B2G-17-005

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$Id:B2G-17-005.tex4606802018-05-1715:47:01Zplujan$

B2G-17-005

# Search for a heavy resonance decaying into a boson and a vector boson in the
$\PGn\PAGn\PQq\PAQq$ final state

###### Abstract

A search is presented for a heavy resonance decaying into either a pair of
bosons or a boson and a boson ($\PZ\PZ$ or ), with a boson decaying into a
pair of neutrinos and the other boson decaying hadronically into two
collimated quarks that are reconstructed as a highly energetic large-cone jet.
The search is performed using the data collected with the CMS detector at the
CERN LHC during 2016 in proton-proton collisions at a center-of-mass energy of
13, corresponding to a total integrated luminosity of 35.9. No excess is
observed in data with regard to background expectations. Results are
interpreted in scenarios of physics beyond the standard model. Limits at 95%
confidence level on production cross sections are set at 0.9fb (63fb) for
spin-1 bosons, included in the heavy vector triplet model, with mass 4.0(1.0),
and at 0.5fb (40fb) for spin-2 bulk gravitons with mass 4.0(1.0). Lower limits
are set on the masses of bosons in the context of two versions of the heavy
vector triplet model of 3.1and 3.4, respectively.

##  0.1 Introduction

Many models of physics beyond the standard model (BSM) predict the existence
of additional heavy resonances that may decay into a pair of vector bosons. A
particular class of models addresses the divergence of quantum mechanical
corrections to the Higgs boson mass, known as the hierarchy problem, by
introducing extra spatial dimensions (such as warped extra dimensions models
[1, 2]), which predict the presence of additional massive particles.

The Randall–Sundrum model [3, 4] introduces one warped extra dimension to
solve the hierarchy problem. In the four-dimensional bulk space, two branes
are hypothesized: one whose fundamental scale is the Planck scale, and one at
the scale, where the standard model (SM) particles are confined. Spin-2
gravitons, expected to have a mass at the scale, are allowed to propagate from
the Planck brane to the brane via the warped fourth spatial dimension. In the
bulk warped extra dimension model, the SM particles can also propagate through
the bulk multidimensional space. In this context, spin-2 bulk gravitons can be
produced at a significant rate via gluon fusion, and can decay into a pair of
vector bosons [5]. Two parameters are used to describe the model: the mass of
the proposed spin-2 particle and $\widetilde{k}=k/\overline{M}_{\mathrm{Pl}}$,
where $k$ is the curvature parameter of the five-dimensional space-time
metric, and $\overline{M}_{\mathrm{Pl}}=\Mpl/\sqrt{8\pi}$ is the reduced
Planck mass.

Other theories extend the SM by adding fields to the SM Lagrangian, resulting
in a larger symmetry. New vector bosons arise from the breaking of this
symmetry. The heavy vector triplet (HVT) model [6] provides a framework for
many BSM models, in particular those where heavy spin-1 partners of the vector
bosons (and bosons) [7, 8] are expected to be weakly coupled to SM particles
(referred to as the “HVT model A” scenario), and the composite Higgs model [9,
10], where exotic vector bosons are strongly coupled to ordinary particles
(the “HVT model B” scenario). Both scenarios are described by three Lagrangian
parameters: the couplings of spin-1 particles to SM fermions
($c_{\mathrm{F}}$) and to SM bosons ($c_{\mathrm{H}}$), and the strength of
the interaction ($g_{\mathrm{V}}$). In the HVT model A scenario,
$g_{\mathrm{V}}=1$, $c_{\mathrm{F}}=-1.316$, and $c_{\mathrm{H}}=-0.556$; in
HVT model B, $g_{\mathrm{V}}=3$, $c_{\mathrm{F}}=1.024$, and
$c_{\mathrm{H}}=0.976$ [6]. Previous searches performed at the CERN LHC
looking for evidence for these models have set limits on the production cross
section of the new heavy bosons (46.1fb at a mass of 1.4and 0.7fb at a mass of
4.1), and mass lower limits of 3.3(3.6) for HVT model A (model B) [11, 12, 13,
14, 15].

In this article, we present the results of a search for heavy resonances
decaying into a pair of vector bosons, where one vector boson is a boson
decaying into neutrinos, while the other boson V (either a or boson) decays
hadronically. The vector bosons are mostly produced in a back-to-back topology
with large Lorentz boosts because of the large mass of the new particle (on
the order of 1); this implies that the two quarks originating from the vector
boson decay are close enough to be reconstructed within one single large-cone
jet, an approach that, in this kinematic region, is more efficient than
building the vector boson candidate as two distinct standard jets. Since
neutrinos do not leave any visible signature in the detector, they are
reconstructed as a large amount of missing transverse momentum () recoiling
against the hadronic component. The sensitivity of the search is enhanced by
the relatively high branching fraction of the boson into neutrinos (20%) and
of the other vector boson into a pair of quarks ($\approx$70%). Jet
substructure techniques [16] are exploited to improve the discrimination
between signal events and SM background processes.

The contributions of the SM backgrounds, composed mainly of +jets and +jets
events, are estimated using a method that interpolates the data from control
regions into the signal region with a fit constrained by the simulation.

##  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 (HCAL), each composed of a barrel and two endcap sections. Forward
calorimeters extend the pseudorapidity ($\eta$) coverage provided by the
barrel and endcap detectors. Muons are detected in gas-ionization chambers
embedded in the steel flux-return yoke outside the solenoid. Events of
interest are selected using a two-tiered trigger system [17]. The first level,
composed of custom hardware processors, uses information from the calorimeters
and muon detectors. 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.

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

##  0.3 Data and simulated samples

The analysis is performed on data collected in 2016 with the CMS detector
during proton-proton collisions at the LHC at a center-of-mass energy of 13,
corresponding to a total integrated luminosity of 35.9.

Two signal models are simulated: the first considers a spin-1 HVT boson
decaying into a and a boson for both A and B scenarios, and the second
considers a spin-2 bulk graviton decaying into two bosons. Both processes are
generated at leading order (LO) with the v2.2.2 [19] matrix element Monte
Carlo (MC) generator for a range of different mass hypotheses for the
resonances from 0.6 to 4.5. Signals are generated assuming the resonances have
negligible width (0.1% of their masses) compared to the experimental
resolution (4–8% depending on their masses); this assumption is the so-called
“narrow-width approximation”. The actual width of the spin-2 resonances may be
larger depending on the value of the curvature parameter $\widetilde{k}$ in
the model [1, 2], but this effect is only significant for values of
$\widetilde{k}$ larger than 1, which are not considered in this analysis. For
the background, events with a vector boson produced with additional partons
are generated at next-to-leading order (NLO) in with , using the FxFx merging
scheme [20]. Electroweak corrections at NLO [21] are applied to these samples
as a function of the transverse momentum of the vector bosons. Top quark-
antiquark () and single top quark events are simulated at NLO in the five-
flavor scheme with v2 [22, 23, 24, 25, 26]. Inclusive diboson production (, ,
$\PZ\PZ$) is considered as well, and generated with 8.212 [27] at LO. The
hadronization and fragmentation steps of all simulated samples are handled by
with the CUETP8M1 [28] tune. The NNPDF3.1 [29] parton distribution functions
are used in the simulations. The effect of additional proton-proton
interactions within the same or nearby bunch crossings (pileup) is accounted
for by adding simulated minimum bias events to the hard interaction. The
frequency distributions of the pileup events are reweighted to match those
observed in data. The simulation of the CMS detector is performed with [30].

