EXO-19-002

EXO-19-002

[inst1]Maximilian Dieter Heindl

# Search for physics beyond the standard model in multilepton final states in
proton-proton collisions at $\sqrt{s}=13\TeV$

###### Abstract

A search for physics beyond the standard model in events with at least three
charged leptons (electrons or muons) is presented. The data sample corresponds
to an integrated luminosity of 137of proton-proton collisions at
$\sqrt{s}=13\TeV$, collected with the CMS detector at the LHC in 2016–2018.
The two targeted signal processes are pair production of type-III seesaw heavy
fermions and production of a light scalar or pseudoscalar boson in association
with a pair of top quarks. The heavy fermions may be manifested as an excess
of events with large values of leptonic transverse momenta or missing
transverse momentum. The light scalars or pseudoscalars may create a localized
excess in the dilepton mass spectra. The results exclude heavy fermions of the
type-III seesaw model for masses below 880at 95% confidence level in the
scenario of equal branching fractions to each lepton flavor. This is the most
restrictive limit on the flavor-democratic scenario of the type-III seesaw
model to date. Assuming a Yukawa coupling of unit strength to top quarks,
branching fractions of new scalar (pseudoscalar) bosons to dielectrons or
dimuons above 0.004 (0.03) and 0.04 (0.03) are excluded at 95% confidence
level for masses in the range 15–75 and 108–340, respectively. These are the
first limits in these channels on an extension of the standard model with
scalar or pseudoscalar particles.

##  0.1 Introduction

A search for new phenomena in final states with at least three charged leptons
(electrons or muons) is presented, using 137of proton-proton ($\Pp\Pp$)
collision data at $\sqrt{s}=13\TeV$ collected by the CMS experiment at the
CERN LHC from 2016 to 2018. The results are interpreted in the context of two
beyond the standard model (SM) theories, namely the type-III seesaw and light
scalar or pseudoscalar sector extensions to the SM. The event selection and
signal region definitions are chosen in a way that allows other models to be
tested. Phenomenologically, these models show complementary signatures of
resonant and nonresonant multilepton final states, as described below.

The seesaw mechanism introduces new heavy particles coupled to leptons and to
the Higgs boson, in order to explain the light masses of the neutrinos [1, 2,
3, 4, 5, 6, 7, 8, 9]. Within the type-III seesaw model, the neutrino is
assumed to be a Majorana particle whose mass arises via the mediation of new
massive fermions. These massive fermions are an SU(2) triplet of heavy Dirac
charged leptons ($\Sigma^{\pm}$) and a heavy Majorana neutral lepton
($\Sigma^{0}$). In $\Pp\Pp$ collisions, these massive fermions may be pair-
produced through electroweak interactions in both charged-charged and charged-
neutral pairs. Multilepton final states arise from the decays of each of the
$\Sigma^{+}\Sigma^{-}$, $\Sigma^{+}\Sigma^{0}$, and $\Sigma^{-}\Sigma^{0}$
pairs to the nine different pairs of $\PW$, $\PZ$, and Higgs bosons with SM
leptons and the subsequent leptonic decays of the SM bosons. A complete decay
chain example would be
$\Sigma^{\pm}\Sigma^{0}\to(W^{\pm}\nu)(W^{\pm}\ell^{\mp})\to(\ell^{\pm}\nu\nu)(\ell^{\pm}\nu\ell^{\mp})$,
where $\ell$ and $\nu$ are the three flavors of charged and neutral SM
leptons, respectively. All 27 distinct signal production and decay
combinations of the seesaw signal are simulated [10]. The $\Sigma^{\pm,0}$ are
degenerate in mass, their decays are prompt, and the $\Sigma$ decay branching
fractions are identical across all lepton flavors (flavor-democratic
scenario). This is achieved by taking the mixing angles to be
$V_{\Pe}=V_{\mu}=V_{\tau}=10^{-4}$, values that are compatible with the
existing constraints [11, 12, 13, 10, 14].

New light scalars or pseudoscalars are a ubiquitous feature of many theories
of physics beyond the SM, including, but not limited to, extended Higgs
sectors, supersymmetric theories, and dark sector extensions [15, 16, 17, 18].
We consider a generalization of a simple model [19, 20], where a new light CP-
even scalar or CP-odd pseudoscalar boson ($\phi$) is produced in $\Pp\Pp$
collisions via a Yukawa coupling of the $\phi$ to top quarks, $g_{\PQt}$,
either in three-body associated production with top quark pairs, or in top
quark pair production with three-body top quark decays,
${\PQt}\to\cPqb\PW\phi$. The signal is collectively labeled as $\ttbar\phi$.
In this paper, we search for decays of the $\phi$ boson via a Yukawa coupling
to the charged leptons, $g_{\ell}$, into dielectron or dimuon pairs within
multilepton events. The decays of the $\phi$ boson into tau-tau lepton pairs
are not considered. It is assumed that $g_{\ell}\ll g_{\PQt}$ and that all
other couplings of the $\phi$ boson are negligible. Furthermore, the $\phi$
boson decays are taken to be prompt, and the $\phi$ branching fractions into
different flavors of charged lepton pairs, $\mathcal{B}(\phi\to\ell\ell)$, as
well as $g_{\PQt}$, are left as free parameters.

Figure 1 illustrates example diagrams for the production and decay of heavy
fermions in the type-III seesaw model (left) and a light scalar or
pseudoscalar boson in the $\ttbar\phi$ model (right).

Prior searches for the manifestation of the type-III seesaw model have been
conducted by the ATLAS and CMS Collaborations using data recorded at
$\sqrt{s}=7$, 8, and 13 [21, 22, 23, 24]. The most stringent constraints in
the flavor-democratic scenario are from a CMS search using 13data collected in
2016, which excluded $\Sigma$ masses below 850 [24]. The present study of the
$\ttbar\phi$ model is the first direct search for a light scalar or
pseudoscalar boson in leptonic decays produced in association with a top quark
pair.

Figure 1:  Leading order Feynman diagrams for the type-III seesaw (left) and
$\ttbar\phi$ (right) signal models, depicting example production and decay
modes in $\Pp\Pp$ collisions.

##  0.2 The CMS detector

The central feature of the CMS apparatus is a superconducting solenoid of 6m
internal diameter, providing a magnetic field of 3.8T. Within the solenoid
volume are a silicon pixel and strip tracker, a lead tungstate crystal
electromagnetic calorimeter (ECAL), and a brass and scintillator hadron
calorimeter, 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. 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. [25].
The CMS detector uses a two-tiered trigger system [26]. The first level,
composed of custom hardware processors, uses information from the calorimeters
and muon detectors to select the most relevant pp collision events at rates up
to 100kHz. These are further processed by a second level consisting of a farm
of processors, known as the high level trigger, that combines information from
all CMS subdetectors to yield a final event rate of less than 1kHz for data
storage.

##  0.3 Data samples and event simulation

The data samples analyzed in this search correspond to a total integrated
luminosity of 137(35.9, 41.5, and 59.7in years 2016, 2017 and 2018,
respectively), recorded in $\Pp\Pp$ collisions at $\sqrt{s}=13\TeV$. A
combination of isolated single-electron and single-muon triggers was used with
corresponding transverse momentum () thresholds of 24 and 27in 2016, 27 and
32in 2017, and 24 and 32in 2018. Event samples from Monte Carlo (MC)
simulations are used to estimate the rates of signal and relevant SM
background processes. The $\PW\PZ$, $\PZ\gamma$, $\ttbar\PZ$, $\ttbar\PW$, and
triboson backgrounds are generated using (2.2.2 in 2016, 2.4.2 in 2017 and
2018 data analyses) [27] at next-to-leading order (NLO) precision. The top
quark mass used in all simulations is 172.5. The $\PZ\PZ$ background
contribution from quark-antiquark annihilation is generated using 2.0 [28, 29,
30] at NLO, whereas the contribution from gluon-gluon fusion is generated at
leading order (LO) using 7.0.1 [31]. Backgrounds from Higgs boson production
for a Higgs boson mass of 125are generated at NLO using and JHUGen 7.0.11 [32,
33, 34, 35]. Simulated event samples for Drell–Yan (DY) and $\ttbar$
processes, generated at NLO with and , respectively, are used for systematic
uncertainty studies.

All signal samples are simulated using 2.6.1 at LO precision. The production
cross section for the type-III seesaw signal model $\sigma(\Sigma\Sigma)$ is
calculated at NLO plus next-to-leading logarithmic precision, assuming that
the heavy leptons are SU(2) triplet fermions [36, 37], while the $\ttbar\phi$
production cross section $\sigma(\ttbar\phi)$ comes directly from the 2.6.1
generator at LO precision.

All background and signal samples in 2016 are generated with the NNPDF3.0 NLO
or LO parton distribution functions (PDFs), with the order matching that in
the matrix element calculations. In 2017 and 2018, the NNPDF3.1 next-to-next-
to-leading order PDFs [38, 39] are used. Parton showering, fragmentation, and
hadronization for all samples are performed using 8.230 [40] with the
underlying event tune CUETP8M1 [41] for the 2016 analysis, and CP5 [42] for
the 2017 and 2018 analyses. Double counted partons generated with and are
removed using the FxFx [43] matching schemes. The response of the CMS detector
is simulated using dedicated software based on the toolkit [44], and the
presence of multiple $\Pp\Pp$ interactions in the same or adjacent bunch
crossing (pileup) is incorporated by simulating additional interactions, that
are both in-time and out-of-time with the hard collision according to the
pileup in the data samples.

##  0.4 Event reconstruction

A particle-flow (PF) algorithm [45] 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. In each event, the candidate
vertex with the largest value of summed physics-object $\pt^{2}$ is taken to
be the primary $\Pp\Pp$ interaction vertex (PV). Here the physics objects are
the jets, clustered using the jet finding algorithm [46, 47] with the tracks
assigned to candidate vertices as inputs, and the associated missing
transverse momentum, taken as the negative vector sum of the of those jets.
The energy of photons is obtained from the ECAL measurement. The energy of
electrons is determined from a combination of the electron momentum at the PV
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.

Jets used in this analysis are reconstructed using the anti-algorithm [46]
with a distance parameter of 0.4, as implemented in the FastJet package [47].
Jets are required to have $\pt>30\GeV$ and, to be fully in the tracking system
volume, $\abs{\eta}<2.1$. Jet momentum is determined as the vectorial sum of
all particle momenta in the jet, and is found from simulation to be, on
average, within 5–10% of the true momentum over the whole spectrum and
detector acceptance. The effect of the pileup on reconstructed jets is
mitigated through a charged hadron subtraction technique, which removes the
energy of charged hadrons not originating from the PV [45]. The impact of
neutral pileup particles in jets is mitigated by an event-by-event jet-area-
based correction of the jet four-momenta [48, 49, 50].

Jet energy corrections are derived from simulation studies so that the average
measured response of jets becomes identical to that of particle level jets. In
situ measurements of the momentum balance in dijet, photon+jet, leptonically
decaying $\PZ$+jet, and multijet events are used to determine any residual
differences between the jet energy scale in data and in simulation, and
appropriate corrections are made to the jet [50]. Additional quality criteria
are applied to each jet to remove those potentially dominated by instrumental
effects or reconstruction failures [51]. Finally, all selected jets are
required to be outside a cone of $\Delta
R\equiv\sqrt{\smash[b]{(\Delta\eta)^{2}+(\Delta\phi)^{2}}}=0.4$ around a
selected electron or muon as defined below, where $\Delta\phi$ is the
azimuthal distance.

A subset of these reconstructed jets originating from $\Pb$ hadrons is
identified using the DeepCSV tagging algorithm [52]. This algorithm has an
efficiency of 60–75% to identify quark jets, depending on jet and $\eta$, and
a misidentification rate of about 10% for quark jets as well as 1% for light
quark and gluon jets.

The missing transverse momentum vector is computed as the negative vector sum
of the transverse momenta of all the PF candidates in an event, and its
magnitude is denoted as [53]. The is modified to account for corrections to
the energy scale of the reconstructed jets in the event.

Electrons and muons are reconstructed by geometrically matching tracks
reconstructed in the tracking system with energy clusters in the ECAL [54] and
with the tracks in the muon detectors [55], respectively. Electrons are
required to be within the tracking system acceptance, $\abs{\eta}<2.5$, and
muons are required to be within the muon system acceptance, $\abs{\eta}<2.4$.
Both electrons and muons must have $\pt>10\GeV$. Furthermore, electrons must
satisfy shower shape and track quality requirements to suppress those
originating from photon conversions in detector material as well as hadronic
activity misidentified as electrons. Similarly, muons must satisfy track fit
and matching quality requirements to suppress muon misidentification due to
hadron shower remnants that reach the muon system.

Prompt isolated leptons produced by SM boson decays (either directly, or via
an intermediate tau lepton) are indistinguishable from those produced in
signal events. Thus, SM processes that can produce three or more isolated
leptons, such as $\PW\PZ$, $\PZ\PZ$, $\ttbar\PZ$, $\ttbar\PW$, triboson, and
Higgs boson production, constitute the irreducible backgrounds. Reducible
backgrounds arise from SM processes, such as $\PZ$+jets or $\ttbar$+jets
production, accompanied by additional leptons originating from heavy quark
decays or from misidentification of jets. Such leptons arising not from boson
decays, but from leptons inside or near jets, hadrons that reach the muon
detectors, or hadronic showers with large electromagnetic energy fractions,
are referred to as misidentified leptons.

