HIG-18-010

$ssHeadURL:svn+ssh://svn.cern.ch/reps/tdr2/papers/HIG-18-010/trunk/HIG-18-010.tex$
$Id$

HIG-18-010

# Search for MSSM Higgs bosons decaying to $\Pgmp\Pgmm$ in proton-proton
collisions at $\sqrt{s}=13\TeV$

###### Abstract

A search is performed for neutral non-standard-model Higgs bosons decaying to
two muons in the context of the minimal supersymmetric standard model (MSSM).
Proton-proton collision data recorded by the CMS experiment at the CERN Large
Hadron Collider at a center-of-mass energy of 13were used, corresponding to an
integrated luminosity of 35.9. The search is sensitive to neutral Higgs bosons
produced via the gluon fusion process or in association with a $\cPqb\cPaqb$
quark pair. No significant deviations from the standard model expectation are
observed. Upper limits at 95% confidence level are set in the context of the
$m_{\Ph}^{\text{mod+}}$ and phenomenological MSSM scenarios on the parameter
$\tan\beta$ as a function of the mass of the pseudoscalar $\cmsSymbolFace{A}$
boson, in the range from 130 to 600. The results are also used to set a model-
independent limit on the product of the branching fraction for the decay into
a muon pair and the cross section for the production of a scalar neutral
boson, either via gluon fusion, or in association with quarks, in the mass
range from 130 to 1000.

##  0.1 Introduction

The boson discovered at the Large Hadron Collider (LHC) in 2012 [1, 2, 3],
with a mass around 125[4], has properties that are consistent with those
predicted for the standard model (SM) Higgs boson [5]. However, the SM is
known to be incomplete, and several well-motivated theoretical models beyond
the SM predict an extended Higgs sector. One example is supersymmetry [6, 7]
that protects the mass of the Higgs boson against quadratically divergent
quantum corrections. In the minimal supersymmetric standard model (MSSM) [8,
9, 10], the Higgs sector consists of two Higgs doublets, one of which couples
to up-type fermions and the other to down-type fermions. Assuming that CP
symmetry is conserved, this results in two charged bosons , two neutral scalar
bosons, and , and one pseudoscalar boson, $\cmsSymbolFace{A}$.

At the tree level, the Higgs sector in the MSSM can be described by only two
parameters, which are commonly chosen as $m_{\cmsSymbolFace{A}}$, the mass of
the neutral $\cmsSymbolFace{A}$, and $\tan\beta$, the ratio of the vacuum
expectation values of the neutral components of the two Higgs doublets. The
masses of the other four Higgs bosons can be expressed as a function of these
two parameters. Beyond the tree level the MSSM Higgs sector depends on
additional parameters, which enter via higher-order corrections in
perturbation theory, and which are usually fixed to values motivated by
experimental constraints and theoretical assumptions. Setting these parameters
defines a benchmark scenario [11], which is then described by
$m_{\cmsSymbolFace{A}}$ and $\tan\beta$. The relevant scenarios are those
consistent with a mass of one neutral boson of 125for the majority of the
probed $m_{\cmsSymbolFace{A}}$–$\tan\beta$ parameter space [12], and not ruled
out by other existing measurements. In particular, the $m_{\Ph}^{\text{mod+}}$
scenario [11] constrains the mass of the boson to be near 125for a wide range
of $\tan\beta$ and $m_{\cmsSymbolFace{A}}$ values, by tuning some of the MSSM
parameters. In the phenomenological MSSM (hMSSM) [13, 14, 15, 16] the mass of
boson is an input parameter, set to 125, and the observed neutral boson is
interpreted as the boson. Small differences in the cross sections and
branching fractions exist between the two models, although the kinematics of
the Higgs bosons remains almost identical.

This Letter reports on a search for beyond-the-SM neutral Higgs bosons in the
dimuon final state in proton-proton ($\Pp\Pp$) collisions at a center-of-mass
energy $\sqrt{s}$ of 13. The search is performed in the context of the MSSM
for values of $m_{\cmsSymbolFace{A}}$ larger than 130, assuming either the
$m_{\Ph}^{\text{mod+}}$ or the hMSSM scenario. For values of
$m_{\cmsSymbolFace{A}}\gtrsim 200\GeV$, the MSSM is close to the decoupling
limit: the boson takes the role of the observed SM-like Higgs boson at 125,
and the and $\cmsSymbolFace{A}$ bosons are nearly degenerate in mass. For
values of $m_{\cmsSymbolFace{A}}\lesssim 200\GeV$ the MSSM leads to similar,
but not degenerate, masses for the and $\cmsSymbolFace{A}$ bosons [17]. The
mass of the boson is assumed to be at 125, and its width smaller than the
experimental resolution, consistently with the ATLAS and CMS measurements in
other decay modes [4, 18, 19]. The analysis tests the boson production as
predicted by the MSSM and the constraints on its production mechanisms
measured by ATLAS and CMS are not enforced. Alternatively, the search is also
performed in a model-independent way, where a neutral boson is assumed to be
produced either via gluon fusion or in association with a $\cPqb\cPaqb$ quark
pair.

At the LHC, dominant production mechanisms for the neutral $\cmsSymbolFace{A}$
and bosons are gluon fusion, in which the Higgs boson can be produced via a
virtual loop of bottom or top quarks, and -associated production, where the
Higgs boson is produced in association with a quark pair. This is also the
case of the boson for values of $m_{\cmsSymbolFace{A}}\lesssim 200\GeV$,
while, in the decoupling regime, the boson production mechanisms correspond to
those predicted by the SM. Figure 1 shows the Feynman diagrams for the two
production processes at leading order (LO). The gluon fusion mechanism is more
relevant for $\tan\beta\lesssim 30$, whereas at LO, the coupling of the Higgs
boson to down-type fermions is enhanced by $\tan\beta$, resulting in
-associated production becoming more important at large $\tan\beta$. The
coupling of the neutral Higgs boson to charged leptons is enhanced for the
same reason. Although the branching fraction to muons is predicted to be about
300 times smaller than that for the $\Pgt^{+}\Pgt^{-}$ final state, the
$\Pgmp\Pgmm$ channel can be fully reconstructed, and the dimuon invariant mass
can be measured with a precision of a few percent by exploiting the excellent
muon momentum resolution of the CMS detector, making the dimuon final state an
additional probe of the MSSM.

Figure 1: Leading order Feynman diagrams for the production of the MSSM Higgs
boson: gluon fusion production (left) and -associated production (middle and
right).

The common experimental signature of the two production mechanisms is a pair
of opposite-charge muons with high transverse momentum (). The -associated
production process is characterized by the presence of additional jets
originating from quark fragmentation, whereas the events containing jets from
light quarks or gluons are linked to the gluon fusion production mechanism.
The presence of a signal would be characterized by an excess of events over
the SM background in the dimuon invariant mass corresponding to the value of
the Higgs boson masses.

The analysis is performed using the data at $\sqrt{s}=13\TeV$ collected during
2016 by the CMS experiment at the LHC corresponding to an integrated
luminosity of 35.9. Similar searches in the dimuon final state were performed
by the ATLAS and CMS Collaborations using data collected in $\Pp\Pp$
collisions at 7 and 8[20, 21], and by ATLAS at 13[22]. Searches for neutral
Higgs bosons in the framework of the MSSM were performed by the ATLAS and CMS
experiments also in the $\Pgt^{+}\Pgt^{-}$ [20, 23, 24, 25, 26, 27, 28] and
$\cPqb\cPaqb$ [29, 30, 31] final states. Limits on the existence of the MSSM
Higgs bosons were determined also in $\Pep\Pem$ collisions at
$\sqrt{s}=91$–209at the CERN LEP [32] and in proton-antiproton collisions at
$\sqrt{s}=1.96\TeV$ at the Fermilab Tevatron [33, 34, 35, 36].

##  0.2 The CMS detector

The central feature of the CMS apparatus is a superconducting solenoid of 6m
internal diameter, providing a field of 3.8T. Within the field volume are a
silicon pixel and strip tracker, a crystal electromagnetic calorimeter (ECAL),
and a brass and scintillator hadron calorimeter (HCAL), each composed of a
barrel and two endcap sections. Muons are measured in gas-ionization detectors
embedded in the steel return yoke of the magnet. The first level (L1) of the
CMS trigger system uses information from the calorimeters and muon detectors
to select events of interest. The high-level trigger processor farm decreases
the L1 accept rate from around 100kHz to about 1kHz before data storage. A
more detailed description of the CMS detector, together with a description of
the coordinate system and main kinematic variables used in the analysis, can
be found in Ref. [37].

##  0.3 Signal and background simulation

Samples of Monte Carlo (MC) simulated events are generated to model the Higgs
bosons signal for the two leading production processes. This is done for a
large number of $m_{\cmsSymbolFace{A}}$ and $\tan\beta$ combinations, where
$m_{\cmsSymbolFace{A}}$ spans the range from 130 to 1000and $\tan\beta$ is
varied from 5 to 60. Higgs boson events are generated with a mass within $\pm
3\Gamma$ of the nominal Higgs boson mass, where $\Gamma$ is the intrinsic
width. The values of $\Gamma$ strongly depend on $m_{\cmsSymbolFace{A}}$ and
$\tan\beta$, being, for example, $\Gamma=$ 0.2 (2.7)% of the nominal Higgs
boson mass at $m_{\cmsSymbolFace{A}}=150$ (550)and $\tan\beta=10$ (40). The
signal samples are generated with 8.212 [38] at LO. Additional signal samples
are generated at next-to-LO (NLO) for some mass points to estimate higher-
order corrections: gluon fusion samples are produced with 2.0 [39], while
-associated production samples are produced with  [40] using the four-flavor
scheme.

Simulated background processes are used to optimize the event selection but
not to model the background shape and normalization, which are determined
directly from data. The most relevant SM background processes considered are
Drell–Yan (DY) production, and single and pair production of top quarks, which
can produce $\Pgmp\Pgmm$ pairs with large invariant mass. Other background
sources are the diboson production processes, $\PW^{\pm}\PW^{\mp}$,
$\PW^{\pm}\cPZ$, and $\cPZ\cPZ$, whose contributions are each smaller than 1%
for dimuon invariant masses larger than 130, the Higgs boson search region.
The background samples are generated at NLO using  and . Spin correlations in
multiboson processes generated using  are simulated using MadSpin [41]. The
NNPDF 3.0 [42] parton distribution functions (PDFs) are used for all samples.
The parton shower and hadronization processes are modeled by with the CUETP8M1
[43] underlying event tune.

Detector response is based on a detailed description of the CMS detector and
is simulated with the package [44]. Additional $\Pp\Pp$ interactions in the
same or nearby bunch crossings (pileup) are simulated by . During the data
taking period, the CMS experiment was operating with, on average, 23 inelastic
$\Pp\Pp$ collisions per bunch crossing. The distribution of the number of
additional interactions per bunch crossing in the simulation is weighted to
match that observed in the data.

