for the TT signal
categories, is fully correlated between all bins of a particular estimate.
Furthermore, the statistical uncertainty in the antitag region is propagated
to the signal region when the estimate is made. This is uncorrelated from bin
to bin, and the Barlow–Beeston Lite [79, 80] method is used to treat the bin-
by-bin statistical uncertainty in the data. These uncertainties affect both
the shape of the background in the $m_{\text{jj,red}}$ distribution and the
total background yield.

For $m_{\text{jj,red}}\geq 1200\GeV$, the overall background uncertainty is
obtained from the uncertainty in the four simultaneous fits performed for the
antitag and the signal regions in the LL and the TT categories. The dependence
of $R_{\text{p/f}}$ on $m_{\text{jj,red}}$ is accounted for, although this was
found to be negligible.

A complete list of systematic uncertainties is given in Table 0.5.

##  0.6 Results

Figure 9: The limits for the spin-0 radion (left) and the spin-2 bulk graviton
(right) models. The result for $m_{\cmsSymbolFace{X}}<1200\GeV$ uses the
background predicted using the control regions, while for
$m_{\cmsSymbolFace{X}}\geq 1200\GeV$ the background is derived from a combined
signal and background fit to the data in the control and the signal regions.
The predicted theoretical cross sections for a narrow radion or a bulk
graviton are also shown.

As shown in Figs. 6 and 8, for the signal regions, the observed
$m_{\text{jj,red}}$ distribution is consistent with the estimated background.
The results are interpreted in terms of upper limits on the product of the
production cross sections and the branching fractions
$\sigma(\Pp\Pp\to\cmsSymbolFace{X})\mathcal{B}(\cmsSymbolFace{X}\to\PH\PH\to\bbbar\bbbar)$
for radion and bulk graviton of various mass hypotheses. The asymptotic
approximation of the modified frequentist approach for confidence levels,
taking the profile likelihood as a test statistic [81, 82, 83], is used. The
limits are shown in Fig. 9 for a narrow width radion or a bulk graviton. These
are compared with the theoretical values of the product of the cross sections
and branching fractions for the benchmarks $\kappa/\overline{\Mpl}=0.5$ and
$\Lambda_{\text{R}}=3\TeV$, where the narrow width approximation for a signal
is valid, and where the corresponding $\PH\PH$ decay branching fractions in
the mass range of interest are 10 and 23%, for the graviton and the radion,
respectively [13]. The expected limits on the bulk graviton are more stringent
than those on the radion because of the higher efficiency of the
$\abs{\Delta\eta(\text{j}_{1},\text{j}_{2})}$ separation requirement for the
former signal.

The upper limits on the production of the cross sections and branching
fraction lies in the range 126–1.4fb for a narrow resonance
$\cmsSymbolFace{X}$ of mass $750<m_{\cmsSymbolFace{X}}<3000\GeV$. Assuming
$\Lambda_{\text{R}}=3\TeV$, a bulk radion with a mass between 970 and 1400is
excluded at 95% confidence level, except in a small region close to 1200,
where the observed limit is 11.4pb, the theoretical prediction being 11.2pb.

##  0.7 Summary

A search for a narrow massive resonance decaying to two standard model Higgs
bosons is performed using the LHC proton-proton collision data collected at a
centre-of-mass energy of 13by the CMS detector, and corresponding to an
integrated luminosity of 35.9. The final state consists of events with both
Higgs bosons decaying to $\PQb$ quark-antiquark pairs, which were identified
using jet substructure and $\PQb$-tagging techniques applied to large-area
jets. The data are found to be consistent with the standard model
expectations, dominated by multijet events. Upper limits are set on the
products of the resonant production cross sections of a Kaluza–Klein bulk
graviton and a Randall–Sundrum radion, and their branching fraction to
$\PH\PH\to\bbbar\bbbar$. The limits range from 126 to 1.4fb at 95% confidence
level for bulk gravitons and radions in the mass range 750–3000. For the mass
scale $\Lambda_{\text{R}}=3\TeV$, a radion of mass between 970 and 1400(except
in a small region close to 1200) is excluded. These limits on the bulk
graviton and the radion decaying to a pair of standard model Higgs bosons are
the most stringent to date, over the mass range explored.