The reducible backgrounds are significantly suppressed by applying a set of
lepton isolation and displacement requirements in addition to the quality
criteria in the lepton identification [54, 55]. The relative isolation is
defined as the scalar sum, normalized to the lepton , of photon and hadron PF
objects within a cone of $\Delta R$ around the lepton. This relative isolation
is required to be in the range of 5–15% for $\Delta R=0.3$ for electrons,
scaling inversely with the electron , and to be less than 15% for $\Delta
R=0.4$ for muons. The isolation quantities are corrected for contributions
from particles originating from pileup vertices. In addition to the isolation
requirement, electrons must satisfy $\abs{d_{z}}<0.1$and $\abs{d_{xy}}<0.05$in
the ECAL barrel ($\abs{\eta}<1.479$), and $\abs{d_{z}}<0.2$and
$\abs{d_{xy}}<0.1$in the ECAL endcap ($\abs{\eta}>1.479$), where $d_{z}$ and
$d_{xy}$ are the longitudinal and transverse impact parameters of electrons
with respect to the primary vertex, respectively. Similarly, muons must
satisfy $\abs{d_{z}}<0.1$and $\abs{d_{xy}}<0.05$. All selected electrons
within a cone of $\Delta R<0.05$ of a selected muon are discarded, since these
are possibly due to bremsstrahlung from the muons.

In trilepton events, where misidentified-background contributions are
dominant, additional 3-dimensional impact parameter significance and tag veto
requirements are imposed on the leptons, removing those with significant
displacement with respect to the PV or whose matching jet is tagged. A PF jet
with $\pt>10\GeV$ and $\abs{\eta}<2.5$ is considered to be matched if it is
located within a cone of $\Delta R<0.4$ around the lepton without any further
quality criteria on the jet. These electron and muon reconstruction and
selection requirements result in typical efficiencies of 40–90 and 75–95%,
respectively, depending on the lepton and $\eta$ [54, 55].

##  0.5 Event selection

In both data and simulated event samples, events satisfying the trigger
criteria are required to pass additional offline selections. Each event is
required to have at least one electron with $\pt>35\GeV$ (30in 2016) or at
least one muon with $\pt>26\GeV$ (29in 2017) to be consistent with the trigger
thresholds, depending on the trigger used to collect the event. Throughout
this analysis, we consider events with exactly 3 leptons (3L) in one category
and four or more leptons (4L) in another category. In the 4L event category,
only the 4 leading-leptons are considered. All events containing a lepton pair
with $\Delta R<0.4$ or a same-flavor lepton pair with dilepton invariant mass
below 12are removed to reduce background contributions from low-mass
resonances as well as final-state radiation. The 3L events containing an
opposite-sign same-flavor (OSSF) lepton pair with the dilepton invariant mass
below 76, when the trilepton invariant mass is within a $\PZ$ boson mass
window ($91\pm 15\GeV$), are also rejected. This suppresses events from the
$\PZ\to\ell\ell^{*}\to\ell\ell\gamma$ background process, where the photon
converts into two additional leptons, one of which is lost. The event
selection criteria for both the type-III seesaw and $\ttbar\phi$ signal models
are orthogonal to those used in the estimation of SM backgrounds.

In the context of the type-III seesaw extension of the SM, pair production of
heavy fermions gives rise to events with multiple energetic charged leptons or
neutrinos in the final state. Given the relatively high momenta of bosons and
leptons originating from the decays of these heavy particles, kinematic
quantities, such as the scalar sum of all leptons, are instrumental in
suppressing SM contributions. This is especially valid for decay modes such as
$\Sigma^{\pm}\to\ell^{\pm}{\PZ}\to\ell^{\pm}\ell^{\pm}\ell^{\mp}$, where all
of the daughter particles of the heavy fermion can be reconstructed in the
detector. However, can be used as a complementary kinematic quantity in other
decay modes, such as $\Sigma^{0}\to\nu\PH\to\nu{\PW}^{\pm}{\PW}^{\mp}$ or
$\Sigma^{\pm}\to\nu\PW^{\pm}\to\nu\ell^{\pm}\nu$, where neutrinos can carry a
significant fraction of the outgoing momentum. We define $L_{\mathrm{T}}$ as
the scalar sum of all charged leptons, and the quantity $L_{\mathrm{T}}$+is
chosen as the primary kinematic discriminant to select this variety of decay
modes.

We classify the selected multilepton events into statistically independent
search channels using the multiplicity of leptons, $N_{\mathrm{leptons}}$, as
well as the multiplicity and mass of distinct OSSF pairs, $N_{\mathrm{OSSF}}$
and $M_{\mathrm{OSSF}}$, respectively. In cases of ambiguity,
$M_{\mathrm{OSSF}}$ is calculated using the OSSF pair with the mass closest to
that of the $\PZ$ boson, considering both electrons and muons. The 3L events
with an OSSF lepton pair are labeled as OSSF1, whereas those without are
labeled as OSSF0. The OSSF1 events are further classified as on-$\PZ$,
below-$\PZ$, and above-$\PZ$, based on the $M_{\mathrm{OSSF}}$ relative to the
$\pm 15\GeV$ window around the $\PZ$ boson mass, where the latter two
categories are also collectively labeled as off-$\PZ$. Similarly, the 4L
events are classified as those with zero, one, and two distinct OSSF lepton
pairs, OSSF0, OSSF1, and OSSF2, respectively.

In the 3L on-$\PZ$ search region, the sensitivity is increased by considering
the transverse mass discriminant
$M_{\mathrm{T}}=\sqrt{\smash[b]{2\ptmiss\pt^{\ell}[1-\cos(\Delta\phi_{\ptvecmiss,\ptvec^{\ell}})]}}$
instead of $L_{\mathrm{T}}$+, where $\ell$ refers to the lepton that is not
part of the on-$\PZ$ pair. We reject 3L on-$\PZ$ events with
$\ptmiss<100\GeV$, and 4L OSSF2 events with $\ptmiss<100\GeV$ and two distinct
OSSF lepton pairs on-$\PZ$, as these are used in the estimation of SM
backgrounds.

This event selection and binning scheme yields a total of 40 statistically
independent search bins for the type-III seesaw model, as summarized in Table
0.5.

Multilepton signal region definitions for the type-III seesaw signal model.
All events containing a same-flavor lepton pair with invariant mass below
12are removed in the 3L and 4L event categories. Furthermore, 3L events
containing an OSSF lepton pair with mass below 76when the trilepton mass is
within a $\PZ$ boson mass window ($91\pm 15\GeV$) are also rejected. The last
$L_{\mathrm{T}}$+or $M_{\mathrm{T}}$ bin in each signal region contains the
overflow events.  Label $N_{\mathrm{leptons}}$ $N_{\mathrm{OSSF}}$
$M_{\mathrm{OSSF}}$ () () Variable and range () Number of bins 3L below-$\PZ$
3 1 $<$76 — $L_{\mathrm{T}}$+ $[0,1200]$ 6 3L on-$\PZ$ 3 1 76–106 $>$100
$M_{\mathrm{T}}$ $[0,700]$ 7 3L above-$\PZ$ 3 1 $>$106 — $L_{\mathrm{T}}$+
$[0,1600]$ 8 3L OSSF0 3 0 — — $L_{\mathrm{T}}$+ $[0,1200]$ 6 4L OSSF0 $\geq$4
0 — — $L_{\mathrm{T}}$+ $[0,600]$ 2 4L OSSF1 $\geq$4 1 — — $L_{\mathrm{T}}$+
$[0,1000]$ 5 4L OSSF2 $\geq$4 2 — $>$100 if both $L_{\mathrm{T}}$+ $[0,1200]$
6 pairs are on-$\PZ$

In contrast, the $\ttbar\phi$ model yields events with a resonant OSSF lepton
pair originating from the $\phi$ decays produced in association with a
$\ttbar$ pair. We consider only 3L or 4L events with at least one OSSF lepton
pair and exclude those with $M_{\mathrm{OSSF}}$ on-$\PZ$. This event selection
requires semileptonic or dileptonic $\ttbar$ decays in the $\ttbar\phi$
signal. Unlike the type-III seesaw heavy fermions, relatively light scalar or
pseudoscalar decays do not necessarily produce energetic charged leptons, but
can yield striking resonant dilepton signatures in events with high hadronic
activity and tagged jets. Therefore, we seek events with resonances in the
OSSF dilepton mass spectra in various $S_{\mathrm{T}}$ bins, where
$S_{\mathrm{T}}$ is defined as the scalar sum of all jets, all charged leptons
($L_{\mathrm{T}}$) and .

We probe the $\ttbar\phi$ signal in light and heavy $\phi$ mass ranges, namely
15–75 and 108–340. Signal masses below 15and in the range of 75–108are not
considered because of background from low-mass quarkonia and $\PZ$ boson
resonances, respectively. Masses above 340are not considered as the
$\phi\to\ttbar$ decay channel becomes kinematically accessible here.

To account for the effects of radiation and resolution on the invariant mass
reconstruction, we consider the 12–77(low) and 106–356(high) reconstructed
dilepton mass ranges for the light and heavy signal mass scenarios,
respectively, in both 3L and 4L channels. Because there can be an ambiguity
caused by additional leptons originating from the $\ttbar$ system, the
reconstruction of the correct $\phi$ mass is not always possible. Therefore,
we define the $M_{\mathrm{OSSF}}^{20}$ and the $M_{\mathrm{OSSF}}^{300}$
variables as the OSSF lepton pair masses of a given lepton flavor closest to
the targeted mass of 20 and 300, respectively. The $M_{\mathrm{OSSF}}^{20}$
variable is used for the low dilepton mass range, while the
$M_{\mathrm{OSSF}}^{300}$ variable is used for the high dilepton mass range.
Events with a value of $M_{\mathrm{OSSF}}^{20}$ ($M_{\mathrm{OSSF}}^{300}$)
outside the low (high) dilepton mass ranges are not considered. The analysis
is insensitive to the choice of the targeted mass value, and this simplified
scheme allows multiple $\ttbar\phi$ signal scenarios to be probed with a
single mass spectrum.

The $M_{\mathrm{OSSF}}^{20}$ and $M_{\mathrm{OSSF}}^{300}$ masses are
calculated separately for each lepton flavor scenario, yielding two
nonorthogonal categories labeled as 3/4L($\Pe\Pe$) and 3/4L($\mu\mu$). Hence,
a given event can qualify for both the low and high dilepton mass regions, as
well as for both lepton flavor channels. For example, a
$\mu^{\pm}\mu^{\pm}\mu^{\mp}$ event could be present in both low and high
dilepton mass regions in the 3L($\mu\mu$) category, and similarly, an
$\Pe^{\pm}\Pe^{\mp}$$\mu^{\pm}\mu^{\mp}$ event could qualify for both the
4L($\Pe\Pe$) and 4L($\mu\mu$) categories. However, for any one given
$\ttbar\phi$ signal mass and flavor scenario, only one of the dilepton mass
ranges of a single flavor category is considered.

Events that satisfy the low or high dilepton mass ranges are considered in
orthogonal $N_{\cPqb}=0$ (0B) and $N_{\cPqb}\geq 1$ (1B) selections, where
$N_{\cPqb}$ is the multiplicity of tagged jets in an event. Events in the 3L
signal channels are further split into 3 $S_{\mathrm{T}}$ bins (0–400,
400–800, and $\geq$800) for both $N_{\cPqb}$ selections, those in the 4L
signal channels are split into 2 $S_{\mathrm{T}}$ (0–400and $\geq$400) bins
for the 0B selection, and only one inclusive bin in $S_{\mathrm{T}}$ is used
for the 1B selection.

This event selection and binning scheme results in a total of 70 (68)
statistically independent low (high) dilepton mass search bins in each of the
3/4L($\Pe\Pe$) and 3/4L($\mu\mu$) channels for the $\ttbar\phi$ signal model,
as summarized in Table 0.5. The signal mass hypotheses that are closer to the
mass bin boundaries than to the bin centers are probed with a modified binning
scheme, where the mass bin boundaries are shifted by half the value of the bin
widths.

Multilepton signal region definitions for the $\ttbar\phi$ signal model. All
events containing a same-flavor lepton pair with invariant mass below 12are
removed in the 3L and 4L event categories. Furthermore, 3L events containing
an OSSF lepton pair with mass below 76when the trilepton mass is within a
$\PZ$ boson mass window ($91\pm 15\GeV$) are also rejected.  Label
$N_{\mathrm{leptons}}$ $N_{\mathrm{OSSF}}$ $M_{\mathrm{OSSF}}$ $N_{\cPqb}$
Variable and range () Number of bins $S_{\mathrm{T}}$ () 0–400 400–800 $>$800
3L(${\Pe\Pe}/\mu\mu$) 0B 3 1 off-$\PZ$ 0 $M_{\mathrm{OSSF}}^{20}$ $[12,77]$ 13
13 5 $M_{\mathrm{OSSF}}^{300}$ $[106,356]$ 10 10 10 3L(${\Pe\Pe}/\mu\mu$) 1B 3
1 off-$\PZ$ $\geq$1 $M_{\mathrm{OSSF}}^{20}$ $[12,77]$ 13 13 5
$M_{\mathrm{OSSF}}^{300}$ $[106,356]$ 10 10 10 $S_{\mathrm{T}}$ () 0–400
$>$400 4L(${\Pe\Pe}/\mu\mu$) 0B $\geq$4 $\geq$1 off-$\PZ$ 0
$M_{\mathrm{OSSF}}^{20}$ $[12,77]$ 3 2 $M_{\mathrm{OSSF}}^{300}$ $[106,356]$ 3
2 $S_{\mathrm{T}}$ inclusive 4L(${\Pe\Pe}/\mu\mu$) 1B $\geq$4 $\geq$1
off-$\PZ$ $\geq$1 $M_{\mathrm{OSSF}}^{20}$ $[12,77]$ 3
$M_{\mathrm{OSSF}}^{300}$ $[106,356]$ 3

##  0.6 Background estimation and systematic uncertainties

The irreducible backgrounds are estimated using simulated event samples and
are dominated by the $\PW\PZ$, $\PZ\PZ$, $\ttbar\PZ$, and $\PZ\gamma$
processes. The event yields of these processes are obtained from theoretical
predictions, with normalization corrections derived in dedicated control
regions as described below. These estimates for the $\PW\PZ$, $\PZ\PZ$ and
$\PZ\gamma$ processes are largely independent of each other. Since these
backgrounds make significant contributions to the $\ttbar\PZ$-enriched control
region, the normalization correction for this process is measured after the
corresponding corrections have been obtained for the other backgrounds. The
normalization correction factors and their associated uncertainties, which
include both statistical and systematic contributions, take the contamination
of events from other processes into account and are applied to the
corresponding background estimates in the signal regions.

