SUS-17-004

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SUS-17-004

# Combined search for electroweak production of charginos and neutralinos in
proton-proton collisions at $\sqrt{s}=13\TeV$

###### Abstract

A statistical combination of several searches for the electroweak production
of charginos and neutralinos is presented. All searches use proton-proton
collision data at $\sqrt{s}=13\TeV$, recorded with the CMS detector at the LHC
in 2016 and corresponding to an integrated luminosity of 35.9. In addition to
the combination of previous searches, a targeted analysis requiring three or
more charged leptons (electrons or muons) is presented, focusing on the
challenging scenario in which the difference in mass between the two least
massive neutralinos is approximately equal to the mass of the Z boson. The
results are interpreted in simplified models of chargino-neutralino or
neutralino pair production. For chargino-neutralino production, in the case
when the lightest neutralino is massless, the combination yields an observed
(expected) limit at the 95% confidence level on the chargino mass of up to 650
(570), improving upon the individual analysis limits by up to 40. If the mass
difference between the two least massive neutralinos is approximately equal to
the mass of the Z boson in the chargino-neutralino model, the targeted search
requiring three or more leptons obtains observed and expected exclusion limits
of around 225on the second neutralino mass and 125on the lightest neutralino
mass, improving the observed limit by about 60in both masses compared to the
previous CMS result. In the neutralino pair production model, the combined
observed (expected) exclusion limit on the neutralino mass extends up to
650–750 (550–750), depending on the branching fraction assumed. This extends
the observed exclusion achieved in the individual analyses by up to 200. The
combined result additionally excludes some intermediate gaps in the mass
coverage of the individual analyses.

##  0.1 Introduction

Supersymmetry (SUSY) [1, 2, 3, 4, 5, 6, 7, 8] is an extension of the standard
model (SM) of particle physics. It posits a new symmetry such that for each
boson (fermion) in the SM, there exists a fermionic (bosonic) superpartner.
Supersymmetry can potentially address several of the open questions in
particle physics, including the hierarchy problem [9, 10, 11] and the
unification of the gauge couplings at high energy scales [12, 13]. If
$R$-parity [14] is conserved, the lightest SUSY particle (LSP) is stable and
could be a potential dark matter candidate [15, 16].

This paper focuses on searches for electroweak production of SUSY particles,
under the assumption that the strongly-coupled SUSY particles are too massive
to be directly produced. The superpartners of the bosons from the SM SU(2) and
U(1) gauge fields before electroweak symmetry breaking are denoted as the
winos and bino, respectively. We consider SUSY models assuming two complex
Higgs doublets, and the superpartners of the Higgs bosons are denoted as
higgsinos. The bino, winos, and higgsinos form mass eigenstates of two
charginos () and four neutralinos () and in general can mix among one another.
In this paper, we focus on the lightest neutralino (), the next-to-lightest
neutralino (), and the lightest chargino (). If the superpartners of the SM
leptons, the sleptons, are much heavier than the charginos and neutralinos,
decays of the charginos and neutralinos proceed through the , , and Higgs
bosons. The branching fractions of neutralinos to the and Higgs bosons depend
on the mixing among the bino, winos, and higgsinos to form mass eigenstates.

Searches performed at LEP exclude promptly-decaying charginos below a mass of
103.5 [17]. At the LHC, several searches have been performed by the ATLAS [18,
19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29] and CMS [30, 31, 32, 33, 34, 35,
36, 37, 38, 39, 40, 41, 42, 43] Collaborations looking for direct production
of charginos and neutralinos. Given the various possible decay modes, a SUSY
signal could simultaneously populate multiple final states. This paper
implements a statistical combination of the searches performed by CMS in Refs.
[38, 39, 40, 41, 42, 43] covering several final states to improve upon the
sensitivity of the individual analyses, particularly in models where the
neutralino has a nonzero branching fraction to both and Higgs bosons. In
addition, we present an extension of a search selecting events with three or
more charged leptons [38]. It targets the difficult region of phase space
where the difference in mass between the and is approximately equal to the
boson mass, and the signal has similar kinematic properties to the dominant
background of SM $\PW\PZ$ production. All searches use a data sample of LHC
proton-proton collisions at $\sqrt{s}=13\TeV$ collected by the CMS experiment
in 2016, corresponding to an integrated luminosity of 35.9.

##  0.2 Signal models

Simplified models of SUSY [44, 45, 46, 47] are used to interpret the combined
search results presented below. In this paper, “” refers to the 125scalar
boson [48], interpreted as the lightest CP-even state of an extended Higgs
sector. The boson is expected to have SM-like properties if all of the other
Higgs bosons are much heavier [49]. All signal models considered involve the
production of two bosons (, , or ) through SUSY decays, and we denote each
model by the specific bosons produced. The , , and bosons are always assumed
to decay according to their SM branching fractions. The sleptons are always
assumed to have much higher masses than the charginos and neutralinos such
that they do not contribute to the interactions.

The first class of models assumes $\PSGcpmDo\PSGczDt$ production. The is
assumed to be the LSP. The always decays to the boson and the , while the can
decay to either of the or bosons plus the . We consider three choices for the
decay: a branching fraction of 100% to $\PZ\PSGczDo$ ($\PW\PZ$ topology), of
100% to $\PH\PSGczDo$ ($\PW\PH$ topology), and of 50% to each of these two
decays (mixed topology). This model is depicted in Fig. 1, showing the two
possible decays. The production cross sections are computed in the limit of
mass-degenerate winos and , and light bino , with all other sparticles assumed
to be heavy and decoupled.

Figure 1: Production of $\PSGcpmDo\PSGczDt$ with the decaying to a boson and
the LSP, , and the decaying to either (left) a boson and the or (right) a
boson and the .

The second class of models assumes $\PSGczDo\PSGczDo$ production. For bino- or
wino-like neutralinos, the neutralino pair production cross section is very
small, and thus we consider a specific gauge-mediated SUSY breaking (GMSB)
model with quasidegenerate higgsinos as next-to-lightest SUSY particles and an
effectively massless gravitino () as the LSP [50, 51, 52]. In the production
of any two of these, or decays immediately to and low-momentum particles that
do not impact the analysis, effectively yielding pair production of
$\PSGczDo\PSGczDo$. The then decays to a and either a or boson, and we
consider varying branching fractions from 100% decay into the boson to 100%
decay into the boson including intermediate values. The possible decays in
this model are shown in Fig. 2.

The production cross sections for the GMSB scenario are computed in a limit of
mass-degenerate higgsino states , , and , with all the other sparticles
assumed to be heavy and decoupled. Following the convention of real mixing
matrices and signed neutralino masses [53], we set the sign of the mass of ()
to $+1$ ($-1$). The lightest two neutralino states are defined as symmetric
(antisymmetric) combinations of higgsino states by setting the product of the
elements $N_{i3}$ and $N_{i4}$ of the neutralino mixing matrix $N$ to $+0.5$
($-0.5$) for $i=1$ (2). The elements $U_{12}$ and $V_{12}$ of the chargino
mixing matrices $U$ and $V$ are set to 1.

Figure 2: A GMSB model with $\PSGczDo\PSGczDo$ pair production. The two
particles decay into the LSP and (left) both to bosons, (center) a and a
boson, or (right) both to bosons.

Cross section calculations to next-to-leading order (NLO) plus next-to-
leading-logarithmic (NLL) accuracy [54, 55, 56, 57, 58, 59] in perturbative
quantum chromodynamics (QCD) are used to normalize the signal samples for the
results presented in Sections 0.6 and 0.7. In this section, we present cross
sections calculated to NLO accuracy [56] to demonstrate the dependence of the
cross section values on assumptions made in decoupling other SUSY particles.
The same qualitative conclusions also hold for the NLO+NLL calculations used
in the final results.

Figure 3 shows the NLO cross section for $\PSGcpmDo\PSGczDt$ production at
$\sqrt{s}=13\TeV$ assuming mass-degenerate winos and . The various curves show
different assumptions on the masses of squarks () and gluinos (), as described
in the legend. The cross section depends significantly on the masses of the
strongly coupled particles until they reach masses of at least 10. For the
range of and masses considered here, the reduction can make up to 90% in the
cross section value. This is due to large destructive interference effects
from $t$-channel diagrams involving squark exchange. The cross section
calculation used in the interpretations of the analysis results assumes a mass
of 100for the squarks and gluinos to have them fully decoupled. The obtained
results would be less stringent if lower masses were assumed for the squarks
and gluinos. We performed the same study for $\PSGcpmDo\PSGczDt$,
$\PSGcpmDo\PSGczDo$, $\PSGcpmDo\widetilde{\chi}^{\mp}_{1}$, and
$\PSGczDt\PSGczDo$ production with the assumption of mass-degenerate higgsinos
, , and . The dependence of the production cross section on the decoupling
mass assumption was found to be much smaller in the higgsino case, at most a
few percent, and it is small compared to the uncertainty in the cross section
calculation.

Figure 3: Cross section for $\PSGcpmDo\PSGczDt$ production at
$\sqrt{s}=13\TeV$ versus the wino mass, calculated to NLO accuracy in QCD with
Resummino [56]. The and are assumed to be mass-degenerate winos. The various
curves show different assumptions on the masses of the squarks and gluinos, as
described in the legend. The green band shows the theoretical uncertainty in
the cross section calculation, from the variation of renormalization and
factorization scales as well as parton density functions, for the 100squark
and gluino mass assumption.

##  0.3 The CMS detector

The central feature of the CMS apparatus is a superconducting solenoid, 13m in
length and 6m in diameter, that provides an axial magnetic field of 3.8T. The
bore of the solenoid is outfitted with various particle detection systems.
Charged-particle trajectories are measured by silicon pixel and strip
trackers, covering $0<\phi<2\pi$ in azimuth and $\abs{\eta}<2.5$, where the
pseudorapidity $\eta$ is defined as $-\log[\tan(\theta/2)]$, with $\theta$
being the polar angle of the trajectory of the particle with respect to the
clockwise beam direction. A crystal electromagnetic calorimeter (ECAL) and a
brass and scintillator hadron calorimeter (HCAL) surround the tracking volume.
The calorimeters provide energy and direction measurements of electrons,
photons, and hadronic jets. Muons are measured in gas-ionization detectors
embedded in the steel flux-return yoke outside the solenoid. The detector is
nearly hermetic, allowing for energy balance measurements in the plane
transverse to the clockwise beam direction. A two-tier trigger system selects
the most interesting $\Pp\Pp$ collision events for use in physics analysis. 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. [60].

##  0.4 Event reconstruction and Monte Carlo simulation

Event reconstruction is based on the particle-flow (PF) algorithm [61], which
optimally combines information from the tracker, calorimeters, and muon
systems to reconstruct and identify PF candidates, , charged and neutral
hadrons, photons, electrons, and muons. To select collision events, we require
at least one reconstructed vertex. The reconstructed vertex with the largest
value of summed physics-object $\pt^{2}$ is taken to be the primary $\Pp\Pp$
interaction vertex, where is the transverse momentum with respect to the beam
axis. The physics objects are the objects returned by a jet finding algorithm
[62, 63] applied to all charged tracks associated with the vertex, plus the
corresponding associated missing transverse momentum. The missing transverse
momentum vector, , is defined as the negative vector sum of the momenta of all
reconstructed PF candidates projected onto the plane perpendicular to the
proton beams. Its magnitude is referred to as . Events with possible
contributions from beam halo processes or anomalous noise in the calorimeters
can have large values of and are rejected using dedicated filters [64].

Electron candidates are reconstructed starting from a cluster of energy
deposits in the ECAL. The cluster is then matched to a reconstructed track.
The electron selection is based on the shower shape, the ratio of energy
measured in the HCAL to that measured in the ECAL, track-cluster matching, and
consistency between the cluster energy and the track momentum [65]. Muon
candidates are reconstructed by performing a global fit that requires
consistent hit patterns in the tracker and the muon system [66]. Photon
candidates are reconstructed from a cluster of energy deposits in the ECAL,
and they are required to pass criteria based on the shower shape and the ratio
of energy measured in the HCAL to that measured in the ECAL [65]. Hadronically
decaying tau lepton candidates () are reconstructed from PF candidates with
the “hadron-plus-strips” algorithm [67]. Electron, muon, photon, and
candidates are required to be isolated from other particles, and electron,
muon, and candidates must satisfy requirements on the transverse and
longitudinal impact parameters relative to the primary vertex.

