B2G-17-006

$HeadURL:svn+ssh://svn.cern.ch/reps/tdr2/papers/B2G-17-006/trunk/B2G-17-006.tex$
$Id:B2G-17-006.tex4076332017-05-3113:21:24Zcgalloni$

B2G-17-006

# Search for heavy resonances decaying into two Higgs bosons or into a Higgs
boson and a or boson in proton-proton collisions at 13

###### Abstract

A search is presented for massive narrow resonances decaying either into two
Higgs bosons, or into a Higgs boson and a or boson. The decay channels
considered are $\PH\PH\to{\bbbar}\tau^{+}\tau^{-}$ and
$\mathrm{V}\PH\to{\qqbar}\tau^{+}\tau^{-}$, where denotes the Higgs boson, and
$\mathrm{V}$ denotes the or boson. This analysis is based on a data sample of
proton-proton collisions collected at a center-of-mass energy of 13by the CMS
Collaboration, corresponding to an integrated luminosity of 35.9. For the
-scale mass resonances considered, substructure techniques provide ways to
differentiate among the hadronization products from vector boson decays to
quarks, Higgs boson decays to bottom quarks, and quark- or gluon-induced jets.
Reconstruction techniques are used that have been specifically optimized to
select events in which the tau lepton pair is highly boosted. The observed
data are consistent with standard model expectations and upper limits are set
at 95% confidence level on the product of cross section and branching fraction
for resonance masses between 0.9 and 4.0. Exclusion limits are set in the
context of bulk radion and graviton models: spin-0 radion resonances are
excluded below a mass of 2.7at 95% confidence level. In the spin-1 heavy
vector triplet framework, mass-degenerate and resonances with dominant
couplings to the standard model gauge bosons are excluded below a mass of
2.8at 95% confidence level. These are the first limits for massive resonances
at the scale with these decay channels at $\sqrt{s}=13\TeV$.

##  0.1 Introduction

Heavy resonances that decay to $\PH\PH$, $\mathrm{V}\mathrm{V}$, or
$\mathrm{V}\PH$, where denotes the Higgs boson, and $\mathrm{V}$ denotes a or
boson, are motivated by theories beyond the standard model (SM) that address
the large difference between the electroweak and gravitational scales. These
heavy particles arise as Kaluza–Klein (KK) excitations of spin-0 radions [1,
2, 3], and as spin-2 gravitons predicted in models based on Randall–Sundrum
warped extra dimensions [4, 5], with the gravitons propagating in the entire
five-dimensional bulk [6, 7, 8]. Heavy spin-1 and particles that decay to
$\mathrm{V}\mathrm{V}$ and $\mathrm{V}\PH$ are also postulated in composite
Higgs models [9, 10, 11, 12], little Higgs models [13, 14], and in the
sequential SM (SSM) [15]. The models containing new spin-1 states are
generalized in the heavy vector triplet (HVT) framework [16]. All of the new
hypothetical particles with spins of 0, 1, or 2 can be produced at the CERN
LHC, via the processes depicted in the Feynman diagrams of Fig. 1.

Figure 1: Feynman diagrams for the production of a spin-0 radion or a spin-2
graviton X that decays to two Higgs bosons (left), and the production of a
heavy vector boson $\mathrm{V}^{\prime}$ (or ) that decays to a vector boson
and a Higgs boson (right).

The bulk graviton model has two free parameters: the mass of the first KK
excitation of the spin-2 boson, denoted as the KK bulk graviton, and the ratio
$\tilde{k}\equiv k/\overline{M}_{\mathrm{Pl}}$, where $k$ is the unknown
curvature scale of the extra dimension and $\overline{M}_{\mathrm{Pl}}\equiv
M_{\mathrm{Pl}}/\sqrt{8\pi}$ is the reduced Planck mass. Searches for radions
in this model can be described in terms of the radion mass and the ultraviolet
cutoff of the theory $\Lambda_{\mathrm{R}}$ [17]. The HVT model is formulated
in terms of four parameters: the mass of the new vector bosons, their coupling
coefficient to fermions $c_{\mathrm{F}}$, their coupling coefficient to the
Higgs boson and longitudinally-polarized SM vector bosons $c_{\PH}$, and the
strength of the new vector boson interaction $g_{\mathrm{V}}$. In the HVT
framework two scenarios are considered and henceforth referred to as model A
and model B, depending on the couplings of the new physics resonance to the SM
particles. In model A ($g_{\mathrm{V}}=1$, $c_{\PH}=-0.556$,
$c_{\mathrm{F}}=-1.316$), the coupling strengths to the SM bosons and fermions
are comparable and the new particles decay primarily to fermions. In model B
($g_{\mathrm{V}}=3$, $c_{\PH}=-0.976$, $c_{\mathrm{F}}=1.024$), the coupling
to the SM fermions are small, and the branching fraction of the new resonance
to SM bosons is nearly 100% [16]. Searches for diboson resonances have
previously been performed in several final states, placing lower limits on the
masses of such resonances above the scale [18, 19, 20, 21, 22, 23, 24, 25, 26,
27, 28, 29, 30, 31, 32, 33].

This paper presents a search for resonances with masses above 900decaying into
or $\mathrm{V}$. The final states analyzed are $\PH\PH\to\bbbar\TT$ and
$\mathrm{V}\PH\to\qqbar\TT$. Events are classified as “semileptonic”, denoted
as $\ell\tauh$, if one lepton decays into a lighter lepton ($\ell$), denoting
either a muon or an electron, and two neutrinos, and the other decays
hadronically ($\tauh$) into hadrons and a neutrino. Events are categorized as
“fully-hadronic”, denoted as $\tauh\tauh$, if both leptons decay hadronically.
The analysis aims to reconstruct the diboson decay products in order to search
for a narrow local enhancement in the diboson invariant mass spectrum with a
width insignificant with respect to the experimental resolution. This search
complements and significantly extends the reach of the CMS search for
$\PZ\PH\to\qqbar\TT$ resonances with data collected at $\sqrt{s}=8\TeV$ [34],
by using a larger data sample collected at $\sqrt{s}=13\TeV$, a more complex
categorization of the final states, and an increased number of signal models.
Resonances of masses below the scale have been excluded by other searches in
similar final states [35, 36].

Since the resonances under study have masses of the order of a few , the
bosons resulting from their decays have transverse momenta () of at least
several hundred GeV. As a consequence, the final decay products are collimated
such that the hadronically decaying bosons cannot be resolved using standard
jet algorithms. Dedicated techniques, called $\mathrm{V}$ tagging and tagging,
are applied to exploit the substructure of these large-cone jets to resolve
the hadronically decaying vector and Higgs bosons.

For the Higgs boson decaying to a pair of leptons, the decay products are also
close in angular separation. The lepton reconstruction and identification
techniques described in Ref. [34] are therefore adopted to achieve optimal
signal significance for this particular event topology.

##  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 measured in gas-ionization detectors
embedded in the steel flux-return yoke outside the solenoid. The CMS two-level
trigger system [37] reduces the event rate from the bunch crossing rate of
40MHz down to around 1kHz for data storage.

A more detailed description of the CMS detector, together with a definition of
the coordinate system used and the kinematic variables, can be found in Ref.
[38].

##  0.3 Data sample and simulation

The data sample analyzed in this search corresponds to an integrated
luminosity of 35.9, collected in 13proton-proton collisions with the CMS
detector during the 2016 data taking period. The signal processes
$\Pp\Pp\to\mathrm{X}\to\mathrm{V}\PH\to\qqbar\TT$ and
$\Pp\Pp\to\mathrm{X}\to\PH\PH\to\bbbar\TT$ are simulated at leading order (LO)
using the v2.2.2 [39] Monte Carlo (MC) event generator, for resonance masses
between 900 and 4000, where the Higgs boson is forced to decay to $\tau$ pairs
and the other boson to a pair of quarks. The signal processes where
$\Pp\Pp\to\mathrm{X}\to\PH\PH\to\bbbar\mathrm{V}\mathrm{V}$ and
$\Pp\Pp\to\mathrm{X}\to\mathrm{V}\PH\to\qqbar\mathrm{V}\mathrm{V}$ are also
considered, in which $\mathrm{V}\mathrm{V}\to 2\ell 2\nu$ or $2\tau 2\nu$, as
they can yield final states similar to those of the primary signal process.
The natural width of the resonance is assumed to be smaller than the
experimental resolution of its reconstructed mass, as consistent with the
benchmark radion, graviton and HVT models.