The values of the Higgs boson masses, widths, and the Yukawa couplings are
calculated as a function of $m_{\cmsSymbolFace{A}}$ and $\tan\beta$ following
the LHC Higgs Cross Section Working Group prescriptions [45, 46], using the
FeynHiggs 2.12.0 [47, 48, 49, 50, 51] program for the $m_{\Ph}^{\text{mod+}}$
scenario. The inclusive cross sections of the Higgs bosons for the gluon
fusion process are obtained with SusHi [52], which includes NLO
supersymmetric-QCD corrections [53, 54, 55, 56, 57, 58], next-to-NLO (NNLO)
QCD corrections for the top-quark contribution in the effective theory of a
heavy top quark [59, 60, 61, 62, 63], and electroweak effects by light quarks
[64, 65]. Higgs boson cross sections for the -associated production are
calculated with SusHi, and rely on matched predictions [66], which are based
on the five flavour NNLO QCD calculation [67] and the four flavour NLO QCD
calculation [68, 69]. Higgs to $\Pgmp\Pgmm$ branching fractions are calculated
with FeynHiggs for the $m_{\Ph}^{\text{mod+}}$ scenario and using the program
hdecay 6.40 [70] for the hMSSM scenario. Cross sections for the and DY
background processes are computed at the NNLO with Top++2.0 [71] and 3.1 [72],
respectively, while for the single top and the diboson production processes
they are computed at NLO with hathor [73, 74] and [75], respectively.

##  0.4 Object reconstruction and event selection

The particle-flow (PF) algorithm [76] aims at reconstructing and identifying
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
obtained 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.

Muons with $20<\pt<100\GeV$ are measured with a relative resolution of 1.3 to
2% in the barrel and better than 6% in the endcaps. The resolution in the
barrel is better than 10% for muons with up to 1[77, 78].

Jets are reconstructed using the anti-clustering algorithm [79] with a
distance parameter of 0.4, as implemented in the package [80]. The quantity
missing transverse momentum, , is defined as the magnitude of the negative
vector sum of all the PF objects (charged and neutral) in the event, and is
modified by corrections to the energy scale of reconstructed jets. Collision
vertices are obtained from reconstructed tracks using a deterministic
annealing algorithm [81]. The reconstructed vertex with the largest value of
summed physics-object $\pt^{2}$ is taken to be the primary $\Pp\Pp$
interaction vertex (PV). The physics objects are the jets, clustered using the
jet finding algorithm [79, 80] with the tracks assigned to the vertex as
inputs, and the associated missing transverse momentum taken as the negative
vector sum of the of those jets.

The combined secondary vertex algorithm of Ref. [82] is used to identify jets
resulting from the hadronization of quarks. A medium operating working point
of the algorithm is applied to jets with $\pt>20\GeV$ in the pseudorapidity
range $\abs{\eta}<2.4$. Within this kinematic range, the efficiency of the
algorithm is 66% with a misidentification probability of 1%.

The events are preselected by the trigger system [83] requiring a muon
candidate with $\abs{\eta}<2.4$, satisfying at least one of the following
criteria: $\pt>24\GeV$ with isolation (iso) requirements, or $\pt>50\GeV$
without isolation requirements. These are the trigger algorithms with the
lowest threshold whose output is not artificially reduced to limit the event
rate and that cover the entire $\eta$ acceptance of the muon detector. Since
the Higgs boson signal is searched for over a large mass range, the of the
muons from its decay can vary from tens to hundreds of GeV. Therefore, two
sets of muon identification (ID) criteria are employed in the analysis: one is
optimized for muons with lower ($\lesssim 200\GeV$) (ID1) and the other for
muons with larger (ID2).

Events with a pair of opposite-charge muons, coming from the PV, are selected
requiring both muons to satisfy the same ID criterion. Accepting, more
generally, pairs of muons that pass any of the two ID criteria would lead to a
negligible increase in signal efficiency. At least one of the two muon
candidates has to match (in $\eta$ and azimuthal angle $\phi$ in radians) the
muon that triggered the event. The trigger requirement depends on the ID
algorithm. Offline reconstructed muons with $\abs{\eta}<2.4$ are considered.
Their offline is required to be higher than 26 or 53, to be compatible with
the muon that triggered the event. To reject muons from nonprompt decays, muon
candidates must be isolated. The offline isolation variable is calculated
depending on the ID algorithm, and is labelled iso1 (iso2) for ID1 (ID2). For
ID1 it is the scalar sum of the PF charged and neutral hadrons in a cone of
radius $\Delta R=\sqrt{\smash[b]{(\Delta\eta)^{2}+(\Delta\phi)^{2}}}=0.4$
around the muon direction, divided by the muon . The charged PF particles not
associated with the PV are not considered in this sum, and a correction is
applied in order to account for the neutral particle contamination arising
from pileup [84]. For ID2 the offline iso is computed as the scalar sum of
tracks in the silicon tracker, excluding the muon, in a cone of radius $\Delta
R=0.3$ around the muon direction, and divided by the muon . Tracks not
associated with the PV are not considered. Energy deposits in the calorimeters
are not included, since electromagnetic showers can develop from photons
radiated by a high-muon. The invariant mass of the Higgs boson candidate is
reconstructed from the two highest-opposite-charge muon candidates in the
event. The dimuon selection criteria are summarized in Table 0.4.

Summary of the muon selection criteria.  Muon selection muon ID1 muon ID2
Online selection: $\abs{\eta}<2.4$ $\abs{\eta}<2.4$ Single muon $\pt>24\GeV$
$\pt>50\GeV$ Online iso Offline selection: $\abs{\eta}<2.4$ $\abs{\eta}<2.4$
Two opposite-charge muons $\pt>26\GeV$ $\pt>53\GeV$ Offline iso1 $<$ 0.25
offline iso2 $<$ 0.1

The muon momentum measurement is crucial for the reconstruction of the Higgs
boson mass peaks since improving the dimuon mass resolution increases the
sensitivity of the analysis. To set limits accurately, the mean and the
resolution of the dimuon mass peaks in simulation must match those of the
data. A correction of the muon momentum has been applied in order to provide
consistent measurements in the different $\phi$ and $\eta$ regions of the
detector, improving the net resolution in data. The correction [78] is also
applied to the simulated muons to align the scale and resolution to those
measured in the data. The magnitudes of the momentum scale corrections are
about 0.2 and 0.3% in the barrel and endcaps, respectively, for muons with up
to 200. For muons with larger , since the statistical precision of the data is
too poor to derive a correction, only a systematic uncertainty is considered
(see Section 0.5).

Figure 2: Distribution of the missing transverse momentum in (left) -tag and
(right) no--tag categories, for events with dimuon invariant mass larger than
130, as observed in data (dots) and predicted by simulation (colored
histograms). The shaded gray band around the total background histogram
represents the total uncertainty in the simulated prediction. The contribution
of the expected signal for $m_{\cmsSymbolFace{A}}=300\GeV$ and $\tan\beta=20$,
scaled by a factor of 100, is superimposed for illustration. The vertical line
represents the upper threshold used to select the events in the two
categories.

When the Higgs boson is produced in association with a $\cPqb\cPaqb$ pair,
additional jets from $\cPqb$ quark fragmentation are expected. Jets with
$\pt>20\GeV$ and $\abs{\eta}<2.4$ are considered in this analysis: those that
satisfy the requirements for the medium -tagging working point [82] are taken
as -jet candidates, otherwise they are taken as untagged jets. Events
containing -jet candidates provide the highest sensitivity for the -associated
production channel, and events that do not contain -tagged jets provide the
best sensitivity for the gluon fusion production channel. The events are
therefore split into two exclusive categories: the -tag category, containing
events with strictly one jet and at most one additional untagged jet, and the
no--tag category, containing events without -tagged jets. In the first
category, the requirement of strictly one jet is aimed at suppressing about
30% of the dominant background from top quark pairs, since the observed
-tagged jet multiplicity in $\cPqt\cPaqt$ events is on average higher than for
the Higgs boson signal. This is because more than half of the signal events
from -associated production are characterized by jets emitted at large $\eta$,
out of the acceptance of the tracking detector, and failing the -tag
requirements, whereas jets in $\cPqt\cPaqt$ events are preferentially emitted
in the central $\eta$ region. Therefore, discarding events with two or more
-tagged jets allows the $\cPqt\cPaqt$ background to be rejected without any
major impact on the signal efficiency. Furthermore, $\cPqt\cPaqt$ events are
characterized by a higher multiplicity of additional untagged jets than the
signal events.

Signal events are characterized by a rather small . However, the background
content is quite different for the two categories, as shown in Fig. 2. The
background from $\cPqt\cPaqt$ events, characterized by a relatively large from
boson decays, is much more relevant for the -tag category. For the no--tag
category, the dominant background is DY production, whose events are
characterized by a distribution that is similar to that of the signal. For
this reason, a requirement on , separately tuned for the -tag and the no--tag
events, improves the background rejection and increases the signal
sensitivity. Events belonging to the -tag (no--tag) category are required to
have $\ptmiss<40$ (80). This requirement reduces the background from top quark
production by about 75% (40%). The selection criteria that define the two
categories are summarized in Table 1.

Table 1: Summary of the selection criteria that define the two event categories. Categorization is applied after the muon selection. |  -tag category | No--tag category
---|---|---
-tagged jets | 1 with $\pt>20\GeV$, $\abs{\eta}<2.4$ | Veto
Untagged jets | 0,1 with $\pt>20\GeV$, $\abs{\eta}<2.4$ |
|  $<$40  |  $<$80

##  0.5 Signal efficiency and signal systematic uncertainties

For each value of $m_{\cmsSymbolFace{A}}$ and $\tan\beta$, the signal
efficiency for each Higgs boson sample is defined as the fraction of generated
events that fulfill the selection criteria. This definition of efficiency also
includes the effects of limited detector acceptance and the selections
outlined in Section 0.4.

Figure 3: The selection efficiency for the $\cmsSymbolFace{A}$ boson, as a
function of its mass, for the two production mechanisms, -associated and gluon
fusion, and for each of the two event categories. The band centered on each
curve corresponds to the envelope of efficiencies obtained when varying
$\tan\beta$, combined with the statistical and systematic uncertainties.

Figure 3 shows the selection efficiency for the $\cmsSymbolFace{A}$ boson as a
function of $m_{\cmsSymbolFace{A}}$, for the gluon fusion and the -associated
production processes, and for the two event categories. Each curve corresponds
to the mean of the efficiency obtained by varying $\tan\beta$ between 5 and
60, while the band of each curve corresponds to the efficiency variations
combined with the statistical and systematic uncertainties (described in the
next paragraph) of the simulated samples. For a given mass, the selection
efficiency is weakly dependent on $\tan\beta$, since this parameter mostly
affects the Higgs boson width, with a negligible impact on the kinematic
properties of the event. The efficiency to detect events produced in
association with quarks is approximately 10% at high masses for the -tag
category. This value is mostly determined by the large fraction of jets that
are emitted with an $\eta$ value that is outside the coverage of the tracking
detectors, and indeed $\approx$50% of events from -associated samples are
reconstructed in the no--tag category. The efficiency to detect events from
gluon fusion reaches a maximal value at $\approx$65% for
$m_{\cmsSymbolFace{A}}\gtrsim 400\GeV$. The very small but nonvanishing
efficiency for signal produced via gluon fusion in the -tag category is due to
the misidentification probability, which is about 1%. The corresponding
efficiencies for the boson are consistent with those shown in Fig. 3.

