EXO-17-023

$HeadURL:svn+ssh://svn.cern.ch/reps/tdr2/papers/EXO-17-023/trunk/EXO-17-023.tex$
$Id:EXO-17-023.tex4750982018-09-1517:28:36Zkakwok$

AN-16-467

# Search for black holes and sphalerons in high-multiplicity final states in
proton-proton collisions at $\sqrt{s}=13\TeV$222We dedicate this paper to the
memory of Prof. Stephen William Hawking, on whose transformative ideas much of
this work relies.

CMS Collaboration

###### Abstract

A search in energetic, high-multiplicity final states for evidence of physics
beyond the standard model, such as black holes, string balls, and electroweak
sphalerons, is presented. The data sample corresponds to an integrated
luminosity of $35.9\fbinv$ collected with the CMS experiment at the LHC in
proton-proton collisions at a center-of-mass energy of 13in 2016. Standard
model backgrounds, dominated by multijet production, are determined from
control regions in data without any reliance on simulation. No evidence for
excesses above the predicted background is observed. Model-independent 95%
confidence level upper limits on the cross section of beyond the standard
model signals in these final states are set and further interpreted in terms
of limits on semiclassical black hole, string ball, and sphaleron production.
In the context of models with large extra dimensions, semiclassical black
holes with minimum masses as high as 10.1and string balls with masses as high
as 9.5are excluded by this search. Results of the first dedicated search for
electroweak sphalerons are presented. An upper limit of 0.021 is set at 95%
confidence level on the fraction of all quark-quark interactions above the
nominal threshold energy of 9resulting in the sphaleron transition.

##  0.1 Introduction

Many theoretical models of physics beyond the standard model (SM) [1, 2, 3]
predict strong production of particles decaying into high-multiplicity final
states, i.e., characterized by three or more energetic jets, leptons, or
photons. Among these models are supersymmetry [4, 5, 6, 7, 8, 9, 10, 11], with
or without $R$-parity violation [12], and models with low-scale quantum
gravity [13, 14, 15, 16, 17], strong dynamics, or other nonperturbative
physics phenomena. While the final states predicted in these models differ
significantly in the type of particles produced, their multiplicity, and the
transverse momentum imbalance, they share the common feature of a large number
of energetic objects (jets, leptons, and/or photons) in the final state. The
search described in this paper targets these models of beyond-the-SM (BSM)
physics by looking for final states of various inclusive multiplicities
featuring energetic objects. Furthermore, since such final states can be used
to test a large variety of models, we provide model-independent exclusions on
hypothetical signal cross sections. Considering concrete examples of such
models, we interpret the results of the search explicitly in models with
microscopic semiclassical black holes (BHs) and string balls (SBs), as well as
in models with electroweak (EW) sphalerons. These examples are discussed in
detail in the rest of this section.

###  0.1.1 Microscopic black holes

In our universe, gravity is the weakest of all known forces. Indeed, the
Newton constant, ${\sim}10^{-38}\GeV^{-2}$, which governs the strength of
gravity, is much smaller than the Fermi constant, ${\sim}10^{-4}\GeV^{-2}$,
which characterizes the strength of EW interactions. Consequently, the Planck
scale ${M_{\mathrm{Pl}}}\sim 10^{19}\GeV$, , the energy at which gravity is
expected to become strong, is 17 orders of magnitude higher than the EW scale
of ${\sim}100\GeV$. With the discovery of the Higgs boson [18, 19, 20] with a
mass [21, 22] at the EW scale, the large difference between the two scales
poses what is known as the hierarchy problem [23]. This is because in the SM,
the Higgs boson mass is not protected against quadratically divergent quantum
corrections and—in the absence of fine tuning—is expected to be naturally at
the largest energy scale of the theory: the Planck scale. A number of
theoretical models have been proposed that attempt to solve the hierarchy
problem, such as supersymmetry, technicolor [24], and, more recently,
theoretical frameworks based on extra dimensions in space: the Arkani-Hamed,
Dimopoulos, and Dvali (ADD) model [13, 14, 15] and the Randall–Sundrum model
[16, 17].

In this paper, we look for the manifestation of the ADD model that postulates
the existence of ${n_{\mathrm{ED}}}\geq 2$ “large” (compared to the inverse of
the EW energy scale) extra spatial dimensions, compactified on a sphere or a
torus, in which only gravity can propagate. This framework allows one to elude
the hierarchy problem by explaining the apparent weakness of gravity in the
three-dimensional space via the suppression of the fundamentally strong
gravitational interaction by the large volume of the extra space. As a result,
the fundamental Planck scale, , in $3+{{n_{\mathrm{ED}}}}$ dimensions is
related to the apparent Planck scale in 3 dimensions via Gauss’s law as:
${M_{\mathrm{Pl}}}^{2}\sim\MD^{{n_{\mathrm{ED}}}+2}R^{n_{\mathrm{ED}}}$, where
$R$ is the radius of extra dimensions. Since could be as low as a few TeV, ,
relatively close to the EW scale, the hierarchy problem would be alleviated.

At high-energy colliders, one of the possible manifestations of the ADD model
is the formation of microscopic BHs [25, 26] with a production cross section
proportional to the squared Schwarzschild radius, given as:

${R_{\mathrm{S}}}=\frac{1}{\sqrt{\pi}\MD}\left[\frac{{M_{\mathrm{BH}}}}{\MD}\left(\frac{8\Gamma(\frac{{n_{\mathrm{ED}}}+3}{2})}{{n_{\mathrm{ED}}}+2}\right)\right]^{\frac{1}{{n_{\mathrm{ED}}}+1}},$

where $\Gamma$ is the gamma function and ${M_{\mathrm{BH}}}$ is the mass of
the BH. In the simplest production scenario, the cross section is given by the
area of a disk of radius ${R_{\mathrm{S}}}$, ,
$\sigma\approx\pi{R_{\mathrm{S}}}^{2}$ [25, 26]. In more complicated
production scenarios, , a scenario with energy loss during the formation of
the BH horizon, the cross section is modified from this “black disk”
approximation by a factor of order one [26].

As BH production is a threshold phenomenon, we search for BHs above a certain
minimum mass ${M_{\mathrm{BH}}^{\text{min}}}\geq\MD$. In the absence of
signal, we will express the results of the search as limits on
${M_{\mathrm{BH}}^{\text{min}}}$. In the semiclassical case (strictly valid
for ${M_{\mathrm{BH}}}\gg\MD$), the BH quickly evaporates via Hawking
radiation [27] into a large number of energetic particles, such as gluons,
quarks, leptons, photons, The relative abundance of various particles produced
in the process of BH evaporation is expected to follow the number of degrees
of freedom per particle in the SM. Thus, about 75% of particles produced are
expected to be quarks and gluons, because they come in three or eight color
combinations, respectively. A significant amount of missing transverse
momentum may be also produced in the process of BH evaporation via production
of neutrinos, which constitute ${\sim}5\%$ of the products of a semiclassical
BH decay, and boson decays, heavy-flavor quark decays, gravitons, or
noninteracting stable BH remnants.

If the mass of a BH is close to , it is expected to exhibit quantum features,
which can modify the characteristics of its decay products. For example,
quantum BHs [28, 29, 30] are expected to decay before they thermalize,
resulting in low-multiplicity final states. Another model of semiclassical BH
precursors is the SB model [31], which predicts the formation of a long,
jagged string excitation, folded into a “ball”. The evaporation of an SB is
similar to that of a semiclassical BH, except that it takes place at a fixed
Hagedorn temperature [32], which depends only on the string scale
${M_{\mathrm{S}}}$. The formation of an SB occurs once the mass of the object
exceeds ${{M_{\mathrm{S}}}/{g_{\mathrm{S}}}}$, where ${g_{\mathrm{S}}}$ is the
string coupling. As the mass of the SB grows, eventually it will transform
into a semiclassical BH, once its mass exceeds
${{M_{\mathrm{S}}}/{g_{\mathrm{S}}}^{2}}>\MD$.

A number of searches for both semiclassical and quantum BHs, as well as for
SBs have been performed at the CERN LHC using the Run 1 ($\sqrt{s}=7$ and 8)
and Run 2 ($\sqrt{s}=13\TeV$) data. An extensive review of Run 1 searches can
be found in Ref. [33]. The most recent Run 2 searches for semiclassical BHs
and SBs were carried out by ATLAS [34, 35] and CMS [36] using 2015 data.
Results of searches for quantum BHs in Run 2 based on 2015 and 2016 data can
be found in Refs. [37, 38, 39, 40, 41, 42]. The most stringent limits on
${M_{\mathrm{BH}}^{\text{min}}}$ set by the Run 2 searches are 9.5 and 9.0 TeV
for semiclassical and quantum BHs, respectively, for $\MD=4\TeV$ [34, 36]. The
analogous limits on the minimum SB mass depend on the choice of the string
scale and coupling and are in the 6.6–9range for the parameter choices
considered in Refs. [34, 36].

###  0.1.2 Sphalerons

The Lagrangian of the EW sector of the SM has a possible nonperturbative
solution, which includes a vacuum transition known as a “sphaleron”. This
class of solutions to gauge field theories was first proposed in 1976 by ’t
Hooft [43]. The particular sphaleron solution of the SM was first described by
Klinkhamer and Manton in 1984 [44]. It is also a critical piece of EW
baryogenesis theory [45], which explains the matter-antimatter asymmetry of
the universe by such processes. The crucial feature of the sphaleron, which
allows such claims to be made, is the violation of baryon ($B$) and lepton
($L$) numbers, while preserving $B-L$. The possibility of sphaleron
transitions at hadron colliders and related phenomenology has been discussed
since the late 1980s [46].

Within the framework of perturbative SM physics, there are twelve globally
conserved currents, one for each of the 12 fundamental fermions:
$J^{\mu}=\overline{\psi}_{L}\gamma^{\mu}\psi_{L}$. An anomaly breaks this
conservation, in particular
$\partial_{\mu}J^{\mu}=[g^{2}/(16\pi^{2})]\mathrm{Tr}[F_{\mu\nu}\widetilde{F}^{\mu\nu}]$.
This is because the integral of this term, known as a Chern–Simons (or
winding) number ${N_{\mathrm{CS}}}$ [47], is nonzero. The anomaly exists for
each fermion doublet. This means that the lepton number changes by
3${N_{\mathrm{CS}}}$, since each of three leptons produced has absolute lepton
number of 1. The baryon number will also change by $3{N_{\mathrm{CS}}}$
because each quark has an absolute baryon number of $1/3$ and there are three
colors and three generations of quarks produced. This results in two important
relations, which are essential to the phenomenology of sphalerons:
$\Delta(B+L)=6{N_{\mathrm{CS}}}$ and $\Delta(B-L)=0$. The anomaly only exists
if there is enough energy to overcome the potential in ${N_{\mathrm{CS}}}$,
which is fixed by the values of the EW couplings. Assuming the state at 125
GeV to be the SM Higgs boson, the precise measurement of its mass [21, 22]
allowed the determination of these couplings, giving an estimate of the energy
required for the sphaleron transitions of ${E_{\mathrm{sph}}}\approx 9\TeV$
[44, 48].

While the ${E_{\mathrm{sph}}}$ threshold is within the reach of the LHC, it
was originally thought that the sphaleron transition probability would be
significantly suppressed by a large potential barrier. However, in a recent
work [48] it has been suggested that the periodic nature of the Chern–Simons
potential reduces this suppression at collision energies
$\sqrt{\hat{s}}<{E_{\mathrm{sph}}}$, removing it completely for
$\sqrt{\hat{s}}\geq{E_{\mathrm{sph}}}$. This argument opens up the possibility
of observing an EW sphaleron transition in proton-proton () collisions at the
LHC via processes such as: $\cPqu+\cPqu\to\Pep\Pgmp\Pgt^{+}$
$\PAQt\,\PAQt\,\PAQb\,\PAQc\,\PAQc\,\PAQs\,\PAQd+X$. Fundamentally, the
${N_{\mathrm{CS}}}=+1$ ($-1$) sphaleron transitions involve 12 (anti)fermions:
three (anti)leptons, one from each generation, and nine (anti)quarks,
corresponding to three colors and three generations, with the total electric
charge and weak isospin of zero. Nevertheless, at the LHC, we consider
signatures with 14, 12, or 10 particles produced, that arise from a
$\cPq+\cPq^{\prime}\to\cPq+\cPq^{\prime}+\mathrm{sphaleron}$ process, where 0,
1, or 2 of the 12 fermions corresponding to the sphaleron transition may
“cancel” the $\cPq$ or $\cPq^{\prime}$ inherited from the initial state [49,
50]. Since between zero and three of the produced particles are neutrinos, and
also between zero and three are top quarks, which further decay, the actual
multiplicity of the visible final-state particles may vary between 7 and 20 or
more. Some of the final-state particles may also be gluons from either
initial- or final-state radiation. While the large number of allowed
combinations of the 12 (anti)fermions results in over a million unique
transitions [51], many of the final states resulting from these transitions
would look identical in a typical collider experiment, as no distinction is
made between quarks of the first two generations, leading to only a few dozen
phenomenologically unique transitions, determined by the charges and types of
leptons and the third-generation quarks in the final state. These transitions
would lead to characteristic collider signatures, which would have many
energetic jets and charged leptons, as well as large missing transverse
momentum due to undetected neutrinos.

