HIG-16-018

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$Id:HIG-16-018.tex4730252018-08-2711:46:22Zchayanit$

HIG-16-018

# Search for beyond the standard model Higgs bosons decaying into a pair in
collisions at $\sqrt{s}=13\TeV$

###### Abstract

A search for Higgs bosons that decay into a bottom quark-antiquark pair and
are accompanied by at least one additional bottom quark is performed with the
CMS detector. The data analyzed were recorded in proton-proton collisions at a
centre-of-mass energy of $\sqrt{s}=13\TeV$ at the LHC, corresponding to an
integrated luminosity of 35.7. The final state considered in this analysis is
particularly sensitive to signatures of a Higgs sector beyond the standard
model, as predicted in the generic class of two Higgs doublet models (2HDMs).
No signal above the standard model background expectation is observed.
Stringent upper limits on the cross section times branching fraction are set
for Higgs bosons with masses up to 1300. The results are interpreted within
several MSSM and 2HDM scenarios.

##  0.1 Introduction

In the standard model (SM), a Higgs boson at a mass of 125has a large coupling
to quarks via Yukawa interactions. Its production in association with quarks
and subsequent decay into quarks at the CERN LHC is, however, difficult to
detect because of the high rate of heavy-flavour multijet production. There
are, nevertheless, models beyond the SM that predict an enhancement of Higgs
boson production in association with quarks, which motivate the search for
such processes.

Prominent examples of models beyond the SM are the two Higgs doublet model
(2HDM) [1], which contains two scalar Higgs doublets, as well as one
particular realization within the minimal supersymmetric extension of the SM
(MSSM) [2]. These result in two charged Higgs bosons, and three neutral ones,
jointly denoted as $\phi$. Among the latter are, under the assumption that
$CP$ is conserved, one $CP$-odd (A), and two $CP$-even (h, ) states, where
usually denotes the lighter $CP$-even state. For the purpose of this analysis,
the boson discovered in 2012 with a mass near 125 [3, 4, 5, 6] is interpreted
as , whose mass is thus constrained to the measured value. The two heavier
neutral states, and A, are the subject of the search presented here.

In the 2HDM, flavour changing neutral currents at tree level can be suppressed
by introducing discrete symmetries, which restrict the choice of Higgs
doublets to which the fermions can couple. This leads to four types of models
with natural flavour conservation at tree level:

  * •

type-I: all charged fermions couple to the same doublet;

  * •

type-II: up-type quarks (, , ) couple to one doublet, down-type fermions (, ,
, , , ) couple to the other. This structure is also implemented in the MSSM;

  * •

lepton-specific: all charged leptons couple to one doublet, all quarks couple
to the other;

  * •

flipped: charged leptons and up-type quarks couple to one doublet, down-type
quarks to the other.

While until now the type-I and -II models have been most intensively tested,
the flipped model is remarkably unexplored from the experimental side. The
$\PSA/\PH\to\bbbar{}$ decay mode is ideally suited to constrain this model due
to the large branching fraction of the Higgs boson into quarks.

The $CP$-conserving 2HDMs have seven free parameters. They can be chosen as
the Higgs boson masses ($m_{\Ph}$, $m_{\PH}$, $m_{\PSA}$, $m_{\PHpm}$), the
mixing angle between the $CP$-even Higgs bosons ($\alpha$), the ratio of the
vacuum expectation values of the two doublets ($\tanb=v_{2}/v_{1}$), and the
parameter that potentially mixes the two Higgs doublets ($m_{12}$). For
$\cos(\beta-\alpha)\to 0$, the light $CP$-even Higgs boson (h) obtains
properties indistinguishable from the SM Higgs boson with the same mass in all
four types of models listed above [1].

The MSSM Higgs sector has the structure of a type-II 2HDM. The additional
constraints given by the fermion-boson symmetry fix all mass relations between
the Higgs bosons and the angle $\alpha$ at tree level, reducing the number of
parameters at this level to only two. These parameters are commonly chosen as
the mass of the pseudoscalar Higgs boson, $m_{\PSA}$, and . After the Higgs
boson discovery at the LHC, MSSM benchmark scenarios have been refined to
match the experimental data and to reveal characteristic features of certain
regions of the parameter space [7, 8]. Considered in this analysis are the
$m_{\Ph}^{\text{mod+}}$, the hMSSM [9], the light stau ($\sTau$), and the
light stop ($\sTop$) scenarios [7].

The $m_{\Ph}^{\text{mod+}}$ scenario is a modification of the
$m_{\Ph}^{\text{max}}$ scenario, which was originally defined to give
conservative exclusion bounds on $\tanb$ in the LEP Higgs boson searches [10,
11, 12]. It has been modified such that the mass of the lightest $CP$-even
state, $m_{\Ph}$, is compatible with the mass of the observed boson within
$\pm 3\GeV$ [13, 14] in a large fraction of the considered parameter space
[7]. The hMSSM approach [15, 9, 16] describes the MSSM Higgs sector in terms
of just $m_{\PSA}$ and , given the experimental knowledge of $m_{\PZ}$ and
$m_{\Ph}$. It defines a largely model-independent scenario, because the
predictions for the properties of the MSSM Higgs bosons do not depend on the
details of the supersymmetric sector [17]. Further variations of the
supersymmetric sector are implemented in the light $\sTau$ and light $\sTop$
scenarios [7], which are also designed such that the light scalar is
compatible with the measured Higgs boson mass [18].

For values larger than one, the couplings of the Higgs fields to quarks are
enhanced both in the flipped and the type-II models, and thus also in the
MSSM. Furthermore, there is an approximate mass degeneracy between the and
bosons in the MSSM for the studied range of $m_{\PSA}$. For the 2HDM scenarios
considered in this paper, such a degeneracy will be imposed. These effects
enhance the combined cross section for producing these Higgs bosons in
association with quarks by a factor of up to 2 with respect to the SM. The
decay $\PSA/\PH\to\bbbar$ is expected to have a high branching fraction, even
at large values of the Higgs boson mass and $\abs{\cos(\beta-\alpha)}$ [19].

The most stringent constraints on the MSSM parameter so far, with exclusion
limits in the range 4–60 in the mass interval of 90–1600, have been obtained
in measurements at the LHC in the $\phi\to\tau\tau$ decay mode [20, 21, 22,
23, 24, 25]. Preceding limits have been obtained by the LEP [10] and the
Tevatron experiments [26, 27, 28]. The $\phi\to\Pgm\Pgm$ decay mode has been
investigated as well [21, 29, 30].

In the $\phi\to\bbbar$ decay mode, searches have initially been performed at
LEP [10] and by the CDF and Collaborations [31] at the Tevatron collider. At
the LHC, the only analyses in this channel with associated jets have also been
performed by the CMS Collaboration using the 7 and 8data [32, 33]. In the
absence of any signal, limits on the
$\Pp\Pp\to\cPqb\phi(\to\bbbar)+\mathrm{X}$ cross section have been derived in
the 90–900mass range. The combined 7 and 8data analyses translate into upper
bounds on between 14 and 50 in the Higgs boson mass range of 100–500, assuming
the $m_{\Ph}^{\text{mod+}}$ scenario of the MSSM.

The ATLAS and CMS Collaborations have performed extensive 2HDM interpretations
of measurements in different production and decay channels, in particular also
in the $\PSA\to\PZ\Ph$, $\Ph\to\bbbar$ decay mode [34, 35, 36]. The ATLAS
interpretation [35] also covers the flipped scenario, and the 2HDM
interpretations reported in this paper are compared to these.

With the proton-proton () collision data set corresponding to an integrated
luminosity of 35.7collected at a centre-of-mass energy of $\sqrt{s}=13\TeV$ in
2016, the sensitivity to key model parameters with respect to previous CMS
searches is significantly extended. The analysis focuses on neutral Higgs
bosons and with masses $m_{\PSA/\PH}\geq 300\GeV$ that are produced in
association with at least one quark and decay to $\bbbar$, as shown by the
diagrams in Fig. 1. The signal signature therefore comprises final states
characterized by at least three quark jets (” jets”), and the dominant
background is multijet production. A fourth jet is not explicitly required,
since due to the process topology the majority of the signal events are found
to have at most three jets within the acceptance of this analysis. Events are
selected by dedicated triggers that identify jets already during data taking.
This helps significantly to suppress the large rate of multijet production,
while maintaining sensitivity to the signal process. The analysis searches for
a peak in the invariant mass distribution, $M_{12}$, of the two jets with the
highest transverse momentum $p_{T}$values, which originate from the Higgs
boson decay in about 66% of all cases at $m_{\PSA/\PH}=300\GeV$, increasing up
to 75% for $m_{\PSA/\PH}\geq 700\GeV$. The dominant background is the
production of heavy-flavour multijet events containing either three jets, or
two jets plus a third jet originating from either a charm quark, a light-
flavour quark, or a gluon, which is misidentified as a jet.

Figure 1: Example Feynman diagrams for the signal processes.

##  0.2 The CMS detector

The central feature of the CMS apparatus is a superconducting solenoid of 6m
internal diameter, providing a magnetic field of 3.8T. Within the field
volume, the inner tracker is formed by a silicon pixel and strip tracker. It
measures charged particles within the pseudorapidity range $\abs{\eta}<2.5$.
The tracker provides a transverse impact parameter resolution of approximately
15and a resolution on $p_{T}$of about 1.5% for particles with p_T$=100\GeV$.
Also inside the field volume are a crystal electromagnetic calorimeter, and a
brass and scintillator hadron calorimeter. Forward calorimetry extends the
coverage provided by the barrel and endcap detectors up to $\abs{\eta}<5$.
Muons are measured in gas-ionization detectors embedded in the steel flux-
return yoke, in the range $\abs{\eta}<2.4$, with detector planes made using
three technologies: drift tubes, cathode strip chambers, and resistive-plate
chambers. Matching muons to tracks measured in the silicon tracker results in
a $p_{T}$resolution between 1 and 10%, for $p_{T}$values up to 1. A detailed
description of the CMS detector, together with a definition of the coordinate
system used and the relevant kinematic variables, can be found in Ref. [37].

##  0.3 Event reconstruction and simulation

A particle-flow algorithm [38] aims to reconstruct and identify all particles
in the event, electrons, muons, photons, and charged and neutral hadrons, with
an optimal combination of all CMS detector systems.

The reconstructed vertex with the largest value of summed physics-object p_T2
is taken to be the primary interaction vertex. The physics objects chosen are
those that have been defined using information from the tracking detector,
including jets, the associated missing transverse momentum, which is taken as
the negative vector sum of the $p_{T}$of those jets, and charged leptons.

Jets are clustered from the reconstructed particle-flow candidates using the
anti-algorithm [39, 40] with a distance parameter of 0.4. Each jet is required
to pass dedicated quality criteria to suppress the impact of instrumental
noise and misreconstruction. Contributions from additional interactions within
the same or neighbouring bunch crossing (pileup) affect the jet momentum
measurement. To mitigate this effect, charged particles associated with other
vertices than the reference primary vertex are discarded before jet
reconstruction [41], and residual contributions (from neutral particles) are
accounted for using a jet-area based correction [42]. Subsequent jet energy
corrections are derived from simulation, and are confirmed with in situ
measurements of the energy balance in dijet, multijet, and / events [43].

For the offline identification of jets, the combined secondary vertex (CSVv2)
algorithm [44] is used. This algorithm combines information on track impact
parameters and secondary vertices within a jet into an artificial neural
network classifier that provides separation between jets and jets of other
flavours.

