EXO-16-050

$HeadURL:svn+ssh://svn.cern.ch/reps/tdr2/papers/EXO-16-050/trunk/EXO-16-050.tex$
$Id:EXO-16-050.tex4649522018-06-1809:24:35Zbmaier$

EXO-16-050

# Search for dark matter produced in association with a Higgs boson decaying
to a pair of bottom quarks in proton-proton collisions at $\sqrt{s}=13\TeV$

###### Abstract

A search for dark matter produced in association with a Higgs boson decaying
to a pair of bottom quarks is performed in proton-proton collisions at a
center-of-mass energy of 13collected with the CMS detector at the LHC. The
analyzed data sample corresponds to an integrated luminosity of 35.9. The
signal is characterized by a large missing transverse momentum recoiling
against a bottom quark-antiquark system that has a large Lorentz boost. The
number of events observed in the data is consistent with the standard model
background prediction. Results are interpreted in terms of limits both on
parameters of the type-2 two-Higgs doublet model extended by an additional
light pseudoscalar boson (2HDM+) and on parameters of a baryonic $\cPZpr$
simplified model. The 2HDM+model is tested experimentally for the first time.
For the baryonic $\cPZpr$ model, the presented results constitute the most
stringent constraints to date.

##  0.1 Introduction

Astrophysical evidence for dark matter (DM) is one of the most compelling
motivations for physics beyond the standard model (SM) [1, 2, 3]. Cosmological
observations demonstrate that around 85% of the matter in the universe is
comprised of DM [4] and they are largely consistent with the hypothesis that
DM is composed primarily of weakly interacting massive particles. If
nongravitational interactions exist between DM and SM particles, DM could be
produced by colliding SM particles at high energy. Assuming the pair
production of DM particles in hadron collisions occurs through a spin-0 or
spin-1 bosonic mediator coupled to the initial-state particles, the DM
particles leave the detector without measurable signatures. If DM particles
are produced in association with a detectable SM particle, which could be
emitted as initial-state radiation from the interacting constituents of the
colliding protons, or through new effective couplings between DM and SM
particles, their existence could be inferred via a large transverse momentum
imbalance in the collision event.

The production of the SM Higgs boson [5, 6, 7] via initial-state radiation is
highly suppressed because of the mass dependence of its coupling strength to
fermions. Nonetheless, the associated production of a Higgs boson and DM
particles can occur if the Higgs boson takes part in the interaction producing
the DM particles [8, 9, 10]. Such a production mechanism would allow one to
directly probe the structure of the effective DM-SM coupling.

In this paper, we present a search for DM production in association with a
scalar Higgs boson, h, with a mass of 125that decays to a bottom quark-
antiquark pair (). As the decay mode has the largest branching fraction of all
Higgs boson decay modes allowed in the SM, it provides the largest signal
yield. The search is performed using the data set collected by the CMS
experiment [11] at the CERN Large Hadron Collider (LHC) at a center-of-mass
energy of 13in 2016, corresponding to an integrated luminosity of
approximately 35.9. Similar searches have been conducted at the LHC by both
the ATLAS and CMS Collaborations, analyzing data collected at 8 [12] and 13
[13, 14]. Results are interpreted in terms of two simplified models predicting
this signature. The first is a type-2 two-Higgs doublet model extended by an
additional light pseudoscalar boson (2HDM+) [15]. The boson mixes with the
scalar and pseudoscalar partners of the observed Higgs boson, and decays to a
pair of DM particles, $\chi\overline{\chi}$. The second is a baryonic $\cPZpr$
model [10], in which a “baryonic Higgs” boson mixes with the SM Higgs boson.
In this model, a vector mediator $\cPZpr$ is exchanged in the $s$-channel and,
after the radiation of an SM Higgs boson, decays to two DM particles.
Representative Feynman diagrams for the two models are presented in Fig. 1.

In the 2HDM+model, the DM particle candidate $\chi$ is a fermion that can
couple to SM particles only through a spin-0, pseudoscalar mediator. Since the
couplings of the new spin-0 mediator to SM gauge bosons are strongly
suppressed, the 2HDM+model is consistent with measurements of the SM Higgs
boson production and decay modes, which so far show no significant deviation
from SM predictions [16]. In contrast to previously explored two-Higgs doublet
models [9, 12, 13, 17], the 2HDM+framework ensures gauge invariance and
renormalizability.

Figure 1: Feynman diagrams for the 2HDM+model (left) and the baryonic model
(right). In both models, the scalar can be identified with the observed
125Higgs boson.

In this model there are six mass eigenstates. Two are charge-parity (CP)-even
scalars: the light , assumed to be the observed 125Higgs boson, and the heavy
. These are the result of the mixing of the neutral CP-even weak eigenstates
with a mixing angle $\alpha$. The two CP-odd pseudoscalar mass eigenstates are
the light and the heavy , which are linear combinations of the CP-odd weak
eigenstates, with a mixing angle $\theta$. Finally, there are two heavy
charged scalars with identical mass.

The masses of and , the angle $\theta$, and the ratio of the vacuum
expectation values of and , $\tan\beta$, are varied in this search. The mixing
angle $\alpha$ changes with $\beta$ following the relation
$\alpha=\beta-\pi/2$. Perturbativity and unitarity put restrictions on the
magnitudes and the signs of the three quartic couplings
$\lambda_{3},~{}\lambda_{\mathrm{P}1},~{}\lambda_{\mathrm{P}2}$, and we set
their values to $\lambda_{3}=\lambda_{\mathrm{P}1}=\lambda_{\mathrm{P}2}=3$
[15]. The masses of the charged Higgs bosons and of the heavy CP-even Higgs
boson are assumed to be the same as the mass of the heavy pseudoscalar, ,
$m_{\PH}=m_{\Hpm}=m_{\PSA}$. When performing a scan in the
$m_{\PSA}$-$m_{\Pa}$ plane, $\tan\beta$ is assumed to be 1 and $\sin\theta$ is
assumed to be 0.35, following the recommendations in Ref. [18]. The DM
particle $\chi$ is assumed to have a mass of $m_{\chi}=10\GeV$. For
$\tan\beta\gg 1$, the coupling strengths of both and to quarks are enhanced,
and effects from -initiated production are included in the signal simulation
for all values of $\tan\beta$.

The baryonic model [10] is an extension of the SM with an additional U(1)B
gauge boson that couples to the baryon number $B$. The model predicts the
existence of a new Dirac fermion that is neutral under SM gauge symmetries,
has non-zero $B$, and is stable because of the corresponding U(1)B symmetry.
The state therefore serves as a good DM candidate. To generate the mass, a
baryonic Higgs scalar field is introduced to spontaneously break the U(1)B
symmetry. In analogy with the SM, there remains a physical baryonic Higgs
particle, $\Ph_{B}$, with a vacuum expectation value $v_{B}$, which couples to
the boson. The and the SM Higgs boson, , interact with a coupling strength of
$g_{\Ph\cPZpr\cPZpr}$ = $m_{\cPZpr}^{2}\sin\zeta/v_{B}$, where $\zeta$ is the
-$\Ph_{B}$ mixing angle. The chosen value for the coupling to quarks,
$g_{\cPq}$, is 0.25 and the coupling to DM, $g_{\chi}$, is set to 1, following
the recommendations in Ref. [19]. This is well below the bounds
$g_{\cPq},g_{\chi}\sim 4\pi$, where perturbativity and the validity of the
effective field theory break down [10]. Constraints on the SM Higgs boson
properties make the mixing angle $\zeta$ consistent with $\cos\zeta=1$ within
uncertainties of the order of 10%, thereby requiring $\sin\zeta$ to be less
than 0.4 [10]. In this search, it is assumed that $\sin\zeta=0.3$. It is also
assumed that $g_{\Ph\cPZpr\cPZpr}/m_{\cPZpr}=1$, which implies
$v_{B}=m_{\cPZpr}\sin\zeta$. This choice maximizes the cross section without
violating the bounds imposed by SM measurements. The free parameters in the
model under these assumptions are thus $m_{\cPZpr}$ and $m_{\chi}$, which are
varied in this search.

Signal events are characterized by a large imbalance in the transverse
momentum (or hadronic recoil), which indicates the presence of invisible DM
particles, and by hadronic activity consistent with the production of an SM
Higgs boson that decays to a pair. Thus, the search strategy followed imposes
requirements on the mass of the reconstructed Higgs boson candidate, which is
also required to be Lorentz-boosted. Together with the identification of the
hadronization products of the two quarks produced in the Higgs boson decay,
these requirements define a data sample that is expected to be enriched in
signal events. Several different SM processes can mimic this topology, the
most important of which are top quark pair production and the production of a
vector boson (V) in association with multiple jets. For each of these SM
processes that constitute the largest sources of background, statistically
independent data samples are used to predict the hadronic recoil
distributions. Both the signal and background contributions to the hadronic
recoil distributions observed in data are extracted with a likelihood fit,
performed simultaneously in all samples.

##  0.2 The CMS detector

The CMS detector, described in detail in Ref. [11], is a multipurpose
apparatus designed to study high transverse momentum () processes in proton-
proton (pp) and heavy ion collisions. A superconducting solenoid occupies its
central region, providing a magnetic field of 3.8T parallel to the beam
direction. Charged particle trajectories are measured using silicon pixel and
strip trackers that cover a pseudorapidity region of $\abs{\eta}<2.5$. A lead
tungstate crystal electromagnetic calorimeter (ECAL), and a brass and
scintillator hadron calorimeter surround the tracking volume and extend to
$\abs{\eta}<3$. The steel and quartz-fiber forward Cherenkov hadron
calorimeter extends the coverage to $\abs{\eta}<5$. The muon system consists
of gas-ionization detectors embedded in the steel flux-return yoke outside the
solenoid and covers $\abs{\eta}<2.4$. Online event selection is accomplished
via the two-tiered CMS trigger system [20]. The first level is designed to
select events in less than 4, using information from the calorimeters and muon
detectors. Subsequently, the high-level trigger processor farm reduces the
event rate to 1 kHz.

##  0.3 Simulated data samples

The signal processes are simulated at leading order (LO) accuracy in quantum
chromodynamics (QCD) perturbation theory using the v2.4.2 [21] program. To
model the contributions from SM Higgs boson processes as well as from the and
single top quark backgrounds, we use the v2 [22, 23, 24] generator. These
processes are generated at the next-to-leading order (NLO) in QCD. The
production cross section is further corrected using calculations at the next-
to-next-to-leading order in QCD including corrections for soft-gluon radiation
estimated with next-to-next-to-leading logarithmic accuracy [25]. Events with
multiple jets produced via the strong interaction (referred to as QCD multijet
events) are generated at LO using v2.2.2 with up to four partons in the matrix
element calculations. The MLM prescription [26] is used for matching these
partons to parton shower jets. Simulated samples of +jets and +jets processes
are generated at LO using v2.3.3. Up to four additional partons are considered
in the matrix element and matched to their parton showers using the MLM
technique. The V+jets (V=,) samples are corrected by weighting the of the
respective boson with NLO QCD corrections obtained from large samples of
events generated with and the FxFx merging technique [27] with up to two
additional jets stemming from the matrix element calculations. These samples
are further corrected by applying NLO electroweak corrections [28, 29, 30]
that depend on the boson . Predictions for the SM diboson production modes , ,
and are obtained at LO with the 8.205 [31] generator and normalized to NLO
accuracy using v6.0 [32].

The LO or NLO NNPDF 3.0 parton distribution functions (PDFs) [33] are used,
depending on the QCD order of the generator used for each physics process.
Parton showering, fragmentation, and hadronization are simulated with 8.212
using the CUETP8M1 underlying event tune [34, 35]. Interactions of the
resulting final state particles with the CMS detector are simulated using the
program [36]. Additional inelastic pp interactions in the same or a
neighboring bunch crossing (pileup) are included in the simulation. The pileup
distribution is adjusted to match the corresponding distribution observed in
data.

##  0.4 Event reconstruction

The reconstructed interaction vertex with the largest value of summed physics-
object $\pt^{2}$ is taken to be the primary event vertex. The physics objects
used for the primary event vertex determination are the clusters found by the
anti-$\kt$ clustering algorithm [37, 38], with a distance parameter of 0.4,
from the charged particle tracks in the event, as well as the associated
missing transverse momentum, taken as the negative vector sum of the of those
clusters. The offline selection requires all events to have a primary vertex
reconstructed within a 24window along the $z$-axis around the nominal
interaction point, and a transverse distance from the nominal interaction
region less than 2.

