HIG-17-007

$HeadURL:svn+ssh://svn.cern.ch/reps/tdr2/papers/HIG-17-007/trunk/HIG-17-007.tex$
$Id:HIG-17-007.tex4795292018-10-2822:07:33Zshilpi$

HIG-17-007

# Search for the decay of a Higgs boson in the $\ell\ell\gamma$ channel in
proton-proton collisions at $\sqrt{s}=13\TeV$

###### Abstract

A search for a Higgs boson decaying into a pair of electrons or muons and a
photon is described. Higgs boson decays to a $\cPZ$ boson and a photon
($\PH\to\cPZ\gamma\to\ell\ell\gamma$,$\ell=\Pe$ or $\mu$), or to two photons,
one of which has an internal conversion into a muon pair
($\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$) were considered. The analysis is
performed using a data set recorded by the CMS experiment at the LHC from
proton-proton collisions at a center-of-mass energy of 13, corresponding to an
integrated luminosity of 35.9. No significant excess above the background
prediction has been found. Limits are set on the cross section for a standard
model Higgs boson decaying to opposite-sign electron or muon pairs and a
photon. The observed limits on cross section times the corresponding branching
fractions vary between 1.4 and 4.0 (6.1 and 11.4) times the standard model
cross section for $\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$
($\PH\to\cPZ\gamma\to\ell\ell\gamma$) in the 120–130mass range of the
$\ell\ell\gamma$ system. The $\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ and
$\PH\to\cPZ\gamma\to\ell\ell\gamma$ analyses are combined for
$m_{\PH}=125\GeV$, obtaining an observed (expected) 95% confidence level upper
limit of 3.9 (2.0) times the standard model cross section.

##  0.1 Introduction

Measurements of rare decays of the Higgs boson, such as
$\PH\to\gamma^{*}\gamma$ and $\PH\to\cPZ\gamma$, would enhance our
understanding of the standard model (SM) of particle physics, and allow us to
probe exotic couplings introduced by possible extensions of the SM [1, 2, 3,
4]. The decay width can be modified by the theories involving heavy fermions,
gauge bosons or charged scalars [5, 6, 7, 8, 9]. Simple extensions of the SM
like two Higgs doublet models, or the minimal supersymmetric standard model
also exhibit similar features [10]. Certain coefficients of the dimension-6
extension of the standard model effective field theory can be constrained by
measuring the $\PH\to\cPZ\gamma$ branching ratio precisely [11]. As an
example, a model [10] which includes a hypercharge zero triplet extension,
shows a modification in $\mathcal{B}(\PH\to\cPZ\gamma)$, with respect to the
SM value, of about 10% for an additional scalar field with mass between 0 and
400.

In the search for $\PH\to\gamma^{*}\gamma\to\ell\ell\gamma$, the leptonic
channel, $\gamma^{*}/\cPZ\to\ell\ell$ ($\ell=\Pe$ or $\mu$) is most promising
as it has relatively low background. The diagrams in Fig. 1 illustrate the
dominant Higgs boson decay channels contributing to these final states. The
$\PH\to\gamma^{*}\gamma\to\ell\ell\gamma$ and
$\PH\to\cPZ\gamma\to\ell\ell\gamma$ diagrams correspond to the same initial
and final state and interfere with each other. Experimentally one can separate
the off- and on-shell contributions, and define the respective signal regions,
using a selection based on the invariant mass of the dilepton system,
$m_{\ell\ell}=m_{\gamma^{*}/\cPZ}$. For the measurements presented in this
paper a threshold of $m_{\ell\ell}=50\GeV$ is used to separate the two
processes.

Figure 1: Dominant Feynman diagrams contributing to the $\PH\to\ell\ell\gamma$
process.

It is informative to express the branching fractions for these decays relative
to the $\PH\to\gamma\gamma$ process. In the SM, for a Higgs boson with mass
$m_{\PH}=125\GeV$ [12, 13], these ratios are:

$\frac{\mathcal{B}(\PH\to\gamma^{*}\gamma\to\mu\mu\gamma)}{\mathcal{B}(\PH\to\gamma\gamma)}=(1.69\pm
0.10)\%,\quad\frac{\mathcal{B}(\PH\to\cPZ\gamma\to\Pep\Pem\gamma/\mu\mu\gamma)}{\mathcal{B}(\PH\to\gamma\gamma)}=(2.27\pm
0.14)\%,$ (1)

where $\mathcal{B}(\PH\to\cPZ\gamma\to\Pep\Pem\gamma/\mu\mu\gamma)=0.051\times
10^{-3}$ and $\mathcal{B}(\PH\to\gamma\gamma)=2.27\times 10^{-3}$ are taken
from Ref. [14], and
$\mathcal{B}(\PH\to\gamma^{*}\gamma\to\mu\mu\gamma)=3.83\times 10^{-5}$ is
obtained with the 7.0.1 program [15], which is in agreement with calculations
in Refs. [16, 17, 18].

The ATLAS and CMS Collaborations at the CERN LHC have both performed searches
for the decay $\PH\to\cPZ\gamma\to\ell\ell\gamma$ [19, 20] at $\sqrt{s}=7$ and
$8\TeV$. The ATLAS Collaboration set an upper limit on
$\sigma/\sigma_{\mathrm{SM}}$ of 11 (where $\sigma_{\mathrm{SM}}$ is the
expected cross section of the SM signal process) at 95% confidence level ()
for an SM Higgs boson with $m_{\PH}=125.5\GeV$, and the CMS Collaboration set
an upper limit of 9.5 at 95% for $m_{\PH}=125\GeV$. The CMS Collaboration has
also searched for the $\PH\to\gamma^{*}\gamma\to\ell\ell\gamma$ process with
$m_{\ell\ell}<20$ (1.5)in the dimuon (dielectron) channel at $8\TeV$ [21]. The
two channels were combined to set an upper limit of 6.7 at 95% on
$\sigma/\sigma_{\mathrm{SM}}$ for $m_{\PH}=125\GeV$. The ATLAS Collaboration
has also performed a search for $\PH\to\cPZ\gamma\to\ell\ell\gamma$ at
$\sqrt{s}=13\TeV$ using 36.1of data collected in 2016. This search set an
upper limit on $\sigma/\sigma_{\mathrm{SM}}$ of 6.6 at 95% for an SM Higgs
boson with $m_{\PH}=125.09\GeV$ [22].

This paper describes a search for Higgs bosons decaying to
$\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ and
$\PH\to\cPZ\gamma\to\ell\ell\gamma$ at 13. The study of the
$\PH\to\gamma^{*}\gamma\to\Pe\Pe\gamma$ decay is challenging [21], because if
$m_{\ell\ell}$ is low, the pair of electron showers merge in the
electromagnetic calorimeter (ECAL). This merging makes it difficult to trigger
on such events and also to reconstruct them offline. Therefore, this channel
is not included in the present analysis.

The analysis uses a data sample of proton-proton ($\Pp\Pp$) collisions at a
center-of-mass energy of 13recorded by the CMS experiment during 2016,
corresponding to an integrated luminosity of 35.9. The sensitivity of the
search is enhanced by dividing the selected events into mutually exclusive
classes, according to the expected mass resolution and the signal-to-
background ratio, and then combining the results from each class. This paper
is structured as follows. In Section 0.2, the CMS detector is described. The
event selection used in the analysis is outlined in Section 0.3. Section 0.4
discusses about signal and background modeling. Systematic uncertainties and
the results of this study are presented in Section 0.5, followed by the
summary in Section 0.6.

##  0.2 The CMS detector and trigger

A detailed description of the CMS detector can be found in Ref. [23]. The
central feature of the CMS apparatus is a superconducting solenoid, 13m in
length and 6m in diameter, which provides an axial magnetic field of 3.8T.
Within the field volume there are several particle detection systems. Charged-
particle trajectories are measured by silicon pixel and silicon strip
trackers, covering $0\leq\phi\leq 2\pi$ in azimuth and $\abs{\eta}<2.5$ in
pseudorapidity. A lead-tungstate crystal ECAL and a brass and scintillator
hadron calorimeter (HCAL) surround the tracking volume and cover the region
$\abs{\eta}<3$. They provide energy measurements of photons, electrons and
hadronic jets. The ECAL is partitioned into a barrel region with
$\abs{\eta}<1.48$ and two endcaps that extend up to $\abs{\eta}=3$. A lead and
silicon-strip preshower detector is located in front of the endcap of the
ECAL. Muons are identified and measured in gas-ionization detectors embedded
in the steel return yoke outside the solenoid. The detector is nearly
hermetic, allowing energy balance measurements in the plane transverse to the
beam direction.

A two-level trigger system selects collision events of interest for physics
analysis [24]. The trigger used in the $\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$
channel requires a muon and a photon with transverse momenta, , greater than
17 and 30, respectively. The trigger efficiency is determined using signal
events in simulation and $\mu\mu\gamma$ events in data using an orthogonal
data set selected with a single muon trigger. For events satisfying the
selection criteria described in Section 0.3 the trigger efficiency is 83% in
both cases. The $\PH\to\cPZ\gamma\to\ell\ell\gamma$ events are required to
pass at least one of the dielectron or dimuon triggers. The dielectron trigger
requires a leading (subleading) electron with greater than 23 (12). The dimuon
trigger requires a leading (subleading) muon with greater than 17 (8). The
efficiencies of these dilepton triggers as measured in data, for events
satisfying the selection criteria, are dependent on the $\pt$ and $\eta$ of
the leptons and are measured to be 90–98% and 93–95% for the $\Pe\Pe\gamma$
and $\mu\mu\gamma$ channels, respectively.

##  0.3 Event selection

Selected events are required to have at least one good primary vertex, with
reconstructed longitudinal position within 24cm of the geometric center of the
detector and transverse position within 2cm of the beam interaction region.
Due to the high instantaneous luminosity of the LHC, there are multiple
$\Pp\Pp$ interactions per bunch crossing (pileup). In the case of multiple
vertices, the vertex with the largest value of summed physics-object $\pt^{2}$
is taken to be the primary $\Pp\Pp$ interaction vertex. The physics objects
chosen are those that have been defined using information from the tracking
detector, including jets, the associated missing transverse momentum, which is
defined as the negative vector sum of the of those jets, and charged leptons.
All leptons, which are used to select events, are required to have transverse
and longitudinal impact parameters with respect to the primary vertex smaller
than 5 and 10 mm, respectively.

The particle-flow (PF) event reconstruction algorithm [25] is used to
reconstruct and identify each individual particle using an optimized
combination of information from the various elements of the CMS detector.

Photon candidates are reconstructed from clusters of crystals in the ECAL with
significant energy deposits [26]. Clusters are grouped into superclusters to
recover the energy from electron bremsstrahlung and photons converting in the
tracker. In the endcaps, the preshower detector energy is also included for
the region covered by the preshower detector ($1.65<\abs{\eta}<2.6$). The
clustering algorithms result in almost complete recovery of the energy of
photons. Photon candidates are selected with a multivariate discriminant that
uses, as inputs, isolation variables, the ratio of the energy in the HCAL
behind an electromagnetic supercluster to the supercluster energy, and the
transverse width of the electromagnetic shower. Isolation variables are based
on particle candidates from the PF algorithm. A conversion-safe electron veto
[26] is applied to avoid misidentifying an electron as a photon. This vetoes
events that have a charged particle track with a hit in the inner layer of the
pixel detector that points to the photon cluster in the ECAL, unless that
track is matched to a conversion vertex. Photons are required to lie in the
geometrical region $\abs{\eta}<2.5$ and have $\pt>15\GeV$. The efficiency of
the photon identification is measured from $\cPZ\to\Pe\Pe$ events using tag-
and-probe techniques [27]. It is found to be between 84 and 91 (77 and 94)% in
the barrel (endcaps) depending on the $\pt$ of the photon, after including the
electron veto inefficiencies measured with $\cPZ\to\mu\mu\gamma$ events, where
the photon is produced by final-state radiation.

Electron reconstruction starts from superclusters in the ECAL, which are
matched to hits in the silicon strip and the pixel detectors. The energy of
electrons is determined from a combination of the electron track momentum at
the main interaction vertex and the energy of the corresponding ECAL cluster.
Electrons are selected using a multivariate discriminant that includes
observables sensitive to the presence of bremsstrahlung along the electron
trajectory, the geometrical and momentum-energy matching between the electron
trajectory and the energy of the associated cluster in the ECAL, the shape of
the electromagnetic shower in the ECAL, and the variables that discriminate
against electrons originating from photon conversions [13]. In this analysis,
we accept electrons with $\pt>7\GeV$ and $\abs{\eta}<2.5$.

Muon candidates are reconstructed in the tracker and identified by the PF
algorithm using hits in the tracker and the muon systems. The matching between
the inner and outer tracks proceeds either outside-in, starting from a track
in the muon system, or inside-out, starting from a track in the silicon
tracker. In the latter case, tracks that match track segments in only one or
two planes of the muon system are also considered in the analysis in order to
collect very low-$\pt$ muons that may not have sufficient energy to penetrate
the entire muon system. The muons are selected from the reconstructed muon
track candidates by applying minimal requirements on the track in both the
muon system and inner tracker system, and taking into account compatibility
with small energy deposits in the calorimeters. We accept muons with
$\pt>4$and $\abs{\eta}<2.4$ [13].