The SM background processes are generated using MC simulation. The
$\PZ/\gamma^{*}$+jets events and the +jets events are simulated at LO with the
generator. The v2 generator is used to simulate and single top quark
production at next-to-leading order [40, 41, 42, 43]. The LO 8.205 [44]
generator is used for SM diboson ($\PW\PW$, $\PW\PZ$, or $\PZ\PZ$) and
multijet events. For all signal and background samples, showering and
hadronization are modeled using , lepton decays are described using tauola
1.1.5 [45], and the response of the detector is simulated using [46].
Additional collisions in the same or adjacent bunch crossings (pileup) are
superimposed onto the hard scattering processes, with the pileup vertex
multiplicity distribution adjusted to match that of data.

##  0.4 Event reconstruction

The particle flow (PF) event algorithm [47] reconstructs and identifies each
individual particle through an optimized combination of information from the
various elements of the CMS detector. The energy of each electron is
determined from the electron momentum 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
energies of muons are obtained from the curvature of the corresponding tracks.
The energies of charged hadrons are 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 energies of neutral
hadrons are obtained from the corresponding corrected ECAL and HCAL energies.

The identified particles are clustered into jets using the anti-algorithm
[48], implemented in the package [49]. Two distance parameters are used in the
analysis, 0.4 and 0.8, yielding jet collections referred to as AK4 and AK8
jets, respectively. The AK4 jets are used primarily to reject or select events
with top quarks, while the larger AK8 jets are used to identify and contain
hadronically decaying , , and Higgs boson candidates. The charged-hadron
subtraction (CHS) algorithm for mitigating pileup [47] discards charged
particles not originating from the primary vertex (PV). The PV is defined as
the vertex with the largest $\pt^{2}$ sum of the physics objects. Here, the
physics objects are the AK4 jets, and the associated missing transverse
momentum, which is taken as the negative vector sum of the of the jets. The
residual contamination from neutral pileup particles is estimated to be
proportional to the event energy density and the jet area, and is removed from
the jet energy calculation. The jet momentum is determined as the vectorial
sum of all particle momenta in the jet, and is found from simulation to be
within 5 to 10% of the true momentum over the entire spectrum and detector
acceptance. Jet energy corrections are obtained from simulation, and are
confirmed with in situ measurements of the energy balance in dijet, multijet,
$\gamma$+jets, and leptonically decaying +jets events [50]. Additional
selection criteria are applied to each event to remove spurious jet-like
features originating from isolated noise patterns in certain HCAL regions
[51]. The AK4 and AK8 jets must have $\pt>20$ and $\pt>200\GeV$, respectively,
and $\abs{\eta}<2.4$ to be considered in the subsequent steps of the analysis.

To determine the jet mass and the substructure variables used in the
identification of the hadronic decays of bosons, the so-called pileup per
particle identification (PUPPI) algorithm [52] is applied to AK8 jets, instead
of the CHS algorithm, to retain better stability of the substructure variables
in events with a large amount of pileup. The PUPPI algorithm uses the local
distribution of particles, event-pileup properties, and tracking information
to compute a weight describing the likelihood for each particle to originate
from a pileup interaction. The weights are used to rescale the particle four-
momenta, superseding the need for further jet-based corrections. These
particles are subsequently clustered with the anti-algorithm with a distance
parameter of 0.8, and then matched to the CHS AK8 jets described above used
for the kinematic selections.

Subsequently, the soft-drop algorithm [53, 54], designed to remove
contributions from soft radiation, is applied to the AK8 PUPPI jets. The soft-
drop jet mass $m_{\mathrm{j}}$ is defined as the invariant mass associated
with the four-momentum of the soft-drop jet. Dedicated mass corrections,
derived from data in a region enriched with events containing merged hadronic
decays, are applied to $m_{\mathrm{j}}$ to remove any dependence on jet , and
to match the jet mass and resolution observed in data. After the application
of these corrections, the () jet mass resolution is measured to be 10% in the
jet range considered.

The two-prong hadronic decays of and boson candidates are used to discriminate
against jets initiated from single quarks and gluons. The constituents of the
jet are clustered again using the algorithm [48], and the procedure is stopped
when N subjets are obtained. Subsequently, the N-subjettiness as defined in
Ref. [55] is calculated on the PUPPI-corrected jet for the one and two-subjet
hypotheses as

$\tau_{\mathrm{N}}=\frac{1}{d_{0}}\sum_{k}p_{\text{T},k}\min(\Delta
R_{1,k},\Delta R_{2,k},\dots,\Delta R_{\mathrm{N},k}).$ (1)

The normalization factor is given by the factor
$d_{0}=\sum_{k}p_{\text{T},k}\,R_{0}$, where $R_{0}$ is the radius of the
original jet, the index $k$ increments over the jet constituents, and $\Delta
R_{J,k}=\sqrt{\smash[b]{(\Delta\eta_{J,k})^{2}+(\Delta\phi_{J,k})^{2}}}$ are
the angular distances in terms of the differences in $\eta$ and azimuth
($\phi$) calculated between the $k$th jet constituent and the axes of the
$J$th subjet. Small values of the ratio of 2-subjettiness to 1-subjettiness,
$\tau_{21}=\tau_{2}/\tau_{1}$, correspond to a high compatibility with the
hypothesis that the jet is produced by two partons from the decay of a massive
object, rather than arising from a single parton. The efficiency of the
$\tau_{21}$ selection is measured from data in a -enriched sample [56].

Jets originating from the dominant $\bbbar$ decays of Higgs bosons are likely
to have two displaced vertices because of the long lifetime and large mass of
the quarks. Following the procedure above, jet clustering using the anti-
algorithm is halted when two subjets are identified. The inclusive, combined
secondary-vertex tagging algorithm [57] is applied to the two subjets, which
are considered as -tagged if they pass a working point that provides a
misidentification rate of $\approx$10% while maintaining an $85\%$ efficiency.
To remove backgrounds containing top quark decays, events with AK4 jets that
do not overlap with the AK8 jet are subjected to a veto based on the same
tagging algorithm, but with a working point corresponding to an efficiency of
$\approx$70% for identifying hadrons and a $\approx$1% misidentification rate.
The ratio of the tagging efficiency determined from data and simulation is
used as a scale factor to correct the simulated events.

A dedicated algorithm is used to reconstruct Higgs bosons decaying to one or
two $\tauh$ candidates [58]. The procedure begins by using the
Cambridge–Aachen algorithm [59] with a distance parameter of 0.8 to identify
jets with a large cone size, called CA8 jets. For each CA8 jet with
$\pt>100\GeV$, the last step of the clustering is retracted, obtaining two
subjets. If these subjets are found to have $\pt>10\GeV$ and satisfy the mass
drop-condition, which requires
$\mathrm{max}(m_{\mathrm{subjet1}},m_{\mathrm{subjet2}})/m_{\mathrm{CA8jet}}<2/3$,
the two subjets are used as seeds in the standard lepton reconstruction and
the “hadron-plus-strips” algorithm [60] is applied to them to identify $\tauh$
candidates. If the and mass drop conditions are not met, the unclustering and
identification procedures are repeated (iteratively) for the most energetic
subjet. The $\tauh$ candidates selected through the hadron-plus-strips
algorithm are then required to have $\abs{\eta}<2.3$ and $\pt>20\GeV$, and to
satisfy a multivariate-discriminator threshold, obtained using a boosted
decision tree technique [61]. This algorithm is trained to discriminate
between genuine $\tauh$ and generic jets, using variables related to energy
deposits and track impact parameters that are correlated with the lepton
lifetime. If no $\tauh$ candidates are identified with this method, then the
procedure is repeated using AK4 jets as seeds, with similar selection
requirements. The $\tauh$ candidate of highest is required to satisfy an
isolation requirement that corresponds to a 50–60% efficiency in the
considered topology. If two $\tauh$ candidates are identified, as in the
$\tauh\tauh$ channel, the isolation requirement on the $\tauh$ of second
highest is relaxed to achieve a 70–80% efficiency. The probability to
misidentify a CA8 jet as an $\PH\to\TT$ decay is below 0.1%, after these
selection criteria.