##  0.4 Event reconstruction

The particle-flow (PF) event algorithm [31] reconstructs and identifies each
individual particle with an optimized combination of information from the
various elements of the CMS detector. The energy of photons is obtained
directly from the ECAL measurement, corrected for zero-suppression effects.
The energy of electrons is determined from a combination of the electron
momentum at the primary interaction vertex as determined by the tracker, the
energy of the corresponding ECAL cluster, and the energy sum of all
bremsstrahlung photons spatially compatible with originating from the electron
track. The energy of muons is obtained from the curvature of the corresponding
track.

The energy of charged hadrons is determined from a combination of their
momentum measured in the tracker and the matching ECAL and HCAL energy
deposits, corrected for zero-suppression effects and for the response function
of the calorimeters to hadronic showers. Finally, the energy of neutral
hadrons is obtained from the corresponding corrected ECAL and HCAL energies.

Jets are reconstructed from PF inputs, using 3.1 [32] to cluster jets with the
anti-algorithm [33], with two distance parameters: 0.4 (“AK4” jets) and 0.8
(“AK8” jets). The jet momentum is determined as the four-vector sum of all
particle momenta in the jet, and is found from simulation to be within 2 to
10% of the momentum of the quark that initiated the jet, over the whole
spectrum and detector acceptance. The raw jet energies are further corrected
to establish a relative uniform response of the calorimeter in $\eta$ and a
calibrated absolute response in [34]. Charged particles not associated to the
primary vertex are removed from the jet [35]. An additional offset correction
is applied to the jet energies to subtract the contribution from pileup [35].
The jet energy scale (JES) is calculated using a detailed MC simulation of the
detector, and further adjusted using the balance in dijet, multijet,
photon+jet and leptonically decaying +jet events in data [36]. A smearing
procedure has been applied to jets in the simulated samples in order to
account for small differences between the jet momentum resolutions observed in
simulation and in data. The jet energy resolution (JER) is ${\approx}$15% at
10, 8% at 100, and 4% at 1 [36].

A minimum threshold on the energy recorded in the HCAL is applied to remove
spurious jet-like features originating from isolated noise patterns in certain
regions. Jets are required to have more than one PF constituent, and they are
required to have less than 80% of their total energy originating from neutral
hadrons, less than 99% from electrons, and more than 20% from charged hadrons.

The jet mass reconstruction is optimized for this analysis using a combination
of a jet grooming technique [37, 38] and pileup mitigation [39]. In the jet
grooming algorithm, the constituents of the AK8 jets are reclustered using the
Cambridge–Aachen algorithm [40, 41]. The “modified mass drop tagger” algorithm
[37], also known as the “soft drop” algorithm, with angular exponent
$\beta=0$, soft cutoff threshold $z_{\text{cut}}<0.1$, and characteristic
radius $R_{0}=0.8$ [38], is applied to remove soft, wide-angle radiation from
the jet. The pileup mitigation is performed by the “pileup per particle
identification” algorithm [39], a method that assigns a weight to each charged
or neutral particle, which is determined by the probability for the particle
to have originated from the primary vertex of the hard interaction. Finally,
the jet mass is corrected with -dependent factors [42] to account for the
small difference observed in the reconstructed vector boson mass between data
and simulated events in a control sample, in which one boson, originating from
the top or antitop quark, decays into leptons and the other boson decays
hadronically.

The missing transverse momentum vector is defined as the negative sum of the
of all PF candidates in the event:
$\ptvecmiss=-\Sigma_{i}\vec{p}_{\mathrm{T}}^{\kern 1.0pti}$; its magnitude is
referred to as . This raw quantity is corrected by propagating the effect of
the jet energy corrections. Uncertainties in the determination arise from
mismeasurements caused by detector alignment, unclustered energy deposits, and
contributions coming from pileup [43]. Events with spurious missing momentum
related to detector noise and badly reconstructed events are rejected [43].

##  0.5 Event selection

Events are required to satisfy criteria at the HLT trigger level on either or
the missing hadronic activity, $H_{\mathrm{T}}^{\text{miss}}$, which is
defined as the magnitude of the transverse component of the negative sum of
the three-momenta of all the objects identified as jets at trigger level. To
avoid inefficiencies due to the prescaling of the triggers during high-
luminosity LHC operation, several triggers are used, variously requiring
$H_{\mathrm{T}}^{\text{miss}}$ or $\ptmiss>90$, 110, 120, or
$\ptmiss>170\GeV$, in order to have at least one nonprescaled trigger at any
given time.

The trigger efficiency has been measured with data events satisfying one or
more single-muon triggers. A leptonic decay topology is selected
($\PW\to\mu\nu$), since it ensures the presence of in the event, due to the
neutrino. One muon identified by offline algorithms is required: this not only
guarantees that the sample does not overlap with the search region of the
analysis (where events with muons are rejected), but also reduces the
contamination from particles or jets misidentified as leptons at the trigger
level. The additional condition of having at least one AK8 jet is applied, in
order to select events with a topology similar to that of the considered
search. The combination of triggers reaches a plateau in efficiency of 96%
around $\ptmiss>200\GeV$, which is chosen as the minimum threshold for the
event selection. An independent efficiency measurement has been performed
using a data set satisfying single-electron triggers, and the discrepancy with
the result based on the muon data set is taken as a systematic uncertainty,
which amounts to 1%.

The AK8 jets are required to satisfy $\pt>200\GeV$ and $\abs{\eta}<2.4$. The
largest-AK8 jet in the event is assumed to be the hadronically decaying boson
(V) candidate.