Systematic uncertainties in the signal efficiency for the two event
categories. The systematic uncertainties hold for both Higgs boson production
processes except for the sources listed in the last three rows, which apply to
the -associated production process only. For these three sources, in the
model-independent search for a neutral boson produced in association with
quarks, the uncertainties are applied as quoted in the table. In the MSSM
interpretation, these numbers have to be weighted by the relative contribution
of the -associated production process to each category. For those sources of
systematics that depend on $m_{\cmsSymbolFace{A}}$ the range of uncertainty is
quoted.  Source Systematic uncertainty (%) -tag category No--tag category MC
statistical uncertainty 0.5–6 0.2–2 Trigger efficiency 0.9 0.9 Muon
reconstruction 2 2 Muon isolation 1 2 Pileup 0.8 0.9 Jet energy scale 1.6 0.4
Unclustered energy 4.1 0.3 PDF 3 3 Higgs boson  1–4 1–4 tag (only for
-associated production) 2 0.6 jet multiplicity (only for -associated
production) 20–30 7–20 Untagged jet multiplicity (only for -associated
production) 7–25

The systematic uncertainties in the signal description arise from a possible
mismodeling of the signal efficiency, of the signal shape, and, for the model
interpretation, from uncertainties in its cross section.

The systematic uncertainties that affect the signal efficiency are given in
Table 0.5. The size of the simulated signal samples introduces a statistical
uncertainty in the signal efficiency that is between 0.2% and 6%, depending on
the number of generated events.

In order to account for the differences between data and simulation in the
muon trigger efficiency, identification, and isolation, scale factors
calculated using the tag-and-probe technique [77, 78] have been applied to
simulated events. A similar procedure is used to account for discrepancies
between data and simulation in the -tagging efficiency. A global correction,
calculated as the product of the various scale factors, is applied as an
event-by-event weight. The uncertainty associated with each scale factor is
then propagated to the analysis and its impact on the final selection
efficiency is assigned as systematic uncertainty. An event-by-event weight is
also applied to account for the modeling of the pileup in the simulation. The
uncertainty in the knowledge of the pileup multiplicity is evaluated by
varying the total inelastic cross section [85, 86] by $\pm 5\%$, which
translates into an uncertainty smaller than 1% in the signal efficiency. The
uncertainty associated with the jet energy scale [87] is estimated by
rescaling the jet momentum by a factor depending on the and $\eta$ of each
jet. This variation is also propagated to the determination. Its effect on the
signal selection efficiency is about 1.6 (0.4)% for the -tag (no--tag)
category. Systematic uncertainties in the unclustered energy are propagated to
the determination of . The effect on the signal efficiency is 4.1% for the
-tag category, and 0.3% for the no--tag category. Systematic uncertainty in
the -tagging algorithm affects the signal yield and the category migration
with an impact on the signal efficiency of 2% for the -tag category and 0.6%
for the no--tag category. The uncertainty in the total integrated luminosity
is 2.5% [88] and affects the signal yield.

The uncertainties in the MSSM cross sections depend on
$m_{\cmsSymbolFace{A}}$, $\tan\beta$, and the scenario. They are provided by
the LHC Higgs Cross Section Working Group [45, 46]. An uncertainty of 3% is
used to account for the parton distribution functions.

Additional corrections are applied to take into account the fact that the
signal samples are generated with at LO instead of using an NLO generator.
Higher-order corrections affect the Higgs boson modeling, with impacts on the
muon acceptance and the jet multiplicity. Moreover, they cause event migration
between the two categories. The acceptance obtained from the LO samples is
corrected to that predicted at NLO. The corresponding systematic uncertainty
is set to the size of the correction itself. The correction on the modeling of
the Higgs increases the signal efficiency by 1–4%, depending on the Higgs
boson mass. The correction on the -jet multiplicity affects only the
-associated signal, resulting in a correction of 20–30% depending on
$m_{\cmsSymbolFace{A}}$, which increases the signal efficiency for the -tag
category, and a correction of 7–20% decreasing the signal efficiency for the
no--tag category. An additional correction of 7–25%, related to the untagged
jet multiplicity, is applied, and reduces the signal efficiency for the -tag
category, due to the veto on the untagged jets.

The systematic uncertainties in the -tag efficiency and the jet multiplicity
shown in Table 0.5 apply only to the -associated production process. Both the
-tagging and the -jet multiplicity uncertainties are anticorrelated between
the two event categories. In the model-independent analysis for the case in
which the neutral boson is assumed to be entirely produced in association with
quarks, these uncertainties are applied, as quoted in Table 0.5, while in the
MSSM interpretation, where both the gluon fusion and the -associated
production processes contribute to the two event categories, these systematic
uncertainties are weighted by the relative contribution of the latter process.

The shape of the reconstructed Higgs boson invariant mass distribution is
affected by the muon momentum scale and resolution. Uncertainties in the
calibration of these quantities are propagated to the shape of the invariant
mass distribution assuming a Gaussian prior, leading to a variation of up to
10% in the width of the signal mass peak, and to a negligible shift of its
position. These uncertainties are taken into account as a signal shape
variation in the calculation of the exclusion limit.

##  0.6 Modeling of the signal and background shapes

The invariant mass spectrum of the signal events that pass the event selection
is used to determine the signal yield for each category. In the framework of
the MSSM, this is done by fitting the invariant mass distribution of the , ,
and $\cmsSymbolFace{A}$ bosons, separately for the two event categories and
for various combinations of $m_{\cmsSymbolFace{A}}$–$\tan\beta$ values. The
function $F_{\text{sig}}$ used to parametrize the signal mass shape [21] is
defined as:

$F_{\text{sig}}=w_{\Ph}F_{\Ph}+w_{\PH}F_{\PH}+w_{\cmsSymbolFace{A}}F_{\cmsSymbolFace{A}}.$
(1)

In Eq. (1), the terms $F_{\Ph}$, $F_{\PH}$, and $F_{\cmsSymbolFace{A}}$
describe the mass shape of the , , and $\cmsSymbolFace{A}$ signals,
respectively. Each term is a convolution of a Breit–Wigner (BW) function to
describe the resonance, with a Gaussian function to account for the detector
resolution. The two parameters of the BW function, as well as the variance of
each Gaussian function, are free parameters of the fit used to determine the
signal model, while the quantities $w_{\Ph}$, $w_{\PH}$, and
$w_{\cmsSymbolFace{A}}$ are the numbers of expected events for each boson
passing the event selection. For the $m_{\cmsSymbolFace{A}}$–$\tan\beta$
points for which the signal samples were not generated, the parameters are
interpolated from the nearby generated points. In order to correct for
differences of the order of a fewbetween the prediction of $m_{\PH}$ with
respect to the value calculated by FeynHiggs in the $m_{\Ph}^{\text{mod+}}$ or
the value used in the hMSSM, especially for $m_{\cmsSymbolFace{A}}\lesssim
200\GeV$, the invariant mass distribution of the boson is shifted by the
corresponding amount. For the model-independent analysis the signal shape is
described using one single resonance in Eq. (1).

The analysis does not use background estimation from simulation due to the
limited size of simulated events compared to data in the region of interest,
as well as due to the large theoretical uncertainties in the background
description at high invariant masses. Therefore, given the smooth dependence
of the background shape on the dimuon invariant mass, it is estimated from the
data, by assuming a functional form to describe its dependence as a function
of the reconstructed dimuon invariant mass, $m_{\mu\mu}$, and by fitting it to
the observed distribution.

The functional form used to describe the background shape is defined as:

$F_{\text{bkg}}=\exp(\lambda
m_{\mu\mu})\left[\frac{f}{N_{1}}\frac{1}{{(m_{\mu\mu}-m_{\cPZ})}^{2}+\frac{\Gamma^{2}_{\cPZ}}{4}}+\frac{(1-f)}{N_{2}}\frac{1}{{m_{\mu\mu}}^{2}}\right].$
(2)

The quantity $\exp(\lambda m_{\mu\mu})$ parametrizes the exponential part of
the mass distribution, and $f$ represents the weight of the BW term with
respect to DY photon exchange, while N1 and N2 correspond to the integral of
each term in $F_{\text{bkg}}$. The quantities $\lambda$ and $f$ are free
parameters of the fit. The parameters $\Gamma_{\cPZ}$ and $m_{\cPZ}$ are
separately determined for the two event categories by fitting the dimuon mass
distribution close to the $\cPZ$ boson mass. The fit provides the effective
values of such quantities, which include detector and resolution effects.
Their values are then kept constant when using $F_{\text{bkg}}$ in the final
fit. The systematic uncertainty that stems from the choice of the functional
form in Eq. (2), which was used in earlier searches [21], is assessed as
described below.

A linear combination of the functions describing the expected signal and the
background is then used to perform a binned maximum likelihood fit to the
data, where the uncertainties are treated as nuisance parameters:

$F_{\text{fit}}=(1-f_{\text{bkg}})F_{\text{sig}}+f_{\text{bkg}}F_{\text{bkg}}.$
(3)

The fit is performed for each $m_{\cmsSymbolFace{A}}$ and $\tan\beta$
hypothesis, as the yield of the signal events and the shape of
$F_{\text{sig}}$ depend on these quantities. The parameters that describe the
signal are determined by fitting the simulated samples that pass the event
selection with Eq. (1), for each $m_{\cmsSymbolFace{A}}$ and $\tan\beta$ pair,
as explained above. Subsequently they are assigned as constant terms in
$F_{\text{fit}}$. The quantity $f_{\text{bkg}}$ is a free parameter in the
fit, and the fraction of signal events is defined as
$f_{\text{sig}}=(1-f_{\text{bkg}})$. The overall normalization is also a free
parameter and is profiled in the fit.

For each $m_{\cmsSymbolFace{A}}$ assumption, the function $F_{\text{fit}}$ is
used to fit the data over an $m_{\mu\mu}$ range centered on
$m_{\cmsSymbolFace{A}}$. The range has to be large enough to account for the
signal width, including the experimental resolution, and it is $\pm 50\GeV$
for $m_{\cmsSymbolFace{A}}\leq 290\GeV$, $\pm 75\GeV$ for
$290<m_{\cmsSymbolFace{A}}\leq 390\GeV$, and $\pm 100\GeV$ for
$390<m_{\cmsSymbolFace{A}}\leq 500\GeV$. For values of $m_{\cmsSymbolFace{A}}$
smaller than 165the lower bound of the mass window is set to 115. For
$m_{\cmsSymbolFace{A}}>500\GeV$, the entire range from 400 to 1200is used. The
boson is used to constrain the results when its mass is included in the fitted
mass range.

