HIG-18-014

$HeadURL$ $Id$

HIG-18-014

# Search for charged Higgs bosons in the $\PH^{\pm}\to\tau^{\pm}\nu_{\tau}$
decay channel in proton-proton collisions at $\sqrt{s}=13\TeV$

###### Abstract

A search is presented for charged Higgs bosons in the
$\PH^{\pm}\to\tau^{\pm}\nu_{\tau}$ decay mode in the hadronic final state and
in final states with an electron or a muon. The search is based on proton-
proton collision data recorded by the CMS experiment in 2016 at a center-of-
mass energy of 13, corresponding to an integrated luminosity of 35.9. The
results agree with the background expectation from the standard model. Upper
limits at $95\%$ confidence level are set on the production cross section
times branching fraction to $\tau^{\pm}\nu_{\tau}$ for an H± in the mass range
of 80to 3, including the region near the top quark mass. The observed limit
ranges from 6$\unit{pb}$ at 80to 5$\unit{fb}$ at 3. The limits are interpreted
in the context of the minimal supersymmetric standard model
$m_{\Ph}^{\text{mod-}}$ scenario.

##  0.1 Introduction

In 2012, the ATLAS and CMS experiments observed a resonance consistent with
the Higgs boson with a mass of approximately 125at the CERN LHC [1, 2, 3],
providing strong evidence for spontaneous symmetry breaking via the
Brout–Englert–Higgs mechanism [4, 5, 6, 7, 8, 9]. The observation was followed
by precision measurements of the mass, couplings, and CP quantum numbers of
the new boson, which were found to be consistent with the predictions of the
standard model (SM) of particle physics [10, 11, 12, 13, 14].

Several extensions of the SM predict a more complex Higgs sector with several
Higgs fields, yielding a spectrum of Higgs bosons with different masses,
charges, and other properties. These models are constrained, but not excluded,
by the measured properties of the 125boson. The observation of additional
Higgs bosons would provide unequivocal evidence for the existence of physics
beyond the SM. Two-Higgs-doublet models (2HDMs) predict five different Higgs
bosons: two neutral CP-even particles and (with $m_{\Ph}\leq m_{\PH}$), one
neutral CP-odd particle , and two charged Higgs bosons [15].

The 2HDMs are classified into different types, depending on the coupling of
the two Higgs doublets to fermions. This search is interpreted in the context
of the “type II” 2HDM, where one doublet couples to down-type quarks and
charged leptons, and the other to up-type quarks. The minimal supersymmetric
standard model (MSSM) Higgs sector is a type II 2HDM [16]. At tree level, the
Higgs sector of a type II 2HDM can be described with two parameters. In the
context of searches, they are conventionally chosen to be the mass of the
charged Higgs boson ($m_{\PH^{\pm}}$) and the ratio of the vacuum expectation
values of the two Higgs doublets, denoted as $\tanb$. Charged Higgs bosons are
also predicted by more complex models, such as triplet models [17, 18, 19].

The dominant production mechanism of the depends on its mass. Examples of
leading order (LO) diagrams describing the production in 2HDM in different
mass regions are shown in Fig. 1. Light , with a mass smaller than the mass
difference between the top and the bottom quarks
($m_{\PH^{\pm}}<m_{\cPqt}-m_{\cPqb}$), are predominantly produced in decays of
top quarks (double-resonant top quark production, Fig. 1 left), whereas heavy
($m_{\PH^{\pm}}>m_{\cPqt}-m_{\cPqb}$) are produced in association with a top
quark as $\Pp\Pp\to\cPqt\cPqb\PH^{\pm}$ (single-resonant top quark production,
Fig. 1 middle). In the intermediate region near the mass of the top quark
($m_{\PH^{\pm}}\sim m_{\cPqt}$), the nonresonant top quark production mode
(Fig. 1 right) also contributes and the full
$\Pp\Pp\to\Hpm\PW^{\mp}\cPqb\cPaqb$ process must be calculated in order to
correctly account for all three production mechanisms and their interference
[20].

Figure 1: Leading order diagrams describing charged Higgs boson production.
Double-resonant top quark production (left) is the dominant process for light
, whereas the single-resonant top quark production (middle) dominates for
heavy masses. For the intermediate region ($m_{\PH^{\pm}}\sim m_{\cPqt}$),
both production modes and their interplay with the nonresonant top quark
production (right) must be taken into account. Charge-conjugate processes are
implied.

In type II 2HDM, a light decays almost exclusively to a tau lepton and a
neutrino. For the heavy , the decay into top and bottom quarks
($\PH^{+}\to\cPqt\cPaqb$ and $\PH^{-}\to\cPaqt\cPqb$, together denoted as
$\Hpm\to\cPqt\cPqb$) is dominant, but since the coupling of the to leptons is
proportional to $\tanb$, the branching fraction to a tau lepton and a neutrino
($\PH^{+}\to\Pgt^{+}\Pgngt$ and $\PH^{-}\to\Pgt^{-}\Pagngt$, together denoted
as $\PH^{\pm}\to\Pgt^{\pm}\Pgngt$) remains sizable for large values of
$\tanb$.

Direct searches for have been performed at LEP [21], at the Fermilab Tevatron
[22, 23], and by the LHC experiments. The ATLAS and CMS Collaborations have
covered several decay channels, such as $\Pgt^{\pm}\Pgngt$ [24, 25, 26, 27,
28, 29, 30], [28, 31, 32], [33, 34], [35] and $\PW^{\pm}\cPZ$ [36, 37], in
their previous searches at center-of-mass energies of 7, 8, or 13.
Additionally, the ATLAS and CMS results on searches for additional neutral
Higgs bosons have been interpreted in the 2HDM parameter space, constraining
the allowed mass range as a function of $\tanb$ [38, 39, 40, 41].

In this paper, a direct search for decaying into a tau lepton and a neutrino
is presented, based on data collected at a center-of-mass energy of 13by the
CMS experiment in 2016, corresponding to an integrated luminosity of
$35.9\fbinv$. The search is conducted in three different final states, labeled
in this paper as the hadronic final state ($\tauh$ \+ jets, where denotes a
hadronically decaying tau lepton), the leptonic final state with a ($\ell$ \+
$\tauh$), and the leptonic final state without a ($\ell$ \+ no $\tauh$). For
the hadronic final state, events contain a , missing transverse momentum due
to neutrinos, and additional hadronic jets from top quark decays and quarks.
The leptonic final state with a contains a single isolated lepton (electron or
muon), missing transverse momentum, hadronic jets and a . The leptonic final
state without a is defined in a similar way, except that events with a are
rejected. In the leptonic final states, the lepton can originate either from
the decays of the tau leptons from decays, or from a $\PW^{\pm}$ boson decay.

In each final state, events are further classified into different categories
for statistical analysis. A transverse mass distribution is reconstructed in
each category of each final state and used in a maximum likelihood fit to
search for an signal. The mass range from 80to 3is covered in the search,
including the intermediate mass range near $m_{\cPqt}$.

This paper is organized as follows. The CMS detector is briefly presented in
Section 0.2. The methods used in event simulation and reconstruction are
described in Sections 0.3 and 0.4, respectively. The event selection and
categorization criteria are presented in Section 0.5, while Section 0.6
details the background estimation methods used in the analysis. Systematic
uncertainties included in the analysis are described in Section 0.7. Finally,
the results are presented in Section 0.8 and summarized in Section 0.9.

##  0.2 The CMS detector

The central feature of the CMS apparatus is a superconducting solenoid of 6m
internal diameter, providing a magnetic field of 3.8T. Within the solenoid
volume are a silicon pixel and strip tracker, a lead tungstate crystal
electromagnetic calorimeter (ECAL), and a brass and scintillator hadron
calorimeter, each composed of a barrel and two endcap sections. Forward
calorimeters extend the pseudorapidity ($\eta$) coverage provided by the
barrel and endcap detectors up to $\abs{\eta}=5$. Muons are detected in gas-
ionization chambers embedded in the steel flux-return yoke outside the
solenoid. Events of interest are selected using a two-tiered trigger system
[42]. The first level, composed of custom hardware processors, uses
information from the calorimeters and muon detectors to select events at a
rate of around 100kHz within a time interval of less than 4. The second level,
known as the high-level trigger (HLT), consists of a farm of processors
running a version of the full event reconstruction software optimized for fast
processing, and reduces the event rate to around 1kHz before data storage. A
more detailed description of the CMS detector, together with a definition of
the coordinate system used and the relevant kinematic variables, can be found
in Ref. [43].

##  0.3 Event simulation

The signal samples for the light mass values from 80 to 160are generated at
next-to-leading order (NLO) with the v2.3.3 [44] generator, assuming
production via top quark decay ($\Pp\Pp\to\Hpm\PW^{\mp}\cPqb\cPaqb$). For the
heavy mass range from 180to 3, the same approach is used except that
production via $\Pp\Pp\to\cPqt\cPqb\PH^{\pm}$ is assumed. For the intermediate
mass range from 165 to 175, the samples are generated at LO using the v2.3.3
with the model described in Ref. [20], which is available only at LO.

The effect of using LO instead of NLO samples is estimated by comparing
kinematic distributions and final event yields from both types of samples in
mass regions below (150–160) and above (180–220) the intermediate range.
Significant differences are observed in some kinematic variables such as jet
multiplicity, affecting the selection efficiency and the predicted final
signal yield. Since the shapes of the final distributions are found to be
compatible between the LO and the NLO samples, a LO-to-NLO correction is
performed by scaling the final signal event yield from each intermediate-mass
sample. The overall effect of the correction is to scale down the signal event
yield, resulting in more conservative results than would be obtained using LO
samples without this correction.

The NLO/LO signal yield ratios are similar for all mass points within the
150–160and 180–200mass regions, but different between these two regions. Thus
the correction factor for each final state and event category is calculated as
an average over the NLO/LO ratios of the final event yields. This is done
separately for the 150–160and 180–200regions, and the correction derived in
the 150–160region is applied to the intermediate signal sample with
$m_{\PH^{\pm}}=165\GeV$, for which $m_{\PH^{\pm}}<m_{\cPqt}-m_{\cPqb}$ and the
production is still dominated by top quark decays, while the correction
derived in the 180–200region is applied to the 170 and 175samples with
$m_{\PH^{\pm}}>m_{\cPqt}-m_{\cPqb}$. For all signal samples up to
$m_{\PH^{\pm}}=500\GeV$, MadSpin [45] is used to model the decay, while 8.212
is used above 500.

In the leptonic final states, where accurate modeling of jet multiplicity is
needed for the correct categorization of events, the MG5_aMC@NLO v2.2.2
generator [44] is used to simulate the events at NLO. In the hadronic final
state, the statistical uncertainty in the final event yield needs to be
minimized for reliable modeling of the shape of the background, and thus a
larger sample generated using v2.0 [46, 47, 48, 49, 50] with FxFx jet matching
and merging [51] is used to model this background. The v2.0 generator is used
to model single top quark production via $t$-channel and production [52, 53],
while the v2.2.2 generator is used for the $s$-channel production. The value
of $m_{\cPqt}$ is set to 172.5for all and single top quark samples. The +jets
and $\cPZ/\gamma^{*}$ events are generated at LO using v2.2.2 with up to four
noncollinear partons in the final state [54]. The diboson processes (, , ) are
simulated using 8.212.

The simulated samples are normalized to the theoretical cross sections for the
corresponding processes. For the background and the single top quark
background in the $s$ and channels, the cross sections are calculated at next-
to-NLO precision [55, 56]. NLO precision calculations are used for single top
quark production in the $t$ channel, and for the +jets, $\cPZ/\gamma^{*}$, and
diboson processes [57, 56, 58, 59].

For all simulated samples, the NNPDF3.0 parton distribution functions (PDFs)
[60] are used, and the generators are interfaced with 8.212 to model the
parton showering, fragmentation, and the decay of the tau leptons. The
parameters affecting the description of the underlying event are set to the
CUETP8M1 tune [61] for all processes except , for which a customized
CUETP8M2T4 tune [62] is used.

Generated events are processed through a simulation of the CMS detector based
on the v9.4 software [63], and they are reconstructed following the same
algorithms that are used for data. The effect of additional soft inelastic
proton-proton ($\Pp\Pp$) interactions (pileup) is modeled by generating
minimum bias collision events with and mixing them with the simulated hard
scattering events. The effects from multiple inelastic $\Pp\Pp$ collisions
occurring per bunch crossing (in-time pileup), as well as the effect of
inelastic collisions happening in the preceding and subsequent bunch crossings
(out-of-time pileup) are taken into account. The simulated events are weighted
such that the final pileup distribution matches the one observed in data. For
the data collected in 2016, an average of approximately 23 interactions per
bunch crossing was measured.

##  0.4 Event reconstruction

Event reconstruction is based on the particle-flow (PF) algorithm [64] that
aims to reconstruct and identify each individual particle in an event with an
optimized combination of information from the various elements of the CMS
detector. The output of the PF algorithm is a set of PF candidates, classified
into muons, electrons, photons, and charged and neutral hadrons.

The collision vertices are reconstructed from particle tracks using the
deterministic annealing algorithm [65]. The reconstructed vertex with the
largest value of the physics-object transverse momentum squared ($\pt^{2}$)
sum is taken to be the primary interaction vertex. The physics objects in this
case are the jets, clustered using the anti-jet finding algorithm [66, 67]
with the tracks assigned to the vertex as inputs, and the associated missing
transverse momentum, calculated as the negative vector sum of the of those
jets. All other reconstructed vertices are attributed to pileup.

Electrons are reconstructed and their momentum is estimated by combining the
momentum measurement from the tracker at the interaction vertex with the
energy measurement in the ECAL. The energy of the corresponding ECAL cluster
and the energy sum of all bremsstrahlung photons spatially compatible with
originating from the electron tracks are taken into account. The momentum
resolution for electrons with $\pt\approx 45\GeV$ from $\cPZ\to\Pe\Pe$ decays
ranges from 1.7% for nonshowering electrons in the barrel region to 4.5% for
showering electrons in the endcaps [68]. In addition, electrons are required
to pass an identification requirement based on a multivariate discriminant
that combines several variables describing the shape of the energy deposits in
the ECAL, as well as the direction and quality of the associated tracks [69].
A tight working point with 88% identification efficiency for events is used to
select events with an electron, while a loose working point with 95%
efficiency is used to veto events with one or several electrons, depending on
the final state.