###### 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 Severo Ochoa del Principado de Asturias;
the Thalis and Aristeia programmes cofinanced by EU-ESF and the Greek NSRF;
the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn
University and the Chulalongkorn Academic into Its 2nd Century Project
Advancement Project (Thailand); the Welch Foundation, contract C-1845; and the
Weston Havens Foundation (USA).

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##  .8 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, 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
D. Beghin, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, B. Dorney, G.
Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk, G. Karapostoli, T. Lenzi,
J. Luetic, T. Maerschalk, A. Marinov, A. Randle-conde, T. Seva, E. Starling,
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. Khvastunov3, 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, P.
David, S. De Visscher, C. Delaere, M. Delcourt, B. Francois, A. Giammanco, M.
Komm, G. Krintiras, V. Lemaitre, A. Magitteri, A. Mertens, M. Musich, K.
Piotrzkowski, L. Quertenmont, A. Saggio, M. Vidal Marono, S. Wertz, J. Zobec
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. Chinellato4, E. Coelho, E.M.
Da Costa, G.G. Da Silveira5, 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, L.J. Sanchez Rosas, A. Santoro, A. Sznajder, M. Thiel, E.J.
Tonelli Manganote4, F. Torres Da Silva De Araujo, A. Vilela Pereira
Universidade Estadual Paulista a, Universidade Federal do ABC b, São Paulo,
Brazil
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,
G. Sultanov University of Sofia, Sofia, Bulgaria
A. Dimitrov, I. Glushkov, L. Litov, B. Pavlov, P. Petkov Beihang University,
Beijing, China
W. Fang6, X. Gao6, L. Yuan Institute of High Energy Physics, Beijing, China
M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D.
Leggat, H. Liao, Z. Liu, F. Romeo, S.M. 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. Starodumov7, 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. Finger8, M. Finger Jr.8 Universidad San Francisco de Quito, Quito, Ecuador
E. Carrera Jarrin Academy of Scientific Research and Technology of the Arab
Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt
A.A. Abdelalim9,10, Y. Mohammed11, E. Salama12,13 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, H. Kirschenmann, J. Pekkanen, M. Voutilainen Helsinki Institute of
Physics, Helsinki, Finland
J. Havukainen, J.K. Heikkilä, T. Järvinen, V. Karimäki, R. Kinnunen, T.
Lampén, K. Lassila-Perini, S. Laurila, S. Lehti, T. Lindén, P. Luukka, H.
Siikonen, E. Tuominen, J. Tuominiemi 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, C. Leloup, 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, C. Amendola, 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. Agram14, J. Andrea, D. Bloch, J.-M. Brom, M. Buttignol, E.C. Chabert, N.
Chanon, C. Collard, E. Conte14, X. Coubez, J.-C. Fontaine14, 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. Popov15, V. Sordini, M. Vander Donckt, S. Viret Georgian Technical
University, Tbilisi, Georgia
T. Toriashvili16 Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze8 RWTH Aachen University, I. Physikalisches Institut, Aachen,
Germany
C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, C.
Schomakers, J. Schulz, V. Zhukov15 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, T. Müller, A. Nehrkorn, A.
Nowack, C. Pistone, O. Pooth, A. Stahl17 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. Borras18, V. Botta, A.
Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G.
Eckerlin, D. Eckstein, T. Eichhorn, E. Eren, E. Gallo19, J. Garay Garcia, A.
Geiser, A. Gizhko, J.M. Grados Luyando, A. Grohsjean, P. Gunnellini, M.
Guthoff, A. Harb, J. Hauk, M. Hempel20, 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. Lohmann20, 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
R. Aggleton, 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. Pantaleo17, 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, M. Baselga, S. Baur, E. Butz, R. Caspart, T. Chwalek, F.
Colombo, W. De Boer, A. Dierlamm, N. Faltermann, B. Freund, R. Friese, M.
Giffels, D. Haitz, M.A. Harrendorf, F. Hartmann17, S.M. Heindl, U. Husemann,
F. Kassel17, 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, O. Surányi, G.I. Veres21 Wigner Research
Centre for Physics, Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath22, Á. Hunyadi, F. Sikler, V. Veszpremi
