EXO-17-017

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EXO-17-017

# Search for physics beyond the standard model in high-mass diphoton events
from proton-proton collisions at $\sqrt{s}=13\TeV$

###### Abstract

A search for physics beyond the standard model is performed using a sample of
high-mass diphoton events produced in proton-proton collisions at
$\sqrt{s}=13\TeV$. The data sample was collected in 2016 with the CMS detector
at the LHC and corresponds to an integrated luminosity of 35.9. The search is
performed for both resonant and nonresonant new physics signatures. At 95%
confidence level, lower limits on the mass of the first Kaluza–Klein
excitation of the graviton in the Randall–Sundrum warped extra-dimensional
model are determined to be in the range of 2.3 to 4.6, for values of the
associated coupling parameter between 0.01 and 0.2. Lower limits on the
production of scalar resonances and model-independent cross section upper
limits are also provided. For the large extra-dimensional model of Arkani-
Hamed, Dimopoulos, and Dvali, lower limits are set on the string mass scale
$M_{\mathrm{S}}$ ranging from 5.6 to 9.7, depending on the model parameters.
The first exclusion limits are set in the two-dimensional parameter space of a
continuum clockwork model.

##  0.1 Introduction

While the standard model (SM) of particle physics has been an enormously
successful description of observed phenomena, it is still widely believed to
be incomplete. In the SM, the Higgs boson mass receives quantum corrections
from loops containing SM particles. Because the Higgs boson is a fundamental
scalar, the magnitude of the mass corrections is set by the cutoff parameter
of the loop integrals and the only natural mass scale in the SM that can act
as a cutoff is the Planck scale ($\Mpl\sim 10^{19}\GeV$) at which quantum
gravity is expected to emerge. Therefore, unless the Higgs boson mass
parameter is fine-tuned to an extreme degree, there must exist some new
physics beyond the SM to constrain these quantum corrections and stabilize the
mass of the Higgs boson. Many models for such new physics have been proposed.
We consider three such models in this paper.

Through their modification of the effective Planck scale, extra spatial
dimensions have been proposed as a possible solution to this hierarchy problem
[1, 2], which arises from the large difference between the gravitational and
electroweak scales. In the model proposed by Arkani-Hamed, Dimopoulos, and
Dvali (ADD) [3, 4, 5], the existence of $n_{\mathrm{ED}}$ additional spatial
dimensions, compactified with an average radius $r_{\mathrm{c}}$, produces an
effective Planck mass $M_{\mathrm{Pl}}$ in our four-dimensional (4D) world
that is related to the true Planck mass by $M^{2}_{\mathrm{Pl}}\sim
M^{2+n_{\mathrm{ED}}}_{\mathrm{Pl}(4+n_{\mathrm{ED}})}r_{\mathrm{c}}^{n_{\mathrm{ED}}}$.
It is therefore possible, with appropriate values for $n_{\mathrm{ED}}$ and
$r_{\mathrm{c}}$, that the value of the Planck scale in
(4+$n_{\mathrm{ED}}$)-dimensional spacetime,
$M_{\mathrm{Pl}(4+n_{\mathrm{ED}})}$, could be of the order of the electroweak
scale, thus solving the SM hierarchy problem, while still producing the much
larger apparent Planck scale that we observe in our 4D world. In effect, the
true strength of gravity could actually be comparable to the electroweak
force, and it merely appears weaker because of its propagation in the extra
dimensions. At the same time, the SM gauge forces and particles are confined
to our 4D spacetime.

Randall and Sundrum (RS) proposed an alternative model [6, 7] with just one
additional dimension that has a warped geometry, described by a curvature
parameter $k$. The extra dimension is compactified with radius
$r_{\mathrm{c}}$. From the point of view of a 4D observer, a fundamental mass
parameter $m_{0}$ defined on the SM brane in the full five-dimensional (5D)
theory will appear as a physical mass $m=\re^{-kr_{\mathrm{c}}\pi}m_{0}$. In
this model, solving the hierarchy problem requires that the fundamental mass
should be $m_{0}\sim\Mpl$ and the observed mass should be at the scale.
Because of the exponential warp factor, this large hierarchy can be generated
if $kr_{\mathrm{c}}\approx 11$–12, thus requiring very little fine tuning.

A third proposed solution to the hierarchy problem that we consider in this
paper is the continuum clockwork mechanism [8], which coincides with a 5D
gravitational theory on a linear dilaton background [9, 10]. The clockwork
[11, 12] is a general mechanism that can introduce large effective interaction
scales from dynamics occurring at much lower energies. This is achieved by
introducing $N$ copies of some particle content on different sites forming a
one-dimensional lattice in theory space. The physical mass spectrum consists
of a single massless mode localized on the end site of the lattice and a set
of massive modes (‘gears’) distributed along the sites. In the continuum limit
of the clockwork with $N\to\infty$, this lattice is interpreted as a physical
extra dimension.

In all three models, deviations from the SM expectations should be evident at
the CERN LHC through Kaluza–Klein (KK) modes of the graviton, which couple to
the SM through the stress-energy tensor and decay into two SM particles.
Searches for pairs of high-mass photons are favorable because the SM
backgrounds are lower and the mass resolution is better than in the dijet
channel, and the branching fraction to diphoton final states is larger than
that to dilepton final states. In the ADD model, the compactification of the
extra dimensions gives rise to a KK series of virtual graviton states because
the momenta along the extra dimensions are quantized and appear as additional
contributions to the graviton effective mass. Here, the KK modes are very
closely spaced, leading to an effective nonresonant enhancement of the
diphoton spectrum at high invariant mass ($m_{\gamma\gamma}$). In the RS
model, the presence of the additional spatial dimension quantizes the masses
of the KK states. These states are widely spaced and become narrow in the
limit of small $\tilde{k}\equiv k/\overline{\Mpl}$, where
$\overline{\Mpl}=\Mpl/\sqrt{\smash[b]{8\pi}}$ is the reduced Planck mass. In
the continuum clockwork mechanism, the gears play the role of the KK modes.
The usual massless graviton is accompanied by an infinite tower of massive
spin-2 graviton gears with a characteristic pattern of masses and couplings.
In particular, the masses of the graviton gears can be so densely distributed
that they produce an approximately continuous contribution to the diphoton
spectrum as a function of $m_{\gamma\gamma}$ [13, 14], much like in the ADD
model. However, unlike the ADD model, the KK modes are entirely on shell, as
in the RS case, so interference effects are negligible.

In addition to the above models that could address the hierarchy problem,
high-mass diphoton events are also potentially sensitive to other beyond-SM
physics, such as the decays of heavy spin-0 resonances. These spin-0
resonances could arise from extended Higgs sectors [15, 16, 17]. Model-
independent cross section limits can be obtained on generic production of
exotic spin-0 and spin-2 resonances decaying to pairs of photons.

Searches for new physics in the high-mass diphoton channel from Run 2 of the
LHC were previously performed by the ATLAS and CMS experiments using $\Pp\Pp$
collisions at a center-of-mass energy $\sqrt{s}=13\TeV$ [18, 19, 20, 21].
Prior searches have also been performed by both experiments in Run 1 of the
LHC [22, 23, 24, 25], at $\sqrt{s}=7$ and 8, and also at the Tevatron by the
CDF [26] and [27] experiments using $\Pp\Pap$ collisions at
$\sqrt{s}=1.96\TeV$.

We present new results from a search for beyond-SM physics in the high-mass
diphoton spectrum, using data collected with the CMS detector in 2016
corresponding to an integrated luminosity of 35.9. Two complementary
background estimation techniques are used. For a search for resonant excesses
such as in the RS model, we implement a technique where the diphoton spectrum
is fit to a parametrized functional form, allowing for a fully data-driven
description of the shape. To search for nonresonant deviations from the SM
prediction like those that arise in the ADD and clockwork models, a next-to-
next-to-leading-order (NNLO) calculation of the SM diphoton background is
performed and the background from jets being misidentified as photons is
estimated from control samples in data.

The remainder of this document is organized as follows. The CMS detector is
described in Section 0.2. Event reconstruction and selection are outlined in
Section 0.3. Section 0.4 describes the simulation of extra-dimensional signal
models, and the background determinations for the searches for resonant and
nonresonant excesses are described in Section 0.5. Sources of systematic
uncertainty are discussed in Section 0.6. We present our results in Section
0.7.