Muons are identified as tracks in the central tracker, consistent with either
a track or several hits in the muon chambers, and associated with calorimeter
deposits compatible with the muon hypothesis [70]. The momenta of muons are
obtained from the curvatures of the corresponding tracks. Contributions from
other particles misidentified as muons are suppressed with a discriminant
based on the track fit quality. Two working points as defined in Ref. [70] are
used: a medium working point with 97% identification efficiency is used to
select events with a muon, while a loose working point with ${>}99\%$
identification efficiency is used for vetoing muons.

The background contributions from nonprompt and misidentified leptons are
suppressed by requiring the leptons to be isolated from hadronic activity in
the event. For this purpose, an isolation discriminant is defined as the sum
of the PF candidates in a cone around the lepton, divided by the of the
lepton. For optimal performance across the lepton momentum range, the cone
size is varied with the lepton as
$\Delta{R}=\sqrt{\smash[b]{(\Delta\eta)^{2}+(\Delta\phi)^{2}}}=10\GeV/\text{min}(\text{max}(\pt,50\GeV),\allowbreak{200\GeV)}$,
where $\Delta\phi$ denotes a difference in azimuthal angle, leading to cone
radii from 0.05 to 0.20. A tight (loose) isolation criterion with discriminant
$<0.1$ ($0.4$) is used in lepton selection (veto).

For each event, hadronic jets are clustered from the reconstructed PF
candidates using the infrared and collinear safe anti-algorithm [66, 67] with
a distance parameter of 0.4. The jet momentum is determined as the vectorial
sum of all particle momenta in the jet, and is found from simulation to be
within 5 to 10% of the true momentum over the whole spectrum and detector
acceptance. Pileup can contribute additional tracks and calorimetric energy
deposits to the jet momentum. To mitigate this effect, tracks identified as
originating from pileup vertices are discarded and an offset correction is
applied to correct for remaining contributions. Jet energy corrections are
derived from simulation to bring the measured response of jets to that of
particle level jets on average. In situ measurements of the momentum balance
in dijet, $\text{photon}+\text{jet}$, $\cPZ+\text{jet}$, and multijet events
are used to account for any residual differences in jet energy scale between
data and simulation [71]. The jet energy resolution amounts typically to 15%
at 10, 8% at 100, and 4% at 1 [72]. Additional selection criteria are applied
to each jet to remove jets potentially dominated by anomalous contributions
from various subdetector components or reconstruction failures.

Jets originating from the hadronization of quarks ( jets) are identified using
the combined secondary vertex algorithm [73, 74], which uses information on
the decay vertices of long-lived hadrons and the impact parameters of charged
particle tracks as input to a neural network discriminant. The working point
is chosen such that the probability to misidentify jets originating from
light-flavor quarks or gluons ( quarks) as jets is 1% (12%), corresponding to
63% efficiency for the selection of genuine jets in events. Simulated samples
are corrected for differences in jet identification and misidentification
efficiency compared to the data.

The are reconstructed with the hadron-plus-strips algorithm [75, 76], which
uses clustered anti-jets as seeds. The hadron-plus-strips algorithm
reconstructs different decay modes with one charged pion and up to two neutral
pions (one-prong), or three charged pions (three-prong). Since neutral pions
decay promptly to a photon pair, they are reconstructed by defining strips of
ECAL energy deposits in the $\eta$–$\phi$ plane. The candidates are rejected
if they are consistent with the hypothesis of being muons or electrons
misidentified as . The jets originating from the hadronization of quarks or
gluons misidentified as are suppressed using a multivariate discriminant [76].
It combines information on isolation, based on the surrounding hadronic
activity, and on its lifetime, inferred from the tracks of the decay products.
A loose working point is used for this discriminant, corresponding to
${\approx}50\%$ identification efficiency, determined from
$\cPZ/\gamma^{*}\to\Pgt^{+}\Pgt^{-}$ events, and $3\times 10^{-3}$ probability
for misidentifying a jet as a , determined from quantum chromodynamics (QCD)
multijet events. A correction to the energy scale is derived using $\Pe\tauh$
and $\Pgm\tauh$ final states of $\cPZ/\gamma^{*}\to\Pgt^{+}\Pgt^{-}$ events
[76] and applied in simulated samples.

The missing transverse momentum () is defined as the negative vector sum of
the of all reconstructed PF candidates [77]. The energy scale corrections
applied to jets and are propagated to the .

The transverse mass is defined as

$\mT(\tauh/\ell)=\sqrt{2\pt(\tauh/\ell)\ptmiss(1-\cos\Delta\phi(\ptvec(\tauh/\ell),\ptvecmiss))},$
(1)

where $\ell$ is a generic symbol used to label the electron or muon present in
the leptonic final states, while the leading is used in the in the hadronic
final state.

##  0.5 Event selection

The search is conducted in three exclusive final states:

  * •

$\tauh$ \+ jets: hadronic final state (events with an electron or a muon are
vetoed);

  * •

$\ell$ \+ $\tauh$: leptonic final state with a hadronically decaying tau
lepton (events with additional electrons or muons are vetoed); and

  * •

$\ell$ \+ no $\tauh$: leptonic final state without a hadronically decaying tau
lepton (events with a or additional electrons or muons are vetoed).

In the low-$m_{\PH^{\pm}}$ region, below $m_{\cPqt}$, the sensitivity of the
hadronic final state is limited by the relatively high trigger thresholds,
making the leptonic final states most sensitive for the signal. In the
high-$m_{\PH^{\pm}}$ region, above $m_{\cPqt}$, the hadronic final state
dominates the sensitivity, since the selection efficiency is higher as a
result of more inclusive jet multiplicity requirements.

The event selection and categorization strategies are chosen separately for
each final state to efficiently discriminate against the background events,
while ensuring a sufficient signal selection efficiency.

###  0.5.1 Hadronic final state ($\tauh$ \+ jets)

An HLT algorithm requiring the presence of a candidate and trigger-level
missing transverse momentum estimated from calorimeter information
($\pt^{\text{miss,calo}}$) is used to select the events for offline analysis.
The trigger requires the candidate to be loosely isolated with $\pt>50\GeV$
and $\abs{\eta}<2.1$, and with a leading track transverse momentum
$\pt^{\text{track}}>30\GeV$. The $\pt^{\text{miss,calo}}$ is required to be
larger than 90.

The trigger efficiencies for the and $\pt^{\text{miss,calo}}$ requirements are
measured separately. The efficiency of the part of the trigger is determined
with the tag-and-probe technique [78], using
$\cPZ/\gamma^{*}\to\Pgt^{+}\Pgt^{-}$ events with one hadronic and one muonic
tau lepton decay. The efficiency is found to vary between 50 and 100%, as a
function of and $\eta$ of the . The efficiency of the $\pt^{\text{miss,calo}}$
part of the trigger is measured from events with a signal-like topology
selected with a single-trigger, resulting in efficiencies between 10 and 100%,
depending on the value of the . The simulated events are corrected to match
the trigger efficiencies measured in the data.

In the offline selection, low thresholds for the of the reconstructed and are
needed to maximize the sensitivity for light . Thus selection criteria
identical to those in the HLT are applied to the reconstructed candidate and
to the . The one-prong candidates, corresponding to decays into a charged pion
and up to two neutral pions, are selected for further analysis. Events are
required to contain at least three jets with $\pt>30\GeV$ and
$\abs{\eta}<4.7$, separated from the reconstructed by ${\Delta{R}>0.5}$. At
least one of the jets is required to pass the jet identification with
$\abs{\eta}<2.4$. Any event with isolated electrons (muons) with
$\pt>15(10)\GeV$, $\abs{\eta}<2.5$, and passing the loose identification and
isolation criteria is rejected.

To suppress the background from QCD multijet events with a jet misidentified
as a , an additional selection based on $\Delta\phi(\tauh,\ptmiss)$ and
$\Delta\phi(\text{jet}_{n},\ptmiss)$ is applied, where the index $n$ runs over
the three highest jets ($\text{jet}_{n}$) in the event. QCD multijet events
passing the previous selection steps typically contain a hadronic jet
misidentified as a , another hadronic jet recoiling in the opposite direction,
and arising from the mismeasurement of the jet momenta. These events can be
suppressed with an angular discriminant defined as

$R_{\text{bb}}^{\text{min}}=\min_{n}\left\\{\sqrt{\left(180^{\circ}-\Delta\phi(\tauh,\ptvecmiss)\right)^{2}+\left(\Delta\phi(\text{jet}_{n},\ptvecmiss)\right)^{2}}\right\\}.$
(2)

The selected events are required to have
$R_{\text{bb}}^{\text{min}}>40^{\circ}$. The distribution of the
$R_{\text{bb}}^{\text{min}}$ variable after all other selections is shown in
Fig. 2 (left).

Figure 2:  The distribution of the angular discriminant
$R_{\text{bb}}^{\text{min}}$ after all other selections including the
$R_{\Pgt}=\pt^{\text{track}}/\pt^{\tauh}>0.75$ requirement have been applied
(left), and the distribution of the $R_{\Pgt}$ variable used for
categorization after all other selections including the
$R_{\text{bb}}^{\text{min}}>40^{\circ}$ requirement have been applied (right).

The selected events are classified into two categories based on the value of
the variable $R_{\Pgt}=\pt^{\text{track}}/\pt^{\tauh}$, reflecting the
helicity correlations emerging from the opposite polarization states of the
tau leptons originating from $\PW^{\pm}$ and decays [79]. The distribution of
the $R_{\Pgt}$ variable is shown in Fig. 2 (right). After all other
selections, most of the signal events have a large value of $R_{\Pgt}$, and
the high-$R_{\Pgt}$ category provides a good signal-to-background ratio. For
large $m_{\PH^{\pm}}$ values, the signal events are more evenly distributed
between the two categories, so inclusion of the background-dominated
low-$R_{\Pgt}$ category in the statistical analysis further improves the
sensitivity for the heavy . Separating the two categories at $R_{\Pgt}=0.75$
maximizes the signal sensitivity across the $m_{\PH^{\pm}}$ range.

###  0.5.2 Leptonic final state with a hadronically decaying tau lepton
($\ell$ \+ $\tauh$)

Single-lepton trigger algorithms are used for the online selection of events
with isolated electrons or muons. Several HLT algorithms for electron (muon)
selection with different thresholds starting from 27 (24), with
$\abs{\eta}<2.1$ ($2.4$) and with different isolation criteria, are used in or
combination to maximize the efficiency across the lepton range.

In the offline selection, electrons (muons) are required to have
$\pt>35(30)\GeV$ and $\abs{\eta}<2.1(2.4)$ because of trigger constraints.
Electrons (muons) are required to pass the tight (medium) identification and
tight isolation requirements. Events with any additional electrons (muons)
with $\pt>10\GeV$ and $\abs{\eta}<2.1(2.4)$ that pass the loose identification
and isolation criteria are vetoed. Efficiencies for online and offline
identification of leptons are measured, and the simulated events are corrected
to match the efficiencies observed in data. The presence of a is required,
with $\pt>20\GeV$, $\abs{\eta}<2.3$, and with a $\Delta{R}$ separation of at
least 0.5 with respect to the lepton.

One, two, or three jets are required with $\pt>30\GeV$ and $\abs{\eta}<2.4$,
separated from the lepton and the by $\Delta{R}>0.5$. At least one of the jets
is required to pass the jet identification. To suppress the background from
jets misidentified as , the is required to be at least $70\GeV$. The
background contribution from events with muons originating from hadron decays
is suppressed by requiring $\Delta\phi(\ell,\ptvecmiss)$ to exceed 0.5.

The selected events are classified into several categories for statistical
analysis. Three categories are defined based on the jet multiplicity and the
number of jets passing the jet identification: 1j1b (one jet that is also
identified as a jet), $\geq$2j1b, and $\geq$2j$\geq$2b. A second
categorization is performed in bins of : 70–100, 100–150, and ${>}150\GeV$.
Together with the separate electron and muon final states, this results in 18
categories.

The signal-to-background ratio in different categories varies with mass, as
jet categories with two jets and high become more sensitive for higher
$m_{\PH^{\pm}}$ values. The background-enriched categories allow a precise
determination of the background yields with a fit to data and extrapolation of
this information to signal regions. The categorization is found to improve the
expected sensitivity significantly, especially in the low-$m_{\PH^{\pm}}$
region, where efficient discrimination against backgrounds is essential.

###  0.5.3 Leptonic final state without a hadronically decaying tau lepton
($\ell$ \+ no $\tauh$)

The event selection criteria for the $\ell$ \+ no $\tauh$ final state are
identical to those described in Section 0.5.2 for the $\ell$ \+ $\tauh$ final
state, except for the following requirements. An event is vetoed if it
contains a with $\pt>20\GeV$, $\abs{\eta}<2.3$, and with a $\Delta{R}$
separation of at least 0.5 with respect to the lepton. Two or three jets are
required, each jet separated from the lepton by $\Delta{R}>0.5$. Higher jet
multiplicities are not selected, because they are expected to be more
sensitive in searches for other decay modes, such as $\Hpm\to\cPqt\cPqb$. At
least one of the jets is required to pass the jet identification.

The number of QCD multijet events with jets misidentified as leptons is
reduced to a negligible level by requiring a high of ${>}100\GeV$ and by
applying the following angular selections:

  * •

$\Delta\phi(\ell,\ptvecmiss)>0.5$;

  * •

$\Delta\phi(\text{leading jet},\ptvecmiss)>0.5$; and

  * •

$\min(\Delta\phi(\ell,\text{jet}_{n}))<\pi-0.5$,

where $\text{jet}_{n}$ refers to any of the selected jets in the events. The
first criterion is identical to the one applied in the $\ell$ \+ $\tauh$ final
state against muons from hadron decays whereas the second discriminates
efficiently against the QCD multijet background. The last requirement is
designed to reject background events where all the jets are back-to-back with
respect to the selected lepton.

To further enhance the signal sensitivity and to constrain the backgrounds, a
similar categorization as in the $\ell$ \+ $\tauh$ final state is established.
Four categories are used based on jet multiplicity and the number of jets
passing the jet identification: 2j1b, 2j2b, 3j1b, and 3j$\geq$2b, followed by
two categories in : 100–150 and ${>}150\GeV$. Together with the separate
electron and muon final states, this results in 16 categories.

An overview of the event selection criteria in all three final states is shown
in Table 0.5.3.

