EXO-17-005

$Revision:477148$
$HeadURL:svn+ssh://svn.cern.ch/reps/tdr2/papers/EXO-17-005/trunk/EXO-17-005.tex$
$Id:EXO-17-005.tex4771482018-10-0513:08:03Zknam$

EXO-17-005

# Search for Z$\gamma$ resonances using leptonic and hadronic final states in
proton-proton collisions at $\sqrt{s}=13$

###### Abstract

A search is presented for resonances decaying to a Z boson and a photon. The
analysis is based on data from proton-proton collisions at a center-of-mass
energy of 13, corresponding to an integrated luminosity of 35.9, and collected
with the CMS detector at the LHC in 2016. Two decay modes of the Z boson are
investigated. In the leptonic channels, the Z boson candidates are
reconstructed using electron or muon pairs. In the hadronic channels, they are
identified using a large-radius jet, containing either light-quark or b quark
decay products of the Z boson, via jet substructure and advanced b quark
tagging techniques. The results from these channels are combined and
interpreted in terms of upper limits on the product of the production cross
section and the branching fraction to Z$\gamma$ for narrow and broad spin-0
resonances with masses between 0.35 and 4.0, providing thereby the most
stringent limits on such resonances.

##  0.1 Introduction

One of the key aspects of the CERN LHC physics program is the search for new
resonances predicted in theories beyond the standard model (SM). Given the
fairly stringent limits already set on masses of such resonances in fermionic
decay channels (e.g., via dilepton or dijet searches), it is particularly
interesting to explore bosonic decay channels, which can dominate if the
couplings of a new resonance to fermions are suppressed. Examples of such
signatures are decays into a pair of massive bosons: VV and VH, where V
represents either a $\PW$ or a $\PZ$ boson, and H refers to the recently
discovered Higgs boson [1, 2, 3]. The latest results from these searches at
the LHC are described in Refs. [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] for
the VV channels and in Refs. [10, 16, 17, 18, 19, 20, 21] for the VH channels.

Diboson decays involving photons, , $\PW\Pgg$, $\PZ\Pgg$, and $\Pgg\Pgg$
channels, are also important, as the search in the $\Pgg\Pgg$ channel
demonstrated by contributing significantly to the discovery of the Higgs boson
by the ATLAS and CMS Collaborations in 2012 [1, 2, 3]. While a resonance
decaying to diphotons cannot be a vector or an axial vector, due to the
Landau–Yang theorem [22, 23], having one of the two bosons massive alleviates
this constraint. Thus, charged (neutral) bosons of spin 0, 1, or 2 can be
sought in the $\PW\Pgg$ ($\PZ\Pgg$) channel, leading to a broad search
program. Such resonances are predicted in many extensions of the SM, such as
technicolor [24] and little Higgs [25] models, as well as models with an
extended Higgs boson sector [26, 27] or with extra spatial dimensions [28,
29].

In this paper, we describe a search for $\PZ\gamma$ resonances in the leptonic
($\ell\ell$, where $\ell$ refers to $\Pe$ or $\mu$) and hadronic decay
channels of the boson, as well as the combination of these channels. While the
results in this paper are interpreted in terms of spin-0 resonances, they are
broadly applicable to spin-1 and spin-2 states, as the signal acceptance
depends only weakly on the spin of the resonance [30]. Similar searches in a
combination of leptonic and hadronic decay channels of the boson have been
recently published by ATLAS [31] at $\sqrt{s}=13$and by CMS at $\sqrt{s}=8$
and 13 [32], based on significantly smaller integrated luminosities. Other
searches for $\PZ\Pgg$ resonances have been performed only in the dilepton
channels. These include searches by the L3 Collaboration at the CERN LEP [33]
and the D0 Collaboration at the Fermilab Tevatron [34, 35]. At the LHC, they
have been done by ATLAS at $\sqrt{s}=7,$ 8, and 13 [36, 37, 30], and CMS at
$\sqrt{s}=8$ and 13 [38], as well as by ATLAS and CMS using the combined 7 and
8data [39, 40], and by ATLAS using the 13data [30] in the context of a search
for the $\PH\to\PZ\gamma$ decay.

The present search is for a resonance with a relatively narrow width appearing
as an excess over the smooth $\PZ\gamma$ invariant mass ($m_{\Z\gamma}$)
spectrum constructed from an energetic photon and the $\PZ\to\ell\ell$ or
$\PZ\to\qqbar$ decay products. While a search in the leptonic channels has
lower SM backgrounds, resulting in higher sensitivity to resonance masses
$<$1, at larger mass values, where backgrounds are small, the hadronic
channels, with their higher branching fraction, dominate the sensitivity. The
backgrounds in both channels are determined directly from fits to data.

The boson decays in the leptonic channels are reconstructed using an electron
or a muon pair. The dominant backgrounds in the $\ell\ell\Pgg$ channel are the
irreducible contribution from continuum $\PZ\Pgg$ production and the reducible
backgrounds from either final-state radiation in $\PZ\to\ell\ell$ events or
from boson production in association with one or more jets ($\PZ$+jets), where
a jet is misidentified as a photon.

The boson decay products in the hadronic channels can be reconstructed either
as two well-separated small-radius jets, or as a single large-radius jet (J)
resulting from the merging of the two quark jets because of the large Lorentz
boost of a boson produced in the decay of a heavy resonance. The fraction of
events corresponding to the merged topology, which has low background from SM
sources, increases with the mass of the resonance. To optimize signal relative
to background, in this paper we consider just the merged jet topology
($\mathrm{J}\gamma$), and thus the search in the hadronic channels is focused
on relatively high resonance masses where the trigger for these events is
efficient. We use jet substructure techniques to infer the presence of two
subjets, and dedicated b tagging algorithms to identify those subjets that
originate from b quark fragmentation. This provides the means to distinguish a
signal from the dominant background from prompt-photon and QCD multijet
production, with one of the jets spuriously passing jet substructure
requirements (and, in the latter case, with another jet mimicking a photon).

##  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 coverage provided by the barrel and
endcap detectors. Muons are detected in gas-ionization chambers embedded in
the steel flux-return yoke outside the solenoid.

The silicon tracker measures charged particles within the pseudorapidity range
$\abs{\eta}<2.5$. It consists of 1440 silicon pixel and 15 148 silicon strip
detector modules. For nonisolated particles of $1<\pt<10\GeV$ and
$\abs{\eta}<1.4$, the track resolutions are typically 1.5% in and 25–90
(45–150)in the transverse (longitudinal) impact parameter [41]

The ECAL consists of 75 848 lead tungstate crystals, which provide coverage in
pseudorapidity $\abs{\eta}<1.48$ in a barrel region (EB) and
$1.48<\abs{\eta}<3.0$ in two endcap regions (EE). Preshower detectors
consisting of two planes of silicon sensors interleaved with a total of
$3X_{0}$ of lead are located in front of each EE detector.

In the region $\abs{\eta}<1.74$, the HCAL cells have widths of 0.087 in
pseudorapidity and 0.087 in azimuth ($\phi$). In the $\eta$-$\phi$ plane, and
for $\abs{\eta}<1.48$, the HCAL cells map on to $5\times 5$ arrays of ECAL
crystals to form calorimeter towers projecting radially outwards from close to
the nominal interaction point. For $\abs{\eta}>1.74$, the coverage of the
towers increases progressively to a maximum of 0.174 in $\Delta\eta$ and
$\Delta\phi$. Within each tower, the energy deposits in ECAL and HCAL cells
are summed to define the calorimeter tower energies, subsequently used to
provide the energies and directions of hadronic jets.

The electron momentum is estimated by combining the energy measurement in the
ECAL with the momentum measurement in the tracker. The momentum resolution for
electrons with $\pt\approx 45\GeV$ from $\Z\rightarrow\Pe\Pe$ decays ranges
from 1.7% for nonshowering electrons in the barrel region to 4.5% for
showering electrons in the endcaps [42].

Muons are measured in the pseudorapidity range $\abs{\eta}<2.4$, with
detection planes made using three technologies: drift tubes, cathode strip
chambers, and resistive-plate chambers. Matching muons to tracks measured in
the silicon tracker results in a relative transverse momentum resolution for
muons with $20<\pt<100\GeV$ of 1.3–2.0% in the barrel and better than 6% in
the endcaps. The resolution in the barrel is better than 10% for muons with up
to 1 [43].

Events of interest are selected using a two-tiered trigger system [44]. The
first level, composed of custom hardware processors, uses information from the
calorimeters and muon detectors to select events at a rate of around 100kHz
within a time interval of less than 4. The second level, known as the high-
level trigger, consists of a farm of processors running a version of the full
event reconstruction software optimized for fast processing, and reduces the
event rate to around 1kHz before data storage.

A more detailed description of the CMS detector, together with a definition of
the coordinate system used and the relevant kinematic variables, can be found
in Ref. [45].

##  0.3 Data sets and event selection

The data used in this search correspond to an integrated luminosity of
35.9recorded by the CMS experiment at $\sqrt{s}=13$in 2016. The high
instantaneous luminosity delivered by the LHC results in additional
interactions in the same or neighboring bunch crossings (pileup) as the hard
scattering interaction. The average number of pileup interactions in the 2016
data set is around 23.

In the $\Pe\Pe\gamma$ channel, the selected events are required to pass a
double-photon trigger with the transverse momentum $\pt>60\GeV$ and
pseudorapidity $\abs{\eta}<2.5$ requirements on both photon candidates. Since
the photon trigger requirements do not include any track veto, this trigger is
equally efficient in selecting photon and electron candidates. A combination
of single-muon triggers requiring $\pt>50\GeV$ and $\abs{\eta}<2.4$ on a muon
candidate are used in the $\Pgm\Pgm\gamma$ channel. In the $\mathrm{J}\gamma$
channel, we require a logical “OR” of several triggers with the separate
requirements: the scalar sum of transverse energies of all reconstructed jets
($\HT$) is above 800 or 900; a jet is present with the transverse energy above
500; and a photon candidate is present with $\pt>165$ or 175and
$\abs{\eta}<2.5$. We determine the selection efficiency for these trigger
combinations using unbiased data samples collected with different triggers.
The triggers are found to be 98–100% efficient with respect to the offline
selection, for the entire mass range used, in all three channels. The small
residual inefficiency is taken into account when calculating the signal
acceptance.

Simulated signal events of spin-0 resonances decaying to $\Z\gamma$ are
generated at leading order (LO) in perturbative QCD using 8.205 [46] with the
CUETP8M1 [47, 48] underlying-event tune. Several samples are generated with
masses ranging from 0.3 to 4.0. Two resonance width assumptions were used in
the simulation: one, termed “narrow”, has its width ($\Gamma_{\mathrm{X}}$)
set to 0.014% of the resonance mass ($m_{\mathrm{X}}$), and the second,
referred to as “broad”, has $\Gamma_{\mathrm{X}}/m_{\mathrm{X}}=5.6\%$. The
first choice corresponds to a resonance with a natural width much smaller than
the detector resolution. The second choice facilitates a direct comparison
with the previous CMS publications [38, 32]. We assume no interference between
signal and the SM nonresonant $\PZ\gamma$ production.

