TOP-17-008

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TOP-17-008

# Measurement of the top quark mass in the all-jets final state at
$\sqrt{s}=13\TeV$ and combination with the lepton+jets channel

###### Abstract

A top quark mass measurement is performed using $35.9\fbinv$ of LHC proton-
proton collision data collected with the CMS detector at $\sqrt{s}=13\TeV$.
The measurement uses the all-jets final state. A kinematic fit is performed to
reconstruct the decay of the system and suppress the multijet background.
Using the ideogram method, the top quark mass ($m_{\cPqt}$) is determined,
simultaneously constraining an additional jet energy scale factor (JSF). The
resulting value of $m_{\cPqt}=172.34\pm 0.20\,\text{(stat+JSF)}\pm
0.70\syst\GeV$ is in good agreement with previous measurements. In addition, a
combined measurement that uses the lepton+jets and all-jets final states is
presented, using the same mass extraction method, and provides an $m_{\cPqt}$
measurement of $172.26\pm 0.07\,\text{(stat+JSF)}\pm 0.61\syst\GeV$. This is
the first combined $m_{\cPqt}$ extraction from the lepton+jets and all-jets
channels through a single likelihood function.

##  0.1 Introduction

The top quark [1, 2] is the most massive known fundamental particle and its
mass $m_{\cPqt}$ is an important parameter of the standard model (SM) of
particle physics. Precise measurements of $m_{\cPqt}$ can be used to test the
internal consistency of the SM [3, 4, 5] and to search for new physical
phenomena. Since the top quark dominates the higher-order corrections to the
Higgs boson mass, a precise $m_{\cPqt}$ determination is crucial to put
constraints on the stability of the electroweak vacuum [6, 7].

At the CERN LHC, top quarks are predominantly produced in quark-antiquark
pairs () through the gluon fusion process, and decay almost exclusively to a
bottom quark and a boson. Each event can be classified through the decays of
the bosons. Events in the all-jets final state correspond to those that have
both $\PW$ bosons decaying further into $\Pq\Paq^{\prime}$ pairs, while events
in the lepton+jets final state have one boson decaying to a charged lepton and
a neutrino.

This paper presents a measurement of $m_{\cPqt}$ obtained in the all-jets
decay channel using proton-proton ($\Pp\Pp$) collision data taken in 2016 by
the CMS experiment at a center-of-mass energy of $\sqrt{s}=13\TeV$,
corresponding to an integrated luminosity of $35.9\fbinv$. The two bottom
quarks and the four light quarks from the decay are all required to be
physically separated in the laboratory frame of reference, and the nominal
experimental signature is therefore characterized by six jets in the detector.

Although this final state provides the largest branching fraction of all
decays, this measurement of $m_{\cPqt}$ is particularly challenging, because
of the large background from multijet production. A kinematic fit of the decay
products to the hypothesis is therefore employed to separate signal from
background events.

The value of $m_{\cPqt}$ is extracted using the ideogram method [8, 9], which
is based on a likelihood function that depends either just on the mass
parameter $m_{\cPqt}$, or on $m_{\cPqt}$ combined with an additional jet
energy scale factor (JSF). In the second case, the invariant mass of the two
jets associated with the $\PW\rightarrow\cPq\cPaq^{\prime}$ decay serves as an
observable to directly estimate the JSF.

Previous measurements in this decay channel have been performed by Tevatron
and LHC experiments at lower center-of-mass energies [10, 11, 12, 13, 14]. The
most precise one of these has been obtained by CMS at $\sqrt{s}=8\TeV$,
resulting in a mass of $m_{\cPqt}=172.32\pm 0.25\,\text{(stat+JSF)}\pm
0.59\syst\GeV$. Combining the results of several measurements using different
final states at $\sqrt{s}=7$ and $8\TeV$, ATLAS and CMS reported values of
$m_{\cPqt}=172.69\pm 0.48\GeV$ [15] and $172.44\pm 0.48\GeV$ [12],
respectively, while a value of $m_{\cPqt}=174.30\pm 0.65\GeV$ was obtained by
combining the Tevatron results [16].

The top quark mass has been measured for the first time with $\Pp\Pp$ data at
$\sqrt{s}=13\TeV$, using the lepton+jets channel [17], yielding a value of
$m_{\cPqt}=172.25\pm 0.08\,\text{(stat+JSF)}\pm 0.62\syst\GeV$. A measurement
using both all-jets and lepton+jets events is presented here. This is possible
since the two measurements use the same mass extraction method, so a single
likelihood can be used, rather than just combining the two results
statistically. With this approach, no assumptions on correlations between
different uncertainties of the measurements have to be made. This is the first
report of a combined $m_{\cPqt}$ measurement in the lepton+jets and all-jets
final states using a single likelihood function.

##  0.2 The CMS detector and event reconstruction

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 (HCAL), each composed of a barrel and two endcap sections. Forward
calorimeters extend the pseudorapidity ($\eta$) coverage provided by the
barrel and endcap detectors. 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 [18]. The
first level, composed of custom hardware processors, uses information from the
calorimeters and muon detectors to select events within a time interval of 4,
resulting in a trigger rate of around 100kHz. 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.

The particle-flow (PF) algorithm [19] aims to reconstruct and identify each
individual particle in an event, with an optimized combination of information
from the various elements of the CMS detector. The energy of photons is
obtained from the ECAL measurement. The energy of electrons is determined from
a combination of the electron momentum at the primary interaction vertex as
determined by the tracker, the energy of the corresponding ECAL cluster, and
the energy sum of all bremsstrahlung photons spatially compatible with
originating from the electron track. The energy of muons is obtained from the
curvature of the corresponding track. The energy of charged hadrons is
determined from a combination of their momentum measured in the tracker and
the matching ECAL and HCAL energy deposits, corrected for zero-suppression
effects and for the response function of the calorimeters to hadronic showers.
Finally, the energy of neutral hadrons is obtained from the corresponding
corrected ECAL and HCAL energy.

The reconstructed vertex with the largest value of summed physics-object
$\pt^{2}$ is taken to be the primary proton-proton interaction vertex. The
physics objects are the jets, clustered using the jet finding algorithm [20,
21] with the tracks assigned to the vertex as inputs, and the associated
missing transverse momentum, taken as the negative vector sum of the
transverse momentum of those jets.