PF candidates are clustered to form jets using the anti-clustering algorithm
[62] with a distance parameter of 0.4, as implemented in the package [63].
Identification of jets originating from b quarks (b jets) is performed with
either the combined secondary vertex (CSVv2) algorithm [68] or the DeepCSV
algorithm [69]. Data events are selected using a variety of triggers requiring
the presence of electrons, muons, photons, jets, or , depending on the final
state targeted in each analysis.

Monte Carlo (MC) simulated samples are used in the various searches to
estimate the background from some SM processes, to assess systematic
uncertainties in prediction methods that rely on data, and to calculate the
selection efficiency for signal models. Most SM background samples are
produced with the v2.2.2 or v2.3.3 generator [70] at leading order (LO) or NLO
accuracy in perturbative QCD, including up to four additional partons in the
matrix element calculations, depending on the process and calculation order.
Other samples are produced with the v2 [71, 72] generator without additional
partons in the matrix element calculations. Standard model $\PW\PZ$ production
in particular is modeled with v2.2.2 at NLO precision for the search described
in Section 0.6, which requires a precise description of initial-state
radiation (ISR). In other cases, v2 is used. The NNPDF3.0 LO or NLO [73]
parton distribution functions (PDFs) are used in the event generation. Parton
showering and fragmentation in all of these samples are performed using the
v8.212 [74] generator and the CUETP8M1 tune [75]. A double counting of the
partons generated with and those with is removed using the MLM [76] and the
FxFx [77] matching schemes, in the LO and NLO samples, respectively. Cross
section calculations at NLO or next-to-NLO [70, 78, 79, 80, 81, 82] are used
to normalize the simulated background samples.

Signal samples are generated with at LO precision, including up to two
additional partons in the matrix element calculations. Cross section
calculations to NLO plus NLL accuracy [83, 55, 56] are used to normalize the
signal samples. For these samples we improve on the modeling of ISR, which
affects the total transverse momentum of the system of SUSY particles
($\pt^{\mathrm{ISR}}$), by reweighting the $\pt^{\mathrm{ISR}}$ distribution
in these events. This reweighting procedure is based on experimental studies
of the of bosons [84]. The reweighting factors range between 1.18 (at
$\pt^{\mathrm{ISR}}=125\GeV$) and 0.78 (for $\pt^{\mathrm{ISR}}>600\GeV$). We
take the deviation from 1.0 as the systematic uncertainty in the reweighting
procedure.

For both signal and background events, additional simultaneous proton-proton
interactions (pileup) are generated with and superimposed on the hard
collisions. The response of the CMS detector for SM background samples is
simulated using a -based model [85], while that for new physics signals is
performed using the CMS fast simulation package [86]. All simulated events are
processed with the same chain of reconstruction programs as used for collision
data. Corrections are applied to simulated samples to account for differences
between the trigger, b tagging, and lepton and photon selection efficiencies
measured in data and the simulation. Additional differences arising from the
fast simulation modeling of selection efficiencies, as well as from the
modeling of , are corrected in the fast simulation and included in the
systematic uncertainties considered.

##  0.5 Individual searches

The experimental searches included in the combination are briefly described
here. Table 0.5 lists which searches are used to place exclusion limits for
each of the topologies introduced in Section 0.2. The selections for all
searches were checked to be mutually exclusive, such that no events fulfill
the signal region requirements for more than one search. No significant
deviations from the SM predictions were observed in any of these searches.

Summary of all experimental searches considered in the combination (rows), and
the signal topologies for which each search is used in the combined results
(columns). The searches are described in Sections 0.5.1 through 0.5.6 and
Section 0.6. The ${\geq}3\ell$ search described in Section 0.5.5 is used for
all signal topologies except for $\PW\PZ$, where the reoptimized search
strategy from Section 0.6 is employed instead.  Signal topology Search
$\PW\PZ$ $\PW\PH$ $\PZ\PZ$ $\PZ\PH$ $\PH\PH$ $1\ell$ 2 ✓ 4 ✓ $2\ell$ on- ✓ ✓ ✓
$2\ell$ soft ✓ ${\geq}3\ell$ ✓ ✓ ✓ ✓ ✓ $\PH(\cPgg\cPgg)$ ✓ ✓ ✓

###  0.5.1 Search for one lepton, two b jets, and

The “$1\ell$ 2” search [43], targeting the $\PW\PH$ topology, selects events
with exactly one charged lepton ( or ), exactly two b jets, and large . The
invariant mass of the two b jets is required to be consistent with the mass of
the boson. Kinematic variables are used to suppress backgrounds, which
predominantly come from dileptonic decays in production. Two exclusive signal
regions are defined based on : $125\leq\ptmiss<200\GeV$ and $\ptmiss\geq
200\GeV$. The SM backgrounds are predicted using MC simulation, with the
predictions validated in data control regions distinct from the signal region.

###  0.5.2 Search for four b jets and

The “4” search [41], targeting the $\PH\PH$ topology, selects events with
exactly four or five jets, with at least two of them identified as b jets,
large , and no charged leptons. In each event, the four jets with the highest
b tagging discriminator scores are considered to form dijet candidates. There
are three possible groupings to make two pairs of jets. The grouping is
selected to minimize the difference between the invariant masses of the two
dijet pairs, and the difference in masses is required to be less than 40. The
average invariant mass of the two pairs is then required to be consistent with
the mass of the boson. Exclusive signal regions are defined based on the
number of b jets (three or at least four) and multiple bins in . The primary
background to this search comes from semileptonic decays in production, with
smaller contributions from or production in association with jets and from QCD
multijet production. The backgrounds are predicted using data control samples
that require either exactly two b jets or an average dijet invariant mass
inconsistent with the boson.

###  0.5.3 Search for two leptons consistent with a boson, jets, and

The “$2\ell$ on-” search [42], targeting the $\PW\PZ$, $\PZ\PZ$, and $\PZ\PH$
topologies, selects events with exactly two opposite-sign, same-flavor (OSSF)
leptons ($\Pep\Pem$ or $\Pgmp\Pgmm$) consistent with the boson mass, at least
two jets, and large . In the signal region targeting the $\PW\PZ$ and $\PZ\PZ$
topologies, two jets are required to have an invariant mass less than 110to be
compatible with the and boson masses, and events with b jets are rejected. To
target the $\PZ\PH$ topology, events are required to have two b jets with an
invariant mass less than 150to be compatible with the boson mass. Signal
regions are defined with multiple exclusive bins in . The backgrounds fall
into three categories. First, flavor symmetric backgrounds, such as
production, yield $\Pe^{\pm}\Pgm^{\mp}$ events at the same rate as $\Pep\Pem$
and $\Pgmp\Pgmm$ events combined, and they are predicted from a data control
sample of $\Pe^{\pm}\Pgm^{\mp}$ events. Second, events with a boson and
mismeasured jets give instrumental , and they are predicted from a data
control sample of +jets events. Third, events with a boson and at least one
prompt neutrino, arising from processes such as $\PW\PZ$, $\PZ\PZ$, and
$\ttbar\PZ$ production, are estimated using simulation.

###  0.5.4 Search for two soft leptons and

The “$2\ell$ soft” search [39] selects events with exactly two low- leptons
($\Pep\Pem$ or $\Pgmp\Pgmm$ in the relevant selections), jets, and large . It
targets the $\PW\PZ$ topology where the mass difference between and is small
such that the and bosons are off-shell, and the observable decay products have
low momentum. The leptons are required to satisfy $5<\pt<30\GeV$ and have an
invariant mass in the range $4<m_{\ell\ell}<50\GeV$, strongly suppressing SM
backgrounds while retaining good acceptance for compressed signal scenarios.
Additional kinematic requirements are applied to further reduce backgrounds,
and the relevant signal regions are binned in $m_{\ell\ell}$ and . The largest
backgrounds arise from $\PZ/\gamma^{*}$ and production, as well as
misidentification of nonprompt leptons. The first two are predicted from
simulation with constraints from data control regions, while the latter is
predicted entirely using data.

###  0.5.5 Search for three or more leptons, and

The “${\geq}3\ell$” search [38] selects events with three or more leptons (, ,
and up to two ) and large . Several exclusive categories are defined based on
the number of leptons, lepton flavor and charge, the presence of an OSSF pair,
and kinematic variables such as the invariant mass of the OSSF pair and .
Events with a b jet are rejected to reduce the background from production. The
various categories are designed to give this search sensitivity for a wide
range of new physics models, including all of the topologies introduced in
Section 0.2. The best performance is seen in the $\PW\PZ$ and $\PZ\PZ$ models,
while the lower branching fraction of the boson to leptons reduces the
sensitivity to other models. The SM backgrounds in this search vary across the
categories, and the most important for the relevant regions in these
interpretations are SM $\PW\PZ$ and $\PZ\PZ$ production, and events with
misidentified nonprompt leptons. The former are predicted using simulation,
which in case of $\PW\PZ$ is validated in a set of dedicated control regions,
while the latter are predicted entirely from data.

A further optimization of this analysis has been performed for the $\PW\PZ$
topology in the case where the difference in the masses of and is equal to the
boson mass, focusing on a category selecting events with three light-flavor
leptons (, ). This update is presented in Section 0.6.

###  0.5.6 Search for a boson decaying to diphotons and

The “$\PH(\cPgg\cPgg)$” search [40] selects events with two photons consistent
with the boson mass, along with jets and large . Events are categorized based
on the of the diphoton system, the expected resolution on the diphoton mass,
the presence of two b jets compatible with the or boson masses, and the razor
kinematic variables [87, 88]. It exhibits sensitivity to the $\PW\PH$,
$\PZ\PH$, and $\PH\PH$ topologies. The background arises either from
$\gamma$+jets or SM boson production. The former is estimated using a fit to
the diphoton mass spectrum in a wider range than the signal window, while the
latter is predicted using simulation.

##  0.6 Search for three light leptons consistent with $\PW\PZ$ production and

The multilepton search described in Section 0.5.5 contains a category
selecting events with three light-flavor leptons (, ), two of which must form
an OSSF pair. This final state aims to provide sensitivity for a variety of
SUSY models, including the $\PW\PZ$ topology depicted in Fig. 1 (left). The
dominant background in this search category is SM $\PW\PZ$ production.

Exclusion limits on the $\PW\PZ$ topology were placed in Ref. [38], and the
sensitivity was found to be significantly reduced for
$m_{\PSGczDt}-m_{\PSGczDo}\approx m_{\PZ}$, referred to here as the “$\PW\PZ$
corridor.” In this case, SUSY signal is kinematically similar to the SM
background. We present here a further optimization of the search for the
$\PW\PZ$ topology designed to target this challenging region of phase space.
The search methodology remains the same as in Ref. [38], but the event
categorization has been updated as described below.

We require events to have three light-flavor leptons with two forming an OSSF
pair. Events are categorized using the following kinematic variables: , the
invariant mass $m_{\ell\ell}$ of the OSSF pair, and the transverse mass
$M_{\text{T}}$ of the third lepton computed with respect to . Three bins in
$m_{\ell\ell}$ are defined to separate contributions from on- and off-shell
boson decays, and three bins are defined in $M_{\text{T}}$ to separate the SM
boson contribution.

To improve the separation between signal and background in the $\PW\PZ$
corridor, we exploit ISR by further categorizing the events in , the scalar
sum of the jets with $\pt>30\GeV$. Due to the presence of the LSPs, signal
model points in the $\PW\PZ$ corridor will tend to have more events at high
values of and $M_{\text{T}}$ than the SM background for the same value of ,
with the effect becoming relevant at $m_{\PSGczDo}\approx m_{\PZ}$ and more
pronounced at higher . This is demonstrated in Fig. 4, which shows the
expected distributions of for background and two signal model points after
requiring (left) $\HT<100\GeV$ and (right) $\geq 200\GeV$. The categorization
is applied in the regions $m_{\ell\ell}<75\GeV$ and $75\leq
m_{\ell\ell}<105\GeV$. The full set of search regions is summarized in Table
0.6.

Figure 4: Distributions of for two representative signal points in the
$\PW\PZ$ corridor as well as the expected SM background for $\HT<100$ (left)
and $\geq 200\GeV$ (right). The mass values for the signal points are given as
$(m_{\PSGczDt}/m_{\PSGczDo})$ in . For larger values of , the shape difference
between signal and background becomes more pronounced due to the presence of
LSPs with large Lorentz boost.