The relative isolation variable, used to select prompt leptons, is defined as:

${\cal
I}^{\ell}\equiv\Big{(}\sum\PT^{\text{charged}}+\max\big{[}0,\sum\PT^{\text{neutral}}+\sum\PT^{\Pgg}-\PT^{\mathrm{PU}}(\ell)\big{]}\Big{)}/\PT^{\ell},$
(2)

and is required to be less than 0.35, where $\sum\PT^{\text{charged}}$ is the
scalar sum of the transverse momenta of charged hadrons originating from the
primary vertex, $\sum\PT^{\text{neutral}}$ and $\sum\PT^{\Pgg}$ are the scalar
sums of the transverse momenta for neutral hadrons and photons, respectively,
and $\sum\PT^{\mathrm{PU}}(\ell)$ accounts for the contribution of neutral
pileup particles. The isolation sums are performed over a cone of angular
radius $\DR=\sqrt{\smash[b]{(\Delta\phi)^{2}+(\Delta\eta)^{2}}}=0.3$ around
the lepton direction at the primary vertex. For muons,
$\PT^{\mathrm{PU}}(\Pgm)\equiv 0.5\,\sum_{i}\PT^{\mathrm{PU},i}$, where $i$
runs over the momenta of the charged hadron PF candidates not originating from
the primary vertex. For electrons,
$\PT^{\mathrm{PU}}(\Pe)\equiv\rho\,A_{\text{eff}}$, where the effective area
$A_{\text{eff}}$ is a coefficient that is dependent on electron $\eta$ and is
chosen in such a way that the isolation efficiency is independent of pileup
(PU), and $\rho$ is the median of the $\PT$ density distribution for neutral
particles [28, 29, 30]. Finally, $\PT^{\ell}$ is the transverse momentum of
the selected lepton. To suppress muons originating from non-prompt decays of
hadrons and electrons from photon conversions, we require each lepton track to
have a 3D impact parameter with respect to the primary vertex that is less
than four times its uncertainty.

The optimized electron selection criteria, including the isolation
requirement, give an efficiency of approximately 85–93 (81–92)% in the barrel
(endcaps) for electrons from $\PW$ or $\cPZ$ bosons. For muons, the
identification is tuned to maintain efficiency at low $\DR$ where the two
muons are close to each other. The identification and isolation efficiency for
single muons from $\cPZ\to\mu\mu$ or $\cPJgy$ meson decays is 85–97 (88–96)%
in the barrel (endcaps). In the case of the
$\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$, the $\DR(\mu\mu)$ between the two
muons is small due to their low invariant mass and the high $\PT$ of the
$\gamma^{*}$. Hence, no isolation requirement is applied to the subleading
muons as they are within the isolation cone of the leading muons in most
events. Also, if the subleading muon falls within the isolation cone of the
leading muon, it is not included in the calculation of the isolation variable.
The identification efficiency of muons from $\gamma^{*}$ is approximately
94–98 (92–97)% in the barrel (endcaps).

Selected events are classified as described in detail below. The dijet-tagged
(explained in Section 0.3.1) event class uses jets that are built by
clustering the PF candidates using the anti-clustering algorithm with a
distance parameter of 0.4 using the software package [28]. Charged PF
candidates from pileup vertices are discarded to reduce the contribution to
the jet energies from pileup interactions. An offset correction is applied to
account for the remaining contributions. In situ measurements of the momentum
balance in dijet, photon+jet, $\cPZ$+jet, and multijet events are used to
account for any residual differences in jet energy scale in data and
simulation. Additional selection criteria are applied to each event to remove
spurious jet-like features originating from isolated noise patterns in certain
HCAL regions. Calibrated and corrected jets are required to have $\pt$ greater
than 30and $\abs{\eta}<4.7$, and to be separated by at least 0.4 in $\DR$ from
leptons and photons passing the selection requirements described above.

###  0.3.1 $\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ selection

In the $\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ search we select events with
two muons and a photon, where the muons must have opposite charges and
$\PT>20\,(4)\GeV$ for the leading (subleading) muon. The requirement on the
leading muon is driven by the trigger threshold, and that on the subleading
muon by the minimum energy needed to reach the muon system. The photon and
dimuon transverse momenta both must satisfy $\pt>0.30m_{\mu\mu\gamma}$, where
$m_{\mu\mu\gamma}$ is the invariant mass of the $\mu\mu\gamma$ system. This
requirement rejects the $\gamma^{*}+$jet and $\gamma+$jet backgrounds without
any loss in the signal sensitivity and without introducing a bias in the
$m_{\mu\mu\gamma}$ spectrum. The separation between each muon and the photon
is required to satisfy $\DR>1$ in order to suppress Drell–Yan background
events with final-state radiation.

The dimuon invariant mass is required to be less than 50to make this selection
and the $\cPZ\gamma$ selection described in Section 0.3.2 mutually exclusive.
Events with a dimuon mass in the ranges $2.9<m_{\mu\mu}<3.3\GeV$ and
$9.3<m_{\mu\mu}<9.7\GeV$ are rejected to avoid $\cPJgy\to\mu\mu$ and
$\Upsilon(nS)\to\mu\mu$ contamination, respectively. The invariant mass
$m_{\mu\mu\gamma}$ is required to satisfy $110<m_{\mu\mu\gamma}<170\GeV$. In
the cases where there are multiple dilepton pairs in the event, the one with
the smallest dimuon invariant mass is chosen.

A variable $\RNINE$ is defined as the energy sum of the 3$\times$3 ECAL
crystals centered on the most energetic crystal in the supercluster divided by
the energy of the supercluster. The selected events are separated into four
mutually exclusive event classes based on the $\RNINE$ and $\eta$ of the
photon and the presence of jets. An $\RNINE$ value of 0.94 is used to separate
the reconstructed photons into two regions. The region containing unconverted
photons, with larger values of $\RNINE$ and better energy resolution, has a
smaller background. By separating events into two regions of low/high $\RNINE$
value, the sensitivity of the analysis is increased. We therefore have the
following four categories: events that require the presence of at least two
jets passing the selection criteria as described below; photon in the ECAL
barrel (EB) region with a high $\RNINE$ value; photon in the barrel with low
$\RNINE$ value; and photon in the ECAL endcap (EE) regions. Only events that
do not pass the dijet tag are included in the EB or EE classes. By using this
event classification scheme, as opposed to combining all events into one
class, the sensitivity of this analysis is increased by 11%.

For the dijet tag event class the two highest transverse energy jets are used
and the requirements are: (i) the difference in pseudorapidity between the two
jets is greater than 3.5; (ii) the Zeppenfeld variable [31]
($\eta_{\ell\ell\gamma}-(\eta_{\mathrm{j1}}+\eta_{\mathrm{j2}})/2$) is less
than 2.5, where $\eta_{\ell\ell\gamma}$ is the $\eta$ of the $\ell\ell\gamma$
system and $\eta_{\mathrm{j1}}$ and $\eta_{\mathrm{{j2}}}$ are the
pseudorapidities of the leading and subleading jets, respectively; (iii) the
dijet mass is greater than 500; and (iv) the difference in azimuthal angles
between the dijet system and the $\ell\ell\gamma$ system is greater than 2.4.
These requirements mainly target the vector boson fusion (VBF) production
mechanism of the Higgs boson.

The resulting acceptance times efficiency for
$\Pp\Pp\to\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ is 26–27% for $m_{\PH}$
between 120 and 130.

###  0.3.2 $\PH\to\cPZ\gamma\to\ell\ell\gamma$ selection

In the $\PH\to\cPZ\gamma\to\ell\ell\gamma$ search, events with a photon and
with at least two same-flavor leptons ($\Pe$ or $\mu$) consistent with a
$\cPZ$ boson decay are selected. All particles must be isolated, and have
$\pt$ greater than 25 (15)for the leading (subleading) electron, 20 (10)for
the leading (subleading) muon, and 15for the photon. In the cases where there
are multiple dilepton pairs in the event, the one with the mass closest to the
$\cPZ$ boson nominal mass [32] is selected. The invariant mass of the selected
pair is required to be larger than 50. This ensures that the
$\PH\to\cPZ\gamma\to\ell\ell\gamma$ event selection is orthogonal to that for
$\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$.

The events are required to have a photon with $\ET>0.14m_{\ell\ell\gamma}$,
which rejects the $\cPZ+$jets background without significant loss in signal
sensitivity and without introducing a bias in the $m_{\ell\ell\gamma}$
spectrum. Leptons are required to have $\DR>0.4$ with respect to the photon in
order to reject events with final-state radiation. In addition, we require
$m_{\ell\ell\gamma}+m_{\ell\ell}>185\GeV$ to reject events with final-state
radiation from Drell–Yan processes. Finally, the invariant mass of the
$\ell\ell\gamma$ system is required to be $115<m_{\ell\ell\gamma}<170\GeV$.

The selected events are classified into mutually exclusive categories. A
lepton-tag class contains events with an additional electron (or muon) with
$\pt>7$ (5), to target Higgs boson production in association with either a
$\cPZ$ or $\PW$ boson. Events not included in the lepton class are considered
for the dijet class. In this case the criteria described in Section 0.3.1 are
used to select events containing a dijet, targeting Higgs boson production in
a VBF process. The next class considered is the boosted class, which requires
that the $\pt$ of the $\ell\ell\gamma$ system is greater than 60in order to
enhance the fraction of events that contain a Lorentz-boosted Higgs boson
recoiling against a jet. Events that do not fall into these three classes are
placed in the untagged categories. A significant fraction of the signal events
are expected to have the photon and both leptons in the barrel, while only a
sixth of the signal events have the photon in the endcap. This is in contrast
to the background, where about one third of the events are expected to have a
photon in the endcap. Furthermore, events where the photon does not convert to
$\Pe^{+}\Pe^{-}$ have a smaller fraction of background events and better
energy resolution. For these reasons, the untagged events are classified into
four categories according to the pseudorapidity of the leptons and photon, and
the $\RNINE$ value of the photon. These categories are indicated as untagged
1, untagged 2, untagged 3 and untagged 4 as shown in Table 0.3.2.

Categories in $\PH\to\cPZ\gamma\to\ell\ell\gamma$ search. The electron and
muon channels are considered separately in all classes except for the lepton-
tag class.  Category $\Pep\Pem\gamma$ $\mu^{+}\mu^{-}\gamma$ Lepton tag
Additional electron ($\pt>7\GeV$) or muon ($\pt>5\GeV$) Dijet tag At least 2
jets required At least 2 jets required dijet selection (Section 0.3.1) dijet
selection (Section 0.3.1) Boosted $\pt(\Pe\Pe\gamma)>60\GeV$
$\pt(\mu\mu\gamma)>60\GeV$ Untagged 1 Photon $0<\abs{\eta}<1.4442$ Photon
$0<\abs{\eta}<1.4442$ Both leptons $0<\abs{\eta}<1.4442$ Both leptons
$0<\abs{\eta}<2.1$ $\RNINE>0.94$ and one lepton $0<\abs{\eta}<0.9$
$\RNINE>0.94$ Untagged 2 Photon $0<\abs{\eta}<1.4442$ Photon
$0<\abs{\eta}<1.4442$ Both leptons $0<\abs{\eta}<1.4442$ Both leptons
$0<\abs{\eta}<2.1$ $\RNINE<0.94$ and one lepton $0<\abs{\eta}<0.9$
$\RNINE<0.94$ Untagged 3 Photon $0<\abs{\eta}<1.4442$ Photon
$0<\abs{\eta}<1.4442$ At least one lepton $1.4442<\abs{\eta}<2.5$ Both leptons
in $\abs{\eta}>0.9$ No requirement on $\RNINE$ or one lepton in
$2.1<\abs{\eta}<2.4$ No requirement on $\RNINE$ Untagged 4 Photon
$1.566<\abs{\eta}<2.5$ Photon $1.566<\abs{\eta}<2.5$ Both leptons
$0<\abs{\eta}<2.5$ Both leptons $0<\abs{\eta}<2.4$ No requirement on $\RNINE$
No requirement on $\RNINE$

It should be noted that the electron and muon channels are considered
separately in all classes except for the lepton-tag class where the number of
events is small. This event classification scheme increases the sensitivity of
the analysis by 18%. The resulting acceptance times efficiency for
$\Pp\Pp\to\PH\to\cPZ\gamma\to\ell\ell\gamma$ in the electron (muon) channel is
between 18 and 24 (25 and 31)% for $m_{\PH}$ between 120 and 130.

A complete list of all the categories considered in the analysis
($\Pp\Pp\to\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ and
$\Pp\Pp\to\PH\to\cPZ\gamma\to\ell\ell\gamma$), together with the expected
yields for a 125SM Higgs boson signal processes, is shown in Table 0.3.2. This
table also reports yields from signal processes: gluon-gluon fusion
($\Pg\Pg\PH$), vector boson fusion (VBF), associated $\mathrm{V}\PH$
production ($\mathrm{V}\PH$) and Higgs boson production in association with
top quarks ($\ttbar\PH$).