Simulated samples of signal and background events were produced using
different event generators and include pileup events. The MSSM Higgs boson
signal samples, $\Pp\Pp\to\bbbar\phi$+X with $\phi\to\bbbar$, were produced at
leading order (LO) in the 4-flavour scheme with 8.212 [45]. Comparing this
prediction to computationally expensive next-to-leading order (NLO)
calculations [46] generated using in version 2.3.0 [47, 48], we find a very
good agreement in the shapes of the leading dijet invariant mass distribution,
$M_{12}$, while the selection efficiency is up to 10% lower when using the NLO
prediction. We correct the NLO effect by applying mass-dependent correction
factors to the LO signal samples and assign a corresponding systematic
uncertainty in the final results. Multijet background events from quantum
chromodynamics (QCD) processes have been simulated with the event generator
[49, 50] using the 5-flavour scheme and MLM merging [51]; they are used for
studying qualitative features but not for a quantitative background
prediction. The NNPDF 3.0 [52] parton distribution functions (PDFs) are used
in all generated samples. For all generators, fragmentation, hadronization,
and the underlying event have been modelled using with tune CUETP8M1 [53]. The
response of the CMS detector is modelled with the toolkit [54].

##  0.4 Trigger and event selection

A major challenge to this search is posed by the huge hadronic interaction
rate at the LHC. This is addressed with a dedicated trigger scheme [55],
especially designed to suppress the multijet background. Only events with at
least two jets in the range of $\abs{\eta}\leq 2.4$ are selected. The two
leading jets are required to have p_T$>100\GeV$, and an event is accepted only
if the absolute value of the difference in pseudorapidity, $\Delta\eta$,
between any two jets fulfilling the $p_{T}$and $\eta$ requirements, is less
than or equal to 1.6. The tight online requirements on the opening angles
between jets are introduced to reduce the trigger rates, while preserving high
efficiency in the probed mass range of the Higgs bosons. At trigger level,
jets are identified using the CSVv2 algorithm with slightly tighter
requirements than for the offline analysis. At least two jets in the event
must satisfy the online tagging criteria.

The efficiency of the jet $p_{T}$requirements in the trigger is derived from
data collected with prescaled single-jet triggers with lower threshold. The
efficiency in data and simulation is measured as a function of jet p_T

$and\eta.Thedifferencesbetweenthetwoarecorrectedforintheanalysisofthesimulatedsamples.Theonline\cPqb\
taggingefficienciesrelativetotheoff\/line\cPqb\
taggingselectionareobtainedfromdatausingprescaleddijettriggerswithasingleb-
tagrequirement.Atag-and-
probemethodisemployedtodeterminetheefficiencyasafunctionofp_{T}$

and $\eta$ of the jets. Both leading jets are required to pass offline
selection criteria including tagging requirements similar to the final event
selection described below. The second-leading jet must always pass the online
tagging requirement to ensure that it has fired the trigger. The fraction of
the first leading jets that also satisfy the online tagging requirements is a
direct measure of the relative online tagging efficiency. Relative
efficiencies are found to range from above 80% for p_T$\approx 100\GeV$ to
around 50% for p_T$\approx 900\GeV$, averaged over $\eta$.

The offline selection requires at least two jets with p_T$>100\GeV$ and
another one with p_T$>40\GeV$, which all need to satisfy $\abs{\eta}\leq 2.2$.
The $\eta$ selection is applied to benefit from optimal tagging performance.
The three leading jets have to pass the CSVv2 tagging requirement of the
medium working point [44]. This working point features a 1% probability for
light-flavour jets (attributed to , , , or partons) to be misidentified as
jets, and has a jet identification efficiency of about 70%. The separation
between the two leading jets in $\eta$ has to be less than 1.55, and a minimal
pairwise separation of $\Delta R>1$ between each two of the three leading jets
is imposed to suppress background from pairs arising from gluon splitting.
This sample is referred to as “triple tag” sample in the following.

##  0.5 Signal modeling

A signal template for the $M_{12}$ distribution is obtained for each Higgs
boson mass considered by applying the full selection to the corresponding
simulated signal data set, for nominal masses in the range of 300–1300. The
sensitivity of this analysis does not extend down to cross sections as low as
that of the SM Higgs boson. Thus, a signal model with a single mass peak is
sufficient. This is in contrast to the $\phi\to\tau\tau$ analysis [25], where
the signal model comprises the three neutral Higgs bosons of the MSSM, one of
which is SM-like.

The signal efficiency for each Higgs boson mass point is obtained from
simulation and shown in Fig. 2. A scale factor for the efficiency of the
kinematic trigger selection has been derived with data from control triggers,
as described in Section 0.4, and is applied as a weight for each event.
Correction factors to account for the different tagging efficiencies in data
and simulation [44] are also applied. The total signal efficiency ranges
between 0.5 and 1.4% and peaks around 500. The efficiency first increases due
to the kinematic selection and then decreases for masses beyond 500due to the
requirement of three -tagged jets, and the fact that the tagging efficiency
decreases at high jet $p_{T}$.

Figure 2:  Signal efficiency as a function of the Higgs boson mass after
different stages of event selection.

For nominal masses between 300 and 500, each signal shape is parameterized by
a bifurcated Gaussian function, which has different widths on the right- and
left-hand side of the peak position, continued at higher masses with an
exponential function to describe the tail. The function has five parameters.
The signal of the 600mass point requires one additional Gaussian function on
each side of the peak position to be able to describe the tails of the
distribution. This function has nine parameters in total. For nominal masses
in the range 700–1300, a Bukin function as defined in Appendix .10, which has
five parameters, is used. All parameterizations provide a very good modelling
of the $M_{12}$ spectra.

Figure 3: Invariant mass distributions of the two leading jets in simulated
signal events and their parameterizations for three different /masses,
normalized to unity.

The distributions of the invariant mass of the two leading jets, $M_{12}$, of
the signal templates and parameterizations of the probability density function
for different Higgs boson masses are shown in Fig. 3. The natural width
expected for an MSSM Higgs boson in the considered mass and region is
negligible compared to the detector resolution. For example, in the
$m_{\Ph}^{\text{mod+}}$ scenario at a mass of 600and $\tanb=60$, the natural
width of the mass peak is found to be only about 19% of the full width at half
maximum of the reconstructed mass distribution. The shape of the mass
distribution is thus dominated by the experimental resolution, and the
possibility of the two leading jets used to compute $M_{12}$ not being the
daughters of the Higgs boson, which we refer to as wrong jet pairing.
Pronounced tails towards lower masses are attributed to cases of incomplete
reconstruction of the Higgs daughter partons, for example due to the missing
momentum of neutrinos in semileptonic decays of hadrons containing bottom and
charm quarks. The wrong jet pairing gives rise to tails in both directions.
For the lower mass points, however, the tails towards lower masses are
suppressed because of the jet $p_{T}$threshold.

##  0.6 Background model

The main background for this analysis originates from multijet production,
with at least two energetic jets containing hadrons, and a third jet that
satisfies the tagging selection but possibly as a result of a mistag. Top
quark-antiquark production exhibits a shape very similar to the multijet
process. It is found to be negligible, but nevertheless is implicitly covered
by our background model.

The relevant features of the multijet background are studied in a suitable
control region (CR) in data, which is obtained from the triple tag selection
by imposing a b-tag veto on the third leading jet. This veto rejects jets that
would satisfy a loose tagging requirement, defined by a 10% probability for
light-flavour jets to be misidentified as jets, and has a jet identification
efficiency of about 80%. This CR has no overlaps with the triple tag signal
region (SR), while it preserves similar kinematic distributions for the three
leading jets. In addition, the signal contamination in the CR is negligible.

A suitably chosen analytic function is used to model the multijet background.
This function is extensively validated in the tag veto CR. In order to improve
the background description and reduce the potential bias related to the choice
of the background model, the $M_{12}$ distribution is divided into the three
overlapping subranges [200, 650], [350, 1190], and [500, 1700]. Their borders
are chosen to largely cover the signal shapes of the associated mass points of
[300, 500], [500, 1100], and [1100, 1300], respectively (as discussed in
Section 0.5).

In the first subrange, the selection criteria introduce a kinematic edge
(turn-on) in the $M_{12}$ distribution. The chosen function is a product of
two terms. The first term is a turn-on function, represented by a Gaussian
error function in the form of:

$f(M_{12})=0.5\,\bigl{[}\erf(p_{0}[M_{12}-p_{1}])+1\bigr{]},$ (1)

where

$\erf(x)=\frac{2}{\sqrt{\pi}}\int_{0}^{x}\re^{-t^{2}}\rd{}t,$ (2)

and the parameters $p_{0}$ and $p_{1}$ describe the slope and point of the
turn-on, respectively.

The falling part of the spectrum is described by an extension of the
Novosibirsk function originally used to describe a Compton spectrum [56],
defined as:

$g(M_{12})=p_{2}\exp\left(-\frac{1}{2\sigma_{0}^{2}}\ln^{2}[1-\frac{M_{12}-p_{3}}{p_{4}}p_{5}-\frac{(M_{12}-p_{3})^{2}}{p_{4}}p_{5}p_{6}]-\frac{\sigma_{0}^{2}}{2}\right),$
(3)

where $p_{2}$ is a normalization parameter, $p_{3}$ the peak value of the
distribution, $p_{4}$ and $p_{5}$ are the parameters describing the asymmetry
of the spectrum, and $p_{6}$ is the parameter of the extended term. The
variable $\sigma_{0}$ is defined as:

$\sigma_{0}=\frac{2}{\xi}\sinh^{-1}(p_{5}\xi/2),\ \text{where}\ \xi=2\sqrt{\ln
4}.$ (4)

In the second and third subranges, we choose a nonextended Novosibirsk
function ($p_{6}\equiv 0$) without turn-on factor.

Figure 4 shows the fits of the chosen functions to the CR data, which have
been prescaled to give similar event count as in the SR. In the first
subrange, $M_{12}=[200,650]\GeV$, the turn-on effect due to the jet
$p_{T}$threshold at trigger level is clearly visible. In the other two mass
subranges, the spectrum shows only the expected falling behaviour with
$M_{12}$. The values of the parameters $p_{0}$ and $p_{1}$ used to model the
turn-on obtained in the CR are also used for the SR fit since the turn-on
behaviour in the two regions is found to be very similar. The other function
parameters are allowed to vary independently in the CR and SR fits.

Different families of alternative probability density functions such as
Bernstein polynomials and the so-called dijet function as defined in Ref. [57]
are studied to estimate the possible bias from the choice of the background
model. For each family, a systematic bias on the extraction of a signal with
mass $m_{\PSA/\PH}$ is determined: the alternative function is fit to the
observed data, from which toy experiments are drawn. Using the nominal
background model in the respective subrange, a maximum-likelihood fit of
signal and background is performed for each pseudo-experiment. The difference
in the extracted and injected number of signal events is divided by the
statistical uncertainty of the fit. The resulting pull distribution is
considered to represent the systematic bias on the signal strength due to the
choice of the background function and our insufficient knowledge of the
background processes. We infer a bias of 100, 20, and 25% in units of the
statistical uncertainty of the signal strength for the first, second, and
third subranges, respectively.

Figure 4: Distributions of the dijet invariant mass $M_{12}$, obtained from
the tag veto CR as described in the text in the three subranges used for the
fit: $M_{12}=[200,650]\GeV$ (upper left) in linear scale,
$M_{12}=[350,1190]\GeV$ (upper right) and $M_{12}=[500,1700]\GeV$ (lower) in
logarithmic scale. The dots represent the data. The full line is the result of
the fit of the background parameterizations described in the text. In the
bottom panel of each plot, the normalized difference [(Data-
Fit)/$\sqrt{\mathrm{Fit}}$] is shown.

##  0.7 Systematic uncertainties

The following systematic uncertainties in the expected signal and background
estimation affect the determination of the signal yield or its interpretation
within the MSSM or generic 2HDM models.

The signal yields are affected by the following uncertainties:

  * •

a 2.5% uncertainty in the estimated integrated luminosity of the data sample
[58];

  * •

the uncertainty in the online tagging efficiency scale factor, which results
in an overall uncertainty in the range of 0.8–1.3% for Higgs boson masses of
300–1300 GeV;

  * •

a 5% uncertainty in the correction of the selection efficiency comparing to
the NLO prediction;

  * •

the effect due to the choice of PDFs and the value of $\alpha_{s}$ (1–6%),
following the recommendations of the LHC Higgs Cross Section Working Group
[59] when interpreting the results in benchmark models;

  * •

the uncertainty in the normalization and factorization scales (1–10%) when
interpreting the results in benchmark models.