Definition of the search regions (SRs) optimized for the $\PW\PZ$ corridor in
the $\PW\PZ$ signal topology. Events must have three leptons (, ) forming at
least one OSSF pair and they are categorized in $m_{\ell\ell}$,
$M_{\text{T}}$, and . Where ranges of values are given, the lower bound is
inclusive while the upper bound is exclusive, , $75\leq m_{\ell\ell}<105\GeV$.
$m_{\ell\ell}$ () $M_{\text{T}}$ () $\ptmiss$ () $\HT<100\GeV$
$100\leq\HT<200\GeV$ $\HT\geq 200\GeV$ 0–75 0–100 50–100 SR 01 SR 12 100–150
SR 02 150–200 SR 03 $\geq$200 SR 04 100–160 50–100 SR 05 SR 13 100–150 SR 06
$\geq$150 SR 07 $\geq$160 50–100 SR 08 SR 14 100–150 SR 09 150–200 SR 10
$\geq$200 SR 11 75–105 0–100 50–100 (WZ CR) SR 27 SR 40 100–150 SR 15 SR 28
150–200 SR 16 SR 29 SR 41 200–250 SR 17 SR 30 250–350 SR 18 SR 31 SR 42
$\geq$350 SR 43 100–160 50–100 SR 19 SR 32 SR 44 100–150 SR 20 SR 33 SR 45
150–200 SR 21 SR 34 SR 46 200–250 SR 22 SR 35 SR 47 250–300 SR 48 $\geq$300 SR
49 $\geq$160 50–100 SR 23 SR 36 SR 50 100–150 SR 24 SR 37 SR 51 150–200 SR 25
SR 38 SR 52 200–250 SR 26 SR 39 SR 53 250–300 SR 54 $\geq$300 SR 55 $\geq$105
0–100 $\geq$50 SR 56 100–160 $\geq$50 SR 57 $\geq$160 $\geq$50 SR 58

The dominant background in this search is SM $\PW\PZ$ production, which
provides a signature very similar to the signal process in the form of three
isolated leptons and substantial due to the neutrino from the boson decay.
This background is estimated from simulation, while two control regions are
used to assess the overall normalization and to validate the modeling of
events at large values of , $M_{\text{T}}$, or both. Further backgrounds arise
from misidentification of nonprompt leptons from processes like production,
external and internal photon conversions, and rare SM processes such as
triboson production, $\ttbar\PW$, and $\ttbar\PZ$. The contribution of the
nonprompt lepton background is predicted using the “tight-to-loose” ratio
method [89], which relies entirely on data. External and internal photon
conversions as well as rare SM processes are predicted from simulation, and a
dedicated data control region is used to constrain the normalization of the
conversion background.

The SM $\PW\PZ$ background normalization is constrained in a data control
region requiring $75\leq m_{\ell\ell}<105\GeV$, $M_{\text{T}}<100\GeV$,
$35<\ptmiss<100\GeV$, and $\HT<100\GeV$. The fraction of selected background
events arising from SM $\PW\PZ$ production in this region is approximately
86%. The validation of the and $M_{\text{T}}$ shape modeling is done using a
data control sample enriched in $\PW\gamma$ events, with the remainder of
events coming mainly from $\PW\mathrm{+jets}$ production. A photon with
$\pt>40\GeV$ is required together with a lepton and $\ptmiss\geq 50\GeV$,
corresponding to a leptonic boson decay. The minimum photon threshold ensures
that the photon does not arise from final-state radiation. The motivation
behind this selection is that the boson $M_{\text{T}}$ distribution in both
$\PW\gamma$ and $\PW\mathrm{+jets}$ events is found to be consistent with that
of SM $\PW\PZ$ production. A systematic uncertainty is assigned to the signal
region bins with high $M_{\text{T}}$ and based on the statistical precision of
this control region.

Distributions of key kinematic observables for the events entering the search
regions are shown in Fig. 5 with two representative signal mass points
included. The data agree with the prediction within systematic uncertainties,
which are dominated at high $M_{\text{T}}$ and by the $\PW\PZ$ control region
statistical precision as described above. This uncertainty is taken as
correlated across signal region bins. The comparison between expected and
observed yields in the search regions is shown in Fig. 6 and Table 0.6. No
significant deviations from the SM expectations are observed. The predicted
background yields and uncertainties presented in this section are used as
inputs to the likelihood fit for interpretation, described in Section 0.7. The
interpretation of the results in the $\PW\PZ$ topology at 95% confidence level
(CL) is presented in Fig. 7. Compared to Ref. [38], the expected lower mass
limit in the $\PW\PZ$ corridor has improved from around
$(m_{\PSGczDt},m_{\PSGczDo})=(200,100)$ to around $(225,125)\GeV$, while the
observed limit has improved by around 60in both mass values. The expected
limit contour for signal points with $m_{\PSGczDt}-m_{\PSGczDo}>m_{\PZ}$ has
also improved by as much as 25due to the new selections. The upper limit on
the $\PSGcpmDo\PSGczDt$ production cross section has improved by a factor of
2.

The event selections listed in Table 0.6 are used to replace the selections
for category A in Ref. [38] in the combination below with other analyses, when
interpreting results in the models with either 100% or 50% branching fraction
to the SUSY $\PW\PZ$ topology. In this case, the systematic uncertainties in
the background prediction are treated as being fully correlated with the other
categories from Ref. [38].

Figure 5: Distributions of the transverse mass of the third lepton with
respect to (upper left), the (upper right), the $m_{\ell\ell}$ of the OSSF
pair (lower left), and the (lower right). Distributions for two signal mass
points in the $\PW\PZ$ corridor are overlaid for illustration. The mass values
for the signal points are given as $(m_{\PSGczDt}/m_{\PSGczDo})$ in . The
bottom panel shows the ratio of observed data to predicted yields. The dark
purple band shows the statistical uncertainty in the background prediction,
while the light blue band shows the total uncertainty. Figure 6: Expected and
observed yield comparison in the search regions. Two example signal mass
points along the $\PW\PZ$ corridor are overlaid for illustration. The mass
values for the signal points are given as $(m_{\PSGczDt}/m_{\PSGczDo})$ in .
The bottom panel shows the ratio of observed data to predicted yields. The
dark purple band shows the statistical uncertainty in the background
prediction, while the light blue band shows the total uncertainty.

Expected and observed event yields in the search regions. For each bin, the
first number corresponds to the expected yield and its total uncertainty while
the second number gives the observation. Where ranges of values are given for
the selections, the lower bound is inclusive while the upper bound is
exclusive, , $75\leq m_{\ell\ell}<105\GeV$.  $m_{\ell\ell}$ () $M_{\text{T}}$
() () $\HT<100\GeV$ $100\leq\HT<200\GeV$ $\HT\geq 200\GeV$ 0–75 0–100 50–100
175 $\pm$ 20 166 39 $\pm$ 6 41 100–150 27 $\pm$ 4 23 150–200 5 $\pm$ 1 6
$\geq$200 2.5 $\pm$ 0.8 1 100–160 50–100 50 $\pm$ 8 56 10 $\pm$ 3 13 100–150
12 $\pm$ 3 13 $\geq$150 1.2 $\pm$ 0.4 1 $\geq$160 50–100 12 $\pm$ 2 13 6 $\pm$
2 11 100–150 11 $\pm$ 3 14 150–200 2.6 $\pm$ 0.9 2 $\geq$200 1.2 $\pm$ 0.5 1
75–105 0–100 50–100 (WZ CR) 279 $\pm$ 34 250 310 $\pm$ 40 292 100–150 286
$\pm$ 44 260 87 $\pm$ 13 81 150–200 62 $\pm$ 14 51 26 $\pm$ 6 20 81 $\pm$ 18
69 200–250 20 $\pm$ 5 10 8 $\pm$ 2 10 250–350 16 $\pm$ 4 9 6 $\pm$ 1 5 25
$\pm$ 6 23 $\geq$350 13 $\pm$ 3 8 100–160 50–100 321 $\pm$ 42 297 54 $\pm$ 8
49 45 $\pm$ 6 45 100–150 50 $\pm$ 14 38 11 $\pm$ 3 11 14 $\pm$ 3 12 150–200 5
$\pm$ 2 2 2.2 $\pm$ 0.9 2 4 $\pm$ 2 5 200–250 1.1 $\pm$ 0.5 2 0.5 $\pm$ 0.4 2
1.9 $\pm$ 0.8 1 250–300 1.8 $\pm$ 0.8 2 $\geq$300 1.0 $\pm$ 0.5 1 $\geq$160
50–100 25 $\pm$ 6 18 6 $\pm$ 2 5 9 $\pm$ 3 12 100–150 12 $\pm$ 5 13 3.0 $\pm$
1.3 2 4 $\pm$ 2 2 150–200 5 $\pm$ 2 5 1.1 $\pm$ 0.4 0 2.0 $\pm$ 0.7 2 200–250
4 $\pm$ 2 2 0.9 $\pm$ 0.4 3 1.5 $\pm$ 0.7 2 250–300 0.6 $\pm$ 0.3 1 $\geq$300
1.1 $\pm$ 0.5 1 $\geq$105 0–100 $\geq$50 173 $\pm$ 21 170 100–160 $\geq$50 44
$\pm$ 7 28 $\geq$160 $\geq$50 23 $\pm$ 6 12

Figure 7:  The 95% confidence level upper limit on the production cross
section in the plane of $m_{\PSGcpmDo}$ and $m_{\PSGczDo}$ for the model of
$\PSGcpmDo\PSGczDt$ production with the $\PW\PZ$ topology, using only the
search requiring three or more leptons as described in Section 0.6. The thick
solid black (dashed red) curve represents the observed (expected) exclusion
contour assuming the theory cross sections. The area below each curve is the
excluded region. The thin dashed red lines indicate the $\pm
1\sigma_{\text{experiment}}$ uncertainty. The thin black lines show the effect
of the theoretical uncertainties (${\pm}1\sigma_{\text{theory}}$) on the
signal cross section. The color scale shows the observed limit at 95% CL on
the signal production cross section.

##  0.7 Interpretation

The results of the searches described in Sections 0.5 and 0.6 are interpreted
using the simplified models introduced in Section 0.2. Cross section limits as
a function of the SUSY particle masses are set using a modified frequentist
approach, employing the CL${}_{\text{s}}$ criterion and an asymptotic
formulation [90, 91, 92, 93]. The uncertainties in the signal efficiency and
acceptance and in the background predictions are incorporated as nuisance
parameters. The observed data yields in control regions are typically
incorporated either by a simultaneous maximum likelihood fit of the signal and
control regions or through parameterization using the gamma function. Other
nuisance parameters are implemented using lognormal functions, whose widths
reflect the size of the systematic uncertainty, or as alternate shapes of the
relevant distributions. Within each signal model, the experimental and
theoretical uncertainties affecting the signal prediction are treated as fully
correlated for all analyses. The dominant uncertainties in the background
predictions are not correlated among analyses as they tend to be either
statistical in nature, arising from independent control regions, or
uncertainties in the prediction methods, which are unique to each analysis.
For each signal topology, the analyses with a check mark in Table 0.5 are
combined to place exclusion limits.

The following sources of uncertainty in the signal acceptance and efficiency
are assumed to be fully correlated among analyses: determination of the
integrated luminosity, lepton identification and isolation efficiency, lepton
efficiency modeling in fast simulation, b tagging efficiency, jet energy
scale, modeling of in fast simulation, modeling of ISR, simulation of pileup,
and variations of the generator factorization and renormalization scales.
Variations in the PDF set used are found to primarily affect the signal
acceptance by changing the distribution of the initially-produced sparticle
pair, $\PSGcpmDo\PSGczDt$ or $\PSGczDo\PSGczDo$. This is already incorporated
in the empirical uncertainty in the modeling of ISR as described in Section
0.4, and we therefore do not apply a dedicated uncertainty in signal
acceptance from PDF variations. All analyses also include the statistical
uncertainty of the simulated signal samples, which is taken as being
uncorrelated in every bin, and the uncertainty in the modeling of the trigger
efficiency, which is also taken as uncorrelated given the different trigger
requirements applied in each analysis. Some analyses have additional
uncertainties beyond these, such as the uncertainty in the modeling of the
diphoton mass resolution for the $\PH(\cPgg\cPgg)$ analysis, which are
analysis-specific and treated as being uncorrelated.