The uncertainty introduced by the choice of the analytical function used to
parametrize the background is estimated by using a method similar to that used
in Refs. [3, 21, 89]. The method is based on the determination of the number
of spurious signal events that are introduced by the choice of the background
function $F_{\mathrm{bkg}}$, when the background is fit by the function
$F_{\mathrm{fit}}$. The invariant mass spectrum is fitted by the function
$F_{\mathrm{bkg}}^{a}$, chosen among various functional forms: Eq. (2) or
other similar expressions that include a BW plus exponentials, and sum of
exponentials. All these functional forms adequately describe the background
distribution observed in data. The fit is performed in the proper mass range
centered around the assumed value of $m_{\cmsSymbolFace{A}}$, and the
parameters of $F_{\mathrm{bkg}}^{a}$ are determined. Then, thousands of MC
pseudo-experiments are generated, each one containing the same number of
events as observed in the data, distributed according to the functional form
$F_{\mathrm{bkg}}^{a}$. For each pseudo-experiment, the invariant mass
distribution is then fit with the function $F_{\mathrm{fit}}$ of Eq. (3), once
using $F_{\mathrm{bkg}}^{a}$, and then using a different function
$F_{\mathrm{bkg}}^{b}$, given by Eq. (2). For each pseudo-experiment, the
spurious signal yield, expressed by the number of events
$N_{\mathrm{bias}}^{a}$ and $N_{\mathrm{bias}}^{b}$, is determined. The
quantity $N_{\mathrm{bias}}^{a}$ is on average consistent with zero within
statistical fluctuations. The quantity $N_{\mathrm{bias}}^{b}$ represents the
number of spurious signal events that are found in the signal yield if the
function $F_{\mathrm{bkg}}^{b}$ is used to describe the background, when the
background itself is actually distributed according to $F_{\mathrm{bkg}}^{a}$.
The median of the distribution of the difference
$N_{\mathrm{bias}}^{a}-N_{\mathrm{bias}}^{b}$ obtained from the pseudo-
experiments is defined as the bias introduced by using the function
$F_{\mathrm{bkg}}^{b}$, relative to the tested mass $m_{\cmsSymbolFace{A}}$.
This procedure is repeated for each function $F_{\mathrm{bkg}}^{a}$ among the
functional forms mentioned above, and the largest bias is taken as the
systematic uncertainty in the number of signal events obtained from the
maximum likelihood fit, due to the choice of Eq. (2) to parametrize the
background distribution. Choosing a different function $F_{\mathrm{bkg}}^{b}$,
instead of Eq. (2), was shown to lead to similar biases over the whole mass
range. The number of spurious signal events varies between a few units and a
few hundred depending on the mass of the signal and the event category.
Although the bias is due to the modelling of the background, its impact on the
result depends on the expected signal strength and shape, both varying
according to $m_{\cmsSymbolFace{A}}$ and $\tan\beta$ in the model-dependent
analysis, and according to the mass of a generic resonance $\phi$ for the
model-independent case. More details about the effect of the bias on the final
results are discussed in Section 0.7.

An example of fits to the data with Eq. (3), for the model-independent case,
is shown in Fig. 4. Two mass hypotheses, 400 and 980, are assumed for a single
narrow-width resonance $\phi$ decaying to two muons. The two event categories
are combined according to their sensitivity, $S/(S+B)$, where S and B are the
number of events in the expected signal and observed background, respectively.
The uncertainties in the integrated luminosity, in the signal efficiency, and
in the background parametrization are taken into account as nuisance
parameters.

Figure 4: Examples of fits to data with a signal plus background hypothesis,
for a narrow-width signal with a mass of 400(left), and 980(right), for the
two event categories added together, after weighting by their sensitivity. The
resonance $\phi$ is assumed to be produced via the -associated production, and
to decay to two muons. The 68 and 95% CL bands, shown in dark green and light
yellow, respectively, include the uncertainties in the background component of
the fit. The lower panel shows the difference between the data and the
background component of the fit.

##  0.7 Results

No evidence of Higgs boson production beyond the SM prediction is observed in
the mass range in which the analysis has been performed. Exclusion limits at
95% confidence level (CL) are therefore determined.

A maximum likelihood fit to the data, as explained in the previous section, is
performed under the background only and the signal-plus-background hypotheses,
where the background includes the expectation for the SM Higgs boson. The
systematic uncertainties are incorporated as nuisance parameters in the
likelihood. The upper limits for the signal production are computed using the
[90, 91] criterion and the hybrid frequentist-bayesian approach, where the
distributions of the test-statistic are derived from pseudo-experiments [92].

The results are interpreted within the MSSM in the context of the
$m_{\Ph}^{\text{mod+}}$ and hMSSM scenarios, by combining both event
categories. The 95% CL limit on the parameter $\tan\beta$ is presented as a
function of $m_{\cmsSymbolFace{A}}$: the exclusion limit is chosen for each
$m_{\cmsSymbolFace{A}}$ as the $\tan\beta$ value at which the is lower than
0.05.

Figure 5: The 95% CL expected, including the 68 and 95% CL bands, and observed
upper limits, on $\tan\beta$ as a function of $m_{\cmsSymbolFace{A}}$ for the
$m_{\Ph}^{\text{mod+}}$ (left) and the hMSSM (right) scenarios of the MSSM.
The observed exclusion contour is indicated by the purple region, while the
area under the red curve is excluded by requiring the neutral boson mass
consistent with $125\pm 3\GeV$.

To estimate the impact of the various systematic uncertainties, the 95% CL
limits have been determined by including different combination of
uncertainties: statistical plus all systematic uncertainties, statistical plus
systematic uncertainties in the fit bias, statistical plus systematic
uncertainties in the efficiency. The comparison shows that the systematic
uncertainties pertaining to the selection efficiency and the fit bias have
similar impact.

The results in terms of the expected 95% CL upper limit on the
$m_{\Ph}^{\text{mod+}}$ MSSM scenario (with the higgsino mass parameter
$\mu=200$), including the 68 and 95% CL bands, are shown in Fig. 5 (left), in
the $m_{\cmsSymbolFace{A}}$–$\tan\beta$ plane. The results are obtained
including the statistical and all systematic uncertainties. The 95% CL upper
limit is computed up to $m_{\cmsSymbolFace{A}}=600\GeV$, where the excluded
$\tan\beta$ value exceeds 50. For higher values of $\tan\beta$ the MSSM
predictions are no longer reliable. These results extend the excluded
$\tan\beta$ range obtained at 7 and 8[21] and also extend the range of the
tested $m_{\cmsSymbolFace{A}}$ values from 300 to 600. The data are also
interpreted in terms of the hMSSM model. The corresponding 95% CL upper limit
on $\tan\beta$ as a function of $m_{\cmsSymbolFace{A}}$ are shown in Fig. 5
(right). The observed limits are very similar in the two scenarios, since, in
the $m_{\cmsSymbolFace{A}}$–$\tan\beta$ range covered by this analysis the
$m_{\Ph}^{\text{mod+}}$ predictions for the boson mass are consistent with the
SM Higgs boson mass, and the cross sections of the and $\cmsSymbolFace{A}$
bosons are similar between the two models.

The results of the $\Pgt^{+}\Pgt^{-}$ analysis [28] exclude a much larger
$m_{\cmsSymbolFace{A}}$–$\tan\beta$ region, reaching the value of
$\tan\beta=60$ at $m_{\cmsSymbolFace{A}}=1.5\TeV$. For values of
$m_{\cmsSymbolFace{A}}$ up to 400the $\Pgmp\Pgmm$ results exclude a larger
$m_{\cmsSymbolFace{A}}$–$\tan\beta$ region compared to the results of the
$\cPqb\cPaqb$ analysis [31], which is instead slightly more sensitive at
higher $m_{\cmsSymbolFace{A}}$ reaching the value of $\tan\beta=60$ at about
$m_{\cmsSymbolFace{A}}=700\GeV$.

Figure 6: The 95% CL expected, including the 68 and 95% CL bands, and observed
model-independent upper limits on the production cross section times branching
fraction of a generic $\phi$ boson decaying to a dimuon pair, in the case of
-associated (left) and gluon fusion (right) production. The results are
obtained using a signal template with an intrinsic narrow width.

Limits on the production cross section times decay branching fraction
$\sigma\mathcal{B}({\phi}\to\PGmp\PGmm)$ for a single neutral scalar boson
$\phi$ have also been determined. In the model-independent interpretation the
$\phi$ boson is searched for as a single resonance with mass $m_{\phi}$
assuming a narrow width or a width equal to 10% of $m_{\phi}$. In the first
case the intrinsic width of the signal is smaller than the invariant mass
resolution, while in the second case the width is larger even for mass values
near 1000(lower sensitivity of the analysis). The simulated signal of the
$\cmsSymbolFace{A}$ boson in the $\tan\beta=5$ case (smallest intrinsic width,
dominated by the detector resolution) is used as a template to compute the
detection efficiency of a generic $\phi$ boson decaying to a muon pair. The
$\phi$ boson is assumed to be produced entirely either via the -associated or
the gluon fusion process, and the analysis is performed separately for the two
production mechanisms. Figure 6 shows the 95% CL upper limits on the cross
section times the decay branching fraction to $\Pgmp\Pgmm$ as a function of
the $\phi$ mass for a narrow resonance. These limits are more stringent by a
factor of 2 to 3 than those recently obtained by ATLAS in a similar search
[22]. The corresponding upper limits assuming a signal template with a width
equal to 10% of its mass value are shown in Fig. 7. In the case of large
signal widths, the upper limits as a function of $m_{\phi}$ start from 140.
This is done to have the signal peak $\pm 3\Gamma$ within the fit range.
Moreover, as one may expect, the limits are less stringent than for the
narrow-width approximation, and it is no longer possible to distinguish the
fine structure of the 95% CL limits as a function of the mass, as observed for
the narrow-width case.

Figure 7: The 95% CL expected, including the 68 and 95% CL bands, and observed
model-independent upper limits on the production cross section times branching
fraction of a generic $\phi$ boson decaying to a dimuon pair, in the case of
-associated (left) and gluon fusion (right) production. The results are
obtained using a signal template with an intrinsic width equal to the 10% of
the nominal mass.

##  0.8 Summary

A search for neutral minimal supersymmetric standard model (MSSM) Higgs bosons
decaying to $\PGmp\PGmm$ was performed using 13data collected in proton-proton
collisions by the CMS experiment at the LHC. No excess of events was found
above the expected background due to standard model (SM) processes. The 95%
confidence level upper limit for the production of beyond SM neutral Higgs
bosons is determined in the framework of the $m_{\Ph}^{\text{mod+}}$ and the
phenomenological scenarios of the MSSM. For the ratio of the vacuum
expectation values of the neutral components of the two Higgs doublets,
$\tan\beta$, its excluded values range from $\approx$10 to $\approx$60 for a
mass of the pseudoscalar $\cmsSymbolFace{A}$ boson ($m_{\cmsSymbolFace{A}}$)
from 130 to 600. The larger collected luminosity and the higher center-of-mass
energy exclude a larger $m_{\cmsSymbolFace{A}}$–$\tan\beta$ region, compared
to what was obtained at 7 and 8in a similar analysis. Model-independent
exclusion limits on the production cross section times branching fraction of a
generic narrow-width neutral boson decaying to two muons have been determined
assuming the neutral boson to be produced entirely either via -associated or
gluon fusion mechanisms. The limits are determined in the mass range from 130
to 1000, separately for the two production mechanisms. Similarly, exclusion
limits are also obtained assuming a signal width equal to 10% of its mass
value.