Uncertainties affecting the shape as well as the normalization of the signal
templates are:

  * •

the uncertainty in the jet trigger efficiencies, ranging between subpercent
values and 7% per jet depending on its $\eta$ and $p_{T}$;

  * •

the uncertainty in the offline tagging efficiency (2–5% per jet depending on
its transverse momentum) and the mistag scale factors ($<$0.3%);

  * •

the jet energy scale (JES) and jet energy resolution (JER) uncertainties
(1–6%): their impact is estimated by varying the JES and JER in the simulation
within the measured uncertainties;

  * •

the uncertainty in the total inelastic cross section of 4.6% assumed in the
pileup simulation procedure [60].

For the background estimation, the bias on the extracted signal strength, as
reported in Section 0.6, is considered as an additional bias term to the
background fitting function. This poses the largest uncertainty for the
analysis.

##  0.8 Results

The number of potential signal events is extracted by performing a maximum-
likelihood fit of the signal plus background parameterizations to the $M_{12}$
data distribution. Initially, a fit with only the background parameterizations
is performed. Results of this background-only fit in all three subranges are
given in Fig. 5. A good description of the data is observed. The normalized
differences between data and fit together with the post-fit uncertainties are
shown for each subrange.

Figure 5: Distribution of the dijet invariant mass $M_{12}$ in the data triple
tag sample showing the three subranges together with the corresponding
background-only fits. The shaded area shows the post-fit uncertainty. For
illustration, the expected signal contribution for three representative mass
points is shown, scaled to cross sections suitable for visualization. The
change of slope around 350of the 300signal shape is caused by wrong jet
pairing. In the bottom panels the normalized difference ((Data-
Bkg)/$\sqrt{\mathrm{Bkg}}$), where Bkg is the background as estimated by the
fit, for the three subranges is shown.

In a second step, a combined fit of signal and background to the data is
performed. No significant excess over the background-only distribution is
observed and upper limits at 95% confidence level (CL) on the cross section
times branching fraction
${\sigma(\Pp\Pp\to\PQb\PSA/\PH+\mathrm{X})\mathcal{B}(\PSA/\PH\to\bbbar)}$ are
derived. For the calculation of exclusion limits, the modified frequentist
criterion [61, 62, 63] is adopted using the RooStats package [64]. The test
statistic is based on the profile likelihood ratio. Systematic uncertainties
are treated as nuisance parameters and profiled in the statistical
interpretation using log-normal priors for uncertainties affecting the signal
yield, while Gaussian priors are used for shape uncertainties.

Model-independent upper cross section times branching fraction limits are
shown as a function of the mass of the /bosons in Fig. 6 up to a mass of 1300.
The visible steps in the expected and observed limits at 500 and 1100are due
to the transitions between the mass subranges as explained in Section 0.6. The
limits range from about 20pb at 300, to about 0.4pb at 1100. The limits are
also summarized in Table .11 in Appendix .11.

Figure 6:  Expected and observed upper limits on
$\sigma(\Pp\Pp\to\PQb\PSA/\PH+\mathrm{X})\,\mathcal{B}(\PSA/\PH\to\bbbar)$ at
$95\%$ CL as a function of the Higgs boson mass $m_{\PSA/\PH}$. The inner and
the outer bands indicate the regions containing 68 and 95%, respectively, of
the distribution of limits expected under the background-only hypothesis. The
dashed horizontal lines illustrate the borders between the three subranges in
which the results have been obtained.

###  0.8.1 Interpretation within the MSSM

The cross section limits shown in Fig. 6 are translated into exclusion limits
on the MSSM parameters and $m_{\PSA}$. The cross sections for $\PQb+\PSA/\PH$
associated production as obtained with the four-flavour NLO [65, 66] and the
five-flavour NNLO QCD calculations implemented in bbh@nnlo [67] were combined
using the Santander matching scheme [68]. The branching fractions were
computed with FeynHiggs version 2.12.0 [13, 69, 70, 71] and Hdecay [72, 73] as
described in Ref. [19].

The observed and expected $95\%$ CL median upper limits on versus $m_{\PSA}$
are shown in Fig. 7 (upper row). They were computed within the MSSM
$m_{\Ph}^{\mathrm{mod+}}$ benchmark scenario [8] with the higgsino mass
parameter $\mu=+200\GeV$ and in the hMSSM scenario [15, 9, 16]. In the former
scenario, the observed upper limits range from of about 25 at
$m_{\PSA}=300\GeV$ to about 60 at $m_{\PSA}=750\GeV$. These results
considerably extend the preceding measurements at $\sqrt{s}=7$ and 8 [32, 33].
The model interpretation is not extended beyond values of 60, as theoretical
predictions are not considered reliable for much higher values. Additional
model interpretations for $m_{\PSA}$ vs. in the light $\sTau$ and the light
$\sTop$ benchmark scenarios are given in Fig. 7 (lower), and in Tables .11–.11
in Appendix .11.

Figure 7: Expected and observed upper limits at $95\%$ CL for $m_{\PSA}$ vs.
the MSSM parameter in the (upper left) $m_{\Ph}^{\mathrm{mod+}}$ benchmark
scenario with $\mu=+200\GeV$, in the (upper right) hMSSM, the (lower left)
light $\sTau$, and the (lower right) light $\sTop$ benchmark scenarios. The
inner and outer bands indicate the regions containing 68 and 95%,
respectively, of the distribution of limits expected under the background-only
hypothesis. The excluded parameter space is indicated by the red shaded area.
The hashed area is excluded because $m_{\Ph,\PH}$ would deviate by more than
$\pm 3\GeV$ from the mass of the observed Higgs boson at 125. Since
theoretical calculations for $\tanb>60$ are not reliable, no limits are set
beyond this value. To illustrate the improvement in sensitivity, the observed
and expected upper limits from the preceding CMS analyses at $\sqrt{s}=7$ and
8 [32, 33] are also shown as solid and dashed black lines.

###  0.8.2 Interpretation within the 2HDM

Cross sections and branching fractions for the and processes within different
2HDM models have been computed at NNLO using SusHi version 1.6.1 [74], 2hdmc
version 1.7.0 [75] and lhapdf version 6.1.6 [76]. The 2HDM parameters have
been set according to the “Scenario G” proposed in Ref. [77]. Specifically,
the heavier Higgs bosons are assumed to be degenerate in mass ($m_{\PSA}$ =
$m_{\PH}$ = $m_{\PHpm}$), and the mixing term has been set to
$m_{12}^{2}=0.5m_{\PSA}^{2}\sin 2\beta$. The choice of such an MSSM-like
parameterization allows using the same signal samples as for the MSSM
analysis.

The results for the type-II and flipped models are displayed in Fig. 8 as
upper limits for as a function of $\cos(\beta-\alpha)$. Observed upper limits
derived from the ATLAS $\PSA\to\PZ\Ph$ analysis [24] at a centre-of-mass
energy of 13are shown as well. The results for the flipped model presented
here provide competitive upper limits in the central region of
$\cos(\beta-\alpha)$ and strong unique constraints on . Figure 9 shows the
upper limits for as a function of $\cos(\beta-\alpha)$ in the type-II and
flipped models for $m_{\PSA/\PH}=500\GeV$.

Figure 8: Upper limits for the parameter at 95% CL for the flipped (upper) and
type-II (lower) models, as a function of $\cos(\beta-\alpha)$ in the range of
$[-0.5,0.5]$ for the mass $m_{\PH}=m_{\PSA}=300\GeV$ (left) and as a function
of $m_{\PSA/\PH}$ when $\cos(\beta-\alpha)=0.1$ (right). The observed limits
from the ATLAS $\PSA\to\PZ\Ph$ analysis [24] at 95% CL, which are provided up
to $\tanb=50$, are also shown as blue shaded area for comparison.

Figure 9: Upper limits for the parameter at 95% confidence level for the
flipped (left) and type-II (right) models as a function of
$\cos(\beta-\alpha)$ in the full range of $[-1.0,1.0]$, for the mass
$m_{\PH}=m_{\PSA}=500\GeV$. The inner and outer bands indicate the regions
containing 68 and 95%, respectively, of the distribution of limits expected
under the background-only hypothesis.

##  0.9 Summary

A search for a heavy Higgs boson decaying into a bottom quark-antiquark pair
and accompanied by at least one additional bottom quark has been performed.
The data analyzed correspond to an integrated luminosity of 35.7, recorded in
proton-proton collisions at a centre-of-mass energy of $\sqrt{s}=13\TeV$ at
the LHC. For this purpose, dedicated triggers using all-hadronic jet
signatures combined with online tagging were developed. The signal is
characterized by events with at least three b-tagged jets. The search has been
performed in the invariant mass spectrum of the two leading jets that are also
required to be b-tagged.

No evidence for a signal is found. Upper limits on the Higgs boson cross
section times branching fraction are obtained in the mass region 300–1300at
95% confidence level. They range from about 20pb at the lower end of the mass
range, to about 0.4pb at 1100, and extend to considerably higher masses than
those accessible to previous analyses in this channel.

The results are interpreted within various benchmark scenarios of the minimal
supersymmetric extension of the standard model (MSSM). They yield upper limits
on the model parameter as a function of the mass parameter $m_{\PSA}$. The
observed limit at 95% confidence level for is as low as about 25 at the lowest
$m_{\PSA}$ value of 300in the $m_{\Ph}^{\text{mod+}}$ scenario with a higgsino
mass parameter of $\mu=+200\GeV$. In the hMSSM, scenarios with values above 22
to 60 for Higgs boson masses from 300 to 900are excluded at 95% confidence
level. The results are also interpreted in the two Higgs doublet model (2HDM)
type-II and flipped scenarios. In the flipped 2HDM scenario, similar upper
limits on as for the hMSSM are set over the full $\cos(\beta-\alpha)$ range
and for Higgs boson masses from 300 to 850. The limits obtained for the
flipped scenario provide competitive upper limits in the region around zero of
$\cos(\beta-\alpha)$ and provide strong unique constraints on .

###### Acknowledgements.

The authors would like to thank Stefan Liebler and Oscar Stål for their help
with the interpretation of the results in the 2HDM models. 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 centres 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, RFBR and RAEP
(Russia); MESTD (Serbia); SEIDI, CPAN, PCTI and FEDER (Spain); Swiss Funding
Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA
(Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United
Kingdom); DOE and NSF (USA). Individuals have received support from the Marie-
Curie programme and the European Research Council and Horizon 2020 Grant,
contract No. 675440 (European Union); the Leventis Foundation; the A. P. Sloan
Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science
Policy Office; the Fonds pour la Formation à la Recherche dans l’Industrie et
dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door
Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium)
under the “Excellence of Science - EOS” - be.h project n. 30820817; the
Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the
Lendület (”Momentum”) Programme and the János Bolyai Research Scholarship of
the Hungarian Academy of Sciences, the New National Excellence Program ÚNKP,
the NKFIA research grants 123842, 123959, 124845, 124850 and 125105 (Hungary);
the Council of Science and Industrial Research, India; the HOMING PLUS
programme of the Foundation for Polish Science, cofinanced from European
Union, Regional Development Fund, the Mobility Plus programme of the Ministry
of Science and Higher Education, the National Science Center (Poland),
contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543,
2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406;
the National Priorities Research Program by Qatar National Research Fund; the
Programa Estatal de Fomento de la Investigación Científica y Técnica de
Excelencia María de Maeztu, grant MDM-2015-0509 and the Programa Severo Ochoa
del Principado de Asturias; the Thalis and Aristeia programmes cofinanced by
EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral
Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its
2nd Century Project Advancement Project (Thailand); the Welch Foundation,
contract C-1845; and the Weston Havens Foundation (USA).