For the models of $\PSGcpmDo\PSGczDt$ production, 95% confidence level
exclusion limits are presented in the plane of $m_{\PSGcpmDo}$ and
$m_{\PSGczDo}$. Figure 8 shows the exclusion limits for the combination of
analyses for the $\PW\PZ$ topology, the $\PW\PH$ topology, and the mixed
topology with 50% branching fraction to each of the $\PW\PZ$ and $\PW\PH$
channels. Figure 9 shows the analysis with the best expected limit for each
point in the plane for the same topologies. The on-dilepton analysis generally
gives the best sensitivity for large values of $\Delta
m=m_{\PSGczDt}-m_{\PSGczDo}$. The search for three light-flavor leptons
provides the best sensitivity at intermediate values of $\Delta m$, including
the region where $\Delta m\approx m_{\PZ}$, while the soft-dilepton analysis
provides unique sensitivity to the smallest values of $\Delta m$. Figure 10
(left) shows the observed and expected limit contours for each of the
individual analyses considered in the combination, and Fig. 10 (right) shows
the results from the combination for all three topologies considered. For a
massless LSP , the combined result gives an observed (expected) limit in
$m_{\PSGcpmDo}$ of about 650 (570)for the $\PW\PZ$ topology, 480 (455)for the
$\PW\PH$ topology, and 535 (440)for the mixed topology. The combination also
excludes intermediate mass values that were not excluded by individual
analyses, including $m_{\PSGcpmDo}$ values between 180 and 240for a massless
LSP in the $\PW\PH$ topology.

Figure 8: The 95% CL upper limits on the production cross sections in the
plane of $m_{\PSGcpmDo}$ and $m_{\PSGczDo}$ for the models of
$\PSGcpmDo\PSGczDt$ production with (upper) the $\PW\PZ$ topology, (middle)
the $\PW\PH$ topology, or (lower) the mixed topology with 50% branching
fraction to each of $\PW\PZ$ and $\PW\PH$. The thick solid black (dashed red)
curve represents the observed (expected) exclusion contour assuming the theory
cross sections. The area below each curve is the excluded region. The thin
dashed red lines indicate the $\pm 1\sigma_{\text{experiment}}$ uncertainty.
The thin black lines show the effect of the theoretical uncertainties ($\pm
1\sigma_{\text{theory}}$) on the signal cross section. The color scale shows
the observed limit at 95% CL on the signal production cross section.

Figure 9: The analysis with the best expected exclusion limit at each point in
the plane of $m_{\PSGcpmDo}$ and $m_{\PSGczDo}$ for the models of
$\PSGcpmDo\PSGczDt$ production with (upper) the $\PW\PZ$ topology, (middle)
the $\PW\PH$ topology, and (lower) the mixed topology 50% branching fraction
to each of $\PW\PZ$ and $\PW\PH$.

Figure 10: Exclusion contours at 95% CL in the plane of $m_{\PSGcpmDo}$ and
$m_{\PSGczDo}$ for the models of $\PSGcpmDo\PSGczDt$ production (left) for the
individual analyses and (right) for the combination of analyses. The decay
modes assumed for each contour are given in the legends.

For the models of $\PSGczDo\PSGczDo$ production, the exclusion limits are
presented in the plane of $m_{\PSGczDo}$ and the branching fraction
$\mathcal{B}(\PSGczDo\to\PH\PXXSG)$. The decay $\PSGczDo\to\PZ\PXXSG$ is
assumed to make up the remainder of the branching fraction. Figure 11 shows
the observed and expected limits from the combination in this plane. The
expected mass exclusion limit varies between about 550 and 750, being least
stringent around $\mathcal{B}(\PSGczDo\to\PH\PXXSG)=0.4$. The observed limit
ranges between about 650 and 750, allowing us to exclude masses below
650independent of this branching fraction.

Figure 12 shows the observed limits from each analysis separately compared
with the combined result. Figure 13 shows the analysis with the best expected
exclusion limit for each point in the same plane. At higher values of
$m_{\PSGczDo}$, the searches for at least one hadronically decaying boson
provide the best sensitivity, the 4 search when
$\mathcal{B}(\PSGczDo\to\PH\PXXSG)$ is large and the on-dilepton search when
it is smaller. At lower values of $m_{\PSGczDo}$, below around 200, the
$\PH(\cPgg\cPgg)$ analysis is most sensitive when
$\mathcal{B}(\PSGczDo\to\PH\PXXSG)$ is large, while the three or more lepton
search is dominant when it is small. Figure 14 then shows the exclusion limits
as a function of $m_{\PSGczDo}$ for three choices of
$\mathcal{B}(\PSGczDo\to\PH\PXXSG)$: 0%, yielding the $\PZ\PZ$ topology; 100%,
yielding the $\PH\PH$ topology; and 50%, yielding a mix of events from the
$\PZ\PZ$, $\PH\PH$, and $\PZ\PH$ topologies.

Figure 11: Combined exclusion contours at the 95% CL in the plane of
$m_{\PSGczDo}$ and $\mathcal{B}(\PSGczDo\to\PH\PXXSG)$ for the model of
$\PSGczDo\PSGczDo$ production. The area to the left of or below the solid
(dashed) black curve represents the observed (expected) exclusion region. The
green and yellow bands indicate the $\pm$1 and 2$\sigma$ uncertainties in the
expected limit. The thin black lines show the effect of the theoretical
uncertainties (${\pm}1\sigma_{\text{theory}}$) on the signal cross section.
Figure 12: Observed exclusion contours at the 95% CL in the plane of
$m_{\PSGczDo}$ and $\mathcal{B}(\PSGczDo\to\PH\PXXSG)$ for the model of
$\PSGczDo\PSGczDo$ production for each individual analysis compared with the
combination. For the 4 contour, the region above is excluded, while for all
others, the region to the left is excluded. The 4 search drives the exclusion
at large values of $\mathcal{B}(\PSGczDo\to\PH\PXXSG)$ while the on-dilepton
and multilepton searches are competing at lower values of
$\mathcal{B}(\PSGczDo\to\PH\PXXSG)$.  Figure 13: The analysis with the best
expected exclusion limit at each point in the plane of $m_{\PSGczDo}$ and
$\mathcal{B}(\PSGczDo\to\PH\PXXSG)$ for the model of $\PSGczDo\PSGczDo$
production.

Figure 14: The 95% CL upper limits on the production cross sections as a
function of $m_{\PSGczDo}$ for the model of $\PSGczDo\PSGczDo$ production with
three choices of $\mathcal{B}(\PSGczDo\to\PH\PXXSG)$: (upper) 0%, yielding the
$\PZ\PZ$ topology, (middle) 100%, yielding the $\PH\PH$ topology, and (lower)
50%, yielding the $\PZ\PH$ mixed topology. The solid black line represents the
observed exclusion. The dashed black line represents the expected exclusion,
while the green and yellow bands indicate the $\pm$1 and 2$\sigma$
uncertainties in the expected limit. The red line shows the theoretical cross
section with its uncertainty. The other lines in each plot show the observed
exclusion for individual analyses.

##  0.8 Summary

A number of searches for the electroweak production of charginos and
neutralinos predicted in supersymmetry (SUSY) have been performed in different
final states. All searches considered here use proton-proton collision data at
$\sqrt{s}=13\TeV$, recorded with the CMS detector at the LHC and corresponding
to an integrated luminosity of $35.9\fbinv$. No significant deviations from
the standard model expectations have been observed.

A targeted search requiring three or more charged leptons (electrons or muons)
has been presented, focusing on chargino-neutralino production where the
difference in mass between and is approximately equal to the mass of the
boson, and no significant deviations from the standard model predictions are
observed. This search is interpreted in a simplified model scenario of SUSY
chargino-neutralino ($\PSGcpmDo\PSGczDt$) production with decays
$\PSGcpmDo\to\PW^{\pm}\PSGczDo$ and $\PSGczDt\to\PZ\PSGczDo$, where is the
lightest SUSY particle (LSP). In the targeted phase space, the expected and
observed 95% confidence level exclusion limits extend to 225in the mass of and
125in the mass of , improving the observed limits from the previous
publication by up to 60 [38].

A statistical combination of several searches is performed and interpreted in
the context of simplified models of either chargino-neutralino production, or
neutralino pair production in a gauge-mediated SUSY breaking (GMSB) scenario.
For a massless LSP in the chargino-neutralino model, the combined result gives
an observed (expected) limit in the mass of about 650 (570)for the $\PW\PZ$
topology, 480 (455)for the $\PW\PH$ topology, and 535 (440)for the mixed
topology. Compared to the results of individual analyses, the combination
improves the observed exclusion limit by up to 40in the masses of and in the
chargino-neutralino model. The combination also excludes intermediate mass
values that were not excluded by individual analyses, including masses between
180 and 240in the $\PW\PH$ topology. In the GMSB neutralino pair model, the
combined result gives an observed (expected) limit in the mass of 650–750
(550–750). The combined result improves the observed limit by up to 200in the
mass of in the GMSB neutralino pair model, depending on the branching
fractions for the SUSY particle decays. These results represent the most
stringent constraints to date for all models considered.

###### Acknowledgements.

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

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##  .9 The CMS Collaboration