Simulated background events do not enter the analyses directly, as the
backgrounds are obtained from fits to data, but are used to assess the
accuracy of the background model and to optimize event selection. Standard
model nonresonant $\PZ(\ell\ell)\Pgg$ production, which is expected to be the
dominant background process in the $\ell\ell\gamma$ channel, is generated at
next-to-leading order (NLO) accuracy using the 2.3.3 generator [49, 50]. The
$\PZ(\ell\ell)$+jets events with a jet misidentified as a photon, which
constitute a subdominant source of background, are generated at LO using , as
are the dominant $\Pgg$+jets and QCD multijet events, as well as subdominant
hadronically decaying $\PW$+jets and $\PZ$+jets backgrounds in the
$\mathrm{J}\gamma$ channel. All background events are processed with for the
description of fragmentation and hadronization.

All simulated samples were produced using NNPDF3.0 [51] parton distribution
functions (PDFs), processed with the full CMS detector model based on [52],
and reconstructed with the same suite of programs as used for collision data.
Pileup effects are taken into account by superimposing minimum bias events on
the hard scattering interaction. The simulated samples are reweighted to match
the reconstructed vertex multiplicity distribution observed in data.

The particle-flow (PF) event algorithm [53] aims to reconstruct and identify
each individual particle in an event, based on an optimized combination of
information from the various elements of the CMS detector. The energy of
photons is directly obtained from the ECAL measurement, corrected for zero-
suppression effects. The energy of electrons is determined from a combination
of the electron momentum at the primary interaction vertex as determined by
the tracker, the energy of the corresponding ECAL cluster, and the energy sum
of all bremsstrahlung photons spatially compatible with originating from the
electron track. The energy of muons is obtained from the curvature of the
reconstructed muon track. The energy of charged hadrons is determined from a
combination of their momentum measured in the tracker and the matching ECAL
and HCAL energy deposits, corrected for zero-suppression effects and for the
response function of the calorimeters to hadronic showers. Finally, the energy
of neutral hadrons is obtained from the corresponding corrected ECAL and HCAL
energy deposits.

The events must contain at least one reconstructed primary vertex with at
least four associated tracks, with transverse (longitudinal) coordinates
required to be within 2 (24)cm of the nominal collision point. The
reconstructed vertex with the largest value of summed physics-object $\pt^{2}$
is taken to be the primary interaction vertex. The physics objects are the
jets, clustered using the jet finding algorithm [54, 55] with the tracks
assigned to the vertex as inputs, and the associated missing transverse
momentum, taken as the negative vector sum of the transverse momenta of those
jets.

Electron candidates must pass loose identification criteria based on the
shower shape variables, on the ratio of energy deposits in the associated HCAL
and ECAL cells, on the geometrical matching between the energy deposits and
the associated track, and on the consistency between the energy reconstructed
in the calorimeter and the momentum measured in the tracker [42].

Muon candidates are reconstructed from tracks found in the muon system that
are associated with the tracks in the inner tracking systems. One muon
candidate is required to pass a loose identification [56]. Another muon
candidate is required to pass a tighter identification based on the numbers of
associated hits found in the pixel and strip trackers, on the numbers of hits
and track segments in the muon detector, and on criteria for the matching
between the silicon detector track and the muon track segments [56].

Leptons are required to be isolated from other energy deposits in the event.
This is expected for signal leptons from $\PZ$ boson decays, but is not the
case for backgrounds from nonprompt leptons originating, e.g., from $\PQb$
hadron decays. The relative isolation of a lepton is defined as the scalar sum
of the transverse momenta of all relevant PF candidates within a cone around
the lepton, divided by the of the lepton candidate. For an electron, the cone
size $\Delta R=\sqrt{(\Delta\eta)^{2}+(\Delta\phi)^{2}}$ depends on its :

$\displaystyle\Delta R$ $\displaystyle=\begin{cases}0.2,&\text{for }\pt\leq
50\GeV,\\\ \frac{10\GeV}{\pt},&\text{for }50<\pt\leq 200\GeV,\text{ and}\\\
0.05,&\text{for }\pt>200\GeV.\end{cases}$ (1)

The electron isolation is based on the photons, and charged and neutral
hadrons found in the isolation cone. Charged hadrons originating from pileup
vertices are excluded from the sum. The contribution to the isolation sum from
neutral pileup particles is accounted for by using the average energy density
method [57]. The varying isolation cone radius in Eq. (1) takes into account
the aperture of $\PQb$ hadron decays as a function of their , and reduces the
inefficiency from accidental overlap of electrons from $\PZ$ boson decays and
jets. For muons, a fixed cone of a size $\Delta R=0.3$ is used, and the
isolation is based on all charged-particle tracks within the isolation cone,
excluding the candidate muon track. In the case of two spatially close muons
in the event, with overlapping isolation cones, both muons are excluded from
each isolation sum. This procedure, together with the use of a variable cone
size for electron isolation, ensures high lepton identification efficiency
even in the topologies where a Z boson has a high Lorentz boost, as expected
for Z bosons produced in a decay of a heavy resonance. The relative isolation
of electron and muon candidates is required to be less than 0.1.

Photon identification is based on a multivariate analysis, employing a boosted
decision tree algorithm [58, 59]. The inputs to the algorithm include shower
shape variables, isolation sums computed from PF candidates in a cone of
radius $\Delta R=0.3$ around the photon candidate, and variables that account
for the dependences of the shower shape and isolation variables on the pileup
[60]. In addition, a conversion-safe electron veto [60] is applied. Photon
candidates are required to pass a working point that corresponds to a typical
photon reconstruction and identification efficiency of 90%, in the photon
$\pt$ range used in the analysis.

In the $\mathrm{J}\gamma$ channel, large-cone jets are used to reconstruct
hadronically decaying highly Lorentz boosted $\PZ$ boson candidates. Jets are
reconstructed from PF candidates clustered using the anti-algorithm [54] with
a distance parameter of 0.8. Charged hadrons not originating from the primary
vertex are not considered in the jet clustering. Corrections based on the jet
area [57] are applied to remove the energy contribution of neutral hadrons
from pileup interactions. The energies of the jets are further corrected for
the response function of the calorimeter. These corrections are extracted from
simulation and confirmed with in situ measurements using the energy balance in
dijet, multijet, $\Pgg$+jet, and leptonically decaying $\PZ$+jet events [61,
62]. Additional quality criteria are applied to jets to remove rare spurious
noise patterns in the calorimeters, and also to suppress leptons misidentified
as jets. The jet energy resolution amounts typically to 15% at 10, 8% at 100,
and 4% at 1. Jets must have $\pt>200$and $\abs{\eta}<2.0$. The requirement on
the jet $\eta$ suppresses background from $\gamma$+jets and QCD multijet
events, and ensures that the core of the jet is within the tracker volume of
the detector ($\abs{\eta}<2.5$). The latter requirement is important for
subsequent b quark tagging.

Events in the $\ell\ell\gamma$ channel are required to have two same-flavor
leptons (electrons or muons) and a photon. Additionally, leptons in the
$\Pgm\Pgm\gamma$ channel are required to have opposite electric charge. This
requirement is not used in the $\Pe\Pe\gamma$ channel due to a nonnegligible
probability to misreconstruct the charge of an electron candidate because of
an energetic bremsstrahlung. The leading electron (muon) is required to have
$\pt>65$ (52)and $\abs{\eta}<2.5$ (2.4). The subleading lepton is required to
have $\pt>10\GeV$ and to be found in the same pseudorapidity range as the
leading lepton. The photon in the $\Pe\Pe\gamma$ ($\Pgm\Pgm\gamma$) channel is
required to satisfy $\pt>65$ (40)and $\abs{\eta}<2.5$. Electrons and photons
in the ECAL barrel-endcap transition region ($1.44<\abs{\eta}<1.57$) are
excluded from the analysis. In the $\Pe\Pe\gamma$ channel, the thresholds on
the electrons and photons in the ECAL endcap region are increased to 70, in
order to ensure a fully efficient trigger. Photons are required to be
separated from lepton candidates by $\Delta R>0.4$, to reduce the background
from final-state radiation in $\PZ\to\ell\ell$ events. The invariant mass of
the dilepton system is required to be $50<m_{\ell\ell}<130\GeV$. The minimum
dilepton mass requirement suppresses contributions from
$\Pp\Pp\to\gamma\gamma^{*}$ events, where an internal conversion of a photon
produces a lepton pair. Finally, we require the ratio of the photon to
$m_{\Z\gamma}$ to be greater than 0.27. This requirement suppresses
backgrounds due to jets misidentified as photons, without significant loss in
the signal efficiency and without introducing a bias in the $m_{\Z\gamma}$
spectrum. We search for resonances in the $m_{\Z\gamma}$ spectrum above 300
(250)in the electron (muon) channel.

For the $\mathrm{J}\gamma$ channel, the photon candidates are required to have
$\pt>200$and to fall within the barrel fiducial region of the ECAL
($\abs{\eta}<1.44$). Events with a photon reconstructed in the endcap region
suffer from high $\Pgg$+jets background and do not add to the sensitivity of
the analysis; therefore they are not considered. Photon candidates in the
event are required to be separated from large-radius jets by a distance of
$\Delta R>1.1$, which guarantees that the photon isolation cone is not
contaminated with the jet constituents.

To identify $\PZ$ boson candidates in the $\mathrm{J}\gamma$ channel, the
reconstructed large-radius jet mass, evaluated after applying a jet pruning
algorithm [63, 64], is used. The jet pruning reclusters the jet constituents
and eliminates soft, large-angle QCD radiation, which otherwise contributes
significantly to the jet mass. The pruning algorithm reclusters each jet
starting from its original constituents with the Cambridge–Aachen (CA)
algorithm [65] and discards soft and wide-angle recombinations in each step of
the iterative CA procedure. The pruned jet mass
($m_{\mathrm{J}}^{\text{pruned}}$) is computed from the sum of the four-
momenta of the remaining constituents, which are corrected with the same
factor as has already been used in the generic jet reconstruction described
above. A detailed description of the pruning algorithm can be found in Ref.
[66]. For the signal selection, we require a $\PZ$ candidate to have
$75<m_{\mathrm{J}}^{\text{pruned}}<105$.

Finally, in the $\mathrm{J}\gamma$ channel a requirement is imposed on the
ratio of photon $\pt$ to the reconstructed $\PZ\gamma$ mass of
$\pt/m_{\Z\gamma}>0.34$, with the cutoff chosen, based on a study of simulated
signals and backgrounds, to maximize the discovery potential for a narrow
resonance. We search for resonances with masses $m_{\Z\gamma}>650$in this
channel.

To further discriminate against the QCD multijet and $\Pgg+$jets backgrounds
in the $\mathrm{J}\gamma$ channel, we categorize the events according to the
likelihood of a large-radius jet to contain subjets originating from b quark
fragmentation and to contain exactly two subjets. In order to do so, we employ
subjet b tagging and $N$-subjettiness [67] variables ($\tau_{N}$). The
$N$-subjettiness observable measures the spatial distribution of jet
constituents relative to candidate subjet axes in order to quantify how well
the jet can be divided into $N$ subjets. Subjet axes are determined by a one-
pass optimization procedure, which minimizes $N$-subjettiness [68]. In
particular, the ratio of 2- to 1-subjettiness, $\tau_{21}=\tau_{2}/\tau_{1}$,
offers an excellent separation between the QCD jets and jets from vector boson
decays [69], which tend to have lower $\tau_{21}$ values than the former.