Figure 2: The $M_{\mathrm{T}}$ distribution in the $\PW\PZ$-enriched control
region (upper left), the $L_{\mathrm{T}}$ distribution in the
$\ttbar\PZ$-enriched control region (upper right), the $S_{\mathrm{T}}$
distribution in the $\PZ\PZ$-enriched control region (lower left), and the
$L_{\mathrm{T}}$ distribution in the misidentified-lepton ($\PZ$+jets)
enriched control region (lower right). The lower panels show the ratio of
observed to expected events. The hatched gray bands in the upper panels and
the light gray bands in the lower panels represent the total (systematic and
statistical) uncertainty of the backgrounds in each bin, whereas the dark gray
bands in the lower panels represent only the statistical uncertainty of the
backgrounds. The rightmost bins contain the overflow events in each
distribution.

For the $\PW\PZ$ and $\ttbar\PZ$ processes, we select events with exactly
three leptons with an on-$\PZ$ OSSF pair, and the minimum lepton is required
to be above 20to increase the purity of these selections in the targeted
process. For the $\PW\PZ$-enriched selection, we require $50<\ptmiss<100\GeV$
and zero tagged jets, whereas for the $\ttbar\PZ$-enriched selection we
require $\ptmiss<100\GeV$, $S_{\mathrm{T}}>350\GeV$, and at least one tagged
jet. Similarly, for $\PZ\PZ$, we select events with exactly four leptons,
$\ptmiss<100\GeV$, and two distinct on-$\PZ$ OSSF lepton pairs. In the
$\PW\PZ$\- and $\PZ\PZ$-enriched selections, the simulated event yields are
normalized to match those in the data in the 0–3 and 0–2 jet multiplicity bins
including overflows, respectively, yielding normalization factor uncertainties
in the range of 5–25%, whereas an inclusive normalization is performed in the
$\ttbar\PZ$-enriched selection, resulting in a $20\%$ uncertainty. The various
kinematic distributions in the $\PW\PZ$-, $\PZ\PZ$-, and $\ttbar\PZ$-enriched
control regions, where the normalizations of these major irreducible
backgrounds are performed, are illustrated in Fig. 2 (top-left, top-right,
bottom-left).

Similarly, a $\PZ\gamma$-enriched selection is created in three-lepton events
with an OSSF lepton pair with mass below 76and trilepton mass within the $\PZ$
boson mass window, $91\pm 15\GeV$. This selection is dominated by $\PZ$+jets
events with internal and external photon conversions originating from final-
state radiation, and the normalization yields a relative uncertainty of
$20\%$. Conversion contributions from non-$\PZ\gamma$ processes play a
subdominant role, and are estimated using simulated event samples.

Other irreducible backgrounds, such as $\ttbar\PW$, triboson, and Higgs boson
processes, are estimated via simulation as well, using the cross sections
obtained from the MC generation at NLO or higher accuracy, and are
collectively referred to as ‘rare’ backgrounds. All rare and non-$\PZ\gamma$
conversion backgrounds, which are not normalized to data in dedicated control
regions, are assigned a relative normalization uncertainty of $50\%$.

A small fraction of the irreducible backgrounds are due to misidentification
of the charge of one or more prompt electrons. These backgrounds are also
estimated using simulated event samples. Following a study of same-sign
dielectron events, in which the dielectron invariant mass is within a $\PZ$
boson mass window ($91\pm 15\GeV$), a relative uncertainty of $50\%$ is
assigned to such contributions. These constitute less than 35% of the
irreducible $\PW\PZ$, $\PZ\PZ$, and $\ttbar\PZ$ background contributions in
the 3L OSSF0, 4L OSSF1, and 4L OSSF0 signal regions, and are negligible in all
other signal regions.

A category of systematic uncertainties in the simulated events is due to the
corrections applied to background and signal simulation samples to account for
differences with respect to data events. These corrections are used in lepton
reconstruction, identification, isolation, and trigger efficiencies, tagging
efficiencies, pileup modeling, as well as electron and muon resolution, and
electron, muon, jet, and unclustered energy scale measurements. The
uncertainties due to such corrections typically correspond to a 1–10%
variation of the simulation-based irreducible background and signal yields
across all signal regions. Therefore, they form a sub-dominant category of
systematic uncertainties in the simulation-based background estimation.
Similarly, uncertainties due to choices of factorization and renormalization
scales [56] and PDFs [39] are also evaluated for signal and dominant
irreducible background processes, yielding $<$10% variation in signal regions.
The uncertainties in the integrated luminosity are in the range of 2.3–2.5% in
each year of data collection [57, 58, 59].

The reducible backgrounds are due to misidentified leptons (MisID) arising
from events such as $\PZ$+jets and $\ttbar$+jets. These are estimated using a
three-dimensional implementation of a matrix method [60], in which the rates
at which prompt and misidentified leptons satisfying a loose lepton selection
also pass a tight lepton selection are measured in dedicated signal-depleted
selections of events in data. The misidentification rates are measured in
$\PZ$+jets and $\ttbar$+jets enriched trilepton (on-$\PZ$, $\ptmiss<50\GeV$)
and same-sign dilepton (off-$\PZ$, $\ptmiss>50\GeV$, and with at least 3 jets)
selections, respectively, whereas an on-$\PZ$ dilepton selection is used for
the prompt rates. The rates are parametrized as a function of lepton kinematic
distributions and the multiplicity of tracks in the event. A weighted average
of these misidentification rates is used in the analysis, reflecting the
approximate expected composition of the SM backgrounds in a given search
region as obtained from simulated event samples. The final uncertainty in the
estimated background from misidentified leptons is obtained by varying the
rates within the uncertainties as well as the differences in rates in
$\PZ$+jets and $\ttbar$+jets events, and has a relative uncertainty of 30–40%.
Figure 2 (lower right) illustrates the misidentified-lepton background
estimate as a function of $L_{\mathrm{T}}$ in the trilepton selection used to
measure the rates, where a misidentified lepton is produced in association
with a $\PZ$ boson.

A summary of the uncertainty sources in this analysis, including the typical
resultant variations on relevant background and signal processes, as well as
the correlation model across the three different data taking periods, is given
in Table 0.6. The quoted variations on affected processes, except those in the
integrated luminosity, and the inclusive normalizations of the $\ttbar\PZ$,
conversion and rare simulations, are calculated taking into account variations
of the uncertainty sources as a function of object and event dependent
parameters as appropriate, such as lepton momenta, or jet multiplicity. Thus,
these uncertainties also include bin-to-bin correlations across the search
regions. The overall uncertainties in the total expected backgrounds are
largely dominated by those in the irreducible $\PW\PZ$, $\PZ\PZ$, and
$\ttbar\PZ$ processes, as well as the misidentified-lepton contributions,
whereas the relatively large uncertainties in rare and conversion
contributions and those due to electron charge misidentification are
subdominant and have a negligible effect on the results across different
signal regions.

Sources of systematic uncertainties, affected background and signal processes,
relative variations of the affected processes, and presence or otherwise of
correlation between years in signal regions.  Uncertainty source
Signal/Background process Variation (%) Correlation Integrated Luminosity
Signal/Rare/Non-$\PZ\gamma$ conversion 2.3–2.5 No Lepton reconstruction,
identification, Signal/Background⋆ 4–5 No and isolation efficiency Lepton
displacement efficiency (only in 3L) Signal/Background⋆ 3–5 Yes Trigger
efficiency Signal/Background⋆ $<$3 No tagging efficiency Signal/Background⋆
$<$5 No Pileup modeling Signal/Background⋆ $<$3 Yes
Factorization/renormalization scales $\&$ PDF Signal/Background⋆ $<$10 Yes Jet
energy scale Signal/Background⋆ $<$5 Yes Unclustered energy scale
Signal/Background⋆ $<$5 Yes Muon energy scale and resolution
Signal/Background⋆ $<$5 Yes Electron energy scale and resolution
Signal/Background⋆ $<$2 Yes $\PW\PZ$ normalization (0/1/2/$\geq$3 jets)
$\PW\PZ$ 5–10 Yes $\PZ\PZ$ normalization (0/1/$\geq$2 jets) $\PZ\PZ$ 5–10 Yes
$\ttbar\PZ$ normalization $\ttbar\PZ$ 15–20 Yes Conversion normalization
Conversion 20–50 Yes Rare normalization Rare 50 Yes Lepton misidentification
rates Misidentified lepton 30–40 Yes Electron charge misidentification
$\PW\PZ$/$\PZ\PZ$† $<$20 No ${}^{\star}\PW\PZ,~{}\PZ\PZ,~{}\ttbar\PZ$, rare,
and conversion background processes. †Only in 3L OSSF0, 4L OSSF0, and 4L OSSF1
signal regions.

##  0.7 Results

The distributions of expected SM backgrounds and observed event yields in the
signal regions as defined in Tables 0.5 and 0.5 are given in Figs. 3–4 and
5–10 for the type-III seesaw model and the $\ttbar\phi$ model, respectively.
The figures also show the predicted yields for type-III seesaw models with
$\Sigma$ masses of 300 and 700in the flavor-democratic scenario as well as for
$\ttbar\phi$ models with a pseudoscalar (scalar) $\phi$ mass of 20 and 125 (70
and 300)assuming $g_{\PQt}^{2}\mathcal{B}(\phi\to{\Pe\Pe}/\mu\mu)=0.05$.

We perform a goodness-of-fit test based on the saturated model method [61] to
quantify the local deviations between the background-only hypothesis and the
observed data, without considering the look-elsewhere effect [62]. The most
significant local deviation from the SM expectation in the signal regions is
found in the 3L($\mu\mu$) 1B $S_{\mathrm{T}}<400\GeV$ high mass $\ttbar\phi$
channel (Fig. 9) by selecting the bins with $M_{\mathrm{OSSF}}^{300}>206\GeV$,
resulting in a data excess of approximately 3.2 standard deviations.
Similarly, by examining other deviations from the SM, we observe a local data
deficit of 2.5 standard deviations in the $10<M_{\mathrm{OSSF}}^{20}<15\GeV$
bin of the 3L($\Pe\Pe$) 0B $400<S_{\mathrm{T}}<800\GeV$ channel (Fig. 5), and
a local data excess of 2.5 standard deviations in the
$60<M_{\mathrm{OSSF}}^{20}<65\GeV$ bin of the 3L($\mu\mu$) 1B
$400<S_{\mathrm{T}}<800\GeV$ channel (Fig. 9). Other deviations are less
significant. Overall, the observations are found to be globally consistent
with the SM predictions within 2.7 standard deviations, and no statistically
significant excess compatible with the signal models probed is observed.

Figure 3:  Type-III seesaw signal regions in 3L below-$\PZ$ (upper left),
on-$\PZ$ (upper right), above-$\PZ$ (lower left), and OSSF0 (lower right)
events. The total SM background is shown as a stacked histogram of all
contributing processes. The predictions for type-III seesaw models with
$\Sigma$ masses of 300 and 700in the flavor-democratic scenario are also
shown. The lower panels show the ratio of observed to expected events. The
hatched gray bands in the upper panels and the light gray bands in the lower
panels represent the total (systematic and statistical) uncertainty of the
backgrounds in each bin, whereas the dark gray bands in the lower panels
represent only the statistical uncertainty of the backgrounds. The rightmost
bins contain the overflow events in each distribution.

Figure 4:  Type-III seesaw signal regions in 4L OSSF0 (upper left), OSSF1
(upper right), and OSSF2 (lower) events. The total SM background is shown as a
stacked histogram of all contributing processes. The predictions for type-III
seesaw models with $\Sigma$ masses of 300 and 700in the flavor-democratic
scenario are also shown. The lower panels show the ratio of observed to
expected events. The hatched gray bands in the upper panels and the light gray
bands in the lower panels represent the total (systematic and statistical)
uncertainty of the backgrounds in each bin, whereas the dark gray bands in the
lower panels represent only the statistical uncertainty of the backgrounds.
The rightmost bins contain the overflow events in each distribution.

Figure 5:  Dielectron $M_{\mathrm{OSSF}}^{20}$ (left column) and
$M_{\mathrm{OSSF}}^{300}$ (right column) distributions in the 3L($\Pe\Pe$) 0B
$\ttbar\phi$ signal regions. Upper, center, and lower plots are for
$S_{\mathrm{T}}<400\GeV$, $400<S_{\mathrm{T}}<800\GeV$, and
$S_{\mathrm{T}}>800\GeV$, respectively. The total SM background is shown as a
stacked histogram of all contributing processes. The predictions for
$\ttbar\phi(\to{\Pe\Pe}$) models with a pseudoscalar (scalar) $\phi$ of 20 and
125 (70 and 300)mass assuming $g_{\PQt}^{2}\mathcal{B}(\phi\to\Pe\Pe)=0.05$
are also shown. The lower panels show the ratio of observed to expected
events. The hatched gray bands in the upper panels and the light gray bands in
the lower panels represent the total (systematic and statistical) uncertainty
of the backgrounds in each bin, whereas the dark gray bands in the lower
panels represent only the statistical uncertainty of the backgrounds. The
rightmost bins do not contain the overflow events as these are outside the
probed mass ranges.