The jet mass ($m_{\text{j}}$) is used to define the search region. Since the
analysis searches for a diboson resonance where one vector boson decays
hadronically, the mass of the jet candidate is expected to lie within a window
around the nominal masses of the and bosons, chosen to be between 65 and 105.
Two control regions are defined that are expected to be depleted in signal:
the “low sideband”, which lies in the $m_{\text{j}}$ range 30–65, and the
“high sideband”, with $m_{\text{j}}$ above 135. These sidebands play a crucial
role in the background estimation. The region 105–135is excluded from the
sideband selections in order to not overlap with other diboson searches aiming
at a final state containing a hadronically decaying Higgs boson. This
exclusion allows the results to be combined with those of other searches in a
straightforward manner. The region under 30is discarded, since jets are not
reconstructed sufficiently well in this region.

Jet substructure is exploited to further improve the ability to identify
signal events. The $\tau_{21}$ $N$-subjettiness ratio [16] distinguishes jets
with two separable substructure components from jets with only one
substructure component. In the former case, the $\tau_{21}$ distribution is
peaked towards a small fraction of unity; in the latter case, it has a broader
shape, centered around larger values closer to 1. Two exclusive search
categories are defined: a low-purity category ($0.35<\tau_{21}<0.75$) and a
high-purity category ($\tau_{21}<0.35$). In principle, the high-purity
category is the most sensitive to the signals explored; nevertheless, the low-
purity category allows us to retain a significant part of the signal
efficiency, especially for very heavy resonances (3–4). As a consequence, the
signal sensitivity improves by up to 40% when the categories are combined.
Multiplicative scale factors [42] are used to correct observed discrepancies
between data and simulation, and are measured to be $0.99\pm 0.11$ for events
falling into the high-purity category and $1.03\pm 0.23$ for those in the low-
purity category. They have been measured with MC simulation and top quark-
enriched data samples, and are applied to simulated backgrounds.

The reconstructed of the invisibly decaying boson is set equal to . Thus,
instead of the invariant mass, the resulting reconstructed Vcandidate mass is
the transverse mass $m_{\mathrm{T}}^{\mathrm{VZ}}$:

$m_{\mathrm{T}}^{\mathrm{VZ}}=\sqrt{\smash[b]{2\ET^{\text{j}}\ptmiss\left(1-\cos{\Delta\phi(\vec{p}^{\text{\kern
1.0ptj}}_{\mathrm{T}},\ptvecmiss)}\right)}},$ (1)

where $\ET^{\text{j}}=E^{\text{j}}\sin\theta$ and
$\Delta\phi(\vec{p}^{\text{\kern 1.0ptj}}_{\mathrm{T}},\ptvecmiss)$ is the
azimuthal angle between the and the leading AK8 jet transverse momentum
vector.

The AK4 jets are used for background suppression; they are required to satisfy
$\pt>30\GeV$ and $\abs{\eta}<2.4$. If the event contains an AK4 jet passing a
loose b tagging criterion using the combined secondary vertex (CSVv2) [44, 45]
algorithm, and it does not overlap with the AK8 jet identified as the V
candidate, the event is discarded, since this suggests that the event is more
likely to have originated from a top quark decay. Scale factors are applied to
correct for the different b tagging efficiency in data and simulated samples
[44, 45].

A set of selection criteria has been applied to improve the background
rejection. By requiring a minimum azimuthal angular separation of 0.5 between
and the of the AK4 jets outside the cone of the leading AK8 jet, the
contribution of background events originating from soft multijet radiation is
reduced from 30% to 2% or 3%, depending on the purity category. The single top
quark and contributions are approximately halved by applying the loose b tag
veto described above. Background contributions are further suppressed by
requiring a back-to-back topology in the transverse plane between the V and
candidates, specifically, $\Delta\phi>2$.

Final states with photons, electrons, muons, and hadronically decaying tau
leptons are rejected in this analysis. The identification of these objects is
performed using the variables described in Ref. [31]. An event is discarded if
it contains at least one photon with $\pt>15\GeV$ and $\abs{\eta}<2.5$, at
least one electron with $\pt>10\GeV$ and $\abs{\eta}<2.5$, at least one muon
with $\pt>10\GeV$ and $\abs{\eta}<2.4$, or at least one hadronically decaying
tau lepton with $\pt>18\GeV$ and $\abs{\eta}<2.4$.

The main discriminating variables used to perform the background prediction,
$m_{\text{j}}$ and $\tau_{21}$, are compared in data and MC simulation in Fig.
1. Two signal hypotheses, a spin-1 boson and a spin-2 bulk graviton, are
displayed as well. They are characterized by jet mass spectra peaking at the
mass and at the mass, respectively, and by a $\tau_{21}$ distribution
reflecting the two-prong structure of the jet produced in the vector boson
hadronic decay, significantly different from the background. The discrepancy
visible between the data and the background prediction is due to the imperfect
modeling of the jet substructure and momentum in simulation. Agreement is
achieved when a hybrid data/simulation background estimation approach,
described in Section 0.6, is applied.

Figure 1: Comparison of data and simulated events. Left: the corrected mass of
the leading AK8 jet, interpreted as the hadronically decaying vector boson.
Right: the distribution of the $\tau_{21}$ subjettiness of the vector boson
candidate, which is used to define low- and high-purity categories. The
background processes predicted by the SM are depicted as colored filled
histograms. The shaded area on top of the histograms represents the
statistical uncertainty associated to MC simulations. Overflows are shown in
the rightmost bin. Two possible signal hypotheses are shown: a spin-1 boson
with a mass of 3and a spin-2 bulk graviton with a mass of 1. The data points
are shown by the black markers, along with their associated statistical
uncertainties. In the bottom panels, the ratio between data and MC predictions
is calculated for each bin.

##  0.6 Background estimation

This analysis searches for a localized excess in data in the transverse mass
spectrum of the VZ system. Hence, accurate background modeling is crucial to
the analysis.

The main irreducible background is from events in which a boson is produced
along with additional jets (“+jets”) and decays into neutrinos. The second
dominant contribution comes from events in which a boson is produced along
with additional jets (“+jets”) and decays leptonically, with the charged
lepton falling outside the detector acceptance or not correctly identified.
Since the production mechanisms of these two processes are the same, these two
categories of events are grouped together as “V+jets” events. Smaller
background contributions come from events in which at least one top quark
(either a pair or a single top quark, indicated as “Top” background) or a pair
of vector bosons (, , or $\PZ\PZ$, which we call “VV” background) is produced;
these are referred to as “secondary backgrounds”.

The background estimation technique [46], which is now known as the “$\alpha$
method”, takes advantage of the data sidebands to predict the normalization
and $m_{\mathrm{T}}^{\mathrm{VZ}}$ shape of the V+jets background
distributions, which are poorly populated by simulations in phase space
regions with large transverse momentum. The normalization and shape of the
secondary backgrounds are determined from MC simulation. This data-driven
approach allows us to improve the agreement between data and predictions,
especially in the higher tails of the momentum distributions.