To infer the presence of b quark subjets within a large-radius jet, pruned
jets are split into two subjets by reversing the final iteration of the jet
clustering algorithm. These subjets are classified according to the
probability of their originating from b quarks, based on results from the
combined secondary vertex (CSVv2) b tagging algorithm [70, 71]. A jet is
identified as being consistent with the $\PZ\to\bbbar$ decay when at least one
of its subjets satisfies the medium operating point of the CSVv2 algorithm,
and the other subjet satisfies the loose operating point. The medium and loose
operating points correspond to 70 and 85% (20 and 50%) in the b jet tagging
efficiency for $\pt<300\GeV$ ($\pt=1\TeV$), and 1–2% and 10–15%
misidentification probability of a light-flavor jet, respectively. If an event
contains a $\PZ\to\bbbar$ candidate, it is classified as “b tagged”. For the
rest of the events, if the large-radius jet has $\tau_{21}<0.45$, we classify
the event as “$\tau_{21}$ tagged”. Otherwise, the event is assigned to the
“untagged” category. These three categories are mutually exclusive and are
combined for the final result. The additional classification according to the
$\tau_{21}$ value enhances signal sensitivity by 10–15% at low to intermediate
signal masses (up to $\sim$2), relative to a previous analysis in the hadronic
channels [32].

##  0.4 Background and signal modeling

###  0.4.1 Background modeling

Simulations in the $\ell\ell\gamma$ channels indicate that 80–90% of the
background remaining after the full event selection is from SM $\PZ$ boson
production accompanied by initial-state photon radiation, with the remainder
mostly from $\PZ$+jets events, with a jet misreconstructed as a photon. The
background $m_{\Z\gamma}$ distributions fall steeply and smoothly with
increasing mass, in these channels. Likewise, studies for the
$\mathrm{J}\gamma$ channel based on simulated background samples and on the
lower sideband of the jet mass distribution
($50<m_{\mathrm{J}}^{\text{pruned}}<70\GeV$) in data show that the invariant
mass distribution $m_{\Z\gamma}$ of the SM background also falls smoothly in
this channel, and that the distributions of kinematic observables derived from
the lower jet mass sideband match those for the signal selection.

The background is measured directly in data, through unbinned maximum-
likelihood fits to the observed $m_{\Z\gamma}$ distributions, performed
separately in each channel. The background in each channel is parametrized
with an empirical function. Different families of functions inspired by the
ones used in searches for beyond-the-SM phenomena in the dijet, multijet,
diphoton, and VV channels at hadron colliders are evaluated in the signal
region using simulation ($\ell\ell\gamma$ channels) or the lower jet mass
sideband ($\mathrm{J}\gamma$ channel). Examples of these functions are:
$f(x)=P_{0}(1-x^{1/3})^{P_{1}}/x^{P_{2}+P_{3}(\ln x)}$ [72],
$g(x)=P_{0}(1-x)^{P_{1}}/x^{P_{2}+P_{3}(\ln x)}$ [73],
$h(x)=P_{0}x^{P_{1}}\exp(P_{2}x+P_{3}x^{2})$ [74], where
$x=m_{\Z\gamma}/\sqrt{s}$, $\sqrt{s}$ is the center-of-mass energy (13), and
the number of the fit parameters $P_{i}$ shown is the maximum order
considered. The choice of the order within a family of fitting functions for
the background distribution is made independently in each channel using the
Fisher $F$-test [75], which balances the quality of the fit against the number
of parameters. The choice among the families of functions is optimized based
on the results of the bias test described below. The same function [76] was
chosen in both the $\ell\ell\gamma$ and $\mathrm{J}\gamma$ channels:

$\frac{\rd{}N}{\rd m_{\Z\gamma}}=P_{0}\,x^{P_{1}+P_{2}(\ln x)},$ (2)

where $P_{0}$ is a normalization parameter, and $P_{1}$, $P_{2}$ describe the
shape of the invariant mass distribution.

In the $\ell\ell\gamma$ channels, the absence of significant bias in the fit
to background is verified by generating a large number of pseudo-experiments
using the simulated background shapes, fitting them with different background
models, and measuring the difference between the input and fitted background
yields in various $m_{\Z\gamma}$ windows within the entire search range. A
pull variable is defined in each window by the difference between the input
and fitted yields, divided by the combined statistical uncertainties in the
data and the fit. If the absolute value of the median in the pull distribution
is found to be $>$0.5, an additional uncertainty is assigned to the background
parametrization. A modified pull distribution is then constructed, increasing
the statistical uncertainty by an extra term, denoted as the bias term. The
bias term is parametrized as a smooth function of $m_{\Z\gamma}$ and tuned to
make the absolute value of the median of the modified pull distribution to be
$<$0.5 in all mass windows. This additional uncertainty is included in the
likelihood function by adding to the background model a component with a
distribution that is the same as the signal, but a normalization coefficient
distributed as a Gaussian of mean zero, and a width equal to the integral of
the bias term over the signal mass window, defined as the full width at half
maximum. The inclusion of this additional component takes into account the
possible mismodeling of the background shape. The bias term in the
$\ell\ell\gamma$ analysis corresponds to ${\approx}0.3\unit{events}/\GeVns{}$
at $m_{\Z\gamma}=400$and smoothly falls to ${\approx}2\times 10^{-4}$
events/GeV around $m_{\Z\gamma}=2\TeV$. The observed $m_{\Z\gamma}$ invariant
mass spectra in data are shown in Fig. 1 for the $\Pe\Pe\gamma$ (left) and
$\Pgm\Pgm\gamma$ (right) channels. The results of the fits and their
uncertainties at 68% confidence level (CL) are shown by the lines and the
shaded bands, respectively.

Figure 1: Observed $m_{\Z\gamma}$ invariant mass spectra in the $\Pe\Pe\gamma$
(left) and $\Pgm\Pgm\gamma$ (right) channels. The best fits to the background-
only hypotheses are represented by the red lines, with their 68% CL
uncertainty bands given by the gray shadings. Several narrow and broad signal
benchmarks with arbitrary normalization are shown on top of the background
prediction with the dashed lines. The lower panels show the difference between
the data and the fits, divided by the uncertainty, which includes the
statistical uncertainties in the data and the fit. For bins with a small
number of entries, the error bars correspond to the Garwood confidence
intervals [77].

Similarly, in the $\mathrm{J}\gamma$ channel, the mass spectra in the three
analysis categories, derived either from the low jet mass sideband in data or
from simulated background samples, are fitted with a variety of alternative
functions to generate pseudo-data sets. Additionally, in a set of pseudo-
experiments, signals with different mass values and cross sections close to
the expected 95% CL limits are injected. The full spectra are fitted with the
chosen function of Eq. (2) together with a signal model (discussed in Section
0.4.2), and the signal cross section is extracted. Distributions of the
difference between the data and the fits, divided by the overall uncertainty
for the obtained signal cross section, are constructed, and their shapes are
found to be consistent with a normal distribution with a mean less than 0.5
and a width consistent with unity.

Thus, any possible systematic bias from the choice of the functional form in
the region of low background is proven to be small compared to the statistical
uncertainty from the accuracy of the measurements. In the region of large
background, the uncertainty in the signal efficiency (discussed in Section
0.5) completely dominates the effect of the background uncertainty on the
limits. Thus we assign the statistical uncertainty in the fits as the only
uncertainty in the background predictions. The observed $m_{\Z\gamma}$
invariant mass spectra in the signal region
($75<m_{\mathrm{J}}^{\text{pruned}}<105\GeV$) for the b-tagged,
$\tau_{21}$-tagged, and untagged categories, along with the corresponding
fits, are shown in Fig. 2.

Figure 2: Observed $m_{\Z\gamma}$ invariant mass spectra in the
$\mathrm{J}\gamma$ channel in the b-tagged (left), $\tau_{21}$-tagged
(center), and untagged (right) categories. The best fits to the background-
only hypotheses are represented by the red lines, with their 68% CL
uncertainty bands given by the gray shadings. Several narrow and broad signal
benchmarks with arbitrary normalization are shown on top of the background
prediction with the dashed lines. The lower panels show the difference between
the data and the fits, divided by the uncertainty, which includes the
statistical uncertainties in the data and the fit. For bins with a small
number of entries, the error bars correspond to the Garwood confidence
intervals [77].

###  0.4.2 Signal modeling

The signal distribution in $m_{\Z\gamma}$ is obtained from the generated
events that pass the full selection. The signal shape is parametrized with a
Gaussian core and two power-law tails, namely an extended form of the Crystal
Ball (CB) function [78]. We find this functional form to provide an adequate
description for both narrow and broad signals in the entire mass range used in
the analysis. To derive the signal shapes for the intermediate mass values
where simulation points are not available, a linear morphing [79] of the
shapes obtained from the simulation is used. The typical mass resolution for
narrow-width signal events is 1% for the $\Pe\Pe\gamma$ channel, 1–2% for the
$\Pgm\Pgm\gamma$ channel, depending on the mass of the resonance, and 3% in
the $\mathrm{J}\gamma$ channel.

The product of signal acceptance and efficiency for a narrow resonance in the
$\Pe\Pe\gamma$ ($\Pgm\Pgm\gamma$) channel rises from about 27 (42)% at
$m_{\Z\gamma}=0.35$to about 46 (55)% at $m_{\Z\gamma}=2$, and remains steady
until 4. In the $\mathrm{J}\gamma$ channel, the product of signal acceptance
and efficiency for narrow resonances increases from 7 (3)% at 0.65to 9 (9)% at
4in the untagged ($\tau_{21}$-tagged) category, and is between 2 and 3% for
the b-tagged category for the resonance masses between 0.65 and 4.

For a broad resonance the product of signal acceptance and efficiency is
similar to the narrow-resonance case up to 2. At large resonance masses
($>$2), however, the effect of rapidly falling PDFs introduces a lower tail in
the signal mass distribution. The exact characteristics of this tail are quite
sensitive to the resonant line shape. We therefore truncate the mass
distribution of the resonance to correspond to the core of the line shape,
defined as a window centered on the maximum of the CB function with a width
given by $\pm$5 times the CB function parameter $\sigma$, describing the
standard deviation of its Gaussian core. The tails outside this window are
conservatively discarded in the signal acceptance calculations and when
fitting the data. As a result, the product of signal acceptance and efficiency
falls to 2% at 4for the $\Pe\Pe\gamma$ and $\Pgm\Pgm\gamma$ events, to 0.2% in
the untagged and $\tau_{21}$-tagged categories, and to $<$0.1% in the b-tagged
category.

##  0.5 Systematic uncertainties

The statistical uncertainty in the fits of the background function to data is
taken for the background uncertainty in all channels.

The following systematic uncertainties in the signal are defined below, and
summarized in Table 0.5:

  * •

Integrated luminosity: the uncertainty in the CMS integrated luminosity is
based on cluster counting in the silicon pixel detector and amounts to 2.5%
[80].

  * •

PDFs: a 1.0–3.5% uncertainty in the signal efficiency that takes into account
the variation in the kinematic acceptance of the analysis is estimated using
replicas of the NNPDF3.0 set, following the PDF4LHC prescription [81]. The
uncertainty in the signal cross section due to the PDF choice is not
considered.

  * •

Pileup: the uncertainty due to the pileup description in the signal
simulation, evaluated by changing the total inelastic cross section governing
the average multiplicity of pileup interactions by $\pm$5.0% [82], translates
to a 1.0% uncertainty in the signal acceptance in all channels.

  * •

Trigger: the uncertainty due to the trigger efficiency differences in data and
simulation in the $\ell\ell\gamma$ analysis is estimated with dedicated
studies with leptons from $\PZ$ boson decays and amounts to 1.0 (3.5)% for the
$\Pe\Pe\gamma$ ($\Pgm\Pgm\gamma$) channel. In the $\mathrm{J}\gamma$ channel,
a 2.0% uncertainty covers the variation of the trigger efficiency across the
mass range probed in the analysis.