A summary of the event selection criteria applied in each final state. The
electrons, muons, candidates and jets are required to be separated from each
other by $\Delta R>0.5$ in all final states. The ${\dagger}$ symbol means that
the selection is identical between $\ell$ \+ $\tauh$ and $\ell$ \+ no $\tauh$
final states. In all final states, events with additional electrons or muons
are vetoed as detailed in Section 0.5. In this table, “b jets” refers to all
jets passing the b jet identification, and $\text{jet}_{n}$ refers to any of
the selected jets.  Selection $\tauh$ \+ jets $\ell$ \+ $\tauh$ $\ell$ \+ no
$\tauh$ Trigger +$\pt^{\text{miss,calo}}$ single or single  † Number of
candidates $\geq 1$ $\geq 1$ $0$ $\pt>50\GeV$, $\pt^{\text{track}}>30\GeV$
$\pt>20\GeV$ $\abs{\eta}$ $\abs{\eta}<2.1$ $\abs{\eta}<2.3$ Number of
electrons and muons $0$ 1 or 1 (exclusively) † Electron  $\pt>35\GeV$ †
Ekectron $\abs{\eta}$ $\abs{\eta}<2.1$ † Muon  $\pt>30\GeV$ † Muon
$\abs{\eta}$ $\abs{\eta}<2.4$ † Number of jets (incl. b jets) $\geq 3$ jets
1–3 jets 2–3 jets Jet  $\pt>30\GeV$ $\pt>30\GeV$ † Jet $\abs{\eta}$
$\abs{\eta}<4.7$ $\abs{\eta}<2.4$ † Number of b jets $\geq 1$ b jets 1–3 b
jets † b jet $\abs{\eta}$ $\abs{\eta}<2.4$ $\abs{\eta}<2.4$ † $\ptmiss>90\GeV$
$\ptmiss>70\GeV$ $\ptmiss>100\GeV$ Angular selections
$R_{\text{bb}}^{\text{min}}>40^{\circ}$ $\Delta\phi(\ell,\ptmiss)>0.5$
$\Delta\phi(\ell,\ptvecmiss)>0.5$, ($\ell=\Pe$ or ) $\Delta\phi(\text{leading
jet},\ptvecmiss)>0.5$, $\min(\Delta\phi(\ell,\text{jet}_{n}))<\pi-0.5$

##  0.6 Background estimation

The dominant background processes in the hadronic final state are QCD multijet
and production. Other backgrounds are single top quark production, boson
production in association with jets, $\cPZ/\gamma^{*}$ processes, and diboson
production. We refer to and single top quark events as “top events”, and to
+jets, $\cPZ/\gamma^{*}$, and diboson events as “electroweak events”. The
backgrounds from events containing either a genuine or an electron or a muon
misidentified as a are estimated from simulation, while the background from
jets misidentified as a is estimated from data. The correct identification or
misidentification of a is determined by requiring a generator-level tau lepton
to match with the reconstructed within a $\Delta{R}$ cone of 0.1.

In the events where a jet is misidentified as a (denoted as
$\text{jet}\to\tauh$), QCD multijet production is the dominant process. The
jet $\to$ background is estimated using a control sample enriched in jets
misidentified as , obtained by inverting the offline isolation requirement
used for signal selection. The contamination of the control region from
electroweak/top events with a genuine or a lepton misidentified as a is
estimated from the simulation and subtracted from the control sample. The
difference in selection efficiency between signal and control regions is
corrected by normalizing the control sample with fake factors, calculated at
an early stage of event selection (before applying jet identification, offline
selection on or the angular selections), where a possible signal does not
stand out from the large background yield. To account for the correlation
between the of the and as well as geometrical differences in detector
response, the measurement is performed in bins of and $\abs{\eta}$ of the .

The $\text{jet}\to\tauh$ background consists of two components: the QCD
multijet events and electroweak/top events with jets misidentified as . The
jets in these two background components have different quark and gluon
composition implying different tau fake factors. Thus the fake factors for
misidentified from the QCD multijet events and for misidentified from
electroweak/top events are estimated separately. The fake factor for the QCD
multijet events is defined as the ratio of the QCD multijet event yields in
signal and control regions. The QCD multijet event yield in the control region
is estimated by subtracting the simulated electroweak/top contribution (both
genuine and non-genuine events) from data. To estimate the contribution of the
QCD multijet events in the signal region, a binned maximum likelihood fit of
templates to data is performed, using the fraction of the QCD multijet events
as a fit parameter. The templates describe the expected shape of the
distribution for each background component prior to the fit. The shape of the
QCD multijet events is assumed to be similar in the signal and control
regions, so the shape observed in the control region is used as the fit
template. The template for electroweak/top events is obtained directly from
simulation. The fake factor for electroweak/top events is also estimated from
simulation as the ratio of event yields in signal and control regions.
Finally, the overall normalization factor of the control sample (as a function
of the and $\abs{\eta}$ of the ) is determined as a weighted sum of the two
fake factors, where the weight corresponds to the relative fractions of the
QCD multijet and electroweak/top events in the control region after all
selections. A closure test is performed by comparing the background
predictions obtained with the above method to data in a signal-depleted
validation region. The validation region is defined similarly to the signal
region, except that events with jets passing the jet identification are
vetoed.

In the leptonic final states, the dominant background is production in which
the semileptonic decays are dominant in the $\ell$ \+ no $\tauh$ final state
and the dilepton decays are dominant in the $\ell$ \+ $\tauh$ final state.
Minor backgrounds include single top quark, +jets, $\cPZ/\gamma^{*}$, and
diboson production. The QCD multijet background is suppressed to a negligible
level with tight angular selections and requirements. All backgrounds in the
two leptonic final states are estimated from simulation.

##  0.7 Systematic uncertainties

A summary of uncertainties incorporated in the analysis is given in Table 0.7,
where the effects of the different uncertainties on the final event yields are
shown. For the uncertainties common to all final states, the variations in the
yields are similar across the final states. Some of them affect only the final
event yield for a given signal or background process, whereas others also
modify the shape of the final distributions. The uncertainties from different
sources are assumed to be uncorrelated. Each uncertainty is treated as 100%
correlated among the signal and background processes, except for the few
special cases mentioned in the following.

Effect of systematic uncertainties on the final event yields in per cent,
prior to the fit, summed over all final states and categories. For the signal,
the values for $m_{\PH^{\pm}}=200\GeV$ are shown.  Source Shape (200) Jets
$\to$ Single  Electroweak $\tauh+\ptmiss$ trigger efficiency $\checkmark$ 1.4
2.0 0.2 0.2 0.2 identification $\checkmark$ 1.8 0.6 1.1 1.0 0.9 Lepton
selection efficiency 2.3 2.7 2.7 2.7 Jet energy scale and resolution
$\checkmark$ 4.7 0.4 5.1 9.2 13.4 energy scale $\checkmark$ 0.2 0.6 $<$ 0.1
$<$ 0.1 $<$ 0.1 Unclustered energy scale $\checkmark$ 2.6 $<$ 0.1 3.2 5.2 7.2
jet identification $\checkmark$ 3.6 0.8 3.1 3.4 13.8 Integrated luminosity 2.5
0.4 2.5 2.5 2.5 Pileup $\checkmark$ 1.1 $<$ 0.1 0.8 1.2 4.0 Jets misid. as
estimation $\checkmark$ 6.1 Cross section (scales, PDF) 0.8 5.5 5.3 3.6 Top
quark mass 0.4 2.7 2.2 Acceptance (scales, PDF) 5.1 0.5 2.8 2.8 6.8 parton
showering 6.1 Total 9.4 6.6 12.1 13.5 22.7

The simulated events are corrected to match the online and offline selection
efficiencies measured in data. For the trigger used in the $\tauh$ \+ jets
final state, the correction depends on the of the and , so the corresponding
uncertainty is taken into account as a shape uncertainty.

In the $\ell$ \+ $\tauh$ and $\ell$ \+ no $\tauh$ final states, the online
selection with single-lepton triggers is incorporated into the overall lepton
selection efficiency and the corresponding normalization uncertainty.

The systematic uncertainties in identification and isolation efficiencies for
, electron, and muon candidates are taken into account. The agreement of the
identification efficiency between data and simulated samples is measured using
the tag-and-probe technique [76]. The uncertainty in the measurement is 5%. It
is incorporated as a normalization uncertainty for all events with genuine tau
leptons, and anticorrelated between the $\ell$ \+ no $\tauh$ final state and
the final states with a . For the with large , an additional uncertainty of
${}^{+5}_{-35}\%\pt/\TeV$ is applied in the hadronic final state as a shape
uncertainty to account for possible differences arising in the extrapolation
of the measured efficiencies to the high-range. Simulated events with an
electron or a muon misidentified as a are weighted to obtain the
misidentification rates measured in data. The corrections are applied as a
function of $\eta$ and the corresponding uncertainties are propagated to
distributions and incorporated as shape uncertainties.

For the selection of electrons (muons), the combined uncertainty in online
selection and offline identification is 3 (4)%. For leptons vetoed with loose
identification and isolation criteria the effect of this uncertainty in the
final event yield is typically only $0.3\%$. Both effects are included as
normalization uncertainties.

The systematic uncertainties related to the calibration of energy measurement
for jets, and are considered as shape uncertainties. The uncertainties in the
jet energy scale and jet energy resolution are specified as a function of jet
and $\eta$. The uncertainty in the energy scale is $\pm 1.2\%$ for
$\pt<400\GeV$ and $\pm 3\%$ otherwise [76]. The variations of the jet and
energy scales are propagated to , for which the uncertainties arising from the
unclustered energy deposits in the detector are also included. The uncertainty
in the lepton energy scale is negligible for this analysis. Correcting the jet
identification and misidentification efficiencies in simulated samples affects
the final shapes, so the related uncertainties are considered as shape
uncertainties [74].

The systematic uncertainty due to the pileup modeling is obtained by shifting
the mean of the total inelastic $\Pp\Pp$ production cross section by $\pm 5\%$
around its nominal value [80], and propagating the difference to the final
distributions as a shape uncertainty.

The uncertainty in the measurement of the integrated luminosity is $2.5\%$
[81].

The uncertainties related to the $\text{jet}\to\tauh$ background measurement
in the hadronic final state are included. The statistical uncertainties in the
data and simulated samples used to determine the fake factors are propagated
into the final distributions as a normalization uncertainty. The limited
statistical precision of samples in the signal and control region after all
selections can lead to a difference in shapes between the two regions. This
effect is estimated and incorporated as a shape uncertainty. As the
$\text{jet}\to\tauh$ background is estimated by subtracting simulated events
(electroweak/top contribution) from the control data sample, all uncertainties
related to the simulated samples are propagated to this background. These
uncertainties are scaled to correspond to the contribution from simulated
events in the control region after all selections, and anticorrelated between
the $\text{jet}\to\tauh$ background and the other background processes.

The reference cross sections used to normalize each simulated background
process are varied within their theoretical uncertainties related to the
choice of renormalization and factorization (RF) scales and PDFs [82]. For and
single top quark processes, the effect of $m_{\cPqt}$ on the cross sections is
considered by varying $m_{\cPqt}$ by 1.0around the nominal value of 172.5.
Theoretical uncertainties in the acceptance of signal and background events
are determined by varying the RF scales and PDFs [82]. For the RF
uncertainties, the RF scales are varied by factors of 0.5 and 2, excluding the
extreme variations where one scale is varied by 0.5 and the other one by 2.
The envelope of the six variations is used to determine the total uncertainty.
The cross section and acceptance uncertainties are uncorrelated between
different background processes.

The uncertainty arising from the parton shower modeling is included for the
dominant background in the leptonic final states. Four parton showering
variations are included by perturbing the initial- and final-state parameters
[83], the matching of jets from matrix element calculations and from parton
shower, and the underlying event tune [62]. The parton shower uncertainties
are derived in each category and are applied as normalization uncertainties,
uncorrelated between categories. The leptonic final states are sensitive to
the parton shower modeling due to the event categorization based on the jet
multiplicity. In the hadronic final state, the event selection is inclusive in
jet multiplicity and thus this uncertainty is neglected.

For the intermediate-mass signal samples, an additional normalization
uncertainty is assigned to incorporate the statistical uncertainties of the
samples used in the calculation of the LO-to-NLO correction factors.

The statistical uncertainties related to the finite number of events in the
final distributions are taken into account using the Barlow–Beeston method
[84].

##  0.8 Results

A simultaneous binned maximum likelihood fit is performed over all the
categories in the three final states. In total, 36 distributions (two from the
$\tauh$ \+ jets final state, 18 from the $\ell$ \+ $\tauh$ final state, and 16
from the $\ell$ \+ no $\tauh$ final state) are fitted. The distributions are
binned according to the statistical precision of the samples, separately for
each category. This leads to wider bins in the tail of the distributions, such
that the last bin extends to 5. The systematic uncertainties are incorporated
as nuisance parameters in the likelihood. They are profiled in the fit
according to their probability density functions, taking correlations into
account. For normalization uncertainties, log-normal probability density
functions are used as priors. For shape uncertainties, polynomial
interpolation is used to derive continuous prior distributions from the
nominal and varied shape templates. The expected event yields after a
background-only fit to the data and the observed yields are summarized in
Table 0.8.

Number of expected and observed events for the three final states after all
selections, summed over all categories in each final state. For background
processes, the event yields after a background-only fit and the corresponding
uncertainties are shown. For the mass hypotheses of 100, 200, and 2000, the
signal yields are normalized to an production cross section of 1$\unit{pb}$
and the total systematic uncertainties (prior to the fit) are shown.

Process |  $\tauh$ \+ jets |  $\ell$ \+ $\tauh$ |  $\ell$ \+ no $\tauh$
---|---|---|---
Jets misid. as  | $4619\pm 35$ |  |
| $1455\pm 13$ | $30560\pm 470$ | $174740\pm 350$
Single  | $801\pm 13$ | $3006\pm 49$ | $26130\pm 260$
Electroweak | $1739\pm 18$ | $2760\pm 37$ | $52310\pm 220$
Total expected from the SM | $8614\pm 42$ | $36320\pm 500$ | $253190\pm 400$
Observed | $8647$ | $36277$ | $253236$
signal, $m_{\Hpm}=100\GeV$ | $20\pm 3$ | $160\pm 20$ | $241\pm 26$
signal, $m_{\Hpm}=200\GeV$ | $156\pm 22$ | $327\pm 37$ | $682\pm 61$
signal, $m_{\Hpm}=2000\GeV$ | $1630\pm 310$ | $369\pm 24$ | $1571\pm 99$

The distributions of after a background-only fit to the data are shown in Fig.
3 for both categories in the $\tauh$ \+ jets final state, in Fig. 4 for two
categories with high signal sensitivity in the $\ell$ \+ $\tauh$ final state,
and in Fig. 5 for two high-sensitivity categories in the $\ell$ \+ no $\tauh$
final state. No significant excess is observed in any of the categories, and
the result of the simultaneous fit is found to agree with the SM prediction.