The background prediction is performed in two steps for each of the two purity
categories. First, the mass spectrum of the AK8 jet is the variable chosen to
predict the background event yield in the signal region. Then, once the
normalization is determined, the transverse mass distribution of the diboson
candidates is used to predict the background shapes in the signal region.

To perform the normalization prediction, the $m_{\text{j}}$ distribution of
each background is fitted in simulated samples with an empirical probability
density function (pdf), converted into an extended likelihood in order to
allow the event yield to vary in the fit. The main background is modeled by
using two alternative functional forms, and the difference between the two
yield predictions is considered as a systematic uncertainty and propagated to
the final results. The $m_{\text{j}}$ spectrum of the V+jets background is
smoothly falling in the low-purity category; hence, it is modeled as a power
law (main function) or as a Gaussian peak added to a falling exponential
(alternative function), in order to check that a different description of the
slope of the spectrum near the signal region does not significantly affect the
final result. In the high-purity category, the $m_{\text{j}}$ spectrum has a
peaking component, so it is described by a broad Gaussian peak, centered at
approximately 150 GeV, added to a falling exponential (main function), or by
an exponential function convolved with an error function to describe the turn-
on effect at low mass (alternative function). The top quark and diboson
backgrounds are modeled as Gaussian peaks, centered on the top quark and or
masses, respectively, added to a smoothly falling exponential background.

Once the extended likelihoods for the main and secondary backgrounds are added
together, an extended maximum likelihood fit is performed in the data
sidebands. The parameters related to the V+jets background and its
normalization are allowed to vary according to data, whereas those describing
the secondary backgrounds are fixed to the theoretical predictions. The
expected number of background events in the signal region is then evaluated by
integrating the final extended likelihood that describes the total background.

The results of the background estimation are presented in Fig. 2 as smooth
functions, and are compared to data. The fit to the data is performed in the
sideband regions described in Section 0.5. Data are compared to the $\alpha$
method background predictions in the signal region (SR), while the Higgs
region is excluded from the analysis. It can be seen that the data agree with
the background estimates.

Figure 2: Background yield prediction in the signal region obtained with the
$\alpha$ method, in the low-purity (left) and high-purity (right) categories.
Background processes predicted by the SM are depicted as colored areas bounded
by smooth functions. The bottom panels show fit residuals normalized to their
uncertainties.

The final step consists in predicting the functional shape of the
$m_{\mathrm{T}}$ spectrum of the total background. First, the distribution of
$m_{\mathrm{T}}^{\mathrm{VZ}}$ is described separately for each background
using MC simulation, both in the signal region and sidebands. The general
background shape expected for all SM processes is an exponentially falling
function with two parameters, of the form $e^{-x/(a+bx)}$.

The $\alpha$ function is defined as the ratio between the V+jets background
pdf in the signal region ($f_{\text{SR}}^{\text{V+jets}}$) and that in the
sidebands ($f_{\text{SB}}^{\text{V+jets}}$), predicted from simulation:

$\alpha(m_{\mathrm{T}}^{\mathrm{VZ}})=\frac{f_{\text{SR}}^{\text{V+jets}}(m_{\mathrm{T}}^{\mathrm{VZ}})}{f_{\text{SB}}^{\text{V+jets}}(m_{\mathrm{T}}^{\mathrm{VZ}})}.$
(2)

The $\alpha$ ratio can be interpreted as a transfer function from the
sidebands to the signal region, accounting for the small kinematical
differences in the two regions of the V+jets background. The typical
correction resulting from using the $\alpha$ ratio is on the order of 1–5 per
mil. A simultaneous fit to MC simulation and data sidebands is performed in
order to extract the $\alpha$ function and the main background parameters
respectively, while the secondary background shapes are taken from predictions
from MC simulation, as described in the following equation:

$f_{\text{SR}}^{\text{data}}(m_{\mathrm{T}}^{\mathrm{VZ}})=\left[f_{\text{SB}}^{\text{data}}(m_{\mathrm{T}}^{\mathrm{VZ}})-f_{\text{SB}}^{\text{Top}}(m_{\mathrm{T}}^{\mathrm{VZ}})-f_{\text{SB}}^{\text{VV}}(m_{\mathrm{T}}^{\mathrm{VZ}})\right]\alpha(m_{\mathrm{T}}^{\mathrm{VZ}})+f_{\text{SR}}^{\text{Top}}(m_{\mathrm{T}}^{\mathrm{VZ}})+f_{\text{SR}}^{\text{VV}}(m_{\mathrm{T}}^{\mathrm{VZ}}).$
(3)

The background estimation obtained with the $\alpha$ method, , the predicted
spectrum of $m_{\mathrm{T}}^{\mathrm{VZ}}$ in the background-only hypothesis,
is compared with data in Fig. 3, and no significant excess is observed with
regard to the SM expectations.

Figure 3: Expected background shapes as a function of the transverse mass of
the diboson candidate obtained using the $\alpha$ method in the low-purity
(left) and high-purity (right) categories, represented as colored areas
bounded by smooth functions. As a reference, the expected distribution of a
with a mass of 3decaying into a boson and a boson is displayed. Data are shown
as black markers.

The robustness of the $\alpha$ method is tested by splitting the low sideband
into two sub-regions, one considered as a narrower lower sideband (30–50) and
the other (50–65) taken as a validation region. The predictions obtained by
applying the $\alpha$ method in the narrow lower sideband and the high
sideband are then compared to data distributions in the validation region, and
are found to agree.

##  0.7 Systematic uncertainties

The background normalization is predicted from a set of simultaneous fits to
the simulated and data samples, so the uncertainty in the normalization is
estimated by propagating all the uncertainties affecting the main and the
secondary background fits. The statistical uncertainty in the fit, determined
by the number of data events in the sidebands, contributes to the uncertainty
in the main background event yield by 5% and 15% for the low- and high-purity
categories, respectively. A second source of uncertainty is the absolute
difference in the V+jets event yield prediction between the main function and
the alternative function used to fit the $m_{\text{j}}$ spectrum of the V+jets
background in the simulated samples. It amounts to 5% and 4% for the low- and
high-purity categories, respectively. The uncertainties related to the number
of expected events from the secondary backgrounds amount to 68% and 48% for
the low- and high-purity categories, respectively, for the top quark
background yield, and to 11% and 19%, respectively, for the diboson background
yield. Given that the secondary backgrounds are a small fraction of the total,
the overall impact of the uncertainties in their event yields is negligible.

The uncertainties in the parameters describing the shape of the
$m_{\mathrm{T}}^{\mathrm{VZ}}$ distribution of the main background are
obtained by propagating the uncertainties related to each parameter of the
simultaneous fit to simulation and data sidebands. These parameters are then
decorrelated by diagonalizing their covariance matrix with a linear
transformation.