Figure 6:  Dielectron $M_{\mathrm{OSSF}}^{20}$ (left column) and
$M_{\mathrm{OSSF}}^{300}$ (right column) distributions in the 3L($\Pe\Pe$) 1B
$\ttbar\phi$ signal regions. Upper, center, and lower plots are for
$S_{\mathrm{T}}<400\GeV$, $400<S_{\mathrm{T}}<800\GeV$, and
$S_{\mathrm{T}}>800\GeV$, respectively. The total SM background is shown as a
stacked histogram of all contributing processes. The predictions for
$\ttbar\phi(\to{\Pe\Pe}$) models with a pseudoscalar (scalar) $\phi$ of 20 and
125 (70 and 300)mass assuming $g_{\PQt}^{2}\mathcal{B}(\phi\to\Pe\Pe)=0.05$
are also shown. The lower panels show the ratio of observed to expected
events. The hatched gray bands in the upper panels and the light gray bands in
the lower panels represent the total (systematic and statistical) uncertainty
of the backgrounds in each bin, whereas the dark gray bands in the lower
panels represent only the statistical uncertainty of the backgrounds. The
rightmost bins do not contain the overflow events as these are outside the
probed mass ranges.

Figure 7:  Dielectron $M_{\mathrm{OSSF}}^{20}$ (left column) and
$M_{\mathrm{OSSF}}^{300}$ (right column) distributions in the 4L($\Pe\Pe$)
$\ttbar\phi$ signal regions. Upper, center, and lower plots are for 0B
$S_{\mathrm{T}}<400\GeV$, 0B $S_{\mathrm{T}}>400\GeV$, and 1B
$S_{\mathrm{T}}$-inclusive, respectively. The total SM background is shown as
a stacked histogram of all contributing processes. The predictions for
$\ttbar\phi(\to{\Pe\Pe}$) models with a pseudoscalar (scalar) $\phi$ of 20 and
125 (70 and 300)mass assuming $g_{\PQt}^{2}\mathcal{B}(\phi\to\Pe\Pe)=0.05$
are also shown. The lower panels show the ratio of observed to expected
events. The hatched gray bands in the upper panels and the light gray bands in
the lower panels represent the total (systematic and statistical) uncertainty
of the backgrounds in each bin, whereas the dark gray bands in the lower
panels represent only the statistical uncertainty of the backgrounds. The
rightmost bins do not contain the overflow events as these are outside the
probed mass range.

Figure 8:  Dimuon $M_{\mathrm{OSSF}}^{20}$ (left column) and
$M_{\mathrm{OSSF}}^{300}$ (right column) distributions in the 3L($\mu\mu$) 0B
$\ttbar\phi$ signal regions. Upper, center, and lower plots are for
$S_{\mathrm{T}}<400\GeV$, $400<S_{\mathrm{T}}<800\GeV$, and
$S_{\mathrm{T}}>800\GeV$, respectively. The total SM background is shown as a
stacked histogram of all contributing processes. The predictions for
$\ttbar\phi(\to\mu\mu$) models with a pseudoscalar (scalar) $\phi$ of 20 and
125 (70 and 300)mass assuming $g_{\PQt}^{2}\mathcal{B}(\phi\to\mu\mu)=0.05$
are also shown. The lower panels show the ratio of observed to expected
events. The hatched gray bands in the upper panels and the light gray bands in
the lower panels represent the total (systematic and statistical) uncertainty
of the backgrounds in each bin, whereas the dark gray bands in the lower
panels represent only the statistical uncertainty of the backgrounds. The
rightmost bins do not contain the overflow events as these are outside the
probed mass range.

Figure 9:  Dimuon $M_{\mathrm{OSSF}}^{20}$ (left column) and
$M_{\mathrm{OSSF}}^{300}$ (right column) distributions in the 3L($\mu\mu$) 1B
$\ttbar\phi$ signal regions. Upper, center, and lower plots are for
$S_{\mathrm{T}}<400\GeV$, $400<S_{\mathrm{T}}<800\GeV$, and
$S_{\mathrm{T}}>800\GeV$, respectively. The total SM background is shown as a
stacked histogram of all contributing processes. The predictions for
$\ttbar\phi(\to\mu\mu$) models with a pseudoscalar (scalar) $\phi$ of 20 and
125 (70 and 300)mass assuming $g_{\PQt}^{2}\mathcal{B}(\phi\to\mu\mu)=0.05$
are also shown. The lower panels show the ratio of observed to expected
events. The hatched gray bands in the upper panels and the light gray bands in
the lower panels represent the total (systematic and statistical) uncertainty
of the backgrounds in each bin, whereas the dark gray bands in the lower
panels represent only the statistical uncertainty of the backgrounds. The
rightmost bins do not contain the overflow events as these are outside the
probed mass range.

Figure 10:  Dimuon $M_{\mathrm{OSSF}}^{20}$ (left column) and
$M_{\mathrm{OSSF}}^{300}$ (right column) distributions in the 4L($\mu\mu$)
$\ttbar\phi$ signal regions. Upper, center, and lower plots are for 0B
$S_{\mathrm{T}}<400\GeV$, 0B $S_{\mathrm{T}}>400\GeV$, and 1B
$S_{\mathrm{T}}$-inclusive, respectively. The total SM background is shown as
a stacked histogram of all contributing processes. The predictions for
$\ttbar\phi(\to\mu\mu$) models with a pseudoscalar (scalar) $\phi$ of 20 and
125 (70 and 300)mass assuming $g_{\PQt}^{2}\mathcal{B}(\phi\to\mu\mu)=0.05$
are also shown. The lower panels show the ratio of observed to expected
events. The hatched gray bands in the upper panels and the light gray bands in
the lower panels represent the total (systematic and statistical) uncertainty
of the backgrounds in each bin, whereas the dark gray bands in the lower
panels represent only the statistical uncertainty of the backgrounds. The
rightmost bins do not contain the overflow events as these are outside the
probed mass range.

Upper limits at 95% confidence level () are set on the product of the signal
production cross sections and branching fractions using a modified frequentist
approach with the criterion [63, 64] and the asymptotic approximation for the
test statistic [65, 66]. Upper limits at 95% are also set on the product of
the branching fractions and the square of the scalar or pseudoscalar Yukawa
coupling in the $\ttbar\phi$ model. A binned maximum-likelihood fit is
performed to discriminate between the potential signal and the SM background
processes for both signal models separately. All of the $L_{\mathrm{T}}$+and
$M_{\mathrm{T}}$ bins are used for the seesaw signal masses under
consideration, whereas the appropriate subset of the lepton flavor and
dilepton mass bins is used for a given $\phi$ mass and branching fraction
scenario in the $\ttbar\phi$ signal model, such that the low (high) dielectron
and dimuon mass spectra are considered for a light (heavy) $\ttbar\phi$ signal
with the $\phi\to{\Pe\Pe}$ and $\phi\to\mu\mu$ decays, respectively.

The uncertainties in the mean values of both the expected signal and
background yields are treated as nuisance parameters modeled by log-normal and
gamma distributions for systematic and statistical uncertainties,
respectively. Statistical uncertainties in the signal and background yields in
each bin and year are assumed to be fully uncorrelated, whereas all systematic
uncertainties are assumed to be fully correlated among the signal bins in a
given year. The correlation model of all nuisance parameters across the
datasets collected in different years is summarized in Table 0.6.

Figure 11:  The 95% confidence level expected and observed upper limits on the
total production cross section of heavy fermion pairs. The inner (green) and
the outer (yellow) bands indicate the regions containing 68 and 95%,
respectively, of the distribution of limits expected under the background-only
hypothesis. Also shown are the theoretical prediction for the cross section
and the associated uncertainty of the $\Sigma$ pair production via the type-
III seesaw mechanism. Type-III seesaw heavy fermions are excluded for masses
below 880(expected limit 930) in the flavor-democratic scenario.

Figure 12:  The 95% confidence level expected and observed upper limits on the
product of the signal production cross section and branching fraction of a
scalar $\phi$ boson in the dielectron (upper left) and dimuon (lower left)
channels, and of a pseudoscalar $\phi$ boson in the dielectron (upper right)
and dimuon (lower right) channels, where $\phi$ is produced in association
with a top quark pair. The inner (green) and the outer (yellow) bands indicate
the regions containing 68 and 95%, respectively, of the distribution of limits
expected under the background-only hypothesis. The vertical hatched gray band
indicates the mass region corresponding to the $\PZ$ boson veto. Also shown
are the theoretical predictions for the product of the production cross
section and branching fraction of the $\ttbar\phi$ model, with their
uncertainties, and assuming
${g}_{t}^{2}\mathcal{B}(\phi\to{\Pe\Pe}/\mu\mu)=0.05$. All $\ttbar\phi$ signal
scenarios are excluded for the product of the production cross section and
branching fraction above 1–20fb for $\phi$ masses in the range of 15–75, and
above 0.3–5fb for $\phi$ masses in the range of 108–340.

Figure 13:  The 95% confidence level expected and observed upper limits on the
product of the square of the Yukawa coupling to top quarks and branching
fraction of a scalar $\phi$ boson in the dielectron (upper left) and dimuon
(lower left) channels, and of a pseudoscalar $\phi$ boson in the dielectron
(upper right) and dimuon (lower right) channels, where $\phi$ is produced in
association with a top quark pair. The inner (green) and the outer (yellow)
bands indicate the regions containing 68 and 95%, respectively, of the
distribution of limits expected under the background-only hypothesis. The
vertical hatched gray band indicates the mass region corresponding to the
$\PZ$ boson veto. The dashed horizontal line marks the unity value of the
product of the square of the Yukawa coupling to top quarks and the branching
fraction. Assuming a Yukawa coupling of unit strength to top quarks, the
branching fraction of new scalar (pseudoscalar) bosons to dielectrons or
dimuons above 0.0004–0.004 (0.004–0.03) are excluded for masses in the range
of 15–75, and above 0.004–0.04 (0.006–0.03) for masses in the range of
108–340.

The observed and expected upper limits on the production cross section
$\sigma(\Sigma\Sigma)$ in the type-III seesaw signal model are given in Fig.
11. Type-III seesaw heavy fermions are excluded at 95% with masses below
880assuming the flavor-democratic scenario. Similarly, the upper limits on
$\sigma($$\ttbar\phi$$)\mathcal{B}(\phi\to{\Pe\Pe}/\mu\mu)$ and
$g_{\PQt}^{2}\mathcal{B}(\phi\to{\Pe\Pe}/\mu\mu)$ in the $\ttbar\phi$ signal
model are shown in Figs. 12 and 13, respectively. In the $\ttbar\phi$ signal
model, we exclude cross sections above 1–20fb for $\phi$ masses in the range
of 15–75, and above 0.3–5fb for $\phi$ masses in the range of 108–340.
Furthermore, $g_{\PQt}^{2}\mathcal{B}(\phi\to{\Pe\Pe}/\mu\mu)$ above
(0.4–4)$\ten{-3}$ for the scalar and above (0.4–3)$\ten{-2}$ for the
pseudoscalar scenarios are excluded for $\phi$ masses in the 15–75range,
whereas the two models perform similarly for masses 108–340and are excluded
above (0.4–4)$\ten{-2}$ for the scalar and above (0.6–3)$\ten{-2}$ for the
pseudoscalar scenarios. Uncertainties in the production cross sections due to
scale and PDF choices are considered for both signal models [36, 37, 67], and
are also shown in Figs. 11 and 12.

The differences in the low-mass exclusion limits of scalar and pseudoscalar
$\ttbar\phi$ models result from the kinematic structure of the couplings,
which affect both the production cross section and the signal efficiency of
the $\phi$ bosons. The coupling of a scalar boson to a fermion is momentum
independent, whereas that of a pseudoscalar boson is proportional to the
momentum in the low momentum limit. Therefore, the low $\phi$ momentum part of
the production cross section is suppressed in the pseudoscalar model in
comparison to the scalar model for $\phi$ masses below the top quark mass
scale, while both production cross sections are similar for $\phi$ masses at
and above the top quark mass scale. Furthermore, this coupling structure
results in more pseudoscalar $\phi$ bosons in the Lorentz-boosted region
compared to the scalar $\phi$ bosons, yielding more energetic leptons with
higher selection efficiencies. The product of the fiducial acceptance and the
event selection efficiency for the type-III seesaw and the $\ttbar\phi$ models
for various signal mass hypotheses, calculated after all analysis selection
requirements, are given in Table 0.7.

Product of the fiducial acceptance and the event selection efficiency for the
signal models at various signal mass hypotheses calculated after all analysis
selection requirements.  Signal model Product of acceptance and efficiency (%)
Type-III seesaw (flavor-democratic scenario) $\Sigma$ mass () 100 200 300 400
550 700 850 1000 1250 1500 0.32 1.82 2.63 3.02 3.29 3.34 3.29 3.21 2.99 2.82
$\ttbar\phi$ $\phi$ mass () 15 20 25 30 40 50 60 70 75 108 125 150 200 250 300
Scalar $\phi(\to{\Pe\Pe}$) 0.85 1.29 1.67 2.02 2.74 3.44 4.25 5.16 4.95 5.53
8.32 9.00 10.3 11.1 11.5 Scalar $\phi(\to\mu\mu$) 1.54 2.16 2.81 3.35 4.38
5.29 6.40 7.69 7.56 8.74 11.6 12.3 14.0 14.8 15.3 Pseudoscalar
$\phi(\to{\Pe\Pe}$) 0.96 1.81 2.69 3.45 4.88 5.82 6.62 7.35 6.83 6.8 9.77 10.4
11.0 11.4 11.9 Pseudoscalar $\phi(\to\mu\mu$) 1.69 2.95 4.24 5.38 7.14 8.46
9.73 10.4 9.93 10.3 13.4 14.0 14.9 15.2 15.9

##  0.8 Summary

A search has been performed for physics beyond the standard model, using
multilepton events in 137of $\Pp\Pp$ collision data at $\sqrt{s}=13\TeV$,
collected with the CMS detector in 2016–2018. The observations are found to be
consistent with the expectations from standard model processes, with no
statistically significant signal-like excess in any of the probed channels.
The results are used to constrain the allowed parameter space of the targeted
signal models. At 95% confidence level, heavy fermions of the type-III seesaw
model with masses below 880are excluded assuming identical $\Sigma$ decay
branching fractions across all lepton flavors. This is the most restrictive
limit on the flavor-democratic scenario of the type-III seesaw model to date.
Assuming a Yukawa coupling of unit strength to top quarks, branching fractions
of new scalar (pseudoscalar) bosons to dielectrons or dimuons above 0.004
(0.03) are excluded at 95% confidence level for masses in the range 15–75, and
above 0.04 (0.03) for masses in the range 108–340. These are the first limits
in these channels on an extension of the standard model with scalar or
pseudoscalar particles.