Electrons are reconstructed in the region $\abs{\eta}<2.5$ by matching energy
deposits in the ECAL with tracks reconstructed in the tracker [62]. Electron
identification is based on the distribution of energy deposited along the
electron trajectory and the direction and momentum of the track in the inner
tracker. Additional requirements are applied to remove electrons produced
through photon conversions. Electrons are also required to be isolated from
other particles in the detector, by imposing an upper threshold on the
isolation parameter. The electron isolation parameter is defined as the
magnitude of the $\pt$ sum of all the PF candidates (excluding the electron)
within $\Delta R<0.3$ around the electron direction, after the contributions
from pileup and particles associated with reconstructed $\tauh$ candidates
within the isolation cone are removed.

Muons are reconstructed within the acceptance of the CMS muon system,
$\abs{\eta}<2.4$, using information from both the muon spectrometer and the
silicon tracker [63]. Muon candidates are identified based on the
compatibility of tracks reconstructed in the silicon tracker with tracks
reconstructed from a combination of hits in both the tracker and the muon
detector. In addition, the trajectory is required to be compatible with
originating from the primary vertex, and to have a sufficient number of hits
in the tracker and muon systems. Muons are required to be isolated by imposing
a limit on the magnitude of the $\pt$ sum of all the PF candidates (excluding
the muon) within $\Delta R<0.4$ around the muon direction, after the
contributions particles associated with reconstructed $\tauh$ candidates
within the isolation cone are removed.

The missing transverse momentum vector $\ptvecmiss$ is defined as the negative
vectorial sum of the momenta of all PF candidates associated with the primary
vertex projected onto the plane perpendicular to the beam direction. The
missing transverse momentum $\ptmiss$ is defined as the magnitude of
$\ptvecmiss$. The observable is defined as the magnitude of the vectorial sum
of all AK4 jets with $\pt>30\GeV$ and $\abs{\eta}<3.0$.

##  0.5 Event selection

Events are selected using a set of triggers that require or larger than 90, in
combination with additional trigger requirements, such as the presence of a
jet with $\pt>80\GeV$. The efficiency of the trigger for events subsequently
satisfying the offline event selection, measured in an independent sample of
events selected with muon triggers, is verified to be $>95$%, with an
uncertainty of 2%.

All events are required to contain one Higgs boson candidate decaying to
$\ell\tauh$ or $\tauh\tauh$. The other boson candidate is reconstructed as a
jet, using the same kinematic criteria in all categories. Its soft-drop jet
mass must be in the interval of 65–135. If the mass is in the range 65–85, the
candidate is classified as a boson, if it is in the range 85–105it is
classified as a boson, and if it is the range 105–135it is considered to be a
Higgs boson. To discriminate against backgrounds, the jets are required to
have small values of $\tau_{21}$, and events are divided into categories of
high-purity (HP) if $\tau_{21}<0.4$, and low-purity (LP) if
$0.4<\tau_{21}<0.75$. A jet is $\mathrm{V}$ tagged if it fulfills the soft-
drop jet mass and $\tau_{21}$ requirements. The normalization scale factors
$0.99\pm 0.06$ for the HP category and $0.96\pm 0.11$ for the LP category [56]
are applied to simulated events with genuine hadronic boson decays. Higgs
boson jet candidates are classified according to the number of subjets (1 or
2) that pass the tagging selection. Subjet tagging is not used for jets
compatible with or candidates and no N-subjettiness requirement is applied to
the Higgs boson candidate jet. If neither the N-subjettiness nor the tagging
requirements are satisfied, the event is discarded.

Events are divided into categories depending on the number of identified
$\tauh$ candidates (1 or 2), and on the classification of the large jet cone,
either HP or LP in $\tau_{21}$, or either 1 or 2 -tagged subjets.

Since the undetected neutrinos carry a significant fraction of the momentum in
the system, signal events are expected to have a large , thereby justifying
the use of triggers that require large or . A stringent offline requirement of
greater than 200is applied to the reconstructed , to ensure a stable trigger
efficiency and to suppress the background contribution from multijet events.
Events with top quark pairs or single top quarks are suppressed by removing
events in which any AK4 jet not overlapping with the AK8 jet is -tagged.

Several selection requirements are applied to remove SM backgrounds, such as
meson and baryon resonances, +jets, +jets and and single top quark production.
The angular distance $\Delta R_{\Pgt\Pgt}$ should be smaller than 1.5, in
order to reject +jets events in which a jet misidentified as a lepton is
typically spatially well-separated from the genuine lepton. To further
increase the signal purity, the di-tau mass, as estimated from the SVfit
procedure [64, 65, 66], should be between 50 and 150. The SVfit algorithm,
based on a likelihood approach, estimates the di-$\tau$ system mass using the
measured momenta of the visible decay products of both $\tau$ leptons, the
reconstructed , and the resolution.

Finally, the resonance candidate mass $m_{\text{X}}$, defined as the invariant
mass of the $\PH\to\tau\tau$ candidate and the hadronically decaying boson
jet, is required to be larger than 750in order to ensure full trigger and
reconstruction efficiencies.

After these selection requirements, the selection efficiency of a radion
signal in the 1 and 2 tag categories is 1–6% in the $\tauh\tauh$ channel, and
3–10% in the $\ell\tauh$ channel, for low and high resonance masses,
respectively. The efficiencies for a signal passing the $\mathrm{V}$-tagging
selection are 2–9% and 8–19% in the $\tauh\tauh$ and $\ell\tauh$ channels,
respectively. Events in which $\PH\to\mathrm{V}\mathrm{V}$ are found
contribute up to an additional 20–30% of the total signal yield in the
$\ell\tauh$ channels, and less than 10% in the $\tauh\tauh$ channels.

##  0.6 Background estimation

The main sources of background originate from top quark pair production and
from the production of a vector boson in association with jets (+jets and
+jets), while minor contributions arise from single top quark, diboson, and
multijet production. These background contributions are split into either and
single top quark production (, ), or into $\mathrm{V}\text{+jets}$ production.
The latter includes +jets and +jets, multijet, and SM diboson production.

The shape of the distribution of the top quark pair and single top quark
background is determined from simulation, while the normalization is
determined from data through dedicated control regions that are enriched in
top quark events. Control regions having a purity larger than 80% for top
quarks are selected by inverting the tag veto on the AK4 jets and tightening
the tagging criteria. Events are separated according to the requirements of
large-cone jet identification. Data are found to be well-described by
simulations in terms of the jet and dijet resonance-mass distributions.
Multiplicative scale factors are used to correct for the difference in
normalization of data and simulation in the control regions, after subtracting
the other background contributions. Scale factors obtained in control regions
of $\ell\tauh$ events are applied also to the $\tauh\tauh$ channels, where
there are fewer events. The normalization of top quark production processes in
each region is also corrected using the scale factors reported in Table 0.6.

Normalization scale factors for top quark production for different event
categories, depending on the $\mathrm{V}$ tagging and tagging requirement
applied. Uncertainties are due to the limited number of events in the control
regions and the uncertainty in the tagging efficiency.