Jets are clustered from PF objects using the anti-algorithm with a distance
parameter of 0.4 [22, 20, 21]. 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.
Additional proton-proton interactions within the same or nearby bunch
crossings (pileup) can contribute additional tracks and calorimetric energy
depositions to the jet momentum. To mitigate this effect, tracks identified to
be originating from pileup vertices are discarded, and an offset correction is
applied to correct for remaining contributions from neutral hadrons. Jet
energy corrections (JECs) 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, photon+jet, +jet, and multijet
events are used to account for any residual differences in the jet energy
scale in data and simulation [23]. Additional selection criteria are applied
to each jet to remove jets dominated by anomalous contributions from various
subdetector components or reconstruction failures [24].

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. [25].

##  0.3 Event selection and simulation

Only jets with $\pt>30\GeV$ reconstructed within $\abs{\eta}<2.4$ are used in
the analysis. For the identification of jets originating from the
hadronization of quarks, the combined secondary vertex algorithm (CSVv2)
tagger is used [26]. The chosen working point provides an identification
efficiency of approximately $50\%$ with a probability of misidentifying a
$\PQu$/$\PQd$/$\PQs$ quark jet or gluon jet as being a bottom jet of
approximately $0.1\%$, and a misidentification probability for $\PQc$ quark
jets of $2\%$. The hadronic activity, used for the event selection, is defined
as the scalar sum of all jets in the event,

$\HT\equiv\sum_{\text{jets}}\pt.$

Data events are selected using an HLT that requires the presence of at least
six PF jets with $\pt>40\GeV$ and $\HT>450\GeV$. Additionally, the HLT
requires at least one jet to be tagged.

In the offline selection, an event must contain a well reconstructed vertex
localized within 24 cm in the $z$ direction and 2in the $x$–$y$ plane around
the nominal interaction point. Selected events are required to contain at
least six jets, at least two of which have to be tagged as jets. The sixth jet
($\text{jet}_{6}$), ordered in decreasing , must fulfill
$\pt(\text{jet}_{6})>40\GeV$, and $\HT>450\GeV$ is required. The two jets must
be separated in $\Delta R=\sqrt{\smash[b]{\Delta\phi^{2}+\Delta\eta^{2}}}$ by
$\Delta R(\cPqb\cPaqb)>2.0$.

The signal is simulated at an $m_{\cPqt}$ of $172.5\GeV$ using the v2 [27, 28,
29] matrix-element (ME) generator in next-to-leading order (NLO) perturbative
quantum chromodynamics (QCD). For the parton distribution functions (PDFs),
the NNPDF3.0 NLO set [30] is used with the strong coupling constant value of
$\alpS=0.118$. This is one of the first PDF sets to include the total cross
section measurements from ATLAS and CMS at $\sqrt{s}=7$ and $8\TeV$ as input.
The parton shower (PS) and hadronization are handled by 8.219 [31] using the
CUETP8M2T4 tune [32, 33] and is used to simulate the response of the CMS
detector [34]. The simulated signal sample is normalized to the integrated
luminosity of the data sample using a cross section of
$\sigma_{\ttbar}=832\unit{pb}$, calculated at next-to-next-to-leading order in
QCD including resummation of next-to-next-to-leading logarithmic soft gluon
terms [35]. In addition to the default sample, six other samples are used
assuming top quark masses of 166.5, 169.5, 171.5, 173.5, 175.5, and 178.5, and
using the corresponding cross sections.

For simulated events, a trigger emulation is used. The residual differences in
the trigger efficiency between data and simulation are corrected by applying
scale factors to the simulated events. These are obtained by measuring the
trigger efficiency with respect to a reference trigger for both data and
simulation. The parameterized ratio as a function of $\pt(\text{jet}_{6})$ and
is used to reweight the simulated events. Additional $\Pp\Pp$ collisions are
included in the simulated events. These are weighted to match the pileup
distribution in data. Finally, corrections to the jet energy scale and
resolution, as well as to the tagging efficiency and misidentification rate,
are applied to the simulated events.

##  0.4 Kinematic fit and background estimation

To improve the resolution of the top quark mass and decrease the background
contribution, a kinematic fit is applied. It exploits the known topology of
the signal events, , pair production of a heavy particle and antiparticle,
each decaying to $\PW\cPqb$ with $\PW\to\cPq\cPaq^{\prime}$. The three-momenta
of the jets are fitted such that

${\chi^{2}}=\sum_{j\in\text{jets}}\left[\frac{\left({\pt}_{j}^{\text{reco}}-{\pt}_{j}^{\text{fit}}\right)^{2}}{\sigma_{{\pt}_{j}}^{2}}+\frac{\left(\eta_{j}^{\text{reco}}-\eta_{j}^{\text{fit}}\right)^{2}}{\sigma_{\eta_{j}}^{2}}+\frac{\left(\phi_{j}^{\text{reco}}-\phi_{j}^{\text{fit}}\right)^{2}}{\sigma_{\phi_{j}}^{2}}\right]$

is minimized, where all jets assigned to the decay system are considered. The
labels “reco” and “fit” denote the components of the originally reconstructed
and the fitted jets, respectively, and the corresponding resolutions are
labeled $\sigma_{X}$. The minimization is performed, constraining the
invariant mass of the jets assigned to each $\PW$ boson decay to
$m_{\PW}=80.4\GeV$. As an additional constraint, the two top quark candidates
are required to have equal invariant masses.

All possible parton-jet assignments are tested using the leading six jets in
the event, but only -tagged jets are used as candidates and equivalent choices
(, swapping the two jets originating from one boson) are not considered
separately. Of the remaining 12 possibilities, only the assignment yielding
the smallest ${\chi^{2}}$ is used in the following. The ${\chi^{2}}$ value can
be used as a goodness-of-fit (gof) measure. For three degrees of freedom, it
is translated into a $p$-value of

$\displaystyle P_{\text{gof}}\equiv
1-\operatorname{erf}\left(\sqrt{\frac{{\chi^{2}}}{2}}\right)+\sqrt{\frac{2{\chi^{2}}}{\pi}}\re^{-{\chi^{2}}/2}.$

Events are required to fulfill $P_{\text{gof}}>0.1$ for the best assignment.

In simulation, event generator information can be used to validate the
assignment of the reconstructed jets to the top quark decay products. Events
are classified accordingly as _correct_ or _wrong_ permutations. A parton-jet
assignment is considered correct if the jets can be matched unambiguously to
the right partons within $\Delta R<0.3$. Wrong permutations can occur because
of a wrong parton-jet assignment, yielding the smallest ${\chi^{2}}$ or jets
being out of acceptance, not being reconstructed, or failing the
identification requirements.