  * •

Photon efficiency: the systematic uncertainty due to the differences in the
photon identification efficiency between data and simulation is evaluated with
$\PZ\to\Pe\Pe$ events in which the electrons are used as proxies for photons,
and amounts to 1.5% [60].

  * •

Lepton efficiency: the systematic uncertainty due to the differences in the
lepton identification efficiency in data and simulation is evaluated with
$\PZ\to\Pe\Pe$ ($\mu\mu$) events and amounts to 2.5 (2.0)% in the
$\Pe\Pe\gamma$ ($\Pgm\Pgm\gamma$) channel.

  * •

b tagging efficiency: the uncertainty due to the difference in the b tagging
efficiency in data and simulation is estimated from control samples in data
and simulation enriched in b quarks [71], and translates into a 15–32%
uncertainty in the signal yield in the $\mathrm{J}\gamma$ channel. It is
anticorrelated between the b-tagged and the other two categories, as it
induces signal migration between the categories.

  * •

${\tau}_{21}$ tagging efficiency: to account for the difference between the
$\tau_{21}$ distributions in data and simulation, a scale factor of $0.97\pm
0.06$ [69] is introduced for simulated signal samples. This translates into an
uncertainty of 10–12% in the signal yield in the $\tau_{21}$-tagged category
and is anticorrelated with that in the untagged category.

  * •

Electron and photon energy scale and resolution: the electron and photon
energy scale is known with 0.1–5.0% precision, depending on the energy. This
uncertainty is based on the accuracy of the energy scale at the $\PZ$ boson
peak and its extrapolation to higher masses, and translates into a 0.2–4.6
(0.1–2.3)% correlated uncertainty in the $m_{\Z\gamma}$ scale in the
$\Pe\Pe\gamma$ channel ($\Pgm\Pgm\gamma$ and $\mathrm{J}\gamma$ channels). The
uncertainty in the electron and photon energy resolution based on the Gaussian
smearing evaluated at the boson peak translates to a 10 (5)% uncertainty in
the $m_{\Z\gamma}$ resolution in the $\Pe\Pe\gamma$ channel ($\Pgm\Pgm\gamma$
and $\mathrm{J}\gamma$ channels).

  * •

Muon momentum scale and resolution: the muon momentum scale is measured with
0.1–5.0% precision up to $\pt=200$, with an additional 0.1–6.0% uncertainty at
higher values, resulting in a 0.1–4.6% uncertainty in the $m_{\Z\gamma}$ mass
scale in the $\Pgm\Pgm\gamma$ channel. A 10% uncertainty in the $m_{\Z\gamma}$
resolution in the $\Pgm\Pgm\gamma$ channel is conservatively assigned to
account for the uncertainty in the muon momentum resolution.

  * •

Jet energy scale (JES), jet mass scale (JMS), jet energy resolution (JER), and
jet mass resolution (JMR): the uncertainties [61, 62, 66] are propagated to
all the relevant quantities, and affect both the signal yield and its shape.
The overall effect of these uncertainties added in quadrature corresponds to
approximately 5.0% uncertainty in the signal yield, as determined by changing
the four-momenta of the jets accordingly and carrying out the full analysis
with the modified quantities.

Summary of the systematic uncertainties in the signal yield (upper part of the
table) or shape (lower part of the table). A dash indicates that the
uncertainty does not apply.  Source $\Pe\Pe\gamma$ $\Pgm\Pgm\gamma$ b-tagged
$\tau_{21}$-tagged Untagged Integrated luminosity 2.5% 2.5% 2.5% 2.5% 2.5%
PDFs 1–3.5% 1–3.5% 1–3.5% 1–3.5% 1–3.5% Pileup 1% 1% 1% 1% 1% Trigger 1% 3.5%
2% 2% 2% Photon efficiency 1.5% 1.5% 1.5% 1.5% 1.5% Lepton efficiency 2.5% 2%
— — — b tagging efficiency — — 15–32% anticorr. anticorr. $\tau_{21}$ tagging
efficiency — — — 10–12% anticorr. e/$\Pgg$ energy scale 0.2–4.6% 0.1–2.3%
0.1–2.3% 0.1–2.3% 0.1–2.3% e/$\Pgg$ energy resolution 10% 5% 5% 5% 5% Muon
momentum scale — 0.1–4.6% — — — Muon momentum resolution — 10% — — — JES and
JER — — 3.2% 3.2% 3.2% JMS and JMR — — 4.1% 4.1% 4.1%

##  0.6 Results

The data are consistent with the background-only expectations in all channels.
We set upper limits on the production cross section of heavy spin-0 resonances
using the asymptotic approximation [83] of the modified frequentist CLs method
[84, 85, 86], with a likelihood ratio used as a test statistic, and
uncertainties incorporated as nuisance parameters with log-normal
(normalization) or Gaussian (shape) priors. The limits are set in the mass
range between 0.35 (0.30) and 4.0in the $\Pe\Pe\gamma$ ($\Pgm\Pgm\gamma$)
channel and 0.65–4.0in the $\mathrm{J}\gamma$ channel. We note that the
asymptotic approximation tends to produce lower cross section limits than the
exact CLs calculations in the regions with low background. We tested that the
difference is at most 4 (30%) for resonance masses below 1 TeV (around 3 TeV).

###  0.6.1 The $\ell\ell\gamma$ channels

Figure 3: Observed (solid) and expected (dashed) 95% CL upper limits on
$\sigma(\mathrm{X}\to\PZ\Pgg)\,\mathcal{B}(\PZ\to\ell\ell\Pgg)$, as a function
of signal mass $m_{\mathrm{X}}$ for the $\Pe\Pe\gamma$ (left column) and
$\Pgm\Pgm\gamma$ (right column) channels, and for narrow (upper row) and broad
(lower row) spin-0 resonances. The green and yellow shaded bands correspond to
respective 68 and 95% CL ranges in the expected limits for the background-only
hypothesis.

Figure 4: Observed (solid) and expected (dashed) 95% CL upper limits on
$\sigma(\mathrm{X}\to\PZ\Pgg)$ as a function of signal mass $m_{\mathrm{X}}$,
together with the 68% (green) and 95% (yellow) CL ranges of the expected limit
for the background-only hypothesis, for the combination of the $\Pe\Pe\gamma$
and $\Pgm\Pgm\gamma$ channels for (left) narrow and (right) broad spin-0
resonances.

Figure 3 shows the observed and expected 95% CL upper limits on the product of
signal cross section and branching fraction to the $\ell\ell\gamma$ final
state, $\sigma(\mathrm{X}\to\PZ\Pgg)\,\mathcal{B}(\PZ\to\ell\ell\Pgg)$, as a
function of the resonance mass, for the $\Pe\Pe\gamma$ channel (left column)
and the $\Pgm\Pgm\gamma$ channel (right column), for narrow (upper row) and
broad (lower row) resonances. The expected limits for the background-only
hypothesis are represented by the dashed black lines, and their 68 and 95% CL
ranges are shown with the green and yellow bands, respectively. The observed
limits are represented by the solid black lines. The highest observed
deviation is found in the $\Pgm\Pgm\gamma$ channel at the mass of
approximately 350and corresponds to a local (global) significance of
approximately 3.0 (2.1) standard deviations for a narrow resonance. The limits
on $\sigma(\mathrm{X}\to\PZ\Pgg)$, obtained by combining the two leptonic
search channels and taking into account the leptonic branching fraction of the
Z boson decays [87], are shown in Fig. 4. The rapid increase in the limit for
a broad resonance with a mass above approximately 3is due to a significant
low-mass tail in the resonance line-shape extending outside the truncation
window, as discussed in Section 0.4.2.

###  0.6.2 The $\mathrm{J}\gamma$ channel

The observed and expected 95% CL upper limits on the product of signal cross
section and branching fraction in the $\PZ\Pgg$ channel,
$\sigma(\mathrm{X}\to\PZ\Pgg)$ for narrow and broad resonances in the
b-tagged, $\tau_{21}$-tagged, and untagged categories are presented in Fig. 5.
The results based on the combination of the three categories for both narrow
and broad resonances are shown in Fig. 6. The combination includes the
(anti)correlation of systematic uncertainties between the three categories. We
observe a small deviation at a mass $\approx$2with local significance of 2.7
(3.6) standard deviations for the narrow (broad) resonance width hypothesis.
The global significance of this excess is 1.8 (2.8) standard deviations.

Figure 5: Observed (solid) and expected (dashed) 95% CL upper limits on
$\sigma(\mathrm{X}\to\PZ\Pgg)$, as a function of signal mass $m_{\mathrm{X}}$,
for the b-tagged (left column), $\tau_{21}$-tagged (middle column), and
untagged (right column) categories, and for narrow (upper row) and broad
(lower row) spin-0 resonances. The colored bands correspond to the 68% (green)
and 95% (yellow) CL ranges of the expected limit for the background-only
hypothesis.

Figure 6: Observed (solid) and expected (dashed) 95% CL upper limits on
$\sigma(\mathrm{X}\to\PZ\Pgg)$ as a function of signal mass $m_{\mathrm{X}}$,
together with the 68% (green) and 95% (yellow) CL ranges of the expected limit
for the background-only hypothesis, for the combination of the b-tagged,
$\tau_{21}$-tagged, and untagged categories for (left) narrow and (right)
broad spin-0 resonances.

Figure 7: Observed and expected limits on the product of the production cross
section and branching fraction $\mathcal{B}(\mathrm{X}\to\PZ\Pgg)$, as a
function of signal mass $m_{\mathrm{X}}$, for (left) narrow and (right) broad
spin-0 resonances, obtained from the combination of the leptonic and hadronic
decay channels.

###  0.6.3 Combination of the $\ell\ell\gamma$ and $\mathrm{J}\gamma$ channels

The results based on the combination of the $\ell\ell\gamma$ and
$\mathrm{J}\gamma$ channels are shown in Fig. 7, assuming uncorrelated
uncertainties between the leptonic and hadronic channels, except for the
uncertainties in the integrated luminosity, PDFs, and photon energy scale,
which are taken as fully correlated among all the channels. These are the most
stringent limits on resonances decaying in the $\PZ\Pgg$ channel to date in
the mass range probed.

##  0.7 Summary

A search is presented for resonances decaying to a $\PZ$ boson and a photon.
The analysis is based on data from proton-proton collisions at a center-of-
mass energy of 13, corresponding to an integrated luminosity of 35.9,
collected with the CMS detector at the LHC in 2016. Two decay modes of the
$\PZ$ boson are investigated. In the leptonic channels, the Z boson candidates
are reconstructed using electron or muon pairs. In the hadronic channels, they
are identified using a large-radius jet, containing either light-quark or b
quark decay products of the $\PZ$ boson, via jet substructure and advanced b
tagging techniques. The results from these channels are combined and
interpreted in terms of upper limits on the product of the production cross
section and the branching fraction to $\PZ\gamma$ for narrow (broad) spin-0
resonances with masses between 0.35 and 4.0, ranging from 50 (100) to 0.3
(1.5)fb. These are the most stringent limits on such resonances to date.