Expected signal yields for a 125SM Higgs boson, corresponding to an integrated
luminosity of 35.9, for all categories in the
$\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ and
$\PH\to\cPZ\gamma\to\ell\ell\gamma$ processes in the narrowest
$\ell\ell\gamma$ invariant mass window around 125containing 68.3% of the
expected signal distribution.  Number of signal events Analysis Channel
Category for $m_{\PH}=125\GeV$ $\Pg\Pg\PH$ VBF $\mathrm{V}\PH+\ttbar\PH$
$\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ $\mu\mu$ EB, high $\RNINE$ 9.18 0.47
0.33 $\mu\mu$ EB, low $\RNINE$ 5.17 0.27 0.18 $\mu\mu$ EE 3.80 0.20 0.25
$\mu\mu$ Dijet tag 0.45 0.39 0.01 $\PH\to\cPZ\gamma\to\ell\ell\gamma$
$\Pe\Pe+\mu\mu$ Lepton tag 0.08 0.014 0.33 $\Pe\Pe$ Dijet tag 0.34 0.47 0.02
$\Pe\Pe$ Boosted 3.38 0.56 0.33 $\Pe\Pe$ Untagged 1 5.2 0.15 0.06 $\Pe\Pe$
Untagged 2 3.2 0.09 0.04 $\Pe\Pe$ Untagged 3 3.9 0.12 0.06 $\Pe\Pe$ Untagged 4
2.8 0.08 0.04 $\mu\mu$ Dijet tag 0.44 0.62 0.02 $\mu\mu$ Boosted 4.51 0.74
0.44 $\mu\mu$ Untagged 1 7.6 0.22 0.097 $\mu\mu$ Untagged 2 4.8 0.14 0.06
$\mu\mu$ Untagged 3 4.1 0.12 0.06 $\mu\mu$ Untagged 4 3.5 0.11 0.06

##  0.4 Signal and background modeling

The search for signal events is performed using a shape-based analysis of
$\ell\ell\gamma$ invariant mass distributions. The background is estimated
from data and the signal is estimated using the simulation. Even though the
background is estimated from data, simulated samples are used in the
$\PH\to\cPZ\gamma\to\ell\ell\gamma$ search to optimize the event classes. The
main background, $\Pp\Pp\to Z\gamma$, is generated at next-to-leading order
(NLO) using the generator [33]. The $\PZ(\ell\ell)$+jets events with a jet
misidentified as a photon are another important source of background and are
generated at NLO using . The NLO parton distribution function (PDF) set,
NNPDF3.0 [34], and the CUETP8M1 [35] underlying event tune are used to
generate these samples. All background events are interfaced with 8.205 [36,
37] for the fragmentation and hadronization of partons.

Signal samples for the $\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ produced via
$\Pg\Pg\PH$, VBF, and $\mathrm{V}\PH$ processes are simulated at NLO with
2.3.3, with the Higgs boson characterization framework [38, 39]. The
$\ttbar\PH$ production mechanism gives a negligible contribution to the signal
and is therefore ignored. For the $\PH\to\cPZ\gamma\to\ell\ell\gamma$ process,
the simulated events from all four production mechanisms are generated at NLO
using v2.0 [40, 41]. All signal samples are interfaced with 8.212 with the
CUETP8M1 underlying event tune for hadronization and fragmentation. The NLO
PDF set, NNPDF3.0, is used to produce these samples. The SM Higgs boson
production cross sections and branching fractions recommended by the LHC Higgs
cross section working group [14] are used for $\PH\to\cPZ\gamma$, whereas for
$\PH\to\gamma^{*}\gamma$ the Higgs boson production cross sections are also
taken from Ref. [14], but the branching fraction of $\PH\to\gamma^{*}\gamma$
is taken from the calculation and given in Eq.( 1).

The simulated signal and background events are reweighted by taking into
account the difference between data and simulated events so that the
distribution of pileup vertices, the trigger efficiencies, the resolution, the
energy scale, the reconstruction efficiencies, and the isolation
efficiency—for electrons, muons, and photons—observed in data are reproduced.
An additional correction is applied to photons to reproduce the performance of
the $\RNINE$ shower shape variable.

The dominant backgrounds to $\PH\to\ell\ell\gamma$ consist of the irreducible
non-resonant SM $\ell\ell\gamma$ production, final-state radiation in $\cPZ$
decays, $\gamma^{*}$ conversions, and Drell–Yan production in association with
jets, where a jet or a lepton is misidentified as a photon.

The background is estimated from data, by fitting the observed
$\ell\ell\gamma$ mass distributions. Separate fits are performed to the four
event classes for the $\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ analysis and the
thirteen classes for the $\PH\to\cPZ\gamma\to\ell\ell\gamma$ analysis. For the
$\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ ($\PH\to\cPZ\gamma\to\ell\ell\gamma$)
analysis, the range $110(115)<m_{\ell\ell\gamma}<170\GeV$ is used in the fit.
The fit model of the signal is obtained from an unbinned fit to the mass
distribution of the corresponding sample of simulated events, using a double
Crystal Ball function [42] in the $\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$
analysis, and a Crystal Ball function plus a Gaussian function in the
$\PH\to\cPZ\gamma\to\ell\ell\gamma$ analysis. To derive the signal shapes for
the intermediate mass points where simulation was not available, a linear
interpolation of the fitted parameters for available mass points was
performed.

The choice of the background fit function is based on a study that minimizes
the bias that could be introduced by the selected function. The study of the
bias is performed for four families of functions:

  1. 1.

A sum of $N$ exponential functions

$\sum\limits_{i=1}^{N}f_{i}\re^{p_{i}\,m_{\ell\ell\gamma}}$ (3)

with $2N$ free parameters: $p_{i}<0$ and $f_{i}$. The lowest order considered
has $N=$ 1.

  2. 2.

A sum of ${N}$ power-functions

$\sum\limits_{i=1}^{N}f_{i}m_{\ell\ell\gamma}^{p_{i}}\,$ (4)

with $2{N}$ free parameters $p_{i}<0$ and $f_{i}$. The lowest order considered
has $N=1$.

  3. 3.

Bernstein polynomials of $N$th order, with $N=1$, 2, 3, 4, and 5

$\mathrm{Ber}_{N}(m_{\ell\ell\gamma})=\sum\limits_{i=1}^{N}f_{i}^{2}\binom{N}{i}m_{\ell\ell\gamma}^{i}(1-m_{\ell\ell\gamma})^{N-i}$
(5)

with $N$ free parameters $f_{i}$.

  4. 4.

Laurent series with $N=2$, 3, and 4 terms

$f_{2}m_{\ell\ell\gamma}^{-4}+f_{3}m_{\ell\ell\gamma}^{-5},$ (6)
$f_{1}m_{\ell\ell\gamma}^{-3}+f_{2}m_{\ell\ell\gamma}^{-4}+f_{3}m_{\ell\ell\gamma}^{-5},$
(7)

and

$f_{1}m_{\ell\ell\gamma}^{-3}+f_{2}m_{\ell\ell\gamma}^{-4}+f_{3}m_{\ell\ell\gamma}^{-5}+f_{4}m_{\ell\ell\gamma}^{-6},$
(8)

with $N$ free parameters $f_{1\cdots N}$.

A test is then performed to determine the best order in each family. This test
uses the difference in the negative log-likelihood ($NLL$) between the fits
performed to data with two different orders of the same family of functions.
The test starts with the lowest order $N$ in that family of functions and the
order is increased to the $(N{+}M)^{th}$ order until the data support the
hypothesis of the higher-order function. For this purpose, a $p$-value of this
quantity is calculated as:

$p\text{-value}=\mathrm{Prob}(2\Delta{NLL}>2\Delta{NLL}_{N+M}|\chi^{2}(M)),$
(9)

where $\Delta NLL$ is the difference of log-likelihood between the two fits;
$\Delta NLL_{N+M}=2(NLL_{N}-NLL_{N+M})$ follows a $\chi^{2}$ distribution with
$M$ degrees of freedom, where $M$ is the difference in the number of free
parameters between the $N{+}M$ function and the $N$ function; $NLL_{N}$ and
$NLL_{N+M}$ are the values of the log-likelihood of the fit to data using
$N^{th}$ and $(N{+}M)^{th}$ order functions from a family. If the $p$-value is
less than 0.05, the higher order function is supported by the data and the
procedure is then applied to other higher order functions in the same family.
The procedure stops when the $p$-value becomes greater than 0.05.

Once the best order of each family is determined for each category, pseudo-
experiments (with no injected signal) describing possible experimental
outcomes are randomly generated using each of the determined functions as
generators of background. A signal-plus-background fit is performed for each
of these sets of pseudo-experiments with all other background functions of the
chosen order, so that the presence of a possible bias introduced by the
fitting function can be determined. In each fit, the bias is estimated with a
pull variable, computed as
($\mu_{\mathrm{FIT}}-\mu_{\mathrm{t}})/\sigma_{\mathrm{FIT}}$, where
$\mu_{\mathrm{FIT}}$ and $\sigma_{\mathrm{FIT}}$ are the mean and the standard
deviation of the signal strength determined from the signal-plus-background
fit, and $\mu_{\mathrm{t}}$ is the true injected signal strength, which is
zero in this case. A given fit function is deemed acceptable in a given
category if its pull is less than 0.14 when fitting pseudo-experiments
generated with all of the other functional families. With this requirement,
the error on the frequentist coverage of the quoted measurement in the
analysis is less than 1%, where the coverage is defined as the fraction of
experiments in which the true value is contained within the confidence
interval. If several functions pass this criterion, then we choose the one
which has the least pull. Table 0.4 shows the fit functions chosen in each
category of the analysis.

Fit functions chosen as a result of the bias study used in the analysis.
$m_{\ell\ell}$ Category Best fit function $<$50 EB, high $\RNINE$ Bernstein of
order 4 EB, low $\RNINE$ Bernstein of order 4 EE Bernstein of order 4 Dijet
tag Exponential of order 2 $>$50 Lepton tag Power law of order 1 Dijet tag
Power law of order 1 Boosted Bernstein of order 3 Untagged 1 Bernstein of
order 4 Untagged 2 Bernstein of order 5 Untagged 3 Bernstein of order 4
Untagged 4 Bernstein of order 4

The background fits based on the $m_{\ell\ell\gamma}$ data distributions for
the event categories of the $\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ analysis
are shown in Fig. 2 and, for the electron and muon channels in all
$\PH\to\cPZ\gamma\to\ell\ell\gamma$ event class definitions except for the
lepton tag category, in Figs. 3 and 4 respectively. Finally, Fig. 5 shows the
background fit for the lepton tag category in the
$\PH\to\cPZ\gamma\to\ell\ell\gamma$ analysis. As we can see from these
figures, the background fits describe the data well.

Figure 2:  Background model fit to the $m_{\mu\mu\gamma}$ distribution for EB-
high $\RNINE$ (upper left), EB-low $\RNINE$ (upper right), EE (lower left) and
dijet tag (lower right) for the $\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$
selection. The green and yellow bands represent the 68 and 95% uncertainties
in the fit to the data.

Figure 3: Background model fit to the $m_{\Pe\Pe\gamma}$ distribution for
dijet tag (upper left), boosted (upper right), untagged 1 (middle left),
untagged 2 (middle right), untagged 3 (bottom left), and untagged 4 (bottom
right) for the $\PH\to\cPZ\gamma\to\Pe\Pe\gamma$ selection. The green and
yellow bands represent the 68 and 95% uncertainties in the fit to the data.

Figure 4: Background model fit to the $m_{\mu\mu\gamma}$ distribution for
dijet tag (upper left), boosted (upper right), untagged 1 (middle left),
untagged 2 (middle right), untagged 3 (bottom left), and untagged 4 (bottom
right) for the $\PH\to\cPZ\gamma\to\mu\mu\gamma$ selection. The green and
yellow bands represent the 68 and 95% uncertainties in the fit to the data.
Figure 5: Background model fit to the $m_{\ell\ell\gamma}$ distribution for
$\PH\to\cPZ\gamma\to\ell\ell\gamma$ lepton tag category. The green and yellow
bands represent the 68 and 95% uncertainties in the fit to the data.

##  0.5 Systematic uncertainties and results

No significant deviation from the background-only hypothesis is observed. The
data are used to derive upper limits on the Higgs boson production cross
section times the branching fractions,
$\sigma(\Pp\Pp\to\PH)\,\mathcal{B}(\PH\to\gamma^{*}\gamma\to\mu\mu\gamma)$ and
$\sigma(\Pp\Pp\to\PH)\,\mathcal{B}(\PH\to\cPZ\gamma\to\ell\ell\gamma)$,
divided by the corresponding SM predictions. The limits are evaluated using a
modified frequentist approach, asymptotic , taking the profile likelihood as a
test statistic [43, 44, 45, 46]. An unbinned evaluation of the likelihood is
considered.

Background uncertainties are taken from the fit to the data. The sources of
systematic uncertainties related to the signal are listed below. The first two
sources affect the signal shape and the remaining sources affect the signal
yield.

  * •

Electron and photon energy scale and resolution: The electromagnetic energy
scale is known with 0.15–0.5 (1)% precision in EB (EE). To quantify the
corresponding uncertainty, the electron and photon energies are varied and the
effects on signal mean and resolution are propagated as shape nuisance
parameters in the estimation of limits.

  * •

Muon momentum scale and resolution: The uncertainty in the muon momentum scale
is 1%. To quantify the corresponding uncertainty, the muon momentum scale is
varied and the effect on signal mean and resolution is propagated as a shape
nuisance parameter in the estimation of limits.