The $P_{\text{gof}}$ distribution is displayed in Fig. 1 (right). Requiring
$P_{\text{gof}}>0.1$ increases the fraction of correct permutations from $6$
to $51\%$. The fitted top quark mass ($m_{\cPqt}^{\text{fit}}$) is calculated
as the invariant mass of the corresponding jets returned by the kinematic fit.
Compared to the mass calculated from the originally reconstructed jets, the
mass resolution is improved from $14.0$ to $8.8\GeV$ for the correct parton-
jet assignments, where, in both cases, the same events passing the
$P_{\text{gof}}>0.1$ requirement are used.

The $\Delta R(\cPqb\cPaqb)>2.0$ and $P_{\text{gof}}>0.1$ requirements greatly
reduce the background from QCD multijet production from approximately 80 to
25%, but a significant number of multijet events enters the signal selection
owing to the large production cross section of that background contribution.
These events can fulfill the goodness-of-fit criterion because of
combinatorial chance, but not because of an underlying decay topology.
Therefore, it is assumed that jets can be exchanged with light-flavor jets for
the estimation of the background from data, because the probability for
mimicking the topology is the same.

For the background estimation, the same selection as for the signal is
applied, as described above, but instead of requiring two -tagged jets, events
with exactly zero -tagged jets are used. For this veto, a very loose working
point is used for the tagger, to suppress contamination from events in this
QCD-enriched sample. A prescaled trigger similar to the signal trigger is used
for this selection, which does not require the presence of jets. The kinematic
fit is applied as before, but here any of the six light-flavor jets can be
assigned to the partons originating from the $\PW$ decays, as well as to the
partons serving as quarks, leading to 90 possible permutations that have to be
evaluated. This method allows one to determine the kinematic distributions of
the background, but the normalization is unknown. In all plots, the background
is normalized to the difference of the number of data events and the number of
expected signal events. This data sample contains approximately five times the
number of expected background events, so it provides good statistical
precision.

Figure 1: The $\Delta R(\cPqb\cPaqb)$ (left) and $P_{\text{gof}}$ (right)
distributions of data compared to simulated signal and the multijet background
estimate. For each event, the parton-jet assignment yielding the smallest
$\chi^{2}$ in the kinematic fit is used. The simulated signal events are
classified as correct or wrong assignments and displayed separately, and the
distributions are normalized to the integrated luminosity. For the background
estimate, the total normalization is given by the difference of observed data
events and expected signal events. The hashed bands represent the total
uncertainty in the complete prediction. The lower panels show the ratio of
data and prediction.

Figure 2: The fitted top quark mass (left) and reconstructed boson mass
(right) distributions of data compared to simulated signal and the multijet
background estimate. The shown reconstructed boson mass is the average mass of
the two W bosons in the event. For each event, the parton-jet assignment
yielding the smallest $\chi^{2}$ in the kinematic fit is used. The simulated
signal events are classified as correct or wrong assignments and displayed
separately, and the distributions are normalized to the integrated luminosity.
For the background estimate, the total normalization is given by the
difference of observed data events and expected signal events. The hashed
bands represent the total uncertainty in the prediction. The lower panels show
the ratio of data and prediction.

The final selected data set consists of 10 799 events with a signal purity of
$75\%$. Figure 1 shows the distributions of the separation of the two jets
$\Delta R(\cPqb\cPaqb)$ and the quantity $P_{\text{gof}}$ in data, compared to
the background estimate and simulation. For the signal, correct and wrong
parton-jet assignments are shown separately. The corresponding distributions
of $m_{\cPqt}^{\text{fit}}$ and the reconstructed boson mass
$m_{\PW}^{\text{reco}}$, calculated from the originally reconstructed jets,
are shown in Fig. 2. These two quantities are used in the top quark mass
extraction described in the following section.

##  0.5 Ideogram method

For the extraction of $m_{\cPqt}$, the ideogram method is used [8, 9].
Simultaneously, a JSF is determined that is used in addition to the standard
CMS jet energy calibration [12] to reduce the corresponding systematic
uncertainty. The distributions of $m_{\cPqt}^{\text{fit}}$ obtained from the
kinematic fit and $m_{\PW}^{\text{reco}}$ are used in a combined fit. For
$m_{\PW}^{\text{reco}}$, the average mass of the two bosons in an event is
used.

The likelihood

$\displaystyle\mathcal{L}\left(m_{\cPqt},\text{JSF}\right)$
$\displaystyle=P\left(\text{sample}|m_{\cPqt},\text{JSF}\right)$
$\displaystyle=\prod_{\text{events}}P\left(\text{event}|m_{\cPqt},\text{JSF}\right)$
$\displaystyle=\prod_{\text{events}}P\left(m_{\cPqt}^{\text{fit}},m_{\PW}^{\text{reco}}|m_{\cPqt},\text{JSF}\right)$

is maximized, yielding the best fit values for $m_{\cPqt}$ and JSF. A prior
probability for the JSF can be incorporated by maximizing

$P(\text{JSF})P\left(\text{sample}|m_{\cPqt},\text{JSF}\right)$

instead. Treating $m_{\cPqt}^{\text{fit}}$ and $m_{\PW}^{\text{reco}}$ as
uncorrelated, as verified using simulated events, the probability
$P\left(m_{\cPqt}^{\text{fit}},m_{\PW}^{\text{reco}}|m_{\cPqt},\text{JSF}\right)$
factorizes into

$\displaystyle
P\left(m_{\cPqt}^{\text{fit}},m_{\PW}^{\text{reco}}|m_{\cPqt},\text{JSF}\right)={}$
$\displaystyle
f_{\text{sig}}P\left(m_{\cPqt}^{\text{fit}},m_{\PW}^{\text{reco}}|m_{\cPqt},\text{JSF}\right)$
$\displaystyle{}+\left(1-f_{\text{sig}}\right)P_{\text{bkg}}\left(m_{\cPqt}^{\text{fit}},m_{\PW}^{\text{reco}}\right)$
$\displaystyle={}$ $\displaystyle
f_{\text{sig}}\sum_{j}f_{j}P_{j}\left(m_{\cPqt}^{\text{fit}}|m_{\cPqt},\text{JSF}\right)P_{j}\left(m_{\PW}^{\text{reco}}|m_{\cPqt},\text{JSF}\right)$
$\displaystyle{}+\left(1-f_{\text{sig}}\right)P_{\text{bkg}}\left(m_{\cPqt}^{\text{fit}}\right)P_{\text{bkg}}\left(m_{\PW}^{\text{reco}}\right),$

where $f_{j}$ with $j\in\left\\{\text{correct},\text{wrong}\right\\}$ is the
relative fraction of the different permutation cases and $f_{\text{sig}}$ is
the signal fraction.