The particle-flow (PF) algorithm [39] aims to reconstruct and identify each
individual particle in an event, with an optimized combination of information
from the various elements of the CMS detector. The energy of photons is
obtained from the ECAL measurement. The energy of electrons is determined from
a combination of the electron momentum at the primary interaction vertex as
determined by the tracker, the energy of the corresponding ECAL cluster, and
the energy sum of all bremsstrahlung photons spatially compatible with
originating from the electron track. The energy of muons is obtained from the
curvature of the corresponding track. The energy of charged hadrons is
determined from a combination of their momentum measured in the tracker and
the matching ECAL and HCAL energy deposits, corrected for zero-suppression
effects and for the response function of the calorimeters to hadronic showers.
Finally, the energy of neutral hadrons is obtained from the corresponding
corrected ECAL and HCAL energies. The PF candidates are then used to construct
the physics objects described in this section. At large Lorentz boosts, the
two quarks from the Higgs boson decay may produce jets that overlap and make
their individual reconstruction difficult. In this search large-area jets
clustered from PF candidates using the Cambridge–Aachen algorithm [40] with a
distance parameter of 1.5 (CA15 jets) are utilized to identify the Higgs boson
candidate. The large cone size is chosen in order to select signal events
where the Higgs boson has a medium Lorentz-boost and hence its decay products
begin to merge for $\pt(\Ph)\gtrsim 200\GeV$. To reduce the impact of
particles arising from pileup interactions, the four-vector of each PF
candidate is scaled with a weight calculated with the pileup per particle
identification (PUPPI) algorithm [41] prior to the clustering. The absolute
jet energy scale is corrected using calibrations derived from data [42]. The
CA15 jets are also required to be central ($\abs{\eta}<2.4$). The “soft-drop”
(SD) jet grooming algorithm [43] is applied to remove soft wide-angle
radiation from the jets. We refer to the mass of the groomed CA15 jet as
$m_{\mathrm{SD}}$.

The ability to identify two quarks inside a single CA15 jet is crucial for
this search. A likelihood for the CA15 jet to contain two quarks is derived by
combining the information from primary and secondary vertices and tracks in a
multivariate discriminant optimized to distinguish CA15 jets originating from
$\Ph\to\bbbar$ decays from the cases where the hadronization of energetic
quarks or gluons [44] leads to the presence of a CA15 jet. The working point
chosen for this algorithm (the “double- tagger”) corresponds to an
identification efficiency of 50% for a system with a of 200, and a probability
of 10% for misidentifying CA15 jets originating from combinations of quarks or
gluons not coming from a resonance decay. The efficiency of the algorithm
increases with the of the system, reaching an efficiency of 65% for a CA15 jet
with a $\pt>500\GeV$. In this regime, the misidentification rate for QCD jets
is about 13%. The probability for misidentifying CA15 jets from top quark
decays is 14% across the entire spectrum. These estimates are derived with no
additional requirements on the CA15 jet kinematics.

Energy correlation functions are used to identify the two-prong structure in
the CA15 jet expected from a Higgs boson decay to two quarks, and to
distinguish it from QCD-like jets (, jets that do not originate from a heavy
resonance decay) and jets from the hadronic decays of top quarks. The energy
correlation functions (${{}_{v}e}_{N}$) are sensitive to correlations among
the constituents of the CA15 jet [45] and depend on $N$ factors of the
particle energies and $v$ factors of their pairwise angles, weighted by the
angular separation of the constituents.

As motivated in Ref. [45], the ratio
$N_{2}={{}_{2}e}_{3}^{(\beta)}/(_{1}e_{2}^{(\beta)})^{2}$ is used as a two-
prong tagger for the identification of the CA15 jet containing the Higgs boson
decay products. The parameter $\beta$, which controls the weighting of the
angles between constituent pairs in the computation of the $N_{2}$ variable,
is chosen to be 1 since this value gives the best two-prong jet
identification.

It is noted that requiring a jet to be two-pronged based on the value of a jet
substructure variable, such as $N_{2}$, will affect the shape of the
distribution of $m_{\mathrm{SD}}$ for the background processes. In this
search, the value of $m_{\mathrm{SD}}$ is required to be consistent with the
Higgs boson mass. It is therefore desirable to preserve a smoothly falling jet
mass distribution for QCD-like jets. As motivated in Ref. [46], the dependence
of $N_{2}$ on the variable $\rho=\ln(m_{\mathrm{SD}}^{2}/\pt^{2})$ is tested,
since the distribution of $\rho$ in QCD-like jets is expected to be invariant
of the jet mass and . The decorrelation strategy described in Ref. [46] is
applied, choosing a QCD misidentification efficiency of 20%, which corresponds
to a signal efficiency of 55% and a misidentification rate for top quark jets
of 36% across the entire CA15 jet spectrum. This results in a modified tagging
variable, which we denote as $N_{2}^{\mathrm{DDT}}$, where the superscript DDT
stands for “designing decorrelated taggers” [46]. Figure 2 shows the expected
distribution of $N_{2}^{\mathrm{DDT}}$ for CA15 jets matched to a Higgs boson
decaying to a pair, together with the distributions expected for CA15 jets
matched to hadronically decaying top quarks and for QCD-like CA15 jets.

Figure 2: The $N_{2}^{\text{DDT}}$ distribution as expected for CA15 jets
originating from a Higgs boson decaying to a pair (solid red) is compared with
the expected distribution for CA15 jets originating from the decay products of
top quarks decaying hadronically (dotted grey). The distribution corresponding
to CA15 jets that do not originate from a heavy resonance decay is also shown
(dashed blue).

This search also utilizes narrow jets clustered from the PF candidates using
the anti-$\kt$ algorithm with a distance parameter of 0.4 (“AK4 jets”). Narrow
jets originating from quarks are identified using the combined secondary
vertex (CSVv2) algorithm [44]. The working point used in this search has a
-jet identification efficiency of 81%, a charm jet selection efficiency of
37%, and a 9% probability of misidentifying light-flavor jets [44]. Jets that
are -tagged are required to be central ($\abs{\eta}<2.4$).

Electron reconstruction requires the matching of a supercluster in the ECAL
with a track in the silicon tracker. Reconstructed electrons are required to
be within $\abs{\eta}<2.5$, excluding the transition region
$1.44<\abs{\eta}<1.57$ between the ECAL barrel and endcap. Identification
criteria [47] based on the ECAL shower shape and the consistency of the
electron track with the primary vertex are imposed. Muon candidates are
selected by two different reconstruction approaches [48]: one in which tracks
in the silicon tracker are matched to a track segment in the muon detector,
and another in which a track fit spanning the silicon tracker and muon
detector is performed starting with track segments in the muon detector.
Further identification criteria are imposed on muon candidates to reduce the
number of hadrons and poorly measured mesons misidentified as muons [48].
These additional criteria include requirements on the number of hits in the
tracker and in the muon systems, the fit quality of the global muon track, and
the track’s consistency with the primary vertex. Muon candidates with
$\abs{\eta}<2.4$ are considered in this analysis. A minimum of 10is required
for electron and muon candidates. Both are required to satisfy isolation
requirements that limit the total energy of tracks and calorimeter clusters
measured in conical regions about them. Hadronically decaying $\tau$ leptons,
$\tau_{\text{had}}$, are reconstructed using the hadron-plus-strips algorithm
[49], which uses charged hadron and neutral electromagnetic objects to
reconstruct intermediate resonances into which the $\tau$ lepton decays. The
$\tau_{\text{had}}$ candidates with $\pt>18\GeV$ and $\abs{\eta}<2.3$ are
considered [47, 50, 49]. Photon candidates, identified by means of
requirements on the ECAL energy distribution and its distance to the closest
track, must have $\pt>15\GeV$ and $\abs{\eta}<2.5$.

The missing transverse momentum is defined as the negative vectorial sum of
the of all the reconstructed PF candidates. Its magnitude is denoted as .
Corrections to jet momenta are propagated to the calculation, and event
filters are used to remove spurious high events caused by instrumental noise
in the calorimeters or beam halo muons [51]. These filters remove about 1% of
signal events.

##  0.5 Event selection

Signal events are characterized by a high value of , the absence of any
isolated lepton (e, $\mu$, or $\tau$) or photon, and the presence of a CA15
jet identified as a Higgs boson candidate. In the signal region (SR) described
below, the dominant background contributions arise from +jets, +jets, and
production. To predict the spectra of these processes in the SR, data from
different control regions (CRs) are used. Single-lepton CRs are designed to
predict the and +jets backgrounds, while dilepton CRs predict the +jets
background contribution. The hadronic recoil, $U$, serves as a proxy for the
distribution of the main background processes in the SR and is defined by
excluding the electron(s) and muon(s) from the computation in the CRs.
Predictions for other backgrounds are obtained from simulation.

Events are selected online by the high level trigger system, using a jet
reconstruction algorithm and constituents that mirror those of the offline
analysis. The trigger requires large values of
$p_{\text{T,trig}}^{\text{miss}}$ or , where $p_{\text{T,trig}}^{\text{miss}}$
is the magnitude of the vectorial $\ptvec$ sum over all PF particles and is
the magnitude of the vectorial $\ptvec$ sum over all AK4 jets with
$\pt>20\GeV$ and $\abs{\eta}<5.2$ at the trigger level. Muon candidates are
excluded from the online $p_{\text{T,trig}}^{\text{miss}}$ calculation.
Minimum thresholds on $p_{\text{T,trig}}^{\text{miss}}$ and are between 90 and
120, depending on the data-taking period. Collectively, online requirements on
$p_{\text{T,trig}}^{\text{miss}}$ and are referred to as triggers. These
triggers are measured to be 96% efficient for $\ptmiss(U)>200\GeV$ and 100%
efficient for $\ptmiss(U)>350\GeV$. For CRs that require the presence of
electrons, events are collected by single-electron triggers, in which at least
one electron is required by the online selection criteria. These sets of
requirements are referred to as single-electron triggers.

A common set of preselection criteria is used for all regions. The presence of
exactly one CA15 jet with $\pt>200\GeV$ and $\abs{\eta}<2.4$ is required. It
is also required that $100<m_{\mathrm{SD}}<150\GeV$ and
$N_{2}^{\mathrm{DDT}}<0$. In the SR (CRs), ($U$) has to be larger than 200,
and the minimum azimuthal angle $\phi$ between any AK4 jet and the direction
of ($\vec{U}$) must be larger than 0.4 radians to reject multijet events that
mimic signal events. Events with any $\tau_{\text{had}}$ candidate or photon
candidate are vetoed. The number of AK4 jets for which $\Delta
R=\sqrt{(\Delta\eta)^{2}+(\Delta\phi)^{2}}>1.5$, where $\Delta\eta$ and
$\Delta\phi$ are, respectively, the differences in pseudorapidity and in the
azimuthal angle (measured in radians) of a given AK4 jet and the CA15 jet, is
required to be smaller than two. This number is referred to as “additional AK4
jets” in the following. This requirement significantly reduces the
contribution from events in the SR.

Events that meet the preselection criteria described above are split into the
SR and the different CRs based on their lepton multiplicity and the presence
of a -tagged AK4 jet not overlapping with the CA15 jet, as summarized in Table
0.5. For the SR, events are selected if they have no isolated electrons
(muons) with $\pt>10\GeV$ and $\abs{\eta}<2.5$ (2.4), and the previously
described double- tag requirement on the Higgs boson candidate CA15 jet is
imposed.

Event selection criteria defining the signal and control regions. These
criteria are applied in addition to the preselection common to all regions, as
described in the text. The presence of a -tagged AK4 jet that does not overlap
with the CA15 jet is vetoed in all analysis regions except for the single-
lepton CR enriched in events, for which such an AK4 tag is required.  Region
Main background process Additional AK4 tag Leptons Double- tag Signal +jets, ,
+jets 0 0 pass Single-lepton +jets,  0 1 pass/fail Single-lepton, -tagged ,
+jets 1 1 pass/fail Dilepton +jets 0 2 pass/fail

To predict the spectrum of the +jets process in the SR, dimuon and dielectron
CRs are used. Dimuon events are selected online employing the same triggers
that are used in the SR. These events are required to have two oppositely
charged muons (having $\pt>20\GeV$ and $\pt>10\GeV$ for the leading and
trailing muon, respectively) with an invariant mass between 60 and 120. The
leading muon has to satisfy tight identification and isolation requirements
and is selected with an average efficiency of 95%. Dielectron events are
selected online using single-electron triggers. Two oppositely charged
electrons with greater than 10are required offline, and they must form an
invariant mass between 60 and 120. To be on the plateau of the trigger
efficiency, at least one of the two electrons must have $\pt>40\GeV$ and must
satisfy tight identification and isolation requirements that correspond to an
efficiency of 70% [47].