###### Acknowledgements.

We thank M. J. Strassler for drawing our attention to the need to include top
quark pair production with three-body top quark decays,
${\PQt}\to\cPqb\PW\phi$, in the $\ttbar\phi$ signal model. 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, PUT 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 (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
Nos. 675440, 752730, and 765710 (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 Beijing Municipal Science & Technology Commission, No.
Z181100004218003; the Ministry of Education, Youth and Sports (MEYS) of the
Czech Republic; the Lendület (“Momentum”) Program and the János Bolyai
Research Scholarship of the Hungarian Academy of Sciences, the New National
Excellence Program ÚNKP, the NKFIA research grants 123842, 123959, 124845,
124850, 125105, 128713, 128786, and 129058 (Hungary); the Council of Science
and Industrial Research, India; the HOMING PLUS program of the Foundation for
Polish Science, cofinanced from European Union, Regional Development Fund, the
Mobility Plus program of the Ministry of Science and Higher Education, the
National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus
2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis
2012/07/E/ST2/01406; the National Priorities Research Program by Qatar
National Research Fund; the Ministry of Science and Education, grant no.
3.2989.2017 (Russia); the Programa Estatal de Fomento de la Investigación
Científica y Técnica de Excelencia María de Maeztu, grant MDM-2015-0509 and
the Programa Severo Ochoa del Principado de Asturias; the Thalis and Aristeia
programs cofinanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund
for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn
Academic into Its 2nd Century Project Advancement Project (Thailand); the
Nvidia Corporation; the Welch Foundation, contract C-1845; and the Weston
Havens Foundation (USA).

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##  .9 The CMS Collaboration