The probability densities
$P_{j}\left(m_{\cPqt}^{\text{fit}}|m_{\cPqt},\text{JSF}\right)$ and
$P_{j}\left(m_{\PW}^{\text{reco}}|m_{\cPqt},\text{JSF}\right)$ for the signal
are described by analytic functions parametrized in $m_{\cPqt}$ and JSF. For
the determination of the parameters, a simultaneous fit to simulated samples
for seven different generated top quark masses $m_{\cPqt}^{\text{gen}}$ and
five different input JSF values is used. The background shape is described by
a spline interpolation as a function of $m_{\cPqt}^{\text{fit}}$ and
$m_{\PW}^{\text{reco}}$, but independent of the model parameters $m_{\cPqt}$
and JSF.

Three variations of a maximum likelihood fit are performed to extract the top
quark mass. In the one-dimensional (1D) analysis, the JSF is fixed to unity
(corresponding to a Dirac delta function for the prior probability), , the
standard CMS jet energy calibration. For the two-dimensional (2D) analysis,
the JSF is a free parameter in the maximum likelihood fit, making possible a
compensation of part of the systematic uncertainties. The signal fraction and
correct permutation fraction are free parameters in both cases. The third
(hybrid) method is a weighted combination of both approaches, corresponding to
a measurement with a Gaussian constraint on the JSF around unity. In the limit
of an infinitely narrow JSF constraint, the hybrid method is identical to the
1D method, while for an infinitely broad prior probability distribution, the
2D method is recovered. The width of the Gaussian constraint in the hybrid
method is optimized to yield the smallest total uncertainty.

To calibrate the mass extraction method, pseudo-experiments are performed for
the seven different generated values of $m_{\cPqt}^{\text{gen}}$ and three
input JSF values (0.98, 1.00, and 1.02). The extracted $m_{\cPqt}$ and JSF
values are compared to the input values and the residual slopes in
$m_{\cPqt}^{\text{gen}}$ and JSF are used as calibration. The residual biases
after the calibration are shown in Fig. 3 for pseudo-experiments with
different JSF and $m_{\cPqt}^{\text{gen}}$ values. As expected, neither a
significant residual offset nor a slope are observed after the calibration
procedure.

Figure 3: Difference between extracted and generated top quark masses (upper
panel) and JSFs (lower panel) for different input masses and JSFs after the
calibration in the all-jets channel. The values are extracted using the 2D
method.

##  0.6 Systematic uncertainties

A summary of the systematic uncertainty sources is shown in Table 0.6. The
corresponding values are obtained from pseudo-experiments, using Monte Carlo
(MC) signal samples with variations of the individual systematic uncertainty
sources. In the following, details for the determination of the most important
uncertainties are given. Most systematic uncertainty sources are shifted by
$\pm 1$ standard deviation, and the absolute value of the largest resulting
shifts in $m_{\cPqt}$ and JSF are quoted as systematic uncertainties for the
measurement. For some uncertainties, different models are compared, and are
described individually. The maximum of the statistical uncertainty on the
observed shift and the shift itself is used as the systematic uncertainty.

List of systematic uncertainties for the all-jets channel. The signs of the
shifts ($\delta x=x_{\text{variation}}-x_{\text{nominal}}$) correspond to the
$+1$ standard deviation variation of the systematic uncertainty source. For
linear sums of the uncertainty groups, the relative signs have been
considered. Shifts determined using dedicated samples for the systematic
variation are displayed with the corresponding statistical uncertainty.  2D 1D
hybrid $\delta m_{\cPqt}^{\text{2D}}$ $\delta\text{JSF}^{\text{2D}}$ $\delta
m_{\cPqt}^{\text{1D}}$ $\delta m_{\cPqt}^{\text{hyb}}$
$\delta\text{JSF}^{\text{hyb}}$ [GeV] [%] [GeV] [GeV] [%] Experimental
uncertainties Method calibration $0.06$ $0.2$ $0.06$ $0.06$ $0.2$ JEC (quad.
sum) $0.18$ $0.3$ $0.73$ $0.15$ $0.2$ – Intercalibration $-0.04$ $-0.1$
$+0.12$ $-0.04$ $-0.1$ – MPFInSitu $-0.03$ $0.0$ $+0.22$ $+0.08$ $+0.1$ –
Uncorrelated $-0.17$ $-0.3$ $+0.69$ $+0.12$ $+0.2$ Jet energy resolution
$-0.09$ $+0.2$ $+0.09$ $-0.04$ $+0.1$ tagging $0.02$ $0.0$ $0.01$ $0.02$ $0.0$
Pileup $-0.06$ $+0.1$ $0.00$ $-0.04$ $+0.1$ Background $0.10$ $0.1$ $0.03$
$0.07$ $0.1$ Trigger $+0.04$ $-0.1$ $-0.04$ $+0.02$ $-0.1$ Modeling
uncertainties JEC flavor (linear sum) $-0.35$ $+0.1$ $-0.31$ $-0.34$ $0.0$ –
light quarks (uds) $+0.10$ $-0.1$ $-0.01$ $+0.07$ $-0.1$ – charm $+0.03$ $0.0$
$-0.01$ $+0.02$ $0.0$ – bottom $-0.29$ $0.0$ $-0.29$ $-0.29$ $0.0$ – gluon
$-0.19$ $+0.2$ $+0.03$ $-0.13$ $+0.2$ jet modeling (quad. sum) $0.09$ $0.0$
$0.09$ $0.09$ $0.0$ – frag. Bowler–Lund $-0.07$ $0.0$ $-0.07$ $-0.07$ $0.0$ –
frag. Peterson $-0.05$ $0.0$ $-0.04$ $-0.05$ $0.0$ – semileptonic hadron
decays $-0.03$ $0.0$ $-0.03$ $-0.03$ $0.0$ PDF $0.01$ $0.0$ $0.01$ $0.01$
$0.0$ Ren. and fact. scales $0.05$ $0.0$ $0.04$ $0.04$ $0.0$ ME/PS matching
$+0.32\pm 0.20$ $-0.3$ $-0.05\pm 0.14$ $+0.24\pm 0.18$ $-0.2$ ISR PS scale
$+0.17\pm 0.17$ $-0.2$ $+0.13\pm 0.12$ $+0.12\pm 0.14$ $-0.1$ FSR PS scale
$+0.22\pm 0.12$ $-0.2$ $+0.11\pm 0.08$ $+0.18\pm 0.11$ $-0.1$ Top quark $\pt$
$+0.03$ $0.0$ $+0.02$ $+0.03$ $0.0$ Underlying event $+0.16\pm 0.19$ $-0.3$
$-0.07\pm 0.14$ $+0.10\pm 0.17$ $-0.2$ Early resonance decays $+0.02\pm 0.28$
$+0.4$ $+0.38\pm 0.19$ $+0.13\pm 0.24$ $+0.3$ CR modeling (max. shift)
$+0.41\pm 0.29$ $-0.4$ $-0.43\pm 0.20$ $-0.36\pm 0.25$ $-0.3$ – “gluon move”
(ERD on) $+0.41\pm 0.29$ $-0.4$ $+0.10\pm 0.20$ $+0.32\pm 0.25$ $-0.3$ – “QCD
inspired” (ERD on) $-0.32\pm 0.29$ $-0.1$ $-0.43\pm 0.20$ $-0.36\pm 0.25$
$-0.1$ Total systematic $0.81$ $0.9$ $1.03$ $0.70$ $0.7$ Statistical
(expected) $0.21$ $0.2$ $0.16$ $0.20$ $0.1$ Total (expected) $0.83$ $0.9$
$1.04$ $0.72$ $0.7$