  * •

Integrated luminosity: The uncertainty in the integrated luminosity is 2.5%
[47]. This is applied as a normalization uncertainty to the total expected
yield of the signal.

  * •

Object identification and isolation: The corrections applied to the simulation
to reproduce the performance of the lepton and photon selection are measured
with $\cPZ\to\Pe\Pe$ and $\cPZ\to\mu\mu$ events.

  * •

Pileup: The uncertainty from the description of the pileup in the signal
simulation is estimated by varying the total inelastic cross section by
$\pm$4.6% [48].

  * •

Jet-energy scale and resolution: The uncertainties in the jet energy scale and
resolution are accounted for by changing the jet response and resolution by
$\sim$2$\%$.

  * •

Underlying event and parton shower uncertainty: The uncertainty associated
with the choice and tuning of the generator is estimated with dedicated
samples which are generated by varying the parameters of the tune used
(CUETP8M1) to generate the original signal samples. The difference in signal
yields with respect to the nominal configuration is propagated as the
uncertainty.

  * •

$\RNINE$ reweighting: This shower-shape variable in the signal simulation is
reweighted to match that in the data. This reweighting introduces an
uncertainty that is estimated by removing the $\RNINE$ reweighting in the
simulation and then estimating the yields in the categories where $\RNINE$ is
used for categorization.

  * •

Theoretical uncertainties: These include the systematic uncertainties from the
effect of the choice of PDF on the signal cross section [49, 50, 51] and the
uncertainty in the Higgs boson branching fraction prediction. The uncertainty
in the branching ratio of $\PH\to\cPZ\gamma$ is calculated to be 5.6% [14]. In
the case of $\PH\to\gamma^{*}\gamma$ analysis, there is no available
theoretical uncertainty. So it is taken by rounding off the error on the
branching ratio of $\PH\to\cPZ\gamma$ to 6%.

The pre-fit values of the nuisance parameters, averaged over all the
categories, are summarized in Table 0.5.

Sources of systematic uncertainties considered in the
$\PH\to\cPZ\gamma\to\ell\ell\gamma$ and
$\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ analyses. The pre-fit values of the
nuisance parameters are shown averaged over all the categories in the analysis
which either affect the normalization of the simulated signal event yields or
the mean and resolution of $m_{\ell\ell\gamma}$. The “” indicates that the
uncertainty is not applicable.  Sources $\PH\to\cPZ\gamma\to\ell\ell\gamma$
$\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ Theory – $\Pg\Pg\PH$ cross section
(scale) $3.9\%$ $3.9\%$ – $\Pg\Pg\PH$ cross section (PDF) $3.2\%$ $3.2\%$ –
VBF cross section (scale) $+0.4\%-0.3\%$ $+0.4\%-0.3\%$ – VBF cross section
(PDF) $2.1\%$ $2.1\%$ – $\PW\PH$ cross section (scale) $+0.5\%-0.7\%$
$+0.5\%-0.7\%$ – $\PW\PH$ cross section (PDF) $1.9\%$ $1.9\%$ – $\cPZ\PH$
cross section (scale) $+3.8\%-3.1\%$ $+3.8\%-3.1\%$ – $\cPZ\PH$ cross section
(PDF) $1.6\%$ $1.6\%$ – $\ttbar\PH$ cross section (scale) $+5.8\%-9.2\%$ –
$\ttbar\PH$ cross section (PDF) $3.6\%$ Underlying event and parton shower –
Muon channel $3\%$ $4.7\%$ – Electron channel $3\%$ Branching fraction $5.7\%$
$6\%$ Integrated luminosity $2.5\%$ $2.5\%$ Lepton identification and
isolation – Muon channel $0.6\%$ $2\%$ – Electron channel $1.2\%$ Photon
identification and isolation – Muon channel $2.3\%$ $1.6\%$ – Electron channel
$2.2\%$ Pileup reweighting – Muon channel $0.6\%$ $0.3\%$ – Electron channel
$0.9\%$ reweighting – Muon channel $6.5\%$ $9\%$ – Electron channel $6.8\%$
Trigger – Muon channel $1.3\%$ $4\%$ – Electron channel $1\%$ Energy and
momentum (muon channel) – Signal mean $0.04\%$ $0.08\%$ – Signal resolution
$4\%$ $5\%$ Energy (electron channel) – Signal mean $0.15\%$ – Signal
resolution $4\%$ Jet energy scale – Muon channel $2.5\%$ $3.8\%$ – Electron
channel $2.7\%$ Jet energy resolution – Muon channel $0.3\%$ $0.7\%$ –
Electron channel $0.3\%$

Based on the fit bias studies, the uncertainty in the background estimation
due to the chosen functional form is assumed to be negligible. Furthermore, to
combine the $\PH\to\cPZ\gamma\to\ell\ell\gamma$ and
$\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ channels, uncertainties from
theoretical sources, integrated luminosity, object identification, $\RNINE$
reweighting, jet energy correction and resolution are considered to be
correlated across the categories.

The expected and observed exclusion limits at 95% for the process
$\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ are shown in Fig 6. The expected
limits are between 2.1 and 2.3 times the SM cross section and the observed
limit varies between about 1.4 and 4.0 times the SM cross section. The limits
are calculated at 1intervals in the mass range of $120<m_{\PH}<130\GeV$.
Figure 6 also shows the combined limit for the
$\PH\to\cPZ\gamma\to\ell\ell\gamma$ channel. The expected exclusion limits at
95% are between 3.9 and 9.1 times the SM cross section and the observed limit
varies between about 6.1 and 11.4 times the SM cross section.

Finally, Fig. 7 shows the expected limit for each category and the combined
limit for both channels for $m_{\PH}=125\GeV$. The combined observed
(background only expected) limit is 3.9 (2.0) for a 125Higgs boson decaying to
$\ell\ell\gamma$. The same figure shows the combined expected limit of 2.9,
assuming an SM Higgs boson with $m_{\PH}=125\GeV$, decaying to the
$\ell\ell\gamma$ channel. After combining both analyses,
$\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ and
$\PH\to\cPZ\gamma\to\ell\ell\gamma$ and considering the background-only
hypothesis, the observed $p$-value at $m_{\PH}=125\GeV$ is $0.02$, which
corresponds to about two standard deviations. The combined expected $p$-value
for an SM Higgs boson at $m_{\PH}=125\GeV$ is $0.16$, corresponding to a
significance of around one standard deviation.

##  0.6 Summary

A search is performed for a standard model (SM) Higgs boson decaying into a
lepton pair and a photon. This final state has contributions from Higgs boson
decays to a $\cPZ$ boson and a photon
($\PH\to\cPZ\gamma\to\ell\ell\gamma$,$\ell=\Pe$ or $\mu$), or to two photons,
one of which has an internal conversion into a muon pair
($\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$). The analysis is performed using a
data set from $\Pp\Pp$ collisions at a center-of-mass energy of 13,
corresponding to an integrated luminosity of 35.9. No significant excess above
the expected background is found. Limits on the Higgs boson production cross
section times the corresponding branching fractions are set. The expected
exclusion limits at 95% confidence level are about 2.1–2.3 (3.9–9.1) times the
SM cross section in the $\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$
($\PH\to\cPZ\gamma\to\ell\ell\gamma$) channel in the mass range from 120 to
130, and the observed limit varies between about 1.4 and 4.0 (6.1 and 11.4)
times the SM cross section. Finally, the
$\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ and
$\PH\to\cPZ\gamma\to\ell\ell\gamma$ analyses are combined for
$m_{\PH}=125\GeV$, obtaining an observed (expected) 95$\%$ confidence level
upper limit of 3.9 (2.0) times the SM cross section.

Figure 6:  Exclusion limit, at 95% , on the cross section of the
$\PH\to\gamma^{*}\gamma\to\mu\mu\gamma$ process (upper plot) and the
$\PH\to\cPZ\gamma\to\ell\ell\gamma$ process (lower plot) relative to the SM
prediction, as a function of the Higgs boson mass.  Figure 7:  Exclusion
limit, at 95% , on the cross section of $\PH\to\ell\ell\gamma$ relative to the
SM prediction, for an SM Higgs boson of $m_{\PH}=125\GeV$. The upper limits of
each analysis category, as well as their combinations, are shown. Black full
(empty) circles show the observed (background only expected) limit. Red
circles show the expected upper limit assuming an SM Higgs boson decaying to
$\ell\ell\gamma$ decay channel.