A phenomenological reinterpretation in terms of limits on the EW sphaleron
production of an ATLAS search for microscopic BHs in the multijet final states
at $\sqrt{s}=13\TeV$ [34], comparable to an earlier CMS analysis [36], was
recently performed in Ref. [49]. In the present paper, we describe the first
dedicated experimental search for EW sphaleron transitions.

##  0.2 The CMS detector and the data sample

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.

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

Events of interest are selected using a two-tiered trigger system [52]. 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 (HLT), 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. [53].

The analysis is based on a data sample recorded with the CMS detector in
collisions at a center-of-mass energy of 13in 2016, corresponding to an
integrated luminosity of $35.9\fbinv$. Since typical signal events are
expected to contain multiple jets, we employ a trigger based on the variable,
defined as the scalar sum of the transverse momenta () of all jets in an event
reconstructed at the HLT. We require $\HT>800$–900 and also use a logical OR
with several single-jet triggers with thresholds of 450–500 . The resulting
trigger selection is fully efficient for events that subsequently satisfy the
offline requirements used in the analysis.

##  0.3 Event reconstruction

The particle-flow (PF) algorithm [54] aims to reconstruct and identify each
individual particle in an event with an optimized combination of information
from the various elements of the CMS detector. The energy of photons is
directly obtained from the ECAL measurement, corrected for zero-suppression
effects. The energy of electrons is determined from a combination of the
electron momentum at the primary interaction vertex as determined by the
tracker, the energy of the corresponding ECAL cluster, and the energy sum of
all bremsstrahlung photons spatially compatible with originating from the
electron track. The energy of muons is obtained from the curvature of the
corresponding track. The energy of charged hadrons is determined from a
combination of their momentum measured in the tracker and the matching ECAL
and HCAL energy deposits, corrected for zero-suppression effects and for the
response function of the calorimeters to hadronic showers. Finally, the energy
of neutral hadrons is obtained from the corresponding corrected ECAL and HCAL
energies.

The reconstructed vertex with the largest value of summed physics-object
$\pt^{2}$ is taken to be the primary $\Pp\Pp$ interaction vertex. The physics
objects are the jets, clustered using the anti-jet finding algorithm [55, 56]
with the tracks assigned to the vertex as inputs, and the associated missing
transverse momentum, taken as the negative vector sum of the of those jets.
Events are required to have at least one reconstructed vertex within 24 (2)cm
of the nominal collision point in the direction parallel (perpendicular) to
the beams.

For each event, hadronic jets are clustered from the PF candidates using the
anti-algorithm with a distance parameter of 0.4. The jet momentum is
determined as the vectorial sum of all particle momenta in the jet, and is
found from simulation to be within 5 to 10% of the true momentum over the
whole spectrum and detector acceptance. Additional interactions within the
same or neighboring bunch crossings (pileup) can contribute additional tracks
and calorimetric energy depositions to the jet momentum. To mitigate this
effect, tracks originating from pileup vertices are discarded and an offset
correction is applied to correct for the remaining contributions. Jet energy
corrections are derived from simulation, to bring the measured response of
jets to that of particle-level jets on average. In situ measurements of the
momentum balance in dijet, multijet, +jet, and leptonically decaying +jet
events are used to account for any residual differences in the jet energy
scales in data and simulation [57]. The jet energy resolution amounts
typically to 15% at a jet of 10, 8% at 100, and 4% at 1. Additional selection
criteria are applied to each jet to remove those potentially dominated by
anomalous contributions from various subdetector components or reconstruction
failures. All jets are required to have $\pt>70\GeV$ and be within
$\abs{\eta}<5$. For the leading jet in each event, the energy fraction carried
by muon candidates failing the standard identification [58] is required to be
less than 80%. This requirement removes events where a low-momentum muon is
misreconstructed with very high momentum and misidentified as a high-energy
jet. We further require the leading jet in an event to have a charged-hadron
fraction of less than 0.99 if this jet is found within $\abs{\eta}<2.4$ [59].

The missing transverse momentum, $\ptmiss$, is defined as the magnitude of the
vectorial sum of transverse momenta of all PF candidates in an event. The jet
energy corrections are further propagated to the calculation.

Details of muon reconstruction can be found in Ref. [58]. The muon candidate
is required to have at least one matching energy deposit in the pixel tracker
and at least six deposits in the silicon strip tracker, as well as at least
two track segments in the muon detector. The transverse impact parameter and
the longitudinal distance of the track associated with the muon with respect
to the primary vertex are required to be less than 2 and 5mm, respectively, to
reduce contamination from cosmic ray muons. The global track fit to the
tracker trajectory and to the muon detector segments must have a $\chi^{2}$
per degree of freedom of less than 10. Muon candidates are required to have
$\pt>70\GeV$ and to be within $\abs{\eta}<2.4$.

Details of electron and photon reconstruction can be found in Refs. [60] and
[61], respectively. Electron and photon candidates are required to have
$\pt>70\GeV$ and $\abs{\eta}<2.5$, excluding the $1.44<\abs{\eta}<1.57$
transition region between the ECAL barrel and endcap detectors where the
reconstruction is suboptimal. We use standard identification criteria,
corresponding to an average efficiency of 80% per electron or photon. The
identification criteria include a requirement that the transverse size of the
electromagnetic cluster be compatible with the one expected from a genuine
electron or photon, and that the ratio of the HCAL to ECAL energies be less
then 0.25 (0.09) for electrons and less than 0.0396 (0.0219) for photons in
the barrel (endcap). In addition, photon candidates are required to pass the
conversion-safe electron veto requirements [61], which disambiguates them from
electron candidates.

Muons, electrons, and photons are required to be isolated from other energy
deposits in the tracker and the calorimeters. The isolation $\mathcal{I}$ is
defined as the ratio of the sum of various types of additional PF candidates
in a cone of radius $\Delta
R=\sqrt{\smash[b]{(\Delta\eta)^{2}+(\Delta\phi)^{2}}}$ of 0.4 (muons) or 0.3
(electrons and photons), centered on the lepton or photon candidate, to the
candidate’s . For muons, the numerator of the ratio is corrected for the
contribution of neutral particles due to pileup, using one half of the carried
by the charged hadrons originating from pileup vertices. For electrons and
photons, an average area method [62], as estimated with [56], is used. The
isolation requirements are the same as used in an earlier 13analysis [36],
except that for electrons we use a tighter isolation requirement of ${\cal
I}<0.07$.

To avoid double counting, we remove jets that are found within a radius of
$\Delta R=0.3$ from a muon, electron, or photon, if the latter object
contributes more than 80, 70, or 50% of the jet , respectively.

##  0.4 Analysis strategy

We follow closely the approach for semiclassical BH searches originally
developed by CMS for Run 1 analyses [63, 64, 65] and subsequently used in the
studies of early Run 2 [36] data. This approach is based on an inclusive
search for BH decays to all possible final states, dominated by the high-
multiplicity multijet ones in the semiclassical BH case. This type of analysis
is less sensitive to the details of BH evaporation and the relative abundance
of various particles produced, as it considers all types of particles in the
final state. We use a single discriminating variable ${S_{\mathrm{T}}}$,
defined as the scalar sum of of all $N$ energetic objects in an event (which
we define as jets, electrons, muons, and photons with above a given
threshold), plus in the event, if it exceeds the same threshold:
${S_{\mathrm{T}}}=\ptmiss+\sum_{i=1}^{N}\pt^{i}$. Accounting for in the
${S_{\mathrm{T}}}$ variable makes ${S_{\mathrm{T}}}$ a better measure of the
total transverse momentum in the event carried by all the various particles.
Since it is impossible to tell how many objects lead to the in the event, we
do not consider values above the threshold when determining the object
multiplicity.

This definition of ${S_{\mathrm{T}}}$ is robust against variations in the BH
evaporation model, and is also sensitive to the cases when there is large due
to enhanced emission of gravitons or to models in which a massive, weakly
interacting remnant of a BH is formed at the terminal stage of Hawking
evaporation, with a mass below . It is equally applicable to sphaleron
searches, given the expected energetic, high-multiplicity final states,
possibly with large .

The ${S_{\mathrm{T}}}$ distributions are then considered separately for
various inclusive object multiplicities (,
$N\geq{N^{\mathrm{min}}}=3,\dots,11$). The background is dominated by SM QCD
multijet production and is estimated exclusively from control samples in data.
The observed number of events with ${S_{\mathrm{T}}}$ values above a chosen
threshold is compared with the background and signal+background predictions to
either establish a signal or to set limits on the signal production. This
approach does not rely on the Monte Carlo (MC) simulation of the backgrounds,
and it also has higher sensitivity than exclusive searches in specific final
states, , lepton+jets [66, 67].

The main challenge of the search is to describe the inclusive multijet
background in a robust way, as both BH and sphaleron signals correspond to a
broad enhancement in the high tail of the ${S_{\mathrm{T}}}$ distribution,
rather than to a narrow peak. Since these signals are expected to involve a
high multiplicity of final-state particles, one has to reliably describe the
background for large jet multiplicities, which is quite challenging
theoretically as higher-order calculations that fully describe multijet
production do not exist. Thus, one cannot rely on simulation to reproduce the
${S_{\mathrm{T}}}$ spectrum for large $N$ correctly.

To overcome this problem, a dedicated method of predicting the QCD multijet
background directly from collision data has been developed for the original
Run 1 analysis [63] and used in the subsequent Run 1 [64, 65] and Run 2 [36]
searches. It has been found empirically, first via simulation-based studies,
and then from the analysis of data at low jet multiplicities, that the shape
of the ${S_{\mathrm{T}}}$ distribution for the dominant QCD multijet
background does not depend on the multiplicity of the final state, above a
certain turn-on threshold. This observation reflects the way a parton shower
develops via nearly collinear emission, which conserves ${S_{\mathrm{T}}}$. It
allows one to predict the ${S_{\mathrm{T}}}$ spectrum of a multijet final
state using low-multiplicity QCD events, , dijet or trijet events. This
“${S_{\mathrm{T}}}$ invariance” provides a powerful method of predicting the
dominant background for BH production by taking the ${S_{\mathrm{T}}}$ shape
from low-multiplicity events, for which the signal contamination is expected
to be negligible, and normalizing it to the observed spectrum at high
multiplicities at the low end of the ${S_{\mathrm{T}}}$ distribution, where
signal contamination is negligible even for large multiplicities of the final-
state objects. The method has been also used for other CMS searches, , a
search for stealth supersymmetry [68] and a search for multijet resonances
[69].

##  0.5 Simulated samples

###  0.5.1 Black hole and string ball signal samples

Signal simulation is performed using the BlackMax v2.02.0 [70] (semiclassical
BHs) and 2 v1.003 [71, 72] (semiclassical BHs and SBs) generators. The
generator settings of each model are listed in Tables 0.5.1 and 0.5.1.