###### Acknowledgements.

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

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##  .9 The CMS Collaboration

Yerevan Physics Institute, Yerevan, Armenia
A.M. Sirunyan${}^{\textrm{\textdagger}}$, A. Tumasyan Institut für
Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, T. Bergauer, J. Brandstetter, M. Dragicevic, J. Erö, A.
Escalante Del Valle, M. Flechl, R. Frühwirth1, M. Jeitler1, N. Krammer, I.
Krätschmer, D. Liko, T. Madlener, I. Mikulec, N. Rad, J. Schieck1, R.
Schöfbeck, M. Spanring, D. Spitzbart, W. Waltenberger, J. Wittmann, C.-E.
Wulz1, M. Zarucki Institute for Nuclear Problems, Minsk, Belarus
V. Drugakov, V. Mossolov, J. Suarez Gonzalez Universiteit Antwerpen,
Antwerpen, Belgium
M.R. Darwish, E.A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, A. Lelek, M.
Pieters, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel Vrije
Universiteit Brussel, Brussel, Belgium
F. Blekman, J. D’Hondt, J. De Clercq, 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, L. Favart, A. Grebenyuk, A.K. Kalsi, J. Luetic, A. Popov, 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, C. Roskas, D.
Trocino, M. Tytgat, W. Verbeke, B. Vermassen, M. Vit, N. Zaganidis Université
Catholique de Louvain, Louvain-la-Neuve, Belgium
O. Bondu, G. Bruno, C. Caputo, P. David, C. Delaere, M. Delcourt, A.
Giammanco, G. Krintiras, V. Lemaitre, A. Magitteri, K. Piotrzkowski, A.
Saggio, M. Vidal Marono, P. Vischia, J. Zobec Centro Brasileiro de Pesquisas
Fisicas, Rio de Janeiro, Brazil
F.L. Alves, G.A. Alves, G. Correia Silva, C. Hensel, A. Moraes, P. Rebello
Teles Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil
E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato3, E. Coelho, E.M.
Da Costa, G.G. Da Silveira4, D. De Jesus Damiao, C. De Oliveira Martins, S.
Fonseca De Souza, L.M. Huertas Guativa, H. Malbouisson, D. Matos Figueiredo,
M. Medina Jaime5, 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, D. De Souza Lemos, 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, G. Antchev, 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. Fang6, X. Gao6, L. Yuan Institute of High Energy Physics, Beijing, China
M. Ahmad, G.M. Chen, H.S. Chen, M. Chen, C.H. Jiang, D. Leggat, H. Liao, Z.
Liu, S.M. Shaheen7, A. Spiezia, J. Tao, E. Yazgan, H. Zhang, S. Zhang7, J.
Zhao State Key Laboratory of Nuclear Physics and Technology, Peking
University, Beijing, China
A. Agapitos, Y. Ban, G. Chen, A. Levin, J. Li, L. Li, Q. Li, Y. Mao, S.J.
Qian, D. Wang Tsinghua University, Beijing, China
Y. Wang Universidad de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, L.F. Chaparro Sierra, C. Florez, C.F. González
Hernández, M.A. Segura Delgado Universidad de Antioquia, Medellin, Colombia
J.D. Ruiz Alvarez University of Split, Faculty of Electrical Engineering,
Mechanical Engineering and Naval Architecture, Split, Croatia
D. Giljanović, N. Godinovic, D. Lelas, I. Puljak, T. Sculac University of
Split, Faculty of Science, Split, Croatia
Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia
V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, M. Roguljic, A. Starodumov8,
T. Susa University of Cyprus, Nicosia, Cyprus
M.W. Ather, A. Attikis, E. Erodotou, A. Ioannou, M. Kolosova, S. Konstantinou,
G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H.
Rykaczewski, D. Tsiakkouri Charles University, Prague, Czech Republic
M. Finger9, M. Finger Jr.9 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
H. Abdalla10, A.A. Abdelalim11,12 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, K. Osterberg, J. Pekkanen, M. Voutilainen Helsinki
Institute of Physics, Helsinki, Finland
F. Garcia, 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, B. Fabbro, J.L. Faure, F.
Ferri, S. Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry,
C. Leloup, E. Locci, J. Malcles, J. Rander, A. Rosowsky, M.Ö. Sahin, A. Savoy-
Navarro13, M. Titov Laboratoire Leprince-Ringuet, Ecole polytechnique,
CNRS/IN2P3, Université Paris-Saclay, Palaiseau, France
C. Amendola, F. Beaudette, P. Busson, C. Charlot, B. Diab, R. Granier de
Cassagnac, I. Kucher, A. Lobanov, C. Martin Perez, M. Nguyen, C. Ochando, P.
Paganini, J. Rembser, R. Salerno, J.B. Sauvan, Y. Sirois, A. Zabi, A. Zghiche
Université de Strasbourg, CNRS, IPHC UMR 7178, Strasbourg, France
J.-L. Agram14, J. Andrea, D. Bloch, G. Bourgatte, J.-M. Brom, E.C. Chabert, C.
Collard, E. Conte14, J.-C. Fontaine14, D. Gelé, U. Goerlach, M. Jansová, A.-C.
Le Bihan, N. Tonon, P. Van Hove Centre de Calcul de l’Institut National de
Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne,
France
S. Gadrat Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3,
Institut de Physique Nucléaire de Lyon, Villeurbanne, France
S. Beauceron, C. Bernet, G. Boudoul, C. Camen, N. Chanon, R. Chierici, D.
Contardo, P. Depasse, H. El Mamouni, J. Fay, S. Gascon, M. Gouzevitch, B.
Ille, Sa. Jain, F. Lagarde, I.B. Laktineh, H. Lattaud, M. Lethuillier, L.
Mirabito, S. Perries, V. Sordini, G. Touquet, M. Vander Donckt, S. Viret
Georgian Technical University, Tbilisi, Georgia
A. Khvedelidze9 Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze9 RWTH Aachen University, I. Physikalisches Institut, Aachen,
Germany
C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, D. Meuser, A.
Pauls, M. Preuten, M.P. Rauch, C. Schomakers, J. Schulz, M. Teroerde, B.
Wittmer RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
A. Albert, M. Erdmann, S. Erdweg, T. Esch, B. Fischer, R. Fischer, S. Ghosh,
T. Hebbeker, K. Hoepfner, H. Keller, L. Mastrolorenzo, M. Merschmeyer, A.
Meyer, P. Millet, G. Mocellin, S. Mondal, S. Mukherjee, D. Noll, A. Novak, T.
Pook, A. Pozdnyakov, T. Quast, M. Radziej, Y. Rath, H. Reithler, M. Rieger, A.
Schmidt, S.C. Schuler, A. Sharma, S. Thüer, S. Wiedenbeck RWTH Aachen
University, III. Physikalisches Institut B, Aachen, Germany
G. Flügge, O. Hlushchenko, T. Kress, T. Müller, A. Nehrkorn, A. Nowack, C.
Pistone, O. Pooth, D. Roy, H. Sert, A. Stahl15 Deutsches Elektronen-
Synchrotron, Hamburg, Germany
M. Aldaya Martin, C. Asawatangtrakuldee, P. Asmuss, I. Babounikau, H.
Bakhshiansohi, K. Beernaert, O. Behnke, U. Behrens, A. Bermúdez Martínez, D.
Bertsche, A.A. Bin Anuar, K. Borras16, V. Botta, A. Campbell, A. Cardini, P.
Connor, S. Consuegra Rodríguez, C. Contreras-Campana, V. Danilov, A. De Wit,
M.M. Defranchis, C. Diez Pardos, D. Domínguez Damiani, G. Eckerlin, D.
Eckstein, T. Eichhorn, A. Elwood, E. Eren, E. Gallo17, A. Geiser, J.M. Grados
Luyando, A. Grohsjean, M. Guthoff, M. Haranko, A. Harb, N.Z. Jomhari, H. Jung,
A. Kasem16, M. Kasemann, J. Keaveney, C. Kleinwort, J. Knolle, D. Krücker, W.
Lange, T. Lenz, J. Leonard, J. Lidrych, K. Lipka, W. Lohmann18, R. Mankel,
I.-A. Melzer-Pellmann, A.B. Meyer, M. Meyer, M. Missiroli, G. Mittag, J.
Mnich, A. Mussgiller, V. Myronenko, D. Pérez Adán, S.K. Pflitsch, D. Pitzl, A.
Raspereza, A. Saibel, M. Savitskyi, V. Scheurer, P. Schütze, C.
Schwanenberger, R. Shevchenko, A. Singh, H. Tholen, O. Turkot, A. Vagnerini,
M. Van De Klundert, G.P. Van Onsem, R. Walsh, Y. Wen, K. Wichmann, C. Wissing,
O. Zenaiev, R. Zlebcik University of Hamburg, Hamburg, Germany
R. Aggleton, S. Bein, L. Benato, A. Benecke, V. Blobel, T. Dreyer, A.
Ebrahimi, A. Fröhlich, C. Garbers, E. Garutti, D. Gonzalez, P. Gunnellini, J.
Haller, A. Hinzmann, A. Karavdina, G. Kasieczka, R. Klanner, R. Kogler, N.
Kovalchuk, S. Kurz, V. Kutzner, J. Lange, T. Lange, A. Malara, 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, B. Vormwald, I.
Zoi Karlsruher Institut fuer Technologie, Karlsruhe, Germany
M. Akbiyik, C. Barth, M. Baselga, S. Baur, T. Berger, E. Butz, R. Caspart, T.
Chwalek, W. De Boer, A. Dierlamm, K. El Morabit, N. Faltermann, M. Giffels, P.
Goldenzweig, M.A. Harrendorf, F. Hartmann15, U. Husemann, S. Kudella, S.
Mitra, M.U. Mozer, Th. Müller, M. Musich, A. Nürnberg, G. Quast, K. Rabbertz,
M. Schröder, I. Shvetsov, H.J. Simonis, R. Ulrich, M. Weber, C. Wöhrmann, R.
Wolf Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia
Paraskevi, Greece
G. Anagnostou, P. Asenov, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas,
G. Paspalaki National and Kapodistrian University of Athens, Athens, Greece
M. Diamantopoulou, G. Karathanasis, P. Kontaxakis, A. Panagiotou, I.
Papavergou, N. Saoulidou, K. Theofilatos, K. Vellidis National Technical
University of Athens, Athens, Greece
G. Bakas, K. Kousouris, I. Papakrivopoulos, G. Tsipolitis University of
Ioánnina, Ioánnina, Greece
I. Evangelou, C. Foudas, P. Gianneios, P. Katsoulis, P. Kokkas, S. Mallios, K.
Manitara, N. Manthos, I. Papadopoulos, 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, P. Major, K. Mandal, A. Mehta, M.I. Nagy, G. Pasztor,
O. Surányi, G.I. Veres Wigner Research Centre for Physics, Budapest, Hungary