Events that satisfy the SR selection because of the loss of a single lepton
primarily originate from +jets and semileptonic events. To predict these
backgrounds, four single-lepton samples are used: single-electron and single-
muon, with and without a -tagged AK4 jet outside the CA15 jet. The single-
lepton CRs with a -tagged AK4 jet target events, while the other two single-
lepton CRs target +jets events. Single-muon events are selected using the
triggers described above. Single-electron events are selected using the same
single-electron triggers employed in the online selection of dielectron
events. The electron (muon) candidate in these events is required to have
$\pt>40$ (20)and to satisfy tight identification and isolation requirements.
In addition, samples with a single electron must have $\ptmiss>50\GeV$ to
avoid a large contamination from multijet events.

Each CR is further split into two subsamples depending on whether or not the
CA15 jet satisfies the double- tag requirement. This division allows for an in
situ calibration of the scale factor that corrects the simulated
misidentification probability of the double- tagger for the three main
backgrounds to the probability observed in data.

##  0.6 Signal extraction

As mentioned in Section 0.1, signal and background contributions to the data
are extracted with a simultaneous binned likelihood fit (using the RooStats
package [52]) to the and $U$ distributions in the SR and the CRs. The dominant
SM process in each CR is used to predict the respective background in the SR
via transfer factors $T$. These factors are determined in simulation and are
given by the ratio of the prediction for a given bin in in the SR and the
corresponding bin in $U$ in the CR, for the given process. This ratio is
determined independently for each bin of the corresponding distribution.

For example, if b$\ell$ denotes the process in the -tagged single-lepton
control sample that is used to estimate the contribution in the SR, the
expected number of events, $N_{i}$, in the $i^{\text{th}}$ bin of the SR is
then given by $N_{i}=\mu^{\ttbar}_{i}/T^{\mathrm{b}\ell}_{i}$, where
$\mu^{\ttbar}_{i}$ is a freely floating parameter included in the likelihood
to scale the contribution in bin $i$ of $U$ in the CR.

The transfer factors used to predict the +jets and backgrounds take into
account the impact of lepton acceptances and efficiencies, the tagging
efficiency, and, for the single-electron control samples, the additional
requirement on . Since the CRs with no -tagged AK4 jets and a double--tagged
CA15 jet also have significant contributions from the process, transfer
factors to predict this contamination from events are also imposed between the
single-lepton CRs with and without -tagged AK4 jets. A similar approach is
applied to estimate the contamination from +jets production in the CR with
events that fail the double- tag requirement. Likewise, the +jets background
prediction in the signal region is connected to the dilepton CRs via transfer
factors. They account for the difference in the branching fractions of the
${\cPZ}\to\nu\nu$ and the ${\cPZ}\to\ell\ell$ decays and the impacts of lepton
acceptances and selection efficiencies.

##  0.7 Systematic uncertainties

Nuisance parameters are introduced into the likelihood fit to represent the
systematic uncertainties of the search. They can affect either the
normalization or the shape of the ($U$) distribution for a given process in
the SR (CRs) and can be constrained in the fit. The shape uncertainties are
incorporated by means of Gaussian prior distributions, while the rate
uncertainties are given a log-normal prior distributions. The list of the
systematic uncertainties considered in this search is presented in Table 0.7.
To better estimate their impact on the results, uncertainties from a similar
source (, uncertainties in the trigger efficiencies) have been grouped. The
groups of uncertainties have been ordered by the improvement in sensitivity
obtained by removing the corresponding nuisances in the likelihood fit. The
sensitivity in the baryonic model is generally poorer than that of a
2HDM+model because the former predicts a more background-like distribution.
The description of each single uncertainty in the text follows the same order
as in the table.

Scale factors are used to correct for differences in the double- tagger
misidentification efficiencies in data and in the simulated /+jets and
samples. These scale factors are measured by simultaneously fitting events
that pass or fail the double- tag requirement. The correlation between the
double- tagger and (or $U$) is taken into account by allowing recoil bins to
fluctuate within a constraint that depends on the recoil value. Such
dependence is estimated from the profile of the two-dimensional distribution
of the double- tag discriminant vs. the $\pt$ of the CA15 jet. This is the
shape uncertainty that has the largest impact on the upper limits on the
signal cross sections.

Shape uncertainties due to the bin-by-bin statistical uncertainties in the
transfer factors are considered for the +jets, +jets, and processes.

For the signal and the SM processes, an uncertainty in the double- tagging
efficiency is applied that depends on the of the CA15 jet. This shape
uncertainty has been derived through a measurement performed using a sample
enriched in multijet events with double-muon-tagged $\Pg\to\bbbar$ splittings.
A 7% rate uncertainty in the efficiency of the requirement on the substructure
variable $N_{2}^{\mathrm{DDT}}$, which is used to identify two-prong CA15
jets, is assigned to all processes where the decay of a resonance inside the
CA15 jet cone is expected. Such processes include signal production together
with SM and diboson production. The uncertainty has been derived from the
efficiency measurement obtained by performing a fit in a control sample
enriched in semi-leptonic events, where the CA15 jet originates from the boson
that comes from the hadronically decaying top quark.

A 4% rate uncertainty due to the imperfect knowledge of the CA15 jet energy
scale [42] is assigned to all the processes obtained from simulation.

Similarly, a 5% rate uncertainty in the magnitude, as measured by CMS in Ref.
[53], is assigned to each of the processes estimated from simulation.

A rate uncertainty of 2.5% in the integrated luminosity measurement [54] is
included and assigned to processes determined from simulation. In these cases,
uncertainties in the PDFs and uncertainties due to variations in the QCD
renormalization and factorization scales are included as shape uncertainties,
obtained by varying those parameters in the simulation.

Sources of systematic uncertainty, along with the type (rate/shape) of
uncertainty and the affected processes. For the rate uncertainties, the
percentage value of the prior is quoted. The last column denotes the
improvement in the expected limit when removing the uncertainty group from the
list of nuisances included in the likelihood fit. Such improvement is
estimated considering as signal processes the 2HDM+model with
$m_{\PSA}=1.1\TeV$ and $m_{\Pa}=150\GeV$ and the baryonic model with
$m_{\cPZpr}=0.2\TeV$ and $m_{\chi}=50\GeV$.  Systematic uncertainty Type
Processes Impact on sensitivity 2HDM+ Baryonic  Double- mistagging shape
+jets, +jets,  4.8% 14.8% Transfer factor stat. uncertainties shape +jets,
+jets,  1.9% 4.0% Double- tagging shape SM , signal 1.2% 1.1%
$N_{2}^{\mathrm{DDT}}$ efficiency 7% diboson, SM , signal CA15 jet energy 4%
single , diboson, multijet, SM , signal 0.8% 0.6% magnitude 5% all 0.7%
$<$0.5% Integrated luminosity 2.5% single , diboson, multijet, SM , signal
$<$0.5% $<$0.5% $\ptmiss$ trigger efficiency shape/rate all $<$0.5% $<$0.5%
Single-electron trigger 1% all AK4 tagging shape all $<$0.5% $<$0.5% $\tau$
lepton veto 3% all $<$0.5% $0.7\%$ Lepton efficiency 1% per lepton all
Renorm./fact. scales shape SM  $<$0.5% $<$0.5% PDF shape SM  Multijet
normalization 100% multijet Theoretical cross section 20% single , diboson

The trigger efficiency is parametrized as a function of $U$ and measured using
both single-muon and dimuon events. The difference between these measurements
is used to derive an uncertainty, which results in a 1% rate uncertainty for
processes estimated using simulation. Processes estimated using control
regions (, +jets, and +jets) are sensitive to the effect of this uncertainty
as a function of $U$, so a shape uncertainty (as large as 2% at low $U$
values) is considered for such processes. The efficiencies of the single-
electron triggers are parametrized as a function of the electron and $\eta$
and an associated 1% systematic uncertainty is added into the fit.

An uncertainty in the efficiency of the CSV tagging algorithm applied to
isolated AK4 jets is assigned to the transfer factors used to predict the
background. The scale factors that correct this efficiency are measured with
standard CMS methods [44]. They depend on the and $\eta$ of the -tagged (or
mistagged) jet and therefore their uncertainties are included in the fit as
shape uncertainties.

The uncertainty in the $\tau$ lepton veto amounts to 3%, correlated across all
$U$ bins. Also correlated across all $U$ bins are the uncertainties in the
electron and muon selection efficiencies, which amount to 1%.

An uncertainty of 21% in the heavy-flavor fraction of +jets is reported in
previous CMS measurements [55, 56]. The uncertainty in the heavy-flavor
fraction of jets produced together with a boson is measured to be 22% [57,
58]. To take into account the variation of the double- tagging efficiency
introduced by such uncertainties, the efficiencies for the +jets and +jets
processes are reevaluated after varying the heavy-flavor component in the
simulation. The difference in the efficiency with respect to the nominal
efficiency value is taken as a systematic uncertainty, and amounts to 4% in
the rate of the +jets process and 5% in the rate of the +jets process.

Uncertainties in the SM production due to variations of the
renormalization/factorization scales and PDFs are included as shape
variations. An uncertainty of 100% is assigned to the QCD multijet yield. This
uncertainty is estimated using a sample enriched in multijet events. The
sample is obtained by vetoing leptons and photons, requiring $\ptmiss>250\GeV$
and requiring that the minimum azimuthal angle between and the jet directions
be less than 0.1 radians. One nuisance parameter represents the uncertainty in
QCD multijet yields in the signal region, while separate nuisance parameters
are introduced for the muon CRs and electron CRs. A systematic uncertainty of
20% is assigned to the single top quark background yields as reported by CMS
in Ref. [59] and is correlated between the SR and the CRs. An uncertainty of
20%, correlated across the SR and CRs, is also assigned to the diboson
production cross section as measured by CMS in Refs. [60, 61].

##  0.8 Results

The expected yields for each background in the SR and their uncertainties, as
determined in the likelihood fit under the background-only assumption, are
presented in Table 0.8, along with the observed data yields. Good agreement is
observed between data and the predictions. Due to anticorrelations between
background processes, in some bins the uncertainty in the background sum is
smaller than the uncertainties in the individual contributions, such as, for
example, the +jets yields.

Post-fit event yield expectations per bin for the SM backgrounds in the signal
region when including the signal region data in the likelihood fit, under the
background-only assumption. Also quoted are the expected yields for two signal
models. Uncertainties quoted in the predictions include both the systematic
and statistical components.  bin 200–270 270–350 350–475 $>$475 +jets $249\pm
22$ $97.2\pm 8.5$ $32.6\pm 3.6$ $11.1\pm 1.9$ $199\pm 14$ $52.1\pm 5.2$
$11.1\pm 2.0$ $0.7\pm 0.4$ +jets $122\pm 22$ $45.0\pm 8.7$ $8.4\pm 1.9$
$2.9\pm 0.9$ Single  $21.0\pm 4.2$ $6.1\pm 1.2$ $0.9\pm 0.2$ $0.2\pm 0.1$
Diboson $16.0\pm 3.1$ $7.6\pm 1.5$ $2.4\pm 0.5$ $1.0\pm 0.2$ SM  $12.6\pm 1.4$
$6.6\pm 0.7$ $3.3\pm 0.3$ $1.3\pm 0.1$ $\Sigma~{}(\text{SM})$ $619\pm 20$
$215\pm 8$ $58.7\pm 3.7$ $17.2\pm 2.0$ Data 619 214 59 21 2HDM+,
$m_{\PSA}=1\TeV$, $m_{\Pa}=150\GeV$ $5.7\pm 0.6$ $9.8\pm 1.1$ $18.5\pm 2.1$
$5.2\pm 0.6$ Bar. , $m_{\cPZpr}=0.2\TeV$, $m_{\chi}=50\GeV$ $184\pm 20$
$118\pm 13$ $69.5\pm 7.7$ $28.9\pm 3.3$

(a)  Figure 3: The distribution in the signal region before and after a
likelihood fit. The data are in agreement with post-fit background predictions
for the SM backgrounds, and no significant excess is observed. The dashed red
histogram corresponds to the pre-fit estimate for the SM backgrounds. The
lower panel shows the ratio of the data to the predicted SM background, before
and after the fit. The rightmost bin includes overflow events.