Figure 3: The transverse mass distributions in the $\tauh$ \+ jets final state
after a background-only fit to the data. Left: category defined by
$R_{\Pgt}<0.75$. Transverse mass values up to $5\TeV$ are considered in the
fit, but the last bins with $\mT>650\GeV$ do not contain any observed events.
Right: category defined by $R_{\Pgt}>0.75$. The last bin shown extends to
$5\TeV$.

Figure 4: The transverse mass distributions for two $\ell$ \+ $\tauh$
categories with high signal sensitivity after a background-only fit to the
data. Left: category with one electron, one , one jet identified as a jet, and
$\ptmiss>150\GeV$. Right: category with one muon, one , one jet identified as
a jet and $100<\ptmiss<150\GeV$. In both categories, the last bin shown
extends to $5\TeV$.

Figure 5: The distributions for two $\ell$ \+ no $\tauh$ categories with high
signal sensitivity after a background-only fit to the data. Left: category
with one electron, no , two jets (one identified as a jet), and
$\ptmiss>150\GeV$. Right: category with one muon, no , two jets (one
identified as a jet) and $\ptmiss<150\GeV$. In both categories, the last bin
shown extends to $5\TeV$.

The modified frequentist criterion [85, 86] based on the profile likelihood
ratio test statistic [87] is applied to determine the 95% confidence level
(CL) limit for the product of the production cross section and the branching
fraction $\mathcal{B}(\PH^{\pm}\to\Pgt^{\pm}\Pgngt)$. The asymptotic
approximation [88] is used throughout the analysis. Pseudo-experiments are
performed for selected signal mass hypotheses to verify the validity of the
asymptotic approximation. For the mass range up to 165, the limit on
$\mathcal{B}(\cPqt\to\cPqb\PH^{\pm})\mathcal{B}(\PH^{\pm}\to\Pgt^{\pm}\Pgngt)$
is calculated, scaling down the background component consistently with the
$\mathcal{B}(\cPqt\to\cPqb\PH^{\pm})$ signal hypothesis, and the result is
interpreted as a limit on
$\sigma_{\PH^{\pm}}\mathcal{B}(\PH^{\pm}\to\Pgt^{\pm}\Pgngt)$ by assuming
$\sigma_{\PH^{\pm}}=2\sigma_{\ttbar}\mathcal{B}(\cPqt\to\cPqb\PH^{\pm})(1-\mathcal{B}(\cPqt\to\cPqb\PH^{\pm}))$,
where the production cross section $\sigma_{\ttbar}$ is assumed unmodified by
the presence of and the value of $831.76\unit{pb}$ is used [55, 56]. For the
mass range from 170to 3, the limit on
$\sigma_{\PH^{\pm}}\mathcal{B}(\PH^{\pm}\to\Pgt^{\pm}\Pgngt)$ is calculated
without assuming a specific production mode.

The model-independent upper limit with all final states and categories
combined is shown on the left side of Fig. 6. The numerical values are listed
in Table 0.8. The observed limit ranges from 6$\unit{pb}$ at 80to 5$\unit{fb}$
at 3. For the light mass range of 80–160, the limit corresponds to
$\mathcal{B}(\cPqt\to\cPqb\PH^{\pm})\mathcal{B}(\PH^{\pm}\to\Pgt^{\pm}\Pgngt)$
values between 0.36% (at 80) and 0.08% (at 160). In the light mass range, this
is the most stringent limit on
$\mathcal{B}(\cPqt\to\cPqb\PH^{\pm})\mathcal{B}(\PH^{\pm}\to\Pgt^{\pm}\Pgngt)$
to date set by the CMS Collaboration, with a factor of 1.5–3.0 improvement
with respect to Ref. [28], depending on $m_{\PH^{\pm}}$. In the intermediate
mass range of 165–175, this is the first limit on
$\sigma_{\PH^{\pm}}\mathcal{B}(\PH^{\pm}\to\Pgt^{\pm}\Pgngt)$ set by the CMS
Collaboration. The drop in the expected and observed limits in the
intermediate region is not predicted from theory [20] but is rather an
experimental feature explained by the fact that in this region LO signal
samples are used instead of NLO. This dip is mitigated but not completely
cancelled by the LO-to-NLO corrections extrapolated from the surrounding mass
regions. In the heavy mass range from 180, this result extends the search
region up to $m_{\PH^{\pm}}=3\TeV$, compared to 600in Ref. [28].

In the light and intermediate mass regions all three final states contribute
significantly to the sensitivity, and the combined limits are on average
$\approx$40% lower compared to the $\tauh$ \+ jets final state alone. In the
heavy mass region, the sensitivity of the leptonic final states decreases, and
the $\tauh$ \+ jets final state starts to dominate the limit as
$m_{\PH^{\pm}}$ increases. Above $m_{\PH^{\pm}}=500\GeV$ the combined limit is
solely driven by the $\tauh$ \+ jets final state.

The limit is interpreted in the MSSM $m_{\Ph}^{\text{mod-}}$ benchmark
scenario [89] by comparing the observed limit on the cross section to the
theoretical cross sections predicted in this scenario [90, 91, 92, 93, 94,
20]. The MSSM $m_{\Ph}^{\text{mod-}}$ scenario is specified using low-energy
MSSM parameters and is designed to give a mass of approximately 125for the
light CP-even Higgs boson over a wide region of the parameter space. The limit
for the MSSM $m_{\Ph}^{\text{mod-}}$ scenario in the $m_{\PH^{\pm}}$–$\tanb$
plane is shown on the right side of Fig. 6. Based on the observed limit, all
values of the parameter $\tanb$ from 1 to 60 are excluded for $m_{\PH^{\pm}}$
values up to 160. The limit extends to $m_{\PH^{\pm}}=500\GeV$. For
$m_{\PH^{\pm}}=200$ (400), the observed limit excludes all $\tanb$ values
above 26 (40), compared to 45 (56) excluded in Ref. [28].

Figure 6: The observed 95% CL exclusion limits on
$\sigma_{\PH^{\pm}}\mathcal{B}(\PH^{\pm}\to\Pgt^{\pm}\Pgngt)$ (solid black
points), compared to the expected limit assuming only standard model processes
(dashed line) for the mass range from 80to 3(left), and the same limit
interpreted in the $m_{\Ph}^{\text{mod-}}$ benchmark scenario (right). The
green (yellow) bands represent one (two) standard deviations from the expected
limit. On the left, the horizontal axis is linear from 80 to 180and
logarithmic for larger $m_{\PH^{\pm}}$ values. On the right, the region below
the red line is excluded assuming that the observed neutral Higgs boson is the
light CP-even 2HDM Higgs boson with a mass of ${125\pm 3\GeV}$, where the
uncertainty is the theoretical uncertainty in the mass calculation.

The expected and observed 95% CL exclusion limits on
$\sigma_{\PH^{\pm}}\mathcal{B}(\PH^{\pm}\to\Pgt^{\pm}\Pgngt)$ for the mass
range from 80to 3. The $\pm 1$ s.d. ($\pm 2$ s.d.) refers to one (two)
standard deviations from the expected limit.  $m_{\PH^{\pm}}$ Expected limit
(pb) Observed () $-2$ s.d. $-1$ s.d. median +1 s.d. +2 s.d. limit (pb) 80 3.17
4.25 5.87 8.15 10.89 5.97 90 3.05 4.08 5.69 7.96 10.75 4.59 100 2.67 3.56 4.94
6.90 9.26 3.24 120 2.04 2.72 3.78 5.29 7.12 2.55 140 1.41 1.87 2.61 3.63 4.88
2.22 150 1.19 1.58 2.20 3.07 4.14 1.63 155 1.06 1.41 1.95 2.71 3.64 1.48 160
1.05 1.39 1.93 2.69 3.61 1.31 165 0.76 1.02 1.45 2.67 2.86 1.01 170 0.40 0.54
0.77 1.12 1.59 0.57 175 0.37 0.50 0.71 1.03 1.45 0.52 180 0.44 0.60 0.83 1.18
1.59 0.85 200 0.30 0.41 0.57 0.80 1.09 0.65 220 0.22 0.30 0.41 0.58 0.80 0.47
250 0.15 0.21 0.29 0.41 0.56 0.31 300 0.08 0.11 0.15 0.22 0.30 0.14 400 0.032
0.043 0.062 0.090 0.125 0.078 500 0.016 0.022 0.031 0.046 0.067 0.048 750
0.0035 0.0050 0.0077 0.012 0.019 0.014 800 0.0029 0.0041 0.0064 0.0102 0.0157
0.0107 1000 0.0020 0.0030 0.0047 0.0077 0.0121 0.0085 2000 0.0009 0.0014
0.0025 0.0044 0.0074 0.0050 2500 0.0007 0.0012 0.0022 0.0042 0.0068 0.0047
3000 0.0007 0.0012 0.0022 0.0043 0.0067 0.0048

##  0.9 Summary

A search is presented for charged Higgs bosons decaying as
$\PH^{\pm}\to\Pgt^{\pm}\Pgngt$, using events recorded by the CMS experiment in
2016 at a center-of-mass energy of 13. Transverse mass distributions are
reconstructed in hadronic and leptonic final states and are found to agree
with the standard model expectation. Upper limits for the product of the
production cross section and the branching fraction to $\Pgt^{\pm}\Pgngt$ are
set at 95% confidence level for an mass ranging from 80to 3, including the
range close to the top quark mass. The observed limit ranges from $6\unit{pb}$
at 80to $5\unit{fb}$ at 3. The results are interpreted as constraints in the
parameter space of the minimal supersymmetric standard model
$m_{\Ph}^{\text{mod-}}$ benchmark scenario. In this scenario, all $\tanb$
values from 1 to 60 are excluded for charged Higgs boson masses up to 160.