Institute of Nuclear Research ATOMKI, Debrecen, Hungary
N. Beni, S. Czellar, J. Karancsi23, A. Makovec, J. Molnar, Z. Szillasi
Institute of Physics, University of Debrecen, Debrecen, Hungary
M. Bartók21, 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. Bahinipati24, S. Bhowmik, P. Mal, K. Mandal, A. Nayak25, D.K. Sahoo24, 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, S. 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. Mohanty17, 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. Maity26, G. Majumder, K. Mazumdar, T. Sarkar26, N. Wickramage27
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. Chenarani28, E. Eskandari Tadavani, S.M. Etesami28, M. Khakzad, M.
Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi29, F. Rezaei
Hosseinabadi, B. Safarzadeh30, 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,17, R. Vendittia, P. Verwilligena INFN Sezione di
Bologna a, Università di Bologna b, Bologna, Italy
G. Abbiendia, C. Battilanaa,b, D. Bonacorsia,b, L. Borgonovia,b, S. Braibant-
Giacomellia,b, R. Campaninia,b, P. Capiluppia,b, A. Castroa,b, F.R. Cavalloa,
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,31, G. Sguazzonia, D. Stroma, L. Viliania,b,17 INFN Laboratori
Nazionali di Frascati, Frascati, Italy
L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera17 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, A. Beschi, 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,32, 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,17, F. Fabozzia,c, F. Fiengaa,b,
A.O.M. Iorioa,b, W.A. Khana, L. Listaa, S. Meolaa,d,17, P. Paoluccia,17, 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, P. De Castro
Manzanoa, T. Dorigoa, U. Dossellia, F. Gasparinia,b, U. Gasparinia,b, A.
Gozzelinoa, S. Lacapraraa, M. Margonia,b, A.T. Meneguzzoa,b, N. Pozzobona,b,
P. Ronchesea,b, R. Rossina,b, F. Simonettoa,b, E. Torassaa, 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,17, 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,31, 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,33, 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,17, 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 Ali34, F. Mohamad Idris35, 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 Cruz36, 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. Byszuk37, 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. Matveev38,39, 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. Kim40, E. Kuznetsova41, 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. Bylinkin39 National Research Nuclear University ’Moscow
Engineering Physics Institute’ (MEPhI), Moscow, Russia
R. Chistov42, M. Danilov42, P. Parygin, D. Philippov, S. Polikarpov, E.
Tarkovskii P.N. Lebedev Physical Institute, Moscow, Russia
V. Andreev, M. Azarkin39, I. Dremin39, M. Kirakosyan39, A. Terkulov Skobeltsyn
Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow,
Russia
A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin43, L. Dudko, A.
Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, M.
Perfilov, S. Petrushanko, V. Savrin Novosibirsk State University (NSU),
Novosibirsk, Russia
V. Blinov44, Y.Skovpen44, D. Shtol44 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, P. Mandrik, 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. Adzic45, 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, 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, B. Akgun, E. Auffray, P. Baillon, A.H. Ball, D. Barney, J.
Bendavid, 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, N. Deelen, M. Dobson, T. du
Pree, M. Dünser, N. Dupont, A. Elliott-Peisert, P. Everaerts, F. Fallavollita,
G. Franzoni, J. Fulcher, W. Funk, D. Gigi, A. Gilbert, K. Gill, F. Glege, D.
Gulhan, P. Harris, J. Hegeman, V. Innocente, A. Jafari, P. Janot, O.
Karacheban20, J. Kieseler, V. Knünz, A. Kornmayer, 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.
Milenovic46, 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, D. Rabady, A. Racz, T. Reis, G.
Rolandi47, M. Rovere, H. Sakulin, C. Schäfer, C. Schwick, M. Seidel, M.
Selvaggi, A. Sharma, P. Silva, P. Sphicas48, A. Stakia, J. Steggemann, M.
Stoye, M. Tosi, D. Treille, A. Triossi, A. Tsirou, V. Veckalns49, M. Verweij,
W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland
W. Bertl${}^{\textrm{\textdagger}}$, L. Caminada50, K. Deiters, W. Erdmann, R.
Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe,
S.A. Wiederkehr ETH Zurich - Institute for Particle Physics and Astrophysics