Expected yields are also presented for two signal models. The selection
efficiencies for the chosen points correspond to 5% for the 2HDM+model and 1%
for the baryonic model.

Figure 3 shows the pre-fit and post-fit distributions in the SR for signal and
for all SM backgrounds, as well as the observed data distribution. The
likelihood fit has been performed simultaneously in all analysis regions. The
data agree with the background predictions at the one standard deviation
level, and the post-fit estimate of the SM background is slightly larger than
the pre-fit one. The distributions for $U$ in the muon and electron CRs, after
a fit to the data, are presented in Figs. 4 and 5.

Figure 4: The $U$ distribution in the electron control regions before and
after a background-only fit to data, including the data in the signal region
in the likelihood. For the distributions on the left the CA15 jet passes the
double- tag requirement and for the distributions on the right it fails the
double- tag requirement. The lower panel shows the ratio of the data to the
predicted SM background, before and after the fit. The rightmost $U$ bin
includes overflow events.

Figure 5: The $U$ distribution in the muon control regions before and after a
background-only fit to data, including the data in the signal region in the
likelihood. For the distributions on the left the CA15 jet passes the double-
tag requirement and for the distributions on the right it fails the double-
tag requirement. The lower panel shows the ratio of the data to the predicted
SM background, before and after the fit. The rightmost $U$ bin includes
overflow events.

No significant excess over the SM background expectation is observed in the
SR. The results of this search are interpreted in terms of upper limits on the
signal strength modifier $\mu=\sigma/\sigma_{\text{theory}}$, where
$\sigma_{\text{theory}}$ is the predicted production cross section of DM
candidates in association with a Higgs boson and $\sigma$ is the upper limit
on the observed cross section. The upper limits are calculated at 95%
confidence level () using a modified frequentist method [62, 63, 64] computed
with an asymptotic approximation [65].

Figure 6 shows the upper limits on $\mu$ for the three scans ($m_{\PSA}$,
$\sin\theta$, and $\tan\beta$) performed. For the 2HDM+model, $m_{\PSA}$
masses are excluded between 500 and 900for $m_{\Pa}=150\GeV$,
$\sin\theta=0.35$ and $\tan\beta=1$. Mixing angles with $0.35<\sin\theta<0.75$
are excluded for $m_{\PSA}=600\GeV$ and $m_{\Pa}=200\GeV$, assuming
$\tan\beta=1$. Also excluded are $\tan\beta$ values between 0.5 and 2.0 (1.6)
for $m_{\Pa}=100$ (150)and $m_{\PSA}=600\GeV$, given $\sin\theta=0.35$. These
are the first experimental limits on the 2HDM+model.

Figure 6: Upper limits at 95% on the signal strength modifier, defined as
$\mu=\sigma/\sigma_{\text{theory}}$, where $\sigma_{\text{theory}}$ is the
predicted production cross section of DM candidates in association with a
Higgs boson and $\sigma$ is the upper limit on the observed cross section.
Limits are shown for the 2HDM+model when scanning $m_{\PSA}$ and $m_{\Pa}$
(upper left), the mixing angle $\theta$ (upper right), or $\tan\beta$ (lower).
The uncertainty in the computation of $\sigma_{\text{theory}}$ is 20% and is
shown as a red band around the exclusion line at $\mu=1$.

Figure 7 shows the expected and observed exclusion range as a function of
$m_{\cPZpr}$ and $m_{\chi}$ for the baryonic model. For a DM mass of 1, masses
$m_{\cPZpr}<1.6\TeV$ are excluded. The expected exclusion boundary is 1.85.
Masses for the DM particles of up to 430are excluded for a 960 mass. These are
the most stringent limits on this model so far.

Figure 7: Upper limits at 95% on the signal strength modifier, defined as
$\mu=\sigma/\sigma_{\text{theory}}$, where $\sigma_{\text{theory}}$ is the
predicted production cross section of DM candidates in association with a
Higgs boson and $\sigma$ is the upper limit on the observed cross section.
Limits are shown for the baryonic model as a function of $m_{\cPZpr}$ and
$m_{\chi}$. Mediators of up to 1.6are excluded for a DM mass of 1. Masses of
the DM particle itself are excluded up to 430for a mass of 960.

To compare results with DM direct detection experiments, limits from the
baryonic model are presented in terms of a spin-independent (SI) cross section
$\sigma_{\mathrm{SI}}$ for DM scattering off a nucleus. Following the
recommendation of Ref. [66], the value of $\sigma_{\mathrm{SI}}$ is determined
by the equation:

$\sigma_{\text{SI}}=\frac{f^{2}(g_{\cPq})g^{2}_{\chi}\mu^{2}_{\mathrm{n}\chi}}{\pi
m^{4}_{\mathrm{med}}},$ (1)

where $\mu_{\mathrm{n}\chi}$ is the reduced mass of the DM-nucleon system,
$f(g_{\cPq})$ is the mediator-nucleon coupling, which depends on the mediator
coupling to SM quarks $g_{\cPq}$, $g_{\chi}$ is the mediator coupling to SM
particles, and $m_{\text{med}}$ is the mass of the mediator. The resulting
$\sigma_{\mathrm{SI}}$ limits as a function of the DM mass are shown in Fig.
8. Under the assumptions made for the baryonic model, these limits on the DM-
nucleon SI cross section are the most stringent to date for $m_{\chi}<5\GeV$.

Figure 8: The 90% exclusion limits on the DM-nucleon SI scattering cross
section as a function of $m_{\chi}$. Results for the baryonic model obtained
in this analysis are compared with those from a selection of direct detection
(DD) experiments. The latter exclude the regions above the curves. Limits from
CRESST-II [67], CDMSlite [68], LUX [69], XENON-1T [70], PandaX-II [71], and
CDEX-10 [72] are shown.

##  0.9 Summary

A search for dark matter (DM) produced in association with a Higgs boson
decaying to a pair of bottom quarks in a sample of proton-proton collision
data corresponding to 35.9is presented. No significant deviation from the
predictions of the standard model is observed, and 95% upper limits on the
production cross sections predicted by a type-2 two-Higgs doublet model
extended by an additional light pseudoscalar boson (2HDM+) and by the baryonic
model are established. These limits constitute the most stringent exclusions
from collider experiments placed on the parameters of these models to date.
The 2HDM+model is probed experimentally for the first time. For the nominal
choice of the mixing angles $\sin\theta$ and $\tan\beta$ in the 2HDM+model,
the search excludes masses $500<m_{\PSA}<900\GeV$ (where is the heavy
pseudoscalar boson) assuming $m_{\Pa}=150\GeV$. Scanning over $\sin\theta$
with $\tan\beta$ = 1, we exclude $0.35<\sin\theta<0.75$ for $m_{\PSA}=600\GeV$
and $m_{\Pa}=200\GeV$. Finally, $\tan\beta$ values between 0.5 and 2.0 (1.6)
are excluded for $m_{\PSA}=600\GeV$ and $m_{\Pa}=100$ (150)and
$\sin\theta=0.35$. In all 2HDM+interpretations, a DM mass of $m_{\chi}=10\GeV$
is assumed. For the baryonic model, we exclude boson masses up to 1.6for a DM
mass of 1, and DM masses up to 430for a boson mass of 960. The
reinterpretation of the results for the baryonic model in terms of an SI
nucleon scattering cross section yields a higher sensitivity for
$m_{\chi}<5\GeV$ than existing results from direct detection experiments,
under the assumptions imposed by the model.

###### Acknowledgements.

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

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##  .10 The CMS Collaboration