##  0.2 The CMS detector

The CMS detector is a multi-purpose collider detector at the LHC. The central
feature of the CMS apparatus is a superconducting solenoid of 6m internal
diameter, providing a magnetic field of 3.8T. Within the solenoid volume are a
silicon pixel and strip tracker, a lead tungstate crystal electromagnetic
calorimeter (ECAL), and a brass and scintillator hadron calorimeter (HCAL),
each composed of a barrel and two endcap sections. Forward calorimeters extend
the pseudorapidity ($\eta$) coverage provided by the barrel and endcap
detectors. Muons are detected in gas-ionization chambers embedded in the steel
flux-return yoke outside the solenoid.

The ECAL barrel (EB) provides coverage in the range $\abs{\eta}<1.48$. This is
extended by each ECAL endcap (EE) to $1.48<\abs{\eta}<3$. In the EB, photons
that have energies above the range of tens of GeV have an energy resolution of
about 1.3% up to $\abs{\eta}=1$, rising to about 2.5% at $\abs{\eta}=1.4$. In
each EE, photons in this energy range have a resolution between 3 and 4% [28].

Events of interest are selected using a two-tiered trigger system [29]. The
first level, composed of custom hardware processors, uses information from the
calorimeters and muon detectors to select events at a rate of around 100kHz
within a time interval of less than 4. The second level, known as the high-
level trigger, consists of a farm of processors running a version of the full
event reconstruction software optimized for fast processing, and reduces the
event rate to around 1kHz before data storage.

A more detailed description of the CMS detector, together with a definition of
the coordinate system used and the relevant kinematic variables, can be found
in Ref. [30].

##  0.3 Event reconstruction and selection

Individual particles in the CMS detector are reconstructed using the particle-
flow event algorithm [31]. Photon candidates are reconstructed from energy
deposits in the ECAL. Individual energy deposits are grouped into
superclusters [28] that are compatible with the expected shower shape
extending along the azimuthal ($\phi$) direction. This allows for the recovery
of the energy deposited by bremsstrahlung and photon conversions. The
clustering algorithm does not make any hypothesis as to whether the particle
originating from the interaction point is a photon or an electron. Thus the
same algorithm used for photon reconstruction can be applied to
$\cPZ\to\Pep\Pem$ events and these events are used to measure the efficiency
of the photon selection criteria and of the photon energy scale and
resolution. A more detailed description of photon reconstruction in the CMS
detector can be found in Ref. [28].

Reconstructed photon candidates must pass additional identification criteria
to suppress misidentified jets and electrons, while maintaining high
efficiency. These criteria are based on observables sensitive to the
electromagnetic shower shape and the extra activity surrounding the shower.
The electromagnetic shower shape is measured using $\sigma_{\eta\eta}$, the
spatial second-order moment of the photon candidate in the $\eta$ direction
[28]. Isolation variables are based on the total transverse momentum of
particle candidates with coordinates $(\eta,\,\phi)$ reconstructed within a
cone of size $\DR=0.3$ around the photon candidate with coordinates
$(\eta_{\gamma},\,\phi_{\gamma})$, where
$\DR=\sqrt{\smash[b]{(\eta-\eta_{\gamma})^{2}+(\phi-\phi_{\gamma})^{2}}}$.
Separate isolation variables are defined for charged hadron and photon
candidates. Electrons are vetoed based on hits in the silicon pixel and strip
trackers with a further check to ensure photon candidates associated with
electron tracks are incompatible with those resulting from photon conversions.

Events are selected by a trigger that requires at least two reconstructed
photon candidates, each with transverse momentum $\pt>60\GeV$. For these
events, the ratio of the energy deposited in the HCAL behind each photon
candidate and the photon energy in the ECAL is required to be less than 0.15.
To avoid non-uniform efficiency near the trigger threshold, a more stringent
selection of photon $\pt>75\GeV$ is applied offline. Events are required to
have one photon in the EB with $\abs{\eta}<1.44$, and another in either the EB
or in an EE, where it must have $1.57<\abs{\eta}<2.5$. Events with both photon
candidates in the EEs are dominated by SM production and have negligible
sensitivity to the target beyond-SM signals, and thus are omitted from this
analysis. Two signal regions are considered: one with both photons in the EB,
denoted EBEB, and the other with one photon in the EB and the other in either
EE, denoted EBEE. The invariant mass of the photon pair must satisfy a minimum
requirement of $m_{\gamma\gamma}>230$ and 330in the EBEB and EBEE categories,
respectively. This threshold avoids sculpting of the distribution while
maintaining full efficiency in each region. In the search for nonresonant
signals, this requirement is increased to $m_{\gamma\gamma}>500\GeV$ in both
categories and photon pairs must additionally satisfy $\DR>0.45$, to be
consistent with the background calculation for SM diphoton production, as
described in Section 0.5.2.

The trigger and identification efficiencies are found to be compatible within
uncertainties (3%) between data and simulation and the overall efficiency is
about 90 (87)% for single photons in the barrel (endcaps). The selection
criteria as well as the level of agreement between data and simulation were
determined using simulated signal, background, and control data samples and
were fixed before inspecting the diphoton invariant mass distribution in the
search regions. The product of the event selection efficiency ($\varepsilon$)
and the detector acceptance ($A$) is shown in Fig. 1 for two spin hypotheses
in the narrowest resonance-width scenario considered in this analysis, as
discussed further in Section 0.4. (For the other two resonance-width
hypotheses considered, the acceptance values are very close to this one.)

Figure 1:  The product of the event selection efficiency ($\varepsilon$) and
the detector acceptance (A) is shown as a function of signal resonance mass
$m_{\mathrm{X}}$ for the $\Gamma_{\mathrm{X}}/m_{\mathrm{X}}=1.4\times
10^{-4}$ signal width hypothesis. The total (black), EBEB (red), and EBEE
(blue) curves are shown for the spin (J) hypotheses $\mathrm{J}=0$ (solid) and
$\mathrm{J}=2$ (dashed).

In order to obtain the optimal energy resolution, the ECAL signals are
calibrated and corrected for several detector effects. The variation of the
crystal transparency during data taking is monitored and corrected using a
dedicated monitoring system and the single-channel response is equalized using
collision events. The data used for this analysis were reconstructed with a
detector calibration optimized for the 2016 data taking conditions. The
energies of the photon candidates are first measured by the ECAL and are then
corrected for shower noncontainment effects using a multivariate regression
procedure. The corrections are tuned using a simulation of photon candidates
with energies spanning the entire range explored by this analysis.

Differences in the photon energy scale and resolution between data and
simulation are estimated using dielectron events. Energy scale and resolution
corrections are derived primarily from $\cPZ\to\Pep\Pem$ events, with the
electrons reconstructed as photons, using the procedure described in Ref.
[28]. The corrections are derived in eight categories defined in terms of the
variable (defined as the ratio of the energy deposited in the central
$3{\times}3$ crystal matrix and the full cluster energy) and the location of
the photon within the detector along the $\eta$ direction.

The size of the energy scale corrections derived from $\cPZ\to\Pep\Pem$ events
is of the order of 0.5%, while the additional Gaussian smearing needed to
match the energy resolution of simulated events with that in data varies
between 0.8 and 1.5% for photon candidates in the EB region and between 2 and
2.5% for photon candidates in the EE regions.

The diphoton mass resolution has contributions from the measurements of the
photon energies and from the resolution of the measurement between the two
photons. If the $z$ position of the vertex from which the photons originate is
known to within about 10, then the experimental angular resolution between the
photons makes a negligible contribution to the mass resolution. Correctly
associating the diphoton candidate with one of the vertices reconstructed from
the charged-particle tracks in the event satisfies the above requirements
since the positions of these vertices are measured with far greater precision.
The interaction vertex associated with the diphoton system is selected using
the algorithm described in Refs. [32, 33]. Because photons do not deposit
ionization energy in the tracker, the assignment of the diphoton candidate to
a vertex can only be done indirectly by exploiting the properties of each
reconstructed vertex. Three discriminating variables are calculated for each
reconstructed vertex: the $\pt^{2}$ sum of the charged-particle tracks
associated with the vertex, and two variables that quantify the vector and
scalar balance of between the diphoton system and the tracks associated with
the vertex. In addition, if either photon has an associated track that has
been identified as originating from a photon conversion to an electron-
positron pair, the conversion information is used. These variables provide the
inputs to a multivariate classifier based on a boosted decision tree used to
select the reconstructed vertex of the diphoton system. For signal events with
diphoton invariant masses above 500, the fraction of events in which the
interaction vertex is correctly assigned is approximately 90%.