(IPA), Zurich, Switzerland
M. Backhaus, L. Bäni, P. Berger, L. Bianchini, B. Casal, G. Dissertori, M.
Dittmar, M. Donegà, C. Dorfer, 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, D.A.
Sanz Becerra, M. Schönenberger, L. Shchutska, V.R. Tavolaro, K. Theofilatos,
M.L. Vesterbacka Olsson, R. Wallny, D.H. Zhu Universität Zürich, Zurich,
Switzerland
T.K. Aarrestad, C. Amsler51, 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, K. Schweiger, C. Seitz, Y. Takahashi, A. Zucchetta National
Central University, Chung-Li, Taiwan
V. Candelise, C.W. Chen, G.I. De Leon, 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
F. Boran, S. Cerci52, S. Damarseckin, Z.S. Demiroglu, C. Dozen, I. Dumanoglu,
S. Girgis, G. Gokbulut, Y. Guler, I. Hos53, E.E. Kangal54, O. Kara, A. Kayis
Topaksu, U. Kiminsu, M. Oglakci, G. Onengut55, K. Ozdemir56, D. Sunar Cerci52,
B. Tali52, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical
University, Physics Department, Ankara, Turkey
B. Bilin, G. Karapinar57, K. Ocalan58, M. Yalvac, M. Zeyrek Bogazici
University, Istanbul, Turkey
E. Gülmez, M. Kaya59, O. Kaya60, S. Tekten, E.A. Yetkin61 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
F. Ball, L. Beck, J.J. Brooke, D. Burns, E. Clement, D. Cussans, O. Davignon,
H. Flacher, J. Goldstein, G.P. Heath, H.F. Heath, J. Jacob, L. Kreczko, D.M.
Newbold62, S. Paramesvaran, T. Sakuma, S. Seif El Nasr-storey, D. Smith, V.J.
Smith Rutherford Appleton Laboratory, Didcot, United Kingdom
K.W. Bell, A. Belyaev63, 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, J. Borg, 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. Nikitenko7, 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 Acosta64, T. Virdee17, 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, S. Zahid 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, M. Hadley, J. Hakala, U. Heintz, J.M.
Hogan, K.H.M. Kwok, E. Laird, G. Landsberg, J. Lee, 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, E. Kennedy, F. Lacroix, O.R. Long, M. Olmedo Negrete,
M.I. Paneva, W. Si, L. Wang, H. Wei, S. Wimpenny, B. R. Yates University of
California, San Diego, La Jolla, USA
J.G. Branson, S. Cittolin, M. Derdzinski, R. Gerosa, D. Gilbert, 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. Wasserbaech65, 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, 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, D. Quach, A. Rinkevicius, A. Ryd, L. Skinnari, L. Soffi, S.M. Tan,
Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek Fermi National Accelerator
Laboratory, Batavia, USA
S. Abdullin, M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, A. Apyan, S.
Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, 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, 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, S.V. Gleyzer, B.M. Joshi, J.
Konigsberg, A. Korytov, K. Kotov, P. Ma, K. Matchev, H. Mei, G. Mitselmakher,
D. Rank, K. Shi, 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. Bilki66, W. Clarida, K. Dilsiz67, S. Durgut, R.P. Gandrajula, M.
Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya68, A. Mestvirishvili,
A. Moeller, J. Nachtman, H. Ogul69, Y. Onel, F. Ozok70, 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, Y. Feng, 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, M. Hu, 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, J. Hiltbrand, S.
Kalafut, Y. Kubota, Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack,
J. Turkewitz, M.A. Wadud University of Mississippi, Oxford, USA
J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA
E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, 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
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, 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. Musienko38, 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, H. Qiu, 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, Z. Chen, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Guilbaud, M.
Kilpatrick, W. Li, B. Michlin, M. Northup, B.P. Padley, J. Roberts, J. Rorie,
W. Shi, Z. Tu, J. Zabel, A. Zhang 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. Bouhali71, A. Castaneda Hernandez71, A. Celik, M. Dalchenko, M. De Mattia,
A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, T. Kamon72, 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. Mengke, S. Muthumuni, T.