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##  .10 Definition of Bukin function

The Bukin function as implemented in ROOT version 6.06/01 [78] is defined as:

$\displaystyle f(M_{12})$ $\displaystyle=A_{p}\exp\left[-\ln
2\frac{\ln^{2}\left(1+\sqrt{2}\xi\sqrt{\xi^{2}+1}\frac{(M_{12}-x_{p})}{\sqrt{\ln
2}\sigma_{p}}\right)}{\ln^{2}\left(1+2\xi(\xi-\sqrt{\xi^{2}+1})\right)}\right],$
if $x_{1}<M_{12}<x_{2}$, (5) $\displaystyle f(M_{12})$
$\displaystyle=A_{p}\exp\left[\pm\frac{\xi\sqrt{\xi^{2}+1}(M_{12}-x_{i})\sqrt{2\ln
2}}{\sigma_{p}\ln(\sqrt{\xi^{2}+1}+\xi)\left(\sqrt{\xi^{2}+1}\mp\xi\right)^{2}}+\rho_{i}\left(\frac{M_{12}-x_{i}}{x_{p}-x_{i}}\right)^{2}-\ln
2\right],$ $\displaystyle\text{ if $M_{12}\leq x_{1}$ or $M_{12}\geq x_{2}$},$
(6)

where $\rho_{i}=\rho_{1}$ and $x_{i}=x_{1}$ for $M_{12}\leq x_{1}$,
$\rho_{i}=\rho_{2}$ and $x_{i}=x_{2}$ when $M_{12}\geq x_{2}$, and:

$x_{1,2}=x_{p}+\sigma_{p}\sqrt{2\ln 2}\left(\frac{\xi}{\sqrt{\xi+1}}\mp
1\right).$ (7)

The parameters $x_{p}$ and $\sigma_{p}$ are the peak position and width,
respectively, and $\xi$ is an asymmetry parameter.

##  .11 Exclusion limits

The model-independent 95% CL limits on
$\sigma(\Pp\Pp\to\PQb\PSA/\PH+\mathrm{X})\,\mathcal{B}(\PSA/\PH\to\bbbar)$ are
listed in Table .11 for different Higgs boson masses $m_{\PSA/\PH}$. The 95%
CL limits of $(\tanb,m_{\PSA})$ are listed in Tables .11 to .11 for different
MSSM benchmark scenarios.

Expected and observed 95% CL upper limits on
$\sigma(\Pp\Pp\to\PQb\PSA/\PH+\mathrm{X})\,\mathcal{B}(\PSA/\PH\to\bbbar)$ in
pb as a function of $m_{\PSA/\PH}$.  Mass [GeV] $-2\sigma$ $-1\sigma$ Median
$+1\sigma$ $+2\sigma$ Observed 300 10.8 14.3 19.7 27.5 36.5 19.1 350 6.3 8.4
11.7 16.3 21.7 14.0 400 3.6 4.8 6.7 9.2 12.3 5.7 500 1.7 2.2 3.1 4.4 5.9 1.9
600 1.0 1.4 1.9 2.7 3.7 2.1 700 0.7 0.9 1.3 1.8 2.4 1.5 900 0.4 0.6 0.8 1.2
1.6 0.9 1100 0.36 0.49 0.68 0.96 1.36 0.40 1300 0.36 0.48 0.68 0.96 1.31 0.50

Expected and observed 95% CL upper limits on as a function of $m_{\PSA}$ in
the $m_{\Ph}^{\text{mod+}}$, $\mu=+200\GeV$, benchmark scenario. Since
theoretical predictions for $\tanb>60$ are not reliable, entries for which
would exceed this value are indicated by —.  Mass [GeV] $-2\sigma$ $-1\sigma$
Median $+1\sigma$ $+2\sigma$ Observed 300 19.3 22.0 25.8 30.6 35.7 25.4 350
21.5 24.4 28.5 33.6 39.0 31.2 400 22.6 25.5 29.4 34.4 39.7 27.3 500 26.9 30.2
34.9 40.9 47.4 28.3 600 32.9 37.1 43.0 50.6 58.5 44.5 700 39.0 44.2 51.7 — —
55.9 900 58.5 — — — — —

Expected and observed 95% CL upper limits on as a function of $m_{\PSA}$ in
the hMSSM benchmark scenario. Since theoretical predictions for $\tanb>60$ are
not reliable, entries for which would exceed this value are indicated by —.
Mass [GeV] $-2\sigma$ $-1\sigma$ Median $+1\sigma$ $+2\sigma$ Observed 300
16.8 19.3 22.6 26.7 30.9 22.3 350 17.5 20.2 23.8 28.2 32.5 26.1 400 17.6 20.3
23.8 28.1 32.4 21.9 500 19.6 22.6 26.7 31.6 36.9 20.9 600 23.6 27.2 32.1 38.0
44.3 33.2 700 27.9 32.2 38.0 45.1 52.4 41.2 900 42.8 49.4 58.4 — — —

Expected and observed 95% CL upper limits on as a function of $m_{\PSA}$ in
the light $\sTau$ benchmark scenario. Since theoretical predictions for
$\tanb>60$ are not reliable, entries for which would exceed this value are
indicated by —.  Mass [GeV] $-2\sigma$ $-1\sigma$ Median $+1\sigma$ $+2\sigma$
Observed 300 19.9 23.6 28.8 35.8 43.7 28.2 350 21.0 25.0 30.8 38.4 47.5 34.7
400 21.7 25.5 31.2 38.8 47.9 28.0 500 25.0 29.8 37.2 47.8 — 27.0 600 31.5 38.0
48.5 — — 51.5 700 40.0 48.8 — — — —

Expected and observed 95% CL upper limits on as a function of $m_{\PSA}$ in
the light $\sTop$ benchmark scenario. Since theoretical predictions for
$\tanb>60$ are not reliable, entries for which would exceed this value are
indicated by —.  Mass [GeV] $-2\sigma$ $-1\sigma$ Median $+1\sigma$ $+2\sigma$
Observed 300 22.2 26.9 34.6 46.3 — 33.6 350 23.6 28.9 37.6 52.3 — 44.5 400
23.8 29.3 37.9 51.9 — 32.9 500 27.9 34.8 47.4 — — 30.7 600 37.4 49.0 — — — —