##  0.4 Signal simulation

The ADD signal samples used in this analysis were produced at leading order
(LO) using the Monte Carlo (MC) event generator 2.1.1 [34] with the CT10 set
of parton distribution functions (PDFs) [35, 36]. These simulations include
the effect of interference between the ADD signal and the SM diphoton
processes, which can be large. To be able to set limits on possible deviations
from the SM, additional SM-only samples are generated identically, and the
difference between these and the ADD samples therefore encompasses the
combined effects of the ADD signal and the interference.

The implementation of the ADD model within is parametrized by the ultraviolet
string cutoff scale $M_{\mathrm{S}}$, which is related to the fundamental
Planck scale and the number of extra dimensions $n_{\mathrm{ED}}$. Since the
ADD model is an effective theory only valid below the cutoff scale, the
generated diphoton mass spectra are truncated at the chosen value of
$M_{\mathrm{S}}$. The amplitude for a process involving virtual graviton
exchange involves a sum over the KK tower of graviton mass states. This
process can be represented by a higher-dimensional operator with coefficients
suppressed by some mass scale [37], which can be parametrized by
$\eta_{\mathrm{G}}=\mathcal{F}/M_{\mathrm{S}}^{4}$, where $\mathcal{F}$ is a
dimensionless parameter for which several conventions exist in the literature.
We consider the conventions by Giudice, Rattazzi, and Wells (GRW) [38], by
Han, Lykken, and Zhang (HLZ) [39], and by Hewett [40], expressed as:

$\mathcal{F}=\begin{cases}1\quad\text{(GRW)},\\\
\log\left(\frac{M_{\mathrm{S}}^{2}}{\hat{s}}\right),\;\text{if}\;n_{\mathrm{ED}}=2\\\
\frac{2}{n_{\mathrm{ED}}-2},\;\text{if}\;n_{\mathrm{ED}}>2\\\
\pm\frac{2}{\pi}\quad\text{(Hewett)},\end{cases}\text{(HLZ)},$ (1)

where $\sqrt{\hat{s}}$ is the center-of-mass energy of the colliding partons.

Signal model assumptions from different conventions but with the same value of
$\eta_{\mathrm{G}}$ are equivalent, reducing the number of distinct scenarios
allowed by Eq. (1). All possible choices of model parameters can be made
equivalent to the signals produced using either the convention by GRW, HLZ
assuming $n_{\mathrm{ED}}=2$, or Hewett using $\mathcal{F}=-2/\pi$. Twelve
model points for each choice are generated in the range
$3<M_{\mathrm{S}}<11\TeV$. For each model point, the CMS detector response is
simulated using [41] and includes the effects of multiple proton-proton
collisions occurring within the same LHC bunch crossing, known as ‘pileup’.

No additional samples are needed to generate the clockwork signal; instead the
ADD signal samples are reinterpreted to produce the clockwork prediction. In
the clockwork model, the KK modes are all on shell, so there is no
interference effect, while the ADD prediction includes both a direct term and
an interference term. The GRW and negative Hewett models have opposite signs
for the interference term, so the direct term can be isolated by linearly
adding, with appropriate weights, the predictions assuming the GRW and
negative Hewett conventions. The direct term is then rescaled by Eq. (2),
provided by the authors of Ref. [14]:

$\theta(m_{\gamma\gamma}-k)\frac{30M_{\mathrm{S}}^{8}}{283\pi
M_{5}^{3}}\sqrt{1-\frac{k^{2}}{m_{\gamma\gamma}^{2}}}\frac{1}{m_{\gamma\gamma}^{5}}\Bigg{[}1+\frac{(5^{2})(7)(17)}{(283)(2^{8})}\Big{(}1-\frac{k}{m_{\gamma\gamma}}\Big{)}^{9}\sqrt{\frac{m_{\gamma\gamma}}{k}}\Bigg{]}^{-1}.$
(2)

Here, $M_{\mathrm{S}}$ is defined in the GRW convention, $M_{5}$ is the
fundamental scale of the gravitational interactions, and $k$ is the ‘clockwork
spring’, which, phenomenologically, controls the energy scale at which the KK
modes can be excited. To solve the hierarchy problem, $M_{5}$ should be close
to the electroweak scale. Demanding perturbativity of the theory imposes the
constraint $k<M_{5}$.

For resonant diphoton production, the signal distribution in
$m_{\gamma\gamma}$ is determined from the convolution of the intrinsic shape
of the resonance and the ECAL detector response. The intrinsic shapes of both
the spin-0 and spin-2 resonant signals were derived using the 8.2 [42] event
generator with the NNPDF2.3 [43] set of PDFs and the CUETP8M1 [44] underlying
event tune. The spin-0 signal corresponds to a heavy SM-like Higgs boson,
while the spin-2 signal corresponds to the RS graviton. Three signal width
hypotheses are considered: $\Gamma_{\mathrm{X}}/m_{\mathrm{X}}=1.4\times
10^{-4}$, $1.4\times 10^{-2}$, and $5.6\times 10^{-2}$, corresponding to a
width narrower than, comparable to, and wider than the detector resolution,
respectively. These three width hypotheses correspond, in the case of an RS
graviton, to $\tilde{k}=0.01$, 0.1, and 0.2, respectively. A set of signal
samples was simulated excluding the detector response, forming a fine grid of
mass points with 125spacing. These samples are used to measure the signal
kinematic acceptance and generator-level mass shape. The resulting shapes are
interpolated to intermediate mass points using a parametric description of the
distribution. The detector response was determined using signal samples
simulated with , and includes the effects of pileup. These samples were
generated assuming small intrinsic width, with additional Gaussian smearing,
determined using dielectron events, applied to correct the simulated
resolution to that of data. Nine equidistant mass hypotheses in the range
500–4500were employed. The signal mass resolution, quantified through the
ratio of the full width at half maximum (FWHM) of the distribution, divided by
2.35, to the peak position, is roughly 1 and 1.5% for the EBEB and EBEE
categories, respectively.

For the spin-0 and spin-2 assumptions, in order to determine the signal
normalization the final selection efficiency was combined with the kinematic
acceptance. The former is obtained from fully simulated samples and
interpolated using a quadratic function of the resonance mass; the latter is
obtained from the finely spaced grid of samples and parametrized as a
quadratic function of both the resonance mass and its width.

##  0.5 Background determination

The primary background to the signal comes from prompt SM diphoton production.
An additional and reducible source of background occurs when a fragmenting jet
mimics a genuine photon signature in the detector. Two different methods are
used to determine the SM background. As described in Section 0.5.1, the
resonant signal search uses a maximum likelihood fit to the diphoton invariant
mass spectrum, seeking a local excess in the data that could indicate the
presence of beyond-SM physics. The nonresonant signal search uses simulation
to model the SM diphoton component and a method based on control samples in
data to estimate the contribution from misidentified jets; this method is
described in Section 0.5.2.

###  0.5.1 Background for resonant diphoton search

In the resonant signal search, the background $m_{\gamma\gamma}$ spectrum is
described by a parametric function of $m_{\gamma\gamma}$:

$f(m_{\gamma\gamma})=m_{\gamma\gamma}^{a+b\,\log(m_{\gamma\gamma}/{\GeVns})},$
(3)

where the parameters $a$ and $b$ are obtained from a fit to the data and are
considered as unconstrained nuisance parameters in the hypothesis test.

The chosen parametric form is designed to be an approximation of the true but
unknown background shape. The degree of accuracy with which the model
describes the true shape is tested using a set of five different parametric
models, all of which can describe relatively well the observed
$m_{\gamma\gamma}$ spectrum. If the chosen model is flexible enough to
accommodate the shape of each of the alternative models, then we assume that
it would likely be able to describe a similar true background shape.