Yerevan Physics Institute, Yerevan, Armenia
A.M. Sirunyan, A. Tumasyan Institut für Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, M. Dragicevic,
J. Erö, A. Escalante Del Valle, M. Flechl, R. Frühwirth1, V.M. Ghete, J.
Hrubec, M. Jeitler1, N. Krammer, I. Krätschmer, D. Liko, T. Madlener, I.
Mikulec, N. Rad, H. Rohringer, J. Schieck1, R. Schöfbeck, M. Spanring, D.
Spitzbart, A. Taurok, W. Waltenberger, J. Wittmann, C.-E. Wulz1, M. Zarucki
Institute for Nuclear Problems, Minsk, Belarus
V. Chekhovsky, V. Mossolov, J. Suarez Gonzalez Universiteit Antwerpen,
Antwerpen, Belgium
E.A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, M. Pieters, H. Van
Haevermaet, P. Van Mechelen, N. Van Remortel Vrije Universiteit Brussel,
Brussel, Belgium
S. Abu Zeid, F. Blekman, J. D’Hondt, J. De Clercq, K. Deroover, G. Flouris, D.
Lontkovskyi, S. Lowette, I. Marchesini, S. Moortgat, L. Moreels, Q. Python, K.
Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders, I. Van Parijs
Université Libre de Bruxelles, Bruxelles, Belgium
D. Beghin, B. Bilin, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, B.
Dorney, G. Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk, A.K. Kalsi, T.
Lenzi, J. Luetic, N. Postiau, E. Starling, L. Thomas, C. Vander Velde, P.
Vanlaer, D. Vannerom, Q. Wang Ghent University, Ghent, Belgium
T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov2, D. Poyraz, C. Roskas,
D. Trocino, M. Tytgat, W. Verbeke, B. Vermassen, M. Vit, N. Zaganidis
Université Catholique de Louvain, Louvain-la-Neuve, Belgium
H. Bakhshiansohi, O. Bondu, S. Brochet, G. Bruno, C. Caputo, P. David, C.
Delaere, M. Delcourt, A. Giammanco, G. Krintiras, V. Lemaitre, A. Magitteri,
A. Mertens, K. Piotrzkowski, A. Saggio, M. Vidal Marono, S. Wertz, J. Zobec
Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil
F.L. Alves, G.A. Alves, M. Correa Martins Junior, G. Correia Silva, C. Hensel,
A. Moraes, M.E. Pol, P. Rebello Teles Universidade do Estado do Rio de
Janeiro, Rio de Janeiro, Brazil
E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato3, E. Coelho, E.M.
Da Costa, G.G. Da Silveira4, D. De Jesus Damiao, C. De Oliveira Martins, S.
Fonseca De Souza, H. Malbouisson, D. Matos Figueiredo, M. Melo De Almeida, C.
Mora Herrera, L. Mundim, H. Nogima, W.L. Prado Da Silva, L.J. Sanchez Rosas,
A. Santoro, A. Sznajder, M. Thiel, E.J. Tonelli Manganote3, F. Torres Da Silva
De Araujo, A. Vilela Pereira Universidade Estadual Paulista a, Universidade
Federal do ABC b, São Paulo, Brazil
S. Ahujaa, C.A. Bernardesa, L. Calligarisa, T.R. Fernandez Perez Tomeia, E.M.
Gregoresb, P.G. Mercadanteb, S.F. Novaesa, SandraS. Padulaa Institute for
Nuclear Research and Nuclear Energy, Bulgarian Academy of Sciences, Sofia,
Bulgaria
A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, A. Marinov, M. Misheva, M. Rodozov,
M. Shopova, G. Sultanov University of Sofia, Sofia, Bulgaria
A. Dimitrov, L. Litov, B. Pavlov, P. Petkov Beihang University, Beijing, China
W. Fang5, X. Gao5, L. Yuan Institute of High Energy Physics, Beijing, China
M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D.
Leggat, H. Liao, Z. Liu, F. Romeo, S.M. Shaheen6, A. Spiezia, J. Tao, Z. Wang,
E. Yazgan, H. Zhang, S. Zhang6, J. Zhao State Key Laboratory of Nuclear
Physics and Technology, Peking University, Beijing, China
Y. Ban, G. Chen, A. Levin, J. Li, L. Li, Q. Li, Y. Mao, S.J. Qian, D. Wang
Tsinghua University, Beijing, China
Y. Wang Universidad de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, C.A. Carrillo Montoya, L.F. Chaparro Sierra, C. Florez,
C.F. González Hernández, M.A. Segura Delgado University of Split, Faculty of
Electrical Engineering, Mechanical Engineering and Naval Architecture, Split,
Croatia
B. Courbon, N. Godinovic, D. Lelas, I. Puljak, T. Sculac University of Split,
Faculty of Science, Split, Croatia
Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia
V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, A. Starodumov7, T. Susa
University of Cyprus, Nicosia, Cyprus
M.W. Ather, A. Attikis, M. Kolosova, G. Mavromanolakis, J. Mousa, C. Nicolaou,
F. Ptochos, P.A. Razis, H. Rykaczewski Charles University, Prague, Czech
Republic
M. Finger8, M. Finger Jr.8 Escuela Politecnica Nacional, Quito, Ecuador
E. Ayala Universidad San Francisco de Quito, Quito, Ecuador
E. Carrera Jarrin Academy of Scientific Research and Technology of the Arab
Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt
Y. Assran9,10, S. Elgammal10, S. Khalil11 National Institute of Chemical
Physics and Biophysics, Tallinn, Estonia
S. Bhowmik, A. Carvalho Antunes De Oliveira, R.K. Dewanjee, K. Ehataht, M.
Kadastik, M. Raidal, C. Veelken Department of Physics, University of Helsinki,
Helsinki, Finland
P. Eerola, H. Kirschenmann, J. Pekkanen, M. Voutilainen Helsinki Institute of
Physics, Helsinki, Finland
J. Havukainen, J.K. Heikkilä, T. Järvinen, V. Karimäki, R. Kinnunen, T.
Lampén, K. Lassila-Perini, S. Laurila, S. Lehti, T. Lindén, P. Luukka, T.
Mäenpää, H. Siikonen, E. Tuominen, J. Tuominiemi Lappeenranta University of
Technology, Lappeenranta, Finland
T. Tuuva IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
M. Besancon, F. Couderc, M. Dejardin, D. Denegri, J.L. Faure, F. Ferri, S.
Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, C. Leloup,
E. Locci, J. Malcles, G. Negro, J. Rander, A. Rosowsky, M.Ö. Sahin, M. Titov
Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Université
Paris-Saclay, Palaiseau, France
A. Abdulsalam12, C. Amendola, I. Antropov, F. Beaudette, P. Busson, C.
Charlot, R. Granier de Cassagnac, I. Kucher, A. Lobanov, J. Martin Blanco, C.
Martin Perez, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P. Pigard, J.
Rembser, R. Salerno, J.B. Sauvan, Y. Sirois, A.G. Stahl Leiton, A. Zabi, A.
Zghiche Université de Strasbourg, CNRS, IPHC UMR 7178, Strasbourg, France
J.-L. Agram13, J. Andrea, D. Bloch, J.-M. Brom, E.C. Chabert, V. Cherepanov,
C. Collard, E. Conte13, J.-C. Fontaine13, D. Gelé, U. Goerlach, M. Jansová,
A.-C. Le Bihan, N. Tonon, P. Van Hove Centre de Calcul de l’Institut National
de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne,
France
S. Gadrat Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3,
Institut de Physique Nucléaire de Lyon, Villeurbanne, France
S. Beauceron, C. Bernet, G. Boudoul, N. Chanon, R. Chierici, D. Contardo, P.
Depasse, H. El Mamouni, J. Fay, L. Finco, S. Gascon, M. Gouzevitch, G.
Grenier, B. Ille, F. Lagarde, I.B. Laktineh, H. Lattaud, M. Lethuillier, L.
Mirabito, S. Perries, A. Popov14, V. Sordini, G. Touquet, M. Vander Donckt, S.
Viret Georgian Technical University, Tbilisi, Georgia
A. Khvedelidze8 Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze8 RWTH Aachen University, I. Physikalisches Institut, Aachen,
Germany
C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, M.P.
Rauch, C. Schomakers, J. Schulz, M. Teroerde, B. Wittmer RWTH Aachen
University, III. Physikalisches Institut A, Aachen, Germany
A. Albert, D. Duchardt, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, S. Ghosh,
A. Güth, T. Hebbeker, C. Heidemann, K. Hoepfner, H. Keller, L. Mastrolorenzo,
M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, T. Pook, M. Radziej, H.
Reithler, M. Rieger, A. Schmidt, D. Teyssier, S. Thüer RWTH Aachen University,
III. Physikalisches Institut B, Aachen, Germany
G. Flügge, O. Hlushchenko, T. Kress, A. Künsken, T. Müller, A. Nehrkorn, A.
Nowack, C. Pistone, O. Pooth, D. Roy, H. Sert, A. Stahl15 Deutsches
Elektronen-Synchrotron, Hamburg, Germany
M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, I. Babounikau, K.
Beernaert, O. Behnke, U. Behrens, A. Bermúdez Martínez, D. Bertsche, A.A. Bin
Anuar, K. Borras16, V. Botta, A. Campbell, P. Connor, C. Contreras-Campana, V.
Danilov, A. De Wit, M.M. Defranchis, C. Diez Pardos, D. Domínguez Damiani, G.
Eckerlin, T. Eichhorn, A. Elwood, E. Eren, E. Gallo17, A. Geiser, J.M. Grados
Luyando, A. Grohsjean, M. Guthoff, M. Haranko, A. Harb, J. Hauk, H. Jung, M.
Kasemann, J. Keaveney, C. Kleinwort, J. Knolle, D. Krücker, W. Lange, A.
Lelek, T. Lenz, J. Leonard, K. Lipka, W. Lohmann18, R. Mankel, I.-A. Melzer-
Pellmann, A.B. Meyer, M. Meyer, M. Missiroli, G. Mittag, J. Mnich, V.
Myronenko, S.K. Pflitsch, D. Pitzl, A. Raspereza, M. Savitskyi, P. Saxena, P.
Schütze, C. Schwanenberger, R. Shevchenko, A. Singh, H. Tholen, O. Turkot, A.
Vagnerini, G.P. Van Onsem, R. Walsh, Y. Wen, K. Wichmann, C. Wissing, O.
Zenaiev University of Hamburg, Hamburg, Germany
R. Aggleton, S. Bein, L. Benato, A. Benecke, V. Blobel, T. Dreyer, A.
Ebrahimi, E. Garutti, D. Gonzalez, P. Gunnellini, J. Haller, A. Hinzmann, A.
Karavdina, G. Kasieczka, R. Klanner, R. Kogler, N. Kovalchuk, S. Kurz, V.
Kutzner, J. Lange, D. Marconi, J. Multhaup, M. Niedziela, C.E.N. Niemeyer, D.
Nowatschin, A. Perieanu, A. Reimers, O. Rieger, C. Scharf, P. Schleper, S.
Schumann, J. Schwandt, J. Sonneveld, H. Stadie, G. Steinbrück, F.M. Stober, M.
Stöver, A. Vanhoefer, B. Vormwald, I. Zoi Karlsruher Institut fuer
Technologie, Karlsruhe, Germany
M. Akbiyik, C. Barth, M. Baselga, S. Baur, E. Butz, R. Caspart, T. Chwalek, F.
Colombo, W. De Boer, A. Dierlamm, K. El Morabit, N. Faltermann, B. Freund, M.
Giffels, M.A. Harrendorf, F. Hartmann15, S.M. Heindl, U. Husemann, I.
Katkov14, S. Kudella, S. Mitra, M.U. Mozer, Th. Müller, M. Musich, M. Plagge,
G. Quast, K. Rabbertz, M. Schröder, I. Shvetsov, H.J. Simonis, R. Ulrich, S.
Wayand, M. Weber, T. Weiler, C. Wöhrmann, R. Wolf Institute of Nuclear and
Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece
G. Anagnostou, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas, G.
Paspalaki, I. Topsis-Giotis National and Kapodistrian University of Athens,
Athens, Greece
G. Karathanasis, S. Kesisoglou, P. Kontaxakis, A. Panagiotou, I. Papavergou,
N. Saoulidou, E. Tziaferi, K. Vellidis National Technical University of
Athens, Athens, Greece
K. Kousouris, I. Papakrivopoulos, G. Tsipolitis University of Ioánnina,
Ioánnina, Greece
I. Evangelou, C. Foudas, P. Gianneios, P. Katsoulis, P. Kokkas, S. Mallios, N.
Manthos, I. Papadopoulos, E. Paradas, J. Strologas, F.A. Triantis, D.
Tsitsonis MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
M. Bartók19, M. Csanad, N. Filipovic, P. Major, M.I. Nagy, G. Pasztor, O.
Surányi, G.I. Veres Wigner Research Centre for Physics, Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath20, Á. Hunyadi, F. Sikler, T.Á. Vámi, V.
Veszpremi, G. Vesztergombi${}^{\textrm{\textdagger}}$ Institute of Nuclear
Research ATOMKI, Debrecen, Hungary
N. Beni, S. Czellar, J. Karancsi21, A. Makovec, J. Molnar, Z. Szillasi
Institute of Physics, University of Debrecen, Debrecen, Hungary
P. Raics, Z.L. Trocsanyi, B. Ujvari Indian Institute of Science (IISc),
Bangalore, India
S. Choudhury, J.R. Komaragiri, P.C. Tiwari National Institute of Science