##  .12 The CMS Collaboration

Yerevan Physics Institute, Yerevan, Armenia
A.M. Sirunyan, A. Tumasyan Institut für Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, E. Brondolin, M.
Dragicevic, J. Erö, A. Escalante Del Valle, M. Flechl, R. Frühwirth1, V.M.
Ghete, J. Hrubec, M. Jeitler1, N. Krammer, I. Krätschmer, D. Liko, T.
Madlener, I. Mikulec, N. Rad, H. Rohringer, J. Schieck1, R. Schöfbeck, M.
Spanring, D. Spitzbart, A. Taurok, W. Waltenberger, J. Wittmann, C.-E. Wulz1,
M. Zarucki Institute for Nuclear Problems, Minsk, Belarus
V. Chekhovsky, V. Mossolov, J. Suarez Gonzalez Universiteit Antwerpen,
Antwerpen, Belgium
E.A. De Wolf, D. Di Croce, X. Janssen, J. Lauwers, M. Pieters, M. Van De
Klundert, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel Vrije
Universiteit Brussel, Brussel, Belgium
S. Abu Zeid, F. Blekman, J. D’Hondt, I. De Bruyn, J. De Clercq, K. Deroover,
G. Flouris, D. Lontkovskyi, S. Lowette, I. Marchesini, S. Moortgat, L.
Moreels, Q. Python, K. Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders,
I. Van Parijs Université Libre de Bruxelles, Bruxelles, Belgium
D. Beghin, B. Bilin, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, B.
Dorney, G. Fasanella, L. Favart, R. Goldouzian, A. Grebenyuk, A.K. Kalsi, T.
Lenzi, J. Luetic, N. Postiau, E. Starling, L. Thomas, C. Vander Velde, P.
Vanlaer, D. Vannerom, Q. Wang Ghent University, Ghent, Belgium
T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov2, D. Poyraz, C. Roskas,
D. Trocino, M. Tytgat, W. Verbeke, B. Vermassen, M. Vit, N. Zaganidis
Université Catholique de Louvain, Louvain-la-Neuve, Belgium
H. Bakhshiansohi, O. Bondu, S. Brochet, G. Bruno, C. Caputo, P. David, C.
Delaere, M. Delcourt, B. Francois, A. Giammanco, G. Krintiras, V. Lemaitre, A.
Magitteri, A. Mertens, M. Musich, K. Piotrzkowski, A. Saggio, M. Vidal Marono,
S. Wertz, J. Zobec Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro,
Brazil
F.L. Alves, G.A. Alves, L. Brito, G. Correia Silva, C. Hensel, A. Moraes, M.E.
Pol, P. Rebello Teles Universidade do Estado do Rio de Janeiro, Rio de
Janeiro, Brazil
E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato3, E. Coelho, E.M.
Da Costa, G.G. Da Silveira4, D. De Jesus Damiao, C. De Oliveira Martins, S.
Fonseca De Souza, H. Malbouisson, D. Matos Figueiredo, M. Melo De Almeida, C.
Mora Herrera, L. Mundim, H. Nogima, W.L. Prado Da Silva, L.J. Sanchez Rosas,
A. Santoro, A. Sznajder, M. Thiel, E.J. Tonelli Manganote3, F. Torres Da Silva
De Araujo, A. Vilela Pereira Universidade Estadual Paulista a, Universidade
Federal do ABC b, São Paulo, Brazil
S. Ahujaa, C.A. Bernardesa, L. Calligarisa, T.R. Fernandez Perez Tomeia, E.M.
Gregoresb, P.G. Mercadanteb, S.F. Novaesa, SandraS. Padulaa, D. Romero Abadb
Institute for Nuclear Research and Nuclear Energy, Bulgarian Academy of
Sciences, Sofia, Bulgaria
A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, A. Marinov, M. Misheva, M. Rodozov,
M. Shopova, G. Sultanov University of Sofia, Sofia, Bulgaria
A. Dimitrov, L. Litov, B. Pavlov, P. Petkov Beihang University, Beijing, China
W. Fang5, X. Gao5, L. Yuan Institute of High Energy Physics, Beijing, China
M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D.
Leggat, H. Liao, Z. Liu, F. Romeo, S.M. Shaheen, A. Spiezia, J. Tao, C. Wang,
Z. Wang, E. Yazgan, H. Zhang, J. Zhao State Key Laboratory of Nuclear Physics
and Technology, Peking University, Beijing, China
Y. Ban, G. Chen, J. Li, Q. Li, Y. Mao, S.J. Qian, D. Wang, Z. Xu Tsinghua
University, Beijing, China
Y. Wang Universidad de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, C.A. Carrillo Montoya, L.F. Chaparro Sierra, C. Florez,
C.F. González Hernández, M.A. Segura Delgado University of Split, Faculty of
Electrical Engineering, Mechanical Engineering and Naval Architecture, Split,
Croatia
B. Courbon, N. Godinovic, D. Lelas, I. Puljak, T. Sculac University of Split,
Faculty of Science, Split, Croatia
Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia
V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, A. Starodumov6, T. Susa
University of Cyprus, Nicosia, Cyprus
M.W. Ather, A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos,
P.A. Razis, H. Rykaczewski Charles University, Prague, Czech Republic
M. Finger7, M. Finger Jr.7 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. Abdalla8, A.A. Abdelalim9,10, S. Khalil10 National Institute of Chemical
Physics and Biophysics, Tallinn, Estonia
S. Bhowmik, A. Carvalho Antunes De Oliveira, R.K. Dewanjee, K. Ehataht, M.
Kadastik, L. Perrini, M. Raidal, C. Veelken Department of Physics, University
of Helsinki, Helsinki, Finland
P. Eerola, H. Kirschenmann, J. Pekkanen, M. Voutilainen Helsinki Institute of
Physics, Helsinki, Finland
J. Havukainen, J.K. Heikkilä, T. Järvinen, V. Karimäki, R. Kinnunen, T.
Lampén, K. Lassila-Perini, S. Laurila, S. Lehti, T. Lindén, P. Luukka, T.
Mäenpää, H. Siikonen, E. Tuominen, J. Tuominiemi Lappeenranta University of
Technology, Lappeenranta, Finland
T. Tuuva IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
M. Besancon, F. Couderc, M. Dejardin, D. Denegri, J.L. Faure, F. Ferri, S.
Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, C. Leloup,
E. Locci, J. Malcles, G. Negro, J. Rander, A. Rosowsky, M.Ö. Sahin, M. Titov
Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Université
Paris-Saclay, Palaiseau, France
A. Abdulsalam11, C. Amendola, I. Antropov, F. Beaudette, P. Busson, C.
Charlot, R. Granier de Cassagnac, I. Kucher, S. Lisniak, A. Lobanov, J. Martin
Blanco, M. Nguyen, C. Ochando, G. Ortona, P. Pigard, R. Salerno, J.B. Sauvan,
Y. Sirois, A.G. Stahl Leiton, A. Zabi, A. Zghiche Université de Strasbourg,
CNRS, IPHC UMR 7178, F-67000 Strasbourg, France
J.-L. Agram12, J. Andrea, D. Bloch, J.-M. Brom, E.C. Chabert, V. Cherepanov,
C. Collard, E. Conte12, J.-C. Fontaine12, D. Gelé, U. Goerlach, M. Jansová,
A.-C. Le Bihan, N. Tonon, P. Van Hove Centre de Calcul de l’Institut National
de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne,
France
S. Gadrat Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3,
Institut de Physique Nucléaire de Lyon, Villeurbanne, France
S. Beauceron, C. Bernet, G. Boudoul, N. Chanon, R. Chierici, D. Contardo, P.
Depasse, H. El Mamouni, J. Fay, L. Finco, S. Gascon, M. Gouzevitch, G.
Grenier, B. Ille, F. Lagarde, I.B. Laktineh, H. Lattaud, M. Lethuillier, L.
Mirabito, A.L. Pequegnot, S. Perries, A. Popov13, V. Sordini, M. Vander
Donckt, S. Viret, S. Zhang Georgian Technical University, Tbilisi, Georgia
A. Khvedelidze7 Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze7 RWTH Aachen University, I. Physikalisches Institut, Aachen,
Germany
C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, M.P.
Rauch, C. Schomakers, J. Schulz, M. Teroerde, B. Wittmer, V. Zhukov13 RWTH
Aachen University, III. Physikalisches Institut A, Aachen, Germany
A. Albert, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg, T. Esch, R. Fischer,
S. Ghosh, A. Güth, T. Hebbeker, C. Heidemann, K. Hoepfner, S. Knutzen, L.
Mastrolorenzo, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, T. Pook, M.
Radziej, H. Reithler, M. Rieger, F. Scheuch, A. Schmidt, D. Teyssier, S. Thüer
RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany
G. Flügge, O. Hlushchenko, B. Kargoll, T. Kress, A. Künsken, T. Müller, A.
Nehrkorn, A. Nowack, C. Pistone, O. Pooth, H. Sert, A. Stahl14 Deutsches
Elektronen-Synchrotron, Hamburg, Germany
M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, I. Babounikau, K.
Beernaert, O. Behnke, U. Behrens, A. Bermúdez Martínez, D. Bertsche, A.A. Bin
Anuar, K. Borras15, V. Botta, A. Campbell, P. Connor, C. Contreras-Campana, F.
Costanza, V. Danilov, A. De Wit, M.M. Defranchis, C. Diez Pardos, D. Domínguez
Damiani, G. Eckerlin, T. Eichhorn, A. Elwood, E. Eren, E. Gallo16, A. Geiser,
J.M. Grados Luyando, A. Grohsjean, P. Gunnellini, M. Guthoff, A. Harb, J.
Hauk, H. Jung, M. Kasemann, J. Keaveney, C. Kleinwort, J. Knolle, D. Krücker,
W. Lange, A. Lelek, T. Lenz, K. Lipka, W. Lohmann17, R. Mankel, I.-A. Melzer-
Pellmann, A.B. Meyer, M. Meyer, M. Missiroli, G. Mittag, J. Mnich, V.
Myronenko, S.K. Pflitsch, D. Pitzl, A. Raspereza, M. Savitskyi, P. Saxena, P.
Schütze, C. Schwanenberger, R. Shevchenko, A. Singh, N. Stefaniuk, H. Tholen,
A. Vagnerini, G.P. Van Onsem, R. Walsh, Y. Wen, K. Wichmann, C. Wissing, O.
Zenaiev University of Hamburg, Hamburg, Germany
R. Aggleton, S. Bein, A. Benecke, V. Blobel, M. Centis Vignali, T. Dreyer, E.
Garutti, D. Gonzalez, J. Haller, A. Hinzmann, M. Hoffmann, A. Karavdina, G.
Kasieczka, R. Klanner, R. Kogler, N. Kovalchuk, S. Kurz, V. Kutzner, J. Lange,
D. Marconi, J. Multhaup, M. Niedziela, D. Nowatschin, A. Perieanu, A. Reimers,
O. Rieger, C. Scharf, P. Schleper, S. Schumann, J. Schwandt, J. Sonneveld, H.
Stadie, G. Steinbrück, F.M. Stober, M. Stöver, D. Troendle, E. Usai, A.
Vanhoefer, B. Vormwald Karlsruher Institut fuer Technology
M. Akbiyik, C. Barth, M. Baselga, S. Baur, E. Butz, R. Caspart, T. Chwalek, F.
Colombo, W. De Boer, A. Dierlamm, N. Faltermann, B. Freund, M. Giffels, M.A.
Harrendorf, F. Hartmann14, S.M. Heindl, U. Husemann, F. Kassel14, I. Katkov13,
S. Kudella, H. Mildner, S. Mitra, M.U. Mozer, Th. Müller, M. Plagge, G. Quast,
K. Rabbertz, M. Schröder, I. Shvetsov, G. Sieber, H.J. Simonis, R. Ulrich, S.
Wayand, M. Weber, T. Weiler, S. Williamson, C. Wöhrmann, R. Wolf Institute of
Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece
G. Anagnostou, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas, G.
Paspalaki, I. Topsis-Giotis National and Kapodistrian University of Athens,
Athens, Greece
G. Karathanasis, S. Kesisoglou, P. Kontaxakis, A. Panagiotou, N. Saoulidou, E.
Tziaferi, K. Vellidis National Technical University of Athens, Athens, Greece
K. Kousouris, I. Papakrivopoulos, G. Tsipolitis University of Ioánnina,
Ioánnina, Greece
I. Evangelou, C. Foudas, P. Gianneios, P. Katsoulis, P. Kokkas, S. Mallios, N.
Manthos, I. Papadopoulos, E. Paradas, J. Strologas, F.A. Triantis, D.
Tsitsonis MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
M. Csanad, N. Filipovic, P. Major, M.I. Nagy, G. Pasztor, O. Surányi, G.I.
Veres Wigner Research Centre for Physics, Budapest, Hungary
G. Bencze, C. Hajdu, D. Horvath18, 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. Karancsi20, A. Makovec, J. Molnar, Z. Szillasi
Institute of Physics, University of Debrecen, Debrecen, Hungary
M. Bartók19, P. Raics, Z.L. Trocsanyi, B. Ujvari Indian Institute of Science
(IISc), Bangalore, India
S. Choudhury, J.R. Komaragiri National Institute of Science Education and
Research, HBNI, Bhubaneswar, India
S. Bahinipati21, P. Mal, K. Mandal, A. Nayak22, D.K. Sahoo21, S.K. Swain