###### Acknowledgements.

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

## References

  * [1] ATLAS Collaboration, “Observation of a new particle in the search for the standard model Higgs boson with the ATLAS detector at the LHC”,  Phys. Lett. B 716 (2012) 1, 10.1016/j.physletb.2012.08.020, arXiv:1207.7214.
  * [2] CMS Collaboration, “Observation of a new boson at a mass of 125 GeV with the CMS experiment at the LHC”,  Phys. Lett. B 716 (2012) 30, 10.1016/j.physletb.2012.08.021, arXiv:1207.7235.
  * [3] CMS Collaboration, “Observation of a new boson with mass near 125 GeV in pp collisions at $\sqrt{s}$ = 7 and 8 TeV”,  JHEP 06 (2013) 081, 10.1007/JHEP06(2013)081, arXiv:1303.4571.
  * [4] P. W. Higgs, “Broken symmetries, massless particles and gauge fields”,  Phys. Lett. 12 (1964) 132, 10.1016/0031-9163(64)91136-9.
  * [5] P. W. Higgs, “Broken symmetries and the masses of gauge bosons”,  Phys. Rev. Lett. 13 (1964) 508, 10.1103/PhysRevLett.13.508.
  * [6] G. S. Guralnik, C. R. Hagen, and T. W. B. Kibble, “Global conservation laws and massless particles”,  Phys. Rev. Lett. 13 (1964) 585, 10.1103/PhysRevLett.13.585.
  * [7] P. W. Higgs, “Spontaneous symmetry breakdown without massless bosons”,  Phys. Rev. 145 (1966) 1156, 10.1103/PhysRev.145.1156.
  * [8] T. W. B. Kibble, “Symmetry breaking in non-Abelian gauge theories”,  Phys. Rev. 155 (1967) 1554, 10.1103/PhysRev.155.1554.
  * [9] F. Englert and R. Brout, “Broken symmetry and the mass of gauge vector mesons”,  Phys. Rev. Lett. 13 (1964) 321, 10.1103/PhysRevLett.13.321.
  * [10] CMS Collaboration, “Constraints on the spin-parity and anomalous HVV couplings of the Higgs boson in proton collisions at 7 and 8 TeV”,  Phys. Rev. D 92 (2015) 012004, 10.1103/PhysRevD.92.012004, arXiv:1411.3441.
  * [11] ATLAS and CMS Collaborations, “Combined measurement of the Higgs boson mass in pp collisions at $\sqrt{s}=7$ and 8 TeV with the ATLAS and CMS experiments”,  Phys. Rev. Lett. 114 (2015) 191803, 10.1103/PhysRevLett.114.191803, arXiv:1503.07589.
  * [12] ATLAS Collaboration, “Study of the spin and parity of the Higgs boson in diboson decays with the ATLAS detector”,  Eur. Phys. J. C 75 (2015) 476, 10.1140/epjc/s10052-015-3685-1, arXiv:1506.05669. [Erratum: 10.1140/epjc/s10052-016-3934-y].
  * [13] ATLAS and CMS Collaborations, “Measurements of the Higgs boson production and decay rates and constraints on its couplings from a combined ATLAS and CMS analysis of the LHC pp collision data at $\sqrt{s}=7$ and 8 TeV”,  JHEP 08 (2016) 045, 10.1007/JHEP08(2016)045, arXiv:1606.02266.
  * [14] CMS Collaboration, “Measurements of properties of the Higgs boson decaying into the four-lepton final state in pp collisions at $\sqrt{s}=13$ TeV”,  JHEP 11 (2017) 047, 10.1007/JHEP11(2017)047, arXiv:1706.09936.
  * [15] G. C. Branco et al., “Theory and phenomenology of two-Higgs-doublet models”,  Phys. Rept. 516 (2012) 1, 10.1016/j.physrep.2012.02.002, arXiv:1106.0034.
  * [16] A. Djouadi, “The anatomy of electro-weak symmetry breaking. II. the Higgs bosons in the minimal supersymmetric model”,  Phys. Rept. 459 (2008) 1, 10.1016/j.physrep.2007.10.005, arXiv:hep-ph/0503173.
  * [17] G. Senjanovic and R. N. Mohapatra, “Exact left-right symmetry and spontaneous violation of parity”,  Phys. Rev. D 12 (1975) 1502, 10.1103/PhysRevD.12.1502.
  * [18] J. F. Gunion, R. Vega, and J. Wudka, “Higgs triplets in the standard model”,  Phys. Rev. D 42 (1990) 1673, 10.1103/PhysRevD.42.1673.
  * [19] H. Georgi and M. Machacek, “Doubly charged Higgs bosons”,  Nucl. Phys. B 262 (1985) 463, 10.1016/0550-3213(85)90325-6.
  * [20] C. Degrande et al., “Accurate predictions for charged Higgs production: Closing the $m_{\mathrm{h}^{\pm}}\sim m_{\mathrm{t}}$ window”,  Phys. Lett. B 772 (2017) 87, 10.1016/j.physletb.2017.06.037, arXiv:1607.05291.
  * [21] ALEPH, DELPHI, L3, OPAL and LEP Collaborations, “Search for charged Higgs bosons: combined results using LEP data”,  Eur. Phys. J. C 73 (2013) 2463, 10.1140/epjc/s10052-013-2463-1, arXiv:1301.6065.
  * [22] CDF Collaboration, “Search for Higgs bosons predicted in two-Higgs-doublet models via decays to tau lepton pairs in 1.96 TeV $\mathrm{p\overline{p}}$ collisions”,  Phys. Rev. Lett. 103 (2009) 201801, 10.1103/PhysRevLett.103.201801, arXiv:0906.1014.
  * [23] D0 Collaboration, “Search for Higgs bosons of the minimal supersymmetric standard model in $\mathrm{p\overline{p}}$ collisions at $\sqrt{s}=1.96$ TeV”,  Phys. Lett. B 710 (2012) 569, 10.1016/j.physletb.2012.03.021, arXiv:1112.5431.
  * [24] ATLAS Collaboration, “Search for charged Higgs bosons decaying via $\mathrm{H}^{+}\to\tau\nu$ in top quark pair events using pp collision data at $\sqrt{s}=7$ TeV with the ATLAS detector”,  JHEP 06 (2012) 039, 10.1007/JHEP06(2012)039, arXiv:1204.2760.
  * [25] CMS Collaboration, “Search for a light charged Higgs boson in top quark decays in pp collisions at $\sqrt{s}=7$ TeV”,  JHEP 07 (2012) 143, 10.1007/JHEP07(2012)143, arXiv:1205.5736.
  * [26] ATLAS Collaboration, “Search for charged Higgs bosons through the violation of lepton universality in $\mathrm{t\overline{t}}$ events using pp collision data at $\sqrt{s}=7$ TeV with the ATLAS experiment”,  JHEP 03 (2013) 076, 10.1007/JHEP03(2013)076, arXiv:1212.3572.
  * [27] ATLAS Collaboration, “Search for charged Higgs bosons decaying via $\mathrm{H}^{\pm}\rightarrow\tau^{\pm}\nu$ in fully hadronic final states using pp collision data at $\sqrt{s}=8$ TeV with the ATLAS detector”,  JHEP 03 (2015) 088, 10.1007/JHEP03(2015)088, arXiv:1412.6663.
  * [28] CMS Collaboration, “Search for a charged Higgs boson in pp collisions at $\sqrt{s}=8$ TeV”,  JHEP 11 (2015) 018, 10.1007/JHEP11(2015)018, arXiv:1508.07774.
  * [29] ATLAS Collaboration, “Search for charged Higgs bosons produced in association with a top quark and decaying via $\mathrm{H}^{\pm}\rightarrow\tau\nu$ using pp collision data recorded at $\sqrt{s}=13$ TeV by the ATLAS detector”,  Phys. Lett. B 759 (2016) 555, 10.1016/j.physletb.2016.06.017, arXiv:1603.09203.
  * [30] ATLAS Collaboration, “Search for charged Higgs bosons decaying via $\mathrm{H}^{\pm}\to\tau^{\pm}\nu_{\tau}$ in the $\tau$+jets and $\tau$+lepton final states with 36 fb-1 of pp collision data recorded at $\sqrt{s}=13$ TeV with the ATLAS experiment”,  JHEP 09 (2018) 139, 10.1007/JHEP09(2018)139, arXiv:1807.07915.
  * [31] ATLAS Collaboration, “Search for charged Higgs bosons in the $\mathrm{H}^{\pm}\rightarrow tb$ decay channel in pp collisions at $\sqrt{s}=8$ TeV using the ATLAS detector”,  JHEP 03 (2016) 127, 10.1007/JHEP03(2016)127, arXiv:1512.03704.
  * [32] ATLAS Collaboration, “Search for charged Higgs bosons decaying into top and bottom quarks at $\sqrt{s}$ = 13 TeV with the ATLAS detector”,  JHEP 11 (2018) 085, 10.1007/JHEP11(2018)085, arXiv:1808.03599.
  * [33] ATLAS Collaboration, “Search for a light charged Higgs boson in the decay channel $\mathrm{H}^{+}\to\mathrm{c}\overline{\mathrm{s}}$ in $\mathrm{t\overline{t}}$ events using pp collisions at $\sqrt{s}$ = 7 TeV with the ATLAS detector”,  Eur. Phys. J. C 73 (2013) 2465, 10.1140/epjc/s10052-013-2465-z, arXiv:1302.3694.
  * [34] CMS Collaboration, “Search for a light charged Higgs boson decaying to $\mathrm{c}\overline{\mathrm{s}}$ in pp collisions at $\sqrt{s}=8$ TeV”,  JHEP 12 (2015) 178, 10.1007/JHEP12(2015)178, arXiv:1510.04252.
  * [35] CMS Collaboration, “Search for a charged Higgs boson decaying to charm and bottom quarks in proton-proton collisions at $\sqrt{s}=$ 8 TeV”,  JHEP 11 (2018) 115, 10.1007/JHEP11(2018)115, arXiv:1808.06575.
  * [36] ATLAS Collaboration, “Search for a charged Higgs boson produced in the vector-boson fusion mode with decay $\mathrm{H}^{\pm}\to\mathrm{W}^{\pm}\mathrm{Z}$ using pp collisions at $\sqrt{s}=8$ TeV with the ATLAS experiment”,  Phys. Rev. Lett. 114 (2015) 231801, 10.1103/PhysRevLett.114.231801, arXiv:1503.04233.
  * [37] CMS Collaboration, “Search for charged Higgs bosons produced via vector boson fusion and decaying into a pair of W and Z bosons using pp collisions at $\sqrt{s}=13\text{ }\text{}\mathrm{TeV}$”,  Phys. Rev. Lett. 119 (2017) 141802, 10.1103/PhysRevLett.119.141802, arXiv:1705.02942.
  * [38] ATLAS Collaboration, “Search for additional heavy neutral Higgs and gauge bosons in the ditau final state produced in 36 fb-1 of pp collisions at $\sqrt{s}=13$ TeV with the ATLAS detector”,  JHEP 01 (2018) 055, 10.1007/JHEP01(2018)055, arXiv:1709.07242.
  * [39] CMS Collaboration, “Search for additional neutral MSSM Higgs bosons in the $\tau\tau$ final state in proton-proton collisions at $\sqrt{s}=13$ TeV”,  JHEP 09 (2018) 007, 10.1007/JHEP09(2018)007, arXiv:1803.06553.
  * [40] CMS Collaboration, “Search for beyond the standard model Higgs bosons decaying into a $\mathrm{b\overline{b}}$ pair in pp collisions at $\sqrt{s}=$ 13 TeV”,  JHEP 08 (2018) 113, 10.1007/JHEP08(2018)113, arXiv:1805.12191.
  * [41] A. Arbey, F. Mahmoudi, O. Stal, and T. Stefaniak, “Status of the charged Higgs boson in two Higgs doublet models”,  Eur. Phys. J. C 78 (2018) 182, 10.1140/epjc/s10052-018-5651-1, arXiv:1706.07414.
  * [42] CMS Collaboration, “The CMS trigger system”,  JINST 12 (2017) P01020, 10.1088/1748-0221/12/01/P01020, arXiv:1609.02366.
  * [43] CMS Collaboration, “The CMS experiment at the CERN LHC”,  JINST 3 (2008) S08004, 10.1088/1748-0221/3/08/S08004.
  * [44] J. Alwall et al., “The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations”,  JHEP 07 (2014) 079, 10.1007/JHEP07(2014)079, arXiv:1405.0301.
  * [45] P. Artoisenet, R. Frederix, O. Mattelaer, and R. Rietkerk, “Automatic spin-entangled decays of heavy resonances in Monte Carlo simulations”,  JHEP 03 (2013) 015, 10.1007/JHEP03(2013)015, arXiv:1212.3460.