Education and Research, HBNI, Bhubaneswar, India
S. Bahinipati22, C. Kar, P. Mal, K. Mandal, A. Nayak23, D.K. Sahoo22, S.K.
Swain Panjab University, Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, S. Chauhan, R. Chawla, N. Dhingra, R.
Gupta, A. Kaur, M. Kaur, S. Kaur, P. Kumari, M. Lohan, A. Mehta, K. Sandeep,
S. Sharma, J.B. Singh, A.K. Virdi, G. Walia University of Delhi, Delhi, India
A. Bhardwaj, B.C. Choudhary, R.B. Garg, M. Gola, S. Keshri, Ashok Kumar, S.
Malhotra, M. Naimuddin, P. Priyanka, K. Ranjan, Aashaq Shah, R. Sharma Saha
Institute of Nuclear Physics, HBNI, Kolkata, India
R. Bhardwaj24, M. Bharti24, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep24,
D. Bhowmik, S. Dey, S. Dutt24, S. Dutta, S. Ghosh, K. Mondal, S. Nandan, A.
Purohit, P.K. Rout, A. Roy, S. Roy Chowdhury, G. Saha, S. Sarkar, M. Sharan,
B. Singh24, S. Thakur24 Indian Institute of Technology Madras, Madras, India
P.K. Behera Bhabha Atomic Research Centre, Mumbai, India
R. Chudasama, D. Dutta, V. Jha, V. Kumar, P.K. Netrakanti, L.M. Pant, P.
Shukla Tata Institute of Fundamental Research-A, Mumbai, India
T. Aziz, M.A. Bhat, S. Dugad, G.B. Mohanty, N. Sur, B. Sutar, RavindraKumar
Verma Tata Institute of Fundamental Research-B, Mumbai, India
S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, Sa. Jain, S.
Karmakar, S. Kumar, M. Maity25, G. Majumder, K. Mazumdar, N. Sahoo, T.
Sarkar25 Indian Institute of Science Education and Research (IISER), Pune,
India
S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, S.
Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
S. Chenarani26, E. Eskandari Tadavani, S.M. Etesami26, M. Khakzad, M.
Mohammadi Najafabadi, M. Naseri, F. Rezaei Hosseinabadi, B. Safarzadeh27, M.
Zeinali University College Dublin, Dublin, Ireland
M. Felcini, M. Grunewald INFN Sezione di Bari a, Università di Bari b,
Politecnico di Bari c, Bari, Italy
M. Abbresciaa,b, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L. Cristellaa,b,
N. De Filippisa,c, M. De Palmaa,b, A. Di Florioa,b, F. Erricoa,b, L. Fiorea,
A. Gelmia,b, G. Iasellia,c, M. Incea,b, S. Lezkia,b, G. Maggia,c, M. Maggia,
G. Minielloa,b, S. Mya,b, S. Nuzzoa,b, A. Pompilia,b, G. Pugliesea,c, R.
Radognaa, A. Ranieria, G. Selvaggia,b, A. Sharmaa, L. Silvestrisa, R.
Vendittia, P. Verwilligena, G. Zitoa INFN Sezione di Bologna a, Università di
Bologna b, Bologna, Italy
G. Abbiendia, C. Battilanaa,b, D. Bonacorsia,b, L. Borgonovia,b, S. Braibant-
Giacomellia,b, R. Campaninia,b, P. Capiluppia,b, A. Castroa,b, F.R. Cavalloa,
S.S. Chhibraa,b, C. Cioccaa, G. Codispotia,b, M. Cuffiania,b, G.M.
Dallavallea, F. Fabbria, A. Fanfania,b, E. Fontanesi, P. Giacomellia, C.
Grandia, L. Guiduccia,b, S. Lo Meoa, S. Marcellinia, G. Masettia, A.
Montanaria, F.L. Navarriaa,b, A. Perrottaa, F. Primaveraa,b,15, A.M. Rossia,b,
T. Rovellia,b, G.P. Sirolia,b, N. Tosia INFN Sezione di Catania a, Università
di Catania b, Catania, Italy
S. Albergoa,b, A. Di Mattiaa, R. Potenzaa,b, A. Tricomia,b, C. Tuvea,b INFN
Sezione di Firenze a, Università di Firenze b, Firenze, Italy
G. Barbaglia, K. Chatterjeea,b, V. Ciullia,b, C. Civininia, R.
D’Alessandroa,b, E. Focardia,b, G. Latino, P. Lenzia,b, M. Meschinia, S.
Paolettia, L. Russoa,28, G. Sguazzonia, D. Stroma, L. Viliania INFN Laboratori
Nazionali di Frascati, Frascati, Italy
L. Benussi, S. Bianco, F. Fabbri, D. Piccolo INFN Sezione di Genova a,
Università di Genova b, Genova, Italy
F. Ferroa, R. Mulargiaa,b, F. Raveraa,b, E. Robuttia, S. Tosia,b INFN Sezione
di Milano-Bicocca a, Università di Milano-Bicocca b, Milano, Italy
A. Benagliaa, A. Beschib, F. Brivioa,b, V. Cirioloa,b,15, S. Di Guidaa,d,15,
M.E. Dinardoa,b, S. Fiorendia,b, S. Gennaia, A. Ghezzia,b, P. Govonia,b, M.
Malbertia,b, S. Malvezzia, A. Massironia,b, D. Menascea, F. Monti, L. Moronia,
M. Paganonia,b, D. Pedrinia, S. Ragazzia,b, T. Tabarelli de Fatisa,b, D.
Zuoloa,b INFN Sezione di Napoli a, Università di Napoli ’Federico II’ b,
Napoli, Italy, Università della Basilicata c, Potenza, Italy, Università G.
Marconi d, Roma, Italy
S. Buontempoa, N. Cavalloa,c, A. De Iorioa,b, A. Di Crescenzoa,b, F.
Fabozzia,c, F. Fiengaa, G. Galatia, A.O.M. Iorioa,b, W.A. Khana, L. Listaa, S.
Meolaa,d,15, P. Paoluccia,15, C. Sciaccaa,b, E. Voevodinaa,b INFN Sezione di
Padova a, Università di Padova b, Padova, Italy, Università di Trento c,
Trento, Italy
P. Azzia, N. Bacchettaa, D. Biselloa,b, A. Bolettia,b, A. Bragagnolo, R.
Carlina,b, P. Checchiaa, M. Dall’Ossoa,b, P. De Castro Manzanoa, T. Dorigoa,
U. Gasparinia,b, A. Gozzelinoa, S.Y. Hoh, S. Lacapraraa, P. Lujan, M.
Margonia,b, A.T. Meneguzzoa,b, M. Passaseoa, J. Pazzinia,b, N. Pozzobona,b, P.
Ronchesea,b, R. Rossina,b, F. Simonettoa,b, A. Tiko, E. Torassaa, M. Tosia,b,
M. Zanettia,b, P. Zottoa,b, G. Zumerlea,b INFN Sezione di Pavia a, Università
di Pavia b, Pavia, Italy
A. Braghieria, A. Magnania, P. Montagnaa,b, S.P. Rattia,b, V. Rea, M.
Ressegottia,b, C. Riccardia,b, P. Salvinia, I. Vaia,b, P. Vituloa,b INFN
Sezione di Perugia a, Università di Perugia b, Perugia, Italy
M. Biasinia,b, G.M. Bileia, C. Cecchia,b, D. Ciangottinia,b, L. Fanòa,b, P.
Laricciaa,b, R. Leonardia,b, E. Manonia, G. Mantovania,b, V. Mariania,b, M.
Menichellia, A. Rossia,b, A. Santocchiaa,b, D. Spigaa INFN Sezione di Pisa a,
Università di Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy
K. Androsova, P. Azzurria, G. Bagliesia, L. Bianchinia, T. Boccalia, L.
Borrello, R. Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, G. Fedia, F. Fioria,c,
L. Gianninia,c, A. Giassia, M.T. Grippoa, F. Ligabuea,c, E. Mancaa,c, G.
Mandorlia,c, A. Messineoa,b, F. Pallaa, A. Rizzia,b, G. Rolandi29, P.
Spagnoloa, R. Tenchinia, G. Tonellia,b, A. Venturia, P.G. Verdinia INFN
Sezione di Roma a, Sapienza Università di Roma b, Rome, Italy
L. Baronea,b, F. Cavallaria, M. Cipriania,b, D. Del Rea,b, E. Di Marcoa,b, M.
Diemoza, S. Gellia,b, E. Longoa,b, B. Marzocchia,b, P. Meridiania, G.
Organtinia,b, F. Pandolfia, R. Paramattia,b, F. Preiatoa,b, S. Rahatloua,b, C.
Rovellia, F. Santanastasioa,b INFN Sezione di Torino a, Università di Torino
b, Torino, Italy, Università del Piemonte Orientale c, Novara, Italy
N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, N. Bartosika,
R. Bellana,b, C. Biinoa, N. Cartigliaa, F. Cennaa,b, S. Comettia, M. Costaa,b,
R. Covarellia,b, N. Demariaa, B. Kiania,b, C. Mariottia, S. Masellia, E.
Migliorea,b, V. Monacoa,b, E. Monteila,b, M. Montenoa, M.M. Obertinoa,b, L.
Pachera,b, N. Pastronea, M. Pelliccionia, G.L. Pinna Angionia,b, A. Romeroa,b,
M. Ruspaa,c, R. Sacchia,b, K. Shchelinaa,b, V. Solaa, A. Solanoa,b, D.
Soldia,b, A. Staianoa INFN Sezione di Trieste a, Università di Trieste b,
Trieste, Italy
S. Belfortea, V. Candelisea,b, M. Casarsaa, F. Cossuttia, A. Da Rolda,b, G.
Della Riccaa,b, F. Vazzolera,b, A. Zanettia Kyungpook National University,
Daegu, Korea
D.H. Kim, G.N. Kim, M.S. Kim, J. Lee, S. Lee, S.W. Lee, C.S. Moon, Y.D. Oh,
S.I. Pak, S. Sekmen, D.C. Son, Y.C. Yang Chonnam National University,
Institute for Universe and Elementary Particles, Kwangju, Korea
H. Kim, D.H. Moon, G. Oh Hanyang University, Seoul, Korea
B. Francois, J. Goh30, T.J. Kim Korea University, Seoul, Korea
S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, K. Lee, K.S. Lee, S.
Lee, J. Lim, S.K. Park, Y. Roh Sejong University, Seoul, Korea
H.S. Kim Seoul National University, Seoul, Korea
J. Almond, J. Kim, J.S. Kim, H. Lee, K. Lee, K. Nam, S.B. Oh, B.C. Radburn-
Smith, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu University of Seoul, Seoul,
Korea
D. Jeon, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park Sungkyunkwan University,
Suwon, Korea
Y. Choi, C. Hwang, J. Lee, I. Yu Vilnius University, Vilnius, Lithuania
V. Dudenas, A. Juodagalvis, J. Vaitkus National Centre for Particle Physics,
Universiti Malaya, Kuala Lumpur, Malaysia
I. Ahmed, Z.A. Ibrahim, M.A.B. Md Ali31, F. Mohamad Idris32, W.A.T. Wan
Abdullah, M.N. Yusli, Z. Zolkapli Universidad de Sonora (UNISON), Hermosillo,
Mexico
J.F. Benitez, A. Castaneda Hernandez, J.A. Murillo Quijada Centro de
Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico
H. Castilla-Valdez, E. De La Cruz-Burelo, M.C. Duran-Osuna, I. Heredia-De La
Cruz33, R. Lopez-Fernandez, J. Mejia Guisao, R.I. Rabadan-Trejo, M. Ramirez-
Garcia, G. Ramirez-Sanchez, R. Reyes-Almanza, A. Sanchez-Hernandez Universidad
Iberoamericana, Mexico City, Mexico
S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita
Universidad Autonoma de Puebla, Puebla, Mexico
J. Eysermans, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad
Autónoma de San Luis Potosí, San Luis Potosí, Mexico
A. Morelos Pineda University of Auckland, Auckland, New Zealand
D. Krofcheck University of Canterbury, Christchurch, New Zealand
S. Bheesette, P.H. Butler National Centre for Physics, Quaid-I-Azam
University, Islamabad, Pakistan
A. Ahmad, M. Ahmad, M.I. Asghar, Q. Hassan, H.R. Hoorani, A. Saddique, M.A.
Shah, M. Shoaib, M. Waqas National Centre for Nuclear Research, Swierk, Poland
H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Górski, M. Kazana, M.
Szleper, P. Traczyk, P. Zalewski Institute of Experimental Physics, Faculty of
Physics, University of Warsaw, Warsaw, Poland
K. Bunkowski, A. Byszuk34, K. Doroba, A. Kalinowski, M. Konecki, J.
Krolikowski, M. Misiura, M. Olszewski, A. Pyskir, M. Walczak Laboratório de
Instrumentação e Física Experimental de Partículas, Lisboa, Portugal
M. Araujo, P. Bargassa, C. Beirão Da Cruz E Silva, A. Di Francesco, P.
Faccioli, B. Galinhas, M. Gallinaro, J. Hollar, N. Leonardo, J. Seixas, G.
Strong, O. Toldaiev, J. Varela Joint Institute for Nuclear Research, Dubna,
Russia
S. Afanasiev, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev,
V. Karjavine, A. Lanev, A. Malakhov, V. Matveev35,36, P. Moisenz, V. Palichik,
V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin,
A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg),
Russia
V. Golovtsov, Y. Ivanov, V. Kim37, E. Kuznetsova38, P. Levchenko, V. Murzin,
V. Oreshkin, I. Smirnov, D. Sosnov, V. Sulimov, L. Uvarov, S. Vavilov, A.
Vorobyev Institute for Nuclear Research, Moscow, Russia
Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov,
N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical
and Experimental Physics, Moscow, Russia
V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G.
Safronov, A. Spiridonov, A. Stepennov, V. Stolin, M. Toms, E. Vlasov, A.
Zhokin Moscow Institute of Physics and Technology, Moscow, Russia
T. Aushev National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
R. Chistov39, M. Danilov39, P. Parygin, D. Philippov, S. Polikarpov39, E.
Tarkovskii P.N. Lebedev Physical Institute, Moscow, Russia
V. Andreev, M. Azarkin, I. Dremin36, M. Kirakosyan, A. Terkulov Skobeltsyn
Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow,
Russia