Panjab University, Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, S. Chauhan, R. Chawla, N. Dhingra, R.
Gupta, A. Kaur, A. Kaur, M. Kaur, S. Kaur, R. Kumar, P. Kumari, M. Lohan, A.
Mehta, S. Sharma, J.B. Singh, G. Walia University of Delhi, Delhi, India
A. Bhardwaj, B.C. Choudhary, R.B. Garg, M. Gola, S. Keshri, Ashok Kumar, S.
Malhotra, M. Naimuddin, P. Priyanka, K. Ranjan, Aashaq Shah, R. Sharma Saha
Institute of Nuclear Physics, HBNI, Kolkata, India
R. Bhardwaj23, M. Bharti, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep23,
D. Bhowmik, S. Dey, S. Dutt23, S. Dutta, S. Ghosh, K. Mondal, S. Nandan, A.
Purohit, P.K. Rout, A. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, B. Singh,
S. Thakur23 Indian Institute of Technology Madras, Madras, India
P.K. Behera Bhabha Atomic Research Centre, Mumbai, India
R. Chudasama, D. Dutta, V. Jha, V. Kumar, P.K. Netrakanti, L.M. Pant, P.
Shukla Tata Institute of Fundamental Research-A, Mumbai, India
T. Aziz, M.A. Bhat, S. Dugad, B. Mahakud, G.B. Mohanty, N. Sur, B. Sutar,
RavindraKumar Verma Tata Institute of Fundamental Research-B, Mumbai, India
S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, Sa. Jain, S.
Kumar, M. Maity24, G. Majumder, K. Mazumdar, N. Sahoo, T. Sarkar24 Indian
Institute of Science Education and Research (IISER), Pune, India
S. Chauhan, S. Dube, V. Hegde, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, S.
Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
S. Chenarani25, E. Eskandari Tadavani, S.M. Etesami25, M. Khakzad, M.
Mohammadi Najafabadi, M. Naseri, F. Rezaei Hosseinabadi, B. Safarzadeh26, M.
Zeinali University College Dublin, Dublin, Ireland
M. Felcini, M. Grunewald INFN Sezione di Bari a, Università di Bari b,
Politecnico di Bari c, Bari, Italy
M. Abbresciaa,b, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L. Cristellaa,b,
N. De Filippisa,c, M. De Palmaa,b, A. Di Florioa,b, F. Erricoa,b, L. Fiorea,
A. Gelmia,b, G. Iasellia,c, S. Lezkia,b, G. Maggia,c, M. Maggia, G.
Minielloa,b, S. Mya,b, S. Nuzzoa,b, A. Pompilia,b, G. Pugliesea,c, R.
Radognaa, A. Ranieria, G. Selvaggia,b, A. Sharmaa, L. Silvestrisa,14, R.
Vendittia, P. Verwilligena, G. Zitoa INFN Sezione di Bologna a, Università di
Bologna b, Bologna, Italy
G. Abbiendia, C. Battilanaa,b, D. Bonacorsia,b, L. Borgonovia,b, S. Braibant-
Giacomellia,b, L. Brigliadoria,b, R. Campaninia,b, P. Capiluppia,b, A.
Castroa,b, F.R. Cavalloa, S.S. Chhibraa,b, G. Codispotia,b, M. Cuffiania,b,
G.M. Dallavallea, F. Fabbria, A. Fanfania,b, P. Giacomellia, C. Grandia, L.
Guiduccia,b, S. Marcellinia, G. Masettia, A. Montanaria, F.L. Navarriaa,b, A.
Perrottaa, A.M. Rossia,b, T. Rovellia,b, G.P. Sirolia,b, N. Tosia INFN Sezione
di Catania a, Università di Catania b, Catania, Italy
S. Albergoa,b, A. Di Mattiaa, R. Potenzaa,b, A. Tricomia,b, C. Tuvea,b INFN
Sezione di Firenze a, Università di Firenze b, Firenze, Italy
G. Barbaglia, K. Chatterjeea,b, V. Ciullia,b, C. Civininia, R.
D’Alessandroa,b, E. Focardia,b, G. Latino, P. Lenzia,b, M. Meschinia, S.
Paolettia, L. Russoa,27, G. Sguazzonia, D. Stroma, L. Viliania INFN Laboratori
Nazionali di Frascati, Frascati, Italy
L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera14 INFN Sezione di
Genova a, Università di Genova b, Genova, Italy
F. Ferroa, F. Raveraa,b, E. Robuttia, S. Tosia,b INFN Sezione di Milano-
Bicocca a, Università di Milano-Bicocca b, Milano, Italy
A. Benagliaa, A. Beschib, L. Brianzaa,b, F. Brivioa,b, V. Cirioloa,b,14, S. Di
Guidaa,d,14, M.E. Dinardoa,b, S. Fiorendia,b, S. Gennaia, A. Ghezzia,b, P.
Govonia,b, M. Malbertia,b, S. Malvezzia, R.A. Manzonia,b, A. Massironia,b, D.
Menascea, L. Moronia, M. Paganonia,b, D. Pedrinia, S. Ragazzia,b, T. Tabarelli
de Fatisa,b INFN Sezione di Napoli a, Università di Napoli ’Federico II’ b,
Napoli, Italy, Università della Basilicata c, Potenza, Italy, Università G.
Marconi d, Roma, Italy
S. Buontempoa, N. Cavalloa,c, A. Di Crescenzoa,b, F. Fabozzia,c, F. Fiengaa,b,
G. Galatia,b, A.O.M. Iorioa,b, W.A. Khana, L. Listaa, S. Meolaa,d,14, P.
Paoluccia,14, 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, M. Bellatoa, L. Benatoa,b, 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, U. Gasparinia,b, A. Gozzelinoa, S.
Lacapraraa, P. Lujan, M. Margonia,b, A.T. Meneguzzoa,b, N. Pozzobona,b, P.
Ronchesea,b, R. Rossina,b, F. Simonettoa,b, A. Tiko, E. Torassaa, M.
Zanettia,b, P. Zottoa,b INFN Sezione di Pavia a, Università di Pavia b, Pavia,
Italy
A. Braghieria, A. Magnania, P. Montagnaa,b, S.P. Rattia,b, V. Rea, M.
Ressegottia,b, C. Riccardia,b, P. Salvinia, I. Vaia,b, P. Vituloa,b INFN
Sezione di Perugia a, Università di Perugia b, Perugia, Italy
L. Alunni Solestizia,b, M. Biasinia,b, G.M. Bileia, C. Cecchia,b, D.
Ciangottinia,b, L. Fanòa,b, P. Laricciaa,b, E. Manonia, G. Mantovania,b, V.
Mariania,b, M. Menichellia, A. Rossia,b, A. Santocchiaa,b, D. Spigaa INFN
Sezione di Pisa a, Università di Pisa b, Scuola Normale Superiore di Pisa c,
Pisa, Italy
K. Androsova, P. Azzurria, G. Bagliesia, L. Bianchinia, T. Boccalia, L.
Borrello, R. Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, G. Fedia, L.
Gianninia,c, A. Giassia, M.T. Grippoa, F. Ligabuea,c, E. Mancaa,c, G.
Mandorlia,c, A. Messineoa,b, F. Pallaa, A. Rizzia,b, P. Spagnoloa, R.
Tenchinia, G. Tonellia,b, A. Venturia, P.G. Verdinia INFN Sezione di Roma a,
Sapienza Università di Roma b, Rome, Italy
L. Baronea,b, F. Cavallaria, M. Cipriania,b, N. Dacia, D. Del Rea,b, E. Di
Marcoa,b, M. Diemoza, S. Gellia,b, E. Longoa,b, B. Marzocchia,b, P.
Meridiania, G. Organtinia,b, F. Pandolfia, R. Paramattia,b, F. Preiatoa,b, S.
Rahatloua,b, C. Rovellia, F. Santanastasioa,b INFN Sezione di Torino a,
Università di Torino b, Torino, Italy, Università del Piemonte Orientale c,
Novara, Italy
N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, N. Bartosika,
R. Bellana,b, C. Biinoa, N. Cartigliaa, F. Cennaa,b, M. Costaa,b, R.
Covarellia,b, N. Demariaa, B. Kiania,b, C. Mariottia, S. Masellia, E.
Migliorea,b, V. Monacoa,b, E. Monteila,b, M. Montenoa, M.M. Obertinoa,b, L.
Pachera,b, N. Pastronea, M. Pelliccionia, G.L. Pinna Angionia,b, A. Romeroa,b,
M. Ruspaa,c, R. Sacchia,b, K. Shchelinaa,b, V. Solaa, A. Solanoa,b, A.
Staianoa INFN Sezione di Trieste a, Università di Trieste b, Trieste, Italy
S. Belfortea, V. Candelisea,b, M. Casarsaa, F. Cossuttia, G. Della Riccaa,b,
F. Vazzolera,b, A. Zanettia Kyungpook National University
D.H. Kim, G.N. Kim, M.S. Kim, J. Lee, S. Lee, S.W. Lee, C.S. Moon, Y.D. Oh, S.
Sekmen, D.C. Son, Y.C. Yang Chonnam National University, Institute for
Universe and Elementary Particles, Kwangju, Korea
H. Kim, D.H. Moon, G. Oh Hanyang University, Seoul, Korea
J. Goh, T.J. Kim Korea University, Seoul, Korea
S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, K. Lee, K.S. Lee, S.
Lee, J. Lim, S.K. Park, Y. Roh Sejong University, Seoul, Korea
H. Kim Seoul National University, Seoul, Korea
J. Almond, J. Kim, J.S. Kim, H. Lee, K. Lee, K. Nam, S.B. Oh, B.C. Radburn-
Smith, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu University of Seoul, Seoul,
Korea
H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park Sungkyunkwan University, Suwon, Korea
Y. Choi, C. Hwang, J. Lee, I. Yu Vilnius University, Vilnius, Lithuania
V. Dudenas, A. Juodagalvis, J. Vaitkus National Centre for Particle Physics,
Universiti Malaya, Kuala Lumpur, Malaysia
I. Ahmed, Z.A. Ibrahim, M.A.B. Md Ali28, F. Mohamad Idris29, W.A.T. Wan
Abdullah, M.N. Yusli, Z. Zolkapli Centro de Investigacion y de Estudios
Avanzados del IPN, Mexico City, Mexico
M.C. Duran-Osuna, H. Castilla-Valdez, E. De La Cruz-Burelo, G. Ramirez-
Sanchez, I. Heredia-De La Cruz30, R.I. Rabadan-Trejo, R. Lopez-Fernandez, J.
Mejia Guisao, R Reyes-Almanza, A. Sanchez-Hernandez Universidad
Iberoamericana, Mexico City, Mexico
S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita
Universidad Autonoma de Puebla, Puebla, Mexico
J. Eysermans, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad
Autónoma de San Luis Potosí, San Luis Potosí, Mexico
A. Morelos Pineda University of Auckland, Auckland, New Zealand
D. Krofcheck University of Canterbury, Christchurch, New Zealand
S. Bheesette, P.H. Butler National Centre for Physics, Quaid-I-Azam
University, Islamabad, Pakistan
A. Ahmad, M. Ahmad, M.I. Asghar, Q. Hassan, H.R. Hoorani, A. Saddique, M.A.
Shah, M. Shoaib, M. Waqas National Centre for Nuclear Research, Swierk, Poland
H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Górski, M. Kazana, K.
Nawrocki, M. Szleper, P. Traczyk, P. Zalewski Institute of Experimental
Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland
K. Bunkowski, A. Byszuk31, K. Doroba, A. Kalinowski, M. Konecki, J.
Krolikowski, M. Misiura, M. Olszewski, A. Pyskir, M. Walczak Laboratório de
Instrumentação e Física Experimental de Partículas, Lisboa, Portugal
P. Bargassa, C. Beirão Da Cruz E Silva, A. Di Francesco, P. Faccioli, B.
Galinhas, M. Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias, M.V.
Nemallapudi, J. Seixas, G. Strong, O. Toldaiev, D. Vadruccio, J. Varela Joint
Institute for Nuclear Research, Dubna, Russia
V. Alexakhin, A. Golunov, I. Golutvin, N. Gorbounov, I. Gorbunov, A. Kamenev,
V. Karjavin, A. Lanev, A. Malakhov, V. Matveev32,33, P. Moisenz, V. Palichik,
V. Perelygin, M. Savina, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, A.
Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg),
Russia
V. Golovtsov, Y. Ivanov, V. Kim34, E. Kuznetsova35, P. Levchenko, V. Murzin,
V. Oreshkin, I. Smirnov, D. Sosnov, V. Sulimov, L. Uvarov, S. Vavilov, A.
Vorobyev Institute for Nuclear Research, Moscow, Russia
Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov,
N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical
and Experimental Physics, Moscow, Russia
V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G.
Safronov, A. Spiridonov, A. Stepennov, V. Stolin, M. Toms, E. Vlasov, A.
Zhokin Moscow Institute of Physics and Technology, Moscow, Russia
T. Aushev, A. Bylinkin33 National Research Nuclear University ’Moscow
Engineering Physics Institute’ (MEPhI), Moscow, Russia
R. Chistov36, M. Danilov36, P. Parygin, D. Philippov, S. Polikarpov36, E.
Tarkovskii P.N. Lebedev Physical Institute, Moscow, Russia
V. Andreev, M. Azarkin33, I. Dremin33, M. Kirakosyan33, S.V. Rusakov, A.
Terkulov Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State
University, Moscow, Russia
A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin37, L. Dudko, V.
Klyukhin, O. Kodolova, I. Lokhtin, I. Miagkov, S. Obraztsov, M. Perfilov, S.
Petrushanko, V. Savrin, A. Snigirev Novosibirsk State University (NSU),
Novosibirsk, Russia
V. Blinov38, T. Dimova38, L. Kardapoltsev38, D. Shtol38, Y. Skovpen38 State
Research Center of Russian Federation, Institute for High Energy Physics of