Generator settings used for BlackMax signal sample generation.  Model
Choose_a_case Mass_loss_factor Momentum_loss_factor turn_on_graviton B1
tensionless_nonrotating 0 0 FALSE B2 rotating_nonsplit 0 0 FALSE B3
rotating_nonsplit 0.1 0.1 TRUE

Generator settings used for 2 signal sample generation.  Model BHSPIN MJLOST
YRCSC NBODYAVERAGE NBODYPHASE NBODYVAR RMSTAB RMBOIL C1 TRUE FALSE FALSE FALSE
TRUE TRUE FALSE FALSE C2 FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE C3 TRUE
FALSE FALSE TRUE FALSE FALSE FALSE FALSE C4 TRUE TRUE TRUE FALSE TRUE TRUE
FALSE FALSE C5 TRUE TRUE TRUE FALSE FALSE FALSE TRUE FALSE C6 TRUE TRUE TRUE
FALSE FALSE FALSE FALSE TRUE

For semiclassical BH signals, we explore different aspects of BH production
and decay by simulating various scenarios, including nonrotating BHs (B1,C2),
rotating BHs (B2,C1), rotating BHs with mass loss (B3), and rotating BHs with
Yoshino–Rychkov bounds [73] (C4). Models C3, C5, and C6 explore the
termination phase of the BH with different object multiplicities from the BH
remnant, varying from 2-body decaying remnant (C3), stable remnant (C5, for
which additionally the generator parameter NBODY was changed from its default
value of 2 to 0), and ”boiling” remnant (C6), where the remnant continues to
evaporate until a maximum Hawking temperature equal to is reached. For each
model, the fundamental Planck scale is varied within 2–9in 1steps, each with
${n_{\mathrm{ED}}}=2,\,4,\,6$. The minimum black hole mass
${M_{\mathrm{BH}}^{\text{min}}}$ is varied between $\MD+1\TeV$ and 11in
1steps.

For SB signals, two sets of benchmark points are generated with 2, such that
different regimes of the SB production can be explored. For a constant string
coupling value ${g_{\mathrm{S}}}=0.2$ the string scale ${M_{\mathrm{S}}}$ is
varied from 2 to 4, while at constant ${M_{\mathrm{S}}}=3.6\TeV$,
${g_{\mathrm{S}}}$ is varied from 0.2 to 0.4. For all SB samples,
${n_{\mathrm{ED}}}=6$ is used. The SB dynamics below the first transition
(${{M_{\mathrm{S}}}/{g_{\mathrm{S}}}}$), where the SB production cross section
scales with ${g_{\mathrm{S}}}^{2}/{M_{\mathrm{S}}}^{4}$, are probed with the
constant ${g_{\mathrm{S}}}=0.2$ and low ${M_{\mathrm{S}}}$ values as well as
with the constant ${M_{\mathrm{S}}}$ scan. The saturation regime
(${{M_{\mathrm{S}}}/{g_{\mathrm{S}}}}<{M_{\mathrm{SB}}}<{{M_{\mathrm{S}}}/{g_{\mathrm{S}}}^{2}}$),
where the SB production cross section no longer depends on ${g_{\mathrm{S}}}$,
is probed by the higher ${M_{\mathrm{S}}}$ points of the constant
${g_{\mathrm{S}}}$ benchmark. For each benchmark point, the scale is chosen
such that the cross section at the SB–BH transition
(${{M_{\mathrm{S}}}/{g_{\mathrm{S}}}^{2}}$) is continuous.

For the BH and SB signal samples we use leading order (LO) MSTW2008LO [74, 75]
parton distribution functions (PDFs). This choice is driven by the fact that
this set tends to give a conservative estimate of the signal cross section at
high masses, as checked with the modern NNPDF3.0 [76] LO PDFs, with the value
of strong coupling constant of 0.118 used for the central prediction, with a
standard uncertainty eigenset. The MSTW2008LO PDF set was also used in all Run
1 BH searches [63, 64, 65] and in an earlier Run 2 [36] search, which makes
the comparison with earlier results straightforward.

###  0.5.2 Sphaleron signal samples

The electroweak sphaleron processes are generated at LO with the BaryoGEN v1.0
generator [50], capable of simulating various final states described in
Section 0.1.2. We simulate the sphaleron signal for three values of the
transition energy ${E_{\mathrm{sph}}}=8$, 9, and 10. The parton-level
simulation is done with the CT10 LO PDF set [77]. In the process of studying
various PDF sets, we found that the NNPDF3.0 yields a significantly larger
fraction of sea quarks in the kinematic region of interest than all other
modern PDFs. While the uncertainty in this fraction is close to 100%, we chose
the CT10 set, for which this fraction is close to the median of the various
PDF sets we studied. The PDF uncertainties discussed in Section 0.7 cover the
variation in the signal acceptance between various PDFs due to this effect.

The typical final-state multiplicities for the ${N_{\mathrm{CS}}}=\pm 1$
sphaleron transitions resulting in 10, 12, or 14 parton-level final states are
shown in Fig. 1. The ${N_{\mathrm{CS}}}=1$ transitions are dominated by 14
final-state partons, as the proton mainly consists of valence quarks, thus
making the probability of cancellations small.

Figure 1: Observed final-state particle multiplicity $N$ distributions for
${N_{\mathrm{CS}}}=\pm 1$ sphaleron transitions resulting in 10, 12, and 14
parton-level final-state multiplicities. The relative numbers of events in the
histograms are proportional to the relative probabilities of these three
parton-level configurations. The peaks at positive values correspond to
${N_{\mathrm{CS}}}=1$ transitions, while those at negative values correspond
to ${N_{\mathrm{CS}}}=-1$ transitions and therefore are shifted toward lower
multiplicity $N$ because of cancellations with initial-state partons.

The cross section for sphaleron production is given by [49]:
$\sigma=\mathrm{PEF}\,\sigma_{0}$, where $\sigma_{0}=121,$ 10.1, and 0.51fb
for ${E_{\mathrm{sph}}}=8,$ 9, and 10, respectively, and PEF is the pre-
exponential factor, defined as the fraction of all quark-quark interactions
above the sphaleron energy threshold ${E_{\mathrm{sph}}}$ that undergo the
sphaleron transition.

###  0.5.3 Background samples

In addition, we use simulated samples of +jets, +jets, +jets, , and QCD
multijet events for auxiliary studies. These events are generated with the
v2.2.2 [78] event generator at LO or next-to-LO, with the NNPDF3.0 PDF set of
a matching order.

The fragmentation and hadronization of parton-level signal and background
samples is done with v8.205 [79], using the underlying event tune CUETP8M1
[80]. All signal and background samples are reconstructed with the detailed
simulation of the CMS detector via [81]. The effect of pileup interactions is
simulated by superimposing simulated minimum bias events on the hard-
scattering interaction, with the multiplicity distribution chosen to match the
one observed in data.

##  0.6 Background estimate

###  0.6.1 Background composition

The main backgrounds in the analyzed multi-object final states are: QCD
multijet, V+jets (where V = , ), +jets, and production, with the QCD multijet
background being by far the most dominant. Figure 2 illustrates the relative
importance of these backgrounds for the inclusive multiplicity $N\geq 3$ and 6
cases, based on simulated background samples. To reach the overall agreement
with the data, all simulated backgrounds except for the QCD multijets are
normalized to the most accurate theoretical predictions available, while the
QCD multijet background is normalized so that the total number of background
events matches that in data. While we do not use simulated backgrounds to
obtain the main results in this analysis, Fig. 2 illustrates an important
point: not only is the QCD multijet background at least an order of magnitude
more important than other backgrounds, for both low- and high-multiplicity
cases, but also the shape of the ${S_{\mathrm{T}}}$ distributions for all
major backgrounds is very similar, so the method we use to estimate the
multijet background, discussed below, provides an acceptable means of
predicting the overall background as well.

Figure 2: The ${S_{\mathrm{T}}}$ distribution in data for inclusive
multiplicities of (left) $N\geq 3$ and (right) $N\geq 6$, compared with the
normalized background prediction from simulation, illustrating the relative
contributions of major backgrounds. The lower panels show the difference
between the data and the simulated background prediction, divided by the
statistical uncertainty in data. We note that despite an overall agreement, we
do not rely on simulation for obtaining the background prediction.

###  0.6.2 Background shape determination

The background prediction method used in the analysis follows closely that in
previous similar CMS searches [63, 64, 65, 36]. As discussed in Section 0.4,
the central idea of this method is that the shape of the ${S_{\mathrm{T}}}$
distribution for the dominant multijet background is invariant with respect to
the final-state object multiplicity $N$. Consequently, the background shape
can be extracted from low-multiplicity spectra and used to describe the
background at high multiplicities. The ${S_{\mathrm{T}}}$ value is preserved
by the final-state radiation, which is the dominant source of extra jets
beyond LO $2\to 2$ QCD processes, as long as the additional jets are above the
threshold used in the definition of ${S_{\mathrm{T}}}$. At the same time, jets
from initial-state radiation (ISR) change the ${S_{\mathrm{T}}}$ value, but
because their spectrum is steeply falling they typically contribute only a few
percent to the ${S_{\mathrm{T}}}$ value and change the multiplicity $N$ by
just one unit, for events used in the analysis. Consequently, we extract the
background shape from the $N=3$ ${S_{\mathrm{T}}}$ spectrum, which already has
a contribution from ISR jets, and therefore reproduces the ${S_{\mathrm{T}}}$
shape at higher multiplicities better than the $N=2$ spectrum used in earlier
analyses. To estimate any residual noninvariance in the ${S_{\mathrm{T}}}$
distribution, the $N=4$ ${S_{\mathrm{T}}}$ spectrum, normalized to the $N=3$
spectrum in terms of the total number of events, is also used as an additional
component of the background shape uncertainty. Furthermore, to be less
sensitive to the higher instantaneous luminosity delivered by the LHC in 2016,
which resulted in a higher pileup, and to further reduce the effect of ISR,
the threshold for all objects was raised to 70, compared to 50used in earlier
analyses. The reoptimization that has resulted in the choice of a new
exclusive multiplicity to be used for the baseline QCD multijet background
prediction and a higher minimum threshold for the objects counted toward
${S_{\mathrm{T}}}$ was based on extensive studies of MC samples and
low-${S_{\mathrm{T}}}$ events in data.

In order to obtain the background template, we use a set of 16 functions
employed in earlier searches for BSM physics in dijets, VV events, and
multijet events at various colliders. These functions typically have an
exponential or power-law behavior with ${S_{\mathrm{T}}}$, and are described
by 3–5 free parameters. Some of the functions are monotonously falling with
${S_{\mathrm{T}}}$ by construction; however, some of them contain polynomial
terms, such that they are not constrained to have a monotonic behavior. In
order to determine the background shape, we fit the $N=3$ ${S_{\mathrm{T}}}$
distribution or the $N=4$ ${S_{\mathrm{T}}}$ distribution, normalized to the
same total event count as the $N=3$ distribution, in the range of 2.5–4.3,
where any sizable contributions from BSM physics have been ruled out by
earlier versions of this analysis, with all 16 functional forms. The lowest
masses of the signal models considered, which have not been excluded by the
previous analysis [36], contribute less than 2% to the total number of events
within the fit range. Any functional form observed not to be monotonically
decreasing up to ${S_{\mathrm{T}}}=13\TeV$ after the fit to both
multiplicities is discarded. The largest spread among all the accepted
functions in the $N=3$ and $N=4$ fits is used as an envelope of the systematic
uncertainty in the background template. The use of both $N=3$ and $N=4$
distributions to construct the envelope allows one to take into account any
residual ${S_{\mathrm{T}}}$ noninvariance in the systematic uncertainty in the
background prediction. We observe a good closure of the method to predict the
background distributions in simulated QCD multijet events.

The best fits (taking into account the F-test criterion [82] within each set
of nested functions) to the $N=3$ and $N=4$ distributions in data, along with
the corresponding uncertainty envelopes, are shown in the two panels of Fig.
3. In both cases, the best fit function is
$f(x)=p_{0}(1-x^{1/3})^{p_{1}}/(x^{p_{2}+p_{3}\log^{2}(x)})$, where
$x={S_{\mathrm{T}}}/\sqrt{s}={S_{\mathrm{T}}}/(13\TeV)$ and $p_{i}$ are the
four free parameters of the fit. The envelope of the predictions at large
${S_{\mathrm{T}}}$ (${S_{\mathrm{T}}}>5.5\TeV$, most relevant for the present
search) is given by the fit with the following 5-parameter function:
$\phi(x)=p_{0}(1-x)^{p_{1}}/(x^{p_{2}+p_{3}\log(x)+p_{4}\log^{2}(x)})$ to the
$N=4$ (upper edge of the envelope) or $N=3$ (lower edge of the envelope)
distributions. For ${S_{\mathrm{T}}}$ values below 5.5the envelope is built
piecewise from other template functions fitted to either the $N=3$ or $N=4$
distribution.