  * [46] P. Nason, “A new method for combining NLO QCD with shower Monte Carlo algorithms”,  JHEP 11 (2004) 040, 10.1088/1126-6708/2004/11/040, arXiv:hep-ph/0409146.
  * [47] S. Frixione, P. Nason, and C. Oleari, “Matching NLO QCD computations with parton shower simulations: the POWHEG method”,  JHEP 11 (2007) 070, 10.1088/1126-6708/2007/11/070, arXiv:0709.2092.
  * [48] S. Alioli, P. Nason, C. Oleari, and E. Re, “A general framework for implementing NLO calculations in shower Monte Carlo programs: the POWHEG BOX”,  JHEP 06 (2010) 043, 10.1007/JHEP06(2010)043, arXiv:1002.2581.
  * [49] T. Ježo et al., “An NLO+PS generator for $\mathrm{t}\mathrm{\overline{t}}$ and Wt production and decay including non-resonant and interference effects”,  Eur. Phys. J. C 76 (2016) 691, 10.1140/epjc/s10052-016-4538-2, arXiv:1607.04538.
  * [50] S. Frixione, P. Nason, and G. Ridolfi, “A positive-weight next-to-leading-order Monte Carlo for heavy flavour hadroproduction”,  JHEP 09 (2007) 126, 10.1088/1126-6708/2007/09/126, arXiv:0707.3088.
  * [51] R. Frederix and S. Frixione, “Merging meets matching in MC@NLO”,  JHEP 12 (2012) 061, 10.1007/JHEP12(2012)061, arXiv:1209.6215.
  * [52] S. Alioli, P. Nason, C. Oleari, and E. Re, “NLO single-top production matched with shower in POWHEG: $s$\- and $t$-channel contributions”,  JHEP 09 (2009) 111, 10.1007/JHEP02(2010)011, arXiv:0907.4076. [Erratum: 10.1088/1126-6708/2009/09/111].
  * [53] E. Re, “Single-top Wt-channel production matched with parton showers using the POWHEG method”,  Eur. Phys. J. C 71 (2011) 1547, 10.1140/epjc/s10052-011-1547-z, arXiv:1009.2450.
  * [54] J. Alwall et al., “Comparative study of various algorithms for the merging of parton showers and matrix elements in hadronic collisions”,  Eur. Phys. J. C 53 (2008) 473, 10.1140/epjc/s10052-007-0490-5, arXiv:0706.2569.
  * [55] M. Czakon and A. Mitov, “Top++: A program for the calculation of the top-pair cross-section at hadron colliders”,  Comput. Phys. Commun. 185 (2014) 2930, 10.1016/j.cpc.2014.06.021, arXiv:1112.5675.
  * [56] N. Kidonakis, “Top quark production”, in  Proceedings, Helmholtz International Summer School on Physics of Heavy Quarks and Hadrons (HQ 2013), p. 139.  2014\.  arXiv:1311.0283.  10.3204/DESY-PROC-2013-03/Kidonakis.
  * [57] P. Kant et al., “HatHor for single top-quark production: Updated predictions and uncertainty estimates for single top-quark production in hadronic collisions”,  Comput. Phys. Commun. 191 (2015) 74, 10.1016/j.cpc.2015.02.001, arXiv:1406.4403.
  * [58] K. Melnikov and F. Petriello, “Electroweak gauge boson production at hadron colliders through ${O}(\alpha_{s}^{2})$”,  Phys. Rev. D 74 (2006) 114017, 10.1103/PhysRevD.74.114017, arXiv:hep-ph/0609070.
  * [59] J. M. Campbell, R. K. Ellis, and C. Williams, “Vector boson pair production at the LHC”,  JHEP 07 (2011) 018, 10.1007/JHEP07(2011)018, arXiv:1105.0020.
  * [60] NNPDF Collaboration, “Unbiased global determination of parton distributions and their uncertainties at NNLO and at LO”,  Nucl. Phys. B 855 (2012) 153, 10.1016/j.nuclphysb.2011.09.024, arXiv:1107.2652.
  * [61] CMS Collaboration, “Event generator tunes obtained from underlying event and multiparton scattering measurements”,  Eur. Phys. J. C 76 (2016) 155, 10.1140/epjc/s10052-016-3988-x, arXiv:1512.00815.
  * [62] CMS Collaboration, “Investigations of the impact of the parton shower tuning in PYTHIA 8 in the modelling of $\mathrm{t\overline{t}}$ at $\sqrt{s}=8$ and 13 TeV”, CMS Physics Analysis Summary CMS-PAS-TOP-16-021, 2016.
  * [63] GEANT4 Collaboration, “—a simulation toolkit”,  Nucl. Instrum. Meth. A 506 (2003) 250, 10.1016/S0168-9002(03)01368-8.
  * [64] CMS Collaboration, “Particle-flow reconstruction and global event description with the CMS detector”,  JINST 12 (2017) P10003, 10.1088/1748-0221/12/10/P10003, arXiv:1706.04965.
  * [65] K. Rose, “Deterministic annealing for clustering, compression, classification, regression, and related optimization problems”,  Proceedings of the IEEE 86 (1998) 2210, 10.1109/5.726788.
  * [66] M. Cacciari, G. P. Salam, and G. Soyez, “The anti-jet clustering algorithm”,  JHEP 04 (2008) 063, 10.1088/1126-6708/2008/04/063, arXiv:0802.1189.
  * [67] M. Cacciari, G. P. Salam, and G. Soyez, “FastJet user manual”,  Eur. Phys. J. C 72 (2012) 1896, 10.1140/epjc/s10052-012-1896-2, arXiv:1111.6097.
  * [68] CMS Collaboration, “Performance of electron reconstruction and selection with the CMS detector in proton-proton collisions at $\sqrt{s}=8$ TeV”,  JINST 10 (2015) P06005, 10.1088/1748-0221/10/06/P06005, arXiv:1502.02701.
  * [69] H. Voss, A. Höcker, J. Stelzer, and F. Tegenfeldt, “TMVA, the toolkit for multivariate data analysis with ROOT”, in  XIth International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT), p. 40.  2007\.  arXiv:physics/0703039.
  * [70] CMS Collaboration, “Performance of the CMS muon detector and muon reconstruction with proton-proton collisions at $\sqrt{s}=13$ TeV”,  JINST 13 (2018) P06015, 10.1088/1748-0221/13/06/P06015, arXiv:1804.04528.
  * [71] CMS Collaboration, “Jet energy scale and resolution in the CMS experiment in pp collisions at 8 TeV”,  JINST 12 (2017) P02014, 10.1088/1748-0221/12/02/P02014, arXiv:1607.03663.
  * [72] CMS Collaboration, “Jet algorithms performance in 13 TeV data”, CMS Physics Analysis Summary CMS-PAS-JME-16-003, 2017.
  * [73] CMS Collaboration, “Identification of b-quark jets with the CMS experiment”,  JINST 8 (2013) P04013, 10.1088/1748-0221/8/04/P04013, arXiv:1211.4462.
  * [74] CMS Collaboration, “Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV”,  JINST 13 (2018) P05011, 10.1088/1748-0221/13/05/P05011, arXiv:1712.07158.
  * [75] CMS Collaboration, “Reconstruction and identification of $\tau$ lepton decays to hadrons and $\nu_{\tau}$ at CMS”,  JINST 11 (2016) P01019, 10.1088/1748-0221/11/01/P01019, arXiv:1510.07488.
  * [76] CMS Collaboration, “Performance of reconstruction and identification of $\tau$ leptons decaying to hadrons and $\nu_{\tau}$ in pp collisions at $\sqrt{s}=$ 13 TeV”,  JINST 13 (2018) P10005, 10.1088/1748-0221/13/10/P10005, arXiv:1809.02816.
  * [77] CMS Collaboration, “Performance of missing transverse momentum in pp collisions at $\sqrt{s}=13$ TeV using the CMS detector”, CMS Physics Analysis Summary CMS-PAS-JME-17-001, 2018\.
  * [78] CMS Collaboration, “Performance of CMS muon reconstruction in pp collision events at $\sqrt{s}=7$ TeV”,  JINST 7 (2012) P10002, 10.1088/1748-0221/7/10/P10002, arXiv:1206.4071.
  * [79] D. P. Roy, “The hadronic tau decay signature of a heavy charged Higgs boson at LHC”,  Phys. Lett. B 459 (1999) 607, 10.1016/S0370-2693(99)00724-8, arXiv:hep-ph/9905542.
  * [80] ATLAS Collaboration, “Measurement of the inelastic proton-proton cross section at $\sqrt{s}=13$ TeV with the ATLAS detector at the LHC”,  Phys. Rev. Lett. 117 (2016) 182002, 10.1103/PhysRevLett.117.182002, arXiv:1606.02625.
  * [81] CMS Collaboration, “CMS luminosity measurements for the 2016 data taking period”, CMS Physics Analysis Summary CMS-PAS-LUM-17-001, 2017.
  * [82] J. Butterworth et al., “PDF4LHC recommendations for LHC Run II”,  J. Phys. G 43 (2016) 023001, 10.1088/0954-3899/43/2/023001, arXiv:1510.03865.
  * [83] P. Skands, S. Carrazza, and J. Rojo, “Tuning PYTHIA 8.1: the Monash 2013 tune”,  Eur. Phys. J. C 74 (2014) 3024, 10.1140/epjc/s10052-014-3024-y, arXiv:1404.5630.
  * [84] R. J. Barlow and C. Beeston, “Fitting using finite Monte Carlo samples”,  Comput. Phys. Commun. 77 (1993) 219, 10.1016/0010-4655(93)90005-W.
  * [85] T. Junk, “Confidence level computation for combining searches with small statistics”,  Nucl. Instrum. Meth. A 434 (1999) 435, 10.1016/S0168-9002(99)00498-2, arXiv:hep-ex/9902006.
  * [86] A. L. Read, “Presentation of search results: The CL${}_{\text{s}}$ technique”,  J. Phys. G 28 (2002) 2693, 10.1088/0954-3899/28/10/313.
  * [87] ATLAS and CMS Collaborations, The LHC Higgs Combination Group, “Procedure for the LHC Higgs boson search combination in Summer 2011”, Technical Report CMS-NOTE-2011-005, ATL-PHYS-PUB-2011-11, 2011.
  * [88] G. Cowan, K. Cranmer, E. Gross, and O. Vitells, “Asymptotic formulae for likelihood-based tests of new physics”,  Eur. Phys. J. C 71 (2011) 1554, 10.1140/epjc/s10052-011-1554-0, arXiv:1007.1727. [Erratum: 10.1140/epjc/s10052-013-2501-z].
  * [89] M. Carena et al., “MSSM Higgs boson searches at the LHC: Benchmark scenarios after the discovery of a Higgs-like particle”,  Eur. Phys. J. C 73 (2013) 2552, 10.1140/epjc/s10052-013-2552-1, arXiv:1302.7033.
  * [90] D. de Florian et al., “Handbook of LHC Higgs cross sections: 4. deciphering the nature of the Higgs sector”, CERN Report CERN-2017-002-M, 2016.  10.23731/CYRM-2017-002, arXiv:1610.07922.
  * [91] M. Flechl et al., “Improved cross-section predictions for heavy charged Higgs boson production at the LHC”,  Phys. Rev. D 91 (2015) 075015, 10.1103/PhysRevD.91.075015, arXiv:1409.5615.
  * [92] C. Degrande, M. Ubiali, M. Wiesemann, and M. Zaro, “Heavy charged Higgs boson production at the LHC”,  JHEP 10 (2015) 145, 10.1007/JHEP10(2015)145, arXiv:1507.02549.
  * [93] S. Dittmaier, M. Kramer, M. Spira, and M. Walser, “Charged-Higgs-boson production at the LHC: NLO supersymmetric QCD corrections”,  Phys. Rev. D 83 (2011) 055005, 10.1103/PhysRevD.83.055005, arXiv:0906.2648.
  * [94] E. L. Berger, T. Han, J. Jiang, and T. Plehn, “Associated production of a top quark and a charged Higgs boson”,  Phys. Rev. D 71 (2005) 115012, 10.1103/PhysRevD.71.115012, arXiv:hep-ph/0312286.