  * •

Method calibration: The quadratic sum of the statistical uncertainty and the
residual bias of the calibration curve (shown in Fig. 3) after the calibration
is used as the systematic uncertainty.

  * •

JECs: Jet energies are scaled up and down according to the - and
$\eta$-dependent data/simulation uncertainties [23]. The correlation groups
(called Intercalibration, MPFInSitu, and Uncorrelated) follow the
recommendations documented in Ref. [36].

  * •

Jet energy resolution: Since the jet energy resolution measured in data is
worse than in simulation, the simulation is modified to correct for the
difference [23]. The jet energy resolution in the simulation is varied up and
down within the uncertainty.

  * •

tagging: The -dependent uncertainty of the tagging efficiencies and
misidentification rates of the CSVv2 tagger [26] are taken into account by
reweighting the simulated events accordingly.

  * •

Pileup: To estimate the uncertainty in the determination of the number of
pileup events and the reweighting procedure, the inelastic proton-proton cross
section [37] used in the determination is varied by ${\pm}4.6\%$.

  * •

Background: An uncertainty in the background prediction is obtained by
applying the method to simulation and comparing the obtained estimate to the
direct simulation, , generated QCD multijet events passing the signal
selection. A linear fit to the ratio is consistent with a constant value of
unity. The slope is varied up and down within its uncertainty and used to
reweight the events used for the determination of the background probability
density function.

  * •

Trigger: To estimate the uncertainty in the trigger selection, the
data/simulation scale factor described in Section 0.3 is omitted.
Additionally, a base trigger requiring the presence of one muon is used to
obtain the correction factor. The maximum of the observed shifts with respect
to the nominal correction is quoted as an uncertainty.

  * •

JEC flavor: The difference between Lund string fragmentation and cluster
fragmentation is evaluated comparing 6.422 [38] and 2.4 [39]. The jet energy
response is compared separately for each jet flavor [23]. Uncertainties for
jets from different quark flavors and gluons are added linearly, which takes
into account possible differences between the measured JSF, which is mainly
sensitive to light quarks and gluons, and the jet energy scale.

  * •

jet modeling: The uncertainty associated with the fragmentation of quarks is
split into three components. The Bowler–Lund fragmentation function is varied
within its uncertainties as determined by the ALEPH and DELPHI Collaborations
[40, 41]. As an alternative model of the fragmentation into hadrons, the
Peterson fragmentation function is used and the difference obtained relative
to the Bowler–Lund fragmentation function is assigned as an uncertainty. The
third uncertainty source taken into account is the semileptonic hadron
branching fraction, which is varied by $-0.45\%$ and $+0.77\%$, motivated by
measurements of /decays and their corresponding uncertainties [42].

  * •

PDF: The 100 PDF replicas of the NNPDF3.0 NLO ($\alpS=0.118)$ set are used to
repeat the analysis [30]. The variance of the results is used to determine the
PDF uncertainty. In addition, the $\alpS$ value is changed to 0.117 and 0.119.
The maximum of the PDF uncertainty and the $\alpS$ variations is quoted as
uncertainty.

  * •

Renormalization and factorization scales: The renormalization and
factorization scales for the ME calculation are varied. Both are multiplied
independently from each other, and simultaneously by factors of 0.5 and 2 with
respect to the default values. This is achieved by appropriately reweighting
simulated events. The quoted uncertainty corresponds to the envelope of the
resulting shifts.

  * •

ME/PS matching: The matching of the ME calculations to the PS is varied by
shifting the parameter $h_{\text{damp}}=1.58^{+0.66}_{-0.59}$ [33] within the
uncertainties. The jet response $\pt^{\text{reco}}/\pt^{\text{gen}}$ as a
function of $\pt^{\text{gen}}$ is rescaled in the variation samples to
reproduce the response observed in the default sample.

  * •

ISR PS scale: For initial-state radiation (ISR), the PS scale is varied in .
The ISR PS scale is multiplied by factors of 2 and 0.5 in dedicated MC
samples.

  * •

FSR PS scale: The PS scale used for final-state radiation (FSR) is scaled up
by $\sqrt{2}$ and down by $1/\sqrt{2}$ [32], affecting the fragmentation and
hadronization, as well additional jet emission. The jet response is rescaled
in the variation samples to reproduce the response observed in the default
sample.

  * •

Top quark : Recent calculations suggest that the top quark spectrum is
strongly affected by next-to-next-to-leading-order effects [43]. The of the
top quark in simulation is varied to match the distribution measured by CMS
[44, 45] and its impact on the $m_{\cPqt}$ measurement is quoted as a
systematic uncertainty.

  * •

Underlying event: Measurements of the underlying event have been used to tune
parameters describing nonperturbative QCD effects [32, 33]. The parameters of
the tune are varied within their uncertainties.

  * •

Early resonance decays: Modeling of color reconnection (CR) introduces
systematic uncertainties which are estimated by comparing different CR models
and settings. In the default sample, the top quark decay products are not
included in the CR process. This setting is compared to the case of including
the decay products by enabling early resonance decays (ERD) in 8.

  * •

CR modeling: In addition to the default model used in 8, two alternative CR
models are used, namely a model with string formation beyond leading color
(“QCD inspired”) [46] and a model allowing the gluons to be moved to another
string (“gluon move”) [47]. Underlying event measurements are used to tune the
parameters of all models [32, 33]. The largest shifts induced by the
variations are assigned as the CR uncertainty.