Yerevan Physics Institute, Yerevan, Armenia
A.M. Sirunyan, A. Tumasyan Institut für Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, E. Brondolin, M.
Dragicevic, J. Erö, M. Flechl, M. Friedl, R. Frühwirth1, V.M. Ghete, J.
Grossmann, J. Hrubec, M. Jeitler1, A. König, N. Krammer, I. Krätschmer, D.
Liko, T. Madlener, I. Mikulec, E. Pree, N. Rad, H. Rohringer, J. Schieck1, R.
Schöfbeck, M. Spanring, D. Spitzbart, W. Waltenberger, J. Wittmann, C.-E.
Wulz1, M. Zarucki Institute for Nuclear Problems, Minsk, Belarus
V. Chekhovsky, V. Mossolov, J. Suarez Gonzalez Universiteit Antwerpen,
Antwerpen, Belgium
E.A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, M. Van De Klundert, H. Van
Haevermaet, P. Van Mechelen, N. Van Remortel Vrije Universiteit Brussel,
Brussel, Belgium
S. Abu Zeid, F. Blekman, J. D’Hondt, I. De Bruyn, J. De Clercq, K. Deroover,
G. Flouris, D. Lontkovskyi, S. Lowette, I. Marchesini, S. Moortgat, L.
Moreels, Q. Python, K. Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders,
I. Van Parijs Université Libre de Bruxelles, Bruxelles, Belgium
D. Beghin, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, B. Dorney, G.
Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk, T. Lenzi, J. Luetic, T.
Maerschalk, A. Marinov, T. Seva, E. Starling, C. Vander Velde, P. Vanlaer, D.
Vannerom, R. Yonamine, F. Zenoni, F. Zhang2 Ghent University, Ghent, Belgium
A. Cimmino, T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov3, D.
Poyraz, C. Roskas, S. Salva, M. Tytgat, W. Verbeke, N. Zaganidis Université
Catholique de Louvain, Louvain-la-Neuve, Belgium
H. Bakhshiansohi, O. Bondu, S. Brochet, G. Bruno, C. Caputo, A. Caudron, P.
David, S. De Visscher, C. Delaere, M. Delcourt, B. Francois, A. Giammanco, M.
Komm, G. Krintiras, V. Lemaitre, A. Magitteri, A. Mertens, M. Musich, K.
Piotrzkowski, L. Quertenmont, A. Saggio, M. Vidal Marono, S. Wertz, J. Zobec
Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil
W.L. Aldá Júnior, F.L. Alves, G.A. Alves, L. Brito, M. Correa Martins Junior,
C. Hensel, A. Moraes, M.E. Pol, P. Rebello Teles Universidade do Estado do Rio
de Janeiro, Rio de Janeiro, Brazil
E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato4, E. Coelho, E.M.
Da Costa, G.G. Da Silveira5, D. De Jesus Damiao, S. Fonseca De Souza, L.M.
Huertas Guativa, H. Malbouisson, M. Melo De Almeida, C. Mora Herrera, L.
Mundim, H. Nogima, L.J. Sanchez Rosas, A. Santoro, A. Sznajder, M. Thiel, E.J.
Tonelli Manganote4, F. Torres Da Silva De Araujo, A. Vilela Pereira
Universidade Estadual Paulista a, Universidade Federal do ABC b, São Paulo,
Brazil
S. Ahujaa, C.A. Bernardesa, T.R. Fernandez Perez Tomeia, E.M. Gregoresb, P.G.
Mercadanteb, S.F. Novaesa, Sandra S. Padulaa, D. Romero Abadb, J.C. Ruiz
Vargasa Institute for Nuclear Research and Nuclear Energy, Bulgarian Academy
of Sciences, Sofia, Bulgaria
A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Misheva, M. Rodozov, M. Shopova,
G. Sultanov University of Sofia, Sofia, Bulgaria
A. Dimitrov, L. Litov, B. Pavlov, P. Petkov Beihang University, Beijing, China
W. Fang6, X. Gao6, L. Yuan Institute of High Energy Physics, Beijing, China
M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D.
Leggat, H. Liao, Z. Liu, F. Romeo, S.M. Shaheen, A. Spiezia, J. Tao, C. Wang,
Z. Wang, E. Yazgan, H. Zhang, S. Zhang, J. Zhao State Key Laboratory of
Nuclear Physics and Technology, Peking University, Beijing, China
Y. Ban, G. Chen, Q. Li, S. Liu, Y. Mao, S.J. Qian, D. Wang, Z. Xu Universidad
de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, C.A. Carrillo Montoya, L.F. Chaparro Sierra, C. Florez,
C.F. González Hernández, J.D. Ruiz Alvarez, M.A. Segura Delgado University of
Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval
Architecture, Split, Croatia
B. Courbon, N. Godinovic, D. Lelas, I. Puljak, P.M. Ribeiro Cipriano, T.
Sculac University of Split, Faculty of Science, Split, Croatia
Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia
V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, A. Starodumov7, T. Susa
University of Cyprus, Nicosia, Cyprus
M.W. Ather, A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos,
P.A. Razis, H. Rykaczewski Charles University, Prague, Czech Republic
M. Finger8, M. Finger Jr.8 Universidad San Francisco de Quito, Quito, Ecuador
E. Carrera Jarrin Academy of Scientific Research and Technology of the Arab
Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt
A.A. Abdelalim9,10, Y. Mohammed11, E. Salama12,13 National Institute of
Chemical Physics and Biophysics, Tallinn, Estonia
R.K. Dewanjee, M. Kadastik, L. Perrini, M. Raidal, A. Tiko, C. Veelken
Department of Physics, University of Helsinki, Helsinki, Finland
P. Eerola, H. Kirschenmann, J. Pekkanen, M. Voutilainen Helsinki Institute of
Physics, Helsinki, Finland
J. Havukainen, J.K. Heikkilä, T. Järvinen, V. Karimäki, R. Kinnunen, T.
Lampén, K. Lassila-Perini, S. Laurila, S. Lehti, T. Lindén, P. Luukka, H.
Siikonen, E. Tuominen, J. Tuominiemi Lappeenranta University of Technology,
Lappeenranta, Finland
T. Tuuva IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
M. Besancon, F. Couderc, M. Dejardin, D. Denegri, J.L. Faure, F. Ferri, S.
Ganjour, S. Ghosh, P. Gras, G. Hamel de Monchenault, P. Jarry, I. Kucher, C.
Leloup, E. Locci, M. Machet, J. Malcles, G. Negro, J. Rander, A. Rosowsky,
M.Ö. Sahin, M. Titov Laboratoire Leprince-Ringuet, Ecole polytechnique,
CNRS/IN2P3, Université Paris-Saclay, Palaiseau, France
A. Abdulsalam, C. Amendola, I. Antropov, S. Baffioni, F. Beaudette, P. Busson,
L. Cadamuro, C. Charlot, R. Granier de Cassagnac, M. Jo, S. Lisniak, A.
Lobanov, J. Martin Blanco, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P.
Pigard, R. Salerno, J.B. Sauvan, Y. Sirois, A.G. Stahl Leiton, T. Strebler, Y.
Yilmaz, A. Zabi, A. Zghiche Université de Strasbourg, CNRS, IPHC UMR 7178,
F-67000 Strasbourg, France
J.-L. Agram14, J. Andrea, D. Bloch, J.-M. Brom, M. Buttignol, E.C. Chabert, N.
Chanon, C. Collard, E. Conte14, X. Coubez, 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, R. Chierici, D. Contardo, P. Depasse, H.
El Mamouni, J. Fay, L. Finco, S. Gascon, M. Gouzevitch, G. Grenier, B. Ille,
F. Lagarde, I.B. Laktineh, M. Lethuillier, L. Mirabito, A.L. Pequegnot, S.
Perries, A. Popov15, V. Sordini, M. Vander Donckt, S. Viret Georgian Technical
University, Tbilisi, Georgia
A. Khvedelidze8 Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze8 RWTH Aachen University, I. Physikalisches Institut, Aachen,
Germany
C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, C.
Schomakers, J. Schulz, V. Zhukov15 RWTH Aachen University, III. Physikalisches
Institut A, Aachen, Germany
A. Albert, E. Dietz-Laursonn, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg,
T. Esch, R. Fischer, A. Güth, M. Hamer, T. Hebbeker, C. Heidemann, K.
Hoepfner, S. Knutzen, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, T.
Pook, M. Radziej, H. Reithler, M. Rieger, F. Scheuch, D. Teyssier, S. Thüer
RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany
G. Flügge, B. Kargoll, T. Kress, A. Künsken, T. Müller, A. Nehrkorn, A.
Nowack, C. Pistone, O. Pooth, A. Stahl16 Deutsches Elektronen-Synchrotron,
Hamburg, Germany
M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, K. Beernaert, O. Behnke, U.
Behrens, A. Bermúdez Martínez, A.A. Bin Anuar, K. Borras17, V. Botta, A.
Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G.
Eckerlin, D. Eckstein, T. Eichhorn, E. Eren, E. Gallo18, J. Garay Garcia, A.
Geiser, J.M. Grados Luyando, A. Grohsjean, P. Gunnellini, M. Guthoff, A. Harb,
J. Hauk, M. Hempel19, H. Jung, M. Kasemann, J. Keaveney, C. Kleinwort, I.
Korol, D. Krücker, W. Lange, A. Lelek, T. Lenz, J. Leonard, K. Lipka, W.
Lohmann19, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, G. Mittag, J. Mnich,
A. Mussgiller, E. Ntomari, D. Pitzl, A. Raspereza, M. Savitskyi, P. Saxena, R.
Shevchenko, S. Spannagel, N. Stefaniuk, G.P. Van Onsem, R. Walsh, Y. Wen, K.
Wichmann, C. Wissing, O. Zenaiev University of Hamburg, Hamburg, Germany
R. Aggleton, S. Bein, V. Blobel, M. Centis Vignali, T. Dreyer, E. Garutti, D.
Gonzalez, J. Haller, A. Hinzmann, M. Hoffmann, A. Karavdina, R. Klanner, R.
Kogler, N. Kovalchuk, S. Kurz, T. Lapsien, D. Marconi, M. Meyer, M. Niedziela,
D. Nowatschin, F. Pantaleo16, T. Peiffer, A. Perieanu, C. Scharf, P. Schleper,
A. Schmidt, S. Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G. Steinbrück,
F.M. Stober, M. Stöver, H. Tholen, D. Troendle, E. Usai, A. Vanhoefer, B.
Vormwald Institut für Experimentelle Kernphysik, Karlsruhe, Germany
M. Akbiyik, C. Barth, M. Baselga, S. Baur, E. Butz, R. Caspart, T. Chwalek, F.
Colombo, W. De Boer, A. Dierlamm, N. Faltermann, B. Freund, R. Friese, M.
Giffels, M.A. Harrendorf, F. Hartmann16, S.M. Heindl, U. Husemann, F.
Kassel16, S. Kudella, H. Mildner, M.U. Mozer, Th. Müller, M. Plagge, G. Quast,
K. Rabbertz, M. Schröder, I. Shvetsov, G. Sieber, H.J. Simonis, R. Ulrich, S.
Wayand, M. Weber, T. Weiler, S. Williamson, C. Wöhrmann, R. Wolf Institute of
Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece
G. Anagnostou, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas, I. Topsis-
Giotis National and Kapodistrian University of Athens, Athens, Greece
G. Karathanasis, S. Kesisoglou, A. Panagiotou, N. Saoulidou National Technical
University of Athens, Athens, Greece
K. Kousouris University of Ioánnina, Ioánnina, Greece
I. Evangelou, C. Foudas, P. Kokkas, S. Mallios, N. Manthos, I. Papadopoulos,
E. Paradas, J. Strologas, F.A. Triantis MTA-ELTE Lendület CMS Particle and
Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary
M. Csanad, N. Filipovic, G. Pasztor, O. Surányi, G.I. Veres20 Wigner Research
Centre for Physics, Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath21, Á. Hunyadi, F. Sikler, V. Veszpremi
Institute of Nuclear Research ATOMKI, Debrecen, Hungary
N. Beni, S. Czellar, J. Karancsi22, A. Makovec, J. Molnar, Z. Szillasi
Institute of Physics, University of Debrecen, Debrecen, Hungary
M. Bartók20, P. Raics, Z.L. Trocsanyi, B. Ujvari Indian Institute of Science
(IISc), Bangalore, India
S. Choudhury, J.R. Komaragiri National Institute of Science Education and
Research, Bhubaneswar, India
S. Bahinipati23, S. Bhowmik, P. Mal, K. Mandal, A. Nayak24, D.K. Sahoo23, N.
Sahoo, S.K. Swain Panjab University, Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, R. Chawla, N. Dhingra, A.K. Kalsi, A.
Kaur, M. Kaur, S. Kaur, R. Kumar, P. Kumari, A. Mehta, J.B. Singh, G. Walia
University of Delhi, Delhi, India
Ashok Kumar, Aashaq Shah, A. Bhardwaj, S. Chauhan, B.C. Choudhary, R.B. Garg,
S. Keshri, A. Kumar, S. Malhotra, M. Naimuddin, K. Ranjan, R. Sharma Saha
Institute of Nuclear Physics, HBNI, Kolkata, India