Channel |  $\tau_{21}$ LP |  $\tau_{21}$ HP | 1 -tagged subjet | 2 -tagged subjets
---|---|---|---|---
$\ell\tauh$ | 0.96 $\pm$ 0.04 | 1.06 $\pm$ 0.06 | 1.00 $\pm$ 0.06 | 1.11 $\pm$ 0.15

The estimated contribution from $\mathrm{V}\text{+jets}$ backgrounds is based
on data, in regions defined by applying the complete signal selection apart
from the jet-mass requirements. Data are divided into the $\tauh\tauh$ and the
$\ell\tauh$ channels. Two jet-mass sidebands (SB) are defined with jet masses
in the range of 30–65for the low sideband (LSB), or above 135for the high
sideband (HSB), and used to predict the background contribution in the signal
region (SR). Analytic functions are fitted to the simulated distributions of
the jet mass, separately for $\mathrm{V}\text{+jets}$ and for top quark
processes. The former is modeled by a third-order polynomial or an exponential
convoluted with an error function, and the latter with a sum of one or two
Gaussian functions to model the and top quark distributions. The background
model, composed of the sum of the functions modeling the two backgrounds, is
fitted to the data in the jet mass sidebands. In this unbinned likelihood fit,
only the $\mathrm{V}\text{+jets}$ distribution shape and normalization
parameters are left free to float. The number of expected events in the SR is
then obtained by integrating the background components in the jet mass window
compatible with the signal hypothesis. An indicative fit is shown in Fig. 2
(left) for the HP $\tau_{21}$ category of $\ell\tauh$ events. The procedure is
repeated with an alternative function used for modeling the
$\mathrm{V}\text{+jets}$ jet mass, with the observed difference in the
normalization taken to be the associated systematic uncertainty. The expected
number of background events in each signal region is reported in Table 0.6.

The distribution of the $\mathrm{V}\text{+jets}$ background resonance mass
($m_{\text{X}}$) in the SR is estimated from the SBs through a transfer
function $\alpha(m_{\text{X}})$, which accounts for the small kinematical
differences and the correlations involved in the interpolation from the SBs to
the SR, and does not depend on the systematic uncertainties that affect the
simulated $\mathrm{V}\text{+jets}$ spectra, since they cancel out in the
ratio. The $\alpha$ function is determined from simulations as

$\alpha(m_{\mathrm{X}})=\frac{\mathrm{N}^{\mathrm{MC},\mathrm{V}\text{+jets}}_{\mathrm{SR}}(m_{\text{X}})}{\mathrm{N}^{\mathrm{MC},\mathrm{V}\text{+jets}}_{\mathrm{SB}}(m_{\text{X}})},$
(2)

where
$\mathrm{N}^{\mathrm{MC},\mathrm{V}\text{+jets}}_{\mathrm{SR}}(m_{\text{X}})$
and
$\mathrm{N}^{\mathrm{MC},\mathrm{V}\text{+jets}}_{\mathrm{SB}}(m_{\mathrm{X}})$
are analytic functions fitted to the simulated $m_{\mathrm{X}}$ distributions
in the SR and SB regions, respectively. Depending on the category, the
function can either be an exponential using one or two parameters, or a power
law with one parameter. The distribution of the $\mathrm{V}\text{+jets}$
background in the SR is then estimated by fitting an analytic function to data
in the SBs, after subtracting the top quark background estimated from
simulation, and multiplying by the $\alpha(m_{\mathrm{X}})$ transfer function.
The normalization of the $\mathrm{V}\text{+jets}$ is determined from the fit
to the jet mass, as reported in Table 0.6. The resonance mass distribution is
shown in Fig. 2 (right) for $\ell\tauh$ events in the HP category.

Figure 2: Soft-drop jet mass distribution in data in the HP $\ell\tauh$
category, together with the background prediction (fitted to the data as
explained in the text)(left). Spectrum of the resonance mass in data events in
the SBs (right) used for the estimation of the $\mathrm{V}\text{+jets}$
distribution in the SR. The lower panels depict the pulls in each bin,
$(\mathrm{N}_{\mathrm{data}}-\mathrm{N}_{\mathrm{bkg}})/\sigma$, where
$\sigma$ is the statistical uncertainty in data, as given by the Garwood
interval [67].

Predicted number of background events and the observed number in the signal
region, for all event categories. The regions denoted by , and are intervals
in the jet soft-drop mass distribution that range from 65 to 85, from 85 to
105, and from 105 to 135, respectively. Separate sources of uncertainty in the
expected number are reported as the statistical uncertainty in the
$\mathrm{V}\text{+jets}$ contribution from the fitting procedure (fit), the
difference between the nominal and alternative function form chosen for the
fit (alt), and the uncertainty in the background from top quarks from the fit
to the simulated jet mass spectrum.  Category $\mathrm{V}\text{+jets}$ ($\pm$
fit)($\pm$ alt) ,  Total exp. events Data region HP $\ell\tauh$ $38\pm 7\pm
12$ $37.8\pm 0.6$ $76\pm 14$ $78$ $\tauh\tauh$ $13.0\pm 3.2\pm 0.2$ $16.0\pm
1.8$ $29.0\pm 3.7$ $45$ LP $\ell\tauh$ $105.3\pm 6.8\pm 9.0$ $34.2\pm 0.9$
$140\pm 11$ $120$ $\tauh\tauh$ $27.0\pm 3.3\pm 3.0$ $12.3\pm 0.6$ $39.3\pm
4.5$ $37$ region HP $\ell\tauh$ $39.9\pm 6.1\pm 7.9$ $42.4\pm 1.0$ $82\pm 10$
$82$ $\tauh\tauh$ $13.7\pm 3.0\pm 2.5$ $18.0\pm 1.8$ $31.6\pm 4.3$ $33$ LP
$\ell\tauh$ $73.5\pm 4.8\pm 6.1$ $29.1\pm 1.9$ $102.6\pm 8.0$ $92$
$\tauh\tauh$ $19.1\pm 2.3\pm 2.5$ $10.4\pm 0.8$ $29.5\pm 3.5$ $33$ region 2
tag $\ell\tauh$ $2.4\pm 0.9\pm 0.4$ $6.9\pm 0.6$ $9.2\pm 1.2$ $10$
$\tauh\tauh$ $1.1\pm 0.6\pm 0.1$ $3.8\pm 1.8$ $4.9\pm 1.9$ $5$ 1 tag
$\ell\tauh$ $29.3\pm 3.5\pm 6.6$ $37.3\pm 1.2$ $66.6\pm 7.5$ $56$ $\tauh\tauh$
$11.5\pm 2.2\pm 2.6$ $15.4\pm 1.7$ $26.9\pm 3.8$ $23$

The overall background in the SR is then expected to be:

$\mathrm{N}_{\mathrm{SR}}^{\mathrm{data}}(m_{\mathrm{X}})=\alpha(m_{\mathrm{X}})[\mathrm{N}_{\mathrm{SB}}^{\mathrm{data}}-\mathrm{N}_{\mathrm{SB}}^{\ttbar,\cPqt}](m_{\mathrm{X}})+\mathrm{N}_{\mathrm{SR}}^{\ttbar,\cPqt}(m_{\mathrm{X}}),$
(3)

where $\mathrm{N}_{\mathrm{SB}}^{\ttbar,\cPqt}$ and
$\mathrm{N}_{\mathrm{SR}}^{\ttbar,\cPqt}$ are the distributions for the top
quark process in the SB and SR, respectively. The shape and the normalization
of the distribution are fixed from simulation, with the latter corrected using
the appropriate scale factors in Table 0.6. The data in the SR and the
background predictions before and after the fit in the SR are shown in Figs. 3
and 4.

Figure 3: Data and expected backgrounds in the $\ell\tauh$ channel. The mass
window is shown in the HP (upper left) and LP (upper right) categories, the
mass window for the HP (middle left) and LP (middle right) categories, and the
mass window for the two -tagged subjet (lower left) and one -tagged subjet
(lower right) categories. The lower panels depict the pulls in each bin,
$(\mathrm{N}_{\mathrm{data}}-\mathrm{N}_{\mathrm{bkg}})/\sigma$, where
$\sigma$ is the statistical uncertainty in data, as given by the Garwood
interval [67], and provide estimates of the goodness of fit. Signal
contributions are shown, assuming benchmark HVT model B for the
$\mathrm{V}^{\prime}$ and $\Lambda_{\mathrm{R}}=1$ for the radion.

Figure 4: Data and expected backgrounds in the $\tauh\tauh$ channel. The mass
window is shown in the HP (upper left) and LP (upper right) categories, the
mass window for the HP (middle left) and LP (middle right) categories, and the
mass window for the two -tagged subjet (lower left) and one -tagged subjet
(lower right) categories. The lower panels depict the pulls in each bin,
$(\mathrm{N}_{\mathrm{data}}-\mathrm{N}_{\mathrm{bkg}})/\sigma$, where
$\sigma$ is the statistical uncertainty in data, as given by the Garwood
interval [67], and provide estimates of the goodness of fit. Signal
contributions are shown, assuming benchmark HVT model B for the
$\mathrm{V}^{\prime}$ and $\Lambda_{\mathrm{R}}=1$ for the radion.