##  .10 The CMS Collaboration

Yerevan Physics Institute, Yerevan, Armenia
A.M. Sirunyan, A. Tumasyan Institut für Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, M. Dragicevic,
J. Erö, A. Escalante Del Valle, M. Flechl, R. Frühwirth1, V.M. Ghete, J.
Hrubec, M. Jeitler1, N. Krammer, I. Krätschmer, D. Liko, T. Madlener, I.
Mikulec, N. Rad, H. Rohringer, J. Schieck1, R. Schöfbeck, M. Spanring, D.
Spitzbart, 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, A. Lelek, M. Pieters, H.
Van Haevermaet, P. Van Mechelen, N. Van Remortel Vrije Universiteit Brussel,
Brussel, Belgium
S. Abu Zeid, F. Blekman, J. D’Hondt, J. De Clercq, K. Deroover, G. Flouris, D.
Lontkovskyi, S. Lowette, I. Marchesini, S. Moortgat, L. Moreels, Q. Python, K.
Skovpen, S. Tavernier, W. Van Doninck, P. Van Mulders, I. Van Parijs
Université Libre de Bruxelles, Bruxelles, Belgium
D. Beghin, B. Bilin, H. Brun, B. Clerbaux, G. De Lentdecker, H. Delannoy, B.
Dorney, G. Fasanella, L. Favart, 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, 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, M.E. Pol, P.
Rebello Teles Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil
E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato3, E. Coelho, E.M.
Da Costa, G.G. Da Silveira4, D. De Jesus Damiao, C. De Oliveira Martins, S.
Fonseca De Souza, H. Malbouisson, D. Matos Figueiredo, M. Melo De Almeida, C.
Mora Herrera, L. Mundim, H. Nogima, W.L. Prado Da Silva, L.J. Sanchez Rosas,
A. Santoro, A. Sznajder, M. Thiel, E.J. Tonelli Manganote3, F. Torres Da Silva
De Araujo, A. Vilela Pereira Universidade Estadual Paulista a, Universidade
Federal do ABC b, São Paulo, Brazil
S. Ahujaa, C.A. Bernardesa, L. Calligarisa, T.R. Fernandez Perez Tomeia, E.M.
Gregoresb, P.G. Mercadanteb, S.F. Novaesa, SandraS. Padulaa Institute for
Nuclear Research and Nuclear Energy, Bulgarian Academy of Sciences, Sofia,
Bulgaria
A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, A. Marinov, M. Misheva, M. Rodozov,
M. Shopova, G. Sultanov University of Sofia, Sofia, Bulgaria
A. Dimitrov, L. Litov, B. Pavlov, P. Petkov Beihang University, Beijing, China
W. Fang5, X. Gao5, L. Yuan Institute of High Energy Physics, Beijing, China
M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, Y. Chen, C.H. Jiang, D.
Leggat, H. Liao, Z. Liu, S.M. Shaheen6, A. Spiezia, J. Tao, E. Yazgan, H.
Zhang, S. Zhang6, J. Zhao State Key Laboratory of Nuclear Physics and
Technology, Peking University, Beijing, China
Y. Ban, G. Chen, A. Levin, J. Li, L. Li, Q. Li, Y. Mao, S.J. Qian, D. Wang
Tsinghua University, Beijing, China
Y. Wang Universidad de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, C.A. Carrillo Montoya, L.F. Chaparro Sierra, C. Florez,
C.F. González Hernández, M.A. Segura Delgado University of Split, Faculty of
Electrical Engineering, Mechanical Engineering and Naval Architecture, Split,
Croatia
B. Courbon, N. Godinovic, D. Lelas, I. Puljak, T. Sculac University of Split,
Faculty of Science, Split, Croatia
Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia
V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, M. Roguljic, A. Starodumov7,
T. Susa University of Cyprus, Nicosia, Cyprus
M.W. Ather, A. Attikis, M. Kolosova, G. Mavromanolakis, J. Mousa, C. Nicolaou,
F. Ptochos, P.A. Razis, H. Rykaczewski Charles University, Prague, Czech
Republic
M. Finger8, M. Finger Jr.8 Escuela Politecnica Nacional, Quito, Ecuador
E. Ayala Universidad San Francisco de Quito, Quito, Ecuador
E. Carrera Jarrin Academy of Scientific Research and Technology of the Arab
Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt
A.A. Abdelalim9,10, S. Elgammal11, 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, 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, M. Lotti, P.
Luukka, T. Mäenpää, H. Siikonen, E. Tuominen, J. Tuominiemi Lappeenranta
University of Technology, Lappeenranta, Finland
T. Tuuva IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
M. Besancon, F. Couderc, M. Dejardin, D. Denegri, J.L. Faure, F. Ferri, S.
Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, C. Leloup,
E. Locci, J. Malcles, G. Negro, J. Rander, A. Rosowsky, M.Ö. Sahin, M. Titov
Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Université
Paris-Saclay, Palaiseau, France
A. Abdulsalam12, C. Amendola, I. Antropov, F. Beaudette, P. Busson, C.
Charlot, R. Granier de Cassagnac, I. Kucher, A. Lobanov, J. Martin Blanco, C.
Martin Perez, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, J. Rembser, R.
Salerno, J.B. Sauvan, Y. Sirois, A.G. Stahl Leiton, A. Zabi, A. Zghiche
Université de Strasbourg, CNRS, IPHC UMR 7178, Strasbourg, France
J.-L. Agram13, J. Andrea, D. Bloch, G. Bourgatte, J.-M. Brom, E.C. Chabert, V.
Cherepanov, C. Collard, E. Conte13, J.-C. Fontaine13, D. Gelé, U. Goerlach, M.
Jansová, A.-C. Le Bihan, N. Tonon, P. Van Hove Centre de Calcul de l’Institut
National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3,
Villeurbanne, France
S. Gadrat Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3,
Institut de Physique Nucléaire de Lyon, Villeurbanne, France
S. Beauceron, C. Bernet, G. Boudoul, N. Chanon, R. Chierici, D. Contardo, P.
Depasse, H. El Mamouni, J. Fay, L. Finco, S. Gascon, M. Gouzevitch, G.
Grenier, B. Ille, F. Lagarde, I.B. Laktineh, H. Lattaud, M. Lethuillier, L.
Mirabito, S. Perries, A. Popov14, V. Sordini, G. Touquet, M. Vander Donckt, S.
Viret Georgian Technical University, Tbilisi, Georgia
T. Toriashvili15 Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze8 RWTH Aachen University, I. Physikalisches Institut, Aachen,
Germany
C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, M.P.
Rauch, C. Schomakers, J. Schulz, M. Teroerde, B. Wittmer RWTH Aachen
University, III. Physikalisches Institut A, Aachen, Germany
A. Albert, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, S. Ghosh, T. Hebbeker,
C. Heidemann, K. Hoepfner, H. Keller, L. Mastrolorenzo, M. Merschmeyer, A.
Meyer, P. Millet, S. Mukherjee, T. Pook, A. Pozdnyakov, M. Radziej, H.
Reithler, M. Rieger, A. Schmidt, D. Teyssier, S. Thüer RWTH Aachen University,
III. Physikalisches Institut B, Aachen, Germany
G. Flügge, O. Hlushchenko, T. Kress, T. Müller, A. Nehrkorn, A. Nowack, C.
Pistone, O. Pooth, D. Roy, H. Sert, A. Stahl16 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. Borras17, V. Botta, A. Campbell, P. Connor, C. Contreras-Campana, V.
Danilov, A. De Wit, M.M. Defranchis, C. Diez Pardos, D. Domínguez Damiani, G.
Eckerlin, T. Eichhorn, A. Elwood, E. Eren, E. Gallo18, A. Geiser, J.M. Grados
Luyando, A. Grohsjean, M. Guthoff, M. Haranko, A. Harb, H. Jung, M. Kasemann,
J. Keaveney, C. Kleinwort, J. Knolle, D. Krücker, W. Lange, T. Lenz, J.
Leonard, K. Lipka, W. Lohmann19, 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, A. Saibel, M. Savitskyi, P. Saxena, 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 University of Hamburg, Hamburg, Germany
R. Aggleton, S. Bein, L. Benato, A. Benecke, T. Dreyer, A. Ebrahimi, E.
Garutti, D. Gonzalez, P. Gunnellini, J. Haller, A. Hinzmann, A. Karavdina, G.
Kasieczka, R. Klanner, R. Kogler, N. Kovalchuk, S. Kurz, V. Kutzner, J. Lange,
D. Marconi, J. Multhaup, M. Niedziela, C.E.N. Niemeyer, D. Nowatschin, A.
Perieanu, A. Reimers, O. Rieger, C. Scharf, P. Schleper, S. Schumann, J.
Schwandt, J. Sonneveld, H. Stadie, G. Steinbrück, F.M. Stober, M. Stöver, B.
Vormwald, I. Zoi Karlsruher Institut fuer Technologie, Karlsruhe, Germany
M. Akbiyik, C. Barth, M. Baselga, S. Baur, E. Butz, R. Caspart, T. Chwalek, F.
Colombo, W. De Boer, A. Dierlamm, K. El Morabit, N. Faltermann, B. Freund, M.
Giffels, M.A. Harrendorf, F. Hartmann16, S.M. Heindl, U. Husemann, I.
Katkov14, S. Kudella, S. Mitra, M.U. Mozer, Th. Müller, M. Musich, M. Plagge,
G. Quast, K. Rabbertz, M. Schröder, I. Shvetsov, H.J. Simonis, R. Ulrich, S.
Wayand, M. Weber, T. Weiler, C. Wöhrmann, R. Wolf Institute of Nuclear and
Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece
G. Anagnostou, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas, G. Paspalaki
National and Kapodistrian University of Athens, Athens, Greece
A. Agapitos, G. Karathanasis, P. Kontaxakis, A. Panagiotou, I. Papavergou, N.
Saoulidou, 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. Bartók20, 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. Horvath21, 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
P. Raics, Z.L. Trocsanyi, B. Ujvari Indian Institute of Science (IISc),
Bangalore, India
S. Choudhury, J.R. Komaragiri, P.C. Tiwari National Institute of Science
Education and Research, HBNI, Bhubaneswar, India
S. Bahinipati23, C. Kar, P. Mal, K. Mandal, A. Nayak24, S. Roy Chowdhury, D.K.
Sahoo23, 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, A. Mehta, K.
Sandeep, S. Sharma, J.B. Singh 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. Bhardwaj25, M. Bharti25, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep25,
D. Bhowmik, S. Dey, S. Dutt25, S. Dutta, S. Ghosh, M. Maity26, K. Mondal, S.
Nandan, A. Purohit, P.K. Rout, A. Roy, G. Saha, S. Sarkar, T. Sarkar26, M.
Sharan, B. Singh25, S. Thakur25 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, P. Suggisetti 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, Sa. Jain, S.
Karmakar, S. Kumar, G. Majumder, K. Mazumdar, N. Sahoo 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. Chenarani27, E. Eskandari Tadavani, S.M. Etesami27, M. Khakzad, M.
Mohammadi Najafabadi, M. Naseri, F. Rezaei Hosseinabadi, B. Safarzadeh28, M.
Zeinali University College Dublin, Dublin, Ireland
M. Felcini, M. Grunewald INFN Sezione di Bari a, Università di Bari b,
Politecnico di Bari c, Bari, Italy
M. Abbresciaa,b, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L. Cristellaa,b,
N. De Filippisa,c, M. De Palmaa,b, A. Di Florioa,b, F. Erricoa,b, L. Fiorea,
A. Gelmia,b, G. Iasellia,c, M. Incea,b, S. Lezkia,b, G. Maggia,c, M. Maggia,
G. Minielloa,b, S. Mya,b, S. Nuzzoa,b, A. Pompilia,b, G. Pugliesea,c, R.
Radognaa, A. Ranieria, G. Selvaggia,b, A. Sharmaa, L. Silvestrisa, R.
Vendittia, P. Verwilligena 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, 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,29, S. Marcellinia, G. Masettia, A.
Montanaria, 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, 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,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
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,16, S. Di Guidaa,b,16,
M.E. Dinardoa,b, S. Fiorendia,b, S. Gennaia, A. Ghezzia,b, P. Govonia,b, M.
Malbertia,b, S. Malvezzia, D. Menascea, F. Monti, L. Moronia, M. Paganonia,b,
D. Pedrinia, S. Ragazzia,b, T. Tabarelli de Fatisa,b, D. Zuoloa,b INFN Sezione
di Napoli a, Università di Napoli ’Federico II’ b, Napoli, Italy, Università
della Basilicata c, Potenza, Italy, Università G. Marconi d, Roma, Italy
S. Buontempoa, N. Cavalloa,c, A. De Iorioa,b, A. Di Crescenzoa,b, F.
Fabozzia,c, F. Fiengaa, G. Galatia, A.O.M. Iorioa,b, L. Listaa, S.
Meolaa,d,16, P. Paoluccia,16, 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, P. De Castro Manzanoa, T. Dorigoa, U. Dossellia, F.
Gasparinia,b, U. Gasparinia,b, A. Gozzelinoa, S.Y. Hoh, S. Lacapraraa, P.
Lujan, M. Margonia,b, A.T. Meneguzzoa,b, J. Pazzinia,b, N. Pozzobona,b, M.
Presillab, P. Ronchesea,b, R. Rossina,b, F. Simonettoa,b, A. Tiko, E.
Torassaa, M. Tosia,b, S. Venturaa, 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
M. Biasinia,b, G.M. Bileia, C. Cecchia,b, D. Ciangottinia,b, L. Fanòa,b, P.
Laricciaa,b, R. Leonardia,b, E. Manonia, G. Mantovania,b, V. Mariania,b, M.
Menichellia, A. Rossia,b, A. Santocchiaa,b, D. Spigaa INFN Sezione di Pisa a,
Università di Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy
K. Androsova, P. Azzurria, G. Bagliesia, L. Bianchinia, T. Boccalia, L.
Borrello, R. Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, G. Fedia, F. Fioria,c,
L. Gianninia,c, A. Giassia, M.T. Grippoa, F. Ligabuea,c, E. Mancaa,c, G.
Mandorlia,c, A. Messineoa,b, F. Pallaa, A. Rizzia,b, G. Rolandi31, P.
Spagnoloa, R. Tenchinia, G. Tonellia,b, A. Venturia, P.G. Verdinia INFN
Sezione di Roma a, Sapienza Università di Roma b, Rome, Italy
L. Baronea,b, F. Cavallaria, M. Cipriania,b, D. Del Rea,b, E. Di Marcoa,b, M.
Diemoza, S. Gellia,b, E. Longoa,b, B. Marzocchia,b, P. Meridiania, G.
Organtinia,b, F. Pandolfia, R. Paramattia,b, F. Preiatoa,b, S. Rahatloua,b, C.
Rovellia, F. Santanastasioa,b INFN Sezione di Torino a, Università di Torino
b, Torino, Italy, Università del Piemonte Orientale c, Novara, Italy
N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, N. Bartosika,
R. Bellana,b, C. Biinoa, 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
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, J. Goh32, T.J. Kim Korea University, Seoul, Korea
S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, K. Lee, K.S. Lee, S.
Lee, J. Lim, S.K. Park, Y. Roh Sejong University, Seoul, Korea
H.S. Kim Seoul National University, Seoul, Korea
J. Almond, J. Kim, J.S. Kim, H. Lee, K. Lee, S. Lee, K. Nam, S.B. Oh, B.C.
Radburn-Smith, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu University of Seoul,
Seoul, Korea
D. Jeon, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park Sungkyunkwan University,
Suwon, Korea
Y. Choi, C. Hwang, J. Lee, I. Yu Riga Technical University, Riga, Latvia
V. Veckalns33 Vilnius University, Vilnius, Lithuania
V. Dudenas, A. Juodagalvis, J. Vaitkus National Centre for Particle Physics,
Universiti Malaya, Kuala Lumpur, Malaysia
Z.A. Ibrahim, M.A.B. Md Ali34, F. Mohamad Idris35, W.A.T. Wan Abdullah, M.N.
Yusli, Z. Zolkapli Universidad de Sonora (UNISON), Hermosillo, Mexico
J.F. Benitez, A. Castaneda Hernandez, J.A. Murillo Quijada 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
Cruz36, R. Lopez-Fernandez, J. Mejia Guisao, R.I. Rabadan-Trejo, M. Ramirez-
Garcia, G. Ramirez-Sanchez, R. Reyes-Almanza, A. Sanchez-Hernandez Universidad
Iberoamericana, Mexico City, Mexico
S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita
Universidad Autonoma de Puebla, Puebla, Mexico
J. Eysermans, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad
Autónoma de San Luis Potosí, San Luis Potosí, Mexico
A. Morelos Pineda University of Auckland, Auckland, New Zealand
D. Krofcheck University of Canterbury, Christchurch, New Zealand
S. Bheesette, P.H. Butler National Centre for Physics, Quaid-I-Azam
University, Islamabad, Pakistan
A. Ahmad, M. Ahmad, M.I. Asghar, Q. Hassan, H.R. Hoorani, W.A. Khan, M.A.
Shah, M. Shoaib, M. Waqas National Centre for Nuclear Research, Swierk, Poland
H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Górski, M. Kazana, M.
Szleper, P. Traczyk, P. Zalewski Institute of Experimental Physics, Faculty of
Physics, University of Warsaw, Warsaw, Poland
K. Bunkowski, A. Byszuk37, K. Doroba, A. Kalinowski, M. Konecki, J.
Krolikowski, M. Misiura, M. Olszewski, A. Pyskir, M. Walczak Laboratório de
Instrumentação e Física Experimental de Partículas, Lisboa, Portugal
M. Araujo, P. Bargassa, C. Beirão Da Cruz E Silva, A. Di Francesco, P.
Faccioli, B. Galinhas, M. Gallinaro, J. Hollar, N. Leonardo, J. Seixas, G.
Strong, O. Toldaiev, J. Varela Joint Institute for Nuclear Research, Dubna,
Russia
S. Afanasiev, P. Bunin, M. Gavrilenko, I. Golutvin, I. Gorbunov, A. Kamenev,
V. Karjavine, A. Lanev, A. Malakhov, V. Matveev38,39, P. Moisenz, V. Palichik,
V. Perelygin, S. Shmatov, S. Shulha, N. Skatchkov, V. Smirnov, N. Voytishin,
A. Zarubin Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg),
Russia
V. Golovtsov, Y. Ivanov, V. Kim40, E. Kuznetsova41, 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, A. Shabanov, D. Tlisov, A. Toropin Institute for
Theoretical and Experimental Physics, Moscow, Russia
V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G.
Safronov, A. Spiridonov, A. Stepennov, V. Stolin, M. Toms, E. Vlasov, A.
Zhokin Moscow Institute of Physics and Technology, Moscow, Russia
T. Aushev National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
M. Chadeeva42, S. Polikarpov42, E. Popova, V. Rusinov P.N. Lebedev Physical
Institute, Moscow, Russia
V. Andreev, M. Azarkin, I. Dremin39, M. Kirakosyan, A. Terkulov Skobeltsyn
Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow,
Russia