The normalizations of the secondary backgrounds and of the signal are affected
by a 1% uncertainty in the trigger efficiency, calculated as described in
Section 0.5.

The impact of the uncertainties in the of the reconstructed bosons is
evaluated by simultaneously varying their within their uncertainties, since is
influenced by the corrections applied to all the hadronic objects present in
the event. The uncertainties related to JES and JER are evaluated by varying
their numerical values within their uncertainties. They have a negligible
impact (less than 1%) on both the normalization of the signal and secondary
backgrounds, and on their shape; namely, on the parameters describing the
exponential behavior of the spectra. The uncertainty in arising from
unclustered energy deposits is also negligibly small. Uncertainties related to
the $m_{\text{j}}$ corrections are considered, and they affect the signal and
background yields by 1%. Uncertainties related to the jet mass smearing affect
the signal yield by 5.1%, the top quark backgrounds by 3.1%, and the diboson
backgrounds by 2.0%. Jet mass smearing uncertainties affect the parameters
describing the top quark and diboson background shapes by 4% and 1%,
respectively.

The uncertainty related to the $\tau_{21}$ scale factors, as described in
Section 0.5, has the largest single impact on the final results. An additional
source of uncertainty comes from the jet dependence of the $\tau_{21}$ scale
factors. The $\tau_{21}$ distributions are modeled at higher regimes (above
200), where the event yield is very small in data, by using an alternative
showering scheme ( [47]) and compared to . The discrepancy between the
predictions is parameterized as a function of the jet . In this analysis, the
uncertainties due to the $\tau_{21}$ scale factor extrapolations at high
amount to 9–20%, depending on the purity category.

The uncertainty in the b tagging efficiency affecting the veto applied to AK4
jets impacts the signal normalization by 1%, the diboson background
normalization by less than 1%, and the top quark background normalization by
2%.

A minor source of uncertainty comes from the uncertainty in the total
inelastic proton-proton cross section at 13, which affects the pileup
distribution, and thus the normalization of the simulated samples. It amounts
to less than 1% for diboson, top quark, and signal samples.

A 3% uncertainty is assigned to the efficiency of vetoing hadronically
decaying tau leptons. The uncertainty in the measurement of the integrated
luminosity amounts to 2.5% [48].

The renormalization and factorization scales used in the simulation are varied
by a factor of 2 and a factor of 0.5, both separately and independently. Per-
event weights are extracted and propagated to the invariant mass
distributions. These scale variations affect the shape of the top quark
background by a total of 1%, and its normalization by 7% (renormalization
scale) and 3% (factorization scale); they both affect the diboson background
normalization by 1%. The uncertainty related to the choice of the parton
distribution functions used in simulation is estimated by following the
prescriptions in Ref. [49], using the NNPDF3.1 [29] set. The parameters
describing the parton distribution functions are varied together within their
uncertainties, and the resulting variations are used as a set of per-event
weights, applied to the invariant mass distributions. These uncertainties
affect the normalization of the top quark and diboson backgrounds by 0.3%
each; the effect on the top quark and diboson background shapes is negligibly
small. Uncertainties of 15% [50, 51] and 10% [52, 53, 54] are assigned to the
normalization of the diboson and top quark backgrounds, respectively, from the
knowledge of the production cross section.

##  0.8 Results

An unbinned profile likelihood fit is performed on the final spectra of the
transverse mass of the diboson candidates. The signals are modeled with a
Crystal Ball function [55], , a function with a Gaussian core and a power-law
behavior in the low tail. Systematic uncertainties are treated as nuisance
parameters constrained with a log-normal distribution and profiled during the
minimization. The background-only hypothesis is tested in the data, where the
low- and high-purity categories have been combined. The asymptotic modified
frequentist approach [56, 57, 58], or CLs criterion, is used to quote 95%
confidence level (CL) limits.

The observed and expected limits on the product of the cross section and
branching fraction
($\sigma\mathcal{B}(\PWpr\to\PW_{\text{had}}\PZ_{\text{inv}})$) for a spin-1
decaying into and bosons that in turn decay in the hadronic and invisible
channels, respectively, as a function of the mass of the resonance, are shown
in Fig. 4 (left). The hypothesis of a heavy spin-1 resonance, predicted by the
HVT model A scenario, is rejected at 95% CL for masses smaller than 3.1, while
the described in the HVT model B context is excluded up to 3.4. At these mass
values, the product of cross section and branching fraction are expected to be
1.4fb and 1.1fb, respectively.

The observed and expected limits on the product of the cross section and
branching fraction
($\sigma\mathcal{B}(\cPG\to\PZ_{\text{had}}\PZ_{\text{inv}})$) for a spin-2
bulk graviton decaying into a pair of bosons, where one boson decays
hadronically and the other invisibly, are shown in Fig. 4 (right), as a
function of the mass of the resonance. The theoretical predictions for the
curvature parameter hypothesis $\widetilde{k}=0.5$ are shown for comparison.

The results of this search complement those published by the ATLAS
Collaboration [59], which were obtained from an investigation of the same
final state, using different jet substructure and background estimation
techniques. The limits obtained here are the best single limits obtained in
this final state.

Figure 4: The observed and expected limits on the product of the cross section
and branching fraction
$\sigma\mathcal{B}(\PWpr\to\PW_{\text{had}}\PZ_{\text{inv}})$ for a spin-1 HVT
signal hypothesis (left) and
$\sigma\mathcal{B}(\cPG\to\PZ_{\text{had}}\PZ_{\text{inv}})$ for a spin-2 bulk
graviton signal hypothesis (right), as a function of the and mass,
respectively. The low- and high-purity categories have been combined. The
inner and outer shaded bands indicate the 68% and 95% uncertainty intervals
associated with the expected limits. Theoretical predictions are shown for:
(left) the two HVT models considered, model A (blue dotted-and-dashed line)
and model B (red solid line), and (right) a graviton model with a curvature
parameter of $\widetilde{k}=0.5$ (violet solid line).

##  0.9 Summary

A search has been made for heavy diboson resonances (, $\PZ\PZ$) decaying into
a pair of vector bosons, one of which is a boson decaying into $\PGn\PAGn$ and
the other is a or boson that decays into $\PQq\PAQq$. The data were collected
by the CMS detector from proton-proton collisions produced at the LHC at a
center-of-mass energy of 13. In this analysis, the hadronically decaying or
boson is reconstructed as a large-cone jet. The invisible decay of the boson
manifests itself as a large amount of missing transverse momentum recoiling
against the jet. The transverse components of the Vsystem momentum are used to
define the transverse mass variable, where a search for a localized excess is
performed. The expected background is described with a hybrid data/simulation
approach that takes advantage of data sidebands to predict the background
normalization and shape in the signal region. To improve the discovery
potential, two purity categories are defined, based on a jet substructure
observable. An unbinned maximum likelihood fit is performed. No excess is
observed in data compared to standard model predictions. Upper limits are
established at 95% confidence level on the product of the production cross
section and branching fraction for a spin-1 heavy vector triplet (HVT) boson
and spin-2 bulk graviton, which are in the range 0.9–63fb and 0.5–40fb,
respectively, depending on the resonance mass. The existence of a boson is
excluded at 95% confidence level up to a mass of 3.1in the HVT model A and up
to 3.4in the HVT model B.