G. Bencze, C. Hajdu, D. 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. Karancsi19, A. Makovec, J. Molnar, Z. Szillasi
Institute of Physics, University of Debrecen, Debrecen, Hungary
P. Raics, D. Teyssier, Z.L. Trocsanyi, B. Ujvari Eszterhazy Karoly University,
Karoly Robert Campus, Gyongyos, Hungary
T.F. Csorgo, F. Nemes, T. Novak Indian Institute of Science (IISc), Bangalore,
India
S. Choudhury, J.R. Komaragiri, P.C. Tiwari National Institute of Science
Education and Research, HBNI, Bhubaneswar, India
S. Bahinipati22, C. Kar, G. Kole, P. Mal, V.K. Muraleedharan Nair Bindhu, A.
Nayak23, S. Roy Chowdhury, 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, M. Meena, K. Sandeep,
S. Sharma, J.B. Singh, A.K. Virdi, G. Walia University of Delhi, Delhi, India
A. Bhardwaj, B.C. Choudhary, R.B. Garg, M. Gola, S. Keshri, Ashok Kumar, 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. Dutta, S. Ghosh, M. Maity25, K. Mondal, S. Nandan, A.
Purohit, P.K. Rout, A. Roy, G. Saha, S. Sarkar, T. Sarkar25, M. Sharan, B.
Singh24, S. Thakur24 Indian Institute of Technology Madras, Madras, India
P.K. Behera, A. Muhammad Bhabha Atomic Research Centre, Mumbai, India
R. Chudasama, D. Dutta, V. Jha, V. Kumar, D.K. Mishra, P.K. Netrakanti, L.M.
Pant, P. Shukla Tata Institute of Fundamental Research-A, Mumbai, India
T. Aziz, M.A. Bhat, S. Dugad, G.B. Mohanty, N. Sur, RavindraKumar Verma Tata
Institute of Fundamental Research-B, Mumbai, India
S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, S. Karmakar,
S. Kumar, G. Majumder, K. Mazumdar, N. Sahoo, S. Sawant Indian Institute of
Science Education and Research (IISER), Pune, India
S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, A.
Rastogi, 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
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,
S. Mya,b, S. Nuzzoa,b, A. Pompilia,b, G. Pugliesea,c, R. Radognaa, A.
Ranieria, G. Selvaggia,b, L. Silvestrisa, R. Vendittia, P. Verwilligena INFN
Sezione di Bologna a, Università di Bologna b, Bologna, Italy
G. Abbiendia, C. Battilanaa,b, D. Bonacorsia,b, L. Borgonovia,b, S. Braibant-
Giacomellia,b, R. Campaninia,b, P. Capiluppia,b, A. Castroa,b, F.R. Cavalloa,
S.S. Chhibraa,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, F. Iemmia,b, S. Lo Meoa,28, S. Marcellinia, G.
Masettia, F.L. Navarriaa,b, A. Perrottaa, F. Primaveraa,b, A.M. Rossia,b, T.
Rovellia,b, G.P. Sirolia,b, N. Tosia INFN Sezione di Catania a, Università di
Catania b, Catania, Italy
S. Albergoa,b,29, S. Costaa,b, A. Di Mattiaa, R. Potenzaa,b, A. Tricomia,b,29,
C. Tuvea,b INFN Sezione di Firenze a, Università di Firenze b, Firenze, Italy
G. Barbaglia, R. Ceccarelli, 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,30, 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
M. Bozzoa,b, F. Ferroa, R. Mulargiaa,b, E. Robuttia, S. Tosia,b INFN Sezione
di Milano-Bicocca a, Università di Milano-Bicocca b, Milano, Italy
A. Benagliaa, A. Beschib, F. Brivioa,b, V. Cirioloa,b,15, S. Di Guidaa,b,15,
M.E. Dinardoa,b, P. Dinia, S. Fiorendia,b, S. Gennaia, A. Ghezzia,b, P.
Govonia,b, M. Malbertia,b, S. Malvezzia, D. Menascea, F. Monti, L. Moronia, G.
Ortonaa,b, 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, L. Listaa,b, 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. Dossellia, F. Gasparinia,b, U. Gasparinia,b, A. Gozzelinoa, S.Y. Hoh, P.
Lujan, M. Margonia,b, A.T. Meneguzzoa,b, J. Pazzinia,b, M. Presillab, P.
Ronchesea,b, R. Rossina,b, F. Simonettoa,b, A. Tiko, 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, 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, V. Bertacchia,c, L. Bianchinia, T.
Boccalia, 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. Rolandi31, A.
Scribanoa, P. Spagnoloa, R. Tenchinia, G. Tonellia,b, N. Turini, A. Venturia,
P.G. Verdinia INFN Sezione di Roma a, Sapienza Università di Roma b, Rome,
Italy
F. Cavallaria, M. Cipriania,b, D. Del Rea,b, E. Di Marcoa,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, C. Quarantaa,b, S. Rahatloua,b, C.
Rovellia, F. Santanastasioa,b, L. Soffia,b INFN Sezione di Torino a,
Università di Torino b, Torino, Italy, Università del Piemonte Orientale c,
Novara, Italy
N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, N. Bartosika,
R. Bellana,b, C. Biinoa, A. Cappatia,b, 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, R. Salvaticoa,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
B. Kim, D.H. Kim, G.N. Kim, M.S. Kim, J. Lee, S.W. Lee, C.S. Moon, Y.D. Oh,
S.I. Pak, S. Sekmen, D.C. Son, Y.C. Yang Chonnam National University,
Institute for Universe and Elementary Particles, Kwangju, Korea
H. Kim, D.H. Moon, G. Oh Hanyang University, Seoul, Korea
B. Francois, T.J. Kim, J. Park Korea University, Seoul, Korea
S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, K. Lee, K.S. Lee, S.
Lee, J. Lim, J. Park, S.K. Park, Y. Roh Kyung Hee University, Department of
Physics
J. Goh Sejong University, Seoul, Korea
H.S. Kim Seoul National University, Seoul, Korea
J. Almond, J.H. Bhyun, J. Choi, S. Jeon, J. Kim, J.S. Kim, H. Lee, K. Lee, S.
Lee, K. Nam, S.B. Oh, B.C. Radburn-Smith, S.h. Seo, U.K. Yang, H.D. Yoo, I.
Yoon, 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, Y. Jeong, J. Lee, Y. Lee, I. Yu Riga Technical University,
Riga, Latvia
V. Veckalns32 Vilnius University, Vilnius, Lithuania
V. Dudenas, A. Juodagalvis, J. Vaitkus National Centre for Particle Physics,
Universiti Malaya, Kuala Lumpur, Malaysia
Z.A. Ibrahim, F. Mohamad Idris33, W.A.T. Wan Abdullah, M.N. Yusli, Z. Zolkapli
Universidad de Sonora (UNISON), Hermosillo, Mexico
J.F. Benitez, A. Castaneda Hernandez, J.A. Murillo Quijada, L. Valencia Palomo
Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico
H. Castilla-Valdez, E. De La Cruz-Burelo, M.C. Duran-Osuna, I. Heredia-De La
Cruz34, R. Lopez-Fernandez, R.I. Rabadan-Trejo, G. Ramirez-Sanchez, R. Reyes-
Almanza, A. Sanchez-Hernandez Universidad Iberoamericana, Mexico City, Mexico
S. Carrillo Moreno, C. Oropeza Barrera, M. Ramirez-Garcia, F. Vazquez Valencia
Benemerita Universidad Autonoma de Puebla, Puebla, Mexico
J. Eysermans, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad
Autónoma de San Luis Potosí, San Luis Potosí, Mexico
A. Morelos Pineda University of Montenegro, Podgorica, Montenegro
N. Raicevic University of Auckland, Auckland, New Zealand
D. Krofcheck University of Canterbury, Christchurch, New Zealand
S. Bheesette, P.H. Butler National Centre for Physics, Quaid-I-Azam
University, Islamabad, Pakistan
A. Ahmad, M. Ahmad, Q. Hassan, H.R. Hoorani, W.A. Khan, M.A. Shah, M. Shoaib,
M. Waqas AGH University of Science and Technology Faculty of Computer Science,
Electronics and Telecommunications, Krakow, Poland
V. Avati, L. Grzanka, M. Malawski National Centre for Nuclear Research,
Swierk, Poland
H. Bialkowska, M. Bluj, B. Boimska, M. Górski, M. Kazana, M. Szleper, P.
Zalewski Institute of Experimental Physics, Faculty of Physics, University of
Warsaw, Warsaw, Poland
K. Bunkowski, A. Byszuk35, 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, D. Bastos, 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
P. Bunin, M. Gavrilenko, A. Golunov, A. Golunov, I. Golutvin, I. Gorbunov, V.
Karjavine, V. Korenkov, A. Lanev, A. Malakhov, V. Matveev36,37, P. Moisenz, V.
Palichik, V. Perelygin, M. Savina, S. Shmatov, S. Shulha, O. Teryaev, N.
Voytishin, A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St.
Petersburg), Russia
L. Chtchipounov, V. Golovtsov, Y. Ivanov, V. Kim38, E. Kuznetsova39, P.
Levchenko, V. Murzin, V. Oreshkin, I. Smirnov, D. Sosnov, V. Sulimov, L.
Uvarov, A. Vorobyev Institute for Nuclear Research, Moscow, Russia
Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov,
N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical
and Experimental Physics named by A.I. Alikhanov of NRC ‘Kurchatov Institute’,
Moscow, Russia
V. Epshteyn, V. Gavrilov, N. Lychkovskaya, A. Nikitenko8, V. Popov, I.
Pozdnyakov, G. Safronov, A. Spiridonov, A. Stepennov, M. Toms, E. Vlasov, A.
Zhokin Moscow Institute of Physics and Technology, Moscow, Russia
T. Aushev National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
R. Chistov40, M. Danilov40, D. Philippov, E. Tarkovskii P.N. Lebedev Physical
Institute, Moscow, Russia
V. Andreev, M. Azarkin, I. Dremin37, M. Kirakosyan, A. Terkulov Skobeltsyn
Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow,
Russia
A. Belyaev, E. Boos, V. Bunichev, M. Dubinin41, L. Dudko, A. Gribushin, V.
Klyukhin, O. Kodolova, I. Lokhtin, S. Obraztsov, M. Perfilov, S. Petrushanko,
V. Savrin Novosibirsk State University (NSU), Novosibirsk, Russia
A. Barnyakov42, V. Blinov42, T. Dimova42, L. Kardapoltsev42, Y. Skovpen42
Institute for High Energy Physics of National Research Centre ‘Kurchatov
Institute’, Protvino, Russia
I. Azhgirey, I. Bayshev, S. Bitioukov, V. Kachanov, D. Konstantinov, P.