Peltola, S. Undleeb, I. Volobouev, Z. Wang Vanderbilt University, Nashville,
USA
S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K.
Padeken, 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, N. Poudyal, J. Sturdy, P. Thapa, 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. 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 IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
4: Also at Universidade Estadual de Campinas, Campinas, Brazil
5: Also at Universidade Federal de Pelotas, Pelotas, Brazil
6: Also at Université Libre de Bruxelles, Bruxelles, Belgium
7: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia
8: Also at Joint Institute for Nuclear Research, Dubna, Russia
9: Also at Helwan University, Cairo, Egypt
10: Now at Zewail City of Science and Technology, Zewail, Egypt
11: Now at Fayoum University, El-Fayoum, Egypt
12: Also at British University in Egypt, Cairo, Egypt
13: Now at Ain Shams University, Cairo, Egypt
14: Also at Université de Haute Alsace, Mulhouse, France
15: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State
University, Moscow, Russia
16: Also at Tbilisi State University, Tbilisi, Georgia
17: Also at CERN, European Organization for Nuclear Research, Geneva,
Switzerland
18: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
19: Also at University of Hamburg, Hamburg, Germany
20: Also at Brandenburg University of Technology, Cottbus, Germany
21: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
22: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
23: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary
24: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India
25: Also at Institute of Physics, Bhubaneswar, India
26: Also at University of Visva-Bharati, Santiniketan, India
27: Also at University of Ruhuna, Matara, Sri Lanka
28: Also at Isfahan University of Technology, Isfahan, Iran
29: Also at Yazd University, Yazd, Iran
30: Also at Plasma Physics Research Center, Science and Research Branch,
Islamic Azad University, Tehran, Iran
31: Also at Università degli Studi di Siena, Siena, Italy
32: Also at INFN Sezione di Milano-Bicocca; Università di Milano-Bicocca,
Milano, Italy
33: Also at Purdue University, West Lafayette, USA
34: Also at International Islamic University of Malaysia, Kuala Lumpur,
Malaysia
35: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia
36: Also at Consejo Nacional de Ciencia y Tecnología, Mexico city, Mexico
37: Also at Warsaw University of Technology, Institute of Electronic Systems,
Warsaw, Poland
38: Also at Institute for Nuclear Research, Moscow, Russia
39: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
40: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
41: Also at University of Florida, Gainesville, USA
42: Also at P.N. Lebedev Physical Institute, Moscow, Russia
43: Also at California Institute of Technology, Pasadena, USA
44: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
45: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
46: Also at University of Belgrade, Faculty of Physics and Vinca Institute of
Nuclear Sciences, Belgrade, Serbia
47: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy
48: Also at National and Kapodistrian University of Athens, Athens, Greece
49: Also at Riga Technical University, Riga, Latvia
50: Also at Universität Zürich, Zurich, Switzerland
51: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna,
Austria
52: Also at Adiyaman University, Adiyaman, Turkey
53: Also at Istanbul Aydin University, Istanbul, Turkey
54: Also at Mersin University, Mersin, Turkey
55: Also at Cag University, Mersin, Turkey
56: Also at Piri Reis University, Istanbul, Turkey
57: Also at Izmir Institute of Technology, Izmir, Turkey
58: Also at Necmettin Erbakan University, Konya, Turkey
59: Also at Marmara University, Istanbul, Turkey
60: Also at Kafkas University, Kars, Turkey
61: Also at Istanbul Bilgi University, Istanbul, Turkey
62: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom
63: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
64: Also at Instituto de Astrofísica de Canarias, La Laguna, Spain
65: Also at Utah Valley University, Orem, USA
66: Also at Beykent University, Istanbul, Turkey
67: Also at Bingol University, Bingol, Turkey
68: Also at Erzincan University, Erzincan, Turkey
69: Also at Sinop University, Sinop, Turkey
70: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey
71: Also at Texas A&M University at Qatar, Doha, Qatar
72: Also at Kyungpook National University, Daegu, Korea