This approach, as well as the ERD variation, is new relative to the Run 1
results at $\sqrt{s}=7$ and $8\TeV$, because these CR models have become only
recently available in 8. The new models were first used to evaluate the
$m_{\cPqt}$ uncertainty due to CR in Ref. [17]. Like in this analysis, the
same increase in systematic uncertainty with respect to the Run 1 result has
been observed.

A summary of the systematic uncertainties described above is given in Table
0.6. In Ref. [17], an ME generator uncertainty has been considered: Instead of
using v2 as ME generator, the  2.2.2 generator with the FxFx matching scheme
is used [48, 49]. The difference between the results obtained with the two
generators is $\delta m_{\cPqt}^{\text{hyb}}=+0.31\pm 0.52$ for the hybrid
method in the all-jets channel. However, this is not significant because of
the insufficient statistical precision of the available sample. Since the
radiation after the top quark decay is described by , no significant impact of
the ME generator choice is expected beyond the variation of the PS scales and
matching. Therefore, no ME generator uncertainty is considered in the total
uncertainty of the measurement, but the number is just quoted here as a cross-
check.

##  0.7 Results

For the 2D fit using the 10 799 $\ttbar$ all-jets candidate events, the
extracted parameters are

$\displaystyle m_{\cPqt}^{\text{2D}}$ $\displaystyle=172.43\pm
0.22\,\text{(stat+JSF)}\pm 0.81\syst\GeV\text{ and}$
$\displaystyle\text{JSF}^{\text{2D}}$ $\displaystyle=0.996\pm 0.002\stat\pm
0.009\syst.$

The corresponding 1D and hybrid fits yield instead

$\displaystyle m_{\cPqt}^{\text{1D}}$ $\displaystyle=172.13\pm 0.17\stat\pm
1.03\syst\GeV,$ $\displaystyle m_{\cPqt}^{\text{hyb}}$
$\displaystyle=172.34\pm 0.20\,\text{(stat+JSF)}\pm 0.70\syst\GeV\text{, and}$
$\displaystyle\text{JSF}^{\text{hyb}}$ $\displaystyle=0.997\pm 0.002\stat\pm
0.007\syst.$

In all cases the fitted values for the fraction of correct assignments, as
well as the background fraction, are in agreement with the values expected
from simulation. The hybrid measurement of $172.34\pm
0.20\,\text{(stat+JSF)}\pm 0.43\,\text{(CR+ERD)}\pm 0.55\syst\GeV$ is the main
result of this analysis, since it is constructed to provide the smallest
uncertainty. The color reconnection and early resonance decay parts are
separated from the rest of the systematic uncertainties. Because of the larger
data sample used in this analysis, the statistical uncertainty is reduced with
respect to the result of $m_{\cPqt}=172.32\pm 0.25\,\text{(stat+JSF)}\pm
0.59\syst\GeV$ obtained at $\sqrt{s}=8\TeV$. The new result is in good
agreement with the value measured at $\sqrt{s}=8\TeV$, where a leading-order
simulation has been employed to calibrate the measurement, whereas an NLO
simulation has been used here. The systematic uncertainty is increased with
respect to the Run 1 result, because a broader set of CR models has been
compared, which have become available in 8.

##  0.8 Combined measurement with the lepton+jets final state

This measurement is combined with the lepton+jets final state, where only
electrons and muons are explicitly considered as leptons, while tau leptons
enter the selection only when they decay leptonically. The corresponding
analysis for the lepton+jets final state is described in Ref. [17]. All
selection and analysis steps are kept unchanged. Since the same method for the
mass extraction is used, a combination with the all-jets channel at the
likelihood level is possible.

The total likelihood $\mathcal{L}$ is constructed from the single-channel
likelihoods $\mathcal{L}_{i}$,

$\mathcal{L}(m_{\cPqt},\text{JSF})=\mathcal{L}_{\text{A}}(m_{\cPqt},\text{JSF})\mathcal{L}_{\text{L}}(m_{\cPqt},\text{JSF}),$

where the indices A and L indicate the all-jets and lepton+jets channel,
respectively.

No extra calibration of the mass extraction is performed, but the single-
channel calibrations are applied. Figure 4 shows the extracted values for the
top quark mass and JSF for different input values as a validation. No residual
dependence is observed.

Figure 4: Difference between extracted and generated top quark masses (upper
panel) and JSFs (lower panel) for different input masses and JSFs after the
single-channel calibrations for the combined measurement. The values are
extracted using the 2D method.

The systematic uncertainties are evaluated as described above for the all-jets
channel. For the pseudo-experiments, the systematic uncertainty sources are
varied simultaneously for both channels. An exception are uncertainties that
only affect a single channel. These uncertainty sources are only varied for
the corresponding channel. For the all-jets channel, these are the background
and trigger uncertainties. In addition, uncertainties specific to the
lepton+jets channel are introduced, including the background and trigger
uncertainties, as well as the uncertainties arising from the lepton isolation
and identification criteria, and are described in Ref. [17]. The complete list
of uncertainties is shown in Table 0.8. A comparison of the hybrid mass
uncertainties can be found in Table 0.8 for the all-jets and lepton+jets
channels as well as for the combination. In general, the uncertainties for the
combination are smaller than those for the all-jets channel and are close to
the lepton+jets uncertainties, as expected because the combination is
dominated by this channel. The total uncertainty for the combination is
slightly smaller than that for the lepton+jets channel.