###### Acknowledgements.

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

## References

  * [1] A. Abbasabadi, D. Bowser-Chao, D. A. Dicus, and W. W. Repko, “Radiative Higgs boson decays $\PH\to ff\gamma$”,  Phys. Rev. D 55 (1997) 5647, 10.1103/PhysRevD.55.5647, arXiv:hep-ph/9611209.
  * [2] L. B. Chen, C. F. Qiao, and R. L. Zhu, “Reconstructing the 125 GeV SM Higgs boson through $\ell\bar{\ell}\gamma$”,  Phys. Lett. B 726 (2013) 306, 10.1016/j.physletb.2013.08.050, arXiv:1211.6058.
  * [3] Y. Sun, H. Chang, and D. Gao, “Higgs decays to $\gamma\ell^{+}\ell^{-}$ in the standard model”,  JHEP 05 (2013) 061, 10.1007/JHEP05(2013)061, arXiv:1303.2230.
  * [4] G. Passarino, “Higgs boson production and decay: Dalitz sector”,  Phys. Lett. B 727 (2013) 424, 10.1016/j.physletb.2013.10.052, arXiv:1308.0422.
  * [5] M. Carena, I. Low, and C. E. M. Wagner, “Implications of a modified Higgs to diphoton decay width”,  JHEP 08 (2012) 060, 10.1007/JHEP08(2012)060, arXiv:1206.1082.
  * [6] C.-S. Chen, C.-Q. Geng, D. Huang, and L.-H. Tsai, “New scalar contributions to $H\to Z\gamma$”,  Phys. Rev. D 87 (2013) 075019, 10.1103/PhysRevD.87.075019, arXiv:1301.4694.
  * [7] I. Low, J. Lykken, and G. Shaughnessy, “Singlet scalars as Higgs imposters at the Large Hadron Collider”,  Phys. Rev. D 84 (2011) 035027, 10.1103/PhysRevD.84.035027, arXiv:1105.4587.
  * [8] M. Bauer, M. Neubert, and A. Thamm, “LHC as an axion factory: Probing an axion explanation for $(g-2)_{\mu}$ with exotic Higgs decays”,  Phys. Rev. Lett. 119 (2017) 031802, 10.1103/PhysRevLett.119.031802, arXiv:1704.08207.
  * [9] A. Korchin and V. Kovalchuk, “Angular distribution and forward-backward asymmetry of the Higgs-boson decay to photon and lepton pair”,  Eur. Phys. J. C 74 (2014) 3141, 10.1140/epjc/s10052-014-3141-7, arXiv:1408.0342.
  * [10] C.-W. Chiang and K. Yagyu, “Higgs boson decays to $\gamma\gamma$ and Z$\gamma$ in models with Higgs extensions”,  Phys. Rev. D 87 (2013) 033003, 10.1103/PhysRevD.87.033003, arXiv:1207.1065.
  * [11] S. Dawson and P. P. Giardino, “Higgs decays to $ZZ$ and $Z\gamma$ in the standard model effective field theory: An NLO analysis”,  Phys. Rev. D 97 (2018), no. 9, 093003, 10.1103/PhysRevD.97.093003, arXiv:1801.01136.
  * [12] ATLAS and CMS Collaborations, “Combined measurement of the Higgs boson mass in $pp$ collisions at $\sqrt{s}=7$ and 8 TeV with the ATLAS and CMS experiments”,  Phys. Rev. Lett. 114 (2015) 191803, 10.1103/PhysRevLett.114.191803, arXiv:1503.07589.
  * [13] CMS Collaboration, “Measurements of properties of the Higgs boson decaying into the four-lepton final state in pp collisions at $\sqrt{s}=13$ TeV”,  JHEP 11 (2017) 047, 10.1007/JHEP11(2017)047, arXiv:1706.09936.
  * [14] LHC Higgs Cross Section Working Group Collaboration, “Handbook of LHC Higgs cross sections: 4. deciphering the nature of the higgs sector”, (2016). arXiv:1610.07922.
  * [15] J. M. Campbell and R. Ellis, “MCFM for the Tevatron and the LHC”,  Nucl. Phys. Proc. Suppl. 205 (2010) 10, 10.1016/j.nuclphysbps.2010.08.011, arXiv:1007.3492.
  * [16] D. A. Dicus and W. W. Repko, “Calculation of the decay $\PH\to\Pe\bar{\Pe}\gamma$”,  Phys. Rev. D 87 (2013) 077301, 10.1103/PhysRevD.87.077301, arXiv:1302.2159.
  * [17] D. A. Dicus and W. W. Repko, “Dalitz decay $\PH\to f\bar{f}\gamma$ as a background for $\PH\to\gamma\gamma$”,  Phys. Rev. D 89 (2014) 093013, 10.1103/PhysRevD.89.093013, arXiv:1402.5317.
  * [18] A. Firan and R. Stroynowski, “Internal conversions in Higgs decays to two photons”,  Phys. Rev. D 76 (2007) 057301, 10.1103/PhysRevD.76.057301, arXiv:0704.3987.
  * [19] ATLAS Collaboration, “Search for Higgs boson decays to a photon and a Z boson in pp collisions at $\sqrt{s}$ = 7 and 8 TeV with the ATLAS detector”,  Phys. Lett. B 732 (2014) 8, 10.1016/j.physletb.2014.03.015, arXiv:1402.3051.
  * [20] CMS Collaboration, “Search for a Higgs boson decaying into a Z and a photon in pp collisions at $\sqrt{s}=7$ and 8”,  Phys. Lett. B 726 (2013) 587, 10.1016/j.physletb.2013.09.057, arXiv:1307.5515.
  * [21] CMS Collaboration, “Search for a Higgs boson decaying into $\gamma^{*}\gamma\to\ell\ell\gamma$ with low dilepton mass in pp collisions at $\sqrt{s}=$ 8 TeV”,  Phys. Lett. B 753 (2016) 341, 10.1016/j.physletb.2015.12.039, arXiv:1507.03031.
  * [22] ATLAS Collaboration, “Searches for the $Z\gamma$ decay mode of the Higgs boson and for new high-mass resonances in $pp$ collisions at $\sqrt{s}=13$ TeV with the ATLAS detector”,  JHEP 10 (2017) 112, 10.1007/JHEP10(2017)112, arXiv:1708.00212.
  * [23] CMS Collaboration, “The CMS experiment at the CERN LHC”,  JINST 3 (2008) S08004, 10.1088/1748-0221/3/08/S08004.
  * [24] CMS Collaboration, “The CMS trigger system”,  JINST 12 (2017) P01020, 10.1088/1748-0221/12/01/P01020, arXiv:1609.02366.
  * [25] CMS Collaboration, “Particle-flow reconstruction and global event description with the CMS detector”,  JINST 12 (2017) P10003, 10.1088/1748-0221/12/10/P10003, arXiv:1706.04965.
  * [26] CMS Collaboration, “Performance of photon reconstruction and identification with the CMS detector in proton-proton collisions at $\sqrt{s}=8$ TeV”,  JINST 10 (2015) P08010, 10.1088/1748-0221/10/08/P08010, arXiv:1502.02702.
  * [27] CMS Collaboration, “Measurement of the inclusive $W$ and $Z$ production cross sections in $pp$ collisions at $\sqrt{s}=7$ TeV”,  JHEP 10 (2011) 132, 10.1007/JHEP10(2011)132, arXiv:1107.4789.
  * [28] M. Cacciari, G. P. Salam, and G. Soyez, “Fastjet user manual”,  Eur. Phys. J. C 72 (2012) 1896, 10.1140/epjc/s10052-012-1896-2, arXiv:1111.6097.
  * [29] M. Cacciari and G. P. Salam, “Pileup subtraction using jet areas”,  Phys. Lett. B 659 (2008) 119, 10.1016/j.physletb.2007.09.077, arXiv:0707.1378.
  * [30] M. Cacciari, G. P. Salam, and G. Soyez, “The catchment area of jets”,  JHEP 04 (2008) 005, 10.1088/1126-6708/2008/04/005, arXiv:0802.1188.
  * [31] D. L. Rainwater, R. Szalapski, and D. Zeppenfeld, “Probing color singlet exchange in $z$ \+ two jet events at the CERN LHC”,  Phys. Rev. D 54 (1996) 6680, 10.1103/PhysRevD.54.6680, arXiv:hep-ph/9605444.
  * [32] Particle Data Group Collaboration, “Review of particle physics”,  Chin. Phys. C 40 (2016), no. 10, 100001, 10.1088/1674-1137/40/10/100001.
  * [33] J. Alwall et al., “The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations”,  JHEP 07 (2014) 079, 10.1007/JHEP07(2014)079, arXiv:1405.0301.
  * [34] NNPDF Collaboration, “Parton distributions for the LHC run II”,  JHEP 04 (2015) 040, 10.1007/JHEP04(2015)040, arXiv:1410.8849.
  * [35] CMS Collaboration, “Event generator tunes obtained from underlying event and multiparton scattering measurements”,  Eur. Phys. J. C 76 (2016) 155, 10.1140/epjc/s10052-016-3988-x, arXiv:1512.00815.
  * [36] T. Sjöstrand, S. Mrenna, and P. Z. Skands, “A brief introduction to PYTHIA 8.1”,  Comput. Phys. Commun. 178 (2008) 852, 10.1016/j.cpc.2008.01.036, arXiv:0710.3820.
  * [37] T. Sjöstrand et al., “An introduction to PYTHIA 8.2”,  Comput. Phys. Commun. 191 (2015) 159, 10.1016/j.cpc.2015.01.024, arXiv:1410.3012.
  * [38] P. Artoisenet et al., “A framework for Higgs characterisation”,  JHEP 11 (2013) 043, 10.1007/JHEP11(2013)043, arXiv:1306.6464.
  * [39] P. de Aquino and K. Mawatari, “Characterising a Higgs-like resonance at the LHC”, in  Proceedings, 1st Toyama International Workshop on Higgs as a Probe of New Physics 2013 (HPNP2013): Toyama, Japan, February 13-16, 2013.  2013\.  arXiv:1307.5607.
  * [40] S. Alioli, P. Nason, C. Oleari, and E. Re, “NLO Higgs boson production via gluon fusion matched with shower in POWHEG”,  JHEP 04 (2009) 002, 10.1088/1126-6708/2009/04/002, arXiv:0812.0578.
  * [41] P. Nason and C. Oleari, “NLO Higgs boson production via vector-boson fusion matched with shower in POWHEG”,  JHEP 02 (2010) 037, 10.1007/JHEP02(2010)037, arXiv:0911.5299.
  * [42] M. J. Oreglia, “A study of the reactions $\psi^{\prime}\to\gamma\gamma\psi$”.  PhD thesis, Stanford University, 1980.  SLAC Report SLAC-R-236, see Appendix D.
  * [43] A. L. Read, “Presentation of search results: The CLs technique”,  J. Phys. G 28 (2002) 2693, 10.1088/0954-3899/28/10/313.
  * [44] T. Junk, “Confidence level computation for combining searches with small statistics”,  Nucl. Instrum. Meth. A 434 (1999) 435, 10.1016/S0168-9002(99)00498-2, arXiv:hep-ex/9902006.
  * [45] ATLAS and CMS Collaborations, The LHC Higgs combination group, “Procedure for the LHC Higgs boson search combination in summer 2011”, Technical Report CMS-NOTE-2011-005. ATL-PHYS-PUB-2011-11, 2011.
  * [46] G. Cowan, K. Cranmer, E. Gross, and O. Vitells, “Asymptotic formulae for likelihood-based tests of new physics”,  Eur. Phys. J. C 71 (2011) 1554, 10.1140/epjc/s10052-011-1554-0, arXiv:1007.1727. [Erratum: 10.1140/epjc/s10052-013-2501-z].
  * [47] CMS Collaboration, “CMS luminosity measurements for the 2016 data taking period”, CMS Physics Analysis Summary CMS-PAS-LUM-17-001, 2017.
  * [48] CMS Collaboration, “Measurement of the inelastic proton-proton cross section at $\sqrt{s}=$ 13 TeV”, (2018). arXiv:1802.02613.
  * [49] A. D. Martin, W. J. Stirling, R. S. Thorne, and G. Watt, “Parton distributions for the LHC”,  Eur. Phys. J. C 63 (2009) 189, 10.1140/epjc/s10052-009-1072-5, arXiv:0901.0002.
  * [50] H. Lai et al., “New parton distributions for collider physics”,  Phys. Rev. D 82 (2010) 74024, 10.1103/PhysRevD.82.074024, arXiv:1007.2241.
  * [51] J. Butterworth et al., “PDF4LHC recommendations for LHC run II”,  J. Phys. G 43 (2016) 023001, 10.1088/0954-3899/43/2/023001, arXiv:1510.03865.