The accuracy of the background determination is assessed with data using the
following procedure: five different parametric background models are fit to
the data in order to build five different truth models, and the accuracy of
the chosen parametrization is quantified by studying the difference between
the true and predicted number of background events in several
$m_{\gamma\gamma}$ intervals in the search region. The width of these
intervals ranges between 10 and 500, in order to keep an equal amount of data
in each of the mass ranges. The five functions are chosen from five different
families of functions. For each family, the function that requires the minimum
number of parameters to fit the data with a $\chi^{2}$ probability greater
then 5% is chosen. Pseudo-experiments are drawn from the mass spectrum
predicted by the different background models. The total number of events in
each pseudo-experiment is taken from a Poisson distribution where the mean is
determined by the observation in data. For each interval, the distribution of
the pull variable, defined as the difference between the true and predicted
number of events divided by the estimated statistical uncertainty, is
constructed. If the absolute value of the median of this distribution is found
to be above 0.5 in a window, an additional uncertainty is assigned to the
background parametrization. A modified pull distribution is then constructed
increasing the statistical uncertainty on the fit by an extra term, denoted
“bias term”, which is parametrized as a smooth function of $m_{\gamma\gamma}$,
tuned so that the absolute value of the median of the modified pull
distribution is below 0.5 for all regions. The additional uncertainty is then
included in the likelihood function by adding to the background model a
component having the same shape as the signal, with a normalization
coefficient distributed as a Gaussian function of mean zero and width equal to
the integral of the bias term over the FWHM of the tested signal shape. The
inclusion of the additional component has the effect of avoiding falsely
positive or negative tests that could be induced by a mismodeling of the
background shape, and it degrades the analysis sensitivity by 0.1 to 10%
depending on the mass and width of the signal hypothesis.

###  0.5.2 Background for nonresonant diphoton search

In the search for nonresonant deviations from the SM diphoton spectrum, we
make a prediction of the invariant mass distribution expected from SM diphoton
events, as well as of contributions from photon+jet or dijet events where one
or two jets fragment in such a way as to resemble a photon signature in the
CMS detector. Prompt SM diphoton production can occur via quark annihilation
or gluon fusion processes. This irreducible background is modeled using the MC
event generator 2.1.1 [34, 45]. Up to three additional jets are added to the
diphoton final state, to better simulate phase space regions with small-to-
medium angular separation between the two photons. The CT10 set of PDFs is
used for generation, and the generated events are subject to a simulation of
the CMS detector response based on the package [41]. While the inclusion of
explicit final-state jets in the sample incorporates the real radiation
component of higher-order corrections to the basic diphoton process, virtual
corrections are not included in these simulated events. This is remedied by
performing a full NNLO calculation of SM diphoton production using 8.0 [46]. A
$K$ factor, defined as the ratio of the NNLO prediction to the prediction, is
calculated as a function of the diphoton invariant mass. This $K$ factor is
then used to reweight and correct the events (after detector simulation) to
obtain the prediction for the SM diphoton invariant mass spectrum from two
real photons. The $K$ factor is calculated separately for the EBEB and EBEE
acceptance categories, with the renormalization, factorization, and
fragmentation scales for the calculation set to be $m_{\gamma\gamma}$. Events
with very small $\DR_{\gamma\gamma}$ ($<$0.45) are rejected to avoid an
infrared divergence. The $K$ factor for the EBEB (EBEE) event category varies
from 1.4–1.8 (1.5–2.0) over the range 0.5–2.0. Next-to-leading-order (NLO) $K$
factors are also computed in a similar way with both and diphox [47], and are
used to extract systematic uncertainties in the shape of the central, NNLO
calculation.

An additional background occurs from SM photon+jet or dijet events when one or
two jets fragment in such a way as to resemble a photon signature in the
detector. Application of shower shape and isolation criteria to the
identification of photon candidates as described in Section 0.3 aims to
minimize this reducible background, and we use a data-driven method to
estimate the remaining contribution. The method assumes that events where a
jet has fragmented to produce a fake photon signature in the detector can be
modeled by other events where the jet fragmented differently. We define two
distinct categories of jet fragmentation objects, and measure the ratio of the
yields of objects in these two fragmentation categories, in a jet-triggered
reference data sample.

In the first category, whose objects are counted for the numerator of the
ratio, are those misidentified jets that pass the photon identification
requirements; these are the ones whose contribution to the background we wish
to determine. When measured in a reference data sample, however, genuine
photons passing the same ID requirements contribute also to this category.
This contribution is subtracted out statistically, in the following way. The
shower shape variable $\sigma_{\eta\eta}$ is used as a discriminant between
genuine photons and jets misidentified as photons. A template is constructed
for the $\sigma_{\eta\eta}$ distribution of real photons using simulated
events, and a $\sigma_{\eta\eta}$ template for jets misidentified as photons
is obtained from a control sample in data enriched in such jets, by inverting
the identification requirement for charged hadron isolation. These templates
are then fit to the observed $\sigma_{\eta\eta}$ distribution of the numerator
objects, to determine the relative contribution of genuine photons, which is
then subtracted. This template-fitting and subtraction procedure is performed
in bins of photon since the $\sigma_{\eta\eta}$ templates are found to be
dependent. After this procedure, what remains is the contribution to the
numerator object category only from jets that have been misidentified as
photons.

The denominator category consists of ‘photon-like’ jets that pass a less
strict version of the photon ID, but still have a high electromagnetic energy
component. They are additionally required to fail at least one of the
isolation or shower shape requirements for photon candidate identification,
ensuring that the two fragmentation categories are mutually exclusive and that
there is negligible contamination from real photons in the denominator
category.

The ratio of the numbers of objects in the two jet fragmentation categories is
measured as a function of the photon in an independent jet-triggered data
sample. The background prediction for jets that are misidentified as photons
is then obtained by considering events containing objects that pass the looser
‘photon-like’ jet definition, and reweighting those events by the relative
fragmentation ratio. This contribution from misidentified jets to the diphoton
spectrum is found to decrease within the mass range
$0.5<m_{\gamma\gamma}<1\TeV$ from 9 to 4% of the total background in the EBEB
category and from 28 to 17% in the EBEE. For $m_{\gamma\gamma}>1\TeV$, this
integrated contribution from jets misidentified as photons is predicted to be
less than 4 (14)% in the EBEB (EBEE).

##  0.6 Systematic uncertainties

###  0.6.1 Systematic uncertainties for the resonant search

The systematic uncertainties on the search for resonant diphoton signals are
smaller than the associated statistical uncertainties. The parametric
background model has no associated systematic uncertainties, except for the
bias term uncertainty described previously. The shape coefficients are treated
as unconstrained nuisance parameters, and thus the associated uncertainties
contribute to the statistical uncertainty.

Uncertainties associated with the signal modeling are:

  * •

a 2.5% uncertainty in the signal normalization assigned to reflect the
uncertainty in the total integrated luminosity [48];

  * •

a 6% uncertainty in the signal normalization to reflect uncertainty in the
selection efficiency;

  * •

a 6% uncertainty in the signal normalization in order to account for the
variation in the kinematic acceptance estimated by comparing the use of the
alternative PDF sets CT10 [35, 36], NNPDF2.3 [43], and MSTW08 [49] on the
signal hypothesis and taking the largest deviation, following the PDF4LHC
recommendations [50, 51];

  * •

a 1% uncertainty in the photon energy scale is included in the fit to take
into account the uncertainty associated with the photon energy scale at the
boson mass and its extrapolation to higher masses; and

  * •

the uncertainty in the photon energy resolution correction factor evaluated by
summing and subtracting 0.5% in quadrature from the estimated additional
Gaussian smearing measured at the boson peak.