Yerevan Physics Institute, Yerevan, Armenia
A.M. Sirunyan${}^{\textrm{\textdagger}}$, A. Tumasyan Institut für
Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, T. Bergauer, M. Dragicevic, J. Erö, A. Escalante Del
Valle, M. Flechl, R. Frühwirth1, M. Jeitler1, N. Krammer, I. Krätschmer, D.
Liko, T. Madlener, I. Mikulec, N. Rad, J. Schieck1, R. Schöfbeck, M. Spanring,
D. Spitzbart, W. Waltenberger, C.-E. Wulz1, M. Zarucki Institute for Nuclear
Problems, Minsk, Belarus
V. Drugakov, V. Mossolov, J. Suarez Gonzalez Universiteit Antwerpen,
Antwerpen, Belgium
M.R. Darwish, E.A. De Wolf, D. Di Croce, X. Janssen, A. Lelek, M. Pieters, H.
Rejeb Sfar, H. Van Haevermaet, P. Van Mechelen, S. Van Putte, N. Van Remortel
Vrije Universiteit Brussel, Brussel, Belgium
F. Blekman, E.S. Bols, S.S. Chhibra, J. D’Hondt, J. De Clercq, D. Lontkovskyi,
S. Lowette, I. Marchesini, S. Moortgat, Q. Python, K. Skovpen, S. Tavernier,
W. Van Doninck, P. Van Mulders Université Libre de Bruxelles, Bruxelles,
Belgium
D. Beghin, B. Bilin, B. Clerbaux, G. De Lentdecker, H. Delannoy, B. Dorney, L.
Favart, A. Grebenyuk, A.K. Kalsi, A. Popov, N. Postiau, E. Starling, L.
Thomas, C. Vander Velde, P. Vanlaer, D. Vannerom Ghent University, Ghent,
Belgium
T. Cornelis, D. Dobur, I. Khvastunov2, M. Niedziela, C. Roskas, M. Tytgat, W.
Verbeke, B. Vermassen, M. Vit Université Catholique de Louvain, Louvain-la-
Neuve, Belgium
O. Bondu, G. Bruno, C. Caputo, P. David, C. Delaere, M. Delcourt, A.
Giammanco, V. Lemaitre, J. Prisciandaro, A. Saggio, M. Vidal Marono, P.
Vischia, J. Zobec Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro,
Brazil
F.L. Alves, G.A. Alves, G. Correia Silva, C. Hensel, A. Moraes, 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, L.M. Huertas Guativa, H. Malbouisson, J. Martins5, D. Matos
Figueiredo, M. Medina Jaime6, 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
C.A. Bernardesa, L. Calligarisa, T.R. Fernandez Perez Tomeia, E.M. Gregoresb,
D.S. Lemos, P.G. Mercadanteb, S.F. Novaesa, SandraS. Padulaa Institute for
Nuclear Research and Nuclear Energy, Bulgarian Academy of Sciences, Sofia,
Bulgaria
A. Aleksandrov, G. Antchev, R. Hadjiiska, P. Iaydjiev, M. Misheva, M. Rodozov,
M. Shopova, G. Sultanov University of Sofia, Sofia, Bulgaria
M. Bonchev, A. Dimitrov, T. Ivanov, L. Litov, B. Pavlov, P. Petkov Beihang
University, Beijing, China
W. Fang7, X. Gao7, L. Yuan Institute of High Energy Physics, Beijing, China
G.M. Chen, H.S. Chen, M. Chen, C.H. Jiang, D. Leggat, H. Liao, Z. Liu, A.
Spiezia, J. Tao, E. Yazgan, H. Zhang, S. Zhang8, J. Zhao State Key Laboratory
of Nuclear Physics and Technology, Peking University, Beijing, China
A. Agapitos, Y. Ban, G. Chen, A. Levin, J. Li, L. Li, Q. Li, Y. Mao, S.J.
Qian, D. Wang, Q. Wang Tsinghua University, Beijing, China
M. Ahmad, Z. Hu, Y. Wang Zhejiang University, Hangzhou, China
M. Xiao Universidad de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, C. Florez, C.F. González Hernández, M.A. Segura Delgado
Universidad de Antioquia, Medellin, Colombia
J. Mejia Guisao, J.D. Ruiz Alvarez, C.A. Salazar González, N. Vanegas Arbelaez
University of Split, Faculty of Electrical Engineering, Mechanical Engineering
and Naval Architecture, Split, Croatia
D. Giljanović, 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, M. Roguljic, A. Starodumov9,
T. Susa University of Cyprus, Nicosia, Cyprus
M.W. Ather, A. Attikis, E. Erodotou, A. Ioannou, M. Kolosova, S. Konstantinou,
G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H.
Rykaczewski, D. Tsiakkouri Charles University, Prague, Czech Republic
M. Finger10, M. Finger Jr.10, A. Kveton, J. Tomsa 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. Assran11,12, S. Elgammal12 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, L. Forthomme, H. Kirschenmann, K. Osterberg, M. Voutilainen
Helsinki Institute of Physics, Helsinki, Finland
F. Garcia, J. Havukainen, J.K. Heikkilä, V. Karimäki, M.S. Kim, 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, B. Fabbro, J.L. Faure, F.
Ferri, S. Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry,
C. Leloup, B. Lenzi, E. Locci, J. Malcles, J. Rander, A. Rosowsky, M.Ö. Sahin,
A. Savoy-Navarro13, M. Titov, G.B. Yu Laboratoire Leprince-Ringuet,
CNRS/IN2P3, Ecole Polytechnique, Institut Polytechnique de Paris
S. Ahuja, C. Amendola, F. Beaudette, P. Busson, C. Charlot, B. Diab, G.
Falmagne, R. Granier de Cassagnac, I. Kucher, A. Lobanov, C. Martin Perez, M.
Nguyen, C. Ochando, P. Paganini, J. Rembser, R. Salerno, J.B. Sauvan, Y.
Sirois, A. Zabi, A. Zghiche Université de Strasbourg, CNRS, IPHC UMR 7178,
Strasbourg, France
J.-L. Agram14, J. Andrea, D. Bloch, G. Bourgatte, J.-M. Brom, E.C. Chabert, C.
Collard, E. Conte14, J.-C. Fontaine14, 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, C. Camen, A. Carle, N. Chanon, R.
Chierici, D. Contardo, P. Depasse, H. El Mamouni, J. Fay, S. Gascon, M.
Gouzevitch, B. Ille, Sa. Jain, F. Lagarde, I.B. Laktineh, H. Lattaud, A.
Lesauvage, M. Lethuillier, L. Mirabito, S. Perries, V. Sordini, L. Torterotot,
G. Touquet, M. Vander Donckt, S. Viret Georgian Technical University, Tbilisi,
Georgia
T. Toriashvili15 Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze10 RWTH Aachen University, I. Physikalisches Institut, Aachen,
Germany
C. Autermann, L. Feld, K. Klein, M. Lipinski, D. Meuser, A. Pauls, M. Preuten,
M.P. Rauch, J. Schulz, M. Teroerde, B. Wittmer RWTH Aachen University, III.
Physikalisches Institut A, Aachen, Germany
M. Erdmann, B. Fischer, S. Ghosh, T. Hebbeker, K. Hoepfner, H. Keller, L.
Mastrolorenzo, M. Merschmeyer, A. Meyer, P. Millet, G. Mocellin, S. Mondal, S.
Mukherjee, D. Noll, A. Novak, T. Pook, A. Pozdnyakov, T. Quast, M. Radziej, Y.
Rath, H. Reithler, J. Roemer, A. Schmidt, S.C. Schuler, A. Sharma, S.
Wiedenbeck, S. Zaleski RWTH Aachen University, III. Physikalisches Institut B,
Aachen, Germany
G. Flügge, W. Haj Ahmad16, O. Hlushchenko, T. Kress, T. Müller, A. Nowack, C.
Pistone, O. Pooth, D. Roy, H. Sert, A. Stahl17 Deutsches Elektronen-
Synchrotron, Hamburg, Germany
M. Aldaya Martin, P. Asmuss, I. Babounikau, H. Bakhshiansohi, K. Beernaert, O.
Behnke, A. Bermúdez Martínez, D. Bertsche, A.A. Bin Anuar, K. Borras18, V.
Botta, A. Campbell, A. Cardini, P. Connor, S. Consuegra Rodríguez, C.
Contreras-Campana, V. Danilov, A. De Wit, M.M. Defranchis, C. Diez Pardos, D.
Domínguez Damiani, G. Eckerlin, D. Eckstein, T. Eichhorn, A. Elwood, E. Eren,
E. Gallo19, A. Geiser, A. Grohsjean, M. Guthoff, M. Haranko, A. Harb, A.
Jafari, N.Z. Jomhari, H. Jung, A. Kasem18, M. Kasemann, H. Kaveh, J. Keaveney,
C. Kleinwort, J. Knolle, D. Krücker, W. Lange, T. Lenz, J. Lidrych, K. Lipka,
W. Lohmann20, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, M. Meyer, M.
Missiroli, J. Mnich, A. Mussgiller, V. Myronenko, D. Pérez Adán, S.K.
Pflitsch, D. Pitzl, A. Raspereza, A. Saibel, M. Savitskyi, V. Scheurer, P.
Schütze, C. Schwanenberger, R. Shevchenko, A. Singh, H. Tholen, O. Turkot, A.
Vagnerini, M. Van De Klundert, R. Walsh, Y. Wen, K. Wichmann, C. Wissing, O.
Zenaiev, R. Zlebcik University of Hamburg, Hamburg, Germany
R. Aggleton, S. Bein, L. Benato, A. Benecke, V. Blobel, T. Dreyer, A.
Ebrahimi, F. Feindt, A. Fröhlich, C. Garbers, E. Garutti, D. Gonzalez, P.
Gunnellini, J. Haller, A. Hinzmann, A. Karavdina, G. Kasieczka, R. Klanner, R.
Kogler, N. Kovalchuk, S. Kurz, V. Kutzner, J. Lange, T. Lange, A. Malara, J.
Multhaup, C.E.N. Niemeyer, A. Perieanu, A. Reimers, O. Rieger, C. Scharf, P.
Schleper, S. Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G. Steinbrück,
F.M. Stober, B. Vormwald, I. Zoi Karlsruher Institut fuer Technologie,
Karlsruhe, Germany
M. Akbiyik, C. Barth, M. Baselga, S. Baur, T. Berger, E. Butz, R. Caspart, T.
Chwalek, W. De Boer, A. Dierlamm, K. El Morabit, N. Faltermann, M. Giffels, P.
Goldenzweig, A. Gottmann, M.A. Harrendorf, F. Hartmann17, U. Husemann, S.
Kudella, S. Mitra, M.U. Mozer, D. Müller, Th. Müller, M. Musich, A. Nürnberg,
G. Quast, K. Rabbertz, M. Schröder, I. Shvetsov, H.J. Simonis, R. Ulrich, M.
Wassmer, M. Weber, C. Wöhrmann, R. Wolf Institute of Nuclear and Particle
Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece
G. Anagnostou, P. Asenov, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas,
G. Paspalaki National and Kapodistrian University of Athens, Athens, Greece
M. Diamantopoulou, G. Karathanasis, P. Kontaxakis, A. Manousakis-katsikakis,
A. Panagiotou, I. Papavergou, N. Saoulidou, A. Stakia, K. Theofilatos, K.
Vellidis, E. Vourliotis National Technical University of Athens, Athens,
Greece
G. Bakas, K. Kousouris, I. Papakrivopoulos, G. Tsipolitis University of
Ioánnina, Ioánnina, Greece
I. Evangelou, C. Foudas, P. Gianneios, P. Katsoulis, P. Kokkas, S. Mallios, K.
Manitara, N. Manthos, I. Papadopoulos, J. Strologas, F.A. Triantis, D.
Tsitsonis MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
M. Bartók21, R. Chudasama, M. Csanad, P. Major, K. Mandal, A. Mehta, M.I.
Nagy, G. Pasztor, O. Surányi, G.I. Veres Wigner Research Centre for Physics,
Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath22, F. Sikler, T.Á. Vámi, V. Veszpremi, G.
Vesztergombi${}^{\textrm{\textdagger}}$ Institute of Nuclear Research ATOMKI,
Debrecen, Hungary
N. Beni, S. Czellar, J. Karancsi21, J. Molnar, Z. Szillasi Institute of
Physics, University of Debrecen, Debrecen, Hungary
P. Raics, D. Teyssier, Z.L. Trocsanyi, B. Ujvari Eszterhazy Karoly University,
Karoly Robert Campus, Gyongyos, Hungary
T. Csorgo, W.J. Metzger, F. Nemes, T. Novak 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. Bahinipati24, C. Kar, G. Kole, P. Mal, V.K. Muraleedharan Nair Bindhu, A.
Nayak25, D.K. Sahoo24, S.K. Swain Panjab University, Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, S. Chauhan, R. Chawla, N. Dhingra, R.
Gupta, A. Kaur, M. Kaur, S. Kaur, P. Kumari, M. Lohan, M. Meena, K. Sandeep,
S. Sharma, J.B. Singh, A.K. Virdi, G. Walia University of Delhi, Delhi, India
A. Bhardwaj, B.C. Choudhary, R.B. Garg, M. Gola, S. Keshri, Ashok Kumar, M.
Naimuddin, P. Priyanka, K. Ranjan, Aashaq Shah, R. Sharma Saha Institute of
Nuclear Physics, HBNI, Kolkata, India
R. Bhardwaj26, M. Bharti26, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep26,
D. Bhowmik, S. Dutta, S. Ghosh, B. Gomber27, M. Maity28, K. Mondal, S. Nandan,
A. Purohit, P.K. Rout, G. Saha, S. Sarkar, T. Sarkar28, M. Sharan, B. Singh26,
S. Thakur26 Indian Institute of Technology Madras, Madras, India
P.K. Behera, P. Kalbhor, A. Muhammad, P.R. Pujahari, A. Sharma, A.K. Sikdar
Bhabha Atomic Research Centre, Mumbai, India
D. Dutta, V. Jha, V. Kumar, D.K. Mishra, 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, RavindraKumar Verma Tata
Institute of Fundamental Research-B, Mumbai, India
S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, S. Karmakar,
S. Kumar, G. Majumder, K. Mazumdar, N. Sahoo, S. Sawant Indian Institute of
Science Education and Research (IISER), Pune, India
S. Dube, B. Kansal, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, A. Rastogi, S.
Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
S. Chenarani29, E. Eskandari Tadavani, S.M. Etesami29, M. Khakzad, M.
Mohammadi Najafabadi, M. Naseri, F. Rezaei Hosseinabadi 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, R. Alya,b,30, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L.
Cristellaa,b, N. De Filippisa,c, M. De Palmaa,b, A. Di Florioa,b, W.
Elmetenaweea,b, L. Fiorea, A. Gelmia,b, G. Iasellia,c, M. Incea,b, S.
Lezkia,b, G. Maggia,c, M. Maggia, J.A. Merlin, G. Minielloa,b, S. Mya,b, S.
Nuzzoa,b, A. Pompilia,b, G. Pugliesea,c, R. Radognaa, A. Ranieria, G.
Selvaggia,b, L. Silvestrisa, F.M. Simonea,b, R. Vendittia, P. Verwilligena
INFN Sezione di Bologna a, Università di Bologna b, Bologna, Italy
G. Abbiendia, C. Battilanaa,b, D. Bonacorsia,b, L. Borgonovia,b, S. Braibant-
Giacomellia,b, R. Campaninia,b, P. Capiluppia,b, A. Castroa,b, F.R. Cavalloa,
C. Cioccaa, G. Codispotia,b, M. Cuffiania,b, G.M. Dallavallea, F. Fabbria, A.
Fanfania,b, E. Fontanesia,b, P. Giacomellia, C. Grandia, L. Guiduccia,b, F.
Iemmia,b, S. Lo Meoa,31, S. Marcellinia, G. Masettia, F.L. Navarriaa,b, A.
Perrottaa, F. Primaveraa,b, 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,32, S. Costaa,b, A. Di Mattiaa, R. Potenzaa,b, A. Tricomia,b,32,
C. Tuvea,b INFN Sezione di Firenze a, Università di Firenze b, Firenze, Italy
G. Barbaglia, A. Cassese, R. Ceccarelli, V. Ciullia,b, C. Civininia, R.
D’Alessandroa,b, F. Fioria,c, E. Focardia,b, G. Latinoa,b, P. Lenzia,b, M.
Meschinia, S. Paolettia, G. Sguazzonia, L. Viliania INFN Laboratori Nazionali
di Frascati, Frascati, Italy
L. Benussi, S. Bianco, D. Piccolo INFN Sezione di Genova a, Università di
Genova b, Genova, Italy
M. Bozzoa,b, F. Ferroa, R. Mulargiaa,b, E. Robuttia, S. Tosia,b INFN Sezione
di Milano-Bicocca a, Università di Milano-Bicocca b, Milano, Italy
A. Benagliaa, A. Beschia,b, F. Brivioa,b, V. Cirioloa,b,17, M.E. Dinardoa,b,
P. Dinia, S. Gennaia, A. Ghezzia,b, P. Govonia,b, L. Guzzia,b, M. Malbertia,
S. Malvezzia, D. Menascea, F. Montia,b, L. Moronia, M. Paganonia,b, D.
Pedrinia, S. Ragazzia,b, T. Tabarelli de Fatisa,b, D. Valsecchia,b, D.
Zuoloa,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. De Iorioa,b, A. Di Crescenzoa,b, F.
Fabozzia,c, F. Fiengaa, G. Galatia, A.O.M. Iorioa,b, L. Listaa,b, S.
Meolaa,d,17, P. Paoluccia,17, B. Rossia, 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. Bragagnoloa,b, R.
Carlina,b, P. Checchiaa, P. De Castro Manzanoa, T. Dorigoa, U. Dossellia, F.