##  0.7 Systematic uncertainties

Systematic uncertainties, resulting from experimental and theory sources, may
affect both the normalization and shape of the signal and background
distributions.

The principal background is $\mathrm{V}\text{+jets}$, and its modeling
represents the largest uncertainty in the analysis. The systematic uncertainty
in the $\mathrm{V}\text{+jets}$ background is dominated by the statistical
uncertainty associated with the number of events in the jet mass distribution
SBs in data and simulation. An additional uncertainty is related to the choice
of model used for the jet mass in the $\mathrm{V}\text{+jets}$ background. It
is evaluated from the differences in the expected background yields obtained
when using the alternative fitting functions. For the top quark processes,
uncertainties from normalization and shape in the parametrization are
propagated to the final background estimation. The single top quark and top
quark pair production normalization uncertainty arises predominantly from the
limited number of events in the CRs.

The uncertainties in the shape of the $\mathrm{V}\text{+jets}$ distribution
are estimated from the covariance matrix of the fit to $m_{\text{X}}$ in the
sidebands and the uncertainties in the $\alpha(m_{\text{X}})$ ratio, which
depend on the number of events in data and simulation, respectively.

The uncertainties in the trigger efficiency, and in the electron and muon
reconstruction, identification, and isolation efficiencies are obtained by
varying the corresponding scale factors by their uncertainty, and each is
found to be 1–2% [62, 63]. For the $\tauh$ reconstruction and identification,
the uncertainties vary between 6 and 8% and between 10 and 13%, depending on
the resonance mass, in the $\ell\tauh$ and the $\tauh\tauh$ channels,
respectively [60]. A separate uncertainty due to the extrapolation of the
reconstruction and identification of $\tauh$ leptons at large has an impact on
the signal normalization of 18% in the $\ell\tauh$, and 30% in the
$\tauh\tauh$ channels, for a 4signal hypothesis. This uncertainty is
responsible for an increase of 1% in the width of the signal distribution.

Jet energy scale and resolution uncertainties affect both the selection
efficiencies and the shape of distributions. The corrections to the jet mass
scale and resolution are also taken into account, and result in a variation of
1–8% in the expected number of signal events. The jet energy scale uncertainty
accounts for a variation in signal efficiency of 1–3%, while the variation in
the jet energy resolution has an impact of 1–2%. The effect on the mass
distribution is at the level of 1–2% for the mean and the width of the signal
distribution. Event migrations between the mass windows due to the effect of
jet mass scale and resolution variations are estimated to be between 2 and
15%, depending on the signal and the vector boson mass region.

Scale factors for $\mathrm{V}$ tagging and tagging represent the largest
source of normalization uncertainty for the signal. Uncertainties in
normalization correspond to 6 and 11% in the HP and LP categories,
respectively. An additional uncertainty from the extrapolation of the tagging
from the scale to larger values of jet is estimated using an alternative [68]
shower model, and varies from 2 to 18% for 0.9–4mass hypotheses and the two
$\mathrm{V}$ tag categories. In addition, the contribution to the signal
normalization uncertainty from the tagging uncertainty varies between 3 (4)%
to 7 (5)% for the 2 (1) -tagged subjet categories.

The lepton energy-scale uncertainties affect both the selection efficiencies
and their distribution shapes. The effect on the signal yield amounts to 1% in
the $\ell\tauh$ channel. In the $\tauh\tauh$ channel, the effect decreases
from 5% for a resonance with mass of 0.9to 3% for a mass of 4.0.

Normalization uncertainties from the choice of the parton distribution
function (PDF) grow larger with higher resonance mass, and are larger for
gluon-initiated processes than for quark-initiated processes. For and
production, which are sensitive to quark PDFs, effects range from 6 to 37%,
while radion and graviton production depend on gluon PDFs, and result in a
variation of 10 to 64% in the number of expected signal events. Uncertainties
of similar magnitude arise from factor of two variations in the factorization
and renormalization scales, resulting in 3 to 13% variations for and , and 10
to 19% for radion and graviton production. While normalization uncertainties
are not considered in setting limits on production, effects on signal
acceptance are propagated to the final fit, amounting to 0.5–2% for PDF
uncertainties, depending on resonance mass.

Other systematic uncertainties affecting the normalization of signal and minor
backgrounds considered in the analysis include pileup contributions (0.5%) and
integrated luminosity (2.5%) [69]. A list of the main systematic uncertainties
is given in Table 1.

Table 1: Summary of systematic uncertainties for the background and signal events. Uncertainties marked with “shape” are propagated also to the shape of the distributions, and those marked with $\dagger$ are not included in the limit bands, but instead reported in the theory band. The dash symbol is reported where the uncertainty is not applicable to a certain signal or background. The symbols $\cPq\cPq$’ and $\Pg\Pg$ refer to quark-initiated and gluon-initiated processes, respectively. | $\mathrm{V}\text{+jets}$ |  ,  | Signal
---|---|---|---
$\alpha$-function | shape |  |
Bkg. normalization | 11–60% | 2–38% |
Top quark scale factors |  | 5–14% |
Jet energy scale |  |  | shape
Jet energy resolution |  |  | shape
Jet mass scale |  |  | 1%
Jet mass resolution |  |  | 8%
$\mathrm{V}$ tagging |  |  | 6% (HP)–11% (LP)
$\mathrm{V}$ tagging extrapol. |  |  | 8–18% (HP), 2–8% (LP)
tagging |  |  | 3–7% (1b), 4–5% (2b)
-tagged jet veto |  | 3% | 1%
Trigger |  |  | 2%
Lepton identification, isolation |  |  | 2%
$\tau$ lepton identification |  |  | 6–8% ($\ell\tauh$), 10–13% ($\tauh\tauh$)
$\tau$ lepton identification extrapol. |  |  | 0.5–18% ($\ell\tauh$), 0.2–30% ($\tauh\tauh$), shape
$\tau$ lepton energy scale |  |  | 1% ($\ell\tauh$), 3–5% ($\tauh\tauh$), shape
Pileup |  |  | 0.5%
Renorm./fact. scales$\dagger$ |  |  | 2.5–12.5%($\cPq\cPq$’), 10–19%($\Pg\Pg$)
PDF yield$\dagger$ |  |  | 6–37%($\cPq\cPq$’), 10–64%($\Pg\Pg$)
PDF acceptance |  |  | 0.5–2%
Integrated luminosity |  |  | 2.5%

##  0.8 Results

Results are obtained from a combined fit of the signal and background to the
resonance mass distribution in data, based on a profile likelihood, where the
systematic uncertainties are considered as “nuisance” parameters [70, 71]. The
background-only hypothesis is tested against the signal hypothesis
simultaneously in the different categories. No evidence of significant
deviations from the background expectation is found. Assuming that the signals
have widths that are negligible relative to the resonance-mass resolution of
approximately 7%, the 95% confidence level () upper limits are determined for
the signals using the asymptotic frequentist method [72, 70, 73]. Limits are
obtained on the product of the cross section and branching fraction for a
heavy resonance (X) that decays to $\PH\PH$, $\PW\PH$, or $\PZ\PH$, as
reported in Figs. 5–6.

Resonance spins of 0 and 2 are considered for the $\PH\PH$ final state, while
the resonance spin is assumed to be 1 for the $\PW\PH$ and $\PZ\PH$ final
states. For the $\PW\PH$ and $\PZ\PH$ final states, the and boson mass regions
are combined because there are contributions from both signals to the two mass
regions. Because of its higher signal selection efficiency, typical
sensitivities are better for the $\ell\tauh$ channel than for the $\tauh\tauh$
channel, by a factor that varies between 5 and 2 for resonance masses between
0.9 and 4.0. For spin-1 resonances, the HP category has a factor of 4 and 2
better sensitivity than the LP category, for low and high resonance masses,
respectively. For resonances of spin 0 and 2, the 1 b-tagged subjet category
has a sensitivity lower by a factor 6 for low resonance masses, compared to
the category with 2 b-tagged subjets, but their sensitivities are equal for
resonance masses of 4. The exclusion limit ranges from 80 to 5fb for
resonances of spin 0 and 2, and from 180 to 5fb for spin-1 resonances.