###  0.6.2 Systematic uncertainties for the nonresonant search

Although the SM diphoton background prediction is at NNLO accuracy, there is
still the possibility of contribution from unaccounted-for higher-order terms.
Therefore, we allow the normalization of the predicted diphoton background to
float freely, constrained only by the data (predominantly at low
$m_{\gamma\gamma}$ where the statistical uncertainty is smallest). Floating
the normalization also absorbs sources of uncertainty associated with the
integrated luminosity measurement, trigger, and photon selection efficiency.
Provided the shape of the signal differs significantly from the background,
the analysis will still discriminate between the two. Scale uncertainties in
the $K$ factor calculation are estimated by simultaneously varying the
renormalization, factorization, and fragmentation scales between
$m_{\gamma\gamma}/2$ and $2m_{\gamma\gamma}$. The difference between the shape
of the NNLO $m_{\gamma\gamma}$ spectra and the shape predicted at NLO by and
diphox is also taken as an uncertainty and as a conservative bound on the
effects of the absent higher-order terms.

Systematic uncertainties associated with the PDFs are calculated using diphox
at NLO with a consistent set of NLO CT10 PDFs. The 26 eigenvectors of this PDF
set are varied individually by $\pm 1$ standard deviation (rather than taking
an envelope), which allows us to treat consistently the correlations of the
uncertainties as a function of $m_{\gamma\gamma}$ and between the EBEB and
EBEE categories. Uncertainties due to the photon energy scale and resolution
have a negligible impact on the nonresonant search. The uncertainty in the
misidentification rate for both the barrel and endcap is approximately 30%, as
estimated from the variation of the fake rate as a function of pileup and
photon $\eta$, and from the degree of variation observed in a test of the
method using MC simulation. A separate shape uncertainty due to differences in
the samples from which the fake rate was constructed (using a multijet- or
dimuon-triggered data set) makes a subdominant contribution.

Uncertainties in the normalization of the extra dimensional signal from the
measured integrated luminosity and photon selection efficiency are 2.5 and 6%,
respectively, in agreement with the resonance search. Systematic uncertainties
in the signal shape from PDFs are treated in the same manner as the background
by separately varying the 26 eigenvectors. These uncertainties are assumed to
be 100% correlated between signal and background. The effect of the PDF
uncertainty on the signal cross section is treated as a theoretical
uncertainty and is not propagated in the upper limits.

##  0.7 Results

###  0.7.1 Results of the search for resonant excesses

The $m_{\gamma\gamma}$ distribution of the selected diphoton events and the
background parametrization obtained through an unbinned maximum likelihood fit
to these events are shown in Fig. 2. This parametric form corresponds to the
one chosen to model the background given by Eq. (3), as detailed in Section
0.5.

Figure 2:  Observed diphoton invariant mass spectra for the EBEB (left) and
EBEE (right) categories. Also shown are the results of a likelihood fit to the
background-only hypothesis. The shaded region shows the one standard deviation
uncertainty band associated with the fit, reflecting the statistical
uncertainty of the data. The lower panels show the difference between the data
and fit, divided by the statistical uncertainty in the data points.

The results of the search are interpreted in the framework of a composite
statistical hypothesis test. A simultaneous fit to the invariant mass spectra
of the EBEB and EBEE event categories is used to study the compatibility of
the data with the background-only and the signal+background hypotheses.

The test statistic used in the hypothesis tests are based on the profile
likelihood ratio:

$q(\mu)=-2\log\frac{L(\mu
S+B|\hat{\theta}_{\mu})}{L(\hat{\mu}S+B|\hat{\theta})},$ (4)

where $S$ and $B$ are the probability density functions for the resonant
diphoton signal production process and the SM background, respectively; $\mu$
is the signal strength parameter, defined as the ratio between the measured
and expected signal cross sections; and $\theta$ are the nuisance parameters
of the model used to account for the associated systematic uncertainties. The
notation $\hat{x}$ indicates the best fit value of the parameter $x$, while
$\hat{x}_{y}$ denotes the best fit value of $x$, conditionally on $y$.

The data are in agreement with the absence of any significant resonant excess
of events. The largest deviation observed is an approximately 2 standard
deviation local excess at 1.2for the wide-width hypothesis, and is similar for
both the spin-0 and spin-2 signals.

To set upper limits on the resonant diphoton production rate, the modified
frequentist method, commonly known as [52, 53], is used following the
prescription described in Ref. [54]. Asymptotic formulas [55] are used in the
calculations of limits.

Expected and observed upper limits at 95% confidence level (CL) on the
production of scalar and RS graviton resonances are shown in Fig. 3. Using
leading order cross sections from , RS gravitons with masses $m_{\mathrm{X}}$
below 2.3, 4.1, and 4.6can be excluded for $\tilde{k}=0.01$, 0.1, and 0.2,
respectively, corresponding to $\Gamma_{\mathrm{X}}/m_{\mathrm{X}}=1.4\times
10^{-4}$, $1.4\times 10^{-2}$, and $5.6\times 10^{-2}$, respectively.

Figure 3:  Expected and observed 95% CL upper limits on the production cross
section for RS gravitons of mass $m_{\mathrm{\PXXG}}$ and three values of
$\tilde{k}$ (left) and for spin-0 resonances of mass $m_{\mathrm{S}}$ produced
via gluon fusion for the three width hypotheses (right). The shaded bands
represent the 1 and 2 standard deviation uncertainty in the expected limit.

Limits can also be set, in a model independent fashion, on the cross sections
for events in the fiducial volume for the resonant $\Pp\Pp\to\gamma\gamma$
process. The signal shape is modeled in the same way as for the benchmark
models, while the signal normalization accounts only for the detector
efficiency and not for any particular signal acceptance. The fiducial volume
is defined by selecting events in which both photons have generator-level
$\pt>75\GeV$, to match the selection applied in the event reconstruction and
selection. Generator-level photons are also required to have an isolation
energy of less than 10in a cone of radius 0.4 around the photon direction. The
isolation energy is defined as the sum of all final state particles except
neutrinos and the signal photon itself.

The fit is performed independently in the EBEB and EBEE categories for each of
the following width hypotheses: $\Gamma_{\mathrm{X}}/m_{\mathrm{X}}=1.4\times
10^{-4}$, $1.4\times 10^{-2}$, and $5.6\times 10^{-2}$. The results for the
median expected exclusion limits on the fiducial cross sections are presented
in Fig. 4 for each width hypothesis.

Figure 4:  Expected and observed 95% CL upper limits on the fiducial cross
section for the resonant $\Pp\Pp\to\gamma\gamma$ process. Shown are the
results in the EBEB (left) and EBEE (right) categories for the three width
hypotheses. The shaded bands represent the 1 and 2 standard deviation
uncertainty in the expected limit.

###  0.7.2 Results of the search for nonresonant excesses

In the nonresonant search, constraints on the signals are determined by
adopting a Bayesian statistical approach. A binned likelihood is constructed
from the data, with the binning in 100steps beginning at 500. The signal
strengths for each model are assumed to have a flat prior (bounded below by
zero). Nuisance parameters are assigned to each of the systematic
uncertainties described in Section 0.6.2. Except for the diphoton background
normalization nuisance parameter, which has a flat prior, the prior shapes are
either lognormal or Gaussian, depending on whether or not the uncertainty is
bounded below by zero. Nuisance parameters are marginalized using a Markov
chain MC method [56].

Figure 5 (upper) presents the data and background prediction “pre-fit,” ,
before the marginalization of the nuisance parameters. The shaded bands show
the systematic uncertainties, neglecting the (unbounded) normalization of the
diphoton prediction and the NLO shapes. Figure 5 (lower) presents the data and
background prediction “post-fit,” , after the marginalization of the nuisance
parameters. Good agreement is found within the uncertainties for both the pre-
and post-fit spectra, although the uncertainties are smaller, as expected, in
the latter case.

Figure 5:  The diphoton invariant mass distributions in the EBEB (left) and
EBEE (right) categories for the SM diphoton background prediction and the fake
background measurement compared to the data. The last bin includes the
overflow. The error bars on the points indicate the statistical uncertainty.
The upper (lower) plots show the pre-fit (post-fit) background estimates. The
hatched bands indicate the total pre- or post-fit systematic uncertainties.
Invariant mass distributions from two signal scenarios are superimposed on the
lower plots. The bottom panels show the pull distributions, indicating the
difference between the data and background prediction, divided by the
uncertainty in the background, with error bars representing the statistical
uncertainty and shaded bands showing the one standard deviation systematic
uncertainty, normalized by the statistical uncertainty.