###### Acknowledgements.

We congratulate our colleagues in the CERN accelerator departments for the
excellent performance of the LHC and thank the technical and administrative
staffs at CERN and at other CMS institutes for their contributions to the
success of the CMS effort. In addition, we gratefully acknowledge the
computing centers and personnel of the Worldwide LHC Computing Grid for
delivering so effectively the computing infrastructure essential to our
analyses. Finally, we acknowledge the enduring support for the construction
and operation of the LHC and the CMS detector provided by the following
funding agencies: BMWFW and FWF (Austria); FNRS and FWO (Belgium); CNPq,
CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC
(China); COLCIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus);
SENESCYT (Ecuador); MoER, ERC IUT, and ERDF (Estonia); Academy of Finland,
MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF
(Germany); GSRT (Greece); NKFIA (Hungary); DAE and DST (India); IPM (Iran);
SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); LAS
(Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and
UASLP-FAI (Mexico); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC
(Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS, RFBR and RAEP
(Russia); MESTD (Serbia); SEIDI, CPAN, PCTI and FEDER (Spain); Swiss Funding
Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA
(Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United
Kingdom); DOE and NSF (USA). Individuals have received support from the Marie-
Curie program and the European Research Council and Horizon 2020 Grant,
contract No. 675440 (European Union); the Leventis Foundation; the A. P. Sloan
Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science
Policy Office; the Fonds pour la Formation à la Recherche dans l’Industrie et
dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door
Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium)
under the “Excellence of Science - EOS” - be.h project n. 30820817; the
Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the
Lendület (“Momentum”) Program and the János Bolyai Research Scholarship of the
Hungarian Academy of Sciences, the New National Excellence Program ÚNKP, the
NKFIA research grants 123842, 123959, 124845, 124850 and 125105 (Hungary); the
Council of Science and Industrial Research, India; the HOMING PLUS program of
the Foundation for Polish Science, cofinanced from European Union, Regional
Development Fund, the Mobility Plus program of the Ministry of Science and
Higher Education, the National Science Center (Poland), contracts Harmonia
2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and
2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities
Research Program by Qatar National Research Fund; the Programa Estatal de
Fomento de la Investigación Científica y Técnica de Excelencia María de
Maeztu, grant MDM-2015-0509 and the Programa Severo Ochoa del Principado de
Asturias; the Thalis and Aristeia programs cofinanced by EU-ESF and the Greek
NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn
University and the Chulalongkorn Academic into Its 2nd Century Project
Advancement Project (Thailand); the Welch Foundation, contract C-1845; and the
Weston Havens Foundation (USA).

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##  .10 The CMS Collaboration