###### Acknowledgements.

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

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##  .8 The CMS Collaboration

Yerevan Physics Institute, Yerevan, Armenia
A.M. Sirunyan, A. Tumasyan Institut für Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, E. Brondolin, M.
Dragicevic, J. Erö, 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, W.
Waltenberger, J. Wittmann, C.-E. Wulz1, M. Zarucki Institute for Nuclear
Problems, Minsk, Belarus
V. Chekhovsky, V. Mossolov, J. Suarez Gonzalez Universiteit Antwerpen,
Antwerpen, Belgium
E.A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, M. Van De Klundert, H. Van
Haevermaet, P. Van Mechelen, N. Van Remortel Vrije Universiteit Brussel,
Brussel, Belgium
S. Abu Zeid, F. Blekman, J. D’Hondt, I. De Bruyn, J. De Clercq, K. Deroover,
G. Flouris, D. Lontkovskyi, S. Lowette, I. Marchesini, S. Moortgat, L.
Moreels, Q. Python, K. Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders,
I. Van Parijs Université Libre de Bruxelles, Bruxelles, Belgium
D. Beghin, B. Bilin, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, B.
Dorney, G. Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk, T. Lenzi, J.
Luetic, T. Maerschalk, A. Marinov, T. Seva, E. Starling, C. Vander Velde, P.
Vanlaer, D. Vannerom, R. Yonamine, F. Zenoni, F. Zhang2 Ghent University,
Ghent, Belgium
A. Cimmino, T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov3, D.
Poyraz, C. Roskas, S. Salva, M. Tytgat, W. Verbeke, N. Zaganidis Université
Catholique de Louvain, Louvain-la-Neuve, Belgium
H. Bakhshiansohi, O. Bondu, S. Brochet, G. Bruno, C. Caputo, A. Caudron, P.
David, S. De Visscher, C. Delaere, M. Delcourt, B. Francois, A. Giammanco, M.
Komm, G. Krintiras, V. Lemaitre, A. Magitteri, A. Mertens, M. Musich, K.
Piotrzkowski, L. Quertenmont, A. Saggio, M. Vidal Marono, S. Wertz, J. Zobec
Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil
W.L. Aldá Júnior, F.L. Alves, G.A. Alves, L. Brito, M. Correa Martins Junior,
C. Hensel, A. Moraes, M.E. Pol, P. Rebello Teles Universidade do Estado do Rio
de Janeiro, Rio de Janeiro, Brazil
E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato4, E. Coelho, E.M.
Da Costa, G.G. Da Silveira5, D. De Jesus Damiao, S. Fonseca De Souza, L.M.
Huertas Guativa, H. Malbouisson, M. Melo De Almeida, C. Mora Herrera, L.
Mundim, H. Nogima, L.J. Sanchez Rosas, A. Santoro, A. Sznajder, M. Thiel, E.J.
Tonelli Manganote4, F. Torres Da Silva De Araujo, A. Vilela Pereira
Universidade Estadual Paulista a, Universidade Federal do ABC b, São Paulo,
Brazil
S. Ahujaa, C.A. Bernardesa, T.R. Fernandez Perez Tomeia, E.M. Gregoresb, P.G.
Mercadanteb, S.F. Novaesa, Sandra S. Padulaa, D. Romero Abadb, J.C. Ruiz
Vargasa Institute for Nuclear Research and Nuclear Energy, Bulgarian Academy
of Sciences, Sofia, Bulgaria
A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Misheva, M. Rodozov, M. Shopova,
G. Sultanov University of Sofia, Sofia, Bulgaria
A. Dimitrov, L. Litov, B. Pavlov, P. Petkov Beihang University, Beijing, China
W. Fang6, X. Gao6, L. Yuan Institute of High Energy Physics, Beijing, China
M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D.
Leggat, H. Liao, Z. Liu, F. Romeo, S.M. Shaheen, A. Spiezia, J. Tao, C. Wang,
Z. Wang, E. Yazgan, H. Zhang, S. Zhang, J. Zhao State Key Laboratory of
Nuclear Physics and Technology, Peking University, Beijing, China
Y. Ban, G. Chen, 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, J.D. Ruiz Alvarez, M.A. Segura Delgado University of
Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval
Architecture, Split, Croatia
B. Courbon, N. Godinovic, D. Lelas, I. Puljak, P.M. Ribeiro Cipriano, T.
Sculac University of Split, Faculty of Science, Split, Croatia
Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia
V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, A. 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
E. El-khateeb9, S. Elgammal10, A. Mohamed11 National Institute of Chemical
Physics and Biophysics, Tallinn, Estonia
R.K. Dewanjee, M. Kadastik, L. Perrini, M. Raidal, A. Tiko, C. Veelken
Department of Physics, University of Helsinki, Helsinki, Finland
P. Eerola, H. Kirschenmann, J. Pekkanen, M. Voutilainen Helsinki Institute of
Physics, Helsinki, Finland
J. Havukainen, J.K. Heikkilä, T. Järvinen, V. Karimäki, R. Kinnunen, T.
Lampén, K. Lassila-Perini, S. Laurila, S. Lehti, T. Lindén, P. Luukka, H.
Siikonen, E. Tuominen, J. Tuominiemi Lappeenranta University of Technology,
Lappeenranta, Finland
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, P. Gras, G. Hamel de Monchenault, P. Jarry, I. Kucher, C.
Leloup, E. Locci, M. Machet, J. Malcles, G. Negro, J. Rander, A. Rosowsky,
M.Ö. Sahin, M. Titov Laboratoire Leprince-Ringuet, Ecole polytechnique,
CNRS/IN2P3, Université Paris-Saclay, Palaiseau, France
A. Abdulsalam, C. Amendola, I. Antropov, S. Baffioni, F. Beaudette, P. Busson,
L. Cadamuro, C. Charlot, R. Granier de Cassagnac, M. Jo, S. Lisniak, A.
Lobanov, J. Martin Blanco, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P.
Pigard, R. Salerno, J.B. Sauvan, Y. Sirois, A.G. Stahl Leiton, T. Strebler, Y.
Yilmaz, A. Zabi, A. Zghiche Université de Strasbourg, CNRS, IPHC UMR 7178,
F-67000 Strasbourg, France
J.-L. Agram12, J. Andrea, D. Bloch, J.-M. Brom, M. Buttignol, E.C. Chabert, N.
Chanon, C. Collard, E. Conte12, X. Coubez, J.-C. Fontaine12, D. Gelé, U.
Goerlach, M. Jansová, A.-C. Le Bihan, N. Tonon, P. Van Hove Centre de Calcul
de l’Institut National de Physique Nucleaire et de Physique des Particules,
CNRS/IN2P3, Villeurbanne, France
S. Gadrat Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3,
Institut de Physique Nucléaire de Lyon, Villeurbanne, France
S. Beauceron, C. Bernet, G. Boudoul, R. Chierici, D. Contardo, P. Depasse, H.
El Mamouni, J. Fay, L. Finco, S. Gascon, M. Gouzevitch, G. Grenier, B. Ille,
F. Lagarde, I.B. Laktineh, M. Lethuillier, L. Mirabito, A.L. Pequegnot, S.
Perries, A. Popov13, V. Sordini, M. Vander Donckt, S. Viret Georgian Technical
University, Tbilisi, Georgia
A. Khvedelidze8 Tbilisi State University, Tbilisi, Georgia
D. Lomidze RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany
C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, C.
Schomakers, J. Schulz, M. Teroerde, V. Zhukov13 RWTH Aachen University, III.
Physikalisches Institut A, Aachen, Germany
A. Albert, E. Dietz-Laursonn, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg,
T. Esch, R. Fischer, A. Güth, M. Hamer, T. Hebbeker, C. Heidemann, K.
Hoepfner, S. Knutzen, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, T.
Pook, M. Radziej, H. Reithler, M. Rieger, F. Scheuch, D. Teyssier, S. Thüer
RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany
G. Flügge, B. Kargoll, T. Kress, A. Künsken, T. Müller, A. Nehrkorn, A.
Nowack, C. Pistone, O. Pooth, A. Stahl14 Deutsches Elektronen-Synchrotron,
Hamburg, Germany
M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, K. Beernaert, O. Behnke, U.
Behrens, A. Bermúdez Martínez, A.A. Bin Anuar, K. Borras15, V. Botta, A.
Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G.
Eckerlin, D. Eckstein, T. Eichhorn, E. Eren, E. Gallo16, J. Garay Garcia, A.
Geiser, J.M. Grados Luyando, A. Grohsjean, P. Gunnellini, M. Guthoff, A. Harb,
J. Hauk, M. Hempel17, H. Jung, M. Kasemann, J. Keaveney, C. Kleinwort, I.
Korol, D. Krücker, W. Lange, A. Lelek, T. Lenz, J. Leonard, K. Lipka, W.
Lohmann17, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, G. Mittag, J. Mnich,
A. Mussgiller, E. Ntomari, D. Pitzl, A. Raspereza, M. Savitskyi, P. Saxena, R.
Shevchenko, S. Spannagel, N. Stefaniuk, G.P. Van Onsem, R. Walsh, Y. Wen, K.
Wichmann, C. Wissing, O. Zenaiev University of Hamburg, Hamburg, Germany
R. Aggleton, S. Bein, V. Blobel, M. Centis Vignali, T. Dreyer, E. Garutti, D.
Gonzalez, J. Haller, A. Hinzmann, M. Hoffmann, A. Karavdina, R. Klanner, R.
Kogler, N. Kovalchuk, S. Kurz, T. Lapsien, D. Marconi, M. Meyer, M. Niedziela,
D. Nowatschin, F. Pantaleo14, T. Peiffer, A. Perieanu, C. Scharf, P. Schleper,
A. Schmidt, S. Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G. Steinbrück,
F.M. Stober, M. Stöver, H. Tholen, D. Troendle, E. Usai, A. Vanhoefer, B.
Vormwald Institut für Experimentelle Kernphysik, Karlsruhe, Germany
M. Akbiyik, C. Barth, M. Baselga, S. Baur, E. Butz, R. Caspart, T. Chwalek, F.
Colombo, W. De Boer, A. Dierlamm, N. Faltermann, B. Freund, R. Friese, M.
Giffels, M.A. Harrendorf, F. Hartmann14, S.M. Heindl, U. Husemann, F.
Kassel14, S. Kudella, H. Mildner, M.U. Mozer, Th. Müller, M. Plagge, G. Quast,
K. Rabbertz, M. Schröder, I. Shvetsov, G. Sieber, H.J. Simonis, R. Ulrich, S.
Wayand, M. Weber, T. Weiler, S. Williamson, C. Wöhrmann, R. Wolf Institute of
Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece
G. Anagnostou, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas, I. Topsis-
Giotis National and Kapodistrian University of Athens, Athens, Greece
G. Karathanasis, S. Kesisoglou, A. Panagiotou, N. Saoulidou National Technical
University of Athens, Athens, Greece
K. Kousouris University of Ioánnina, Ioánnina, Greece
I. Evangelou, C. Foudas, P. Gianneios, P. Katsoulis, P. Kokkas, S. Mallios, N.
Manthos, I. Papadopoulos, E. Paradas, J. Strologas, F.A. Triantis, D.
Tsitsonis MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
M. Csanad, N. Filipovic, G. Pasztor, O. Surányi, G.I. Veres18 Wigner Research
Centre for Physics, Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath19, Á. Hunyadi, F. Sikler, V. Veszpremi
Institute of Nuclear Research ATOMKI, Debrecen, Hungary