For the ADD model, upper limits are set at 95% CL on the signal strength,
which are translated into lower limits on the mass scale $M_{\mathrm{S}}$ by
interpolating the value of $M_{\mathrm{S}}$ that has a signal strength of 1.0
excluded. Table 0.7.2 summarizes the results for all ADD model conventions
probed. The excluded values of $M_{\mathrm{S}}$ range from 5.6 to 9.7,
depending on the convention.

Exclusion lower limits obtained on the mass scale $M_{\mathrm{S}}$ (in units
of ) for various conventions used in the calculation of the ADD large extra
dimensional scenario, as described in Section 0.4. The total asymmetric
uncertainties are shown on the expected limits.  cccccccccc &
Signal GRW Hewett HLZ
negative positive $n_{\mathrm{ED}}=2$ $n_{\mathrm{ED}}=3$ $n_{\mathrm{ED}}=4$
$n_{\mathrm{ED}}=5$ $n_{\mathrm{ED}}=6$ $n_{\mathrm{ED}}=7$

Expected $7.1^{+0.7}_{-0.5}$ $5.5^{+0.1}_{-0.3}$ $6.3^{+0.6}_{-0.4}$
$8.4^{+1.3}_{-1.1}$ $8.4^{+0.8}_{-0.6}$ $7.1^{+0.7}_{-0.5}$
$6.4^{+0.6}_{-0.5}$ $6.0^{+0.6}_{-0.4}$ $5.6^{+0.6}_{-0.4}$
Observed 7.8 5.6 7.0 9.7 9.3 7.8 7.0 6.6 6.2

The limit-setting strategy for the clockwork model is similar to that for the
ADD model. Only the portion of the diphoton invariant mass spectrum with
$m_{\gamma\gamma}>900\GeV$ can be used for limit setting on the clockwork
model. This constraint is imposed to maintain a statistically precise
prediction after the translation of the ADD to clockwork signal. The ADD
signal is only simulated for $m_{\gamma\gamma}>500\GeV$ and the constructed
clockwork signal acquires sufficient statistics only above 900. A simplifying
effect is that the signal strength normalization scales as $M_{5}^{-3}$, so a
direct translation between an upper limit on the signal strength and a lower
limit on $M_{5}$ can be made (for a fixed value of $k$). Figure 6 shows the
95% CL exclusion limits in the $k$–$M_{5}$ plane. We are able to exclude
values of $M_{5}$ lower than 5for $k$ values in the range of 0.2to 2.0. The
parameter space with $k>M_{5}$ is excluded by a perturbativity requirement,
and this region is denoted ‘nonperturbative’ in the exclusion plot.

Figure 6:  The 95% CL exclusion limits for the continuous graviton model in
the clockwork framework over the $k$–$M_{5}$ parameter space. The shaded bands
represent the 1 and 2 standard deviation uncertainty in the expected limit.
The shaded region with $k>M_{5}$ denotes the area where the theory becomes
nonperturbative.

##  0.8 Summary

A search has been performed for physics beyond the standard model in high-mass
diphoton events from proton-proton collisions at a center-of-mass energy of
13. The data used correspond to an integrated luminosity of 35.9collected by
the CMS detector in 2016. A resonant peak in the diphoton invariant mass
spectrum could indicate the existence of a new scalar particle, such as a
heavy Higgs boson, or of a Kaluza–Klein excitation of the graviton in the
Randall–Sundrum model of warped extra dimensions. A nonresonant excess could
be a signature of large extra dimensions, in the scenario by Arkani-Hamed,
Dimopoulos, and Dvali, or a continuum clockwork model.

The data are found to be in agreement with the predicted background from
standard model sources, and no evidence for new physics is seen. Masses below
2.3–4.6are excluded at 95% confidence level for the excited state of the
Randall–Sundrum graviton, for a coupling parameter in the range
$0.01<\tilde{k}<0.2$. Limits are also set on the production of scalar
resonances, and model-independent cross section limits have been extracted as
a function of diphoton invariant mass for any resonant $\gamma\gamma$
production process. These results extend the sensitivity of the previous
search performed by the CMS experiment [19] and are compatible with those
reported by the ATLAS Collaboration in Ref. [18]. In the large extra-
dimensional model of Arkani-Hamed, Dimopoulos, and Dvali, exclusion limits on
the string mass scale are set in the range $5.6<M_{\mathrm{S}}<9.7\TeV$,
depending on the specific model convention. These results extend the current
best lower limits on $M_{\mathrm{S}}$ from the diphoton channel as presented
in Ref. [18]. Additionally, the first exclusion limits are set in the two-
dimensional parameter space of a continuum clockwork model.

###### Acknowledgements.

We congratulate our colleagues in the CERN accelerator departments for the
excellent performance of the LHC and thank the technical and administrative
staffs at CERN and at other CMS institutes for their contributions to the
success of the CMS effort. In addition, we gratefully acknowledge the
computing centers and personnel of the Worldwide LHC Computing Grid for
delivering so effectively the computing infrastructure essential to our
analyses. Finally, we acknowledge the enduring support for the construction
and operation of the LHC and the CMS detector provided by the following
funding agencies: BMBWF 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); MES
(Latvia); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT,
LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); 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); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST
(Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK
(Turkey); NASU and SFFR (Ukraine); STFC (United Kingdom); DOE and NSF (USA).
Individuals have received support from the Marie-Curie program and the
European Research Council and Horizon 2020 Grant, contract No. 675440
(European Union); the Leventis Foundation; the A. P. Sloan Foundation; the
Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office;
the Fonds pour la Formation à la Recherche dans l’Industrie et dans
l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en
Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the
“Excellence of Science - EOS” - be.h project n. 30820817; the Ministry of
Education, Youth and Sports (MEYS) of the Czech Republic; the Lendület
(“Momentum”) Program and the János Bolyai Research Scholarship of the
Hungarian Academy of Sciences, the New National Excellence Program ÚNKP, the
NKFIA research grants 123842, 123959, 124845, 124850 and 125105 (Hungary); the
Council of Science and Industrial Research, India; the HOMING PLUS program of
the Foundation for Polish Science, cofinanced from European Union, Regional
Development Fund, the Mobility Plus program of the Ministry of Science and
Higher Education, the National Science Center (Poland), contracts Harmonia
2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and
2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities
Research Program by Qatar National Research Fund; the Programa Estatal de
Fomento de la Investigación Científica y Técnica de Excelencia María de
Maeztu, grant MDM-2015-0509 and the Programa Severo Ochoa del Principado de
Asturias; the Thalis and Aristeia programs cofinanced by EU-ESF and the Greek
NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn
University and the Chulalongkorn Academic into Its 2nd Century Project
Advancement Project (Thailand); the Welch Foundation, contract C-1845; and the
Weston Havens Foundation (USA).