Figure 3: The results of the fit to data with $N=3$ (left) and $N=4$ (right),
after discarding the functions that fail to monotonically decrease up to
${S_{\mathrm{T}}}=13\TeV$. The description of the best fit function and the
envelope are given in the main text. A few points beyond the plotted vertical
range in the ratio panels are outside the fit region and do not contribute to
the fit quality.

###  0.6.3 Background normalization

The next step in the background estimation for various inclusive
multiplicities is to normalize the template and the uncertainty envelope,
obtained as described above, to low-${S_{\mathrm{T}}}$ data for various
inclusive multiplicities. This has to be done with care, as the
${S_{\mathrm{T}}}$ invariance is only expected to be observed above a certain
threshold, which depends on the inclusive multiplicity requirement. Indeed,
since there is a threshold on the objects whose transverse energies count
toward the ${S_{\mathrm{T}}}$ value, the minimum possible ${S_{\mathrm{T}}}$
value depends on the number of objects in the final state, and therefore the
shape invariance for an ${S_{\mathrm{T}}}$ spectrum with
$N\geq{N^{\mathrm{min}}}$ is only observed above a certain ${S_{\mathrm{T}}}$
threshold, which increases with ${N^{\mathrm{min}}}$. In order to determine
the minimum value of ${S_{\mathrm{T}}}$ for which this invariance holds, we
find a plateau in the ratio of the ${S_{\mathrm{T}}}$ spectrum for each
inclusive multiplicity to that for $N=3$ in simulated multijet events. The
plateau for each multiplicity is found by fitting the ratio with a sigmoid
function. The lower bound of the normalization region (NR) is chosen to be
above the 99% point of the corresponding sigmoid function. The upper bound of
each NR is chosen to be 0.4above the corresponding lower bound to ensure
sufficient event count in the NR. Since the size of the simulated QCD multijet
background sample is not sufficient to reliably extract the turn-on threshold
for inclusive multiplicities of $N\geq 9$–11, for these multiplicities we use
the same NR as for the $N\geq 8$ distribution. A self-consistency check with
the CMS data sample has shown that this procedure provides an adequate
description of the data. Table 0.6.3 summarizes the turn-on thresholds and the
NR boundaries obtained for each inclusive multiplicity.

The ${S_{\mathrm{T}}}$ invariance thresholds from fits to simulated QCD
multijet background spectra, normalization region definitions, and
normalization scale factors in data for different inclusive multiplicities.
Multiplicity 99% turn-on Normalization Normalization point () region () scale
factor (data) ${\geq}3$ $2.44\pm 0.06$ 2.5–2.9 $3.437\pm 0.025$ ${\geq}4$
$2.47\pm 0.06$ 2.5–2.9 $2.437\pm 0.019$ ${\geq}5$ $2.60\pm 0.07$ 2.7–3.1
$1.379\pm 0.016$ ${\geq}6$ $2.75\pm 0.11$ 2.9–3.3 $0.652\pm 0.012$ ${\geq}7$
$2.98\pm 0.13$ 3.0–3.4 $0.516\pm 0.015$ ${\geq}8$ $3.18\pm 0.21$ 3.2–3.6
$0.186\pm 0.011$ ${\geq}9$ $3.25\pm 0.28$ 3.2–3.6 $0.055\pm 0.006$ ${\geq}10$
$3.02\pm 0.26$ 3.2–3.6 $0.012\pm 0.003$ ${\geq}11$ $2.89\pm 0.24$ 3.2–3.6
$0.002\pm 0.001$

Figure 4: The comparison of data and the background predictions after the
normalization for inclusive multiplicities $N\geq 3,\dots,6$ (left to right,
upper to lower). The gray band shows the background shape uncertainty alone
and the red lines also include the normalization uncertainty. The bottom
panels show the difference between the data and the background prediction from
the fit, divided by the overall uncertainty, which includes the statistical
uncertainty of data as well as the shape and normalization uncertainties in
the background prediction, added in quadrature.

The normalization scale factors are calculated as the ratio of the number of
events in each NR for the inclusive multiplicities of $N\geq 3,\dots,11$ to
that for the exclusive multiplicity of $N=3$ in data, and are listed in Table
0.6.3. The relative scale factor uncertainties are derived from the number of
events in each NR, as $1/\sqrt{N_{\mathrm{NR}}}$, where $N_{\mathrm{NR}}$ is
the number of events in the corresponding NR.

###  0.6.4 Comparison with data

The results of the background prediction and their comparison with the
observed data are shown in Figs. 4 and 5 for inclusive multiplicities $N\geq
3,\dots,11$. The data are consistent with the background predictions in the
entire ${S_{\mathrm{T}}}$ range probed, for all inclusive multiplicities.

Figure 5: The comparison of data and the background predictions after
normalization for inclusive multiplicities of $N\geq 7,\dots,11$ (left to
right, upper to lower). The gray band shows the shape uncertainty and the red
lines also include the normalization uncertainty. The bottom panels show the
difference between the data and the background prediction from the fit,
divided by the overall uncertainty, which includes the statistical uncertainty
of data as well as the shape and normalization uncertainties in the background
prediction, added in quadrature. The $N\geq 7$ ($N\geq 8,\dots,11$)
distributions also show contributions from benchmark BlackMax B1 (sphaleron)
signals added to the expected background.

##  0.7 Systematic uncertainties

There are several sources of systematic uncertainty in this analysis. Since
the background estimation is based on control samples in data, the only
uncertainties affecting the background predictions are the modeling of the
background shape via template functions and the normalization of the chosen
function to data at low ${S_{\mathrm{T}}}$, as described in Section 0.6. They
are found to be 1–130% and 0.7–50%, depending on the values of
${S_{\mathrm{T}}}$ and ${N^{\mathrm{min}}}$, respectively.

For the signal, we consider the uncertainties in the PDFs, jet energy scale
(JES), and the integrated luminosity. For the PDF uncertainty, we only
consider the effect on the signal acceptance, while the PDF uncertainty in the
signal cross section is treated as a part of the theoretical uncertainty and
therefore is not propagated in the experimental cross section limit. The
uncertainty in the signal acceptance is calculated using PDF4LHC
recommendations [83, 84] based on the quadratic sum of variations from the
MSTW2008 uncertainty set (${\approx}0.5\%$), as well as the variations
obtained by using three different PDF sets: MSTW2008, CTEQ6.1 [85], and
NNPDF2.3 [76] (up to 6% based on the difference between the default and
CTEQ6.1 sets) for one of the benchmark models (nonrotating BH with
$\MD=3\TeV$, ${M_{\mathrm{BH}}}=5.5\TeV$, and $n=2$, as generated by
BlackMax); the size of the effect for other benchmark points is similar. To be
conservative, we assign a systematic uncertainty of 6% due to the choice of
PDFs for all signal samples. The JES uncertainty affects the signal acceptance
because of the kinematic requirements on the objects and the fraction of
signal events passing a certain ${S_{\mathrm{T}}^{\text{min}}}$ threshold used
for limit setting, as described in Section 0.8. In order to account for these
effects, the jet four-momenta are simultaneously shifted up or down by the JES
uncertainty, which is a function of the jet and $\eta$, and the largest of the
two differences with respect to the use of the nominal JES is assigned as the
uncertainty. The uncertainty due to JES depends on ${M_{\mathrm{BH}}}$ and
varies between $<$1 and 5%; we conservatively assign a constant value of 5% as
the signal acceptance uncertainty due to JES. Finally, the integrated
luminosity is measured with an uncertainty of 2.5% [86]. Effects of all other
uncertainties on the signal acceptance are negligible.

The values of systematic uncertainties that are used in this analysis are
summarized in Table 0.7.

Summary of systematic uncertainties in the signal acceptance and the
background estimate.  Uncertainty source Effect on signal acceptance Effect on
background PDF $\pm 6\%$ — JES $\pm 5\%$ — Integrated luminosity $\pm 2.5\%$ —
Shape modeling — $\pm$(1–130)%, depending on ${S_{\mathrm{T}}}$ Normalization
— $\pm$(0.7–50)%, depending on ${N^{\mathrm{min}}}$

##  0.8 Results

As shown in Figs. 4 and 5, there is no evidence for a statistically
significant signal observed in any of the inclusive ${S_{\mathrm{T}}}$
distributions. The null results of the search are interpreted in terms of
model-independent limits on BSM physics in energetic, multiparticle final
states, and as model-specific limits for a set of semiclassical BH and SB
scenarios, as well as for EW sphalerons.

Limits are set using the method [87, 88, 89] with log-normal priors in the
likelihood to constrain the nuisance parameters near their best estimated
values. We do not use an asymptotic approximation of the method [90], as for
most of the models the optimal search region corresponds to a very low
background expectation, in which case the asymptotic approximation is known to
overestimate the search sensitivity.

###  0.8.1 Model-independent limits

Figure 6: Model-independent upper limits on the cross section times acceptance
for four sets of inclusive multiplicity thresholds, $N\geq 3,\dots,6$ (left to
right, upper to lower). Observed (expected) limits are shown as the black
solid (dotted) lines. The inner (outer) band represents the $\pm 1$ ($\pm 2$)
standard deviation uncertainty in the expected limit.

Figure 7: Model-independent upper limits on the cross section times acceptance
for five sets of inclusive multiplicity thresholds, $N\geq 7,\dots,11$ (left
to right, upper to lower). Observed (expected) limits are shown as the black
solid (dotted) lines. The inner (outer) band represents the $\pm 1$ ($\pm 2$)
standard deviation uncertainty in the expected limit.

The main result of this analysis is a set of model-independent upper limits on
the product of signal cross section and acceptance ($\sigma\,A$) in inclusive
$N\geq{N^{\mathrm{min}}}$ final states, as a function of the minimum
${S_{\mathrm{T}}}$ requirement, ${S_{\mathrm{T}}^{\text{min}}}$, obtained from
a simple counting experiment for
${S_{\mathrm{T}}}>{S_{\mathrm{T}}^{\text{min}}}$. These limits can then be
translated into limits on the ${M_{\mathrm{BH}}^{\text{min}}}$ in a variety of
models, or on any other signals resulting in an energetic, multi-object final
state. We start with the limits for the inclusive multiplicities $N\geq 3,4$,
which can be used to constrain models resulting in lower multiplicities of the
final-state objects. Since part of the data entering these distributions are
used to determine the background shape and its uncertainties, the limits are
set only for ${S_{\mathrm{T}}^{\text{min}}}$ values above the background fit
region, , for ${S_{\mathrm{T}}}>4.5\TeV$. For other multiplicities, the limits
are shown for ${S_{\mathrm{T}}}$ values above the NRs listed in Table 0.6.3.
These limits at 95% confidence level (CL) are shown in Figs. 6 and 7. When
computing the limits, we use systematic uncertainties in the signal acceptance
applicable to the specific models discussed in this paper, as documented in
Section 0.7. It is reasonable to expect these limits to apply to a large
variety of models resulting in multi-object final states dominated by jets.
The limits on the product of the cross section and acceptance approach 0.08fb
at high values of ${S_{\mathrm{T}}^{\text{min}}}$.

###  0.8.2 Model-specific limits

To determine the optimal point of ${S_{\mathrm{T}}^{\text{min}}}$ and the
minimum multiplicity of the final-state objects ${N^{\mathrm{min}}}$ for
setting an exclusion limit for a particular model, we calculate the acceptance
and the expected limit on the cross section for a given model for each point
of the model-independent limit curves, for all inclusive multiplicities. The
optimal point of $({N^{\mathrm{min}}},{S_{\mathrm{T}}^{\text{min}}})$ is
chosen as the point that gives the lowest expected cross section limit. In
most of the cases this point also maximizes the significance of an
observation, for the case of a nonzero signal present in data [36].