N. Beni, S. Czellar, J. Karancsi20, A. Makovec, J. Molnar, Z. Szillasi
Institute of Physics, University of Debrecen, Debrecen, Hungary
M. Bartók18, P. Raics, Z.L. Trocsanyi, B. Ujvari Indian Institute of Science
(IISc), Bangalore, India
S. Choudhury, J.R. Komaragiri National Institute of Science Education and
Research, Bhubaneswar, India
S. Bahinipati21, S. Bhowmik, P. Mal, K. Mandal, A. Nayak22, D.K. Sahoo21, N.
Sahoo, S.K. Swain Panjab University, Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, N. Dhingra, A.K. Kalsi, A.
Kaur, M. Kaur, S. Kaur, R. Kumar, P. Kumari, A. Mehta, J.B. Singh, G. Walia
University of Delhi, Delhi, India
A. Bhardwaj, S. Chauhan, B.C. Choudhary, R.B. Garg, S. Keshri, A. Kumar, Ashok
Kumar, S. Malhotra, M. Naimuddin, K. Ranjan, Aashaq Shah, R. Sharma Saha
Institute of Nuclear Physics, HBNI, Kolkata, India
R. Bhardwaj, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep, S. Dey, S. Dutt,
S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S.
Nandan, A. Purohit, A. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur
Indian Institute of Technology Madras, Madras, India
P.K. Behera Bhabha Atomic Research Centre, Mumbai, India
R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty14, P.K. Netrakanti,
L.M. Pant, P. Shukla, A. Topkar Tata Institute of Fundamental Research-A,
Mumbai, India
T. Aziz, S. Dugad, B. Mahakud, S. Mitra, G.B. Mohanty, N. Sur, B. Sutar Tata
Institute of Fundamental Research-B, Mumbai, India
S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, Sa. Jain, S.
Kumar, M. Maity23, G. Majumder, K. Mazumdar, T. Sarkar23, N. Wickramage24
Indian Institute of Science Education and Research (IISER), Pune, India
S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, S.
Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
S. Chenarani25, E. Eskandari Tadavani, S.M. Etesami25, M. Khakzad, M.
Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi26, F. Rezaei
Hosseinabadi, B. Safarzadeh27, M. Zeinali University College Dublin, Dublin,
Ireland
M. Felcini, M. Grunewald INFN Sezione di Bari a, Università di Bari b,
Politecnico di Bari c, Bari, Italy
M. Abbresciaa,b, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L. Cristellaa,b,
N. De Filippisa,c, M. De Palmaa,b, F. Erricoa,b, L. Fiorea, G. Iasellia,c, S.
Lezkia,b, G. Maggia,c, M. Maggia, G. Minielloa,b, S. Mya,b, S. Nuzzoa,b, A.
Pompilia,b, G. Pugliesea,c, R. Radognaa, A. Ranieria, G. Selvaggia,b, A.
Sharmaa, L. Silvestrisa,14, R. Vendittia, P. Verwilligena INFN Sezione di
Bologna a, Università di Bologna b, Bologna, Italy
G. Abbiendia, C. Battilanaa,b, D. Bonacorsia,b, L. Borgonovia,b, S. Braibant-
Giacomellia,b, R. Campaninia,b, P. Capiluppia,b, A. Castroa,b, F.R. Cavalloa,
S.S. Chhibraa, G. Codispotia,b, M. Cuffiania,b, G.M. Dallavallea, F. Fabbria,
A. Fanfania,b, D. Fasanellaa,b, P. Giacomellia, C. Grandia, L. Guiduccia,b, S.
Marcellinia, G. Masettia, A. Montanaria, F.L. Navarriaa,b, A. Perrottaa, A.M.
Rossia,b, T. Rovellia,b, G.P. Sirolia,b, N. Tosia INFN Sezione di Catania a,
Università di Catania b, Catania, Italy
S. Albergoa,b, S. Costaa,b, A. Di Mattiaa, F. Giordanoa,b, R. Potenzaa,b, A.
Tricomia,b, C. Tuvea,b INFN Sezione di Firenze a, Università di Firenze b,
Firenze, Italy
G. Barbaglia, K. Chatterjeea,b, V. Ciullia,b, C. Civininia, R.
D’Alessandroa,b, E. Focardia,b, P. Lenzia,b, M. Meschinia, S. Paolettia, L.
Russoa,28, G. Sguazzonia, D. Stroma, L. Viliania,b,14 INFN Laboratori
Nazionali di Frascati, Frascati, Italy
L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera14 INFN Sezione di
Genova a, Università di Genova b, Genova, Italy
V. Calvellia,b, F. Ferroa, 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,14, 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,29, S. Ragazzia,b, T.
Tabarelli de Fatisa,b INFN Sezione di Napoli a, Università di Napoli ’Federico
II’ b, Napoli, Italy, Università della Basilicata c, Potenza, Italy,
Università G. Marconi d, Roma, Italy
S. Buontempoa, N. Cavalloa,c, S. Di Guidaa,d,14, F. Fabozzia,c, F. Fiengaa,b,
A.O.M. Iorioa,b, W.A. Khana, L. Listaa, S. Meolaa,d,14, P. Paoluccia,14, C.
Sciaccaa,b, F. Thyssena INFN Sezione di Padova a, Università di Padova b,
Padova, Italy, Università di Trento c, Trento, Italy
P. Azzia, N. Bacchettaa, L. Benatoa,b, A. Bolettia,b, R. Carlina,b, A.
Carvalho Antunes De Oliveiraa,b, M. Dall’Ossoa,b, P. De Castro Manzanoa, T.
Dorigoa, U. Dossellia, S. Fantinela, U. Gasparinia,b, A. Gozzelinoa, S.
Lacapraraa, P. Lujan, M. Margonia,b, A.T. Meneguzzoa,b, N. Pozzobona,b, P.
Ronchesea,b, R. Rossina,b, F. Simonettoa,b, E. Torassaa, S. Venturaa, M.
Zanettia,b, P. Zottoa,b, G. Zumerlea,b INFN Sezione di Pavia a, Università di
Pavia b, Pavia, Italy
A. Braghieria, A. Magnania, P. Montagnaa,b, S.P. Rattia,b, V. Rea, M.
Ressegottia,b, C. Riccardia,b, P. Salvinia, I. Vaia,b, P. Vituloa,b INFN
Sezione di Perugia a, Università di Perugia b, Perugia, Italy
L. Alunni Solestizia,b, M. Biasinia,b, G.M. Bileia, C. Cecchia,b, D.
Ciangottinia,b, L. Fanòa,b, R. Leonardia,b, E. Manonia, G. Mantovania,b, V.
Mariania,b, M. Menichellia, A. Rossia,b, A. Santocchiaa,b, D. Spigaa INFN
Sezione di Pisa a, Università di Pisa b, Scuola Normale Superiore di Pisa c,
Pisa, Italy
K. Androsova, P. Azzurria,14, G. Bagliesia, T. Boccalia, L. Borrello, R.
Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, G. Fedia, L. Gianninia,c, A.
Giassia, M.T. Grippoa,28, F. Ligabuea,c, T. Lomtadzea, E. Mancaa,c, G.
Mandorlia,c, A. Messineoa,b, F. Pallaa, A. Rizzia,b, A. Savoy-Navarroa,30, P.
Spagnoloa, R. Tenchinia, G. Tonellia,b, A. Venturia, P.G. Verdinia INFN
Sezione di Roma a, Sapienza Università di Roma b, Rome, Italy
L. Baronea,b, F. Cavallaria, M. Cipriania,b, N. Dacia, D. Del Rea,b,14, E. Di
Marcoa,b, M. Diemoza, S. Gellia,b, E. Longoa,b, F. Margarolia,b, B.
Marzocchia,b, P. Meridiania, G. Organtinia,b, R. Paramattia,b, F. Preiatoa,b,
S. Rahatloua,b, C. Rovellia, F. Santanastasioa,b INFN Sezione di Torino a,
Università di Torino b, Torino, Italy, Università del Piemonte Orientale c,
Novara, Italy
N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, N. Bartosika,
R. Bellana,b, C. Biinoa, N. Cartigliaa, F. Cennaa,b, M. Costaa,b, R.
Covarellia,b, A. Deganoa,b, N. Demariaa, B. Kiania,b, C. Mariottia, S.
Masellia, E. Migliorea,b, V. Monacoa,b, E. Monteila,b, M. Montenoa, M.M.
Obertinoa,b, L. Pachera,b, N. Pastronea, M. Pelliccionia, G.L. Pinna
Angionia,b, A. Romeroa,b, M. Ruspaa,c, R. Sacchia,b, K. Shchelinaa,b, V.
Solaa, A. Solanoa,b, A. Staianoa, P. Traczyka,b INFN Sezione di Trieste a,
Università di Trieste b, Trieste, Italy
S. Belfortea, M. Casarsaa, F. Cossuttia, G. Della Riccaa,b, A. Zanettia
Kyungpook National University, Daegu, Korea
D.H. Kim, G.N. Kim, M.S. Kim, J. Lee, S. Lee, S.W. Lee, C.S. Moon, Y.D. Oh, S.
Sekmen, D.C. Son, Y.C. Yang Chonbuk National University, Jeonju, Korea
A. Lee Chonnam National University, Institute for Universe and Elementary
Particles, Kwangju, Korea
H. Kim, D.H. Moon, G. Oh Hanyang University, Seoul, Korea
J.A. Brochero Cifuentes, J. Goh, T.J. Kim Korea University, Seoul, Korea
S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, Y. Kim, K. Lee, K.S.
Lee, S. Lee, J. Lim, S.K. Park, Y. Roh Seoul National University, Seoul, Korea
J. Almond, J. Kim, J.S. Kim, H. Lee, K. Lee, K. Nam, S.B. Oh, B.C. Radburn-
Smith, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu University of Seoul, Seoul,
Korea
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 Ali31, F. Mohamad Idris32, W.A.T. Wan
Abdullah, M.N. Yusli, Z. Zolkapli Centro de Investigacion y de Estudios
Avanzados del IPN, Mexico City, Mexico
Duran-Osuna, M. C., H. Castilla-Valdez, E. De La Cruz-Burelo, Ramirez-Sanchez,
G., I. Heredia-De La Cruz33, Rabadan-Trejo, R. I., R. Lopez-Fernandez, J.
Mejia Guisao, Reyes-Almanza, R, A. Sanchez-Hernandez Universidad
Iberoamericana, Mexico City, Mexico
S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita
Universidad Autonoma de Puebla, Puebla, Mexico
J. Eysermans, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad
Autónoma de San Luis Potosí, San Luis Potosí, Mexico
A. Morelos Pineda University of Auckland, Auckland, New Zealand
D. Krofcheck University of Canterbury, Christchurch, New Zealand
P.H. Butler National Centre for Physics, Quaid-I-Azam University, Islamabad,
Pakistan
A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, A. Saddique, M.A. Shah, M.
Shoaib, M. Waqas National Centre for Nuclear Research, Swierk, Poland
H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Górski, M. Kazana, K.
Nawrocki, M. Szleper, P. Zalewski Institute of Experimental Physics, Faculty
of Physics, University of Warsaw, Warsaw, Poland
K. Bunkowski, A. Byszuk34, 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
V. Alexakhin, P. Bunin, M. Gavrilenko, A. Golunov, I. Golutvin, N. Gorbounov,
A. Kamenev, V. Karjavin, A. Lanev, A. Malakhov, V. Matveev35,36, V. Palichik,
V. Perelygin, M. Savina, S. Shmatov, S. Shulha, V. Smirnov, A. Zarubin
Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia
Y. Ivanov, V. Kim37, E. Kuznetsova38, 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, M. Toms, E. Vlasov, A. Zhokin Moscow
Institute of Physics and Technology, Moscow, Russia
T. Aushev, A. Bylinkin36 National Research Nuclear University ’Moscow
Engineering Physics Institute’ (MEPhI), Moscow, Russia
M. Chadeeva39, P. Parygin, D. Philippov, S. Polikarpov, E. Popova, V. Rusinov
P.N. Lebedev Physical Institute, Moscow, Russia
V. Andreev, M. Azarkin36, I. Dremin36, M. Kirakosyan36, A. Terkulov Skobeltsyn
Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow,