List of systematic uncertainties for the combined mass extraction. The signs
of the shifts ($\delta x=x_{\text{variation}}-x_{\text{nominal}}$) correspond
to the $+1$ standard deviation variation of the systematic uncertainty source.
For linear sums of the uncertainty groups, the relative signs have been
considered. Shifts determined using dedicated samples for the systematic
variation are displayed with the corresponding statistical uncertainty.  2D 1D
hybrid $\delta m_{\cPqt}^{\text{2D}}$ $\delta\text{JSF}^{\text{2D}}$ $\delta
m_{\cPqt}^{\text{1D}}$ $\delta m_{\cPqt}^{\text{hyb}}$
$\delta\text{JSF}^{\text{hyb}}$ [GeV] [%] [GeV] [GeV] [%] Experimental
uncertainties Method calibration $0.03$ $0.0$ $0.03$ $0.03$ $0.0$ JEC (quad.
sum) $0.12$ $0.2$ $0.82$ $0.17$ $0.3$ – Intercalibration $-0.01$ $0.0$ $+0.16$
$+0.04$ $+0.1$ – MPFInSitu $-0.01$ $0.0$ $+0.23$ $+0.07$ $+0.1$ – Uncorrelated
$-0.12$ $-0.2$ $+0.77$ $+0.15$ $+0.3$ Jet energy resolution $-0.18$ $+0.3$
$+0.09$ $-0.10$ $+0.2$ tagging $0.03$ $0.0$ $0.01$ $0.02$ $0.0$ Pileup $-0.07$
$+0.1$ $+0.02$ $-0.05$ $+0.1$ All-jets background $0.01$ $0.0$ $0.00$ $0.01$
$0.0$ All-jets trigger $+0.01$ $0.0$ $0.00$ $+0.01$ $0.0$ $\ell$+jets
Background $-0.02$ $0.0$ $+0.01$ $-0.01$ $0.0$ $\ell$+jets Trigger $0.00$
$0.0$ $0.00$ $0.00$ $0.0$ Lepton isolation $0.00$ $0.0$ $0.00$ $0.00$ $0.0$
Lepton identification $0.00$ $0.0$ $0.00$ $0.00$ $0.0$ Modeling uncertainties
JEC flavor (linear sum) $-0.39$ $+0.1$ $-0.31$ $-0.37$ $+0.1$ – light quarks
(uds) $+0.11$ $-0.1$ $-0.01$ $+0.07$ $-0.1$ – charm $+0.03$ $0.0$ $-0.01$
$+0.02$ $0.0$ – bottom $-0.31$ $0.0$ $-0.31$ $-0.31$ $0.0$ – gluon $-0.22$
$+0.3$ $+0.02$ $-0.15$ $+0.2$ jet modeling (quad. sum) $0.08$ $0.1$ $0.04$
$0.06$ $0.1$ – frag. Bowler–Lund $-0.06$ $+0.1$ $-0.01$ $-0.05$ $0.0$ – frag.
Peterson $-0.03$ $0.0$ $0.00$ $-0.02$ $0.0$ – semileptonic hadron decays
$-0.04$ $0.0$ $-0.04$ $-0.04$ $0.0$ PDF $0.01$ $0.0$ $0.01$ $0.01$ $0.0$ Ren.
and fact. scales $0.01$ $0.0$ $0.02$ $0.01$ $0.0$ ME/PS matching $-0.10\pm
0.08$ $+0.1$ $+0.02\pm 0.05$ $+0.07\pm 0.07$ $+0.1$ ME generator $+0.16\pm
0.21$ $+0.2$ $+0.32\pm 0.13$ $+0.21\pm 0.18$ $+0.1$ ISR PS scale $+0.07\pm
0.08$ $+0.1$ $+0.10\pm 0.05$ $+0.07\pm 0.07$ $0.1$ FSR PS scale $+0.23\pm
0.07$ $-0.4$ $-0.19\pm 0.04$ $+0.12\pm 0.06$ $-0.3$ Top quark $\pt$ $+0.01$
$-0.1$ $-0.06$ $-0.01$ $-0.1$ Underlying event $-0.06\pm 0.07$ $+0.1$
$+0.00\pm 0.05$ $-0.04\pm 0.06$ $+0.1$ Early resonance decays $-0.20\pm 0.08$
$+0.7$ $+0.42\pm 0.05$ $-0.01\pm 0.07$ $+0.5$ CR modeling (max. shift)
$+0.37\pm 0.09$ $-0.2$ $+0.22\pm 0.06$ $+0.33\pm 0.07$ $-0.1$ – “gluon move”
(ERD on) $+0.37\pm 0.09$ $-0.2$ $+0.22\pm 0.06$ $+0.33\pm 0.07$ $-0.1$ – “QCD
inspired” (ERD on) $-0.11\pm 0.09$ $-0.1$ $-0.21\pm 0.06$ $-0.14\pm 0.07$
$-0.1$ Total systematic $0.71$ $1.0$ $1.07$ $0.61$ $0.7$ Statistical
(expected) $0.08$ $0.1$ $0.05$ $0.07$ $0.1$ Total (expected) $0.72$ $1.0$
$1.08$ $0.61$ $0.7$

Comparison of the hybrid mass uncertainties for the all-jets and lepton+jets
[17] channels, as well as the combination. The signs of the shifts follow the
convention of Tables 0.6 and 0.8.  $\delta
m_{\cPqt}^{\text{hyb}}~{}\text{[GeV]}$ all-jets $\ell$+jets combination
Experimental uncertainties Method calibration $0.06$ $0.05$ $0.03$ JEC (quad.
sum) $0.15$ $0.18$ $0.17$ – Intercalibration $-0.04$ $+0.04$ $+0.04$ –
MPFInSitu $+0.08$ $+0.07$ $+0.07$ – Uncorrelated $+0.12$ $+0.16$ $+0.15$ Jet
energy resolution $-0.04$ $-0.12$ $-0.10$ tagging $0.02$ $0.03$ $0.02$ Pileup
$-0.04$ $-0.05$ $-0.05$ All-jets background $0.07$ $-$ $0.01$ All-jets trigger
$+0.02$ $-$ $+0.01$ $\ell$+jets background $-$ $+0.02$ $-0.01$ Modeling
uncertainties JEC flavor (linear sum) $-0.34$ $-0.39$ $-0.37$ – light quarks
(uds) $+0.07$ $+0.06$ $+0.07$ – charm $+0.02$ $+0.01$ $+0.02$ – bottom $-0.29$
$-0.32$ $-0.31$ – gluon $-0.13$ $-0.15$ $-0.15$ jet modeling (quad. sum)
$0.09$ $0.12$ $0.06$ – frag. Bowler–Lund $-0.07$ $-0.05$ $-0.05$ – frag.
Peterson $-0.05$ $+0.04$ $-0.02$ – semileptonic hadron decays $-0.03$ $+0.10$
$-0.04$ PDF $0.01$ $0.02$ $0.01$ Ren. and fact. scales $0.04$ $0.01$ $0.01$
ME/PS matching $+0.24$ $-0.07$ $+0.07$ ME generator $-$ $+0.20$ $+0.21$ ISR PS
scale $+0.14$ $+0.07$ $+0.07$ FSR PS scale $+0.18$ $+0.13$ $+0.12$ Top quark
$\pt$ $+0.03$ $-0.01$ $-0.01$ Underlying event $+0.17$ $-0.07$ $-0.06$ Early
resonance decays $+0.24$ $-0.07$ $-0.07$ CR modeling (max. shift) $-0.36$
$+0.31$ $+0.33$ – “gluon move” (ERD on) $+0.32$ $+0.31$ $+0.33$ – “QCD
inspired” (ERD on) $-0.36$ $-0.13$ $-0.14$ Total systematic $0.70$ $0.62$
$0.61$ Statistical (expected) $0.20$ $0.08$ $0.07$ Total (expected) $0.72$
$0.63$ $0.61$