Gasparinia,b, U. Gasparinia,b, A. Gozzelinoa, S.Y. Hoha,b, P. Lujana, M.
Margonia,b, A.T. Meneguzzoa,b, J. Pazzinia,b, M. Presillab, P. Ronchesea,b, R.
Rossina,b, F. Simonettoa,b, A. Tikoa, M. Tosia,b, M. Zanettia,b, P. Zottoa,b,
G. Zumerlea,b INFN Sezione di Pavia a, Università di Pavia b, Pavia, Italy
A. Braghieria, D. Fiorinaa,b, P. Montagnaa,b, S.P. Rattia,b, V. Rea, M.
Ressegottia,b, C. Riccardia,b, P. Salvinia, I. Vaia, P. Vituloa,b INFN Sezione
di Perugia a, Università di Perugia b, Perugia, Italy
M. Biasinia,b, G.M. Bileia, 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, V. Bertacchia,c, L. Bianchinia, T.
Boccalia, R. Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, S. Donatoa, G. Fedia,
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, G. Rolandi33, S. Roy
Chowdhury, A. Scribanoa, P. Spagnoloa, R. Tenchinia, G. Tonellia,b, N. Turini,
A. Venturia, P.G. Verdinia INFN Sezione di Roma a, Sapienza Università di Roma
b, Rome, Italy
F. Cavallaria, M. Cipriania,b, D. Del Rea,b, E. Di Marcoa, M. Diemoza, E.
Longoa,b, P. Meridiania, G. Organtinia,b, F. Pandolfia, R. Paramattia,b, C.
Quarantaa,b, S. Rahatloua,b, C. Rovellia, F. Santanastasioa,b, L. Soffia,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, A. Bellora, C. Biinoa, A. Cappatia,b, N. Cartigliaa, S.
Comettia, M. Costaa,b, R. Covarellia,b, N. Demariaa, B. Kiania,b, F. Legger,
C. Mariottia, S. Masellia, E. Migliorea,b, V. Monacoa,b, E. Monteila,b, M.
Montenoa, M.M. Obertinoa,b, G. Ortonaa,b, L. Pachera,b, N. Pastronea, M.
Pelliccionia, G.L. Pinna Angionia,b, A. Romeroa,b, M. Ruspaa,c, R.
Salvaticoa,b, V. Solaa, A. Solanoa,b, D. Soldia,b, A. Staianoa, D. Trocinoa,b
INFN Sezione di Trieste a, Università di Trieste b, Trieste, Italy
S. Belfortea, V. Candelisea,b, M. Casarsaa, F. Cossuttia, A. Da Rolda,b, G.
Della Riccaa,b, F. Vazzolera,b, A. Zanettia Kyungpook National University,
Daegu, Korea
B. Kim, D.H. Kim, G.N. Kim, J. Lee, S.W. Lee, C.S. Moon, Y.D. Oh, S.I. Pak, 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
B. Francois, T.J. Kim, J. Park Korea University, Seoul, Korea
S. Cho, S. Choi, Y. Go, S. Ha, B. Hong, K. Lee, K.S. Lee, J. Lim, J. Park,
S.K. Park, Y. Roh, J. Yoo Kyung Hee University, Department of Physics
J. Goh Sejong University, Seoul, Korea
H.S. Kim Seoul National University, Seoul, Korea
J. Almond, J.H. Bhyun, J. Choi, S. Jeon, J. Kim, J.S. Kim, H. Lee, K. Lee, S.
Lee, K. Nam, M. Oh, S.B. Oh, B.C. Radburn-Smith, U.K. Yang, H.D. Yoo, I. Yoon
University of Seoul, Seoul, Korea
D. Jeon, J.H. Kim, J.S.H. Lee, I.C. Park, I.J Watson Sungkyunkwan University,
Suwon, Korea
Y. Choi, C. Hwang, Y. Jeong, J. Lee, Y. Lee, I. Yu Riga Technical University,
Riga, Latvia
V. Veckalns34 Vilnius University, Vilnius, Lithuania
V. Dudenas, A. Juodagalvis, A. Rinkevicius, G. Tamulaitis, J. Vaitkus National
Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia
Z.A. Ibrahim, F. Mohamad Idris35, W.A.T. Wan Abdullah, M.N. Yusli, Z. Zolkapli
Universidad de Sonora (UNISON), Hermosillo, Mexico
J.F. Benitez, A. Castaneda Hernandez, J.A. Murillo Quijada, L. Valencia Palomo
Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico
H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz36, R. Lopez-
Fernandez, A. Sanchez-Hernandez Universidad Iberoamericana, Mexico City,
Mexico
S. Carrillo Moreno, C. Oropeza Barrera, M. Ramirez-Garcia, 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 Montenegro, Podgorica, Montenegro
J. Mijuskovic2, N. Raicevic University of Auckland, Auckland, New Zealand
D. Krofcheck University of Canterbury, Christchurch, New Zealand
S. Bheesette, P.H. Butler National Centre for Physics, Quaid-I-Azam
University, Islamabad, Pakistan
A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, W.A. Khan, M.A. Shah, M. Shoaib,
M. Waqas AGH University of Science and Technology Faculty of Computer Science,
Electronics and Telecommunications, Krakow, Poland
V. Avati, L. Grzanka, M. Malawski National Centre for Nuclear Research,
Swierk, Poland
H. Bialkowska, M. Bluj, B. Boimska, M. Górski, M. Kazana, M. Szleper, P.
Zalewski Institute of Experimental Physics, Faculty of Physics, University of
Warsaw, Warsaw, Poland
K. Bunkowski, A. Byszuk37, K. Doroba, A. Kalinowski, M. Konecki, J.
Krolikowski, M. Olszewski, M. Walczak Laboratório de Instrumentação e Física
Experimental de Partículas, Lisboa, Portugal
M. Araujo, P. Bargassa, D. Bastos, A. Di Francesco, P. Faccioli, B. Galinhas,
M. Gallinaro, J. Hollar, N. Leonardo, T. Niknejad, J. Seixas, K. Shchelina, G.
Strong, O. Toldaiev, J. Varela Joint Institute for Nuclear Research, Dubna,
Russia
S. Afanasiev, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev,
V. Karjavine, A. Lanev, A. Malakhov, V. Matveev38,39, P. Moisenz, V. Palichik,
V. Perelygin, M. Savina, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N.
Voytishin, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St.
Petersburg), Russia
L. Chtchipounov, V. Golovtcov, Y. Ivanov, V. Kim40, E. Kuznetsova41, P.
Levchenko, V. Murzin, V. Oreshkin, I. Smirnov, D. Sosnov, V. Sulimov, L.
Uvarov, 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 named by A.I. Alikhanov of NRC ‘Kurchatov Institute’,
Moscow, Russia
V. Epshteyn, V. Gavrilov, N. Lychkovskaya, A. Nikitenko42, V. Popov, I.
Pozdnyakov, G. Safronov, A. Spiridonov, A. Stepennov, M. Toms, E. Vlasov, A.
Zhokin Moscow Institute of Physics and Technology, Moscow, Russia
T. Aushev National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
O. Bychkova, R. Chistov43, M. Danilov43, S. Polikarpov43, E. Tarkovskii P.N.
Lebedev Physical Institute, Moscow, Russia
V. Andreev, M. Azarkin, I. Dremin, M. Kirakosyan, A. Terkulov Skobeltsyn
Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow,
Russia
A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin44, L. Dudko, A.
Ershov, A. Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, S. Obraztsov, V.
Savrin Novosibirsk State University (NSU), Novosibirsk, Russia
A. Barnyakov45, V. Blinov45, T. Dimova45, L. Kardapoltsev45, Y. Skovpen45
Institute for High Energy Physics of National Research Centre ‘Kurchatov
Institute’, Protvino, Russia
I. Azhgirey, I. Bayshev, S. Bitioukov, V. Kachanov, 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, A. Iuzhakov, V. Okhotnikov Tomsk State University, Tomsk, Russia
V. Borchsh, V. Ivanchenko, E. Tcherniaev University of Belgrade: Faculty of
Physics and VINCA Institute of Nuclear Sciences
P. Adzic46, P. Cirkovic, M. Dordevic, P. Milenovic, J. Milosevic, M.
Stojanovic Centro de Investigaciones Energéticas Medioambientales y
Tecnológicas (CIEMAT), Madrid, Spain
M. Aguilar-Benitez, J. Alcaraz Maestre, A. Álvarez Fernández, I. Bachiller, M.
Barrio Luna, CristinaF. Bedoya, J.A. Brochero Cifuentes, C.A. Carrillo
Montoya, M. Cepeda, M. Cerrada, N. Colino, B. De La Cruz, A. Delgado Peris,
J.P. Fernández Ramos, J. Flix, M.C. Fouz, O. Gonzalez Lopez, S. Goy Lopez,
J.M. Hernandez, M.I. Josa, D. Moran, Á. Navarro Tobar, A. Pérez-Calero
Yzquierdo, J. Puerta Pelayo, I. Redondo, L. Romero, S. Sánchez Navas, M.S.
Soares, A. Triossi, C. Willmott Universidad Autónoma de Madrid, Madrid, Spain
C. Albajar, J.F. de Trocóniz, R. Reyes-Almanza Universidad de Oviedo,
Instituto Universitario de Ciencias y Tecnologías Espaciales de Asturias
(ICTEA), Oviedo, Spain
B. Alvarez Gonzalez, 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 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, G. Gomez, C. Martinez
Rivero, P. Martinez Ruiz del Arbol, F. Matorras, J. Piedra Gomez, C. Prieels,
T. Rodrigo, A. Ruiz-Jimeno, L. Russo47, L. Scodellaro, I. Vila, J.M. Vizan
Garcia University of Colombo, Colombo, Sri Lanka
K. Malagalage University of Ruhuna, Department of Physics, Matara, Sri Lanka
W.G.D. Dharmaratna, N. Wickramage CERN, European Organization for Nuclear
Research, Geneva, Switzerland
D. Abbaneo, B. Akgun, E. Auffray, G. Auzinger, J. Baechler, P. Baillon, A.H.
Ball, D. Barney, J. Bendavid, M. Bianco, A. Bocci, P. Bortignon, E. Bossini,
C. Botta, E. Brondolin, T. Camporesi, A. Caratelli, G. Cerminara, E. Chapon,
G. Cucciati, D. d’Enterria, A. Dabrowski, N. Daci, V. Daponte, A. David, O.
Davignon, A. De Roeck, M. Deile, M. Dobson, M. Dünser, N. Dupont, A. Elliott-
Peisert, N. Emriskova, F. Fallavollita48, D. Fasanella, S. Fiorendi, G.
Franzoni, J. Fulcher, W. Funk, S. Giani, D. Gigi, K. Gill, F. Glege, L.
Gouskos, M. Gruchala, M. Guilbaud, D. Gulhan, J. Hegeman, C. Heidegger, Y.
Iiyama, V. Innocente, T. James, P. Janot, O. Karacheban20, J. Kaspar, J.
Kieseler, M. Krammer1, N. Kratochwil, C. Lange, P. Lecoq, C. Lourenço, L.
Malgeri, M. Mannelli, A. Massironi, F. Meijers, S. Mersi, E. Meschi, F.
Moortgat, M. Mulders, J. Ngadiuba, J. Niedziela, S. Nourbakhsh, S. Orfanelli,
L. Orsini, F. Pantaleo17, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G.
Petrucciani, A. Pfeiffer, M. Pierini, F.M. Pitters, D. Rabady, A. Racz, M.
Rieger, M. Rovere, H. Sakulin, J. Salfeld-Nebgen, C. Schäfer, C. Schwick, M.
Selvaggi, A. Sharma, P. Silva, W. Snoeys, P. Sphicas49, J. Steggemann, S.
Summers, V.R. Tavolaro, D. Treille, A. Tsirou, G.P. Van Onsem, A. Vartak, M.
Verzetti, W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland
L. Caminada50, 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, P. Berger, N. Chernyavskaya, G. Dissertori, M. Dittmar, M.
Donegà, C. Dorfer, T.A. Gómez Espinosa, C. Grab, D. Hits, W. Lustermann, R.A.
Manzoni, M.T. Meinhard, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pauss, G.
Perrin, L. Perrozzi, S. Pigazzini, M.G. Ratti, M. Reichmann, C. Reissel, T.
Reitenspiess, B. Ristic, D. Ruini, D.A. Sanz Becerra, M. Schönenberger, L.
Shchutska, M.L. Vesterbacka Olsson, R. Wallny, D.H. Zhu Universität Zürich,
Zurich, Switzerland
T.K. Aarrestad, C. Amsler51, D. Brzhechko, M.F. Canelli, A. De Cosa, R. Del
Burgo, B. Kilminster, S. Leontsinis, V.M. Mikuni, I. Neutelings, G. Rauco, P.
Robmann, K. Schweiger, C. Seitz, Y. Takahashi, S. Wertz, A. Zucchetta National
Central University, Chung-Li, Taiwan
T.H. Doan, C.M. Kuo, W. Lin, A. Roy, S.S. Yu National Taiwan University (NTU),
Taipei, Taiwan
P. Chang, Y. Chao, K.F. Chen, P.H. Chen, W.-S. Hou, Y.y. Li, R.-S. Lu, E.
Paganis, A. Psallidas, A. Steen Chulalongkorn University, Faculty of Science,
Department of Physics, Bangkok, Thailand
B. Asavapibhop, C. Asawatangtrakuldee, N. Srimanobhas, N. Suwonjandee Çukurova
University, Physics Department, Science and Art Faculty, Adana, Turkey
A. Bat, F. Boran, A. Celik52, S. Cerci53, S. Damarseckin54, Z.S. Demiroglu, F.
Dolek, C. Dozen55, I. Dumanoglu, G. Gokbulut, EmineGurpinar Guler56, Y. Guler,
I. Hos57, C. Isik, E.E. Kangal58, O. Kara, A. Kayis Topaksu, U. Kiminsu, G.
Onengut, K. Ozdemir59, S. Ozturk60, A.E. Simsek, D. Sunar Cerci53, U.G. Tok,
S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University,
Physics Department, Ankara, Turkey
B. Isildak61, G. Karapinar62, M. Yalvac Bogazici University, Istanbul, Turkey
I.O. Atakisi, E. Gülmez, M. Kaya63, O. Kaya64, Ö. Özçelik, S. Tekten, E.A.
Yetkin65 Istanbul Technical University, Istanbul, Turkey
A. Cakir, K. Cankocak, Y. Komurcu, S. Sen66 Istanbul University, Istanbul,
Turkey
B. Kaynak, S. Ozkorucuklu 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
E. Bhal, S. Bologna, J.J. Brooke, D. Burns67, E. Clement, D. Cussans, H.
Flacher, J. Goldstein, G.P. Heath, H.F. Heath, L. Kreczko, B. Krikler, S.
Paramesvaran, B. Penning, T. Sakuma, S. Seif El Nasr-Storey, V.J. Smith, J.
Taylor, A. Titterton Rutherford Appleton Laboratory, Didcot, United Kingdom
K.W. Bell, A. Belyaev68, C. Brew, R.M. Brown, D.J.A. Cockerill, J.A. Coughlan,
K. Harder, S. Harper, J. Linacre, K. Manolopoulos, D.M. Newbold, E. Olaiya, D.
Petyt, T. Reis, T. Schuh, C.H. Shepherd-Themistocleous, A. Thea, I.R. Tomalin,
T. Williams, W.J. Womersley Imperial College, London, United Kingdom
R. Bainbridge, P. Bloch, J. Borg, S. Breeze, O. Buchmuller, A. Bundock,
GurpreetSingh CHAHAL69, D. Colling, P. Dauncey, G. Davies, M. Della Negra, R.
Di Maria, P. Everaerts, G. Hall, G. Iles, M. Komm, L. Lyons, A.-M. Magnan, S.
Malik, A. Martelli, V. Milosevic, A. Morton, J. Nash70, V. Palladino, M.
Pesaresi, D.M. Raymond, A. Richards, A. Rose, E. Scott, C. Seez, A.
Shtipliyski, M. Stoye, T. Strebler, A. Tapper, K. Uchida, T. Virdee17, N.
Wardle, D. Winterbottom, A.G. Zecchinelli, S.C. Zenz Brunel University,
Uxbridge, United Kingdom
J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, C.K. Mackay, I.D. Reid, L.
Teodorescu, S. Zahid Baylor University, Waco, USA
K. Call, B. Caraway, J. Dittmann, K. Hatakeyama, C. Madrid, B. McMaster, N.
Pastika, C. Smith Catholic University of America, Washington, DC, USA
R. Bartek, A. Dominguez, R. Uniyal, A.M. Vargas Hernandez The University of
Alabama, Tuscaloosa, USA
A. Buccilli, S.I. Cooper, C. Henderson, P. Rumerio, C. West Boston University,
Boston, USA
A. Albert, D. Arcaro, Z. Demiragli, D. Gastler, C. Richardson, J. Rohlf, D.
Sperka, I. Suarez, L. Sulak, D. Zou Brown University, Providence, USA
G. Benelli, B. Burkle, X. Coubez18, D. Cutts, Y.t. Duh, M. Hadley, U. Heintz,
J.M. Hogan71, K.H.M. Kwok, E. Laird, G. Landsberg, K.T. Lau, J. Lee, M.
Narain, S. Sagir72, R. Syarif, E. Usai, W.Y. Wong, D. Yu, W. Zhang University
of California, Davis, Davis, USA
R. Band, C. Brainerd, R. Breedon, M. Calderon De La Barca Sanchez, M. Chertok,
J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, F. Jensen, W.
Ko${}^{\textrm{\textdagger}}$, O. Kukral, R. Lander, M. Mulhearn, D. Pellett,