Yerevan Physics Institute, Yerevan, Armenia
A.M. Sirunyan, A. Tumasyan Institut für Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, E. Brondolin, M.
Dragicevic, J. Erö, A. Escalante Del Valle, 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, A. Taurok, 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, I. Marchesini, 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, B. Bilin, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, B.
Dorney, G. Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk, A.K. Kalsi, T.
Lenzi, J. Luetic, T. Maerschalk, A. Marinov, T. Seva, E. Starling, C. Vander
Velde, P. Vanlaer, D. Vannerom, R. Yonamine, F. Zenoni Ghent University,
Ghent, Belgium
T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov2, D. Poyraz, C. Roskas,
S. Salva, D. Trocino, 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
Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil
W.L. Aldá Júnior, F.L. Alves, G.A. Alves, L. Brito, G. Correia Silva, 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, E. Coelho, 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, L.J. Sanchez Rosas, A. Santoro, A. Sznajder, M. Thiel, E.J.
Tonelli Manganote3, F. Torres Da Silva De Araujo, A. Vilela Pereira
Universidade Estadual Paulista a, Universidade Federal do ABC b, São Paulo,
Brazil
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, Bulgarian Academy
of Sciences, Sofia, Bulgaria
A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Misheva, M. Rodozov, M. Shopova,
G. Sultanov University of Sofia, Sofia, Bulgaria
A. Dimitrov, L. Litov, B. Pavlov, P. Petkov Beihang University, Beijing, China
W. Fang5, X. Gao5, 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, T. Yu, H. Zhang, J. Zhao State Key Laboratory of Nuclear
Physics and Technology, Peking University, Beijing, China
Y. Ban, G. Chen, J. Li, Q. Li, S. Liu, Y. Mao, S.J. Qian, D. Wang, Z. Xu, F.
Zhang5 Tsinghua University, Beijing, China
Y. Wang Universidad de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, C.A. Carrillo Montoya, L.F. Chaparro Sierra, C. Florez,
C.F. González Hernández, J.D. Ruiz Alvarez, M.A. Segura Delgado 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
S. Khalil8, M.A. Mahmoud9,10, A. Mahrous11 National Institute of Chemical
Physics and Biophysics, Tallinn, Estonia
S. Bhowmik, 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, T.
Mäenpää, H. Siikonen, E. Tuominen, J. Tuominiemi Lappeenranta University of
Technology, Lappeenranta, Finland
T. Tuuva IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
M. Besancon, F. Couderc, M. Dejardin, D. Denegri, 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. Abdulsalam12, 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. Agram13, J. Andrea, D. Bloch, J.-M. Brom, M. Buttignol, E.C. Chabert, N.
Chanon, C. Collard, E. Conte13, X. Coubez, F. Drouhin13, J.-C. Fontaine13, D.
Gelé, U. Goerlach, M. Jansová, P. Juillot, 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. Popov14, V. Sordini, M. Vander Donckt, S. Viret, S. Zhang Georgian
Technical University, Tbilisi, Georgia
A. Khvedelidze7 Tbilisi State University, Tbilisi, Georgia
D. Lomidze 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, M. Teroerde, B. Wittmer, V. Zhukov14 RWTH Aachen
University, III. Physikalisches Institut A, Aachen, Germany
A. Albert, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg, T. Esch, R. Fischer,
A. Güth, 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. Stahl15 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. Borras16, V. Botta, A.
Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G.
Eckerlin, D. Eckstein, T. Eichhorn, E. Eren, E. Gallo17, J. Garay Garcia, A.
Geiser, J.M. Grados Luyando, A. Grohsjean, P. Gunnellini, M. Guthoff, A. Harb,
J. Hauk, M. Hempel18, H. Jung, M. Kasemann, J. Keaveney, C. Kleinwort, I.
Korol, D. Krücker, W. Lange, A. Lelek, T. Lenz, J. Leonard, K. Lipka, W.
Lohmann18, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, M. Missiroli, G.
Mittag, J. Mnich, A. Mussgiller, E. Ntomari, D. Pitzl, A. Raspereza, M.
Savitskyi, P. Saxena, R. Shevchenko, 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, D. Marconi, M. Meyer, M. Niedziela,
D. Nowatschin, F. Pantaleo15, 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, A. Vanhoefer, B.
Vormwald Institut für Experimentelle Teilchenphysik, 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, M.A. Harrendorf, F. Hartmann15, S.M. Heindl, U. Husemann, F.
Kassel15, 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, 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. Gianneios, P. Katsoulis, P. Kokkas, S. Mallios, N.
Manthos, I. Papadopoulos, E. Paradas, J. Strologas, F.A. Triantis, D.
Tsitsonis MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
M. Csanad, N. Filipovic, G. Pasztor, O. Surányi, G.I. Veres19 Wigner Research
Centre for Physics, Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath20, Á. Hunyadi, F. Sikler, V. Veszpremi, G.
Vesztergombi19 Institute of Nuclear Research ATOMKI, Debrecen, Hungary
N. Beni, S. Czellar, J. Karancsi21, A. Makovec, J. Molnar, Z. Szillasi
Institute of Physics, University of Debrecen, Debrecen, Hungary
M. Bartók19, 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. Bahinipati22, P. Mal, K. Mandal, A. Nayak23, D.K. Sahoo22, N. Sahoo, S.K.
Swain Panjab University, Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, N. Dhingra, A. Kaur, M. Kaur,
S. Kaur, R. Kumar, P. Kumari, A. Mehta, J.B. Singh, G. Walia University of
Delhi, Delhi, India
A. Bhardwaj, S. Chauhan, B.C. Choudhary, R.B. Garg, S. Keshri, A. Kumar, Ashok
Kumar, S. Malhotra, M. Naimuddin, K. Ranjan, Aashaq Shah, 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, 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. Mohanty15, 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. Maity24, G. Majumder, K. Mazumdar, T. Sarkar24, N. Wickramage25
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. Chenarani26, E. Eskandari Tadavani, S.M. Etesami26, M. Khakzad, M.
Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi27, F. Rezaei
Hosseinabadi, B. Safarzadeh28, 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,15, 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,b, 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,29, G. Sguazzonia, D. Stroma, L. Viliania INFN Laboratori Nazionali di
Frascati, Frascati, Italy
L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera15 INFN Sezione di
Genova a, Università di Genova b, Genova, Italy
V. Calvellia,b, F. Ferroa, F. Raveraa,b, E. Robuttia, S. Tosia,b INFN Sezione
di Milano-Bicocca a, Università di Milano-Bicocca b, Milano, Italy
A. Benagliaa, A. Beschib, L. Brianzaa,b, F. Brivioa,b, V. Cirioloa,b,15, 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,30, 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,15, F. Fabozzia,c, F. Fiengaa,b,
A.O.M. Iorioa,b, W.A. Khana, L. Listaa, S. Meolaa,d,15, P. Paoluccia,15, C.
Sciaccaa,b, F. Thyssena INFN Sezione di Padova a, Università di Padova b,
Padova, Italy, Università di Trento c, Trento, Italy
P. Azzia, N. Bacchettaa, L. Benatoa,b, D. Biselloa,b, A. Bolettia,b, R.
Carlina,b, A. Carvalho Antunes De Oliveiraa,b, P. Checchiaa, M. Dall’Ossoa,b,
P. De Castro Manzanoa, T. Dorigoa, 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, M. Zanettia,b, P. Zottoa,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,15, 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,29, F. Ligabuea,c, T. Lomtadzea, E. Mancaa,c, G.
Mandorlia,c, A. Messineoa,b, F. Pallaa, A. Rizzia,b, A. Savoy-Navarroa,31, 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, 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, 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
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 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
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
Duran-Osuna, M. C., H. Castilla-Valdez, E. De La Cruz-Burelo, Ramirez-Sanchez,
G., I. Heredia-De La Cruz34, Rabadan-Trejo, R. I., R. Lopez-Fernandez, J.
Mejia Guisao, Reyes-Almanza, R, A. Sanchez-Hernandez Universidad
Iberoamericana, Mexico City, Mexico
S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita
Universidad Autonoma de Puebla, Puebla, Mexico
J. Eysermans, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad
Autónoma de San Luis Potosí, San Luis Potosí, Mexico
A. Morelos Pineda University of Auckland, Auckland, New Zealand
D. Krofcheck University of Canterbury, Christchurch, New Zealand
S. Bheesette, P.H. Butler National Centre for Physics, Quaid-I-Azam
University, Islamabad, Pakistan
A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, 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, 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, V. Alexakhin, P. Bunin, M. Gavrilenko, A. Golunov, I. Golutvin,
N. Gorbounov, I. Gorbunov, V. Karjavin, A. Lanev, A. Malakhov, V.
Matveev36,37, P. Moisenz, V. Palichik, V. Perelygin, M. Savina, S. Shmatov, V.
Smirnov, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St.
Petersburg), Russia
Y. Ivanov, V. Kim38, E. Kuznetsova39, P. Levchenko, V. Murzin, V. Oreshkin, I.
Smirnov, D. Sosnov, 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, V. Stolin, 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, S.V. Rusakov, 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.