NRC ’Kurchatov Institute’, Protvino, Russia
I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, A. Godizov, V. Kachanov,
A. Kalinin, D. Konstantinov, P. Mandrik, V. Petrov, R. Ryutin, S.
Slabospitskii, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov National
Research Tomsk Polytechnic University, Tomsk, Russia
A. Babaev University of Belgrade, Faculty of Physics and Vinca Institute of
Nuclear Sciences, Belgrade, Serbia
P. Adzic39, P. Cirkovic, D. Devetak, M. Dordevic, J. Milosevic Centro de
Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid,
Spain
J. Alcaraz Maestre, A. Álvarez Fernández, I. Bachiller, M. Barrio Luna, J.A.
Brochero Cifuentes, M. Cerrada, N. Colino, B. De La Cruz, A. Delgado Peris, C.
Fernandez Bedoya, J.P. Fernández Ramos, J. Flix, M.C. Fouz, O. Gonzalez Lopez,
S. Goy Lopez, J.M. Hernandez, M.I. Josa, D. Moran, A. Pérez-Calero Yzquierdo,
J. Puerta Pelayo, I. Redondo, L. Romero, M.S. Soares, A. Triossi Universidad
Autónoma de Madrid, Madrid, Spain
C. Albajar, J.F. de Trocóniz Universidad de Oviedo, Oviedo, Spain
J. Cuevas, C. Erice, J. Fernandez Menendez, S. Folgueras, I. Gonzalez
Caballero, J.R. González Fernández, E. Palencia Cortezon, V. Rodríguez Bouza,
S. Sanchez Cruz, P. Vischia, J.M. Vizan Garcia Instituto de Física de
Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain
I.J. Cabrillo, A. Calderon, B. Chazin Quero, J. Duarte Campderros, M.
Fernandez, P.J. Fernández Manteca, A. García Alonso, J. Garcia-Ferrero, G.
Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, P. Martinez Ruiz del
Arbol, F. Matorras, J. Piedra Gomez, C. Prieels, T. Rodrigo, A. Ruiz-Jimeno,
L. Scodellaro, N. Trevisani, I. Vila, R. Vilar Cortabitarte CERN, European
Organization for Nuclear Research, Geneva, Switzerland
D. Abbaneo, B. Akgun, E. Auffray, P. Baillon, A.H. Ball, D. Barney, J.
Bendavid, M. Bianco, A. Bocci, C. Botta, T. Camporesi, M. Cepeda, G.
Cerminara, E. Chapon, Y. Chen, G. Cucciati, D. d’Enterria, A. Dabrowski, V.
Daponte, A. David, A. De Roeck, N. Deelen, M. Dobson, T. du Pree, M. Dünser,
N. Dupont, A. Elliott-Peisert, P. Everaerts, F. Fallavollita40, D. Fasanella,
G. Franzoni, J. Fulcher, W. Funk, D. Gigi, A. Gilbert, K. Gill, F. Glege, D.
Gulhan, J. Hegeman, V. Innocente, A. Jafari, P. Janot, O. Karacheban17, J.
Kieseler, V. Knünz, A. Kornmayer, M. Krammer1, C. Lange, P. Lecoq, C.
Lourenço, M.T. Lucchini, L. Malgeri, M. Mannelli, F. Meijers, J.A. Merlin, S.
Mersi, E. Meschi, P. Milenovic41, F. Moortgat, M. Mulders, H. Neugebauer, J.
Ngadiuba, S. Orfanelli, L. Orsini, F. Pantaleo14, L. Pape, E. Perez, M.
Peruzzi, A. Petrilli, G. Petrucciani, A. Pfeiffer, M. Pierini, F.M. Pitters,
D. Rabady, A. Racz, T. Reis, G. Rolandi42, M. Rovere, H. Sakulin, C. Schäfer,
C. Schwick, M. Seidel, M. Selvaggi, A. Sharma, P. Silva, P. Sphicas43, A.
Stakia, J. Steggemann, M. Tosi, D. Treille, A. Tsirou, V. Veckalns44, M.
Verweij, W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland
W. Bertl${}^{\textrm{\textdagger}}$, L. Caminada45, K. Deiters, W. Erdmann, R.
Horisberger, Q. Ingram, H.C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe,
S.A. Wiederkehr ETH Zurich - Institute for Particle Physics and Astrophysics
(IPA), Zurich, Switzerland
M. Backhaus, L. Bäni, P. Berger, B. Casal, N. Chernyavskaya, G. Dissertori, M.
Dittmar, M. Donegà, C. Dorfer, C. Grab, C. Heidegger, D. Hits, J. Hoss, T.
Klijnsma, W. Lustermann, M. Marionneau, M.T. Meinhard, D. Meister, F. Micheli,
P. Musella, F. Nessi-Tedaldi, J. Pata, F. Pauss, G. Perrin, L. Perrozzi, S.
Pigazzini, M. Quittnat, M. Reichmann, D. Ruini, D.A. Sanz Becerra, M.
Schönenberger, L. Shchutska, V.R. Tavolaro, K. Theofilatos, M.L. Vesterbacka
Olsson, R. Wallny, D.H. Zhu Universität Zürich, Zurich, Switzerland
T.K. Aarrestad, C. Amsler46, D. Brzhechko, M.F. Canelli, A. De Cosa, R. Del
Burgo, S. Donato, C. Galloni, T. Hreus, B. Kilminster, I. Neutelings, D.
Pinna, G. Rauco, P. Robmann, D. Salerno, K. Schweiger, C. Seitz, Y. Takahashi,
A. Zucchetta National Central University, Chung-Li, Taiwan
Y.H. Chang, K.y. Cheng, T.H. Doan, Sh. Jain, R. Khurana, C.M. Kuo, W. Lin, A.
Pozdnyakov, S.S. Yu National Taiwan University (NTU), Taipei, Taiwan
P. Chang, Y. Chao, K.F. Chen, P.H. Chen, W.-S. Hou, Arun Kumar, Y.y. Li, R.-S.
Lu, E. Paganis, A. Psallidas, A. Steen, J.f. Tsai Chulalongkorn University,
Faculty of Science, Department of Physics, Bangkok, Thailand
B. Asavapibhop, N. Srimanobhas, N. Suwonjandee Çukurova University, Physics
Department, Science and Art Faculty, Adana, Turkey
A. Bat, F. Boran, S. Cerci47, S. Damarseckin, Z.S. Demiroglu, C. Dozen, I.
Dumanoglu, S. Girgis, G. Gokbulut, Y. Guler, E. Gurpinar, I. Hos48, E.E.
Kangal49, O. Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G. Onengut, K.
Ozdemir50, S. Ozturk51, D. Sunar Cerci47, B. Tali47, U.G. Tok, S. Turkcapar,
I.S. Zorbakir, C. Zorbilmez Middle East Technical University, Physics
Department, Ankara, Turkey
B. Isildak52, G. Karapinar53, M. Yalvac, M. Zeyrek Bogazici University,
Istanbul, Turkey
I.O. Atakisi, E. Gülmez, M. Kaya54, O. Kaya55, S. Tekten, E.A. Yetkin56
Istanbul Technical University, Istanbul, Turkey
M.N. Agaras, S. Atay, A. Cakir, K. Cankocak, Y. Komurcu, S. Sen57 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
T. Alexander, F. Ball, L. Beck, J.J. Brooke, D. Burns, E. Clement, D. Cussans,
O. Davignon, H. Flacher, J. Goldstein, G.P. Heath, H.F. Heath, L. Kreczko,
D.M. Newbold58, S. Paramesvaran, B. Penning, T. Sakuma, D. Smith, V.J. Smith,
J. Taylor Rutherford Appleton Laboratory, Didcot, United Kingdom
K.W. Bell, A. Belyaev59, C. Brew, R.M. Brown, D. Cieri, D.J.A. Cockerill, J.A.
Coughlan, K. Harder, S. Harper, J. Linacre, E. Olaiya, D. Petyt, C.H.
Shepherd-Themistocleous, A. Thea, I.R. Tomalin, T. Williams, W.J. Womersley
Imperial College, London, United Kingdom
G. Auzinger, R. Bainbridge, P. Bloch, J. Borg, S. Breeze, O. Buchmuller, A.
Bundock, S. Casasso, D. Colling, L. Corpe, P. Dauncey, G. Davies, M. Della
Negra, R. Di Maria, Y. Haddad, G. Hall, G. Iles, T. James, M. Komm, C. Laner,
L. Lyons, A.-M. Magnan, S. Malik, A. Martelli, J. Nash60, A. Nikitenko6, V.
Palladino, M. Pesaresi, A. Richards, A. Rose, E. Scott, C. Seez, A.
Shtipliyski, G. Singh, M. Stoye, T. Strebler, S. Summers, A. Tapper, K.
Uchida, T. Virdee14, N. Wardle, D. Winterbottom, J. Wright, S.C. Zenz Brunel
University, Uxbridge, United Kingdom
J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, C.K. Mackay, A. Morton, I.D. Reid,
L. Teodorescu, S. Zahid Baylor University, Waco, USA
A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, C. Madrid, B.
Mcmaster, N. Pastika, C. Smith Catholic University of America, Washington DC,
USA
R. Bartek, A. Dominguez The University of Alabama, Tuscaloosa, USA
A. Buccilli, S.I. Cooper, C. Henderson, P. Rumerio, C. West Boston University,
Boston, USA
D. Arcaro, T. Bose, D. Gastler, D. Rankin, C. Richardson, J. Rohlf, L. Sulak,
D. Zou Brown University, Providence, USA
G. Benelli, X. Coubez, D. Cutts, M. Hadley, J. Hakala, U. Heintz, J.M.
Hogan61, K.H.M. Kwok, E. Laird, G. Landsberg, J. Lee, Z. Mao, M. Narain, J.
Pazzini, S. Piperov, S. Sagir62, R. Syarif, D. Yu University of California,
Davis, Davis, USA
R. Band, C. Brainerd, R. Breedon, D. Burns, M. Calderon De La Barca Sanchez,
M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk,
W. Ko, O. Kukral, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, S.
Shalhout, M. Shi, D. Stolp, D. Taylor, K. Tos, M. Tripathi, Z. Wang, F. Zhang
University of California, Los Angeles, USA
M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M.
Ignatenko, N. Mccoll, S. Regnard, D. Saltzberg, C. Schnaible, V. Valuev
University of California, Riverside, Riverside, USA
E. Bouvier, K. Burt, R. Clare, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, G.
Karapostoli, E. Kennedy, F. Lacroix, O.R. Long, M. Olmedo Negrete, M.I.
Paneva, W. Si, L. Wang, H. Wei, S. Wimpenny, B.R. Yates University of
California, San Diego, La Jolla, USA
J.G. Branson, S. Cittolin, M. Derdzinski, R. Gerosa, D. Gilbert, B. Hashemi,
A. Holzner, D. Klein, G. Kole, V. Krutelyov, J. Letts, M. Masciovecchio, D.
Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A.
Vartak, S. Wasserbaech63, J. Wood, F. Würthwein, A. Yagil, G. Zevi Della Porta
University of California, Santa Barbara - Department of Physics, Santa
Barbara, USA
N. Amin, R. Bhandari, J. Bradmiller-Feld, C. Campagnari, M. Citron, A. Dishaw,
V. Dutta, M. Franco Sevilla, L. Gouskos, R. Heller, J. Incandela, A.
Ovcharova, H. Qu, J. Richman, D. Stuart, I. Suarez, S. Wang, J. Yoo California
Institute of Technology, Pasadena, USA
D. Anderson, A. Bornheim, J. Bunn, J.M. Lawhorn, H.B. Newman, T.Q. Nguyen, M.
Spiropulu, J.R. Vlimant, R. Wilkinson, S. Xie, Z. Zhang, R.Y. Zhu Carnegie
Mellon University, Pittsburgh, USA
M.B. Andrews, T. Ferguson, T. Mudholkar, M. Paulini, M. Sun, I. Vorobiev, M.
Weinberg University of Colorado Boulder, Boulder, USA
J.P. Cumalat, W.T. Ford, F. Jensen, A. Johnson, M. Krohn, S. Leontsinis, E.
MacDonald, T. Mulholland, K. Stenson, K.A. Ulmer, S.R. Wagner Cornell
University, Ithaca, USA
J. Alexander, J. Chaves, Y. Cheng, J. Chu, A. Datta, K. Mcdermott, N. Mirman,
J.R. Patterson, D. Quach, A. Rinkevicius, A. Ryd, L. Skinnari, L. Soffi, S.M.
Tan, Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek Fermi National
Accelerator Laboratory, Batavia, USA
S. Abdullin, M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, A. Apyan, S.
Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, G.
Bolla${}^{\textrm{\textdagger}}$, K. Burkett, J.N. Butler, A. Canepa, G.B.
Cerati, H.W.K. Cheung, F. Chlebana, M. Cremonesi, J. Duarte, V.D. Elvira, J.
Freeman, Z. Gecse, E. Gottschalk, L. Gray, D. Green, S. Grünendahl, O.
Gutsche, J. Hanlon, R.M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, B.
Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, B. Klima, M.J. Kortelainen,
B. Kreis, S. Lammel, D. Lincoln, R. Lipton, M. Liu, T. Liu, J. Lykken, K.
Maeshima, N. Magini, J.M. Marraffino, D. Mason, P. McBride, P. Merkel, S.
Mrenna, S. Nahn, V. O’Dell, K. Pedro, C. Pena, O. Prokofyev, G. Rakness, L.
Ristori, A. Savoy-Navarro64, B. Schneider, E. Sexton-Kennedy, A. Soha, W.J.
Spalding, L. Spiegel, S. Stoynev, J. Strait, N. Strobbe, L. Taylor, S.
Tkaczyk, N.V. Tran, L. Uplegger, E.W. Vaandering, C. Vernieri, M. Verzocchi,
R. Vidal, M. Wang, H.A. Weber, A. Whitbeck University of Florida, Gainesville,
USA
D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerhoff, L. Cadamuro,
A. Carnes, M. Carver, D. Curry, R.D. Field, S.V. Gleyzer, B.M. Joshi, J.
Konigsberg, A. Korytov, P. Ma, K. Matchev, H. Mei, G. Mitselmakher, K. Shi, D.
Sperka, J. Wang, S. Wang Florida International University, Miami, USA