An example of a model-specific limit is given in Fig. 8 for a BlackMax
benchmark point B1 (nonrotating semiclassical BH) with = 4,
${n_{\mathrm{ED}}}=6$, and ${M_{\mathrm{BH}}^{\text{min}}}$ between 5 and 11.
In this case, the optimal inclusive multiplicity ${N^{\mathrm{min}}}$ starts
at 7 for the lowest ${M_{\mathrm{BH}}^{\text{min}}}$ value of 5, with the
corresponding ${S_{\mathrm{T}}^{\text{min}}}=5\TeV$. As
${M_{\mathrm{BH}}^{\text{min}}}$ increases, the optimal point shifts to lower
inclusive multiplicities and the corresponding ${S_{\mathrm{T}}^{\text{min}}}$
increases, reaching $(3,7.6\TeV)$ for ${M_{\mathrm{BH}}^{\text{min}}}=11\TeV$.
The corresponding 95% CL upper limit curve and the theoretical cross section
for the chosen benchmark point is shown in Fig. 8. The observed (expected) 95%
CL lower limit on ${M_{\mathrm{BH}}^{\text{min}}}$ in this benchmark model can
be read from this plot as the intersection of the theoretical curve with the
observed (expected) 95% CL upper limit on the cross section, and is found to
be 9.7 (9.7).

Figure 8: Example of a model-specific limit on
${M_{\mathrm{BH}}^{\text{min}}}$ for a semiclassical nonrotating BH model
(BlackMax point B1) with $\MD=4\TeV$ ${n_{\mathrm{ED}}}=6$, as a function of
${M_{\mathrm{BH}}^{\text{min}}}$. The 95% CL upper exclusion limit on the
signal cross section for each ${M_{\mathrm{BH}}^{\text{min}}}$ value is
obtained at the optimal $({N^{\mathrm{min}}},{S_{\mathrm{T}}^{\text{min}}})$
point, which ranges from $(7,5.0\TeV)$ for
${M_{\mathrm{BH}}^{\text{min}}}=5\TeV$ to $(3,7.6\TeV)$ for
${M_{\mathrm{BH}}^{\text{min}}}=11\TeV$. Also shown with a dashed line are the
theoretical cross sections corresponding to these optimal points. The inner
(outer) band represents the $\pm 1$ ($\pm 2$) standard deviation uncertainty
in the expected limit.

We repeat the above procedure for all chosen benchmark scenarios of
semiclassical BHs, listed in Tables 0.5.1 and 0.5.1. The resulting observed
limits on the ${M_{\mathrm{BH}}^{\text{min}}}$ are shown in Figs. 9 and 10,
for the BlackMax and 2 benchmarks, respectively. We also obtain similar limits
on the SB mass for the set of the SB model parameters we scanned. These limits
are shown in Fig. 11 for a fixed string scale ${M_{\mathrm{S}}}=3.6\TeV$, as a
function of the string coupling ${g_{\mathrm{S}}}$ (left plot) and for a fixed
string coupling ${g_{\mathrm{S}}}=0.2$ as a function of the string scale
${M_{\mathrm{S}}}$ (right plot). The search excludes SB masses below 7.1–9.4,
depending on the values of the string scale and coupling.

Figure 9: The observed 95% CL lower limits on ${M_{\mathrm{BH}}^{\text{min}}}$
as a function of at different $n$ for the models B1–B3 generated with
BlackMax. Figure 10: The 95% observed CL lower limits on
${M_{\mathrm{BH}}^{\text{min}}}$ as a function of at different $n$ for the
models C1–C6 generated with 2.

Figure 11: The 95% CL lower limits on a string ball mass as a function of the
string scale ${M_{\mathrm{S}}}$ for a fixed value of the string coupling
${g_{\mathrm{S}}}=0.2$ (left) and as a function of the string coupling
${g_{\mathrm{S}}}$ for a fixed value of the string scale
${M_{\mathrm{S}}}=3.6\TeV$ (right). The inner (outer) band represents the $\pm
1$ ($\pm 2$) standard deviation uncertainty in the expected limit. The area
below the solid curve is excluded by this search.

For the sphaleron signal, the optimal
$({N^{\mathrm{min}}},{S_{\mathrm{T}}^{\text{min}}})$ point is also chosen by
scanning for the lowest expected limit and is found to be $(8,6.2\TeV)$ for
${E_{\mathrm{sph}}}=9$ and 10, and $(9,5.6\TeV)$ for
${E_{\mathrm{sph}}}=8\TeV$. Consequently, the exclusion limit on the sphaleron
cross section can be converted into a limit on the PEF, defined in Section
0.5.2. Following Ref. [49] we calculate the PEF limits for the nominal
${E_{\mathrm{sph}}}=9\TeV$, as well as for the modified values of
${E_{\mathrm{sph}}}=8$ and 10. The observed and expected 95% CL upper limits
on the PEF are shown in Fig. 12. The observed (expected) limit obtained for
the nominal ${E_{\mathrm{sph}}}=9\TeV$ is 0.021 (0.012), which is an order of
magnitude more stringent than the limit obtained in Ref. [49] based on the
reinterpretation of the ATLAS result [34].

Figure 12: Observed (solid curve) and expected (dashed black curve) 95% CL
upper limit on the pre-exponential factor PEF of the sphaleron production as a
function of ${E_{\mathrm{sph}}}$. The inner (outer) band represents the $\pm
1$ ($\pm 2$) standard deviation uncertainty in the expected limit. The area
above the solid curve is excluded by this search.

##  0.9 Summary

A search has been presented for generic signals of beyond the standard model
physics resulting in energetic multi-object final states, such as would be
produced by semiclassical black holes, string balls, and electroweak
sphalerons. The search was based on proton-proton collision data at a center-
of-mass energy of 13, collected with the CMS detector in 2016 and
corresponding to an integrated luminosity of $35.9\fbinv$. The background,
dominated by QCD multijet production, is determined solely from low-
multiplicity samples in data. Comparing the distribution of the total
transverse momentum ${S_{\mathrm{T}}}$ of the final-state objects in data with
that expected from the backgrounds, we set 95% confidence level model-
independent upper limits on the product of the production cross section and
acceptance for such final states, as a function of the minimum
${S_{\mathrm{T}}}$ for minimum final-state multiplicities between 3 and 11.
These limits reach 0.08fb at high ${S_{\mathrm{T}}}$ thresholds. By
calculating the acceptance values for benchmark black hole, string ball, and
sphaleron signal models, we convert these model-independent limits into lower
limits on the minimum semiclassical black hole mass and string ball mass. The
limits extend as high as 10.1, thus improving significantly on previous
results. We have also set the first experimental upper limit on the
electroweak sphaleron pre-exponential factor of 0.021 for the sphaleron
transition energy of 9.

###### 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”) Programme and the János Bolyai Research Scholarship of the
Hungarian Academy of Sciences, the New National Excellence Program ÚNKP, the
NKFIA research grants 123842, 123959, 124845, 124850 and 125105 (Hungary); the
Council of Science and Industrial Research, India; the HOMING PLUS program of
the Foundation for Polish Science, cofinanced from European Union, Regional
Development Fund, the Mobility Plus programme of the Ministry of Science and
Higher Education, the National Science Center (Poland), contracts Harmonia
2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and
2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities
Research Program by Qatar National Research Fund; the Programa Estatal de
Fomento de la Investigación Científica y Técnica de Excelencia María de
Maeztu, grant MDM-2015-0509 and the Programa Severo Ochoa del Principado de
Asturias; the Thalis and Aristeia programmes cofinanced by EU-ESF and the
Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship,
Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century
Project Advancement Project (Thailand); the Welch Foundation, contract C-1845;
and the Weston Havens Foundation (USA).