A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin40, L. Dudko, A.
Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, S.
Petrushanko, V. Savrin, A. Snigirev Novosibirsk State University (NSU),
Novosibirsk, Russia
A. Barnyakov41, V. Blinov41, T. Dimova41, L. Kardapoltsev41, Y. Skovpen41
Institute for High Energy Physics of National Research Centre ’Kurchatov
Institute’, Protvino, Russia
I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, A. Godizov, V. Kachanov,
A. Kalinin, D. Konstantinov, P. Mandrik, V. Petrov, R. Ryutin, S.
Slabospitskii, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov National
Research Tomsk Polytechnic University, Tomsk, Russia
A. Babaev, S. Baidali, V. Okhotnikov University of Belgrade, Faculty of
Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia
P. Adzic42, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic Centro de
Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid,
Spain
J. Alcaraz Maestre, A. Álvarez Fernández, I. Bachiller, M. Barrio Luna, J.A.
Brochero Cifuentes, M. Cerrada, N. Colino, B. De La Cruz, A. Delgado Peris, C.
Fernandez Bedoya, J.P. Fernández Ramos, J. Flix, M.C. Fouz, O. Gonzalez Lopez,
S. Goy Lopez, J.M. Hernandez, M.I. Josa, D. Moran, A. Pérez-Calero Yzquierdo,
J. Puerta Pelayo, I. Redondo, L. Romero, M.S. Soares, A. Triossi Universidad
Autónoma de Madrid, Madrid, Spain
C. Albajar, J.F. de Trocóniz Universidad de Oviedo, Oviedo, Spain
J. Cuevas, C. Erice, J. Fernandez Menendez, S. Folgueras, I. Gonzalez
Caballero, J.R. González Fernández, E. Palencia Cortezon, V. Rodríguez Bouza,
S. Sanchez Cruz, P. Vischia, J.M. Vizan Garcia Instituto de Física de
Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain
I.J. Cabrillo, A. Calderon, B. Chazin Quero, J. Duarte Campderros, M.
Fernandez, P.J. Fernández Manteca, A. García Alonso, J. Garcia-Ferrero, G.
Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, P. Martinez Ruiz del
Arbol, F. Matorras, J. Piedra Gomez, C. Prieels, T. Rodrigo, A. Ruiz-Jimeno,
L. Scodellaro, N. Trevisani, I. Vila, R. Vilar Cortabitarte University of
Ruhuna, Department of Physics, Matara, Sri Lanka
N. Wickramage CERN, European Organization for Nuclear Research, Geneva,
Switzerland
D. Abbaneo, B. Akgun, E. Auffray, G. Auzinger, P. Baillon, A.H. Ball, D.
Barney, J. Bendavid, M. Bianco, A. Bocci, C. Botta, E. Brondolin, T.
Camporesi, M. Cepeda, G. Cerminara, E. Chapon, Y. Chen, G. Cucciati, D.
d’Enterria, A. Dabrowski, N. Daci, V. Daponte, A. David, A. De Roeck, N.
Deelen, M. Dobson, M. Dünser, N. Dupont, A. Elliott-Peisert, P. Everaerts, F.
Fallavollita43, D. Fasanella, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, A.
Gilbert, K. Gill, F. Glege, M. Gruchala, M. Guilbaud, D. Gulhan, J. Hegeman,
C. Heidegger, V. Innocente, A. Jafari, P. Janot, O. Karacheban18, J. Kieseler,
A. Kornmayer, M. Krammer1, C. Lange, P. Lecoq, C. Lourenço, L. Malgeri, M.
Mannelli, F. Meijers, J.A. Merlin, S. Mersi, E. Meschi, P. Milenovic44, F.
Moortgat, M. Mulders, J. Ngadiuba, S. Nourbakhsh, S. Orfanelli, L. Orsini, F.
Pantaleo15, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G. Petrucciani, A.
Pfeiffer, M. Pierini, F.M. Pitters, D. Rabady, A. Racz, T. Reis, M. Rovere, H.
Sakulin, C. Schäfer, C. Schwick, M. Seidel, M. Selvaggi, A. Sharma, P. Silva,
P. Sphicas45, A. Stakia, J. Steggemann, D. Treille, A. Tsirou, V. Veckalns46,
M. Verzetti, W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland
L. Caminada47, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C.
Kaestli, D. Kotlinski, U. Langenegger, T. Rohe, S.A. Wiederkehr ETH Zurich -
Institute for Particle Physics and Astrophysics (IPA), Zurich, Switzerland
M. Backhaus, L. Bäni, P. Berger, N. Chernyavskaya, G. Dissertori, M. Dittmar,
M. Donegà, C. Dorfer, T.A. Gómez Espinosa, C. Grab, D. Hits, T. Klijnsma, W.
Lustermann, R.A. Manzoni, M. Marionneau, M.T. Meinhard, F. Micheli, P.
Musella, F. Nessi-Tedaldi, J. Pata, F. Pauss, G. Perrin, L. Perrozzi, S.
Pigazzini, M. Quittnat, C. Reissel, D. Ruini, D.A. Sanz Becerra, M.
Schönenberger, L. Shchutska, V.R. Tavolaro, K. Theofilatos, M.L. Vesterbacka
Olsson, R. Wallny, D.H. Zhu Universität Zürich, Zurich, Switzerland
T.K. Aarrestad, C. Amsler48, D. Brzhechko, M.F. Canelli, A. De Cosa, R. Del
Burgo, S. Donato, C. Galloni, T. Hreus, B. Kilminster, S. Leontsinis, I.
Neutelings, G. Rauco, P. Robmann, D. Salerno, K. Schweiger, C. Seitz, Y.
Takahashi, A. Zucchetta National Central University, Chung-Li, Taiwan
Y.H. Chang, K.y. Cheng, T.H. Doan, R. Khurana, C.M. Kuo, W. Lin, A.
Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan
P. Chang, Y. Chao, K.F. Chen, P.H. Chen, W.-S. Hou, Arun Kumar, Y.F. Liu,
R.-S. Lu, E. Paganis, A. Psallidas, A. Steen Chulalongkorn University, Faculty
of Science, Department of Physics, Bangkok, Thailand
B. Asavapibhop, N. Srimanobhas, N. Suwonjandee Çukurova University, Physics
Department, Science and Art Faculty, Adana, Turkey
A. Bat, F. Boran, S. Cerci49, S. Damarseckin, Z.S. Demiroglu, F. Dolek, C.
Dozen, I. Dumanoglu, S. Girgis, G. Gokbulut, Y. Guler, E. Gurpinar, I. Hos50,
C. Isik, E.E. Kangal51, O. Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G.
Onengut, K. Ozdemir52, S. Ozturk53, B. Tali49, U.G. Tok, H. Topakli53, S.
Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University,
Physics Department, Ankara, Turkey
B. Isildak54, G. Karapinar55, M. Yalvac, M. Zeyrek Bogazici University,
Istanbul, Turkey
I.O. Atakisi, E. Gülmez, M. Kaya56, O. Kaya57, S. Ozkorucuklu58, S. Tekten,
E.A. Yetkin59 Istanbul Technical University, Istanbul, Turkey
M.N. Agaras, A. Cakir, K. Cankocak, Y. Komurcu, S. Sen60 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. Newbold61,
S. Paramesvaran, B. Penning, T. Sakuma, D. Smith, V.J. Smith, J. Taylor, A.
Titterton Rutherford Appleton Laboratory, Didcot, United Kingdom
K.W. Bell, A. Belyaev62, C. Brew, R.M. Brown, D. Cieri, D.J.A. Cockerill, J.A.
Coughlan, K. Harder, S. Harper, J. Linacre, E. Olaiya, D. Petyt, C.H.
Shepherd-Themistocleous, A. Thea, I.R. Tomalin, T. Williams, W.J. Womersley
Imperial College, London, United Kingdom
R. Bainbridge, P. Bloch, J. Borg, S. Breeze, O. Buchmuller, A. Bundock, D.
Colling, P. Dauncey, G. Davies, M. Della Negra, R. Di Maria, G. Hall, G. Iles,
T. James, M. Komm, C. Laner, L. Lyons, A.-M. Magnan, S. Malik, A. Martelli, J.
Nash63, A. Nikitenko7, V. Palladino, M. Pesaresi, D.M. Raymond, A. Richards,
A. Rose, E. Scott, C. Seez, A. Shtipliyski, G. Singh, M. Stoye, T. Strebler,
S. Summers, A. Tapper, K. Uchida, T. Virdee15, N. Wardle, D. Winterbottom, J.
Wright, S.C. Zenz Brunel University, Uxbridge, United Kingdom
J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, C.K. Mackay, A. Morton, I.D. Reid,
L. Teodorescu, S. Zahid Baylor University, Waco, USA
K. Call, J. Dittmann, K. Hatakeyama, H. Liu, C. Madrid, B. McMaster, N.
Pastika, C. Smith Catholic University of America, Washington, DC, USA
R. Bartek, A. Dominguez The University of Alabama, Tuscaloosa, USA
A. Buccilli, S.I. Cooper, C. Henderson, P. Rumerio, C. West Boston University,
Boston, USA
D. Arcaro, T. Bose, D. Gastler, D. Pinna, D. Rankin, C. Richardson, J. Rohlf,
L. Sulak, D. Zou Brown University, Providence, USA
G. Benelli, X. Coubez, D. Cutts, M. Hadley, J. Hakala, U. Heintz, J.M.
Hogan64, K.H.M. Kwok, E. Laird, G. Landsberg, J. Lee, Z. Mao, M. Narain, S.
Sagir65, R. Syarif, E. Usai, D. Yu University of California, Davis, Davis, USA
R. Band, C. Brainerd, R. Breedon, D. Burns, M. Calderon De La Barca Sanchez,
M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk,
W. Ko, O. Kukral, R. Lander, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout,
M. Shi, D. Stolp, D. Taylor, K. Tos, M. Tripathi, Z. Wang, F. Zhang University
of California, Los Angeles, USA
M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M.
Ignatenko, N. Mccoll, S. Regnard, D. Saltzberg, C. Schnaible, V. Valuev
University of California, Riverside, Riverside, USA
E. Bouvier, K. Burt, R. Clare, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, G.
Karapostoli, E. Kennedy, F. Lacroix, O.R. Long, M. Olmedo Negrete, M.I.
Paneva, W. Si, L. Wang, H. Wei, S. Wimpenny, B.R. Yates University of
California, San Diego, La Jolla, USA
J.G. Branson, P. Chang, S. Cittolin, M. Derdzinski, R. Gerosa, D. Gilbert, B.
Hashemi, A. Holzner, D. Klein, G. Kole, V. Krutelyov, J. Letts, M.
Masciovecchio, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon,
M. Tadel, A. Vartak, S. Wasserbaech66, J. Wood, F. Würthwein, A. Yagil, G.
Zevi Della Porta University of California, Santa Barbara - Department of
Physics, Santa Barbara, USA
N. Amin, R. Bhandari, J. Bradmiller-Feld, C. Campagnari, M. Citron, A. Dishaw,
V. Dutta, M. Franco Sevilla, L. Gouskos, R. Heller, J. Incandela, A.
Ovcharova, H. Qu, J. Richman, D. Stuart, I. Suarez, S. Wang, J. Yoo California
Institute of Technology, Pasadena, USA
D. Anderson, A. Bornheim, J.M. Lawhorn, N. Lu, H.B. Newman, T.Q. Nguyen, M.
Spiropulu, J.R. Vlimant, R. Wilkinson, S. Xie, Z. Zhang, R.Y. Zhu Carnegie
Mellon University, Pittsburgh, USA
M.B. Andrews, T. Ferguson, T. Mudholkar, M. Paulini, M. Sun, I. Vorobiev, M.
Weinberg University of Colorado Boulder, Boulder, USA
J.P. Cumalat, W.T. Ford, F. Jensen, A. Johnson, M. Krohn, E. MacDonald, T.
Mulholland, R. Patel, A. Perloff, K. Stenson, K.A. Ulmer, S.R. Wagner Cornell
University, Ithaca, USA
J. Alexander, J. Chaves, Y. Cheng, J. Chu, A. Datta, K. Mcdermott, N. Mirman,
J.R. Patterson, D. Quach, A. Rinkevicius, A. Ryd, L. Skinnari, L. Soffi, S.M.
Tan, Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek Fermi National
Accelerator Laboratory, Batavia, USA
S. Abdullin, M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, A. Apyan, S.
Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, K. Burkett,
J.N. Butler, A. Canepa, G.B. Cerati, H.W.K. Cheung, F. Chlebana, M. Cremonesi,
J. Duarte, V.D. Elvira, J. Freeman, Z. Gecse, E. Gottschalk, L. Gray, D.
Green, S. Grünendahl, O. Gutsche, J. Hanlon, R.M. Harris, S. Hasegawa, J.
Hirschauer, Z. Hu, B. Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, B.
Klima, M.J. Kortelainen, B. Kreis, S. Lammel, D. Lincoln, R. Lipton, M. Liu,
T. Liu, J. Lykken, K. Maeshima, J.M. Marraffino, D. Mason, P. McBride, P.
Merkel, S. Mrenna, S. Nahn, V. O’Dell, K. Pedro, C. Pena, O. Prokofyev, G.
Rakness, L. Ristori, A. Savoy-Navarro67, B. Schneider, E. Sexton-Kennedy, A.
Soha, W.J. Spalding, L. Spiegel, S. Stoynev, J. Strait, N. Strobbe, L. Taylor,
S. Tkaczyk, N.V. Tran, L. Uplegger, E.W. Vaandering, C. Vernieri, M.
Verzocchi, R. Vidal, M. Wang, H.A. Weber, A. Whitbeck University of Florida,
Gainesville, USA
D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerhoff, L. Cadamuro,
A. Carnes, D. Curry, R.D. Field, S.V. Gleyzer, B.M. Joshi, J. Konigsberg, A.
Korytov, K.H. Lo, P. Ma, K. Matchev, H. Mei, G. Mitselmakher, D. Rosenzweig,