R. Bhardwaj, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep, S. Dey, S. Dutt,
S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S.
Nandan, A. Purohit, A. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur
Indian Institute of Technology Madras, Madras, India
P.K. Behera Bhabha Atomic Research Centre, Mumbai, India
R. Chudasama, D. Dutta, V. Jha, V. Kumar, A.K. Mohanty16, P.K. Netrakanti,
L.M. Pant, P. Shukla, A. Topkar Tata Institute of Fundamental Research-A,
Mumbai, India
T. Aziz, S. Dugad, B. Mahakud, S. Mitra, G.B. Mohanty, N. Sur, B. Sutar Tata
Institute of Fundamental Research-B, Mumbai, India
S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, Sa. Jain, S.
Kumar, M. Maity25, G. Majumder, K. Mazumdar, T. Sarkar25, N. Wickramage26
Indian Institute of Science Education and Research (IISER), Pune, India
S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, S.
Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
S. Chenarani27, E. Eskandari Tadavani, S.M. Etesami27, M. Khakzad, M.
Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi28, F. Rezaei
Hosseinabadi, B. Safarzadeh29, M. Zeinali University College Dublin, Dublin,
Ireland
M. Felcini, M. Grunewald INFN Sezione di Bari a, Università di Bari b,
Politecnico di Bari c, Bari, Italy
M. Abbresciaa,b, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L. Cristellaa,b,
N. De Filippisa,c, M. De Palmaa,b, F. Erricoa,b, L. Fiorea, G. Iasellia,c, S.
Lezkia,b, G. Maggia,c, M. Maggia, G. Minielloa,b, S. Mya,b, S. Nuzzoa,b, A.
Pompilia,b, G. Pugliesea,c, R. Radognaa, A. Ranieria, G. Selvaggia,b, A.
Sharmaa, L. Silvestrisa,16, R. Vendittia, P. Verwilligena INFN Sezione di
Bologna a, Università di Bologna b, Bologna, Italy
G. Abbiendia, C. Battilanaa,b, D. Bonacorsia,b, L. Borgonovia,b, S. Braibant-
Giacomellia,b, R. Campaninia,b, P. Capiluppia,b, A. Castroa,b, F.R. Cavalloa,
S.S. Chhibraa, G. Codispotia,b, M. Cuffiania,b, G.M. Dallavallea, F. Fabbria,
A. Fanfania,b, D. Fasanellaa,b, P. Giacomellia, C. Grandia, L. Guiduccia,b, S.
Marcellinia, G. Masettia, A. Montanaria, F.L. Navarriaa,b, A. Perrottaa, A.M.
Rossia,b, T. Rovellia,b, G.P. Sirolia,b, N. Tosia INFN Sezione di Catania a,
Università di Catania b, Catania, Italy
S. Albergoa,b, S. Costaa,b, A. Di Mattiaa, F. Giordanoa,b, R. Potenzaa,b, A.
Tricomia,b, C. Tuvea,b INFN Sezione di Firenze a, Università di Firenze b,
Firenze, Italy
G. Barbaglia, K. Chatterjeea,b, V. Ciullia,b, C. Civininia, R.
D’Alessandroa,b, E. Focardia,b, P. Lenzia,b, M. Meschinia, S. Paolettia, L.
Russoa,30, G. Sguazzonia, D. Stroma, L. Viliania,b,16 INFN Laboratori
Nazionali di Frascati, Frascati, Italy
L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera16 INFN Sezione di
Genova a, Università di Genova b, Genova, Italy
V. Calvellia,b, F. Ferroa, E. Robuttia, S. Tosia,b INFN Sezione di Milano-
Bicocca a, Università di Milano-Bicocca b, Milano, Italy
A. Benagliaa, A. Beschib, L. Brianzaa,b, F. Brivioa,b, V. Cirioloa,b,16, M.E.
Dinardoa,b, S. Fiorendia,b, S. Gennaia, A. Ghezzia,b, P. Govonia,b, M.
Malbertia,b, S. Malvezzia, R.A. Manzonia,b, D. Menascea, L. Moronia, M.
Paganonia,b, K. Pauwelsa,b, D. Pedrinia, S. Pigazzinia,b,31, S. Ragazzia,b, T.
Tabarelli de Fatisa,b INFN Sezione di Napoli a, Università di Napoli ’Federico
II’ b, Napoli, Italy, Università della Basilicata c, Potenza, Italy,
Università G. Marconi d, Roma, Italy
S. Buontempoa, N. Cavalloa,c, S. Di Guidaa,d,16, F. Fabozzia,c, F. Fiengaa,b,
A.O.M. Iorioa,b, W.A. Khana, L. Listaa, S. Meolaa,d,16, P. Paoluccia,16, C.
Sciaccaa,b, F. Thyssena INFN Sezione di Padova a, Università di Padova b,
Padova, Italy, Università di Trento c, Trento, Italy
P. Azzia, N. Bacchettaa, L. Benatoa,b, D. Biselloa,b, A. Bolettia,b, R.
Carlina,b, A. Carvalho Antunes De Oliveiraa,b, P. Checchiaa, P. De Castro
Manzanoa, T. Dorigoa, U. Dossellia, F. Gasparinia,b, U. Gasparinia,b, A.
Gozzelinoa, S. Lacapraraa, M. Margonia,b, A.T. Meneguzzoa,b, N. Pozzobona,b,
P. Ronchesea,b, R. Rossina,b, F. Simonettoa,b, E. Torassaa, M. Zanettia,b, P.
Zottoa,b, G. Zumerlea,b INFN Sezione di Pavia a, Università di Pavia b, Pavia,
Italy
A. Braghieria, A. Magnania, P. Montagnaa,b, S.P. Rattia,b, V. Rea, M.
Ressegottia,b, C. Riccardia,b, P. Salvinia, I. Vaia,b, P. Vituloa,b INFN
Sezione di Perugia a, Università di Perugia b, Perugia, Italy
L. Alunni Solestizia,b, M. Biasinia,b, G.M. Bileia, C. Cecchia,b, D.
Ciangottinia,b, L. Fanòa,b, P. Laricciaa,b, R. Leonardia,b, E. Manonia, G.
Mantovania,b, V. Mariania,b, M. Menichellia, A. Rossia,b, A. Santocchiaa,b, D.
Spigaa INFN Sezione di Pisa a, Università di Pisa b, Scuola Normale Superiore
di Pisa c, Pisa, Italy
K. Androsova, P. Azzurria,16, G. Bagliesia, T. Boccalia, L. Borrello, R.
Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, G. Fedia, L. Gianninia,c, A.
Giassia, M.T. Grippoa,30, F. Ligabuea,c, T. Lomtadzea, E. Mancaa,c, G.
Mandorlia,c, A. Messineoa,b, F. Pallaa, A. Rizzia,b, A. Savoy-Navarroa,32, P.
Spagnoloa, R. Tenchinia, G. Tonellia,b, A. Venturia, P.G. Verdinia INFN
Sezione di Roma a, Sapienza Università di Roma b, Rome, Italy
L. Baronea,b, F. Cavallaria, M. Cipriania,b, N. Dacia, D. Del Rea,b, E. Di
Marcoa,b, M. Diemoza, S. Gellia,b, E. Longoa,b, F. Margarolia,b, B.
Marzocchia,b, P. Meridiania, G. Organtinia,b, R. Paramattia,b, F. Preiatoa,b,
S. Rahatloua,b, C. Rovellia, F. Santanastasioa,b INFN Sezione di Torino a,
Università di Torino b, Torino, Italy, Università del Piemonte Orientale c,
Novara, Italy
N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, N. Bartosika,
R. Bellana,b, C. Biinoa, N. Cartigliaa, F. Cennaa,b, M. Costaa,b, R.
Covarellia,b, A. Deganoa,b, N. Demariaa, B. Kiania,b, C. Mariottia, S.
Masellia, E. Migliorea,b, V. Monacoa,b, E. Monteila,b, M. Montenoa, M.M.
Obertinoa,b, L. Pachera,b, N. Pastronea, M. Pelliccionia, G.L. Pinna
Angionia,b, F. Raveraa,b, A. Romeroa,b, M. Ruspaa,c, R. Sacchia,b, K.
Shchelinaa,b, V. Solaa, A. Solanoa,b, A. Staianoa, P. Traczyka,b INFN Sezione
di Trieste a, Università di Trieste b, Trieste, Italy
S. Belfortea, M. Casarsaa, F. Cossuttia, G. Della Riccaa,b, A. Zanettia
Kyungpook National University, Daegu, Korea
D.H. Kim, G.N. Kim, M.S. Kim, J. Lee, S. Lee, S.W. Lee, C.S. Moon, Y.D. Oh, S.
Sekmen, D.C. Son, Y.C. Yang Chonbuk National University, Jeonju, Korea
A. Lee Chonnam National University, Institute for Universe and Elementary
Particles, Kwangju, Korea
H. Kim, D.H. Moon, G. Oh Hanyang University, Seoul, Korea
J.A. Brochero Cifuentes, J. Goh, T.J. Kim Korea University, Seoul, Korea
S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, Y. Kim, K. Lee, K.S.
Lee, S. Lee, J. Lim, S.K. Park, Y. Roh Seoul National University, Seoul, Korea
J. Almond, J. Kim, J.S. Kim, H. Lee, K. Lee, K. Nam, S.B. Oh, B.C. Radburn-
Smith, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu University of Seoul, Seoul,
Korea
H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park Sungkyunkwan University, Suwon, Korea
Y. Choi, C. Hwang, J. Lee, I. Yu Vilnius University, Vilnius, Lithuania
V. Dudenas, A. Juodagalvis, J. Vaitkus National Centre for Particle Physics,
Universiti Malaya, Kuala Lumpur, Malaysia
I. Ahmed, Z.A. Ibrahim, M.A.B. Md Ali33, F. Mohamad Idris34, W.A.T. Wan
Abdullah, M.N. Yusli, Z. Zolkapli Centro de Investigacion y de Estudios
Avanzados del IPN, Mexico City, Mexico
Reyes-Almanza, R, Ramirez-Sanchez, G., Duran-Osuna, M. C., H. Castilla-Valdez,
E. De La Cruz-Burelo, I. Heredia-De La Cruz35, Rabadan-Trejo, R. I., R. Lopez-
Fernandez, J. Mejia Guisao, A. Sanchez-Hernandez Universidad Iberoamericana,
Mexico City, Mexico
S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita
Universidad Autonoma de Puebla, Puebla, Mexico
J. Eysermans, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad
Autónoma de San Luis Potosí, San Luis Potosí, Mexico
A. Morelos Pineda University of Auckland, Auckland, New Zealand
D. Krofcheck University of Canterbury, Christchurch, New Zealand
P.H. Butler National Centre for Physics, Quaid-I-Azam University, Islamabad,
Pakistan
A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, A. Saddique, M.A. Shah, M.
Shoaib, M. Waqas National Centre for Nuclear Research, Swierk, Poland
H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Górski, M. Kazana, K.
Nawrocki, M. Szleper, P. Zalewski Institute of Experimental Physics, Faculty
of Physics, University of Warsaw, Warsaw, Poland
K. Bunkowski, A. Byszuk36, K. Doroba, A. Kalinowski, M. Konecki, J.
Krolikowski, M. Misiura, M. Olszewski, A. Pyskir, M. Walczak Laboratório de
Instrumentação e Física Experimental de Partículas, Lisboa, Portugal
P. Bargassa, C. Beirão Da Cruz E Silva, A. Di Francesco, P. Faccioli, B.
Galinhas, M. Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias, M.V.
Nemallapudi, J. Seixas, G. Strong, O. Toldaiev, D. Vadruccio, J. Varela Joint
Institute for Nuclear Research, Dubna, Russia
S. Afanasiev, V. Alexakhin, P. Bunin, M. Gavrilenko, A. Golunov, I. Golutvin,
N. Gorbounov, V. Karjavin, A. Lanev, A. Malakhov, V. Matveev37,38, V.
Palichik, V. Perelygin, M. Savina, S. Shmatov, N. Skatchkov, V. Smirnov, A.
Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg),
Russia
Y. Ivanov, V. Kim39, E. Kuznetsova40, P. Levchenko, V. Murzin, V. Oreshkin, I.
Smirnov, V. Sulimov, L. Uvarov, S. Vavilov, A. Vorobyev Institute for Nuclear
Research, Moscow, Russia
Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov,
N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical
and Experimental Physics, Moscow, Russia
V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G.
Safronov, A. Spiridonov, A. Stepennov, M. Toms, E. Vlasov, A. Zhokin Moscow
Institute of Physics and Technology, Moscow, Russia
T. Aushev, A. Bylinkin38 National Research Nuclear University ’Moscow
Engineering Physics Institute’ (MEPhI), Moscow, Russia
R. Chistov41, M. Danilov41, P. Parygin, D. Philippov, S. Polikarpov, E.
Tarkovskii P.N. Lebedev Physical Institute, Moscow, Russia
V. Andreev, M. Azarkin38, I. Dremin38, M. Kirakosyan38, A. Terkulov Skobeltsyn
Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow,
Russia
A. Baskakov, A. Belyaev, E. Boos, M. Dubinin42, L. Dudko, A. Ershov, A.
Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, S.
Petrushanko, V. Savrin, A. Snigirev Novosibirsk State University (NSU),
Novosibirsk, Russia
V. Blinov43, D. Shtol43, Y. Skovpen43 State Research Center of Russian
Federation, Institute for High Energy Physics of NRC "Kurchatov
Institute", Protvino, Russia
I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, V. Kachanov, A. Kalinin,
D. Konstantinov, P. Mandrik, V. Petrov, R. Ryutin, A. Sobol, S. Troshin, N.
Tyurin, A. Uzunian, A. Volkov University of Belgrade, Faculty of Physics and