## References

  * [1] S. L. Glashow, “Partial symmetries of weak interactions”,  Nucl. Phys. 22 (1961) 579, 10.1016/0029-5582(61)90469-2.
  * [2] S. Weinberg, “A model of leptons”,  Phys. Rev. Lett. 19 (1967) 1264, 10.1103/PhysRevLett.19.1264.
  * [3] A. Salam, “Weak and electromagnetic interactions”, in  Elementary particle physics: relativistic groups and analyticity, N. Svartholm, ed., p. 367.  Almqvist & Wiksell, Stockholm, 1968.  Proceedings of the eighth Nobel symposium.
  * [4] P. Ramond, “Dual theory for free fermions”,  Phys. Rev. D 3 (1971) 2415, 10.1103/PhysRevD.3.2415.
  * [5] Y. A. Gol’fand and E. P. Likhtman, “Extension of the algebra of Poincaré group generators and violation of P invariance”, JETP Lett. 13 (1971) 323\.
  * [6] A. Neveu and J. H. Schwarz, “Factorizable dual model of pions”,  Nucl. Phys. B 31 (1971) 86, 10.1016/0550-3213(71)90448-2.
  * [7] D. V. Volkov and V. P. Akulov, “Possible universal neutrino interaction”, JETP Lett. 16 (1972) 438\.
  * [8] J. Wess and B. Zumino, “A Lagrangian model invariant under supergauge transformations”,  Phys. Lett. B 49 (1974) 52, 10.1016/0370-2693(74)90578-4.
  * [9] J. Wess and B. Zumino, “Supergauge transformations in four dimensions”,  Nucl. Phys. B 70 (1974) 39, 10.1016/0550-3213(74)90355-1.
  * [10] P. Fayet, “Supergauge invariant extension of the Higgs mechanism and a model for the electron and its neutrino”,  Nucl. Phys. B 90 (1975) 104, 10.1016/0550-3213(75)90636-7.
  * [11] H. P. Nilles, “Supersymmetry, supergravity and particle physics”,  Phys. Rep. 110 (1984) 1, 10.1016/0370-1573(84)90008-5.
  * [12] G. R. Farrar and P. Fayet, “Phenomenology of the production, decay, and detection of new hadronic states associated with supersymmetry”,  Phys. Lett. B 76 (1978) 575, 10.1016/0370-2693(78)90858-4.
  * [13] N. Arkani-Hamed, S. Dimopoulos, and G. R. Dvali, “The hierarchy problem and new dimensions at a millimeter”,  Phys. Lett. B 429 (1998) 263, 10.1016/S0370-2693(98)00466-3, arXiv:hep-ph/9803315.
  * [14] I. Antoniadis, N. Arkani-Hamed, S. Dimopoulos, and G. R. Dvali, “New dimensions at a millimeter to a fermi and superstrings at a TeV”,  Phys. Lett. B 436 (1998) 257, 10.1016/S0370-2693(98)00860-0, arXiv:hep-ph/9804398.
  * [15] N. Arkani-Hamed, S. Dimopoulos, and G. R. Dvali, “Phenomenology, astrophysics and cosmology of theories with submillimeter dimensions and TeV scale quantum gravity”,  Phys. Rev. D 59 (1999) 086004, 10.1103/PhysRevD.59.086004, arXiv:hep-ph/9807344.
  * [16] L. Randall and R. Sundrum, “A large mass hierarchy from a small extra dimension”,  Phys. Rev. Lett. 83 (1999) 3370, 10.1103/PhysRevLett.83.3370, arXiv:hep-ph/9905221.
  * [17] L. Randall and R. Sundrum, “An alternative to compactification”,  Phys. Rev. Lett. 83 (1999) 4690, 10.1103/PhysRevLett.83.4690, arXiv:hep-th/9906064.
  * [18] ATLAS Collaboration, “Observation of a new particle in the search for the standard model Higgs boson with the ATLAS detector at the LHC”,  Phys. Lett. B 716 (2012) 1, 10.1016/j.physletb.2012.08.020, arXiv:1207.7214.
  * [19] CMS Collaboration, “Observation of a new boson at a mass of 125 GeV with the CMS experiment at the LHC”,  Phys. Lett. B 716 (2012) 30, 10.1016/j.physletb.2012.08.021, arXiv:1207.7235.
  * [20] CMS Collaboration, “Observation of a new boson with mass near 125 GeV in pp collisions at $\sqrt{s}=7$ and 8 TeV”,  JHEP 06 (2013) 081, 10.1007/JHEP06(2013)081, arXiv:1303.4571.
  * [21] ATLAS and CMS Collaboration, “Combined measurement of the Higgs boson mass in $pp$ collisions at $\sqrt{s}=7$ and 8 TeV with the ATLAS and CMS experiments”,  Phys. Rev. Lett. 114 (2015) 191803, 10.1103/PhysRevLett.114.191803, arXiv:1503.07589.
  * [22] CMS Collaboration, “Measurements of properties of the Higgs boson decaying into the four-lepton final state in pp collisions at $\sqrt{s}=13$ TeV”,  JHEP 11 (2017) 047, 10.1007/JHEP11(2017)047, arXiv:1706.09936.
  * [23] R. Barbieri and G. F. Giudice, “Upper bounds on supersymmetric particle masses”,  Nucl. Phys. B 306 (1988) 63, 10.1016/0550-3213(88)90171-X.
  * [24] S. Dimopoulos and L. Susskind, “Mass without scalars”,  Nucl. Phys. B 155 (1979) 237, 10.1016/0550-3213(79)90364-X.
  * [25] S. Dimopoulos and G. L. Landsberg, “Black holes at the LHC”,  Phys. Rev. Lett. 87 (2001) 161602, 10.1103/PhysRevLett.87.161602, arXiv:hep-ph/0106295.
  * [26] S. B. Giddings and S. D. Thomas, “High energy colliders as black hole factories: the end of short distance physics”,  Phys. Rev. D 65 (2002) 056010, 10.1103/PhysRevD.65.056010, arXiv:hep-ph/0106219.
  * [27] S. W. Hawking, “Particle creation by black holes”,  Commun. Math. Phys. 43 (1975) 199, 10.1007/BF02345020. [Erratum: 10.1007/BF01608497].
  * [28] X. Calmet, W. Gong, and S. D. H. Hsu, “Colorful quantum black holes at the LHC”,  Phys. Lett. B 668 (2008) 20, 10.1016/j.physletb.2008.08.011, arXiv:0806.4605.
  * [29] D. M. Gingrich, “Quantum black holes with charge, color and spin at the LHC”,  J. Phys. G 37 (2010) 105008, 10.1088/0954-3899/37/10/105008, arXiv:0912.0826.
  * [30] D. M. Gingrich, “Monte Carlo event generator for black hole production and decay in proton–proton collisions – QBH version 1.02”,  Comput. Phys. Commun. 181 (2010) 1917, 10.1016/j.cpc.2010.07.027, arXiv:0911.5370.
  * [31] S. Dimopoulos and R. Emparan, “String balls at the LHC and beyond”,  Phys. Lett. B 526 (2002) 393, 10.1016/S0370-2693(01)01525-8, arXiv:hep-ph/0108060.
  * [32] R. Hagedorn, “Statistical thermodynamics of strong interactions at high-energies”,  Nuovo Cim. Suppl. 3 (1965) 147\.
  * [33] G. Landsberg, “Black holes at the Large Hadron Collider”,  Fundam. Theor. Phys. 178 (2015) 267, 10.1007/978-3-319-10852-0_9.
  * [34] ATLAS Collaboration, “Search for strong gravity in multijet final states produced in pp collisions at $\sqrt{s}=13$ TeV using the ATLAS detector at the LHC”,  JHEP 03 (2016) 026, 10.1007/JHEP03(2016)026, arXiv:1512.02586.
  * [35] ATLAS Collaboration, “Search for TeV-scale gravity signatures in high-mass final states with leptons and jets with the ATLAS detector at $\sqrt{s}=13$ TeV”,  Phys. Lett. B 760 (2016) 520, 10.1016/j.physletb.2016.07.030, arXiv:1606.02265.
  * [36] CMS Collaboration, “Search for black holes in high-multiplicity final states in proton-proton collisions at $\sqrt{s}=13$ TeV”,  Phys. Lett. B 774 (2017) 279, 10.1016/j.physletb.2017.09.053, arXiv:1705.01403.
  * [37] ATLAS Collaboration, “Search for new phenomena in dijet mass and angular distributions from $pp$ collisions at $\sqrt{s}=$ 13 TeV with the ATLAS detector”,  Phys. Lett. B 754 (2016) 302, 10.1016/j.physletb.2016.01.032, arXiv:1512.01530.
  * [38] ATLAS Collaboration, “Search for new phenomena with photon+jet events in proton-proton collisions at $\sqrt{s}=13$ TeV with the ATLAS detector”,  JHEP 03 (2016) 041, 10.1007/JHEP03(2016)041, arXiv:1512.05910.
  * [39] CMS Collaboration, “Search for new physics with dijet angular distributions in proton-proton collisions at $\sqrt{s}=13$ TeV”,  JHEP 07 (2017) 013, 10.1007/JHEP07(2017)013, arXiv:1703.09986.
  * [40] ATLAS Collaboration, “Search for new phenomena in dijet events using 37 fb-1 of $pp$ collision data collected at $\sqrt{s}=$13 TeV with the ATLAS detector”,  Phys. Rev. D 96 (2017) 052004, 10.1103/PhysRevD.96.052004, arXiv:1703.09127.
  * [41] ATLAS Collaboration, “Search for new phenomena in high-mass final states with a photon and a jet from $pp$ collisions at $\sqrt{s}=13$ TeV with the ATLAS detector”,  Eur. Phys. J. C 78 (2018) 102, 10.1140/epjc/s10052-018-5553-2, arXiv:1709.10440.
  * [42] CMS Collaboration, “Search for lepton-flavor violating decays of heavy resonances and quantum black holes to e$\mu$ final states in proton-proton collisions at $\sqrt{s}=13$ TeV”,  JHEP 04 (2018) 073, 10.1007/JHEP04(2018)073, arXiv:1802.01122.
  * [43] G. ’t Hooft, “Symmetry breaking through Bell-Jackiw anomalies”,  Phys. Rev. Lett. 37 (1976) 8, 10.1103/PhysRevLett.37.8.
  * [44] F. R. Klinkhamer and N. S. Manton, “A saddle-point solution in the Weinberg-Salam theory”,  Phys. Rev. D 30 (1984) 2212, 10.1103/PhysRevD.30.2212.
  * [45] M. Trodden, “Electroweak baryogenesis”,  Rev. Mod. Phys. 71 (1999) 1463, 10.1103/RevModPhys.71.1463.
  * [46] A. Ringwald, “High-energy breakdown of perturbation theory in the electroweak instanton sector”,  Nucl. Phys. B 330 (1990) 1, 10.1016/0550-3213(90)90300-3.
  * [47] S.-S. Chern and J. Simons, “Characteristic forms and geometric invariants”,  Annals Math. 99 (1974) 48, 10.2307/1971013.
  * [48] S. H. H. Tye and S. S. C. Wong, “Bloch wave function for the periodic sphaleron potential and unsuppressed baryon and lepton number violating processes”,  Phys. Rev. D 92 (2015) 045005, 10.1103/PhysRevD.92.045005, arXiv:1505.03690.
  * [49] J. Ellis and K. Sakurai, “Search for sphalerons in proton-proton collisions”,  JHEP 04 (2016) 086, 10.1007/JHEP04(2016)086, arXiv:1601.03654.
  * [50] C. Bravo and J. Hauser, “BaryoGEN, a Monte Carlo generator for sphaleron-induced transitions in proton-proton collisions”, (2018). arXiv:1805.02786. Submitted to JHEP.
  * [51] E. W. Kolb and M. S. Turner, “The Early Universe”.  Addison Wesley, 1990.  Frontiers in Physics (69). ISBN 978-0201626742,
  * [52] CMS Collaboration, “The CMS trigger system”,  JINST 12 (2017) P01020, 10.1088/1748-0221/12/01/P01020, arXiv:1609.02366.
  * [53] CMS Collaboration, “The CMS experiment at the CERN LHC”,  JINST 3 (2008) S08004, 10.1088/1748-0221/3/08/S08004.
  * [54] CMS Collaboration, “Particle-flow reconstruction and global event description with the CMS detector”,  JINST 12 (2017) P10003, 10.1088/1748-0221/12/10/P10003, arXiv:1706.04965.
  * [55] M. Cacciari, G. P. Salam, and G. Soyez, “The anti-jet clustering algorithm”,  JHEP 04 (2008) 063, 10.1088/1126-6708/2008/04/063, arXiv:0802.1189.
  * [56] M. Cacciari, G. P. Salam, and G. Soyez, “FastJet user manual”,  Eur. Phys. J. C 72 (2012) 1896, 10.1140/epjc/s10052-012-1896-2, arXiv:1111.6097.
  * [57] CMS Collaboration, “Jet energy scale and resolution in the CMS experiment in pp collisions at 8 TeV”,  JINST 12 (2017) P02014, 10.1088/1748-0221/12/02/P02014, arXiv:1607.03663.
  * [58] CMS Collaboration, “Performance of the CMS muon detector and muon reconstruction with proton-proton collisions at $\sqrt{s}=13$ TeV”,  JINST 13 (2018) P06015, 10.1088/1748-0221/13/06/P06015, arXiv:1804.04528.
  * [59] CMS Collaboration, “Jet algorithms performance in 13 TeV data”, Technical Report CMS-PAS-JME-16-003, CERN, 2017.
  * [60] CMS Collaboration, “Performance of electron reconstruction and selection with the CMS detector in proton-proton collisions at $\sqrt{s}=8$ TeV”,  JINST 10 (2015) P06005, 10.1088/1748-0221/10/06/P06005, arXiv:1502.02701.
  * [61] CMS Collaboration, “Performance of photon reconstruction and identification with the CMS detector in proton-proton collisions at $\sqrt{s}=8$ TeV”,  JINST 10 (2015) P08010, 10.1088/1748-0221/10/08/P08010, arXiv:1502.02702.
  * [62] M. Cacciari and G. P. Salam, “Pileup subtraction using jet areas”,  Phys. Lett. B 659 (2008) 119, 10.1016/j.physletb.2007.09.077, arXiv:0707.1378.
  * [63] CMS Collaboration, “Search for microscopic black hole signatures at the Large Hadron Collider”,  Phys. Lett. B 697 (2011) 434, 10.1016/j.physletb.2011.02.032, arXiv:1012.3375.
  * [64] CMS Collaboration, “Search for microscopic black holes in $pp$ collisions at $\sqrt{s}=7$ TeV”,  JHEP 04 (2012) 061, 10.1007/JHEP04(2012)061, arXiv:1202.6396.
  * [65] CMS Collaboration, “Search for microscopic black holes in pp collisions at $\sqrt{s}=8$ TeV”,  JHEP 07 (2013) 178, 10.1007/JHEP07(2013)178, arXiv:1303.5338.
  * [66] ATLAS Collaboration, “Search for TeV-scale gravity signatures in final states with leptons and jets with the ATLAS detector at $\sqrt{s}=7$ TeV”,  Phys. Lett. B 716 (2013) 122, 10.1016/j.physletb.2012.08.009, arXiv:1204.4646.
  * [67] ATLAS Collaboration, “Search for microscopic black holes and string balls in final states with leptons and jets with the ATLAS detector at $\sqrt{s}=8$ TeV”,  JHEP 08 (2014) 103, 10.1007/JHEP08(2014)103, arXiv:1405.4254.
  * [68] CMS Collaboration, “Search for stealth supersymmetry in events with jets, either photons or leptons, and low missing transverse momentum in pp collisions at 8 TeV”,  Phys. Lett. B 743 (2015) 503, 10.1016/j.physletb.2015.03.017, arXiv:1411.7255.
  * [69] CMS Collaboration, “Search for new physics in events with high jet multiplicity and low missing transverse momentum in proton-proton collisions at $\sqrt{s}=8$ TeV”,  Phys. Lett. B 770 (2017) 257, 10.1016/j.physletb.2017.01.073, arXiv:1608.01224.
  * [70] D.-C. Dai et al., “BlackMax: a black-hole event generator with rotation, recoil, split branes, and brane tension”,  Phys. Rev. D 77 (2008) 076007, 10.1103/PhysRevD.77.076007, arXiv:0711.3012.
  * [71] C. M. Harris, P. Richardson, and B. R. Webber, “CHARYBDIS: a black hole event generator”,  JHEP 08 (2003) 033, 10.1088/1126-6708/2003/08/033, arXiv:hep-ph/0307305.
  * [72] J. A. Frost et al., “Phenomenology of production and decay of spinning extra- dimensional black holes at hadron colliders”,  JHEP 10 (2009) 014, 10.1088/1126-6708/2009/10/014, arXiv:0904.0979.
  * [73] H. Yoshino and V. S. Rychkov, “Improved analysis of black hole formation in high-energy particle collisions”,  Phys. Rev. D 71 (2005) 104028, 10.1103/PhysRevD.71.104028, arXiv:hep-th/0503171. [Erratum: 10.1103/PhysRevD.77.089905].
  * [74] A. D. Martin, W. J. Stirling, R. S. Thorne, and G. Watt, “Parton distributions for the LHC”,  Eur. Phys. J. C 63 (2009) 189, 10.1140/epjc/s10052-009-1072-5, arXiv:0901.0002.
  * [75] A. D. Martin, W. J. Stirling, R. S. Thorne, and G. Watt, “Heavy-quark mass dependence in global PDF analyses and 3- and 4-flavour parton distributions”,  Eur. Phys. J. C 70 (2010) 51, 10.1140/epjc/s10052-010-1462-8, arXiv:1007.2624.
  * [76] NNPDF Collaboration, “Parton distributions with LHC data”,  Nucl. Phys. B 867 (2013) 244, 10.1016/j.nuclphysb.2012.10.003, arXiv:1207.1303.
  * [77] H.-L. Lai et al., “New parton distributions for collider physics”,  Phys. Rev. D 82 (2010) 074024, 10.1103/PhysRevD.82.074024, arXiv:1007.2241.
  * [78] J. Alwall et al., “The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations”,  JHEP 07 (2014) 079, 10.1007/JHEP07(2014)079, arXiv:1405.0301.
  * [79] T. Sjöstrand et al., “An introduction to PYTHIA 8.2”,  Comput. Phys. Commun. 191 (2015) 159, 10.1016/j.cpc.2015.01.024, arXiv:1410.3012.
  * [80] CMS Collaboration, “Event generator tunes obtained from underlying event and multiparton scattering measurements”,  Eur. Phys. J. C 76 (2016) 155, 10.1140/epjc/s10052-016-3988-x, arXiv:1512.00815.
  * [81] GEANT4 Collaboration, “—a simulation toolkit”,  Nucl. Instrum. Meth. A 506 (2003) 250, 10.1016/S0168-9002(03)01368-8.
  * [82] R. A. Fisher, “On the interpretation of $\chi^{2}$ from contingency tables, and the calculation of $p$”,  J. Roy. Stat. Soc. 85 (1922) 87, 10.2307/2340521.
  * [83] S. Alekhin et al., “The PDF4LHC working group interim report”, (2011). arXiv:1101.0536.
  * [84] M. Botje et al., “The PDF4LHC working group interim recommendations”, (2011). arXiv:1101.0538.
  * [85] CTEQ Collaboration, “Implications of CTEQ global analysis for collider observables”,  Phys. Rev. D 78 (2008) 013004, 10.1103/PhysRevD.78.013004, arXiv:0802.0007.
  * [86] CMS Collaboration, “CMS luminosity measurements for the 2016 data taking period”, CMS Physics Analysis Summary CMS-PAS-LUM-17-001, CERN, 2017.
  * [87] T. Junk, “Confidence level computation for combining searches with small statistics”,  Nucl. Instrum. Meth. A 434 (1999) 435, 10.1016/S0168-9002(99)00498-2, arXiv:hep-ex/9902006.
  * [88] A. L. Read, “Presentation of search results: the CLs technique”,  J. Phys. G 28 (2002) 2693, 10.1088/0954-3899/28/10/313.
  * [89] ATLAS and CMS Collaborations, “Procedure for the LHC Higgs boson search combination in Summer 2011”, ATL-PHYS-PUB-2011-011, CMS NOTE-2011/005, 2011.
  * [90] G. Cowan, K. Cranmer, E. Gross, and O. Vitells, “Asymptotic formulae for likelihood-based tests of new physics”,  Eur. Phys. J. C 71 (2011) 1554, 10.1140/epjc/s10052-011-1554-0, arXiv:1007.1727. [Erratum: 10.1140/epjc/s10052-013-2501-z].