K. Shi, D. Sperka, J. Wang, S. Wang, X. Zuo Florida International University,
Miami, USA
Y.R. Joshi, S. Linn Florida State University, Tallahassee, USA
A. Ackert, T. Adams, A. Askew, S. Hagopian, V. Hagopian, K.F. Johnson, T.
Kolberg, G. Martinez, T. Perry, H. Prosper, A. Saha, C. Schiber, R. Yohay
Florida Institute of Technology, Melbourne, USA
M.M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, M.
Rahmani, T. Roy, F. Yumiceva University of Illinois at Chicago (UIC), Chicago,
USA
M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, R. Cavanaugh, X. Chen, S.
Dittmer, O. Evdokimov, C.E. Gerber, D.A. Hangal, D.J. Hofman, K. Jung, J.
Kamin, C. Mills, I.D. Sandoval Gonzalez, M.B. Tonjes, H. Trauger, N. Varelas,
H. Wang, X. Wang, Z. Wu, J. Zhang The University of Iowa, Iowa City, USA
M. Alhusseini, B. Bilki68, W. Clarida, K. Dilsiz69, S. Durgut, R.P.
Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, A. Mestvirishvili, A.
Moeller, J. Nachtman, H. Ogul70, Y. Onel, F. Ozok71, A. Penzo, C. Snyder, E.
Tiras, J. Wetzel Johns Hopkins University, Baltimore, USA
B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan,
W.T. Hung, P. Maksimovic, J. Roskes, U. Sarica, M. Swartz, M. Xiao, C. You The
University of Kansas, Lawrence, USA
A. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, A. Bylinkin, J.
Castle, S. Khalil, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, C.
Rogan, S. Sanders, E. Schmitz, J.D. Tapia Takaki, Q. Wang Kansas State
University, Manhattan, USA
S. Duric, A. Ivanov, K. Kaadze, D. Kim, Y. Maravin, D.R. Mendis, T. Mitchell,
A. Modak, A. Mohammadi, L.K. Saini, N. Skhirtladze Lawrence Livermore National
Laboratory, Livermore, USA
F. Rebassoo, D. Wright University of Maryland, College Park, USA
A. Baden, O. Baron, A. Belloni, S.C. Eno, Y. Feng, C. Ferraioli, N.J. Hadley,
S. Jabeen, G.Y. Jeng, R.G. Kellogg, J. Kunkle, A.C. Mignerey, S. Nabili, F.
Ricci-Tam, Y.H. Shin, A. Skuja, S.C. Tonwar, K. Wong Massachusetts Institute
of Technology, Cambridge, USA
D. Abercrombie, B. Allen, V. Azzolini, A. Baty, G. Bauer, R. Bi, S. Brandt, W.
Busza, I.A. Cali, M. D’Alfonso, Z. Demiragli, G. Gomez Ceballos, M. Goncharov,
P. Harris, D. Hsu, M. Hu, Y. Iiyama, G.M. Innocenti, M. Klute, D. Kovalskyi,
Y.-J. Lee, P.D. Luckey, B. Maier, A.C. Marini, C. Mcginn, C. Mironov, S.
Narayanan, X. Niu, C. Paus, C. Roland, G. Roland, G.S.F. Stephans, K. Sumorok,
K. Tatar, D. Velicanu, J. Wang, T.W. Wang, B. Wyslouch, S. Zhaozhong
University of Minnesota, Minneapolis, USA
A.C. Benvenuti${}^{\textrm{\textdagger}}$, R.M. Chatterjee, A. Evans, P.
Hansen, J. Hiltbrand, Sh. Jain, S. Kalafut, Y. Kubota, Z. Lesko, J. Mans, N.
Ruckstuhl, R. Rusack, M.A. Wadud University of Mississippi, Oxford, USA
J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA
E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, F. Golf, R. Gonzalez Suarez,
R. Kamalieddin, I. Kravchenko, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger
State University of New York at Buffalo, Buffalo, USA
A. Godshalk, C. Harrington, I. Iashvili, A. Kharchilava, C. Mclean, D. Nguyen,
A. Parker, S. Rappoccio, B. Roozbahani Northeastern University, Boston, USA
G. Alverson, E. Barberis, C. Freer, Y. Haddad, A. Hortiangtham, D.M. Morse, T.
Orimoto, R. Teixeira De Lima, T. Wamorkar, B. Wang, A. Wisecarver, D. Wood
Northwestern University, Evanston, USA
S. Bhattacharya, J. Bueghly, O. Charaf, K.A. Hahn, N. Mucia, N. Odell, M.H.
Schmitt, K. Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame,
USA
R. Bucci, N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N.
Kellams, K. Lannon, W. Li, N. Loukas, N. Marinelli, F. Meng, C. Mueller, Y.
Musienko35, 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, C.
Hill, W. Ji, T.Y. Ling, W. Luo, B.L. Winer Princeton University, Princeton,
USA
S. Cooperstein, P. Elmer, J. Hardenbrook, S. Higginbotham, A. Kalogeropoulos,
D. Lange, M.T. Lucchini, J. Luo, D. Marlow, K. Mei, I. Ojalvo, J. Olsen, C.
Palmer, P. Piroué, J. Salfeld-Nebgen, D. Stickland, C. Tully University of
Puerto Rico, Mayaguez, USA
S. Malik, S. Norberg Purdue University, West Lafayette, USA
A. Barker, V.E. Barnes, S. Das, L. Gutay, M. Jones, A.W. Jung, A. Khatiwada,
B. Mahakud, D.H. Miller, N. Neumeister, C.C. Peng, S. Piperov, H. Qiu, J.F.
Schulte, J. Sun, F. Wang, R. Xiao, W. Xie Purdue University Northwest,
Hammond, USA
T. Cheng, J. Dolen, N. Parashar Rice University, Houston, USA
Z. Chen, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Kilpatrick, W. Li, B.P.
Padley, J. Roberts, J. Rorie, W. Shi, Z. Tu, A. Zhang University of Rochester,
Rochester, USA
A. Bodek, P. de Barbaro, R. Demina, Y.t. Duh, J.L. Dulemba, C. Fallon, T.
Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs, A.
Khukhunaishvili, E. Ranken, P. Tan, R. Taus Rutgers, The State University of
New Jersey, Piscataway, USA
A. Agapitos, J.P. Chou, Y. Gershtein, E. Halkiadakis, A. Hart, M. Heindl, E.
Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath, R.
Montalvo, K. Nash, M. Osherson, H. Saka, S. Salur, S. Schnetzer, D. Sheffield,
S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker University of
Tennessee, Knoxville, USA
A.G. Delannoy, J. Heideman, G. Riley, S. Spanier Texas A&M University, College
Station, USA
O. Bouhali72, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R.
Eusebi, J. Gilmore, T. Huang, T. Kamon73, S. Luo, R. Mueller, D. Overton, L.
Perniè, D. Rathjens, A. Safonov Texas Tech University, Lubbock, USA
N. Akchurin, J. Damgov, F. De Guio, P.R. Dudero, S. Kunori, K. Lamichhane,
S.W. Lee, T. Mengke, S. Muthumuni, T. Peltola, S. Undleeb, I. Volobouev, Z.
Wang Vanderbilt University, Nashville, USA
S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K.
Padeken, J.D. Ruiz Alvarez, P. Sheldon, S. Tuo, J. Velkovska, M. Verweij, Q.
Xu University of Virginia, Charlottesville, USA
M.W. Arenton, P. Barria, B. Cox, R. Hirosky, M. Joyce, A. Ledovskoy, H. Li, C.
Neu, T. Sinthuprasith, Y. Wang, E. Wolfe, F. Xia Wayne State University,
Detroit, USA
R. Harr, P.E. Karchin, N. Poudyal, J. Sturdy, P. Thapa, S. Zaleski University
of Wisconsin - Madison, Madison, WI, USA
M. Brodski, J. Buchanan, C. Caillol, D. Carlsmith, S. Dasu, I. De Bruyn, L.
Dodd, B. Gomber, M. Grothe, M. Herndon, A. Hervé, U. Hussain, P. Klabbers, A.
Lanaro, K. Long, R. Loveless, T. Ruggles, A. Savin, V. Sharma, N. Smith, W.H.
Smith, N. Woods †: Deceased
1: Also at Vienna University of Technology, Vienna, Austria
2: Also at IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
3: Also at Universidade Estadual de Campinas, Campinas, Brazil
4: Also at Federal University of Rio Grande do Sul, Porto Alegre, Brazil
5: Also at Université Libre de Bruxelles, Bruxelles, Belgium
6: Also at University of Chinese Academy of Sciences, Beijing, China
7: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia
8: Also at Joint Institute for Nuclear Research, Dubna, Russia
9: Also at Suez University, Suez, Egypt
10: Now at British University in Egypt, Cairo, Egypt
11: Also at Zewail City of Science and Technology, Zewail, Egypt
12: Also at Department of Physics, King Abdulaziz University, Jeddah, Saudi
Arabia
13: Also at Université de Haute Alsace, Mulhouse, France
14: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State
University, Moscow, Russia
15: Also at CERN, European Organization for Nuclear Research, Geneva,
Switzerland
16: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
17: Also at University of Hamburg, Hamburg, Germany
18: Also at Brandenburg University of Technology, Cottbus, Germany
19: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
20: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
21: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary
22: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India
23: Also at Institute of Physics, Bhubaneswar, India
24: Also at Shoolini University, Solan, India
25: Also at University of Visva-Bharati, Santiniketan, India
26: Also at Isfahan University of Technology, Isfahan, Iran
27: Also at Plasma Physics Research Center, Science and Research Branch,
Islamic Azad University, Tehran, Iran
28: Also at Università degli Studi di Siena, Siena, Italy
29: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy
30: Also at Kyunghee University, Seoul, Korea
31: Also at International Islamic University of Malaysia, Kuala Lumpur,
Malaysia
32: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia
33: Also at Consejo Nacional de Ciencia y Tecnología, Mexico City, Mexico
34: Also at Warsaw University of Technology, Institute of Electronic Systems,
Warsaw, Poland
35: Also at Institute for Nuclear Research, Moscow, Russia
36: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
37: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
38: Also at University of Florida, Gainesville, USA
39: Also at P.N. Lebedev Physical Institute, Moscow, Russia
40: Also at California Institute of Technology, Pasadena, USA
41: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
42: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
43: Also at INFN Sezione di Pavia a, Università di Pavia b, Pavia, Italy
44: Also at University of Belgrade, Faculty of Physics and Vinca Institute of
Nuclear Sciences, Belgrade, Serbia
45: Also at National and Kapodistrian University of Athens, Athens, Greece
46: Also at Riga Technical University, Riga, Latvia
47: Also at Universität Zürich, Zurich, Switzerland
48: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna,
Austria
49: Also at Adiyaman University, Adiyaman, Turkey
50: Also at Istanbul Aydin University, Istanbul, Turkey
51: Also at Mersin University, Mersin, Turkey
52: Also at Piri Reis University, Istanbul, Turkey
53: Also at Gaziosmanpasa University, Tokat, Turkey
54: Also at Ozyegin University, Istanbul, Turkey
55: Also at Izmir Institute of Technology, Izmir, Turkey
56: Also at Marmara University, Istanbul, Turkey
57: Also at Kafkas University, Kars, Turkey
58: Also at Istanbul University, Faculty of Science, Istanbul, Turkey
59: Also at Istanbul Bilgi University, Istanbul, Turkey
60: Also at Hacettepe University, Ankara, Turkey
61: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom
62: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
63: Also at Monash University, Faculty of Science, Clayton, Australia
64: Also at Bethel University, St. Paul, USA
65: Also at Karamanoğlu Mehmetbey University, Karaman, Turkey
66: Also at Utah Valley University, Orem, USA
67: Also at Purdue University, West Lafayette, USA
68: Also at Beykent University, Istanbul, Turkey
69: Also at Bingol University, Bingol, Turkey
70: Also at Sinop University, Sinop, Turkey
71: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey
72: Also at Texas A&M University at Qatar, Doha, Qatar
73: Also at Kyungpook National University, Daegu, Korea