##  .7 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, R. Frühwirth1, V.M.
Ghete, J. Hrubec, M. Jeitler1, N. Krammer, I. Krätschmer, D. Liko, T.
Madlener, I. Mikulec, N. Rad, H. Rohringer, J. Schieck1, R. Schöfbeck, M.
Spanring, D. Spitzbart, A. Taurok, W. Waltenberger, J. Wittmann, C.-E. Wulz1,
M. Zarucki Institute for Nuclear Problems, Minsk, Belarus
V. Chekhovsky, V. Mossolov, J. Suarez Gonzalez Universiteit Antwerpen,
Antwerpen, Belgium
E.A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, M. Pieters, M. Van De
Klundert, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel Vrije
Universiteit Brussel, Brussel, Belgium
S. Abu Zeid, F. Blekman, J. D’Hondt, I. De Bruyn, J. De Clercq, K. Deroover,
G. Flouris, D. Lontkovskyi, S. Lowette, I. Marchesini, S. Moortgat, L.
Moreels, Q. Python, K. Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders,
I. Van Parijs Université Libre de Bruxelles, Bruxelles, Belgium
D. Beghin, B. Bilin, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, B.
Dorney, G. Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk, A.K. Kalsi, T.
Lenzi, J. Luetic, N. Postiau, E. Starling, L. Thomas, C. Vander Velde, P.
Vanlaer, D. Vannerom, Q. Wang Ghent University, Ghent, Belgium
T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov2, D. Poyraz, C. Roskas,
D. Trocino, M. Tytgat, W. Verbeke, B. Vermassen, M. Vit, N. Zaganidis
Université Catholique de Louvain, Louvain-la-Neuve, Belgium
H. Bakhshiansohi, O. Bondu, S. Brochet, G. Bruno, C. Caputo, P. David, C.
Delaere, M. Delcourt, B. Francois, A. Giammanco, G. Krintiras, V. Lemaitre, A.
Magitteri, A. Mertens, M. Musich, K. Piotrzkowski, A. Saggio, M. Vidal Marono,
S. Wertz, J. Zobec Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro,
Brazil
F.L. Alves, G.A. Alves, L. Brito, G. Correia Silva, C. Hensel, A. Moraes, M.E.
Pol, P. Rebello Teles Universidade do Estado do Rio de Janeiro, Rio de
Janeiro, Brazil
E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato3, E. Coelho, E.M.
Da Costa, G.G. Da Silveira4, D. De Jesus Damiao, C. De Oliveira Martins, S.
Fonseca De Souza, H. Malbouisson, D. Matos Figueiredo, M. Melo De Almeida, C.
Mora Herrera, L. Mundim, H. Nogima, W.L. Prado Da Silva, L.J. Sanchez Rosas,
A. Santoro, A. Sznajder, M. Thiel, E.J. Tonelli Manganote3, F. Torres Da Silva
De Araujo, A. Vilela Pereira Universidade Estadual Paulista a, Universidade
Federal do ABC b, São Paulo, Brazil
S. Ahujaa, C.A. Bernardesa, L. Calligarisa, T.R. Fernandez Perez Tomeia, E.M.
Gregoresb, P.G. Mercadanteb, S.F. Novaesa, SandraS. Padulaa, D. Romero Abadb
Institute for Nuclear Research and Nuclear Energy, Bulgarian Academy of
Sciences, Sofia, Bulgaria
A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, A. Marinov, M. Misheva, M. Rodozov,
M. Shopova, G. Sultanov University of Sofia, Sofia, Bulgaria
A. Dimitrov, L. Litov, B. Pavlov, P. Petkov Beihang University, Beijing, China
W. Fang5, X. Gao5, L. Yuan Institute of High Energy Physics, Beijing, China
M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D.
Leggat, H. Liao, Z. Liu, F. Romeo, S.M. Shaheen, A. Spiezia, J. Tao, C. Wang,
Z. Wang, E. Yazgan, H. Zhang, J. Zhao State Key Laboratory of Nuclear Physics
and Technology, Peking University, Beijing, China
Y. Ban, G. Chen, A. Levin, J. Li, L. Li, Q. Li, Y. Mao, S.J. Qian, D. Wang, Z.
Xu Tsinghua University, Beijing, China
Y. Wang Universidad de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, C.A. Carrillo Montoya, L.F. Chaparro Sierra, C. Florez,
C.F. González Hernández, M.A. Segura Delgado University of Split, Faculty of
Electrical Engineering, Mechanical Engineering and Naval Architecture, Split,
Croatia
B. Courbon, N. Godinovic, D. Lelas, I. Puljak, T. Sculac University of Split,
Faculty of Science, Split, Croatia
Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia
V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, A. Starodumov6, T. Susa
University of Cyprus, Nicosia, Cyprus
M.W. Ather, A. Attikis, M. Kolosova, G. Mavromanolakis, J. Mousa, C. Nicolaou,
F. Ptochos, P.A. Razis, H. Rykaczewski Charles University, Prague, Czech
Republic
M. Finger7, M. Finger Jr.7 Escuela Politecnica Nacional, Quito, Ecuador
E. Ayala 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
H. Abdalla8, A.A. Abdelalim9,10, A. Mohamed10 National Institute of Chemical
Physics and Biophysics, Tallinn, Estonia
S. Bhowmik, A. Carvalho Antunes De Oliveira, R.K. Dewanjee, K. Ehataht, M.
Kadastik, M. Raidal, C. Veelken Department of Physics, University of Helsinki,
Helsinki, Finland
P. Eerola, H. Kirschenmann, J. Pekkanen, M. Voutilainen Helsinki Institute of
Physics, Helsinki, Finland
J. Havukainen, J.K. Heikkilä, T. Järvinen, V. Karimäki, R. Kinnunen, T.
Lampén, K. Lassila-Perini, S. Laurila, S. Lehti, T. Lindén, P. Luukka, T.
Mäenpää, H. Siikonen, E. Tuominen, J. Tuominiemi Lappeenranta University of
Technology, Lappeenranta, Finland
T. Tuuva IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
M. Besancon, F. Couderc, M. Dejardin, D. Denegri, J.L. Faure, F. Ferri, S.
Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, C. Leloup,
E. Locci, 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. Abdulsalam11, C. Amendola, I. Antropov, F. Beaudette, P. Busson, C.
Charlot, R. Granier de Cassagnac, I. Kucher, S. Lisniak, A. Lobanov, J. Martin
Blanco, M. Nguyen, C. Ochando, G. Ortona, P. Pigard, R. Salerno, J.B. Sauvan,
Y. Sirois, A.G. Stahl Leiton, A. Zabi, A. Zghiche Université de Strasbourg,
CNRS, IPHC UMR 7178, Strasbourg, France
J.-L. Agram12, J. Andrea, D. Bloch, J.-M. Brom, E.C. Chabert, V. Cherepanov,
C. Collard, E. Conte12, 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, N. Chanon, R. Chierici, D. Contardo, P.
Depasse, H. El Mamouni, J. Fay, L. Finco, S. Gascon, M. Gouzevitch, G.
Grenier, B. Ille, F. Lagarde, I.B. Laktineh, H. Lattaud, M. Lethuillier, L.
Mirabito, A.L. Pequegnot, S. Perries, A. Popov13, V. Sordini, M. Vander
Donckt, S. Viret, S. Zhang Georgian Technical University, Tbilisi, Georgia
A. Khvedelidze7 Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze7 RWTH Aachen University, I. Physikalisches Institut, Aachen,
Germany
C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, M.P.
Rauch, C. Schomakers, J. Schulz, M. Teroerde, B. Wittmer, V. Zhukov13 RWTH
Aachen University, III. Physikalisches Institut A, Aachen, Germany
A. Albert, D. Duchardt, M. Endres, M. Erdmann, T. Esch, R. Fischer, S. Ghosh,
A. Güth, T. Hebbeker, C. Heidemann, K. Hoepfner, H. Keller, S. Knutzen, L.
Mastrolorenzo, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, T. Pook, M.
Radziej, H. Reithler, M. Rieger, F. Scheuch, A. Schmidt, D. Teyssier RWTH
Aachen University, III. Physikalisches Institut B, Aachen, Germany
G. Flügge, O. Hlushchenko, B. Kargoll, T. Kress, A. Künsken, T. Müller, A.
Nehrkorn, A. Nowack, C. Pistone, O. Pooth, H. Sert, A. Stahl14 Deutsches
Elektronen-Synchrotron, Hamburg, Germany
M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, I. Babounikau, K.
Beernaert, O. Behnke, U. Behrens, A. Bermúdez Martínez, D. Bertsche, A.A. Bin
Anuar, K. Borras15, V. Botta, A. Campbell, P. Connor, C. Contreras-Campana, F.
Costanza, V. Danilov, A. De Wit, M.M. Defranchis, C. Diez Pardos, D. Domínguez
Damiani, G. Eckerlin, T. Eichhorn, A. Elwood, E. Eren, E. Gallo16, A. Geiser,
J.M. Grados Luyando, A. Grohsjean, P. Gunnellini, M. Guthoff, M. Haranko, A.
Harb, J. Hauk, H. Jung, M. Kasemann, J. Keaveney, C. Kleinwort, J. Knolle, D.
Krücker, W. Lange, A. Lelek, T. Lenz, K. Lipka, W. Lohmann17, R. Mankel, I.-A.
Melzer-Pellmann, A.B. Meyer, M. Meyer, M. Missiroli, G. Mittag, J. Mnich, V.
Myronenko, S.K. Pflitsch, D. Pitzl, A. Raspereza, M. Savitskyi, P. Saxena, P.
Schütze, C. Schwanenberger, R. Shevchenko, A. Singh, N. Stefaniuk, H. Tholen,
A. Vagnerini, G.P. Van Onsem, R. Walsh, Y. Wen, K. Wichmann, C. Wissing, O.
Zenaiev University of Hamburg, Hamburg, Germany
R. Aggleton, S. Bein, L. Benato, A. Benecke, V. Blobel, M. Centis Vignali, T.
Dreyer, E. Garutti, D. Gonzalez, J. Haller, A. Hinzmann, A. Karavdina, G.
Kasieczka, R. Klanner, R. Kogler, N. Kovalchuk, S. Kurz, V. Kutzner, J. Lange,
D. Marconi, J. Multhaup, M. Niedziela, D. Nowatschin, A. Perieanu, A. Reimers,
O. Rieger, C. Scharf, P. Schleper, S. Schumann, J. Schwandt, J. Sonneveld, H.
Stadie, G. Steinbrück, F.M. Stober, M. Stöver, D. Troendle, A. Vanhoefer, B.
Vormwald Karlsruher Institut fuer Technology
M. Akbiyik, C. Barth, M. Baselga, S. Baur, E. Butz, R. Caspart, T. Chwalek, F.
Colombo, W. De Boer, A. Dierlamm, N. Faltermann, B. Freund, M. Giffels, M.A.
Harrendorf, F. Hartmann14, S.M. Heindl, U. Husemann, F. Kassel14, I. Katkov13,
S. Kudella, H. Mildner, S. Mitra, 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, G.
Paspalaki, I. Topsis-Giotis National and Kapodistrian University of Athens,
Athens, Greece
G. Karathanasis, S. Kesisoglou, P. Kontaxakis, A. Panagiotou, N. Saoulidou, E.
Tziaferi, K. Vellidis National Technical University of Athens, Athens, Greece
K. Kousouris, I. Papakrivopoulos, G. Tsipolitis 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. Bartók18, M. Csanad, N. Filipovic, P. Major, M.I. Nagy, G. Pasztor, O.
Surányi, G.I. Veres Wigner Research Centre for Physics, Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath19, Á. Hunyadi, F. Sikler, T.Á. Vámi, V.
Veszpremi, G. Vesztergombi${}^{\textrm{\textdagger}}$ 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
P. Raics, Z.L. Trocsanyi, B. Ujvari Indian Institute of Science (IISc),
Bangalore, India
S. Choudhury, J.R. Komaragiri, P.C. Tiwari National Institute of Science
Education and Research, HBNI, Bhubaneswar, India
S. Bahinipati21, C. Kar, P. Mal, K. Mandal, A. Nayak22, D.K. Sahoo21, S.K.
Swain Panjab University, Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, S. Chauhan, R. Chawla, N. Dhingra, R.
Gupta, A. Kaur, A. Kaur, M. Kaur, S. Kaur, R. Kumar, P. Kumari, M. Lohan, A.
Mehta, K. Sandeep, S. Sharma, J.B. Singh, G. Walia University of Delhi, Delhi,
India
A. Bhardwaj, B.C. Choudhary, R.B. Garg, M. Gola, S. Keshri, Ashok Kumar, S.
Malhotra, M. Naimuddin, P. Priyanka, K. Ranjan, Aashaq Shah, R. Sharma Saha
Institute of Nuclear Physics, HBNI, Kolkata, India
R. Bhardwaj23, M. Bharti, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep23,
D. Bhowmik, S. Dey, S. Dutt23, S. Dutta, S. Ghosh, K. Mondal, S. Nandan, A.
Purohit, P.K. Rout, A. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, B. Singh,
S. Thakur23 Indian Institute of Technology Madras, Madras, India
P.K. Behera Bhabha Atomic Research Centre, Mumbai, India
R. Chudasama, D. Dutta, V. Jha, V. Kumar, P.K. Netrakanti, L.M. Pant, P.
Shukla Tata Institute of Fundamental Research-A, Mumbai, India
T. Aziz, M.A. Bhat, S. Dugad, G.B. Mohanty, N. Sur, B. Sutar, RavindraKumar
Verma Tata Institute of Fundamental Research-B, Mumbai, India
S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, Sa. Jain, S.
Karmakar, S. Kumar, M. Maity24, G. Majumder, K. Mazumdar, N. Sahoo, T.
Sarkar24 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, F. Rezaei Hosseinabadi, B. Safarzadeh26, M.
Zeinali University College Dublin, Dublin, Ireland
M. Felcini, M. Grunewald INFN Sezione di Bari a, Università di Bari b,
Politecnico di Bari c, Bari, Italy
M. Abbresciaa,b, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L. Cristellaa,b,
N. De Filippisa,c, M. De Palmaa,b, A. Di Florioa,b, F. Erricoa,b, L. Fiorea,
A. Gelmia,b, G. Iasellia,c, S. Lezkia,b, G. Maggia,c, M. Maggia, 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, G. Zitoa INFN Sezione di Bologna a, Università di
Bologna b, Bologna, Italy
G. Abbiendia, C. Battilanaa,b, D. Bonacorsia,b, L. Borgonovia,b, S. Braibant-
Giacomellia,b, R. Campaninia,b, P. Capiluppia,b, A. Castroa,b, F.R. Cavalloa,
S.S. Chhibraa,b, C. Cioccaa, G. Codispotia,b, M. Cuffiania,b, G.M.
Dallavallea, F. Fabbria, A. Fanfania,b, P. Giacomellia, C. Grandia, L.
Guiduccia,b, F. Iemmia,b, S. Marcellinia, G. Masettia, A. Montanaria, F.L.
Navarriaa,b, A. Perrottaa, F. Primaveraa,b,14, 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, A. Di Mattiaa, R. Potenzaa,b, A. Tricomia,b, C. Tuvea,b INFN
Sezione di Firenze a, Università di Firenze b, Firenze, Italy
G. Barbaglia, K. Chatterjeea,b, V. Ciullia,b, C. Civininia, R.
D’Alessandroa,b, E. Focardia,b, G. Latino, P. Lenzia,b, M. Meschinia, S.
Paolettia, L. Russoa,27, G. Sguazzonia, D. Stroma, L. Viliania INFN Laboratori