##  .10 The CMS Collaboration

Yerevan Physics Institute, Yerevan, Armenia
A.M. Sirunyan, A. Tumasyan Institut für Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, M. Dragicevic,
J. Erö, A. Escalante Del Valle, M. Flechl, R. Frühwirth1, V.M. Ghete, J.
Hrubec, M. Jeitler1, N. Krammer, I. Krätschmer, D. Liko, T. Madlener, I.
Mikulec, N. Rad, H. Rohringer, J. Schieck1, R. Schöfbeck, M. Spanring, D.
Spitzbart, A. Taurok, W. Waltenberger, J. Wittmann, C.-E. Wulz1, M. Zarucki
Institute for Nuclear Problems, Minsk, Belarus
V. Chekhovsky, V. Mossolov, J. Suarez Gonzalez Universiteit Antwerpen,
Antwerpen, Belgium
E.A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, M. Pieters, M. Van De
Klundert, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel Vrije
Universiteit Brussel, Brussel, Belgium
S. Abu Zeid, F. Blekman, J. D’Hondt, I. De Bruyn, J. De Clercq, K. Deroover,
G. Flouris, D. Lontkovskyi, S. Lowette, I. Marchesini, S. Moortgat, L.
Moreels, Q. Python, K. Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders,
I. Van Parijs Université Libre de Bruxelles, Bruxelles, Belgium
D. Beghin, B. Bilin, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, B.
Dorney, G. Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk, A.K. Kalsi, T.
Lenzi, J. Luetic, N. Postiau, E. Starling, L. Thomas, C. Vander Velde, P.
Vanlaer, D. Vannerom, Q. Wang Ghent University, Ghent, Belgium
T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov2, D. Poyraz, C. Roskas,
D. Trocino, M. Tytgat, W. Verbeke, B. Vermassen, M. Vit, N. Zaganidis
Université Catholique de Louvain, Louvain-la-Neuve, Belgium
H. Bakhshiansohi, O. Bondu, S. Brochet, G. Bruno, C. Caputo, P. David, C.
Delaere, M. Delcourt, B. Francois, A. Giammanco, G. Krintiras, V. Lemaitre, A.
Magitteri, A. Mertens, M. Musich, K. Piotrzkowski, A. Saggio, M. Vidal Marono,
S. Wertz, J. Zobec Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro,
Brazil
F.L. Alves, G.A. Alves, L. Brito, 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, D. Romero Abadb
Institute for Nuclear Research and Nuclear Energy, Bulgarian Academy of
Sciences, Sofia, Bulgaria
A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, A. Marinov, M. Misheva, M. Rodozov,
M. Shopova, G. Sultanov University of Sofia, Sofia, Bulgaria
A. Dimitrov, L. Litov, B. Pavlov, P. Petkov Beihang University, Beijing, China
W. Fang5, X. Gao5, L. Yuan Institute of High Energy Physics, Beijing, China
M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D.
Leggat, H. Liao, Z. Liu, F. Romeo, S.M. Shaheen6, A. Spiezia, J. Tao, C. Wang,
Z. Wang, E. Yazgan, H. Zhang, J. Zhao State Key Laboratory of Nuclear Physics
and Technology, Peking University, Beijing, China
Y. Ban, G. Chen, A. Levin, J. Li, L. Li, Q. Li, Y. Mao, S.J. Qian, D. Wang, Z.
Xu Tsinghua University, Beijing, China
Y. Wang Universidad de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, C.A. Carrillo Montoya, L.F. Chaparro Sierra, C. Florez,
C.F. González Hernández, M.A. Segura Delgado University of Split, Faculty of
Electrical Engineering, Mechanical Engineering and Naval Architecture, Split,
Croatia
B. Courbon, N. Godinovic, D. Lelas, I. Puljak, T. Sculac University of Split,
Faculty of Science, Split, Croatia
Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia
V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, A. 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, S. Lisniak, A. Lobanov, J. Martin
Blanco, M. Nguyen, C. Ochando, G. Ortona, P. Pigard, R. Salerno, J.B. Sauvan,
Y. Sirois, A.G. Stahl Leiton, A. Zabi, A. Zghiche Université de Strasbourg,
CNRS, IPHC UMR 7178, F-67000 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, M. Vander
Donckt, S. Viret, S. Zhang 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, T. Esch, R. Fischer, S. Ghosh,
A. Güth, T. Hebbeker, C. Heidemann, K. Hoepfner, H. Keller, S. Knutzen, L.
Mastrolorenzo, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, T. Pook, M.
Radziej, H. Reithler, M. Rieger, F. Scheuch, A. Schmidt, D. Teyssier RWTH
Aachen University, III. Physikalisches Institut B, Aachen, Germany
G. Flügge, O. Hlushchenko, B. Kargoll, T. Kress, A. Künsken, T. Müller, A.
Nehrkorn, A. Nowack, C. Pistone, O. Pooth, H. Sert, A. 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, N. Stefaniuk, 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, D. Nowatschin, A. Perieanu, A. Reimers,
O. Rieger, C. Scharf, P. Schleper, S. Schumann, J. Schwandt, J. Sonneveld, H.
Stadie, G. Steinbrück, F.M. Stober, M. Stöver, D. Troendle, A. Vanhoefer, B.
Vormwald Institut für Experimentelle Teilchenphysik, Karlsruhe, Germany
M. Akbiyik, C. Barth, M. Baselga, S. Baur, E. Butz, R. Caspart, T. Chwalek, F.
Colombo, W. De Boer, A. Dierlamm, N. Faltermann, B. Freund, 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, 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, A. Kaur, M. Kaur, S. Kaur, R. Kumar, P. Kumari, M. Lohan, A.
Mehta, K. Sandeep, S. Sharma, J.B. Singh, G. Walia University of Delhi, Delhi,
India
A. Bhardwaj, B.C. Choudhary, R.B. Garg, M. Gola, S. Keshri, Ashok Kumar, S.
Malhotra, M. Naimuddin, P. Priyanka, K. Ranjan, Aashaq Shah, R. Sharma Saha
Institute of Nuclear Physics, HBNI, Kolkata, India
R. 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, 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
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, D. Biselloa,b, A. Bolettia,b, A. Bragagnolo, M.
Dall’Ossoa,b, P. De Castro Manzanoa, T. Dorigoa, U. Dossellia, F.
Gasparinia,b, U. Gasparinia,b, A. Gozzelinoa, S. Lacapraraa, P. Lujan, M.
Margonia,b, A.T. Meneguzzoa,b, F. Montecassianoa, J. Pazzinia,b, N.
Pozzobona,b, P. Ronchesea,b, R. Rossina,b, F. Simonettoa,b, A. Tiko, E.
Torassaa, M. Zanettia,b, P. Zottoa,b, G. Zumerlea,b INFN Sezione di Pavia a,
Università di Pavia b, Pavia, Italy
A. Braghieria, A. Magnania, P. Montagnaa,b, S.P. Rattia,b, V. Rea, M.
Ressegottia,b, C. Riccardia,b, P. Salvinia, I. Vaia,b, P. Vituloa,b INFN
Sezione di Perugia a, Università di Perugia b, Perugia, Italy
L. Alunni Solestizia,b, M. Biasinia,b, G.M. Bileia, C. Cecchia,b, D.
Ciangottinia,b, L. Fanòa,b, P. Laricciaa,b, R. Leonardia,b, E. Manonia, G.
Mantovania,b, V. Mariania,b, M. Menichellia, A. Rossia,b, A. Santocchiaa,b, D.
Spigaa INFN Sezione di Pisa a, Università di Pisa b, Scuola Normale Superiore
di Pisa c, Pisa, Italy
K. Androsova, P. Azzurria, G. Bagliesia, L. Bianchinia, T. Boccalia, L.
Borrello, R. Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, G. Fedia, F. Fioria,c,
L. Gianninia,c, A. Giassia, M.T. Grippoa, F. Ligabuea,c, E. Mancaa,c, G.
Mandorlia,c, A. Messineoa,b, F. Pallaa, A. Rizzia,b, P. Spagnoloa, R.
Tenchinia, G. Tonellia,b, A. Venturia, P.G. Verdinia INFN Sezione di Roma a,
Sapienza Università di Roma b, Rome, Italy
L. Baronea,b, F. Cavallaria, M. Cipriania,b, N. Dacia, D. Del Rea,b, E. Di
Marcoa,b, M. Diemoza, S. Gellia,b, E. Longoa,b, B. Marzocchia,b, P.
Meridiania, G. Organtinia,b, F. Pandolfia, R. Paramattia,b, F. Preiatoa,b, S.
Rahatloua,b, C. Rovellia, F. Santanastasioa,b INFN Sezione di Torino a,
Università di Torino b, Torino, Italy, Università del Piemonte Orientale c,
Novara, Italy
N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, N. Bartosika,
R. Bellana,b, C. Biinoa, N. Cartigliaa, F. Cennaa,b, S. Cometti, M. Costaa,b,
R. Covarellia,b, N. Demariaa, B. Kiania,b, C. Mariottia, S. Masellia, E.
Migliorea,b, V. Monacoa,b, E. Monteila,b, M. Montenoa, M.M. Obertinoa,b, L.
Pachera,b, N. Pastronea, M. Pelliccionia, G.L. Pinna Angionia,b, A. Romeroa,b,
M. Ruspaa,c, R. Sacchia,b, K. Shchelinaa,b, V. Solaa, A. Solanoa,b, D. Soldi,
A. Staianoa INFN Sezione di Trieste a, Università di Trieste b, Trieste, Italy
S. Belfortea, V. Candelisea,b, M. Casarsaa, F. Cossuttia, G. Della Riccaa,b,
F. Vazzolera,b, A. Zanettia Kyungpook National University
D.H. Kim, G.N. Kim, M.S. Kim, J. Lee, S. Lee, S.W. Lee, C.S. Moon, Y.D. Oh, S.
Sekmen, D.C. Son, Y.C. Yang Chonnam National University, Institute for
Universe and Elementary Particles, Kwangju, Korea
H. Kim, D.H. Moon, G. Oh Hanyang University, Seoul, Korea
J. 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
A. Castaneda Hernandez, J.A. Murillo Quijada Centro de Investigacion y de
Estudios Avanzados del IPN, Mexico City, Mexico
M.C. Duran-Osuna, H. Castilla-Valdez, E. De La Cruz-Burelo, G. Ramirez-
Sanchez, I. Heredia-De La Cruz32, R.I. Rabadan-Trejo, R. Lopez-Fernandez, J.
Mejia Guisao, 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
P. Bargassa, C. Beirão Da Cruz E Silva, A. Di Francesco, P. Faccioli, B.
Galinhas, M. Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias, M.V.
Nemallapudi, J. Seixas, G. Strong, O. Toldaiev, D. Vadruccio, J. Varela Joint
Institute for Nuclear Research, Dubna, Russia
S. Afanasiev, V. Alexakhin, P. Bunin, M. Gavrilenko, A. Golunov, I. Golutvin,
N. Gorbounov, V. Karjavin, A. Lanev, A. Malakhov, V. Matveev34,35, P. Moisenz,
V. Palichik, V. Perelygin, M. Savina, S. Shmatov, 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