Figure 5: Observed 95% upper limits on $\sigma\mathcal{B}$(X(spin-0)
$\to\PH\PH$) (left) and $\sigma\mathcal{B}$(X(spin-2) $\to\PH\PH$) (right).
Expected limits are shown with $\pm$1 and $\pm$2 standard deviation
uncertainty bands. The $\ell\tauh$ and $\tauh\tauh$ final states, and the one
and two -tagged subjet categories are combined, to obtain the limits. The
solid red lines and the red dashed areas correspond to the cross sections
predicted by the bulk radion and graviton and their corresponding
uncertainties, as reported in Table 1.

Figure 6: Observed 95% upper limits on $\sigma\mathcal{B}$($\PWpr\to\PW\PH$)
(left) and $\sigma\mathcal{B}$($\PZpr\to\PZ\PH$) (right). Expected limits are
shown with $\pm$1 and $\pm$2 standard deviation uncertainty bands. The
$\ell\tauh$ and $\tauh\tauh$ final states, for the HP and LP $\tau_{21}$
categories, and the and boson mass signal regions are combined, to obtain the
limits. The solid lines and the relative dashed areas in magenta and red
correspond to the cross sections predicted by the HVT models A and B,
respectively, and their corresponding uncertainties, as reported in Table 1.

The predictions from bulk radion and graviton models are superimposed on the
exclusion limits in Fig. 5, assuming $\Lambda_{\mathrm{R}}=1\TeV$ and
$\tilde{k}=0.5$. With this assumption for the theory parameters, a radion
resonance with mass below 2.7is excluded at 95% . For a spin-1 signal, the
results are interpreted in the context of the simplified HVT benchmark models
A and B. As shown in Fig. 6, a () resonance of mass lower than 2.6 (1.8)is
excluded at 95% in the HVT benchmark model B. The HVT benchmark model A is
also reported for completeness. In the mass-degenerate spin-1 triplet
hypothesis, the expected and observed limits on the $\mathrm{V}^{\prime}$
resonance are shown in Fig. 7 (left).

The exclusion limit shown in Fig. 7 (left) can be interpreted as a limit in
the space of the HVT model parameters
$[g_{\mathrm{V}}c_{\PH},g^{2}c_{\mathrm{F}}/g_{\mathrm{V}}]$. Combining all
channels, the excluded region in such a parameter space for narrow resonances
is shown in Fig. 7 (right). The region of parameter space where the natural
resonance width is larger than the typical experimental resolution of 7%, for
which the narrow width assumption is not valid, is shaded.

Figure 7: Expected and observed 95% upper limit on
$\sigma\mathcal{B}$($\mathrm{V}^{\prime}\to\mathrm{V}\PH$) with $\pm$1 and
$\pm$2 standard deviation uncertainty bands (left) in the $\ell\tauh$ and
$\tauh\tauh$, $\tau_{21}$ HP and LP categories, with the and boson mass signal
regions combined. Observed exclusion limit (right) in the space of the HVT
model parameters $[g_{\mathrm{V}}c_{\PH},g^{2}c_{\mathrm{F}}/g_{\mathrm{V}}]$,
described in the text, for three different mass hypotheses of 1.5, 2.0, and
3.0. The region of parameter space where the natural resonance width is larger
than the typical experimental resolution of 7%, for which the narrow width
assumption is not valid, is shaded in grey.

##  0.9 Summary

A search has been conducted for heavy resonances that decay to two bosons, one
of which is a , , or Higgs boson that decays to a pair of quarks, and the
other is a Higgs boson that decays to a pair of $\tau$ leptons. The analyzed
data are collected by the CMS experiment at $\sqrt{s}=13\TeV$, corresponding
to an integrated luminosity of 35.9. Reconstruction techniques have been
developed to select events in which the $\tau$ lepton pair is highly boosted.
The data are consistent with the standard model expectations and upper limits
at 95% confidence level are set on the product of cross section and branching
fraction for resonance masses between 0.9 and 4.0. This search yields the
first results at $\sqrt{s}=13\TeV$ for -scale resonances in the considered
mass range and final states. Assuming the ultraviolet cutoff of the theory
$\Lambda_{\mathrm{R}}=1$, Kaluza–Klein excitations of spin-0 radions with mass
smaller than 2.7are excluded at 95% confidence level. In the heavy vector
triplet model B context, a mass-degenerate vector triplet
$\mathrm{V}^{\prime}$ resonance with mass below 2.8is excluded at 95%
confidence level.