Nazionali di Frascati, Frascati, Italy
L. Benussi, S. Bianco, F. Fabbri, D. Piccolo INFN Sezione di Genova a,
Università di Genova b, Genova, Italy
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, S. Di
Guidaa,d,14, M.E. Dinardoa,b, S. Fiorendia,b, S. Gennaia, A. Ghezzia,b, P.
Govonia,b, M. Malbertia,b, S. Malvezzia, A. Massironia,b, D. Menascea, L.
Moronia, M. Paganonia,b, D. Pedrinia, 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, A. Di Crescenzoa,b, F. Fabozzia,c, F. Fiengaa,
G. Galatia, A.O.M. Iorioa,b, W.A. Khana, L. Listaa, S. Meolaa,d,14, P.
Paoluccia,14, C. Sciaccaa,b, E. Voevodinaa,b INFN Sezione di Padova a,
Università di Padova b, Padova, Italy, Università di Trento c, Trento, Italy
P. Azzia, N. Bacchettaa, D. Biselloa,b, A. Bolettia,b, A. Bragagnolo, P.
Checchiaa, M. Dall’Ossoa,b, P. De Castro Manzanoa, T. Dorigoa, U. Dossellia,
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,
A. Tiko, 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, P. Laricciaa,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, G. Bagliesia, L. Bianchinia, T. Boccalia, L.
Borrello, R. Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, G. Fedia, F. Fioria,c,
L. Gianninia,c, A. Giassia, M.T. Grippoa, F. Ligabuea,c, E. Mancaa,c, G.
Mandorlia,c, A. Messineoa,b, F. Pallaa, A. Rizzia,b, P. Spagnoloa, R.
Tenchinia, G. Tonellia,b, A. Venturia, P.G. Verdinia INFN Sezione di Roma a,
Sapienza Università di Roma b, Rome, Italy
L. Baronea,b, F. Cavallaria, M. Cipriania,b, N. Dacia, D. Del Rea,b, E. Di
Marcoa,b, M. Diemoza, S. Gellia,b, E. Longoa,b, B. Marzocchia,b, P.
Meridiania, G. Organtinia,b, F. Pandolfia, R. Paramattia,b, F. Preiatoa,b, S.
Rahatloua,b, C. Rovellia, F. Santanastasioa,b INFN Sezione di Torino a,
Università di Torino b, Torino, Italy, Università del Piemonte Orientale c,
Novara, Italy
N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, N. Bartosika,
R. Bellana,b, C. Biinoa, N. Cartigliaa, F. Cennaa,b, S. Cometti, M. Costaa,b,
R. Covarellia,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, D. Soldi,
A. Staianoa INFN Sezione di Trieste a, Università di Trieste b, Trieste, Italy
S. Belfortea, V. Candelisea,b, M. Casarsaa, F. Cossuttia, G. Della Riccaa,b,
F. Vazzolera,b, A. Zanettia Kyungpook National University
D.H. Kim, G.N. Kim, M.S. Kim, J. Lee, S. Lee, S.W. Lee, C.S. Moon, Y.D. Oh, S.
Sekmen, D.C. Son, Y.C. Yang Chonnam National University, Institute for
Universe and Elementary Particles, Kwangju, Korea
H. Kim, D.H. Moon, G. Oh Hanyang University, Seoul, Korea
J. Goh, T.J. Kim Korea University, Seoul, Korea
S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, K. Lee, K.S. Lee, S.
Lee, J. Lim, S.K. Park, Y. Roh Sejong University, Seoul, Korea
H.S. Kim 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
D. Jeon, 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 Ali28, F. Mohamad Idris29, W.A.T. Wan
Abdullah, M.N. Yusli, Z. Zolkapli Centro de Investigacion y de Estudios
Avanzados del IPN, Mexico City, Mexico
H. Castilla-Valdez, E. De La Cruz-Burelo, M.C. Duran-Osuna, I. Heredia-De La
Cruz30, R. Lopez-Fernandez, J. Mejia Guisao, R.I. Rabadan-Trejo, G. Ramirez-
Sanchez, R Reyes-Almanza, A. Sanchez-Hernandez Universidad Iberoamericana,
Mexico City, Mexico
S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita
Universidad Autonoma de Puebla, Puebla, Mexico
J. Eysermans, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad
Autónoma de San Luis Potosí, San Luis Potosí, Mexico
A. Morelos Pineda University of Auckland, Auckland, New Zealand
D. Krofcheck University of Canterbury, Christchurch, New Zealand
S. Bheesette, P.H. Butler National Centre for Physics, Quaid-I-Azam
University, Islamabad, Pakistan
A. Ahmad, M. Ahmad, M.I. Asghar, Q. Hassan, H.R. Hoorani, A. Saddique, M.A.
Shah, M. Shoaib, M. Waqas National Centre for Nuclear Research, Swierk, Poland
H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Górski, M. Kazana, K.
Nawrocki, M. Szleper, P. Traczyk, P. Zalewski Institute of Experimental
Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland
K. Bunkowski, A. Byszuk31, 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, A. Golunov, I. Golutvin, N. Gorbounov, I. Gorbunov, A. Kamenev,
V. Karjavin, A. Lanev, A. Malakhov, V. Matveev32,33, P. Moisenz, V. Palichik,
V. Perelygin, M. Savina, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, A.
Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg),
Russia
V. Golovtsov, Y. Ivanov, V. Kim34, E. Kuznetsova35, P. Levchenko, V. Murzin,
V. Oreshkin, I. Smirnov, D. Sosnov, V. Sulimov, L. Uvarov, S. Vavilov, A.
Vorobyev Institute for Nuclear Research, Moscow, Russia
Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov,
N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical
and Experimental Physics, Moscow, Russia
V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G.
Safronov, A. Spiridonov, A. Stepennov, V. Stolin, M. Toms, E. Vlasov, A.
Zhokin Moscow Institute of Physics and Technology, Moscow, Russia
T. Aushev National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
M. Chadeeva36, P. Parygin, D. Philippov, S. Polikarpov36, E. Popova, V.
Rusinov P.N. Lebedev Physical Institute, Moscow, Russia
V. Andreev, M. Azarkin33, I. Dremin33, M. Kirakosyan33, S.V. Rusakov, A.
Terkulov Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State
University, Moscow, Russia
A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin37, L. Dudko, A.
Ershov, A. Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S.
Obraztsov, S. Petrushanko, V. Savrin Novosibirsk State University (NSU),
Novosibirsk, Russia
V. Blinov38, T. Dimova38, L. Kardapoltsev38, D. Shtol38, Y. Skovpen38 State
Research Center of Russian Federation, Institute for High Energy Physics of
NRC “Kurchatov Institute”, Protvino, Russia
I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, A. Godizov, V. Kachanov,
A. Kalinin, D. Konstantinov, P. Mandrik, V. Petrov, R. Ryutin, S.
Slabospitskii, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov National
Research Tomsk Polytechnic University, Tomsk, Russia
A. Babaev, S. Baidali University of Belgrade, Faculty of Physics and Vinca
Institute of Nuclear Sciences, Belgrade, Serbia
P. Adzic39, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic Centro de
Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid,
Spain
J. Alcaraz Maestre, A. Álvarez Fernández, I. Bachiller, M. Barrio Luna, J.A.
Brochero Cifuentes, M. Cerrada, N. Colino, B. De La Cruz, A. Delgado Peris, C.
Fernandez Bedoya, J.P. Fernández Ramos, J. Flix, M.C. Fouz, O. Gonzalez Lopez,
S. Goy Lopez, J.M. Hernandez, M.I. Josa, D. Moran, A. Pérez-Calero Yzquierdo,
J. Puerta Pelayo, I. Redondo, L. Romero, M.S. Soares, A. Triossi Universidad
Autónoma de Madrid, Madrid, Spain
C. Albajar, J.F. de Trocóniz Universidad de Oviedo, Oviedo, Spain
J. Cuevas, C. Erice, J. Fernandez Menendez, S. Folgueras, I. Gonzalez
Caballero, J.R. González Fernández, E. Palencia Cortezon, V. Rodríguez Bouza,
S. Sanchez Cruz, P. Vischia, J.M. Vizan Garcia Instituto de Física de
Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain
I.J. Cabrillo, A. Calderon, B. Chazin Quero, J. Duarte Campderros, M.
Fernandez, P.J. Fernández Manteca, A. García Alonso, J. Garcia-Ferrero, G.
Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, P. Martinez Ruiz del
Arbol, F. Matorras, J. Piedra Gomez, C. Prieels, T. Rodrigo, A. Ruiz-Jimeno,
L. Scodellaro, N. Trevisani, I. Vila, R. Vilar Cortabitarte CERN, European
Organization for Nuclear Research, Geneva, Switzerland
D. Abbaneo, B. Akgun, E. Auffray, P. Baillon, A.H. Ball, D. Barney, J.
Bendavid, M. Bianco, A. Bocci, C. Botta, T. Camporesi, M. Cepeda, G.
Cerminara, E. Chapon, Y. Chen, G. Cucciati, D. d’Enterria, A. Dabrowski, V.
Daponte, A. David, A. De Roeck, N. Deelen, M. Dobson, T. du Pree, M. Dünser,
N. Dupont, A. Elliott-Peisert, P. Everaerts, F. Fallavollita40, D. Fasanella,
G. Franzoni, J. Fulcher, W. Funk, D. Gigi, A. Gilbert, K. Gill, F. Glege, M.
Guilbaud, D. Gulhan, J. Hegeman, V. Innocente, A. Jafari, P. Janot, O.
Karacheban17, J. Kieseler, A. Kornmayer, M. Krammer1, C. Lange, P. Lecoq, C.
Lourenço, L. Malgeri, M. Mannelli, F. Meijers, J.A. Merlin, S. Mersi, E.
Meschi, P. Milenovic41, F. Moortgat, M. Mulders, J. Ngadiuba, S. Orfanelli, L.
Orsini, F. Pantaleo14, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G.
Petrucciani, A. Pfeiffer, M. Pierini, F.M. Pitters, D. Rabady, A. Racz, T.
Reis, G. Rolandi42, M. Rovere, H. Sakulin, C. Schäfer, C. Schwick, M. Seidel,
M. Selvaggi, A. Sharma, P. Silva, P. Sphicas43, A. Stakia, J. Steggemann, M.
Tosi, D. Treille, A. Tsirou, V. Veckalns44, W.D. Zeuner Paul Scherrer
Institut, Villigen, Switzerland
L. Caminada45, 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, N. Chernyavskaya, G. Dissertori, M. Dittmar,
M. Donegà, C. Dorfer, C. Grab, C. Heidegger, D. Hits, J. Hoss, T. Klijnsma, W.
Lustermann, R.A. Manzoni, M. Marionneau, M.T. Meinhard, F. Micheli, P.
Musella, F. Nessi-Tedaldi, J. Pata, F. Pauss, G. Perrin, L. Perrozzi, S.
Pigazzini, M. Quittnat, D. Ruini, D.A. Sanz Becerra, M. Schönenberger, L.
Shchutska, V.R. Tavolaro, K. Theofilatos, M.L. Vesterbacka Olsson, R. Wallny,
D.H. Zhu Universität Zürich, Zurich, Switzerland
T.K. Aarrestad, C. Amsler46, D. Brzhechko, M.F. Canelli, A. De Cosa, R. Del
Burgo, S. Donato, C. Galloni, T. Hreus, B. Kilminster, I. Neutelings, D.
Pinna, G. Rauco, P. Robmann, D. Salerno, K. Schweiger, C. Seitz, Y. Takahashi,
A. Zucchetta National Central University, Chung-Li, Taiwan
Y.H. Chang, K.y. Cheng, T.H. Doan, Sh. Jain, H.R. Jheng, R. Khurana, C.M. Kuo,
M.Y. Lee, W. Lin, A. Pozdnyakov, V.L. Quilatan, S.S. Yu National Taiwan
University (NTU), Taipei, Taiwan
P. Chang, Y. Chao, K.F. Chen, P.H. Chen, W.-S. Hou, Arun Kumar, Y.y. Li, R.-S.
Lu, E. Paganis, A. Psallidas, A. Steen, J.f. Tsai Chulalongkorn University,
Faculty of Science, Department of Physics, Bangkok, Thailand
B. Asavapibhop, N. Srimanobhas, N. Suwonjandee Çukurova University, Physics
Department, Science and Art Faculty, Adana, Turkey
A. Bat, F. Boran, S. Cerci47, S. Damarseckin, Z.S. Demiroglu, F. Dolek, C.
Dozen, I. Dumanoglu, S. Girgis, G. Gokbulut, Y. Guler, E. Gurpinar, I. Hos48,
C. Isik, E.E. Kangal49, O. Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G.
Onengut, K. Ozdemir50, S. Ozturk51, D. Sunar Cerci47, B. Tali47, U.G. Tok, S.
Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University,
Physics Department, Ankara, Turkey
B. Isildak52, G. Karapinar53, M. Yalvac, M. Zeyrek Bogazici University,
Istanbul, Turkey
I.O. Atakisi, E. Gülmez, M. Kaya54, O. Kaya55, S. Tekten, E.A. Yetkin56
Istanbul Technical University, Istanbul, Turkey
M.N. Agaras, S. Atay, A. Cakir, K. Cankocak, Y. Komurcu, S. Sen57 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. Newbold58,
S. Paramesvaran, B. Penning, T. Sakuma, D. Smith, V.J. Smith, J. Taylor, A.
Titterton Rutherford Appleton Laboratory, Didcot, United Kingdom
K.W. Bell, A. Belyaev59, C. Brew, R.M. Brown, D. Cieri, D.J.A. Cockerill, J.A.
Coughlan, K. Harder, S. Harper, J. Linacre, E. Olaiya, D. Petyt, C.H.
Shepherd-Themistocleous, A. Thea, I.R. Tomalin, T. Williams, W.J. Womersley
Imperial College, London, United Kingdom
G. Auzinger, R. Bainbridge, P. Bloch, J. Borg, S. Breeze, O. Buchmuller, A.
Bundock, S. Casasso, D. Colling, L. Corpe, P. Dauncey, G. Davies, M. Della
Negra, R. Di Maria, Y. Haddad, G. Hall, G. Iles, T. James, M. Komm, C. Laner,
L. Lyons, A.-M. Magnan, S. Malik, A. Martelli, J. Nash60, A. Nikitenko6, V.
Palladino, M. Pesaresi, A. Richards, A. Rose, E. Scott, C. Seez, A.
Shtipliyski, G. Singh, M. Stoye, T. Strebler, S. Summers, A. Tapper, K.
Uchida, 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, C.K. Mackay, A. Morton, I.D. Reid,
L. Teodorescu, S. Zahid Baylor University, Waco, USA
K. Call, J. Dittmann, K. Hatakeyama, H. Liu, C. Madrid, B. Mcmaster, 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, T. Bose, D. Gastler, D. Rankin, C. Richardson, J. Rohlf, L. Sulak,
D. Zou Brown University, Providence, USA
G. Benelli, X. Coubez, D. Cutts, M. Hadley, J. Hakala, U. Heintz, J.M.
Hogan61, K.H.M. Kwok, E. Laird, G. Landsberg, J. Lee, Z. Mao, M. Narain, J.
Pazzini, S. Piperov, S. Sagir62, R. Syarif, E. Usai, 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, O. Kukral, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S.