Y.R. Joshi, S. Linn Florida State University, Tallahassee, USA
A. Ackert, T. Adams, A. Askew, S. Hagopian, V. Hagopian, K.F. Johnson, T.
Kolberg, G. Martinez, T. Perry, H. Prosper, A. Saha, A. Santra, V. Sharma, R.
Yohay Florida Institute of Technology, Melbourne, USA
M.M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, T.
Roy, F. Yumiceva University of Illinois at Chicago (UIC), Chicago, USA
M.R. Adams, L. Apanasevich, D. Berry, R.R. Betts, R. Cavanaugh, X. Chen, S.
Dittmer, O. Evdokimov, C.E. Gerber, D.A. Hangal, D.J. Hofman, K. Jung, J.
Kamin, C. Mills, I.D. Sandoval Gonzalez, M.B. Tonjes, N. Varelas, H. Wang, Z.
Wu, J. Zhang The University of Iowa, Iowa City, USA
M. Alhusseini, B. Bilki65, W. Clarida, K. Dilsiz66, S. Durgut, R.P.
Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, A. Mestvirishvili, A.
Moeller, J. Nachtman, H. Ogul67, Y. Onel, F. Ozok68, A. Penzo, C. Snyder, E.
Tiras, J. Wetzel Johns Hopkins University, Baltimore, USA
B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan,
W.T. Hung, P. Maksimovic, J. Roskes, U. Sarica, M. Swartz, M. Xiao, C. You The
University of Kansas, Lawrence, USA
A. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, J. Castle, S.
Khalil, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, C. Rogan, S.
Sanders, E. Schmitz, J.D. Tapia Takaki, Q. Wang Kansas State University,
Manhattan, USA
A. Ivanov, K. Kaadze, D. Kim, Y. Maravin, D.R. Mendis, T. Mitchell, A. Modak,
A. Mohammadi, L.K. Saini, N. Skhirtladze Lawrence Livermore National
Laboratory, Livermore, USA
F. Rebassoo, D. Wright University of Maryland, College Park, USA
A. Baden, O. Baron, A. Belloni, S.C. Eno, Y. Feng, C. Ferraioli, N.J. Hadley,
S. Jabeen, G.Y. Jeng, R.G. Kellogg, J. Kunkle, A.C. Mignerey, F. Ricci-Tam,
Y.H. Shin, A. Skuja, S.C. Tonwar, K. Wong Massachusetts Institute of
Technology, Cambridge, USA
D. Abercrombie, B. Allen, V. Azzolini, R. Barbieri, A. Baty, G. Bauer, R. Bi,
S. Brandt, W. Busza, I.A. Cali, M. D’Alfonso, Z. Demiragli, G. Gomez Ceballos,
M. Goncharov, P. Harris, D. Hsu, M. Hu, Y. Iiyama, G.M. Innocenti, M. Klute,
D. Kovalskyi, Y.-J. Lee, A. Levin, P.D. Luckey, B. Maier, A.C. Marini, C.
Mcginn, C. Mironov, S. Narayanan, X. Niu, C. Paus, C. Roland, G. Roland,
G.S.F. Stephans, K. Sumorok, K. Tatar, D. Velicanu, J. Wang, T.W. Wang, B.
Wyslouch, S. Zhaozhong University of Minnesota, Minneapolis, USA
A.C. Benvenuti, R.M. Chatterjee, A. Evans, P. Hansen, S. Kalafut, Y. Kubota,
Z. Lesko, J. Mans, S. Nourbakhsh, N. Ruckstuhl, R. Rusack, J. Turkewitz, M.A.
Wadud University of Mississippi, Oxford, USA
J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA
E. Avdeeva, K. Bloom, D.R. Claes, C. Fangmeier, F. Golf, R. Gonzalez Suarez,
R. Kamalieddin, I. Kravchenko, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger
State University of New York at Buffalo, Buffalo, USA
A. Godshalk, C. Harrington, I. Iashvili, A. Kharchilava, D. Nguyen, A. Parker,
S. Rappoccio, B. Roozbahani Northeastern University, Boston, USA
G. Alverson, E. Barberis, C. Freer, A. Hortiangtham, D.M. Morse, T. Orimoto,
R. Teixeira De Lima, T. Wamorkar, B. Wang, A. Wisecarver, D. Wood Northwestern
University, Evanston, USA
S. Bhattacharya, O. Charaf, K.A. Hahn, N. Mucia, N. Odell, M.H. Schmitt, K.
Sung, M. Trovato, M. Velasco University of Notre Dame, Notre Dame, USA
R. Bucci, N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D.J. Karmgard, N.
Kellams, K. Lannon, W. Li, N. Loukas, N. Marinelli, F. Meng, C. Mueller, Y.
Musienko32, M. Planer, A. Reinsvold, R. Ruchti, P. Siddireddy, G. Smith, S.
Taroni, M. Wayne, A. Wightman, M. Wolf, A. Woodard The Ohio State University,
Columbus, USA
J. Alimena, L. Antonelli, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, A.
Hart, C. Hill, W. Ji, T.Y. Ling, W. Luo, B.L. Winer, H.W. Wulsin Princeton
University, Princeton, USA
S. Cooperstein, P. Elmer, J. Hardenbrook, P. Hebda, S. Higginbotham, A.
Kalogeropoulos, D. Lange, J. Luo, D. Marlow, K. Mei, I. Ojalvo, J. Olsen, C.
Palmer, P. Piroué, J. Salfeld-Nebgen, D. Stickland, C. Tully University of
Puerto Rico, Mayaguez, USA
S. Malik, S. Norberg Purdue University, West Lafayette, USA
A. Barker, V.E. Barnes, S. Das, L. Gutay, M. Jones, A.W. Jung, A. Khatiwada,
D.H. Miller, N. Neumeister, C.C. Peng, H. Qiu, J.F. Schulte, J. Sun, F. Wang,
R. Xiao, W. Xie Purdue University Northwest, Hammond, USA
T. Cheng, J. Dolen, N. Parashar Rice University, Houston, USA
Z. Chen, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Guilbaud, M. Kilpatrick, W.
Li, B. Michlin, B.P. Padley, J. Roberts, J. Rorie, W. Shi, Z. Tu, J. Zabel, A.
Zhang University of Rochester, Rochester, USA
A. Bodek, P. de Barbaro, R. Demina, Y.t. Duh, J.L. Dulemba, C. Fallon, T.
Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs, A.
Khukhunaishvili, K.H. Lo, P. Tan, R. Taus, M. Verzetti Rutgers, The State
University of New Jersey, Piscataway, USA
A. Agapitos, J.P. Chou, Y. Gershtein, T.A. Gómez Espinosa, E. Halkiadakis, M.
Heindl, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath,
R. Montalvo, K. Nash, M. Osherson, H. Saka, S. Salur, S. Schnetzer, D.
Sheffield, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker
University of Tennessee, Knoxville, USA
A.G. Delannoy, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa Texas A&M
University, College Station, USA
O. Bouhali69, A. Castaneda Hernandez69, A. Celik, M. Dalchenko, M. De Mattia,
A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, T. Kamon70, R.
Mueller, Y. Pakhotin, R. Patel, A. Perloff, L. Perniè, D. Rathjens, A.
Safonov, A. Tatarinov Texas Tech University, Lubbock, USA
N. Akchurin, J. Damgov, F. De Guio, P.R. Dudero, S. Kunori, K. Lamichhane,
S.W. Lee, T. Mengke, S. Muthumuni, T. Peltola, S. Undleeb, I. Volobouev, Z.
Wang Vanderbilt University, Nashville, USA
S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K.
Padeken, J.D. Ruiz Alvarez, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu University
of Virginia, Charlottesville, USA
M.W. Arenton, P. Barria, B. Cox, R. Hirosky, M. Joyce, A. Ledovskoy, H. Li, C.
Neu, T. Sinthuprasith, Y. Wang, E. Wolfe, F. Xia Wayne State University,
Detroit, USA
R. Harr, P.E. Karchin, N. Poudyal, J. Sturdy, P. Thapa, S. Zaleski University
of Wisconsin - Madison, Madison, WI, USA
M. Brodski, J. Buchanan, C. Caillol, D. Carlsmith, S. Dasu, L. Dodd, S. Duric,
B. Gomber, M. Grothe, M. Herndon, A. Hervé, U. Hussain, P. Klabbers, A.
Lanaro, A. Levine, K. Long, R. Loveless, T. Ruggles, A. Savin, N. Smith, W.H.
Smith, N. Woods †: Deceased
1: Also at Vienna University of Technology, Vienna, Austria
2: Also at IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
3: Also at Universidade Estadual de Campinas, Campinas, Brazil
4: Also at Federal University of Rio Grande do Sul, Porto Alegre, Brazil
5: Also at Université Libre de Bruxelles, Bruxelles, Belgium
6: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia
7: Also at Joint Institute for Nuclear Research, Dubna, Russia
8: Also at Cairo University, Cairo, Egypt
9: Also at Helwan University, Cairo, Egypt
10: Now at Zewail City of Science and Technology, Zewail, Egypt
11: Also at Department of Physics, King Abdulaziz University, Jeddah, Saudi
Arabia
12: Also at Université de Haute Alsace, Mulhouse, France
13: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State
University, Moscow, Russia
14: Also at CERN, European Organization for Nuclear Research, Geneva,
Switzerland
15: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
16: Also at University of Hamburg, Hamburg, Germany
17: Also at Brandenburg University of Technology, Cottbus, Germany
18: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
19: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
20: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary
21: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India
22: Also at Institute of Physics, Bhubaneswar, India
23: Also at Shoolini University, Solan, India
24: Also at University of Visva-Bharati, Santiniketan, India
25: Also at Isfahan University of Technology, Isfahan, Iran
26: Also at Plasma Physics Research Center, Science and Research Branch,
Islamic Azad University, Tehran, Iran
27: Also at Università degli Studi di Siena, Siena, Italy
28: Also at International Islamic University of Malaysia, Kuala Lumpur,
Malaysia
29: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia
30: Also at Consejo Nacional de Ciencia y Tecnología, Mexico city, Mexico
31: Also at Warsaw University of Technology, Institute of Electronic Systems,
Warsaw, Poland
32: Also at Institute for Nuclear Research, Moscow, Russia
33: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
34: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
35: Also at University of Florida, Gainesville, USA
36: Also at P.N. Lebedev Physical Institute, Moscow, Russia
37: Also at California Institute of Technology, Pasadena, USA
38: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
39: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
40: Also at INFN Sezione di Pavia a, Università di Pavia b, Pavia, Italy
41: Also at University of Belgrade, Faculty of Physics and Vinca Institute of
Nuclear Sciences, Belgrade, Serbia
42: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy
43: Also at National and Kapodistrian University of Athens, Athens, Greece
44: Also at Riga Technical University, Riga, Latvia
45: Also at Universität Zürich, Zurich, Switzerland
46: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna,
Austria
47: Also at Adiyaman University, Adiyaman, Turkey
48: Also at Istanbul Aydin University, Istanbul, Turkey
49: Also at Mersin University, Mersin, Turkey
50: Also at Piri Reis University, Istanbul, Turkey
51: Also at Gaziosmanpasa University, Tokat, Turkey
52: Also at Ozyegin University, Istanbul, Turkey
53: Also at Izmir Institute of Technology, Izmir, Turkey
54: Also at Marmara University, Istanbul, Turkey
55: Also at Kafkas University, Kars, Turkey
56: Also at Istanbul Bilgi University, Istanbul, Turkey
57: Also at Hacettepe University, Ankara, Turkey
58: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom
59: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
60: Also at Monash University, Faculty of Science, Clayton, Australia
61: Also at Bethel University, St. Paul, USA
62: Also at Karamanoğlu Mehmetbey University, Karaman, Turkey
63: Also at Utah Valley University, Orem, USA
64: Also at Purdue University, West Lafayette, USA
65: Also at Beykent University, Istanbul, Turkey
66: Also at Bingol University, Bingol, Turkey
67: Also at Sinop University, Sinop, Turkey
68: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey
69: Also at Texas A&M University at Qatar, Doha, Qatar
70: Also at Kyungpook National University, Daegu, Korea