Mandrik, V. Petrov, R. Ryutin, S. Slabospitskii, A. Sobol, S. Troshin, N.
Tyurin, A. Uzunian, A. Volkov National Research Tomsk Polytechnic University,
Tomsk, Russia
A. Babaev, A. Iuzhakov, V. Okhotnikov Tomsk State University, Tomsk, Russia
V. Borchsh, V. Ivantchenko, E. Tcherniaev University of Belgrade: Faculty of
Physics and VINCA Institute of Nuclear Sciences
P. Adzic43, P. Cirkovic, D. Devetak, M. Dordevic, P. Milenovic44, J.
Milosevic, M. Stojanovic Centro de Investigaciones Energéticas
Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain
M. Aguilar-Benitez, J. Alcaraz Maestre, A. Álvarez Fernández, I. Bachiller, M.
Barrio Luna, J.A. Brochero Cifuentes, C.A. Carrillo Montoya, M. Cepeda, 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, Á. Navarro Tobar, A. Pérez-Calero Yzquierdo,
J. Puerta Pelayo, I. Redondo, L. Romero, S. Sánchez Navas, M.S. Soares, A.
Triossi, C. Willmott Universidad Autónoma de Madrid, Madrid, Spain
C. Albajar, J.F. de Trocóniz Universidad de Oviedo, Instituto Universitario de
Ciencias y Tecnologías Espaciales de Asturias (ICTEA)
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, 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, G. Gomez, A. Lopez Virto,
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
University of Colombo, Colombo, Sri Lanka
K. Malagalage University of Ruhuna, Department of Physics, Matara, Sri Lanka
W.G.D. Dharmaratna, N. Wickramage CERN, European Organization for Nuclear
Research, Geneva, Switzerland
D. Abbaneo, B. Akgun, E. Auffray, G. Auzinger, J. Baechler, P.
Baillon${}^{\textrm{\textdagger}}$, A.H. Ball, D. Barney, J. Bendavid, M.
Bianco, A. Bocci, E. Bossini, C. Botta, E. Brondolin, T. Camporesi, A.
Caratelli, G. Cerminara, E. Chapon, G. Cucciati, D. d’Enterria, A. Dabrowski,
N. Daci, V. Daponte, A. David, A. De Roeck, N. Deelen, M. Deile, M. Dobson, M.
Dünser, N. Dupont, A. Elliott-Peisert, F. Fallavollita45, D. Fasanella, G.
Franzoni, J. Fulcher, W. Funk, S. Giani, D. Gigi, A. Gilbert, K. Gill, F.
Glege, M. Gruchala, M. Guilbaud, D. Gulhan, J. Hegeman, C. Heidegger, Y.
Iiyama, V. Innocente, A. Jafari, P. Janot, O. Karacheban18, J. Kaspar, J.
Kieseler, M. Krammer1, C. Lange, P. Lecoq, C. Lourenço, L. Malgeri, M.
Mannelli, A. Massironi, F. Meijers, J.A. Merlin, S. Mersi, E. Meschi, 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, M. Quinto, D. Rabady, A. Racz, M. Rovere,
H. Sakulin, C. Schäfer, C. Schwick, M. Selvaggi, A. Sharma, P. Silva, W.
Snoeys, P. Sphicas46, A. Stakia, J. Steggemann, V.R. Tavolaro, D. Treille, A.
Tsirou, A. Vartak, 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, 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, F. Pauss, G. Perrin, L. Perrozzi, S. Pigazzini, M.
Reichmann, C. Reissel, T. Reitenspiess, D. Ruini, D.A. Sanz Becerra, M.
Schönenberger, L. Shchutska, M.L. Vesterbacka Olsson, R. Wallny, D.H. Zhu
Universität Zürich, Zurich, Switzerland
T.K. Aarrestad, C. Amsler48, D. Brzhechko, M.F. Canelli, A. De Cosa, R. Del
Burgo, S. Donato, C. Galloni, B. Kilminster, S. Leontsinis, V.M. Mikuni, I.
Neutelings, G. Rauco, P. Robmann, D. Salerno, K. Schweiger, C. Seitz, Y.
Takahashi, S. Wertz, A. Zucchetta National Central University, Chung-Li,
Taiwan
T.H. Doan, C.M. Kuo, W. Lin, S.S. Yu National Taiwan University (NTU), Taipei,
Taiwan
P. Chang, Y. Chao, K.F. Chen, P.H. Chen, W.-S. Hou, 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. Damarseckin50, Z.S. Demiroglu, F. Dolek, C.
Dozen, I. Dumanoglu, G. Gokbulut, EmineGurpinar Guler51, Y. Guler, I. Hos52,
C. Isik, E.E. Kangal53, O. Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G.
Onengut, K. Ozdemir54, S. Ozturk55, A.E. Simsek, D. Sunar Cerci49, U.G. Tok,
S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University,
Physics Department, Ankara, Turkey
B. Isildak56, G. Karapinar57, M. Yalvac Bogazici University, Istanbul, Turkey
I.O. Atakisi, E. Gülmez, M. Kaya58, O. Kaya59, B. Kaynak, Ö. Özçelik, S.
Ozkorucuklu60, S. Tekten, E.A. Yetkin61 Istanbul Technical University,
Istanbul, Turkey
A. Cakir, Y. Komurcu, S. Sen62 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, E. Bhal, S. Bologna, J.J. Brooke, D. Burns, E. Clement, D. Cussans,
O. Davignon, H. Flacher, J. Goldstein, G.P. Heath, H.F. Heath, L. Kreczko, S.
Paramesvaran, B. Penning, T. Sakuma, S. Seif El Nasr-Storey, D. Smith, V.J.
Smith, J. Taylor, A. Titterton Rutherford Appleton Laboratory, Didcot, United
Kingdom
K.W. Bell, A. Belyaev63, C. Brew, R.M. Brown, D. Cieri, D.J.A. Cockerill, J.A.
Coughlan, K. Harder, S. Harper, J. Linacre, K. Manolopoulos, D.M. Newbold64,
E. Olaiya, D. Petyt, T. Reis, T. Schuh, C.H. Shepherd-Themistocleous, A. Thea,
I.R. Tomalin, T. Williams, W.J. Womersley Imperial College, London, United
Kingdom
R. Bainbridge, P. Bloch, J. Borg, S. Breeze, O. Buchmuller, A. Bundock,
GurpreetSingh CHAHAL65, D. Colling, P. Dauncey, G. Davies, M. Della Negra, R.
Di Maria, P. Everaerts, G. Hall, G. Iles, T. James, M. Komm, C. Laner, L.
Lyons, A.-M. Magnan, S. Malik, A. Martelli, V. Milosevic, J. Nash66, V.
Palladino, M. Pesaresi, D.M. Raymond, A. Richards, A. Rose, E. Scott, C. Seez,
A. Shtipliyski, M. Stoye, T. Strebler, S. Summers, A. Tapper, K. Uchida, T.
Virdee15, N. Wardle, D. Winterbottom, J. Wright, A.G. Zecchinelli, 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, 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, Z. Demiragli, D. Gastler, S. Girgis, D. Pinna, C.
Richardson, J. Rohlf, D. Sperka, I. Suarez, L. Sulak, D. Zou Brown University,
Providence, USA
G. Benelli, B. Burkle, X. Coubez, D. Cutts, M. Hadley, J. Hakala, U. Heintz,
J.M. Hogan67, K.H.M. Kwok, E. Laird, G. Landsberg, J. Lee, Z. Mao, M. Narain,
S. Sagir68, R. Syarif, E. Usai, D. Yu University of California, Davis, Davis,
USA
R. Band, C. Brainerd, R. Breedon, M. Calderon De La Barca Sanchez, M. Chertok,
J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, F. Jensen, W.
Ko, O. Kukral, R. Lander, M. Mulhearn, D. Pellett, J. Pilot, 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
K. Burt, R. Clare, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, G.
Karapostoli, E. Kennedy, O.R. Long, M. Olmedo Negrete, M.I. Paneva, W. Si, L.
Wang, H. Wei, S. Wimpenny, B.R. Yates, Y. Zhang University of California, San
Diego, La Jolla, USA
J.G. Branson, P. Chang, S. Cittolin, M. Derdzinski, R. Gerosa, D. Gilbert, B.
Hashemi, D. Klein, V. Krutelyov, J. Letts, M. Masciovecchio, S. May, S. Padhi,
M. Pieri, V. Sharma, M. Tadel, F. Würthwein, A. Yagil, G. Zevi Della Porta
University of California, Santa Barbara - Department of Physics, Santa
Barbara, USA
N. Amin, R. Bhandari, C. Campagnari, M. Citron, V. Dutta, M. Franco Sevilla,
L. Gouskos, J. Incandela, B. Marsh, H. Mei, A. Ovcharova, H. Qu, J. Richman,
U. Sarica, D. Stuart, 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, J.
Pata, M. Spiropulu, J.R. Vlimant, S. Xie, Z. Zhang, R.Y. Zhu Carnegie Mellon
University, Pittsburgh, USA
M.B. Andrews, T. Ferguson, T. Mudholkar, M. Paulini, M. Sun, I. Vorobiev, M.
Weinberg University of Colorado Boulder, Boulder, USA
J.P. Cumalat, W.T. Ford, A. Johnson, 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, A. Frankenthal, K.
Mcdermott, N. Mirman, J.R. Patterson, D. Quach, A. Rinkevicius, A. Ryd, S.M.
Tan, Z. Tao, J. Thom, P. Wittich, M. Zientek Fermi National Accelerator
Laboratory, Batavia, USA
S. Abdullin, M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, A. Apyan, S.
Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, K. Burkett,
J.N. Butler, A. Canepa, G.B. Cerati, H.W.K. Cheung, F. Chlebana, M. Cremonesi,
J. Duarte, V.D. Elvira, J. Freeman, Z. Gecse, E. Gottschalk, L. Gray, D.
Green, S. Grünendahl, O. Gutsche, AllisonReinsvold Hall, J. Hanlon, R.M.
Harris, S. Hasegawa, R. Heller, J. Hirschauer, Z. Hu, B. Jayatilaka, S.
Jindariani, M. Johnson, U. Joshi, B. Klima, M.J. Kortelainen, B. Kreis, S.
Lammel, J. Lewis, D. Lincoln, R. Lipton, M. Liu, T. Liu, J. Lykken, K.
Maeshima, J.M. Marraffino, D. Mason, P. McBride, P. Merkel, S. Mrenna, S.
Nahn, V. O’Dell, V. Papadimitriou, K. Pedro, C. Pena, G. Rakness, F. Ravera,
L. Ristori, B. Schneider, E. Sexton-Kennedy, N. Smith, A. Soha, W.J. Spalding,
L. Spiegel, S. Stoynev, J. Strait, N. Strobbe, L. Taylor, S. Tkaczyk, N.V.
Tran, L. Uplegger, E.W. Vaandering, C. Vernieri, M. Verzocchi, R. Vidal, M.
Wang, H.A. Weber University of Florida, Gainesville, USA
D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerhoff, L. Cadamuro,
A. Carnes, V. Cherepanov, D. Curry, R.D. Field, S.V. Gleyzer, B.M. Joshi, M.
Kim, J. Konigsberg, A. Korytov, K.H. Lo, P. Ma, K. Matchev, N. Menendez, G.
Mitselmakher, D. Rosenzweig, K. Shi, J. Wang, S. Wang, X. Zuo Florida
International University, Miami, USA
Y.R. Joshi, S. Linn Florida State University, Tallahassee, USA
T. Adams, A. Askew, S. Hagopian, V. Hagopian, K.F. Johnson, R. Khurana, T.