Shalhout, M. Shi, D. Stolp, D. Taylor, K. Tos, M. Tripathi, Z. Wang, F. Zhang
University of California, Los Angeles, USA
M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M.
Ignatenko, N. Mccoll, S. Regnard, D. Saltzberg, C. Schnaible, V. Valuev
University of California, Riverside, Riverside, USA
E. Bouvier, K. Burt, R. Clare, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, G.
Karapostoli, E. Kennedy, F. Lacroix, O.R. Long, M. Olmedo Negrete, M.I.
Paneva, W. Si, L. Wang, H. Wei, S. Wimpenny, B.R. Yates University of
California, San Diego, La Jolla, USA
J.G. Branson, S. Cittolin, M. Derdzinski, R. Gerosa, D. Gilbert, B. Hashemi,
A. Holzner, D. Klein, G. Kole, V. Krutelyov, J. Letts, M. Masciovecchio, D.
Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A.
Vartak, S. 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, M. Citron, A. Dishaw,
V. Dutta, M. Franco Sevilla, L. Gouskos, R. Heller, J. Incandela, A.
Ovcharova, H. Qu, J. Richman, D. Stuart, I. Suarez, S. Wang, J. Yoo California
Institute of Technology, Pasadena, USA
D. Anderson, A. Bornheim, J.M. Lawhorn, H.B. Newman, T.Q. Nguyen, M.
Spiropulu, J.R. Vlimant, R. Wilkinson, S. Xie, Z. Zhang, R.Y. Zhu Carnegie
Mellon University, Pittsburgh, USA
M.B. Andrews, T. Ferguson, T. Mudholkar, M. Paulini, M. Sun, I. Vorobiev, M.
Weinberg University of Colorado Boulder, Boulder, USA
J.P. Cumalat, W.T. Ford, F. Jensen, A. Johnson, M. Krohn, S. Leontsinis, E.
MacDonald, T. Mulholland, K. Stenson, K.A. Ulmer, S.R. Wagner Cornell
University, Ithaca, USA
J. Alexander, J. Chaves, Y. Cheng, J. Chu, A. Datta, K. Mcdermott, N. Mirman,
J.R. Patterson, D. Quach, A. Rinkevicius, A. Ryd, L. Skinnari, L. Soffi, S.M.
Tan, Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek Fermi National
Accelerator Laboratory, Batavia, USA
S. Abdullin, M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, A. Apyan, S.
Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, G.
Bolla${}^{\textrm{\textdagger}}$, K. Burkett, J.N. Butler, A. Canepa, G.B.
Cerati, H.W.K. Cheung, F. Chlebana, M. Cremonesi, J. Duarte, V.D. Elvira, J.
Freeman, Z. Gecse, E. Gottschalk, L. Gray, D. Green, S. Grünendahl, O.
Gutsche, J. Hanlon, R.M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, B.
Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, B. Klima, M.J. Kortelainen,
B. Kreis, S. Lammel, D. Lincoln, R. Lipton, M. Liu, T. Liu, J. Lykken, K.
Maeshima, J.M. Marraffino, D. Mason, P. McBride, P. Merkel, S. Mrenna, S.
Nahn, V. O’Dell, K. Pedro, C. Pena, O. Prokofyev, G. Rakness, L. Ristori, A.
Savoy-Navarro64, 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, L. Cadamuro,
A. Carnes, M. Carver, D. Curry, R.D. Field, S.V. Gleyzer, B.M. Joshi, J.
Konigsberg, A. Korytov, P. Ma, K. Matchev, H. Mei, G. Mitselmakher, K. Shi, D.
Sperka, J. Wang, S. Wang Florida International University, Miami, USA
Y.R. Joshi, S. Linn 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, M.
Rahmani, T. Roy, F. Yumiceva University of Illinois at Chicago (UIC), Chicago,
USA
M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, R. Cavanaugh, X. Chen, S.
Dittmer, O. Evdokimov, C.E. Gerber, D.A. Hangal, D.J. Hofman, K. Jung, J.
Kamin, C. Mills, I.D. Sandoval Gonzalez, M.B. Tonjes, N. Varelas, H. Wang, X.
Wang, Z. Wu, J. Zhang The University of Iowa, Iowa City, USA
M. Alhusseini, B. Bilki65, W. Clarida, K. Dilsiz66, S. Durgut, R.P.
Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, A. Mestvirishvili, A.
Moeller, J. Nachtman, H. Ogul67, Y. Onel, F. Ozok68, A. Penzo, C. Snyder, E.
Tiras, J. Wetzel Johns Hopkins University, Baltimore, USA
B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan,
W.T. Hung, 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, A. Bylinkin, J.
Castle, S. Khalil, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, C.
Rogan, S. Sanders, E. Schmitz, J.D. Tapia Takaki, Q. Wang Kansas State
University, Manhattan, USA
A. Ivanov, K. Kaadze, D. Kim, Y. Maravin, D.R. Mendis, T. Mitchell, A. Modak,
A. Mohammadi, L.K. Saini, N. Skhirtladze Lawrence Livermore National
Laboratory, Livermore, USA
F. Rebassoo, D. Wright University of Maryland, College Park, USA
A. Baden, O. Baron, A. Belloni, S.C. Eno, Y. Feng, C. Ferraioli, N.J. Hadley,
S. Jabeen, G.Y. Jeng, R.G. Kellogg, J. Kunkle, A.C. Mignerey, F. Ricci-Tam,
Y.H. Shin, A. Skuja, S.C. Tonwar, K. Wong Massachusetts Institute of
Technology, Cambridge, USA
D. Abercrombie, B. Allen, V. Azzolini, A. Baty, G. Bauer, R. Bi, S. Brandt, W.
Busza, I.A. Cali, M. D’Alfonso, Z. Demiragli, G. Gomez Ceballos, M. Goncharov,
P. Harris, D. Hsu, M. Hu, Y. Iiyama, G.M. Innocenti, M. Klute, D. Kovalskyi,
Y.-J. Lee, P.D. Luckey, B. Maier, A.C. Marini, C. Mcginn, C. Mironov, S.
Narayanan, X. Niu, C. Paus, C. Roland, G. Roland, G.S.F. Stephans, K. Sumorok,
K. Tatar, D. Velicanu, J. Wang, T.W. Wang, B. Wyslouch, S. Zhaozhong
University of Minnesota, Minneapolis, USA
A.C. Benvenuti, R.M. Chatterjee, A. Evans, P. Hansen, S. Kalafut, Y. Kubota,
Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack, J. Turkewitz, M.A.
Wadud University of Mississippi, Oxford, USA
J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA
E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, F. Golf, R. Gonzalez Suarez,
R. Kamalieddin, I. Kravchenko, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger
State University of New York at Buffalo, Buffalo, USA
A. Godshalk, C. Harrington, I. Iashvili, A. Kharchilava, D. Nguyen, A. Parker,
S. Rappoccio, B. Roozbahani Northeastern University, Boston, USA
G. Alverson, E. Barberis, C. Freer, A. Hortiangtham, D.M. Morse, T. Orimoto,
R. Teixeira De Lima, T. Wamorkar, B. Wang, A. Wisecarver, D. Wood Northwestern
University, Evanston, USA
S. Bhattacharya, O. Charaf, K.A. Hahn, N. Mucia, N. Odell, M.H. Schmitt, K.
Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, USA
R. Bucci, N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N.
Kellams, K. Lannon, W. Li, N. Loukas, N. Marinelli, F. Meng, C. Mueller, Y.
Musienko32, M. Planer, A. Reinsvold, R. Ruchti, P. Siddireddy, G. Smith, S.
Taroni, M. Wayne, A. Wightman, M. Wolf, A. Woodard The Ohio State University,
Columbus, USA
J. Alimena, L. Antonelli, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, A.
Hart, C. Hill, W. Ji, T.Y. Ling, W. Luo, B.L. Winer, H.W. Wulsin Princeton
University, Princeton, USA
S. Cooperstein, P. Elmer, J. Hardenbrook, P. Hebda, S. Higginbotham, A.
Kalogeropoulos, D. Lange, M.T. Lucchini, J. Luo, D. Marlow, K. Mei, I. Ojalvo,
J. Olsen, C. Palmer, P. Piroué, J. Salfeld-Nebgen, D. Stickland, C. Tully
University of Puerto Rico, Mayaguez, USA
S. Malik, S. Norberg Purdue University, West Lafayette, USA
A. Barker, V.E. Barnes, S. Das, L. Gutay, M. Jones, A.W. Jung, A. Khatiwada,
B. Mahakud, D.H. Miller, N. Neumeister, C.C. Peng, H. Qiu, J.F. Schulte, J.
Sun, F. Wang, R. Xiao, W. Xie Purdue University Northwest, Hammond, USA
T. Cheng, J. Dolen, N. Parashar Rice University, Houston, USA
Z. Chen, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. 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, J.L. Dulemba, C. Fallon, T.
Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs, A.
Khukhunaishvili, K.H. Lo, P. Tan, R. Taus, M. Verzetti Rutgers, The State
University of New Jersey, Piscataway, USA
A. Agapitos, J.P. Chou, Y. Gershtein, T.A. Gómez Espinosa, E. Halkiadakis, M.
Heindl, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath,
R. Montalvo, K. Nash, M. Osherson, H. Saka, S. Salur, S. Schnetzer, D.
Sheffield, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker
University of Tennessee, Knoxville, USA
A.G. Delannoy, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa Texas A&M
University, College Station, USA
O. Bouhali69, A. Castaneda Hernandez69, A. Celik, M. Dalchenko, M. De Mattia,
A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, T. Kamon70, S. Luo,
R. Mueller, Y. Pakhotin, R. Patel, A. Perloff, L. Perniè, D. Rathjens, A.
Safonov, A. Tatarinov Texas Tech University, Lubbock, USA
N. Akchurin, J. Damgov, F. De Guio, P.R. Dudero, S. Kunori, K. Lamichhane,
S.W. Lee, T. Mengke, S. Muthumuni, T. Peltola, S. Undleeb, I. Volobouev, Z.
Wang Vanderbilt University, Nashville, USA
S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K.
Padeken, J.D. Ruiz Alvarez, P. Sheldon, S. Tuo, J. Velkovska, M. Verweij, Q.
Xu University of Virginia, Charlottesville, USA
M.W. Arenton, P. Barria, B. Cox, R. Hirosky, M. Joyce, A. Ledovskoy, H. Li, C.
Neu, T. Sinthuprasith, Y. Wang, E. Wolfe, F. Xia Wayne State University,
Detroit, USA
R. Harr, P.E. Karchin, N. Poudyal, J. Sturdy, P. Thapa, S. Zaleski University
of Wisconsin - Madison, Madison, WI, USA
M. Brodski, J. Buchanan, C. Caillol, D. Carlsmith, S. Dasu, L. Dodd, S. Duric,
B. Gomber, M. Grothe, M. Herndon, A. Hervé, U. Hussain, P. Klabbers, A.
Lanaro, A. Levine, K. Long, R. Loveless, T. Ruggles, A. Savin, N. Smith, W.H.
Smith, N. Woods †: Deceased
1: Also at Vienna University of Technology, Vienna, Austria
2: Also at IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
3: Also at Universidade Estadual de Campinas, Campinas, Brazil
4: Also at Federal University of Rio Grande do Sul, Porto Alegre, Brazil
5: Also at Université Libre de Bruxelles, Bruxelles, Belgium
6: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia
7: Also at Joint Institute for Nuclear Research, Dubna, Russia
8: Also at Cairo University, Cairo, Egypt
9: Also at Helwan University, Cairo, Egypt
10: Now at Zewail City of Science and Technology, Zewail, Egypt
11: Also at Department of Physics, King Abdulaziz University, Jeddah, Saudi
Arabia
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 Shoolini University, Solan, India
24: Also at University of Visva-Bharati, Santiniketan, India
25: Also at Isfahan University of Technology, Isfahan, Iran
26: Also at Plasma Physics Research Center, Science and Research Branch,
Islamic Azad University, Tehran, Iran
27: Also at Università degli Studi di Siena, Siena, Italy
28: Also at International Islamic University of Malaysia, Kuala Lumpur,
Malaysia
29: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia
30: Also at Consejo Nacional de Ciencia y Tecnología, Mexico city, Mexico
31: Also at Warsaw University of Technology, Institute of Electronic Systems,
Warsaw, Poland
32: Also at Institute for Nuclear Research, Moscow, Russia
33: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
34: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
35: Also at University of Florida, Gainesville, USA
36: Also at P.N. Lebedev Physical Institute, Moscow, Russia
37: Also at California Institute of Technology, Pasadena, USA
38: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
39: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
40: Also at INFN Sezione di Pavia a, Università di Pavia b, Pavia, Italy
41: Also at University of Belgrade, Faculty of Physics and Vinca Institute of
Nuclear Sciences, Belgrade, Serbia
42: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy
43: Also at National and Kapodistrian University of Athens, Athens, Greece
44: Also at Riga Technical University, Riga, Latvia
45: Also at Universität Zürich, Zurich, Switzerland
46: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna,
Austria
47: Also at Adiyaman University, Adiyaman, Turkey
48: Also at Istanbul Aydin University, Istanbul, Turkey
49: Also at Mersin University, Mersin, Turkey
50: Also at Piri Reis University, Istanbul, Turkey
51: Also at Gaziosmanpasa University, Tokat, Turkey
52: Also at Ozyegin University, Istanbul, Turkey
53: Also at Izmir Institute of Technology, Izmir, Turkey
54: Also at Marmara University, Istanbul, Turkey
55: Also at Kafkas University, Kars, Turkey
56: Also at Istanbul Bilgi University, Istanbul, Turkey
57: Also at Hacettepe University, Ankara, Turkey
58: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom
59: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
60: Also at Monash University, Faculty of Science, Clayton, Australia
61: Also at Bethel University, St. Paul, USA
62: Also at Karamanoğlu Mehmetbey University, Karaman, Turkey
63: Also at Utah Valley University, Orem, USA
64: Also at Purdue University, West Lafayette, USA
65: Also at Beykent University, Istanbul, Turkey
66: Also at Bingol University, Bingol, 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