V. Blinov40, T. Dimova40, L. Kardapoltsev40, D. Shtol40, Y. Skovpen40 State
Research Center of Russian Federation, Institute for High Energy Physics of
NRC ’Kurchatov Institute’, Protvino, Russia
I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, A. Godizov, V. Kachanov,
A. Kalinin, D. Konstantinov, P. Mandrik, V. Petrov, R. Ryutin, S.
Slabospitskii, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov National
Research Tomsk Polytechnic University, Tomsk, Russia
A. Babaev, S. Baidali University of Belgrade, Faculty of Physics and Vinca
Institute of Nuclear Sciences, Belgrade, Serbia
P. 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 CERN, European
Organization for Nuclear Research, Geneva, Switzerland
D. Abbaneo, B. Akgun, E. Auffray, P. Baillon, A.H. Ball, D. Barney, J.
Bendavid, M. Bianco, A. Bocci, C. Botta, E. Brondolin, T. Camporesi, M.
Cepeda, G. Cerminara, E. Chapon, Y. Chen, G. Cucciati, D. d’Enterria, A.
Dabrowski, V. Daponte, A. David, A. De Roeck, N. Deelen, M. Dobson, T. du
Pree, M. Dünser, N. Dupont, A. Elliott-Peisert, P. Everaerts, F.
Fallavollita42, D. Fasanella, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, A.
Gilbert, K. Gill, F. Glege, M. Guilbaud, D. Gulhan, J. Hegeman, V. Innocente,
A. Jafari, P. Janot, O. 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. 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, 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, C. Heidegger, D. Hits, J. Hoss, T. Klijnsma, W.
Lustermann, R.A. Manzoni, M. Marionneau, M.T. Meinhard, F. Micheli, P.
Musella, F. Nessi-Tedaldi, J. Pata, F. Pauss, G. Perrin, L. Perrozzi, S.
Pigazzini, M. Quittnat, D. Ruini, D.A. Sanz Becerra, M. Schönenberger, L.
Shchutska, V.R. Tavolaro, K. Theofilatos, M.L. Vesterbacka Olsson, R. Wallny,
D.H. Zhu Universität Zürich, Zurich, Switzerland
T.K. Aarrestad, C. Amsler48, D. Brzhechko, M.F. Canelli, A. De Cosa, R. Del
Burgo, S. Donato, C. Galloni, T. Hreus, B. Kilminster, I. Neutelings, D.
Pinna, G. Rauco, P. Robmann, D. Salerno, K. Schweiger, C. Seitz, Y. Takahashi,
A. Zucchetta National Central University, Chung-Li, Taiwan
Y.H. Chang, K.y. Cheng, T.H. Doan, Sh. Jain, 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.y. Li, Y.F.
Liu, R.-S. Lu, E. Paganis, A. Psallidas, A. Steen, J.f. Tsai Chulalongkorn
University, Faculty of Science, Department of Physics, Bangkok, Thailand
B. Asavapibhop, 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, S. Ozturk53, D. Sunar Cerci49, B. Tali49, U.G. Tok, S.
Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University,
Physics Department, Ankara, Turkey
B. Isildak54, G. Karapinar55, M. Yalvac, M. Zeyrek Bogazici University,
Istanbul, Turkey
I.O. Atakisi, E. Gülmez, M. Kaya56, O. Kaya57, 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
G. Auzinger, R. Bainbridge, P. Bloch, J. Borg, S. Breeze, O. Buchmuller, A.
Bundock, S. Casasso, D. Colling, L. Corpe, P. Dauncey, G. Davies, M. Della
Negra, R. Di Maria, Y. Haddad, G. Hall, G. Iles, T. James, M. Komm, C. Laner,
L. Lyons, A.-M. Magnan, S. Malik, A. Martelli, J. 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.
Piperov, 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, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S.
Shalhout, M. Shi, D. Stolp, D. Taylor, K. Tos, M. Tripathi, Z. Wang, F. Zhang
University of California, Los Angeles, USA
M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M.
Ignatenko, N. Mccoll, S. Regnard, D. Saltzberg, C. Schnaible, V. Valuev
University of California, Riverside, Riverside, USA
E. Bouvier, K. Burt, R. Clare, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, G.
Karapostoli, E. Kennedy, F. Lacroix, O.R. Long, M. Olmedo Negrete, M.I.
Paneva, W. Si, L. Wang, H. Wei, S. Wimpenny, B.R. Yates University of
California, San Diego, La Jolla, USA
J.G. Branson, S. Cittolin, M. Derdzinski, R. Gerosa, D. Gilbert, B. Hashemi,
A. Holzner, D. Klein, G. Kole, V. Krutelyov, J. Letts, M. Masciovecchio, D.
Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A.
Vartak, S. 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, S. Leontsinis, E.
MacDonald, T. Mulholland, K. Stenson, K.A. Ulmer, S.R. Wagner Cornell
University, Ithaca, USA
J. Alexander, J. Chaves, Y. Cheng, J. Chu, A. Datta, K. Mcdermott, N. Mirman,
J.R. Patterson, D. Quach, A. Rinkevicius, A. Ryd, L. Skinnari, L. Soffi, S.M.
Tan, Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek Fermi National
Accelerator Laboratory, Batavia, USA
S. Abdullin, M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, A. Apyan, S.
Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, G.
Bolla${}^{\textrm{\textdagger}}$, K. Burkett, J.N. Butler, A. Canepa, G.B.
Cerati, H.W.K. Cheung, F. Chlebana, M. Cremonesi, J. Duarte, V.D. Elvira, J.
Freeman, Z. Gecse, E. Gottschalk, L. Gray, D. Green, S. Grünendahl, O.
Gutsche, J. Hanlon, R.M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, B.
Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, B. Klima, M.J. Kortelainen,
B. Kreis, S. Lammel, D. Lincoln, R. Lipton, M. Liu, T. Liu, J. Lykken, K.
Maeshima, J.M. Marraffino, D. Mason, P. McBride, P. Merkel, S. Mrenna, S.
Nahn, V. O’Dell, K. Pedro, C. Pena, O. Prokofyev, G. Rakness, L. Ristori, A.
Savoy-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, 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, 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, S. Nourbakhsh, N. Ruckstuhl, R. Rusack, J. Turkewitz, M.A.
Wadud University of Mississippi, Oxford, USA
J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA
E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, F. Golf, R. Gonzalez Suarez,
R. Kamalieddin, I. Kravchenko, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger
State University of New York at Buffalo, Buffalo, USA
A. Godshalk, C. Harrington, I. Iashvili, A. Kharchilava, D. Nguyen, A. Parker,
S. Rappoccio, B. Roozbahani Northeastern University, Boston, USA
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, P. Hebda, S. Higginbotham, A.
Kalogeropoulos, D. Lange, M.T. Lucchini, J. Luo, D. Marlow, K. Mei, I. Ojalvo,
J. Olsen, C. Palmer, P. Piroué, J. Salfeld-Nebgen, D. Stickland, C. Tully
University of Puerto Rico, Mayaguez, USA
S. Malik, S. Norberg Purdue University, West Lafayette, USA
A. Barker, V.E. Barnes, S. Das, L. Gutay, M. Jones, A.W. Jung, A. Khatiwada,
B. Mahakud, D.H. Miller, N. Neumeister, C.C. Peng, H. Qiu, J.F. Schulte, J.
Sun, F. Wang, R. Xiao, W. Xie Purdue University Northwest, Hammond, USA
T. Cheng, J. Dolen, N. Parashar Rice University, Houston, USA
Z. Chen, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Kilpatrick, W. Li, B.
Michlin, B.P. Padley, J. Roberts, J. Rorie, W. Shi, Z. Tu, J. Zabel, A. Zhang
University of Rochester, Rochester, USA
A. Bodek, P. de Barbaro, R. Demina, Y.t. Duh, J.L. Dulemba, C. Fallon, T.
Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs, A.
Khukhunaishvili, K.H. Lo, P. Tan, R. Taus, M. Verzetti Rutgers, The State
University of New Jersey, Piscataway, USA
A. Agapitos, J.P. Chou, Y. Gershtein, T.A. Gómez Espinosa, E. Halkiadakis, M.
Heindl, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath,
R. Montalvo, K. Nash, M. Osherson, H. Saka, S. Salur, S. Schnetzer, D.
Sheffield, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker
University of Tennessee, Knoxville, USA
A.G. Delannoy, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa Texas A&M
University, College Station, USA
O. Bouhali71, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R.
Eusebi, J. Gilmore, T. Huang, T. Kamon72, S. Luo, R. Mueller, Y. Pakhotin, R.
Patel, A. Perloff, L. Perniè, D. Rathjens, A. Safonov, A. Tatarinov Texas Tech
University, Lubbock, USA
N. Akchurin, J. Damgov, F. De Guio, P.R. Dudero, S. Kunori, K. Lamichhane,
S.W. Lee, T. Mengke, S. Muthumuni, T. Peltola, S. Undleeb, I. Volobouev, Z.
Wang Vanderbilt University, Nashville, USA
S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K.
Padeken, J.D. Ruiz Alvarez, P. Sheldon, S. Tuo, J. Velkovska, M. Verweij, Q.
Xu University of Virginia, Charlottesville, USA
M.W. Arenton, P. Barria, B. Cox, G. Dezoort, R. Hirosky, H. Jiwon, 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,
A. Levine, K. Long, R. Loveless, T. Ruggles, A. Savin, N. Smith, W.H. Smith,
N. Woods †: Deceased
1: Also at Vienna University of Technology, Vienna, Austria
2: Also at IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
3: Also at Universidade Estadual de Campinas, Campinas, Brazil
4: Also at Federal University of Rio Grande do Sul, Porto Alegre, Brazil
5: Also at Université Libre de Bruxelles, Bruxelles, Belgium
6: Also at 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 Gaziosmanpasa University, Tokat, Turkey
54: Also at Ozyegin University, Istanbul, Turkey
55: Also at Izmir Institute of Technology, Izmir, Turkey
56: Also at Marmara University, Istanbul, Turkey
57: Also at Kafkas University, Kars, 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