Ershov, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, M.
Perfilov, V. Savrin, A. Snigirev Novosibirsk State University (NSU),
Novosibirsk, Russia
V. Blinov42, D. Shtol42, Y. Skovpen42 State Research Center of Russian
Federation, Institute for High Energy Physics of NRC &quot, Kurchatov
Institute&quot, , Protvino, Russia
I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, A. Godizov, 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. Adzic43, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic Centro de
Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid,
Spain
J. Alcaraz Maestre, A. Álvarez Fernández, I. Bachiller, M. Barrio Luna, M.
Cerrada, N. Colino, B. De La Cruz, A. Delgado Peris, C. Fernandez Bedoya, J.P.
Fernández Ramos, J. Flix, M.C. Fouz, O. Gonzalez Lopez, S. Goy Lopez, J.M.
Hernandez, M.I. Josa, D. Moran, A. Pérez-Calero Yzquierdo, J. Puerta Pelayo,
I. Redondo, L. Romero, M.S. Soares, A. Triossi Universidad Autónoma de Madrid,
Madrid, Spain
C. Albajar, J.F. de Trocóniz 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, 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.
Karacheban18, 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.
Milenovic44, 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.
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. 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 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. Amsler49, 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, Y.H. Chang, K.y. Cheng, T.H. Doan, Sh. Jain, R. Khurana, C.M.
Kuo, W. Lin, A. Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei,
Taiwan
P. Chang, Y. Chao, K.F. Chen, P.H. Chen, F. Fiori, W.-S. Hou, Y. Hsiung, Arun
Kumar, Y.F. Liu, R.-S. Lu, E. Paganis, A. Psallidas, A. Steen, J.f. Tsai
Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok,
Thailand
B. Asavapibhop, K. Kovitanggoon, G. Singh, N. Srimanobhas Çukurova University,
Physics Department, Science and Art Faculty, Adana, Turkey
M.N. Bakirci50, A. Bat, F. Boran, S. Cerci51, S. Damarseckin, Z.S. Demiroglu,
C. Dozen, E. Eskut, S. Girgis, G. Gokbulut, Y. Guler, I. Hos52, E.E. Kangal53,
O. Kara, U. Kiminsu, M. Oglakci, G. Onengut54, K. Ozdemir55, S. Ozturk50, A.
Polatoz, U.G. Tok, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East
Technical University, Physics Department, Ankara, Turkey
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, Y. Komurcu 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, L. Kreczko, D.M. Newbold61,
S. Paramesvaran, 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, J. Linacre, E. Olaiya, D.
Petyt, C.H. Shepherd-Themistocleous, A. Thea, I.R. Tomalin, T. Williams, W.J.
Womersley Imperial College, London, United Kingdom
G. Auzinger, R. Bainbridge, P. Bloch, J. Borg, S. Breeze, O. Buchmuller, A.
Bundock, S. Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies,
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Mastrolorenzo, T. Matsushita, J. Nash, A. Nikitenko6, V. Palladino, M.
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Shtipliyski, S. Summers, A. Tapper, K. Uchida, M. Vazquez Acosta63, T.
Virdee15, 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, L. Teodorescu, 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.
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G. Benelli, D. Cutts, M. Hadley, J. Hakala, U. Heintz, J.M. Hogan, K.H.M.
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Piperov, S. Sagir, R. Syarif, D. Yu University of California, Davis, Davis,
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R. Band, C. Brainerd, R. Breedon, D. Burns, M. Calderon De La Barca Sanchez,
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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, G. Karapostoli, 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, M. Masciovecchio, D.
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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, L. Gouskos, R. Heller, J. Incandela, A. Ovcharova, H. Qu,
J. Richman, D. Stuart, I. Suarez, J. Yoo California Institute of Technology,
Pasadena, USA
D. Anderson, A. Bornheim, J. Bunn, J.M. Lawhorn, H.B. Newman, T. Q. Nguyen, C.
Pena, M. Spiropulu, J.R. Vlimant, R. Wilkinson, 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
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J. Alexander, J. Chaves, J. Chu, S. Dittmer, K. Mcdermott, N. Mirman, J.R.
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Vaandering, C. Vernieri, M. Verzocchi, R. Vidal, M. Wang, H.A. Weber, A.
Whitbeck, W. Wu 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.
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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
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Zhang The University of Iowa, Iowa City, USA
B. Bilki65, W. Clarida, K. Dilsiz66, S. Durgut, R.P. Gandrajula, M.
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E. Tiras, J. Wetzel, K. Yi Johns Hopkins University, Baltimore, USA
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Kansas, Lawrence, USA
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Lawrence Livermore National Laboratory, Livermore, USA
F. Rebassoo, D. Wright University of Maryland, College Park, USA
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Cambridge, USA
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J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA
E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, F. Golf, 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
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Rappoccio, B. Roozbahani Northeastern University, Boston, USA
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Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, USA
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Columbus, USA
J. Alimena, L. Antonelli, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, A.
Hart, C. Hill, W. Ji, T.Y. Ling, B. Liu, W. Luo, B.L. Winer, H.W. Wulsin
Princeton University, Princeton, USA
S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, S. Higginbotham,
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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. Jones, A.W. Jung,
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T. Cheng, N. Parashar, J. Stupak Rice University, Houston, USA
Z. Chen, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Guilbaud, M. Kilpatrick, W.
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Verzetti The Rockefeller University, New York, USA
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Jersey, Piscataway, USA
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Sheffield, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker
University of Tennessee, Knoxville, USA
A.G. Delannoy, 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,
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Safonov, A. Tatarinov 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.
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Detroit, USA
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of Wisconsin - Madison, Madison, WI, USA
M. Brodski, J. Buchanan, C. Caillol, D. Carlsmith, 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, V. Rekovic, 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 IRFU; CEA; Université Paris-Saclay, Gif-sur-Yvette, France
3: Also at Universidade Estadual de Campinas, Campinas, Brazil
4: Also at Federal University of Rio Grande do Sul, Porto Alegre, Brazil
5: Also at 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 Zewail City of Science and Technology, Zewail, Egypt
9: Also at Fayoum University, El-Fayoum, Egypt
10: Now at British University in Egypt, Cairo, Egypt
11: Now at Helwan University, Cairo, Egypt
12: Also at Department of Physics; King Abdulaziz University, Jeddah, Saudi
Arabia
13: Also at Université de Haute Alsace, Mulhouse, France
14: Also at Skobeltsyn Institute of Nuclear Physics; Lomonosov Moscow State
University, Moscow, Russia
15: Also at CERN; European Organization for Nuclear Research, Geneva,
Switzerland
16: Also at RWTH Aachen University; III. Physikalisches Institut A, Aachen,
Germany
17: Also at University of Hamburg, Hamburg, Germany
18: Also at Brandenburg University of Technology, Cottbus, Germany
19: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group; Eötvös
Loránd University, Budapest, Hungary
20: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
21: Also at Institute of Physics; University of Debrecen, Debrecen, Hungary
22: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India
23: Also at Institute of Physics, Bhubaneswar, India
24: Also at University of Visva-Bharati, Santiniketan, India
25: Also at University of Ruhuna, Matara, Sri Lanka
26: Also at Isfahan University of Technology, Isfahan, Iran
27: Also at Yazd University, Yazd, Iran
28: Also at Plasma Physics Research Center; Science and Research Branch;
Islamic Azad University, Tehran, Iran
29: Also at Università degli Studi di Siena, Siena, Italy
30: Also at INFN Sezione di Milano-Bicocca; Università di Milano-Bicocca,
Milano, Italy
31: Also at Purdue University, West Lafayette, USA
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 Gaziosmanpasa University, Tokat, 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