###### 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); 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 and RFBR (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 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”) Programme and the János Bolyai Research Scholarship of
the Hungarian Academy of Sciences, the New National Excellence Program ÚNKP,
the NKFIA research grants 123842, 123959, 124845, 124850 and 125105 (Hungary);
the Council of Science and Industrial Research, India; the HOMING PLUS
programme of the Foundation for Polish Science, cofinanced from European
Union, Regional Development Fund, the Mobility Plus programme of the Ministry
of Science and Higher Education, the National Science Center (Poland),
contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543,
2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406;
the National Priorities Research Program by Qatar National Research Fund; the
Programa Estatal de Fomento de la Investigación Científica y Técnica de
Excelencia María de Maeztu, grant MDM-2015-0509 and the Programa Severo Ochoa
del Principado de Asturias; the Thalis and Aristeia programmes cofinanced by
EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral
Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its
2nd Century Project Advancement Project (Thailand); the 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. Pieters, 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. Seva, E. Starling, C. Vander Velde, P. Vanlaer, D.
Vannerom, R. Yonamine Ghent University, Ghent, Belgium
T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov2, D. Poyraz, C. Roskas,
D. Trocino, M. Tytgat, W. Verbeke, B. Vermassen, M. Vit, 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, 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, H.
Malbouisson, M. Medina Jaime5, 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, L. Calligarisa, T.R. Fernandez Perez Tomeia, E.M.
Gregoresb, P.G. Mercadanteb, S.F. Novaesa, SandraS. 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, A. Marinov, 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. 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, 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
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, 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. 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. Ellithi Kamel9, Y. Mohammed10, E. Salama11,12 National Institute of
Chemical Physics and Biophysics, Tallinn, Estonia
S. Bhowmik, R.K. Dewanjee, M. Kadastik, L. Perrini, M. Raidal, 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,
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. Abdulsalam13, C. Amendola, I. Antropov, S. Baffioni, F. Beaudette, P.
Busson, L. Cadamuro, C. Charlot, R. Granier de Cassagnac, M. Jo, I. Kucher, 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, 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, C.
Collard, E. Conte14, X. Coubez, F. Drouhin14, J.-C. Fontaine14, 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, N. Chanon, 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, H. Lattaud, M. Lethuillier, L.
Mirabito, A.L. Pequegnot, S. Perries, A. Popov15, V. Sordini, M. Vander
Donckt, S. Viret, S. Zhang 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, M.P.
Rauch, C. Schomakers, J. Schulz, M. Teroerde, B. Wittmer, V. Zhukov15 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. 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, V. Danilov, A. De Wit,
C. Diez Pardos, D. Domínguez Damiani, G. Eckerlin, D. Eckstein, T. Eichhorn,
E. Eren, E. Gallo19, J. Garay Garcia, A. Geiser, J.M. Grados Luyando, A.
Grohsjean, P. Gunnellini, M. Guthoff, A. Harb, J. Hauk, M. Hempel20, H. Jung,
M. Kasemann, J. Keaveney, C. Kleinwort, J. Knolle, I. Korol, D. Krücker, W.
Lange, A. Lelek, T. Lenz, K. Lipka, W. Lohmann20, R. Mankel, I.-A. Melzer-
Pellmann, A.B. Meyer, M. Meyer, M. Missiroli, G. Mittag, J. Mnich, A.
Mussgiller, D. Pitzl, A. Raspereza, M. Savitskyi, P. Saxena, R. Shevchenko, N.
Stefaniuk, H. Tholen, 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, G. Kasieczka, R.
Klanner, R. Kogler, N. Kovalchuk, S. Kurz, D. Marconi, J. Multhaup, M.
Niedziela, D. Nowatschin, T. Peiffer, A. Perieanu, A. Reimers, C. Scharf, P.
Schleper, A. Schmidt, S. Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G.
Steinbrück, F.M. Stober, M. Stöver, D. Troendle, E. Usai, A. Vanhoefer, B.
Vormwald Karlsruher Institut fuer Technology
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. 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, A. Kyriakis, D. Loukas, I. Topsis-
Giotis National and Kapodistrian University of Athens, Athens, Greece
G. Karathanasis, S. Kesisoglou, A. Panagiotou, N. Saoulidou, E. Tziaferi
National Technical University of Athens, Athens, Greece
K. Kousouris, I. Papakrivopoulos 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. Veres21 Wigner Research
Centre for Physics, Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath22, Á. Hunyadi, F. Sikler, T.Á. Vámi, V.
Veszpremi, G. Vesztergombi21 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, HBNI, Bhubaneswar, India
S. Bahinipati24, P. Mal, K. Mandal, A. Nayak25, D.K. Sahoo24, S.K. Swain
Panjab University, Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, S. Chauhan, R. Chawla, N. Dhingra, R.
Gupta, A. Kaur, M. Kaur, S. Kaur, R. Kumar, P. Kumari, M. Lohan, A. Mehta, S.
Sharma, J.B. Singh, G. Walia University of Delhi, Delhi, India
A. Bhardwaj, 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. Bhardwaj26, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep26, D. Bhowmik,
S. Dey, S. Dutt26, S. Dutta, S. Ghosh, N. Majumdar, K. Mondal, S.
Mukhopadhyay, S. Nandan, A. Purohit, P.K. Rout, A. Roy, S. Roy Chowdhury, S.
Sarkar, M. Sharan, B. Singh, S. Thakur26 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. Maity27, G. Majumder, K. Mazumdar, N. Sahoo, T. Sarkar27, N.
Wickramage28 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. Chenarani29, E. Eskandari Tadavani, S.M. Etesami29, M. Khakzad, M.
Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi30, F. Rezaei
Hosseinabadi, B. Safarzadeh31, 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, A. Di Florioa,b, F. Erricoa,b, L. Fiorea,
A. Gelmia,b, G. Iasellia,c, S. Lezkia,b, G. Maggia,c, M. Maggia, B.
Marangellia,b, 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, G. Zitoa 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, F.
Odoricia, 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, G. Latino, P. Lenzia,b, M. Meschinia, S.
Paolettia, L. Russoa,32, G. Sguazzonia, D. Stroma, L. Viliania 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, 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,17, 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,33, 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,17, F. Fabozzia,c, F. Fiengaa,b,
G. Galatia,b, A.O.M. Iorioa,b, W.A. Khana, L. Listaa, S. Meolaa,d,17, P.
Paoluccia,17, C. Sciaccaa,b, F. Thyssena, E. Voevodinaa,b 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, A. Tiko, 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, L. Bianchinia, T. Boccalia, L.
Borrello, R. Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, G. Fedia, L.
Gianninia,c, A. Giassia, M.T. Grippoa,32, F. Ligabuea,c, T. Lomtadzea, E.
Mancaa,c, G. Mandorlia,c, A. Messineoa,b, F. Pallaa, A. Rizzia,b, 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, B. Marzocchia,b, P.
Meridiania, G. Organtinia,b, F. Pandolfia, 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, R. Castelloa,b, 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 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 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
H. Castilla-Valdez, E. De La Cruz-Burelo, M.C. Duran-Osuna, I. Heredia-De La
Cruz36, R. Lopez-Fernandez, J. Mejia Guisao, R.I. Rabadan-Trejo, G. Ramirez-
Sanchez, R Reyes-Almanza, 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. Traczyk, 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, V. Alexakhin, P. Bunin, M. Gavrilenko, A. Golunov, I. Golutvin,
N. Gorbounov, V. Karjavin, A. Lanev, A. Malakhov, V. Matveev38,39, P. Moisenz,
V. Palichik, V. Perelygin, M. Savina, S. Shmatov, 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, 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. 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, 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. Dubinin43, L. Dudko, A.
Ershov, A. Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S.
Obraztsov, V. Savrin, A. Snigirev Novosibirsk State University (NSU),
Novosibirsk, Russia
V. Blinov44, D. Shtol44, Y. Skovpen44 State Research Center of Russian
Federation, Institute for High Energy Physics of NRC ’Kurchatov Institute’,
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 National Research Tomsk Polytechnic
University, Tomsk, Russia
A. Babaev University of Belgrade, Faculty of Physics and Vinca Institute of
Nuclear Sciences, Belgrade, Serbia
P. Adzic45, 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, S. Folgueras, 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, J. Duarte Campderros, M.
Fernandez, P.J. Fernández Manteca, A. García Alonso, J. Garcia-Ferrero, G.
Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, P. Martinez Ruiz del
Arbol, F. Matorras, J. Piedra Gomez, C. Prieels, 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, 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. Fallavollita46, G.
Franzoni, J. Fulcher, W. Funk, D. Gigi, A. Gilbert, K. Gill, F. Glege, D.
Gulhan, J. Hegeman, V. Innocente, A. Jafari, P. Janot, O. Karacheban20, J.
Kieseler, V. Knünz, A. Kornmayer, 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. Milenovic47, F. Moortgat, M. Mulders, H.
Neugebauer, J. Ngadiuba, S. Orfanelli, L. Orsini, F. Pantaleo17, L. Pape, E.
Perez, M. Peruzzi, A. Petrilli, G. Petrucciani, A. Pfeiffer, M. Pierini, F.M.
Pitters, D. Rabady, A. Racz, T. Reis, G. Rolandi48, M. Rovere, H. Sakulin, C.
Schäfer, C. Schwick, M. Seidel, M. Selvaggi, A. Sharma, P. Silva, P.