A. Belyaev, E. Boos, V. Bunichev, M. Dubinin43, 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. Barnyakov44, V. Blinov44, T. Dimova44, L. Kardapoltsev44, Y. Skovpen44
Institute for High Energy Physics of National Research Centre ’Kurchatov
Institute’, Protvino, Russia
I. Azhgirey, I. Bayshev, S. Bitioukov, V. Kachanov, A. Kalinin, D.
Konstantinov, P. Mandrik, V. Petrov, R. Ryutin, S. Slabospitskii, A. Sobol, S.
Troshin, N. Tyurin, A. Uzunian, A. Volkov National Research Tomsk Polytechnic
University, Tomsk, Russia
A. Babaev, S. Baidali, V. Okhotnikov University of Belgrade: Faculty of
Physics and VINCA Institute of Nuclear Sciences
P. Adzic45, P. Cirkovic, D. Devetak, M. Dordevic, P. Milenovic46, 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, S. Sánchez Navas, 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, J.M. Vizan Garcia Instituto de Física de Cantabria (IFCA),
CSIC-Universidad de Cantabria, Santander, Spain
I.J. Cabrillo, A. Calderon, B. Chazin Quero, J. Duarte Campderros, M.
Fernandez, P.J. Fernández Manteca, A. García Alonso, J. Garcia-Ferrero, G.
Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, P. Martinez Ruiz del
Arbol, F. Matorras, J. Piedra Gomez, C. Prieels, T. Rodrigo, A. Ruiz-Jimeno,
L. Scodellaro, N. Trevisani, I. Vila, R. Vilar Cortabitarte University of
Ruhuna, Department of Physics, Matara, Sri Lanka
N. Wickramage CERN, European Organization for Nuclear Research, Geneva,
Switzerland
D. Abbaneo, B. Akgun, E. Auffray, G. Auzinger, P. Baillon, A.H. Ball, D.
Barney, J. Bendavid, M. Bianco, A. Bocci, C. Botta, E. Brondolin, T.
Camporesi, M. Cepeda, G. Cerminara, E. Chapon, Y. Chen, G. Cucciati, D.
d’Enterria, A. Dabrowski, N. Daci, V. Daponte, A. David, A. De Roeck, N.
Deelen, M. Dobson, M. Dünser, N. Dupont, A. Elliott-Peisert, F.
Fallavollita47, D. Fasanella, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, A.
Gilbert, K. Gill, F. Glege, M. Gruchala, M. Guilbaud, D. Gulhan, J. Hegeman,
C. Heidegger, Y. Iiyama, V. Innocente, G.M. Innocenti, A. Jafari, P. Janot, O.
Karacheban19, J. Kieseler, A. Kornmayer, 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. Pantaleo16, L. Pape, E. Perez, M. Peruzzi, A.
Petrilli, G. Petrucciani, A. Pfeiffer, M. Pierini, F.M. Pitters, D. Rabady, A.
Racz, M. Rovere, H. Sakulin, C. Schäfer, C. Schwick, M. Selvaggi, A. Sharma,
P. Silva, P. Sphicas48, A. Stakia, J. Steggemann, D. Treille, A. Tsirou, A.
Vartak, M. Verzetti, W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland
L. Caminada49, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C.
Kaestli, D. Kotlinski, U. Langenegger, T. Rohe, S.A. Wiederkehr ETH Zurich -
Institute for Particle Physics and Astrophysics (IPA), Zurich, Switzerland
M. Backhaus, L. Bäni, P. Berger, 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, 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. Amsler50, D. Brzhechko, M.F. Canelli, A. De Cosa, R. Del
Burgo, S. Donato, C. Galloni, T. Hreus, 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, R. Khurana, 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, Y.F. Liu, R.-S. Lu, E.
Paganis, A. Psallidas, A. Steen Chulalongkorn University, Faculty of Science,
Department of Physics, Bangkok, Thailand
B. Asavapibhop, N. Srimanobhas, N. Suwonjandee Çukurova University, Physics
Department, Science and Art Faculty, Adana, Turkey
A. Bat, F. Boran, S. Damarseckin, Z.S. Demiroglu, F. Dolek, C. Dozen, I.
Dumanoglu, E. Eskut, G. Gokbulut, Y. Guler, E. Gurpinar, I. Hos51, C. Isik,
E.E. Kangal52, O. Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G. Onengut,
K. Ozdemir53, A. Polatoz, D. Sunar Cerci54, B. Tali54, U.G. Tok, S. Turkcapar,
I.S. Zorbakir, C. Zorbilmez Middle East Technical University, Physics
Department, Ankara, Turkey
B. Isildak55, G. Karapinar56, M. Yalvac, M. Zeyrek Bogazici University,
Istanbul, Turkey
I.O. Atakisi, E. Gülmez, M. Kaya57, O. Kaya58, Ö. Özçelik, S. Ozkorucuklu59,
S. Tekten, E.A. Yetkin60 Istanbul Technical University, Istanbul, Turkey
M.N. Agaras, A. Cakir, K. Cankocak, Y. Komurcu, S. Sen61 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, J.J. Brooke, D. Burns, E. Clement, D. Cussans, O. Davignon, H.
Flacher, J. Goldstein, G.P. Heath, H.F. Heath, L. Kreczko, D.M. Newbold62, S.
Paramesvaran, B. Penning, T. Sakuma, 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, 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, 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, J. Nash64, A. Nikitenko7, V. Palladino, M. Pesaresi, D.M.
Raymond, A. Richards, A. Rose, E. Scott, C. Seez, A. Shtipliyski, G. Singh, M.
Stoye, T. Strebler, S. Summers, A. Tapper, K. Uchida, T. Virdee16, N. Wardle,
D. Winterbottom, J. Wright, S.C. Zenz Brunel University, Uxbridge, United
Kingdom
J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, C.K. Mackay, A. Morton, I.D. Reid,
L. Teodorescu, S. Zahid Baylor University, Waco, USA
K. Call, J. Dittmann, K. Hatakeyama, H. Liu, C. Madrid, B. McMaster, N.
Pastika, C. Smith Catholic University of America, Washington, DC, USA
R. Bartek, A. Dominguez The University of Alabama, Tuscaloosa, USA
A. Buccilli, S.I. Cooper, C. Henderson, P. Rumerio, C. West Boston University,
Boston, USA
D. Arcaro, T. Bose, 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. Hogan65, K.H.M. Kwok, E. Laird, G. Landsberg, J. Lee, Z. Mao, M. Narain,
S. Sagir66, R. Syarif, E. Usai, D. Yu University of California, Davis, Davis,
USA
R. Band, C. Brainerd, R. Breedon, D. Burns, M. Calderon De La Barca Sanchez,
M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk,
W. Ko, O. Kukral, R. Lander, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout,
M. Shi, D. Stolp, D. Taylor, K. Tos, M. Tripathi, Z. Wang, F. Zhang University
of California, Los Angeles, USA
M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, S. Erhan, A. Florent, J.
Hauser, M. Ignatenko, N. Mccoll, S. Regnard, D. Saltzberg, C. Schnaible, V.
Valuev University of California, Riverside, Riverside, USA
E. Bouvier, K. Burt, R. Clare, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, G.
Karapostoli, E. Kennedy, F. Lacroix, O.R. Long, M. Olmedo Negrete, M.I.
Paneva, W. Si, L. Wang, H. Wei, S. Wimpenny, B.R. Yates University of
California, San Diego, La Jolla, USA
J.G. Branson, P. Chang, S. Cittolin, M. Derdzinski, R. Gerosa, D. Gilbert, B.
Hashemi, A. Holzner, D. Klein, G. Kole, V. Krutelyov, J. Letts, M.
Masciovecchio, S. May, D. Olivito, S. Padhi, M. Pieri, V. Sharma, M. Tadel, 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, C. Campagnari, M. Citron, V. Dutta, M. Franco Sevilla,
L. Gouskos, R. Heller, J. Incandela, H. Mei, A. Ovcharova, H. Qu, J. Richman,
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, 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, E. MacDonald, T. Mulholland,
R. Patel, A. Perloff, K. Stenson, K.A. Ulmer, S.R. Wagner Cornell University,
Ithaca, USA
J. Alexander, J. Chaves, Y. Cheng, J. Chu, A. Datta, K. Mcdermott, N. Mirman,
J.R. Patterson, D. Quach, A. Rinkevicius, A. Ryd, L. Skinnari, L. Soffi, S.M.
Tan, Z. Tao, J. Thom, J. Tucker, P. Wittich, M. Zientek Fermi National
Accelerator Laboratory, Batavia, USA
S. Abdullin, M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, A. Apyan, S.
Banerjee, L.A.T. Bauerdick, A. Beretvas, J. Berryhill, P.C. Bhat, K. Burkett,
J.N. Butler, A. Canepa, G.B. Cerati, H.W.K. Cheung, F. Chlebana, M. Cremonesi,
J. Duarte, V.D. Elvira, J. Freeman, Z. Gecse, E. Gottschalk, L. Gray, D.
Green, S. Grünendahl, O. Gutsche, J. Hanlon, R.M. Harris, S. Hasegawa, J.
Hirschauer, Z. Hu, B. Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, B.
Klima, M.J. Kortelainen, B. Kreis, S. Lammel, D. Lincoln, R. Lipton, M. Liu,
T. Liu, J. Lykken, K. Maeshima, J.M. Marraffino, D. Mason, P. McBride, P.
Merkel, S. Mrenna, S. Nahn, V. O’Dell, K. Pedro, C. Pena, O. Prokofyev, G.
Rakness, F. Ravera, A. Reinsvold, L. Ristori, A. Savoy-Navarro67, B.
Schneider, E. Sexton-Kennedy, A. Soha, W.J. Spalding, L. Spiegel, S. Stoynev,
J. Strait, N. Strobbe, L. Taylor, S. Tkaczyk, N.V. Tran, L. Uplegger, E.W.
Vaandering, C. Vernieri, M. Verzocchi, R. Vidal, M. Wang, H.A. Weber
University of Florida, Gainesville, USA
D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerhoff, L. Cadamuro,
A. Carnes, D. Curry, R.D. Field, S.V. Gleyzer, B.M. Joshi, J. Konigsberg, A.
Korytov, K.H. Lo, P. Ma, K. Matchev, 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
A. Ackert, T. Adams, A. Askew, S. Hagopian, V. Hagopian, K.F. Johnson, T.
Kolberg, G. Martinez, T. Perry, H. Prosper, A. Saha, C. Schiber, R. Yohay
Florida Institute of Technology, Melbourne, USA
M.M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, M.
Rahmani, T. Roy, M. Saunders, 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, M.B. Tonjes, N. Varelas, H. Wang, X. Wang, Z. Wu, J. Zhang
The University of Iowa, Iowa City, USA
M. Alhusseini, B. Bilki68, W. Clarida, K. Dilsiz69, S. Durgut, R.P.
Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, A. Mestvirishvili, A.
Moeller, J. Nachtman, H. Ogul70, Y. Onel, F. Ozok71, A. Penzo, C. Snyder, E.
Tiras, J. Wetzel Johns Hopkins University, Baltimore, USA
B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A.V. Gritsan,
W.T. Hung, P. Maksimovic, J. Roskes, U. Sarica, M. Swartz, M. Xiao The
University of Kansas, Lawrence, USA
A. Al-bataineh, P. Baringer, A. Bean, S. Boren, J. Bowen, A. Bylinkin, J.
Castle, S. Khalil, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, C.
Rogan, S. Sanders, E. Schmitz, J.D. Tapia Takaki, Q. Wang Kansas State
University, Manhattan, USA
S. Duric, A. Ivanov, K. Kaadze, D. Kim, Y. Maravin, D.R. Mendis, T. Mitchell,
A. Modak, A. Mohammadi 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, V. Azzolini, 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, Sh. Jain, S. Kalafut, M. Krohn, 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, F. Golf, R. Gonzalez Suarez,
R. Kamalieddin, I. Kravchenko, J. Monroy, J.E. Siado, G.R. Snow, B. Stieger
State University of New York at Buffalo, Buffalo, USA
A. Godshalk, C. Harrington, I. Iashvili, A. Kharchilava, C. Mclean, D. Nguyen,
A. Parker, S. Rappoccio, B. Roozbahani Northeastern University, Boston, USA
G. Alverson, E. Barberis, C. Freer, Y. Haddad, A. Hortiangtham, G. Madigan,
D.M. Morse, T. Orimoto, A. Tishelman-charny, T. Wamorkar, B. Wang, A.
Wisecarver, D. Wood Northwestern University, Evanston, USA
S. Bhattacharya, J. Bueghly, O. Charaf, 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, F. Meng, C. Mueller,
Y. Musienko38, 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, L. Antonelli, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, C.
Hill, W. Ji, A. Lefeld, T.Y. Ling, W. Luo, 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 University of Puerto Rico, Mayaguez, USA
S. Malik, S. Norberg Purdue University, West Lafayette, USA
A. Barker, V.E. Barnes, S. Das, L. Gutay, M. Jones, A.W. Jung, A. Khatiwada,
B. Mahakud, D.H. Miller, N. Neumeister, C.C. Peng, S. Piperov, H. Qiu, J.F.
Schulte, J. Sun, F. Wang, R. Xiao, W. Xie Purdue University Northwest,
Hammond, USA
T. Cheng, J. Dolen, N. Parashar Rice University, Houston, USA
Z. Chen, K.M. Ecklund, S. Freed, F.J.M. Geurts, M. Kilpatrick, Arun Kumar, W.
Li, B.P. Padley, R. Redjimi, J. Roberts, J. Rorie, W. Shi, Z. Tu, A. Zhang
University of Rochester, Rochester, USA
A. Bodek, P. de Barbaro, R. Demina, Y.t. Duh, J.L. Dulemba, C. Fallon, T.
Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs, A.
Khukhunaishvili, E. Ranken, P. Tan, R. Taus Rutgers, The State University of
New Jersey, Piscataway, USA
B. Chiarito, J.P. Chou, Y. Gershtein, E. Halkiadakis, A. Hart, M. Heindl, E.
Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, 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, P.R. Dudero, 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, 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
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, N. Smith, W.H. Smith,
N. Woods †: Deceased
1: Also at Vienna University of Technology, Vienna, Austria
2: Also at IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
3: Also at Universidade Estadual de Campinas, Campinas, Brazil
4: Also at Federal University of Rio Grande do Sul, Porto Alegre, Brazil
5: Also at Université Libre de Bruxelles, Bruxelles, Belgium
6: Also at University of Chinese Academy of Sciences, Beijing, China
7: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia
8: Also at Joint Institute for Nuclear Research, Dubna, Russia
9: Also at Helwan University, Cairo, Egypt
10: Now at Zewail City of Science and Technology, Zewail, Egypt
11: Now at British University in Egypt, Cairo, Egypt
12: Also at Department of Physics, King Abdulaziz University, Jeddah, Saudi
Arabia
13: Also at Université de Haute Alsace, Mulhouse, France
14: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State
University, Moscow, Russia
15: Also at Tbilisi State University, Tbilisi, Georgia
16: Also at CERN, European Organization for Nuclear Research, Geneva,
Switzerland
17: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
18: Also at University of Hamburg, Hamburg, Germany
19: Also at Brandenburg University of Technology, Cottbus, Germany
20: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary
21: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
22: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
23: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India
24: Also at Institute of Physics, Bhubaneswar, India
25: Also at Shoolini University, Solan, India
26: Also at University of Visva-Bharati, Santiniketan, India
27: Also at Isfahan University of Technology, Isfahan, Iran
28: Also at Plasma Physics Research Center, Science and Research Branch,
Islamic Azad University, Tehran, Iran
29: Also at ITALIAN NATIONAL AGENCY FOR NEW TECHNOLOGIES, ENERGY AND
SUSTAINABLE ECONOMIC DEVELOPMENT, Bologna, 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 Kyung Hee University, Department of Physics, Seoul, Korea
33: Also at Riga Technical University, Riga, Latvia
34: Also at International Islamic University of Malaysia, Kuala Lumpur,
Malaysia
35: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia
36: Also at Consejo Nacional de Ciencia y Tecnología, Mexico City, Mexico
37: Also at Warsaw University of Technology, Institute of Electronic Systems,
Warsaw, Poland
38: Also at Institute for Nuclear Research, Moscow, Russia
39: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
40: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
41: Also at University of Florida, Gainesville, USA
42: Also at P.N. Lebedev Physical Institute, Moscow, Russia
43: Also at California Institute of Technology, Pasadena, USA
44: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
45: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
46: Also at University of Belgrade, Belgrade, Serbia
47: Also at INFN Sezione di Pavia a, Università di Pavia b, Pavia, Italy
48: Also at National and Kapodistrian University of Athens, Athens, Greece
49: Also at Universität Zürich, Zurich, Switzerland
50: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna,
Austria
51: Also at Istanbul Aydin University, Istanbul, Turkey
52: Also at Mersin University, Mersin, Turkey
53: Also at Piri Reis University, Istanbul, Turkey
54: Also at Adiyaman University, Adiyaman, Turkey
55: Also at Ozyegin University, Istanbul, Turkey
56: Also at Izmir Institute of Technology, Izmir, Turkey
57: Also at Marmara University, Istanbul, Turkey
58: Also at Kafkas University, Kars, Turkey
59: Also at Istanbul University, Istanbul, Turkey
60: Also at Istanbul Bilgi University, Istanbul, Turkey
61: Also at Hacettepe University, Ankara, Turkey
62: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom
63: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
64: Also at Monash University, Faculty of Science, Clayton, Australia
65: Also at Bethel University, St. Paul, USA
66: Also at Karamanoğlu Mehmetbey University, Karaman, Turkey
67: Also at Purdue University, West Lafayette, USA
68: Also at Beykent University, Istanbul, Turkey
69: Also at Bingol University, Bingol, Turkey
70: Also at Sinop University, Sinop, Turkey
71: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey
72: Also at Texas A&M University at Qatar, Doha, Qatar
73: Also at Kyungpook National University, Daegu, Korea
74: Also at University of Hyderabad, Hyderabad, India