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##  .9 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, 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, 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, M. Correa Martins Junior, 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 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. Shaheen6, A. Spiezia, J. Tao, C. Wang,
Z. Wang, E. Yazgan, H. Zhang, S. Zhang6, 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. Starodumov7, 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. Finger8, M. Finger Jr.8 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
Y. Assran9,10, S. Elgammal10, S. Khalil11 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. Abdulsalam12, C. Amendola, I. Antropov, F. Beaudette, P. Busson, C.
Charlot, R. Granier de Cassagnac, I. Kucher, A. Lobanov, J. Martin Blanco, M.
Nguyen, C. Ochando, G. Ortona, P. Paganini, P. Pigard, J. Rembser, 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. Agram13, J. Andrea, D. Bloch, J.-M. Brom, E.C. Chabert, V. Cherepanov,
C. Collard, E. Conte13, J.-C. Fontaine13, 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. Popov14, V. Sordini, G. Touquet, M.
Vander Donckt, S. Viret Georgian Technical University, Tbilisi, Georgia
A. Khvedelidze8 Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze8 RWTH Aachen University, I. Physikalisches Institut, Aachen,
Germany
C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, M.P.
Rauch, C. Schomakers, J. Schulz, M. Teroerde, B. Wittmer, V. Zhukov14 RWTH
Aachen University, III. Physikalisches Institut A, Aachen, Germany
A. Albert, D. Duchardt, M. Endres, M. Erdmann, S. Ghosh, A. Güth, T. Hebbeker,
C. Heidemann, K. Hoepfner, H. Keller, L. Mastrolorenzo, M. Merschmeyer, A.
Meyer, P. Millet, S. Mukherjee, T. Pook, M. Radziej, H. Reithler, M. Rieger,
A. Schmidt, D. Teyssier RWTH Aachen University, III. Physikalisches Institut
B, Aachen, Germany
G. Flügge, O. Hlushchenko, T. Kress, A. Künsken, T. Müller, A. Nehrkorn, A.
Nowack, C. Pistone, O. Pooth, D. Roy, H. Sert, A. Stahl15 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. Borras16, 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. Gallo17, 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. Lohmann18, 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, H. Tholen, O. Turkot, 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, C.E.N. Niemeyer, 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, A.
Vanhoefer, B. Vormwald, I. Zoi Karlsruher Institut fuer Technologie,
Karlsruhe, Germany
M. Akbiyik, C. Barth, M. Baselga, S. Baur, E. Butz, R. Caspart, T. Chwalek, F.
Colombo, W. De Boer, A. Dierlamm, K. El Morabit, N. Faltermann, B. Freund, M.
Giffels, M.A. Harrendorf, F. Hartmann15, S.M. Heindl, U. Husemann, F.
Kassel15, I. Katkov14, 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, I. Papavergou,
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. Bartók19, 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. Horvath20, 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. Karancsi21, 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. Bahinipati22, C. Kar, P. Mal, K. Mandal, A. Nayak23, D.K. Sahoo22, S.K.
Swain Panjab University, Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, S. Chauhan, R. Chawla, N. Dhingra, R.
Gupta, A. Kaur, M. Kaur, S. Kaur, R. Kumar, P. Kumari, M. Lohan, A. Mehta, K.
Sandeep, S. Sharma, J.B. Singh, A.K. Virdi, 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. Bhardwaj24, M. Bharti, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep24,
D. Bhowmik, S. Dey, S. Dutt24, S. Dutta, S. Ghosh, K. Mondal, S. Nandan, A.
Purohit, P.K. Rout, A. Roy, S. Roy Chowdhury, G. Saha, S. Sarkar, M. Sharan,
B. Singh, S. Thakur24 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. Maity25, G. Majumder, K. Mazumdar, N. Sahoo, T.
Sarkar25 Indian Institute of Science Education and Research (IISER), Pune,
India
S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, S.
Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
S. Chenarani26, E. Eskandari Tadavani, S.M. Etesami26, M. Khakzad, M.
Mohammadi Najafabadi, M. Naseri, F. Rezaei Hosseinabadi, B. Safarzadeh27, M.
Zeinali University College Dublin, Dublin, Ireland
M. Felcini, M. Grunewald INFN Sezione di Bari a, Università di Bari b,
Politecnico di Bari c, Bari, Italy
M. Abbresciaa,b, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L. Cristellaa,b,
N. De Filippisa,c, M. De Palmaa,b, A. Di Florioa,b, F. Erricoa,b, L. Fiorea,
A. Gelmia,b, G. Iasellia,c, M. Incea,b, 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, 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,15, 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,28, 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,15, S. Di
Guidaa,d,15, 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,
D. Zuolo 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,15, P.
Paoluccia,15, 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, A. Bolettia,b, A. Bragagnolo, R. Carlina,b, P.
Checchiaa, M. Dall’Ossoa,b, P. De Castro Manzanoa, T. Dorigoa, U. Dossellia,
F. Gasparinia,b, U. Gasparinia,b, A. Gozzelinoa, S.Y. Hoh, S. Lacapraraa, P.
Lujan, M. Margonia,b, A.T. Meneguzzoa,b, J. Pazzinia,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 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
M. Biasinia,b, G.M. Bileia, C. Cecchia,b, D. Ciangottinia,b, L. Fanòa,b, P.
Laricciaa,b, R. Leonardia,b, E. Manonia, G. Mantovania,b, V. Mariania,b, M.
Menichellia, A. Rossia,b, A. Santocchiaa,b, D. Spigaa INFN Sezione di Pisa a,
Università di Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy
K. Androsova, P. Azzurria, 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, 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. Comettia, 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.
Soldia,b, A. Staianoa INFN Sezione di Trieste a, Università di Trieste b,
Trieste, Italy
S. Belfortea, V. Candelisea,b, M. Casarsaa, F. Cossuttia, A. Da Rolda,b, G.
Della Riccaa,b, F. Vazzolera,b, A. Zanettia Kyungpook National University,
Daegu, Korea
D.H. Kim, G.N. Kim, M.S. Kim, J. Lee, S. Lee, S.W. Lee, C.S. Moon, Y.D. Oh, S.
Sekmen, D.C. Son, Y.C. Yang Chonnam National University, Institute for
Universe and Elementary Particles, Kwangju, Korea
H. Kim, D.H. Moon, G. Oh Hanyang University, Seoul, Korea
J. Goh29, 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 Ali30, F. Mohamad Idris31, W.A.T. Wan
Abdullah, M.N. Yusli, Z. Zolkapli Universidad de Sonora (UNISON), Hermosillo,
Mexico
J.F. Benitez, A. Castaneda Hernandez, J.A. Murillo Quijada 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
Cruz32, R. Lopez-Fernandez, J. Mejia Guisao, R.I. Rabadan-Trejo, M. Ramirez-
Garcia, 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. Byszuk33, 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
M. Araujo, P. Bargassa, C. Beirão Da Cruz E Silva, A. Di Francesco, P.
Faccioli, B. Galinhas, M. Gallinaro, J. Hollar, N. Leonardo, M.V. Nemallapudi,
J. Seixas, G. Strong, O. Toldaiev, D. Vadruccio, J. Varela Joint Institute for
Nuclear Research, Dubna, Russia
S. Afanasiev, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev,
V. Karjavine, A. Lanev, A. Malakhov, V. Matveev34,35, P. Moisenz, V. Palichik,
V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin,
A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg),
Russia
V. Golovtsov, Y. Ivanov, V. Kim36, E. Kuznetsova37, 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
R. Chistov38, M. Danilov38, P. Parygin, D. Philippov, S. Polikarpov38, E.
Tarkovskii P.N. Lebedev Physical Institute, Moscow, Russia
V. Andreev, M. Azarkin35, I. Dremin35, M. Kirakosyan35, S.V. Rusakov, A.
Terkulov Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State
University, Moscow, Russia
A. Baskakov, A. Belyaev, E. Boos, M. Dubinin39, L. Dudko, A. Ershov, A.
Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, S.
Petrushanko, V. Savrin, A. Snigirev Novosibirsk State University (NSU),
Novosibirsk, Russia
A. Barnyakov40, V. Blinov40, T. Dimova40, L. Kardapoltsev40, Y. Skovpen40
Institute for High Energy Physics of National Research Centre ’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, V. Okhotnikov University of Belgrade, Faculty of
Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia
P. Adzic41, 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 University of
Ruhuna, Department of Physics, Matara, Sri Lanka
N. Wickramage CERN, European Organization for Nuclear Research, Geneva,
Switzerland
D. Abbaneo, B. Akgun, E. Auffray, G. Auzinger, P. Baillon, A.H. Ball, D.
Barney, J. Bendavid, M. Bianco, A. Bocci, C. Botta, E. Brondolin, T.
Camporesi, M. Cepeda, G. Cerminara, E. Chapon, Y. Chen, G. Cucciati, D.
d’Enterria, A. Dabrowski, N. Daci, V. Daponte, A. David, A. De Roeck, N.
Deelen, M. Dobson, M. Dünser, N. Dupont, A. Elliott-Peisert, P. Everaerts, F.
Fallavollita42, D. Fasanella, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, A.
Gilbert, K. Gill, F. Glege, M. Guilbaud, D. Gulhan, J. Hegeman, C. Heidegger,