Russia
A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin40, L. Dudko, A.
Ershov, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, M.
Perfilov, S. Petrushanko, V. Savrin Novosibirsk State University (NSU),
Novosibirsk, Russia
V. Blinov41, D. Shtol41, Y. Skovpen41 State Research Center of Russian
Federation, Institute for High Energy Physics, Protvino, Russia
I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, A. Godizov, V. Kachanov,
A. Kalinin, D. Konstantinov, P. Mandrik, V. Petrov, R. Ryutin, A. Sobol, S.
Troshin, N. Tyurin, A. Uzunian, A. Volkov University of Belgrade, Faculty of
Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia
P. Adzic42, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic
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,
A. Quintario Olmeda, I. Redondo, L. Romero, M.S. Soares Universidad Autónoma
de Madrid, Madrid, Spain
C. Albajar, J.F. de Trocóniz, M. Missiroli Universidad de Oviedo, Oviedo,
Spain
J. Cuevas, C. Erice, J. Fernandez Menendez, I. Gonzalez Caballero, J.R.
González Fernández, E. Palencia Cortezon, S. Sanchez Cruz, P. Vischia, J.M.
Vizan Garcia Instituto de Física de Cantabria (IFCA), CSIC-Universidad de
Cantabria, Santander, Spain
I.J. Cabrillo, A. Calderon, B. Chazin Quero, E. Curras, J. Duarte Campderros,
M. Fernandez, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto, J. Marco, C.
Martinez Rivero, P. Martinez Ruiz del Arbol, F. Matorras, J. Piedra Gomez, T.
Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar
Cortabitarte CERN, European Organization for Nuclear Research, Geneva,
Switzerland
D. Abbaneo, B. Akgun, E. Auffray, P. Baillon, A.H. Ball, D. Barney, J.
Bendavid, M. Bianco, P. Bloch, A. Bocci, C. Botta, T. Camporesi, R. Castello,
M. Cepeda, G. Cerminara, E. Chapon, Y. Chen, D. d’Enterria, A. Dabrowski, V.
Daponte, A. David, M. De Gruttola, A. De Roeck, N. Deelen, M. Dobson, T. du
Pree, M. Dünser, N. Dupont, A. Elliott-Peisert, P. Everaerts, F. Fallavollita,
G. Franzoni, J. Fulcher, W. Funk, D. Gigi, A. Gilbert, K. Gill, F. Glege, D.
Gulhan, P. Harris, J. Hegeman, V. Innocente, A. Jafari, P. Janot, O.
Karacheban17, J. Kieseler, V. Knünz, A. Kornmayer, M.J. Kortelainen, M.
Krammer1, C. Lange, P. Lecoq, C. Lourenço, M.T. Lucchini, L. Malgeri, M.
Mannelli, A. Martelli, F. Meijers, J.A. Merlin, S. Mersi, E. Meschi, P.
Milenovic43, F. Moortgat, M. Mulders, H. Neugebauer, J. Ngadiuba, S.
Orfanelli, L. Orsini, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G.
Petrucciani, A. Pfeiffer, M. Pierini, D. Rabady, A. Racz, T. Reis, G.
Rolandi44, M. Rovere, H. Sakulin, C. Schäfer, C. Schwick, M. Seidel, M.
Selvaggi, A. Sharma, P. Silva, P. Sphicas45, A. Stakia, J. Steggemann, M.
Stoye, M. Tosi, D. Treille, A. Triossi, A. Tsirou, V. Veckalns46, M. Verweij,
W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland
W. Bertl${}^{\textrm{\textdagger}}$, L. Caminada47, K. Deiters, W. Erdmann, R.
Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe,
S.A. Wiederkehr ETH Zurich - Institute for Particle Physics and Astrophysics
(IPA), Zurich, Switzerland
M. Backhaus, L. Bäni, P. Berger, L. Bianchini, B. Casal, G. Dissertori, M.
Dittmar, M. Donegà, C. Dorfer, C. Grab, C. Heidegger, D. Hits, J. Hoss, G.
Kasieczka, T. Klijnsma, W. Lustermann, B. Mangano, M. Marionneau, M.T.
Meinhard, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandolfi,
J. Pata, F. Pauss, G. Perrin, L. Perrozzi, M. Quittnat, M. Reichmann, D.A.
Sanz Becerra, M. Schönenberger, L. Shchutska, V.R. Tavolaro, K. Theofilatos,
M.L. Vesterbacka Olsson, R. Wallny, D.H. Zhu Universität Zürich, Zurich,
Switzerland
T.K. Aarrestad, C. Amsler48, M.F. Canelli, A. De Cosa, R. Del Burgo, S.
Donato, C. Galloni, T. Hreus, B. Kilminster, D. Pinna, G. Rauco, P. Robmann,
D. Salerno, K. Schweiger, C. Seitz, Y. Takahashi, A. Zucchetta National
Central University, Chung-Li, Taiwan
V. Candelise, Y.H. Chang, K.y. Cheng, T.H. Doan, Sh. Jain, R. Khurana, C.M.
Kuo, W. Lin, A. Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei,
Taiwan
P. Chang, Y. Chao, K.F. Chen, P.H. Chen, F. Fiori, W.-S. Hou, Y. Hsiung, Arun
Kumar, Y.F. Liu, R.-S. Lu, E. Paganis, A. Psallidas, A. Steen, J.f. Tsai
Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok,
Thailand
B. Asavapibhop, K. Kovitanggoon, G. Singh, N. Srimanobhas Çukurova University,
Physics Department, Science and Art Faculty, Adana, Turkey
A. Bat, F. Boran, S. Damarseckin, Z.S. Demiroglu, C. Dozen, E. Eskut, S.
Girgis, G. Gokbulut, Y. Guler, I. Hos49, E.E. Kangal50, O. Kara, U. Kiminsu,
M. Oglakci, G. Onengut51, K. Ozdemir52, S. Ozturk53, A. Polatoz, D. Sunar
Cerci54, U.G. Tok, H. Topakli53, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez
Middle East Technical University, Physics Department, Ankara, Turkey
G. Karapinar55, K. Ocalan56, M. Yalvac, M. Zeyrek Bogazici University,
Istanbul, Turkey
E. Gülmez, M. Kaya57, O. Kaya58, S. Tekten, E.A. Yetkin59 Istanbul Technical
University, Istanbul, Turkey
M.N. Agaras, S. Atay, A. Cakir, K. Cankocak, I. Köseoglu 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. Newbold60,
S. Paramesvaran, T. Sakuma, S. Seif El Nasr-storey, D. Smith, V.J. Smith
Rutherford Appleton Laboratory, Didcot, United Kingdom
K.W. Bell, A. Belyaev61, C. Brew, R.M. Brown, L. Calligaris, D. Cieri, D.J.A.
Cockerill, J.A. Coughlan, K. Harder, S. Harper, J. Linacre, E. Olaiya, D.
Petyt, C.H. Shepherd-Themistocleous, A. Thea, I.R. Tomalin, T. Williams
Imperial College, London, United Kingdom
G. Auzinger, R. Bainbridge, J. Borg, S. Breeze, O. Buchmuller, A. Bundock, S.
Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies, A. De Wit, M.
Della Negra, R. Di Maria, A. Elwood, Y. Haddad, G. Hall, G. Iles, T. James, R.
Lane, C. Laner, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, T.
Matsushita, J. Nash, A. Nikitenko7, V. Palladino, M. Pesaresi, D.M. Raymond,
A. Richards, A. Rose, E. Scott, C. Seez, A. Shtipliyski, S. Summers, A.
Tapper, K. Uchida, M. Vazquez Acosta62, T. Virdee14, N. Wardle, D.
Winterbottom, J. Wright, S.C. Zenz Brunel University, Uxbridge, United Kingdom
J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, I.D. Reid, 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, A. Garabedian, M. Hadley, J. Hakala, U. Heintz, J.M.
Hogan, K.H.M. Kwok, E. Laird, G. Landsberg, J. Lee, Z. Mao, M. Narain, J.
Pazzini, S. Piperov, S. Sagir, R. Syarif, D. Yu University of California,
Davis, Davis, USA
R. Band, C. Brainerd, 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, K. Tos, M. Tripathi, Z. Wang University of
California, Los Angeles, USA
M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M.
Ignatenko, N. Mccoll, S. Regnard, D. Saltzberg, C. Schnaible, V. Valuev
University of California, Riverside, Riverside, USA
E. Bouvier, K. Burt, R. Clare, J. Ellison, J.W. Gary, S.M.A. Ghiasi Shirazi,
G. Hanson, J. Heilman, G. Karapostoli, E. Kennedy, F. Lacroix, O.R. Long, M.
Olmedo Negrete, M.I. Paneva, W. Si, L. Wang, H. Wei, S. Wimpenny, B. R. Yates
University of California, San Diego, La Jolla, USA
J.G. Branson, S. Cittolin, M. Derdzinski, R. Gerosa, D. Gilbert, B. Hashemi,
A. Holzner, D. Klein, G. Kole, V. Krutelyov, J. Letts, M. Masciovecchio, D.
Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, M. Tadel, A. Vartak, S.
Wasserbaech63, J. Wood, F. Würthwein, A. Yagil, G. Zevi Della Porta University
of California, Santa Barbara - Department of Physics, Santa Barbara, USA
N. Amin, R. Bhandari, J. Bradmiller-Feld, C. Campagnari, A. Dishaw, V. Dutta,
M. Franco Sevilla, F. Golf, 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.M. Lawhorn, H.B. Newman, T. Nguyen, C. Pena, M.
Spiropulu, J.R. Vlimant, S. Xie, Z. Zhang, R.Y. Zhu Carnegie Mellon
University, Pittsburgh, USA
M.B. Andrews, T. Ferguson, T. Mudholkar, M. Paulini, J. Russ, M. Sun, H.
Vogel, I. Vorobiev, M. Weinberg University of Colorado Boulder, Boulder, USA
J.P. Cumalat, W.T. Ford, F. Jensen, A. Johnson, M. Krohn, S. Leontsinis, T.
Mulholland, K. Stenson, S.R. Wagner Cornell University, Ithaca, USA
J. Alexander, J. Chaves, J. Chu, S. Dittmer, K. Mcdermott, N. Mirman, J.R.
Patterson, D. Quach, A. Rinkevicius, A. Ryd, L. Skinnari, L. Soffi, S.M. Tan,
Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek Fermi National Accelerator
Laboratory, Batavia, USA
S. Abdullin, M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, A. Apyan, S.
Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, G.
Bolla${}^{\textrm{\textdagger}}$, K. Burkett, J.N. Butler, A. Canepa, G.B.
Cerati, H.W.K. Cheung, F. Chlebana, M. Cremonesi, J. Duarte, V.D. Elvira, J.
Freeman, Z. Gecse, E. Gottschalk, L. Gray, D. Green, S. Grünendahl, O.
Gutsche, R.M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, B. Jayatilaka, S.
Jindariani, M. Johnson, U. Joshi, B. Klima, B. Kreis, S. Lammel, D. Lincoln,
R. Lipton, M. Liu, T. Liu, R. Lopes De Sá, J. Lykken, K. Maeshima, N. Magini,
J.M. Marraffino, D. Mason, P. McBride, P. Merkel, S. Mrenna, S. Nahn, V.
O’Dell, K. Pedro, O. Prokofyev, G. Rakness, L. Ristori, B. Schneider, E.
Sexton-Kennedy, A. Soha, W.J. Spalding, L. Spiegel, S. Stoynev, J. Strait, N.
Strobbe, L. Taylor, S. Tkaczyk, N.V. Tran, L. Uplegger, E.W. Vaandering, C.
Vernieri, M. Verzocchi, R. Vidal, M. Wang, H.A. Weber, A. Whitbeck University
of Florida, Gainesville, USA
D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerhoff, A. Carnes, M.
Carver, D. Curry, R.D. Field, I.K. Furic, S.V. Gleyzer, B.M. Joshi, J.
Konigsberg, A. Korytov, K. Kotov, P. Ma, K. Matchev, H. Mei, G. Mitselmakher,
K. Shi, D. Sperka, N. Terentyev, L. Thomas, J. Wang, S. Wang, J. Yelton