Vinca Institute of Nuclear Sciences, Belgrade, Serbia
P. Adzic44, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic, V. Rekovic
Centro de Investigaciones Energéticas Medioambientales y Tecnológicas
(CIEMAT), Madrid, Spain
J. Alcaraz Maestre, M. Barrio Luna, M. Cerrada, N. Colino, B. De La Cruz, A.
Delgado Peris, A. Escalante Del Valle, C. Fernandez Bedoya, J.P. Fernández
Ramos, J. Flix, M.C. Fouz, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez,
M.I. Josa, D. Moran, A. Pérez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario
Olmeda, I. Redondo, L. Romero, M.S. Soares, A. Álvarez Fernández Universidad
Autónoma de Madrid, Madrid, Spain
C. Albajar, J.F. de Trocóniz, M. Missiroli Universidad de Oviedo, Oviedo,
Spain
J. Cuevas, C. Erice, J. Fernandez Menendez, I. Gonzalez Caballero, J.R.
González Fernández, E. Palencia Cortezon, S. Sanchez Cruz, P. Vischia, J.M.
Vizan Garcia Instituto de Física de Cantabria (IFCA), CSIC-Universidad de
Cantabria, Santander, Spain
I.J. Cabrillo, A. Calderon, B. Chazin Quero, E. Curras, J. Duarte Campderros,
M. Fernandez, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto, J. Marco, C.
Martinez Rivero, P. Martinez Ruiz del Arbol, F. Matorras, J. Piedra Gomez, T.
Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar
Cortabitarte CERN, European Organization for Nuclear Research, Geneva,
Switzerland
D. Abbaneo, B. Akgun, E. Auffray, P. Baillon, A.H. Ball, D. Barney, J.
Bendavid, M. Bianco, P. Bloch, A. Bocci, C. Botta, T. Camporesi, R. Castello,
M. Cepeda, G. Cerminara, E. Chapon, Y. Chen, D. d’Enterria, A. Dabrowski, V.
Daponte, A. David, M. De Gruttola, A. De Roeck, N. Deelen, M. Dobson, T. du
Pree, M. Dünser, N. Dupont, A. Elliott-Peisert, P. Everaerts, F. Fallavollita,
G. Franzoni, J. Fulcher, W. Funk, D. Gigi, A. Gilbert, K. Gill, F. Glege, D.
Gulhan, P. Harris, J. Hegeman, V. Innocente, A. Jafari, P. Janot, O.
Karacheban19, J. Kieseler, V. Knünz, A. Kornmayer, M.J. Kortelainen, M.
Krammer1, C. Lange, P. Lecoq, C. Lourenço, M.T. Lucchini, L. Malgeri, M.
Mannelli, A. Martelli, F. Meijers, J.A. Merlin, S. Mersi, E. Meschi, P.
Milenovic45, F. Moortgat, M. Mulders, H. Neugebauer, J. Ngadiuba, S.
Orfanelli, L. Orsini, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G.
Petrucciani, A. Pfeiffer, M. Pierini, D. Rabady, A. Racz, T. Reis, G.
Rolandi46, M. Rovere, H. Sakulin, C. Schäfer, C. Schwick, M. Seidel, M.
Selvaggi, A. Sharma, P. Silva, P. Sphicas47, A. Stakia, J. Steggemann, M.
Stoye, M. Tosi, D. Treille, A. Triossi, A. Tsirou, V. Veckalns48, M. Verweij,
W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland
W. Bertl${}^{\textrm{\textdagger}}$, L. Caminada49, K. Deiters, W. Erdmann, R.
Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe,
S.A. Wiederkehr ETH Zurich - Institute for Particle Physics and Astrophysics
(IPA), Zurich, Switzerland
M. Backhaus, L. Bäni, P. Berger, L. Bianchini, B. Casal, G. Dissertori, M.
Dittmar, M. Donegà, C. Dorfer, C. Grab, C. Heidegger, D. Hits, J. Hoss, G.
Kasieczka, T. Klijnsma, W. Lustermann, B. Mangano, M. Marionneau, M.T.
Meinhard, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandolfi,
J. Pata, F. Pauss, G. Perrin, L. Perrozzi, M. Quittnat, M. Reichmann, D.A.
Sanz Becerra, M. Schönenberger, L. Shchutska, V.R. Tavolaro, K. Theofilatos,
M.L. Vesterbacka Olsson, R. Wallny, D.H. Zhu Universität Zürich, Zurich,
Switzerland
T.K. Aarrestad, C. Amsler50, M.F. Canelli, A. De Cosa, R. Del Burgo, S.
Donato, C. Galloni, T. Hreus, B. Kilminster, D. Pinna, G. Rauco, P. Robmann,
D. Salerno, K. Schweiger, C. Seitz, Y. Takahashi, A. Zucchetta National
Central University, Chung-Li, Taiwan
V. Candelise, T.H. Doan, Sh. Jain, R. Khurana, C.M. Kuo, W. Lin, A.
Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan
Arun Kumar, P. Chang, Y. Chao, K.F. Chen, P.H. Chen, F. Fiori, W.-S. Hou, Y.
Hsiung, Y.F. Liu, R.-S. Lu, E. Paganis, A. Psallidas, A. Steen, J.f. Tsai
Chulalongkorn University, Faculty of Science, Department of Physics, Bangkok,
Thailand
B. Asavapibhop, K. Kovitanggoon, G. Singh, N. Srimanobhas Çukurova University,
Physics Department, Science and Art Faculty, Adana, Turkey
M.N. Bakirci51, A. Bat, F. Boran, S. Damarseckin, Z.S. Demiroglu, C. Dozen, E.
Eskut, S. Girgis, G. Gokbulut, Y. Guler, I. Hos52, E.E. Kangal53, O. Kara, U.
Kiminsu, M. Oglakci, G. Onengut54, K. Ozdemir55, S. Ozturk51, A. Polatoz, D.
Sunar Cerci56, U.G. Tok, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East
Technical University, Physics Department, Ankara, Turkey
B. Bilin, G. Karapinar57, K. Ocalan58, M. Yalvac, M. Zeyrek Bogazici
University, Istanbul, Turkey
E. Gülmez, M. Kaya59, O. Kaya60, S. Tekten, E.A. Yetkin61 Istanbul Technical
University, Istanbul, Turkey
M.N. Agaras, S. Atay, A. Cakir, K. Cankocak, I. Köseoglu Institute for
Scintillation Materials of National Academy of Science of Ukraine, Kharkov,
Ukraine
B. Grynyov National Scientific Center, Kharkov Institute of Physics and
Technology, Kharkov, Ukraine
L. Levchuk University of Bristol, Bristol, United Kingdom
F. Ball, L. Beck, J.J. Brooke, D. Burns, E. Clement, D. Cussans, O. Davignon,
H. Flacher, J. Goldstein, G.P. Heath, H.F. Heath, L. Kreczko, D.M. Newbold62,
S. Paramesvaran, T. Sakuma, S. Seif El Nasr-storey, D. Smith, V.J. Smith
Rutherford Appleton Laboratory, Didcot, United Kingdom
K.W. Bell, A. Belyaev63, C. Brew, R.M. Brown, L. Calligaris, D. Cieri, D.J.A.
Cockerill, J.A. Coughlan, K. Harder, S. Harper, J. Linacre, E. Olaiya, D.
Petyt, C.H. Shepherd-Themistocleous, A. Thea, I.R. Tomalin, T. Williams
Imperial College, London, United Kingdom
G. Auzinger, R. Bainbridge, J. Borg, S. Breeze, O. Buchmuller, A. Bundock, S.
Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies, A. De Wit, M.
Della Negra, R. Di Maria, A. Elwood, Y. Haddad, G. Hall, G. Iles, T. James, R.
Lane, C. Laner, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, T.
Matsushita, J. Nash, A. Nikitenko7, V. Palladino, M. Pesaresi, D.M. Raymond,
A. Richards, A. Rose, E. Scott, C. Seez, A. Shtipliyski, S. Summers, A.
Tapper, K. Uchida, M. Vazquez Acosta64, T. Virdee16, N. Wardle, D.
Winterbottom, J. Wright, S.C. Zenz Brunel University, Uxbridge, United Kingdom
J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, I.D. Reid, L. Teodorescu, M.
Turner, S. Zahid Baylor University, Waco, USA
A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika, C. Smith
Catholic University of America, Washington DC, USA
R. Bartek, A. Dominguez The University of Alabama, Tuscaloosa, USA
A. Buccilli, S.I. Cooper, C. Henderson, P. Rumerio, C. West Boston University,
Boston, USA
D. Arcaro, A. Avetisyan, T. Bose, D. Gastler, D. Rankin, C. Richardson, J.
Rohlf, L. Sulak, D. Zou Brown University, Providence, USA
G. Benelli, D. Cutts, A. Garabedian, M. Hadley, J. Hakala, U. Heintz, J.M.
Hogan, K.H.M. Kwok, E. Laird, G. Landsberg, J. Lee, Z. Mao, M. Narain, J.
Pazzini, S. Piperov, S. Sagir, R. Syarif, D. Yu University of California,
Davis, Davis, USA
R. Band, C. Brainerd, R. Breedon, D. Burns, M. Calderon De La Barca Sanchez,
M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk,
W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout,
M. Shi, J. Smith, D. Stolp, K. Tos, M. Tripathi, Z. Wang University of
California, Los Angeles, USA
M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M.
Ignatenko, N. Mccoll, S. Regnard, D. Saltzberg, C. Schnaible, V. Valuev
University of California, Riverside, Riverside, USA
E. Bouvier, K. Burt, R. Clare, J. Ellison, J.W. Gary, S.M.A. Ghiasi Shirazi,
G. Hanson, J. Heilman, G. Karapostoli, E. Kennedy, F. Lacroix, O.R. Long, M.
Olmedo Negrete, M.I. Paneva, W. Si, L. Wang, H. Wei, S. Wimpenny, B. R. Yates
University of California, San Diego, La Jolla, USA
J.G. Branson, S. Cittolin, M. Derdzinski, R. Gerosa, D. Gilbert, B. Hashemi,
A. Holzner, D. Klein, G. Kole, V. Krutelyov, J. Letts, I. Macneill, M.
Masciovecchio, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon,
M. Tadel, A. Vartak, S. Wasserbaech65, J. Wood, F. Würthwein, A. Yagil, G.
Zevi Della Porta University of California, Santa Barbara - Department of
Physics, Santa Barbara, USA
N. Amin, R. Bhandari, J. Bradmiller-Feld, C. Campagnari, A. Dishaw, V. Dutta,
M. Franco Sevilla, F. Golf, L. Gouskos, R. Heller, J. Incandela, A. Ovcharova,
H. Qu, J. Richman, D. Stuart, I. Suarez, J. Yoo California Institute of
Technology, Pasadena, USA
D. Anderson, A. Bornheim, J.M. Lawhorn, H.B. Newman, T. Nguyen, C. Pena, M.
Spiropulu, J.R. Vlimant, S. Xie, Z. Zhang, R.Y. Zhu Carnegie Mellon
University, Pittsburgh, USA
M.B. Andrews, T. Ferguson, T. Mudholkar, M. Paulini, J. Russ, M. Sun, H.
Vogel, I. Vorobiev, M. Weinberg University of Colorado Boulder, Boulder, USA
J.P. Cumalat, W.T. Ford, F. Jensen, A. Johnson, M. Krohn, S. Leontsinis, T.
Mulholland, K. Stenson, S.R. Wagner Cornell University, Ithaca, USA
J. Alexander, J. Chaves, J. Chu, S. Dittmer, K. Mcdermott, N. Mirman, J.R.
Patterson, D. Quach, A. Rinkevicius, A. Ryd, L. Skinnari, L. Soffi, S.M. Tan,
Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek Fermi National Accelerator
Laboratory, Batavia, USA
S. Abdullin, M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, A. Apyan, S.
Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, G.
Bolla${}^{\textrm{\textdagger}}$, K. Burkett, J.N. Butler, A. Canepa, G.B.
Cerati, H.W.K. Cheung, F. Chlebana, M. Cremonesi, J. Duarte, V.D. Elvira, J.
Freeman, Z. Gecse, E. Gottschalk, L. Gray, D. Green, S. Grünendahl, O.
Gutsche, R.M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, B. Jayatilaka, S.
Jindariani, M. Johnson, U. Joshi, B. Klima, B. Kreis, S. Lammel, D. Lincoln,
R. Lipton, M. Liu, T. Liu, R. Lopes De Sá, J. Lykken, K. Maeshima, N. Magini,
J.M. Marraffino, D. Mason, P. McBride, P. Merkel, S. Mrenna, S. Nahn, V.
O’Dell, K. Pedro, O. Prokofyev, G. Rakness, L. Ristori, B. Schneider, E.
Sexton-Kennedy, A. Soha, W.J. Spalding, L. Spiegel, S. Stoynev, J. Strait, N.
Strobbe, L. Taylor, S. Tkaczyk, N.V. Tran, L. Uplegger, E.W. Vaandering, C.
Vernieri, M. Verzocchi, R. Vidal, M. Wang, H.A. Weber, A. Whitbeck University
of Florida, Gainesville, USA
D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerhoff, A. Carnes, M.
Carver, D. Curry, R.D. Field, I.K. Furic, S.V. Gleyzer, B.M. Joshi, J.
Konigsberg, A. Korytov, K. Kotov, P. Ma, K. Matchev, H. Mei, G. Mitselmakher,
D. Rank, K. Shi, D. Sperka, N. Terentyev, L. Thomas, J. Wang, S. Wang, J.
Yelton Florida International University, Miami, USA
Y.R. Joshi, S. Linn, P. Markowitz, J.L. Rodriguez Florida State University,
Tallahassee, USA
A. Ackert, T. Adams, A. Askew, S. Hagopian, V. Hagopian, K.F. Johnson, T.