Kolberg, G. Martinez, T. Perry, H. Prosper, C. Schiber, R. Yohay Florida
Institute of Technology, Melbourne, USA
M.M. Baarmand, V. Bhopatkar, M. Hohlmann, D. Noonan, M. Rahmani, T. Roy, M.
Saunders, F. Yumiceva University of Illinois at Chicago (UIC), Chicago, USA
M.R. Adams, L. Apanasevich, D. Berry, R. Cavanaugh, X. Chen, S. Dittmer, O.
Evdokimov, C.E. Gerber, D.A. Hangal, D.J. Hofman, K. Jung, C. Mills, M.B.
Tonjes, N. Varelas, H. Wang, X. Wang, Z. Wu, J. Zhang The University of Iowa,
Iowa City, USA
M. Alhusseini, B. Bilki51, W. Clarida, K. Dilsiz69, S. Durgut, R.P.
Gandrajula, M. Haytmyradov, V. Khristenko, O.K. Köseyan, 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, M. Swartz, M. Xiao The University of
Kansas, Lawrence, USA
A. Al-bataineh, C. Baldenegro Barrera, P. Baringer, A. Bean, S. Boren, A.
Bylinkin, J. Castle, T. Isidori, S. Khalil, J. King, A. Kropivnitskaya, D.
Majumder, W. Mcbrayer, N. Minafra, M. Murray, C. Rogan, C. Royon, S. Sanders,
E. Schmitz, J.D. Tapia Takaki, Q. Wang, J. Williams Kansas State University,
Manhattan, USA
S. Duric, A. Ivanov, K. Kaadze, D. Kim, Y. Maravin, D.R. Mendis, T. Mitchell,
A. Modak, A. Mohammadi Lawrence Livermore National Laboratory, Livermore, USA
F. Rebassoo, D. Wright University of Maryland, College Park, USA
A. Baden, O. Baron, A. Belloni, S.C. Eno, Y. Feng, C. Ferraioli, N.J. Hadley,
S. Jabeen, G.Y. Jeng, R.G. Kellogg, J. Kunkle, A.C. Mignerey, S. Nabili, F.
Ricci-Tam, M. Seidel, Y.H. Shin, A. Skuja, S.C. Tonwar, K. Wong Massachusetts
Institute of Technology, Cambridge, USA
D. Abercrombie, B. Allen, A. Baty, R. Bi, S. Brandt, W. Busza, I.A. Cali, M.
D’Alfonso, G. Gomez Ceballos, M. Goncharov, P. Harris, D. Hsu, M. Hu, M.
Klute, D. Kovalskyi, Y.-J. Lee, P.D. Luckey, B. Maier, A.C. Marini, C. Mcginn,
C. Mironov, S. Narayanan, X. Niu, C. Paus, D. Rankin, C. Roland, G. Roland, Z.
Shi, G.S.F. Stephans, K. Sumorok, K. Tatar, D. Velicanu, J. Wang, T.W. Wang,
B. Wyslouch University of Minnesota, Minneapolis, USA
A.C. Benvenuti${}^{\textrm{\textdagger}}$, R.M. Chatterjee, A. Evans, P.
Hansen, J. Hiltbrand, S. Kalafut, Y. Kubota, Z. Lesko, J. Mans, 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, L. Finco, F. Golf, R. Gonzalez
Suarez, R. Kamalieddin, I. Kravchenko, 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, G. Madigan,
D.M. Morse, T. Orimoto, L. Skinnari, A. Tishelman-Charny, T. Wamorkar, B.
Wang, A. Wisecarver, D. Wood Northwestern University, Evanston, USA
S. Bhattacharya, J. Bueghly, T. Gunter, K.A. Hahn, N. Odell, M.H. Schmitt, K.
Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, USA
R. Bucci, N. Dev, R. Goldouzian, M. Hildreth, K. Hurtado Anampa, C. Jessop,
D.J. Karmgard, K. Lannon, W. Li, N. Loukas, N. Marinelli, I. Mcalister, F.
Meng, C. Mueller, Y. Musienko36, M. Planer, R. Ruchti, P. Siddireddy, G.
Smith, S. Taroni, M. Wayne, A. Wightman, M. Wolf, A. Woodard The Ohio State
University, Columbus, USA
J. Alimena, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, C. Hill, W. Ji, A.
Lefeld, T.Y. Ling, B.L. Winer Princeton University, Princeton, USA
S. Cooperstein, G. Dezoort, P. Elmer, J. Hardenbrook, N. Haubrich, S.
Higginbotham, A. Kalogeropoulos, S. Kwan, D. Lange, M.T. Lucchini, J. Luo, D.
Marlow, K. Mei, I. Ojalvo, J. Olsen, C. Palmer, P. Piroué, J. Salfeld-Nebgen,
D. Stickland, C. Tully, Z. Wang University of Puerto Rico, Mayaguez, USA
S. Malik, S. Norberg Purdue University, West Lafayette, USA
A. Barker, V.E. Barnes, S. Das, L. Gutay, M. Jones, A.W. Jung, A. Khatiwada,
B. Mahakud, D.H. Miller, G. Negro, N. Neumeister, C.C. Peng, S. Piperov, H.
Qiu, J.F. Schulte, J. Sun, F. Wang, R. Xiao, W. Xie Purdue University
Northwest, Hammond, USA
T. Cheng, J. Dolen, N. Parashar Rice University, Houston, USA
K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Kilpatrick, Arun Kumar, W. Li, B.P.
Padley, R. Redjimi, J. Roberts, J. Rorie, W. Shi, A.G. Stahl Leiton, Z. Tu, A.
Zhang University of Rochester, Rochester, USA
A. Bodek, P. de Barbaro, R. Demina, 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
B. Chiarito, J.P. Chou, Y. Gershtein, E. Halkiadakis, A. Hart, M. Heindl, E.
Hughes, S. Kaplan, S. Kyriacou, I. Laflotte, A. Lath, R. Montalvo, K. Nash, M.
Osherson, H. Saka, S. Salur, S. Schnetzer, D. Sheffield, S. Somalwar, R.
Stone, S. Thomas, P. Thomassen University of Tennessee, Knoxville, USA
H. Acharya, 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, D. Marley, R. Mueller, D.
Overton, L. Perniè, D. Rathjens, A. Safonov Texas Tech University, Lubbock,
USA
N. Akchurin, J. Damgov, F. De Guio, S. Kunori, K. Lamichhane, S.W. Lee, T.
Mengke, S. Muthumuni, T. Peltola, S. Undleeb, I. Volobouev, Z. Wang, A.
Whitbeck Vanderbilt University, Nashville, USA
S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K.
Padeken, F. Romeo, P. Sheldon, S. Tuo, J. Velkovska, M. Verweij University of
Virginia, Charlottesville, USA
M.W. Arenton, P. Barria, B. Cox, G. Cummings, R. Hirosky, M. Joyce, A.
Ledovskoy, C. Neu, B. Tannenwald, Y. Wang, E. Wolfe, F. Xia Wayne State
University, Detroit, USA
R. Harr, P.E. Karchin, N. Poudyal, J. Sturdy, P. Thapa, S. Zaleski University
of Wisconsin - Madison, Madison, WI, USA
J. Buchanan, C. Caillol, D. Carlsmith, S. Dasu, I. De Bruyn, L. Dodd, B.
Gomber74, M. Grothe, M. Herndon, A. Hervé, U. Hussain, P. Klabbers, A. Lanaro,
K. Long, R. Loveless, T. Ruggles, A. Savin, V. Sharma, 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 Universidade Federal de Pelotas, Pelotas, Brazil
6: Also at Université Libre de Bruxelles, Bruxelles, Belgium
7: Also at University of Chinese Academy of Sciences, Beijing, China
8: Also at Institute for Theoretical and Experimental Physics named by A.I.
Alikhanov of NRC ‘Kurchatov Institute’, Moscow, Russia
9: Also at Joint Institute for Nuclear Research, Dubna, Russia
10: Also at Cairo University, Cairo, Egypt
11: Also at Helwan University, Cairo, Egypt
12: Now at Zewail City of Science and Technology, Zewail, Egypt
13: Also at Purdue University, West Lafayette, USA
14: Also at Université de Haute Alsace, Mulhouse, France
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 Institute of Physics, University of Debrecen, Debrecen, Hungary
20: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
21: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, 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 Italian National Agency for New Technologies, Energy and
Sustainable Economic Development, Bologna, Italy
29: Also at Centro Siciliano di Fisica Nucleare e di Struttura della Materia,
Catania, Italy
30: Also at Università degli Studi di Siena, Siena, Italy
31: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy
32: Also at Riga Technical University, Riga, Latvia
33: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia
34: Also at Consejo Nacional de Ciencia y Tecnología, Mexico City, Mexico
35: Also at Warsaw University of Technology, Institute of Electronic Systems,
Warsaw, Poland
36: Also at Institute for Nuclear Research, Moscow, Russia
37: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
38: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
39: Also at University of Florida, Gainesville, USA
40: Also at P.N. Lebedev Physical Institute, Moscow, Russia
41: Also at California Institute of Technology, Pasadena, USA
42: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
43: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
44: Also at University of Belgrade, Belgrade, Serbia
45: Also at INFN Sezione di Pavia a, Università di Pavia b, Pavia, Italy
46: Also at National and Kapodistrian University of Athens, Athens, Greece
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 Sirnak University, SIRNAK, Turkey
51: Also at Beykent University, Istanbul, Turkey
52: Also at Istanbul Aydin University, Istanbul, Turkey
53: Also at Mersin University, Mersin, Turkey
54: Also at Piri Reis University, Istanbul, Turkey
55: Also at Gaziosmanpasa University, Tokat, Turkey
56: Also at Ozyegin University, Istanbul, Turkey
57: Also at Izmir Institute of Technology, Izmir, Turkey
58: Also at Marmara University, Istanbul, Turkey
59: Also at Kafkas University, Kars, Turkey
60: Also at Istanbul University, Istanbul, Turkey
61: Also at Istanbul Bilgi University, Istanbul, Turkey
62: Also at Hacettepe University, Ankara, Turkey
63: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
64: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom
65: Also at Institute for Particle Physics Phenomenology Durham University,
Durham, United Kingdom
66: Also at Monash University, Faculty of Science, Clayton, Australia
67: Also at Bethel University, St. Paul, USA
68: Also at Karamanoğlu Mehmetbey University, Karaman, 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
74: Also at University of Hyderabad, Hyderabad, India