Florida International University, Miami, USA
Y.R. Joshi, S. Linn, P. Markowitz, J.L. Rodriguez Florida State University,
Tallahassee, USA
A. Ackert, T. Adams, A. Askew, S. Hagopian, V. Hagopian, K.F. Johnson, T.
Kolberg, G. Martinez, T. Perry, H. Prosper, A. Saha, A. Santra, V. Sharma, R.
Yohay Florida Institute of Technology, Melbourne, USA
M.M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, T.
Roy, F. Yumiceva University of Illinois at Chicago (UIC), Chicago, USA
M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, R. Cavanaugh, X. Chen, O.
Evdokimov, C.E. Gerber, D.A. Hangal, D.J. Hofman, K. Jung, J. Kamin, I.D.
Sandoval Gonzalez, M.B. Tonjes, H. Trauger, N. Varelas, H. Wang, Z. Wu, J.
Zhang The University of Iowa, Iowa City, USA
B. Bilki64, W. Clarida, K. Dilsiz65, S. Durgut, R.P. Gandrajula, M.
Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya66, A. Mestvirishvili,
A. Moeller, J. Nachtman, H. Ogul67, Y. Onel, F. Ozok68, A. Penzo, C. Snyder,
E. Tiras, J. Wetzel, K. Yi Johns Hopkins University, Baltimore, USA
B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan, P.
Maksimovic, J. Roskes, U. Sarica, M. Swartz, M. Xiao, C. You The University of
Kansas, Lawrence, USA
A. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, J. Castle, S.
Khalil, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, C. Royon, S.
Sanders, E. Schmitz, J.D. Tapia Takaki, Q. Wang Kansas State University,
Manhattan, USA
A. Ivanov, K. Kaadze, Y. Maravin, A. Mohammadi, L.K. Saini, N. Skhirtladze
Lawrence Livermore National Laboratory, Livermore, USA
F. Rebassoo, D. Wright University of Maryland, College Park, USA
C. Anelli, 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, R. Bi, S. Brandt,
W. Busza, I.A. Cali, M. D’Alfonso, Z. Demiragli, G. Gomez Ceballos, M.
Goncharov, D. Hsu, M. Hu, Y. Iiyama, G.M. Innocenti, M. Klute, D. Kovalskyi,
Y.-J. Lee, A. Levin, P.D. Luckey, B. Maier, A.C. Marini, C. Mcginn, C.
Mironov, S. Narayanan, X. Niu, C. Paus, C. Roland, G. Roland, J. Salfeld-
Nebgen, G.S.F. Stephans, K. Tatar, D. Velicanu, J. Wang, T.W. Wang, B.
Wyslouch University of Minnesota, Minneapolis, USA
A.C. Benvenuti, R.M. Chatterjee, A. Evans, P. Hansen, J. Hiltbrand, S.
Kalafut, Y. Kubota, Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack,
J. Turkewitz, M.A. Wadud University of Mississippi, Oxford, USA
J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA
E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, R. Gonzalez Suarez, R.
Kamalieddin, I. Kravchenko, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger State
University of New York at Buffalo, Buffalo, USA
J. Dolen, A. Godshalk, C. Harrington, I. Iashvili, D. Nguyen, A. Parker, S.
Rappoccio, B. Roozbahani Northeastern University, Boston, USA
G. Alverson, E. Barberis, C. Freer, A. Hortiangtham, A. Massironi, D.M. Morse,
T. Orimoto, R. Teixeira De Lima, D. Trocino, 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.
Musienko35, 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, B. Liu, W. Luo, B.L. Winer, H.W. Wulsin Princeton
University, Princeton, USA
S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, S. Higginbotham,
A. Kalogeropoulos, D. Lange, J. Luo, D. Marlow, K. Mei, I. Ojalvo, J. Olsen,
C. Palmer, P. Piroué, D. Stickland, C. Tully University of Puerto Rico,
Mayaguez, USA
S. Malik, S. Norberg Purdue University, West Lafayette, USA
A. Barker, V.E. Barnes, S. Das, S. Folgueras, L. Gutay, M.K. Jha, M. Jones,
A.W. Jung, A. Khatiwada, D.H. Miller, N. Neumeister, C.C. Peng, H. Qiu, J.F.
Schulte, J. Sun, F. Wang, R. Xiao, W. Xie Purdue University Northwest,
Hammond, USA
T. Cheng, N. Parashar, J. Stupak Rice University, Houston, USA
Z. Chen, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Guilbaud, M. Kilpatrick, W.
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, M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K.
Thapa Texas A&M University, College Station, USA
O. Bouhali69, A. Castaneda Hernandez69, A. Celik, M. Dalchenko, M. De Mattia,
A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, T. Kamon70, R.
Mueller, Y. Pakhotin, R. Patel, A. Perloff, L. Perniè, D. Rathjens, A.
Safonov, A. Tatarinov, K.A. Ulmer Texas Tech University, Lubbock, USA
N. Akchurin, J. Damgov, F. De Guio, P.R. Dudero, J. Faulkner, E. Gurpinar, S.
Kunori, K. Lamichhane, S.W. Lee, T. Libeiro, T. Mengke, S. Muthumuni, T.
Peltola, S. Undleeb, I. Volobouev, Z. Wang Vanderbilt University, Nashville,
USA
S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K.
Padeken, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu University of Virginia,
Charlottesville, USA
M.W. Arenton, P. Barria, B. Cox, R. Hirosky, M. Joyce, A. Ledovskoy, H. Li, C.
Neu, T. Sinthuprasith, Y. Wang, E. Wolfe, F. Xia Wayne State University,
Detroit, USA
R. Harr, P.E. Karchin, N. Poudyal, J. Sturdy, P. Thapa, S. Zaleski University
of Wisconsin - Madison, Madison, WI, USA
M. Brodski, J. Buchanan, C. Caillol, S. Dasu, L. Dodd, S. Duric, B. Gomber, M.
Grothe, M. Herndon, A. Hervé, U. Hussain, P. Klabbers, A. Lanaro, A. Levine,
K. Long, R. Loveless, T. Ruggles, A. Savin, N. Smith, W.H. Smith, D. Taylor,
N. Woods †: Deceased
1: Also at Vienna University of Technology, Vienna, Austria
2: Also at State Key Laboratory of Nuclear Physics and Technology; Peking
University, Beijing, China
3: Also at IRFU; CEA; Université Paris-Saclay, Gif-sur-Yvette, France
4: Also at Universidade Estadual de Campinas, Campinas, Brazil
5: Also at Universidade Federal de Pelotas, Pelotas, Brazil
6: Also at Université Libre de Bruxelles, Bruxelles, Belgium
7: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia
8: Also at Joint Institute for Nuclear Research, Dubna, Russia
9: Now at Ain Shams University, Cairo, Egypt
10: Now at British University in Egypt, Cairo, Egypt
11: Also at Zewail City of Science and Technology, Zewail, Egypt
12: Also at Université de Haute Alsace, Mulhouse, France
13: Also at Skobeltsyn Institute of Nuclear Physics; Lomonosov Moscow State
University, Moscow, Russia
14: Also at CERN; European Organization for Nuclear Research, Geneva,
Switzerland
15: Also at RWTH Aachen University; III. Physikalisches Institut A, Aachen,
Germany
16: Also at University of Hamburg, Hamburg, Germany
17: Also at Brandenburg University of Technology, Cottbus, Germany
18: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group; Eötvös
Loránd University, Budapest, Hungary
19: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
20: Also at Institute of Physics; University of Debrecen, Debrecen, Hungary
21: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India
22: Also at Institute of Physics, Bhubaneswar, India
23: Also at University of Visva-Bharati, Santiniketan, India
24: Also at University of Ruhuna, Matara, Sri Lanka
25: Also at Isfahan University of Technology, Isfahan, Iran
26: Also at Yazd University, Yazd, Iran
27: Also at Plasma Physics Research Center; Science and Research Branch;
Islamic Azad University, Tehran, Iran
28: Also at Università degli Studi di Siena, Siena, Italy
29: Also at INFN Sezione di Milano-Bicocca; Università di Milano-Bicocca,
Milano, Italy
30: Also at Purdue University, West Lafayette, USA
31: Also at International Islamic University of Malaysia, Kuala Lumpur,
Malaysia
32: Also at Malaysian Nuclear Agency; MOSTI, Kajang, Malaysia
33: Also at Consejo Nacional de Ciencia y Tecnología, Mexico city, Mexico
34: Also at Warsaw University of Technology; Institute of Electronic Systems,
Warsaw, Poland
35: Also at Institute for Nuclear Research, Moscow, Russia
36: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
37: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
38: Also at University of Florida, Gainesville, USA
39: Also at P.N. Lebedev Physical Institute, Moscow, Russia
40: Also at California Institute of Technology, Pasadena, USA
41: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
42: Also at Faculty of Physics; University of Belgrade, Belgrade, Serbia
43: Also at University of Belgrade; Faculty of Physics and Vinca Institute of
Nuclear Sciences, Belgrade, Serbia
44: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy
45: Also at National and Kapodistrian University of Athens, Athens, Greece
46: Also at Riga Technical University, Riga, Latvia
47: Also at Universität Zürich, Zurich, Switzerland
48: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna,
Austria
49: Also at Istanbul Aydin University, Istanbul, Turkey
50: Also at Mersin University, Mersin, Turkey
51: Also at Cag University, Mersin, Turkey
52: Also at Piri Reis University, Istanbul, Turkey
53: Also at Gaziosmanpasa University, Tokat, Turkey
54: Also at Adiyaman University, Adiyaman, Turkey
55: Also at Izmir Institute of Technology, Izmir, Turkey
56: Also at Necmettin Erbakan University, Konya, Turkey
57: Also at Marmara University, Istanbul, Turkey
58: Also at Kafkas University, Kars, Turkey
59: Also at Istanbul Bilgi University, Istanbul, Turkey
60: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom
61: Also at School of Physics and Astronomy; University of Southampton,
Southampton, United Kingdom
62: Also at Instituto de Astrofísica de Canarias, La Laguna, Spain
63: Also at Utah Valley University, Orem, USA
64: Also at Beykent University, Istanbul, Turkey
65: Also at Bingol University, Bingol, Turkey
66: Also at Erzincan University, Erzincan, Turkey
67: Also at Sinop University, Sinop, Turkey
68: Also at Mimar Sinan University; Istanbul, Istanbul, Turkey
69: Also at Texas A&M University at Qatar, Doha, Qatar
70: Also at Kyungpook National University, Daegu, Korea