J. Pilot, M. Shi, 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, W.A. Nash, S. Regnard, D. Saltzberg, C. Schnaible, B.
Stone, V. Valuev University of California, Riverside, Riverside, USA
K. Burt, Y. Chen, R. Clare, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, G.
Karapostoli, O.R. Long, M. Olmedo Negrete, M.I. Paneva, W. Si, L. Wang, S.
Wimpenny, B.R. Yates, Y. Zhang University of California, San Diego, La Jolla,
USA
J.G. Branson, P. Chang, S. Cittolin, S. Cooperstein, N. Deelen, M. Derdzinski,
R. Gerosa, D. Gilbert, B. Hashemi, D. Klein, V. Krutelyov, J. Letts, M.
Masciovecchio, S. May, S. Padhi, M. Pieri, V. Sharma, M. Tadel, F. Würthwein,
A. Yagil, G. Zevi Della Porta University of California, Santa Barbara -
Department of Physics, Santa Barbara, USA
N. Amin, R. Bhandari, C. Campagnari, M. Citron, V. Dutta, M. Franco Sevilla,
J. Incandela, B. Marsh, H. Mei, A. Ovcharova, H. Qu, J. Richman, U. Sarica, D.
Stuart, S. Wang California Institute of Technology, Pasadena, USA
D. Anderson, A. Bornheim, O. Cerri, I. Dutta, J.M. Lawhorn, N. Lu, J. Mao,
H.B. Newman, T.Q. Nguyen, J. Pata, M. Spiropulu, J.R. Vlimant, S. Xie, Z.
Zhang, R.Y. Zhu Carnegie Mellon University, Pittsburgh, USA
M.B. Andrews, T. Ferguson, T. Mudholkar, M. Paulini, M. Sun, I. Vorobiev, M.
Weinberg University of Colorado Boulder, Boulder, USA
J.P. Cumalat, W.T. Ford, E. MacDonald, T. Mulholland, R. Patel, A. Perloff, K.
Stenson, K.A. Ulmer, S.R. Wagner Cornell University, Ithaca, USA
J. Alexander, Y. Cheng, J. Chu, A. Datta, A. Frankenthal, K. Mcdermott, J.R.
Patterson, D. Quach, A. Ryd, S.M. Tan, Z. Tao, J. Thom, 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, D. Berry, J. Berryhill, P.C. Bhat, 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, AllisonReinsvold Hall, J. Hanlon,
R.M. Harris, S. Hasegawa, R. Heller, J. Hirschauer, B. Jayatilaka, S.
Jindariani, M. Johnson, U. Joshi, T. Klijnsma, B. Klima, M.J. Kortelainen, B.
Kreis, S. Lammel, J. Lewis, 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, V. Papadimitriou, K. Pedro, C. Pena, G. Rakness, F. Ravera,
L. Ristori, B. Schneider, E. Sexton-Kennedy, N. Smith, 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, R. Vidal, M. Wang, H.A. Weber
University of Florida, Gainesville, USA
D. Acosta, P. Avery, D. Bourilkov, A. Brinkerhoff, L. Cadamuro, V. Cherepanov,
F. Errico, R.D. Field, S.V. Gleyzer, D. Guerrero, B.M. Joshi, M. Kim, J.
Konigsberg, A. Korytov, K.H. Lo, K. Matchev, N. Menendez, G. Mitselmakher, D.
Rosenzweig, K. Shi, J. Wang, S. Wang, X. Zuo Florida International University,
Miami, USA
Y.R. Joshi Florida State University, Tallahassee, USA
T. Adams, A. Askew, S. Hagopian, V. Hagopian, K.F. Johnson, R. Khurana, T.
Kolberg, G. Martinez, T. Perry, H. Prosper, C. Schiber, R. Yohay, J. Zhang
Florida Institute of Technology, Melbourne, USA
M.M. Baarmand, M. Hohlmann, D. Noonan, M. Rahmani, M. Saunders, F. Yumiceva
University of Illinois at Chicago (UIC), Chicago, USA
M.R. Adams, L. Apanasevich, R.R. Betts, R. Cavanaugh, X. Chen, S. Dittmer, O.
Evdokimov, C.E. Gerber, D.A. Hangal, D.J. Hofman, C. Mills, T. Roy, M.B.
Tonjes, N. Varelas, J. Viinikainen, H. Wang, X. Wang, Z. Wu The University of
Iowa, Iowa City, USA
M. Alhusseini, B. Bilki56, K. Dilsiz73, S. Durgut, R.P. Gandrajula, M.
Haytmyradov, V. Khristenko, O.K. Köseyan, J.-P. Merlo, A. Mestvirishvili74, A.
Moeller, J. Nachtman, H. Ogul75, Y. Onel, F. Ozok76, A. Penzo, C. Snyder, E.
Tiras, J. Wetzel Johns Hopkins University, Baltimore, USA
B. Blumenfeld, A. Cocoros, N. Eminizer, A.V. Gritsan, W.T. Hung, S. Kyriacou,
P. Maksimovic, J. Roskes, M. Swartz The University of Kansas, Lawrence, USA
C. Baldenegro Barrera, P. Baringer, A. Bean, S. Boren, J. Bowen, A. Bylinkin,
T. Isidori, S. Khalil, J. King, G. Krintiras, A. Kropivnitskaya, C. Lindsey,
D. Majumder, W. Mcbrayer, N. Minafra, M. Murray, C. Rogan, C. Royon, S.
Sanders, E. Schmitz, J.D. Tapia Takaki, Q. Wang, J. Williams, G. Wilson Kansas
State University, Manhattan, USA
S. Duric, A. Ivanov, K. Kaadze, D. Kim, Y. Maravin, D.R. Mendis, T. Mitchell,
A. Modak, A. Mohammadi 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, N.J. Hadley, S. Jabeen,
G.Y. Jeng, R.G. Kellogg, A.C. Mignerey, S. Nabili, F. Ricci-Tam, M. Seidel,
Y.H. Shin, A. Skuja, S.C. Tonwar, K. Wong Massachusetts Institute of
Technology, Cambridge, USA
D. Abercrombie, B. Allen, A. Baty, R. Bi, S. Brandt, W. Busza, I.A. Cali, M.
D’Alfonso, G. Gomez Ceballos, M. Goncharov, P. Harris, D. Hsu, M. Hu, 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, D. Rankin, C. Roland, G. Roland, Z.
Shi, G.S.F. Stephans, K. Sumorok, K. Tatar, D. Velicanu, J. Wang, T.W. Wang,
B. Wyslouch University of Minnesota, Minneapolis, USA
R.M. Chatterjee, A. Evans, S. Guts${}^{\textrm{\textdagger}}$, P. Hansen, J.
Hiltbrand, Sh. Jain, Y. Kubota, Z. Lesko, J. Mans, M. Revering, R. Rusack, R.
Saradhy, N. Schroeder, M.A. Wadud University of Mississippi, Oxford, USA
J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA
K. Bloom, S. Chauhan, D.R. Claes, C. Fangmeier, L. Finco, F. Golf, R.
Kamalieddin, I. Kravchenko, J.E. Siado, G.R. Snow${}^{\textrm{\textdagger}}$,
B. Stieger, W. Tabb State University of New York at Buffalo, Buffalo, USA
G. Agarwal, C. Harrington, I. Iashvili, A. Kharchilava, C. McLean, D. Nguyen,
A. Parker, J. Pekkanen, S. Rappoccio, B. Roozbahani Northeastern University,
Boston, USA
G. Alverson, E. Barberis, C. Freer, Y. Haddad, A. Hortiangtham, G. Madigan, B.
Marzocchi, D.M. Morse, T. Orimoto, L. Skinnari, A. Tishelman-Charny, T.
Wamorkar, B. Wang, A. Wisecarver, D. Wood Northwestern University, Evanston,
USA
S. Bhattacharya, J. Bueghly, A. Gilbert, T. Gunter, K.A. Hahn, N. Odell, M.H.
Schmitt, K. Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame,
USA
R. Bucci, N. Dev, R. Goldouzian, M. Hildreth, K. Hurtado Anampa, C. Jessop,
D.J. Karmgard, K. Lannon, W. Li, N. Loukas, N. Marinelli, I. Mcalister, F.
Meng, Y. Musienko38, R. Ruchti, P. Siddireddy, G. Smith, S. Taroni, M. Wayne,
A. Wightman, M. Wolf, A. Woodard The Ohio State University, Columbus, USA
J. Alimena, B. Bylsma, L.S. Durkin, B. Francis, C. Hill, W. Ji, A. Lefeld,
T.Y. Ling, B.L. Winer Princeton University, Princeton, USA
G. Dezoort, P. Elmer, J. Hardenbrook, N. Haubrich, S. Higginbotham, A.
Kalogeropoulos, S. Kwan, D. Lange, M.T. Lucchini, J. Luo, D. Marlow, K. Mei,
I. Ojalvo, J. Olsen, C. Palmer, P. Piroué, D. Stickland, C. Tully University
of Puerto Rico, Mayaguez, USA
S. Malik, S. Norberg Purdue University, West Lafayette, USA
A. Barker, V.E. Barnes, S. Das, L. Gutay, M. Jones, A.W. Jung, A. Khatiwada,
B. Mahakud, D.H. Miller, G. Negro, N. Neumeister, C.C. Peng, S. Piperov, H.
Qiu, J.F. Schulte, N. Trevisani, F. Wang, R. Xiao, W. Xie Purdue University
Northwest, Hammond, USA
T. Cheng, J. Dolen, N. Parashar Rice University, Houston, USA
U. Behrens, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Kilpatrick, Arun Kumar,
W. Li, B.P. Padley, R. Redjimi, J. Roberts, J. Rorie, W. Shi, A.G. Stahl
Leiton, Z. Tu, A. Zhang University of Rochester, Rochester, USA
A. Bodek, P. de Barbaro, R. Demina, J.L. Dulemba, C. Fallon, T. Ferbel, M.
Galanti, A. Garcia-Bellido, O. Hindrichs, A. Khukhunaishvili, E. Ranken, R.
Taus Rutgers, The State University of New Jersey, Piscataway, USA
B. Chiarito, J.P. Chou, A. Gandrakota, Y. Gershtein, E. Halkiadakis, A. Hart,
M. Heindl, E. Hughes, I. Laflotte, A. Lath, R. Montalvo, K. Nash, M. Osherson,
H. Saka, S. Salur, S. Schnetzer, S. Somalwar, R. Stone, S. Thomas, J. Vora
University of Tennessee, Knoxville, USA
H. Acharya, A.G. Delannoy, S. Spanier Texas A&M University, College Station,
USA
O. Bouhali77, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi,
J. Gilmore, T. Huang, T. Kamon78, H. Kim, S. Luo, S. Malhotra, D. Marley, R.
Mueller, D. Overton, L. Perniè, D. Rathjens, A. Safonov Texas Tech University,
Lubbock, USA
N. Akchurin, J. Damgov, F. De Guio, V. Hegde, S. Kunori, K. Lamichhane, S.W.
Lee, T. Mengke, S. Muthumuni, T. Peltola, S. Undleeb, I. Volobouev, Z. Wang,
A. Whitbeck Vanderbilt University, Nashville, USA
S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K.
Padeken, F. Romeo, P. Sheldon, S. Tuo, J. Velkovska, M. Verweij University of
Virginia, Charlottesville, USA
M.W. Arenton, P. Barria, B. Cox, G. Cummings, J. Hakala, R. Hirosky, M. Joyce,
A. Ledovskoy, C. Neu, B. Tannenwald, Y. Wang, E. Wolfe, F. Xia Wayne State
University, Detroit, USA
R. Harr, P.E. Karchin, N. Poudyal, J. Sturdy, P. Thapa University of Wisconsin
- Madison, Madison, WI, USA
T. Bose, J. Buchanan, C. Caillol, D. Carlsmith, S. Dasu, I. De Bruyn, L. Dodd,
C. Galloni, H. He, M. Herndon, A. Hervé, U. Hussain, A. Lanaro, A. Loeliger,
K. Long, R. Loveless, J. Madhusudanan Sreekala, D. Pinna, T. Ruggles, A.
Savin, V. Sharma, W.H. Smith, D. Teague, S. Trembath-reichert †: 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 UFMS, Nova Andradina, Brazil
6: Also at Universidade Federal de Pelotas, Pelotas, Brazil
7: Also at Université Libre de Bruxelles, Bruxelles, Belgium
8: Also at University of Chinese Academy of Sciences, Beijing, China
9: Also at Institute for Theoretical and Experimental Physics named by A.I.
Alikhanov of NRC ‘Kurchatov Institute’, Moscow, Russia
10: Also at Joint Institute for Nuclear Research, Dubna, Russia
11: Also at Suez University, Suez, Egypt
12: Now at British University in Egypt, Cairo, Egypt
13: Also at Purdue University, West Lafayette, USA
14: Also at Université de Haute Alsace, Mulhouse, France
15: Also at Tbilisi State University, Tbilisi, Georgia
16: Also at Erzincan Binali Yildirim University, Erzincan, Turkey
17: Also at CERN, European Organization for Nuclear Research, Geneva,
Switzerland
18: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
19: Also at University of Hamburg, Hamburg, Germany
20: Also at Brandenburg University of Technology, Cottbus, Germany
21: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary,
Debrecen, Hungary
22: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
23: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary, Budapest, Hungary
24: Also at IIT Bhubaneswar, Bhubaneswar, India, Bhubaneswar, India
25: Also at Institute of Physics, Bhubaneswar, India
26: Also at Shoolini University, Solan, India
27: Also at University of Hyderabad, Hyderabad, India
28: Also at University of Visva-Bharati, Santiniketan, India
29: Also at Isfahan University of Technology, Isfahan, Iran
30: Now at INFN Sezione di Bari a, Università di Bari b, Politecnico di Bari
c, Bari, Italy
31: Also at Italian National Agency for New Technologies, Energy and
Sustainable Economic Development, Bologna, Italy
32: Also at Centro Siciliano di Fisica Nucleare e di Struttura Della Materia,
Catania, Italy
33: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy
34: Also at Riga Technical University, Riga, Latvia, Riga, Latvia
35: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia
36: Also at Consejo Nacional de Ciencia y Tecnología, Mexico City, Mexico
37: Also at Warsaw University of Technology, Institute of Electronic Systems,
Warsaw, Poland
38: Also at Institute for Nuclear Research, Moscow, Russia
39: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
40: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
41: Also at University of Florida, Gainesville, USA
42: Also at Imperial College, London, United Kingdom
43: Also at P.N. Lebedev Physical Institute, Moscow, Russia
44: Also at California Institute of Technology, Pasadena, USA
45: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
46: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
47: Also at Università degli Studi di Siena, Siena, Italy
48: Also at INFN Sezione di Pavia a, Università di Pavia b, Pavia, Italy,
Pavia, Italy
49: Also at National and Kapodistrian University of Athens, Athens, Greece
50: Also at Universität Zürich, Zurich, Switzerland
51: Also at Stefan Meyer Institute for Subatomic Physics, Vienna, Austria,
Vienna, Austria
52: Also at Burdur Mehmet Akif Ersoy University, BURDUR, Turkey
53: Also at Adiyaman University, Adiyaman, Turkey
54: Also at Şırnak University, Sirnak, Turkey
55: Also at Tsinghua University, Beijing, China
56: Also at Beykent University, Istanbul, Turkey, Istanbul, Turkey
57: Also at Istanbul Aydin University, Istanbul, Turkey
58: Also at Mersin University, Mersin, Turkey
59: Also at Piri Reis University, Istanbul, Turkey
60: Also at Gaziosmanpasa University, Tokat, Turkey
61: Also at Ozyegin University, Istanbul, Turkey
62: Also at Izmir Institute of Technology, Izmir, Turkey
63: Also at Marmara University, Istanbul, Turkey
64: Also at Kafkas University, Kars, Turkey
65: Also at Istanbul Bilgi University, Istanbul, Turkey
66: Also at Hacettepe University, Ankara, Turkey
67: Also at Vrije Universiteit Brussel, Brussel, Belgium
68: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
69: Also at IPPP Durham University, Durham, United Kingdom
70: Also at Monash University, Faculty of Science, Clayton, Australia
71: Also at Bethel University, St. Paul, Minneapolis, USA, St. Paul, USA
72: Also at Karamanoğlu Mehmetbey University, Karaman, Turkey
73: Also at Bingol University, Bingol, Turkey
74: Also at Georgian Technical University, Tbilisi, Georgia
75: Also at Sinop University, Sinop, Turkey
76: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey
77: Also at Texas A&M University at Qatar, Doha, Qatar
78: Also at Kyungpook National University, Daegu, Korea, Daegu, Korea