V. Innocente, A. Jafari, P. Janot, O. Karacheban18, 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. Milenovic43, F. Moortgat, M.
Mulders, J. Ngadiuba, S. Nourbakhsh, S. Orfanelli, L. Orsini, F. Pantaleo15,
L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G. Petrucciani, A. Pfeiffer, M.
Pierini, F.M. Pitters, D. Rabady, A. Racz, T. Reis, G. Rolandi44, M. Rovere,
H. Sakulin, C. Schäfer, C. Schwick, M. Seidel, M. Selvaggi, A. Sharma, P.
Silva, P. Sphicas45, A. Stakia, J. Steggemann, M. Tosi, D. Treille, A. Tsirou,
V. Veckalns46, M. Verzetti, W.D. Zeuner Paul Scherrer Institut, Villigen,
Switzerland
L. Caminada47, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C.
Kaestli, D. Kotlinski, U. Langenegger, T. Rohe, S.A. Wiederkehr ETH Zurich -
Institute for Particle Physics and Astrophysics (IPA), Zurich, Switzerland
M. Backhaus, L. Bäni, P. Berger, N. Chernyavskaya, G. Dissertori, M. Dittmar,
M. Donegà, C. Dorfer, C. Grab, 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. Amsler48, D. Brzhechko, M.F. Canelli, A. De Cosa, R. Del
Burgo, S. Donato, C. Galloni, T. Hreus, B. Kilminster, S. Leontsinis, 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, R. Khurana, C.M. Kuo, W. Lin, A.
Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan
P. Chang, Y. Chao, K.F. Chen, P.H. Chen, W.-S. Hou, Arun Kumar, Y.F. Liu,
R.-S. Lu, E. Paganis, A. Psallidas, A. Steen 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. Cerci49, S. Damarseckin, Z.S. Demiroglu, F. Dolek, C.
Dozen, I. Dumanoglu, S. Girgis, G. Gokbulut, Y. Guler, E. Gurpinar, I. Hos50,
C. Isik, E.E. Kangal51, O. Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G.
Onengut, K. Ozdemir52, A. Polatoz, D. Sunar Cerci49, B. Tali49, U.G. Tok, S.
Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University,
Physics Department, Ankara, Turkey
B. Isildak53, G. Karapinar54, M. Yalvac, M. Zeyrek Bogazici University,
Istanbul, Turkey
I.O. Atakisi, E. Gülmez, M. Kaya55, O. Kaya56, S. Ozkorucuklu57, S. Tekten,
E.A. Yetkin58 Istanbul Technical University, Istanbul, Turkey
M.N. Agaras, S. Atay, A. Cakir, K. Cankocak, Y. Komurcu, S. Sen59 Institute
for Scintillation Materials of National Academy of Science of Ukraine,
Kharkov, Ukraine
B. Grynyov National Scientific Center, Kharkov Institute of Physics and
Technology, Kharkov, Ukraine
L. Levchuk University of Bristol, Bristol, United Kingdom
F. Ball, L. Beck, J.J. Brooke, D. Burns, E. Clement, D. Cussans, O. Davignon,
H. Flacher, J. Goldstein, G.P. Heath, H.F. Heath, L. Kreczko, D.M. Newbold60,
S. Paramesvaran, B. Penning, T. Sakuma, D. Smith, V.J. Smith, J. Taylor, A.
Titterton Rutherford Appleton Laboratory, Didcot, United Kingdom
K.W. Bell, A. Belyaev61, 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
R. Bainbridge, P. Bloch, J. Borg, S. Breeze, O. Buchmuller, A. Bundock, S.
Casasso, D. Colling, 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. Nash62, A. Nikitenko7, 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. Virdee15, N. Wardle, D.
Winterbottom, J. Wright, S.C. Zenz Brunel University, Uxbridge, United Kingdom
J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, 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.
Hogan63, K.H.M. Kwok, E. Laird, G. Landsberg, J. Lee, Z. Mao, M. Narain, S.
Sagir64, 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, 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. Wasserbaech65, J. Wood, F. Würthwein, A. Yagil, G. Zevi Della Porta
University of California, Santa Barbara - Department of Physics, Santa
Barbara, USA
N. Amin, R. Bhandari, J. Bradmiller-Feld, C. Campagnari, 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, E. MacDonald, T.
Mulholland, R. Patel, 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-Navarro66, 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, K.H. Lo, 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, C. Schiber, 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. Bilki67, W. Clarida, K. Dilsiz68, S. Durgut, R.P.
Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, A. Mestvirishvili, A.
Moeller, J. Nachtman, H. Ogul69, Y. Onel, F. Ozok70, 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
S. Duric, 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, 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, C. Mclean, 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.
Musienko34, 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, 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, S. Piperov, 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.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, P. Tan, R. Taus 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, S. Spanier Texas A&M University, College
Station, USA
O. Bouhali71, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R.
Eusebi, J. Gilmore, T. Huang, T. Kamon72, S. Luo, R. Mueller, A. Perloff, L.
Perniè, D. Rathjens, A. Safonov 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, B.
Gomber, M. Grothe, M. Herndon, A. Hervé, U. Hussain, P. Klabbers, A. Lanaro,
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 University of Chinese Academy of Sciences, Beijing, China
7: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia
8: Also at Joint Institute for Nuclear Research, Dubna, Russia
9: Also at Suez University, Suez, Egypt
10: Now at British University in Egypt, Cairo, Egypt
11: Also at Zewail City of Science and Technology, Zewail, Egypt
12: Also at Department of Physics, King Abdulaziz University, Jeddah, Saudi
Arabia
13: Also at Université de Haute Alsace, Mulhouse, France
14: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State
University, Moscow, Russia
15: Also at CERN, European Organization for Nuclear Research, Geneva,
Switzerland
16: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
17: Also at University of Hamburg, Hamburg, Germany
18: Also at Brandenburg University of Technology, Cottbus, Germany
19: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
20: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
21: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary
22: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India
23: Also at Institute of Physics, Bhubaneswar, India
24: Also at Shoolini University, Solan, India
25: Also at University of Visva-Bharati, Santiniketan, India
26: Also at Isfahan University of Technology, Isfahan, Iran
27: Also at Plasma Physics Research Center, Science and Research Branch,
Islamic Azad University, Tehran, Iran
28: Also at Università degli Studi di Siena, Siena, Italy
29: Also at Kyunghee University, Seoul, Korea
30: Also at International Islamic University of Malaysia, Kuala Lumpur,
Malaysia
31: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia
32: Also at Consejo Nacional de Ciencia y Tecnología, Mexico city, Mexico
33: Also at Warsaw University of Technology, Institute of Electronic Systems,
Warsaw, Poland
34: Also at Institute for Nuclear Research, Moscow, Russia
35: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
36: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
37: Also at University of Florida, Gainesville, USA
38: Also at P.N. Lebedev Physical Institute, Moscow, Russia
39: Also at California Institute of Technology, Pasadena, USA
40: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
41: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
42: Also at INFN Sezione di Pavia a, Università di Pavia b, Pavia, Italy
43: Also at University of Belgrade, Faculty of Physics and Vinca Institute of
Nuclear Sciences, Belgrade, Serbia
44: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy
45: Also at National and Kapodistrian University of Athens, Athens, Greece
46: Also at Riga Technical University, Riga, Latvia
47: Also at Universität Zürich, Zurich, Switzerland
48: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna,
Austria
49: Also at Adiyaman University, Adiyaman, Turkey
50: Also at Istanbul Aydin University, Istanbul, Turkey
51: Also at Mersin University, Mersin, Turkey
52: Also at Piri Reis University, Istanbul, Turkey
53: Also at Ozyegin University, Istanbul, Turkey
54: Also at Izmir Institute of Technology, Izmir, Turkey
55: Also at Marmara University, Istanbul, Turkey
56: Also at Kafkas University, Kars, Turkey
57: Also at Istanbul University, Faculty of Science, Istanbul, Turkey
58: Also at Istanbul Bilgi University, Istanbul, Turkey
59: Also at Hacettepe University, Ankara, Turkey
60: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom
61: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
62: Also at Monash University, Faculty of Science, Clayton, Australia
63: Also at Bethel University, St. Paul, USA
64: Also at Karamanoğlu Mehmetbey University, Karaman, Turkey
65: Also at Utah Valley University, Orem, USA
66: Also at Purdue University, West Lafayette, USA
67: Also at Beykent University, Istanbul, Turkey
68: Also at Bingol University, Bingol, Turkey
69: Also at Sinop University, Sinop, Turkey
70: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey
71: Also at Texas A&M University at Qatar, Doha, Qatar
72: Also at Kyungpook National University, Daegu, Korea