Sphicas49, A. Stakia, J. Steggemann, M. Stoye, M. Tosi, D. Treille, A. Tsirou,
V. Veckalns50, M. Verweij, W.D. Zeuner Paul Scherrer Institut, Villigen,
Switzerland
W. Bertl${}^{\textrm{\textdagger}}$, L. Caminada51, 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, B. Casal, N. Chernyavskaya, G. Dissertori, M.
Dittmar, M. Donegà, C. Dorfer, C. Grab, C. Heidegger, D. Hits, J. Hoss, T.
Klijnsma, W. Lustermann, M. Marionneau, M.T. Meinhard, D. Meister, F. Micheli,
P. Musella, F. Nessi-Tedaldi, J. Pata, F. Pauss, G. Perrin, L. Perrozzi, M.
Quittnat, M. Reichmann, D. Ruini, 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. Amsler52, D. Brzhechko, M.F. Canelli, A. De Cosa, R. Del
Burgo, S. Donato, C. Galloni, T. Hreus, B. Kilminster, I. Neutelings, 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. Bakirci53, A. Bat, F. Boran, S. Damarseckin, Z.S. Demiroglu, C. Dozen, S.
Girgis, G. Gokbulut, Y. Guler, I. Hos54, E.E. Kangal55, O. Kara, A. Kayis
Topaksu, U. Kiminsu, M. Oglakci, G. Onengut, K. Ozdemir56, S. Ozturk53, A.
Polatoz, B. Tali57, U.G. Tok, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle
East Technical University, Physics Department, Ankara, Turkey
G. Karapinar58, K. Ocalan59, M. Yalvac, M. Zeyrek Bogazici University,
Istanbul, Turkey
E. Gülmez, M. Kaya60, O. Kaya61, S. Tekten, E.A. Yetkin62 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. Newbold63,
S. Paramesvaran, T. Sakuma, S. Seif El Nasr-storey, D. Smith, V.J. Smith
Rutherford Appleton Laboratory, Didcot, United Kingdom
K.W. Bell, A. Belyaev64, C. Brew, R.M. Brown, 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, D. Colling, L. Corpe, P. Dauncey, G. Davies, M. Della
Negra, R. Di Maria, A. Elwood, Y. Haddad, G. Hall, G. Iles, T. James, M. Komm,
R. Lane, C. Laner, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, T.
Matsushita, J. Nash65, A. Nikitenko7, V. Palladino, M. Pesaresi, A. Richards,
A. Rose, E. Scott, C. Seez, A. Shtipliyski, T. Strebler, S. Summers, A.
Tapper, K. Uchida, M. Vazquez Acosta66, 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, A. Morton, 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.
Rohlf, L. Sulak, D. Zou Brown University, Providence, USA
G. Benelli, D. Cutts, M. Hadley, J. Hakala, U. Heintz, J.M. Hogan67, 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, R. Breedon, D. Burns, M. Calderon De La Barca Sanchez,
M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk,
W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout,
M. Shi, J. Smith, D. Stolp, D. Taylor, K. Tos, M. Tripathi, Z. Wang, F. Zhang
University of California, Los Angeles, USA
M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M.
Ignatenko, N. Mccoll, 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, 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.
Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A.
Vartak, S. Wasserbaech68, 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, M. Citron, 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
J.P. Cumalat, W.T. Ford, F. Jensen, A. Johnson, M. Krohn, S. Leontsinis, E.
MacDonald, T. Mulholland, K. Stenson, K.A. Ulmer, S.R. Wagner Cornell
University, Ithaca, USA
J. Alexander, J. Chaves, Y. Cheng, J. Chu, A. Datta, 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, J. Hanlon, R.M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, B.
Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, B. Klima, M.J. Kortelainen,
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, A. Savoy-Navarro69, 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, 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.
Konigsberg, A. Korytov, K. Kotov, P. Ma, K. Matchev, H. Mei, G. Mitselmakher,
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, S.
Dittmer, O. Evdokimov, C.E. Gerber, D.A. Hangal, D.J. Hofman, K. Jung, J.
Kamin, I.D. Sandoval Gonzalez, M.B. Tonjes, N. Varelas, H. Wang, Z. Wu, J.
Zhang The University of Iowa, Iowa City, USA
B. Bilki70, W. Clarida, K. Dilsiz71, S. Durgut, R.P. Gandrajula, M.
Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya72, A. Mestvirishvili,
A. Moeller, J. Nachtman, H. Ogul73, Y. Onel, F. Ozok74, 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. Rogan, C.
Royon, S. Sanders, E. Schmitz, J.D. Tapia Takaki, Q. Wang Kansas State
University, Manhattan, USA
A. Ivanov, K. Kaadze, Y. Maravin, A. Modak, A. Mohammadi, L.K. Saini, N.
Skhirtladze Lawrence Livermore National Laboratory, Livermore, USA
F. Rebassoo, D. Wright University of Maryland, College Park, USA
A. Baden, O. Baron, A. Belloni, S.C. Eno, Y. Feng, 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, G. Bauer, R. Bi,
S. Brandt, W. Busza, I.A. Cali, M. D’Alfonso, Z. Demiragli, G. Gomez Ceballos,
M. Goncharov, P. Harris, D. Hsu, M. Hu, Y. Iiyama, G.M. Innocenti, M. Klute,
D. Kovalskyi, 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,
G.S.F. Stephans, K. Sumorok, K. Tatar, D. Velicanu, J. Wang, T.W. Wang, B.
Wyslouch, S. Zhaozhong University of Minnesota, Minneapolis, USA
A.C. Benvenuti, R.M. Chatterjee, A. Evans, P. Hansen, S. Kalafut, Y. Kubota,
Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack, J. Turkewitz, 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, 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
A. Godshalk, C. Harrington, I. Iashvili, D. Nguyen, A. Parker, S. Rappoccio,
B. Roozbahani Northeastern University, Boston, USA
G. Alverson, E. Barberis, C. Freer, A. Hortiangtham, A. Massironi, D.M. Morse,
T. Orimoto, R. Teixeira De Lima, T. Wamorkar, B. Wang, A. Wisecarver, D. Wood
Northwestern University, Evanston, USA
S. Bhattacharya, O. Charaf, K.A. Hahn, N. Mucia, N. Odell, M.H. Schmitt, K.
Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, USA
R. Bucci, N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N.
Kellams, K. Lannon, W. Li, N. Loukas, N. Marinelli, F. Meng, C. Mueller, Y.
Musienko38, M. Planer, A. Reinsvold, R. Ruchti, P. Siddireddy, G. Smith, S.
Taroni, M. Wayne, A. Wightman, 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, T.Y. Ling, W. Luo, B.L. Winer, H.W. Wulsin Princeton
University, Princeton, USA
S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, S. Higginbotham,
A. Kalogeropoulos, D. Lange, J. Luo, D. Marlow, K. Mei, I. Ojalvo, J. Olsen,
C. Palmer, P. Piroué, J. Salfeld-Nebgen, 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, L. Gutay, M. Jones, A.W. Jung, A. Khatiwada,
D.H. Miller, N. Neumeister, C.C. Peng, H. Qiu, J.F. Schulte, J. Sun, F. Wang,
R. Xiao, W. Xie Purdue University Northwest, Hammond, USA
T. Cheng, J. Dolen, N. Parashar Rice University, Houston, USA
Z. Chen, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Guilbaud, M. Kilpatrick, W.
Li, B. Michlin, 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, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa Texas A&M
University, College Station, USA
O. Bouhali75, A. Castaneda Hernandez75, A. Celik, M. Dalchenko, M. De Mattia,
A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, T. Kamon76, R.
Mueller, Y. Pakhotin, R. Patel, A. Perloff, L. Perniè, D. Rathjens, A.
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. 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, J.D. Ruiz Alvarez, 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, 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, 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 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: Now at Cairo University, Cairo, Egypt
10: Now at Fayoum University, El-Fayoum, Egypt
11: Also at British University in Egypt, Cairo, Egypt
12: Now at Ain Shams University, Cairo, Egypt
13: Also at Department of Physics, King Abdulaziz University, Jeddah, Saudi
Arabia
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 Shoolini University, Solan, India
27: Also at University of Visva-Bharati, Santiniketan, India
28: Also at University of Ruhuna, Matara, Sri Lanka
29: Also at Isfahan University of Technology, Isfahan, Iran
30: Also at Yazd University, Yazd, Iran
31: Also at Plasma Physics Research Center, Science and Research Branch,
Islamic Azad University, Tehran, Iran
32: Also at Università degli Studi di Siena, Siena, Italy
33: Also at INFN Sezione di Milano-Bicocca a, Università di Milano-Bicocca b,
Milano, Italy
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 INFN Sezione di Pavia a, Università di Pavia b, Pavia, Italy
47: Also at University of Belgrade, Faculty of Physics and Vinca Institute of
Nuclear Sciences, Belgrade, Serbia
48: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy
49: Also at National and Kapodistrian University of Athens, Athens, Greece
50: Also at Riga Technical University, Riga, Latvia
51: Also at Universität Zürich, Zurich, Switzerland
52: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna,
Austria
53: Also at Gaziosmanpasa University, Tokat, Turkey
54: Also at Istanbul Aydin University, Istanbul, Turkey
55: Also at Mersin University, Mersin, Turkey
56: Also at Piri Reis University, Istanbul, Turkey
57: Also at Adiyaman University, Adiyaman, Turkey
58: Also at Izmir Institute of Technology, Izmir, Turkey
59: Also at Necmettin Erbakan University, Konya, Turkey
60: Also at Marmara University, Istanbul, Turkey
61: Also at Kafkas University, Kars, Turkey
62: Also at Istanbul Bilgi University, Istanbul, Turkey
63: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom
64: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
65: Also at Monash University, Faculty of Science, Clayton, Australia
66: Also at Instituto de Astrofísica de Canarias, La Laguna, Spain
67: Also at Bethel University, St. Paul, USA
68: Also at Utah Valley University, Orem, USA
69: Also at Purdue University, West Lafayette, USA
70: Also at Beykent University, Istanbul, Turkey
71: Also at Bingol University, Bingol, Turkey
72: Also at Erzincan University, Erzincan, Turkey
73: Also at Sinop University, Sinop, Turkey
74: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey
75: Also at Texas A&M University at Qatar, Doha, Qatar
76: Also at Kyungpook National University, Daegu, Korea