Kolberg, G. Martinez, T. Perry, H. Prosper, A. Saha, A. Santra, V. Sharma, R.
Yohay Florida Institute of Technology, Melbourne, USA
M.M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, T.
Roy, F. Yumiceva University of Illinois at Chicago (UIC), Chicago, USA
M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, R. Cavanaugh, X. Chen, O.
Evdokimov, C.E. Gerber, D.A. Hangal, D.J. Hofman, K. Jung, J. Kamin, I.D.
Sandoval Gonzalez, M.B. Tonjes, H. Trauger, N. Varelas, H. Wang, Z. Wu, J.
Zhang The University of Iowa, Iowa City, USA
B. Bilki66, W. Clarida, K. Dilsiz67, S. Durgut, R.P. Gandrajula, M.
Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya68, A. Mestvirishvili,
A. Moeller, J. Nachtman, H. Ogul69, Y. Onel, F. Ozok70, A. Penzo, C. Snyder,
E. Tiras, J. Wetzel, K. Yi Johns Hopkins University, Baltimore, USA
B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan, P.
Maksimovic, J. Roskes, U. Sarica, M. Swartz, M. Xiao, C. You The University of
Kansas, Lawrence, USA
A. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, J. Castle, S.
Khalil, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, C. Royon, S.
Sanders, E. Schmitz, J.D. Tapia Takaki, Q. Wang Kansas State University,
Manhattan, USA
A. Ivanov, K. Kaadze, Y. Maravin, A. Mohammadi, L.K. Saini, N. Skhirtladze, S.
Toda Lawrence Livermore National Laboratory, Livermore, USA
F. Rebassoo, D. Wright University of Maryland, College Park, USA
C. Anelli, A. Baden, O. Baron, A. Belloni, S.C. Eno, Y. Feng, C. Ferraioli,
N.J. Hadley, S. Jabeen, G.Y. Jeng, R.G. Kellogg, J. Kunkle, A.C. Mignerey, F.
Ricci-Tam, Y.H. Shin, A. Skuja, S.C. Tonwar Massachusetts Institute of
Technology, Cambridge, USA
D. Abercrombie, B. Allen, V. Azzolini, R. Barbieri, A. Baty, R. Bi, S. Brandt,
W. Busza, I.A. Cali, M. D’Alfonso, Z. Demiragli, G. Gomez Ceballos, M.
Goncharov, D. Hsu, M. Hu, Y. Iiyama, G.M. Innocenti, M. Klute, D. Kovalskyi,
Y.S. Lai, Y.-J. Lee, A. Levin, P.D. Luckey, B. Maier, A.C. Marini, C. Mcginn,
C. Mironov, S. Narayanan, X. Niu, C. Paus, C. Roland, G. Roland, J. Salfeld-
Nebgen, G.S.F. Stephans, K. Tatar, D. Velicanu, J. Wang, T.W. Wang, B.
Wyslouch University of Minnesota, Minneapolis, USA
A.C. Benvenuti, R.M. Chatterjee, A. Evans, P. Hansen, J. Hiltbrand, S.
Kalafut, Y. Kubota, Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack,
J. Turkewitz, M.A. Wadud University of Mississippi, Oxford, USA
J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA
E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, R. Gonzalez Suarez, R.
Kamalieddin, I. Kravchenko, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger State
University of New York at Buffalo, Buffalo, USA
J. Dolen, A. Godshalk, C. Harrington, I. Iashvili, D. Nguyen, A. Parker, S.
Rappoccio, B. Roozbahani Northeastern University, Boston, USA
G. Alverson, E. Barberis, A. Hortiangtham, A. Massironi, D.M. Morse, T.
Orimoto, R. Teixeira De Lima, D. Trocino, D. Wood Northwestern University,
Evanston, USA
S. Bhattacharya, O. Charaf, K.A. Hahn, N. Mucia, N. Odell, M.H. Schmitt, K.
Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, USA
N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N. Kellams,
K. Lannon, W. Li, N. Loukas, N. Marinelli, F. Meng, C. Mueller, Y. Musienko37,
M. Planer, A. Reinsvold, R. Ruchti, P. Siddireddy, G. Smith, S. Taroni, M.
Wayne, A. Wightman, M. Wolf, A. Woodard The Ohio State University, Columbus,
USA
J. Alimena, L. Antonelli, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, A.
Hart, C. Hill, W. Ji, B. Liu, W. Luo, B.L. Winer, H.W. Wulsin Princeton
University, Princeton, USA
S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, S. Higginbotham,
A. Kalogeropoulos, D. Lange, J. Luo, D. Marlow, K. Mei, I. Ojalvo, J. Olsen,
C. Palmer, P. Piroué, D. Stickland, C. Tully University of Puerto Rico,
Mayaguez, USA
S. Malik, S. Norberg Purdue University, West Lafayette, USA
A. Barker, V.E. Barnes, S. Das, S. Folgueras, L. Gutay, M.K. Jha, M. Jones,
A.W. Jung, A. Khatiwada, D.H. Miller, N. Neumeister, C.C. Peng, H. Qiu, J.F.
Schulte, J. Sun, F. Wang, W. Xie Purdue University Northwest, Hammond, USA
T. Cheng, N. Parashar, J. Stupak Rice University, Houston, USA
A. Adair, Z. Chen, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Guilbaud, M.
Kilpatrick, W. Li, B. Michlin, M. Northup, B.P. Padley, J. Roberts, J. Rorie,
W. Shi, Z. Tu, J. Zabel, A. Zhang University of Rochester, Rochester, USA
A. Bodek, P. de Barbaro, R. Demina, Y.t. Duh, T. Ferbel, M. Galanti, A.
Garcia-Bellido, J. Han, O. Hindrichs, A. Khukhunaishvili, K.H. Lo, P. Tan, M.
Verzetti The Rockefeller University, New York, USA
R. Ciesielski, K. Goulianos, C. Mesropian Rutgers, The State University of New
Jersey, Piscataway, USA
A. Agapitos, J.P. Chou, Y. Gershtein, T.A. Gómez Espinosa, E. Halkiadakis, M.
Heindl, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath,
R. Montalvo, K. Nash, M. Osherson, H. Saka, S. Salur, S. Schnetzer, D.
Sheffield, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker
University of Tennessee, Knoxville, USA
A.G. Delannoy, M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K.
Thapa Texas A&M University, College Station, USA
O. Bouhali71, A. Castaneda Hernandez71, A. Celik, M. Dalchenko, M. De Mattia,
A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, T. Kamon72, R.
Mueller, Y. Pakhotin, R. Patel, A. Perloff, L. Perniè, D. Rathjens, A.
Safonov, A. Tatarinov, K.A. Ulmer Texas Tech University, Lubbock, USA
N. Akchurin, J. Damgov, F. De Guio, P.R. Dudero, J. Faulkner, E. Gurpinar, S.
Kunori, K. Lamichhane, S.W. Lee, T. Libeiro, T. Mengke, S. Muthumuni, T.
Peltola, S. Undleeb, I. Volobouev, Z. Wang Vanderbilt University, Nashville,
USA
S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K.
Padeken, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu University of Virginia,
Charlottesville, USA
M.W. Arenton, P. Barria, B. Cox, R. Hirosky, M. Joyce, A. Ledovskoy, H. Li, C.
Neu, T. Sinthuprasith, Y. Wang, E. Wolfe, F. Xia Wayne State University,
Detroit, USA
R. Harr, P.E. Karchin, N. Poudyal, J. Sturdy, P. Thapa, S. Zaleski University
of Wisconsin - Madison, Madison, WI, USA
M. Brodski, J. Buchanan, C. Caillol, S. Dasu, L. Dodd, S. Duric, B. Gomber, M.
Grothe, M. Herndon, A. Hervé, U. Hussain, P. Klabbers, A. Lanaro, A. Levine,
K. Long, R. Loveless, T. Ruggles, A. Savin, N. Smith, W.H. Smith, D. Taylor,
N. Woods †: Deceased
1: Also at Vienna University of Technology, Vienna, Austria
2: Also at State Key Laboratory of Nuclear Physics and Technology, Peking
University, Beijing, China
3: Also at IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
4: Also at Universidade Estadual de Campinas, Campinas, Brazil
5: Also at Universidade Federal de Pelotas, Pelotas, Brazil
6: Also at Université Libre de Bruxelles, Bruxelles, Belgium
7: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia
8: Also at Joint Institute for Nuclear Research, Dubna, Russia
9: Also at Helwan University, Cairo, Egypt
10: Now at Zewail City of Science and Technology, Zewail, Egypt
11: Now at Fayoum University, El-Fayoum, Egypt
12: Also at British University in Egypt, Cairo, Egypt
13: Now at Ain Shams University, Cairo, Egypt
14: Also at Université de Haute Alsace, Mulhouse, France
15: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State
University, Moscow, Russia
16: Also at CERN, European Organization for Nuclear Research, Geneva,
Switzerland
17: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
18: Also at University of Hamburg, Hamburg, Germany
19: Also at Brandenburg University of Technology, Cottbus, Germany
20: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
21: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
22: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary
23: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India
24: Also at Institute of Physics, Bhubaneswar, India
25: Also at University of Visva-Bharati, Santiniketan, India
26: Also at University of Ruhuna, Matara, Sri Lanka
27: Also at Isfahan University of Technology, Isfahan, Iran
28: Also at Yazd University, Yazd, Iran
29: Also at Plasma Physics Research Center, Science and Research Branch,
Islamic Azad University, Tehran, Iran
30: Also at Università degli Studi di Siena, Siena, Italy
31: Also at INFN Sezione di Milano-Bicocca; Università di Milano-Bicocca,
Milano, Italy
32: Also at Purdue University, West Lafayette, USA
33: Also at International Islamic University of Malaysia, Kuala Lumpur,
Malaysia
34: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia
35: Also at Consejo Nacional de Ciencia y Tecnología, Mexico city, Mexico
36: Also at Warsaw University of Technology, Institute of Electronic Systems,
Warsaw, Poland
37: Also at Institute for Nuclear Research, Moscow, Russia
38: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
39: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
40: Also at University of Florida, Gainesville, USA
41: Also at P.N. Lebedev Physical Institute, Moscow, Russia
42: Also at California Institute of Technology, Pasadena, USA
43: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
44: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
45: Also at University of Belgrade, Faculty of Physics and Vinca Institute of
Nuclear Sciences, Belgrade, Serbia
46: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy
47: Also at National and Kapodistrian University of Athens, Athens, Greece
48: Also at Riga Technical University, Riga, Latvia
49: Also at Universität Zürich, Zurich, Switzerland
50: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna,
Austria
51: Also at Gaziosmanpasa University, Tokat, Turkey
52: Also at Istanbul Aydin University, Istanbul, Turkey
53: Also at Mersin University, Mersin, Turkey
54: Also at Cag University, Mersin, Turkey
55: Also at Piri Reis University, Istanbul, Turkey
56: Also at Adiyaman University, Adiyaman, Turkey
57: Also at Izmir Institute of Technology, Izmir, Turkey
58: Also at Necmettin Erbakan University, Konya, Turkey
59: Also at Marmara University, Istanbul, Turkey
60: Also at Kafkas University, Kars, Turkey
61: Also at Istanbul Bilgi University, Istanbul, Turkey
62: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom
63: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
64: Also at Instituto de Astrofísica de Canarias, La Laguna, Spain
65: Also at Utah Valley University, Orem, USA
66: Also at Beykent University, Istanbul, Turkey
67: Also at Bingol University, Bingol, Turkey
68: Also at Erzincan University, Erzincan, Turkey
69: Also at Sinop University, Sinop, Turkey
70: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey
71: Also at Texas A&M University at Qatar, Doha, Qatar
72: Also at Kyungpook National University, Daegu, Korea