The combined measurement yields

$\displaystyle m_{\cPqt}^{\text{2D}}$ $\displaystyle=172.39\pm
0.08\,\text{(stat+JSF)}\pm 0.71\syst\GeV\text{ and}$
$\displaystyle\text{JSF}^{\text{2D}}$ $\displaystyle=0.995\pm 0.001\stat\pm
0.010\syst$

for the 2D method and

$\displaystyle m_{\cPqt}^{\text{1D}}$ $\displaystyle=171.94\pm 0.05\stat\pm
1.07\syst\GeV,$ $\displaystyle m_{\cPqt}^{\text{hyb}}$
$\displaystyle=172.26\pm 0.07\,\text{(stat+JSF)}\pm 0.61\syst\GeV\text{, and}$
$\displaystyle\text{JSF}^{\text{hyb}}$ $\displaystyle=0.996\pm 0.001\stat\pm
0.007\syst$

for the 1D and hybrid fits. The likelihood contours for
$-2\Delta\ln\mathcal{L}=2.3$, corresponding to the $68\%$ confidence level, in
the $m_{\cPqt}$-JSF plane are shown in Fig. 5 for the hybrid measurement
results for the all-jets and lepton+jets channels, as well as for the
combination. Additionally, the likelihood profiles are displayed as a function
of $m_{\cPqt}$. Both channels are in statistical agreement with each other.
The result of the combination is closer to the lepton+jets channel, as
expected.

Figure 5: Likelihood contours for $-2\Delta\ln\mathcal{L}=2.3$, corresponding
to the $68\%$ confidence level, in the $m_{\cPqt}$-JSF plane (upper panel) and
the likelihood profiles for the top quark mass (lower panel), where the level
corresponding to one standard deviation ($\sigma$) is indicated. The hybrid
measurement results for the all-jets and lepton+jets channels, as well as for
the combination, are shown.

Just as for the single-channel results, the hybrid measurement provides the
best precision and is considered the main result. This is the first top quark
mass measurement using the $\ttbar$ lepton+jets and all-jets final states
combined in a single likelihood function. The largest uncertainty contribution
is related to the modeling of color reconnection, as it was observed for the
all-jets channel and the lepton+jets channel before using the same CR models.
Accordingly, the quoted systematic uncertainty is larger than those reported
in the most precise combination reported by the CMS Collaboration [12], and
comparable to the value reported by the ATLAS Collaboration [50].

##  0.9 Summary

A measurement of the top quark mass ($m_{\cPqt}$) using the all-jets final
state is presented. The analyzed data set was collected by the CMS experiment
in proton-proton collisions at $\sqrt{s}=13\,\TeV$ that correspond to an
integrated luminosity of $35.9\fbinv$. The kinematic properties in each event
are reconstructed using a constrained fit that assumes a hypothesis, which
suppresses the dominant multijet background and improves the mass resolution.

The value of $m_{\cPqt}$ and an additional jet energy scale factor (JSF) are
extracted using the ideogram method, which uses the likelihood of the values
of $m_{\cPqt}$ and JSF in each event to determine these parameters. The
resulting $m_{\cPqt}$ is measured to be $172.34\pm 0.20\,\text{(stat+JSF)}\pm
0.70\syst\GeV$. This is in good agreement with previous CMS results obtained
at $\sqrt{s}=7$, $8$, and $13\TeV$. The modeling uncertainties are larger than
in the previous measurements at lower center-of-mass energies because of the
use of new alternative color reconnection models that were not previously
available.

A combined measurement using also the lepton+jets final state results in
$m_{\cPqt}=172.26\pm 0.07\,\text{(stat+JSF)}\pm 0.61\syst\GeV$. This is the
first combined $m_{\cPqt}$ result obtained in the all-jets and lepton+jets
final states using a single likelihood function.

###### 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”) Programme and the János Bolyai Research Scholarship of the
Hungarian Academy of Sciences, the New National Excellence Program ÚNKP, the
NKFIA research grants 123842, 123959, 124845, 124850, and 125105 (Hungary);
the Council of Science and Industrial Research, India; the HOMING PLUS program
of the Foundation for Polish Science, cofinanced from European Union, Regional
Development Fund, the Mobility Plus program of the Ministry of Science and
Higher Education, the National Science Center (Poland), contracts Harmonia
2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and
2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities
Research Program by Qatar National Research Fund; the Programa Estatal de
Fomento de la Investigación Científica y Técnica de Excelencia María de
Maeztu, grant MDM-2015-0509 and the Programa Severo Ochoa del Principado de
Asturias; the Thalis and Aristeia programs cofinanced by EU-ESF and the Greek
NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn
University and the Chulalongkorn Academic into Its 2nd Century Project
Advancement Project (Thailand); the Welch Foundation, contract C-1845; and the
Weston Havens Foundation (USA).

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##  .10 The CMS Collaboration

Yerevan Physics Institute, Yerevan, Armenia
A.M. Sirunyan, A. Tumasyan Institut für Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, E. Asilar, T. Bergauer, J. Brandstetter, M. Dragicevic,
J. Erö, A. Escalante Del Valle, M. Flechl, R. Frühwirth1, V.M. Ghete, J.
Hrubec, M. Jeitler1, N. Krammer, I. Krätschmer, D. Liko, T. Madlener, I.
Mikulec, N. Rad, H. Rohringer, J. Schieck1, R. Schöfbeck, M. Spanring, D.
Spitzbart, 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
H. Abdalla9, S. Khalil10, A. Mohamed10 National Institute of Chemical Physics
and Biophysics, Tallinn, Estonia
S. Bhowmik, A. Carvalho Antunes De Oliveira, R.K. Dewanjee, K. Ehataht, M.
Kadastik, M. Raidal, C. Veelken Department of Physics, University of Helsinki,
Helsinki, Finland
P. Eerola, H. Kirschenmann, J. Pekkanen, M. Voutilainen Helsinki Institute of
Physics, Helsinki, Finland
J. Havukainen, J.K. Heikkilä, T. Järvinen, V. Karimäki, R. Kinnunen, T.
Lampén, K. Lassila-Perini, S. Laurila, S. Lehti, T. Lindén, P. Luukka, T.
Mäenpää, H. Siikonen, E. Tuominen, J. Tuominiemi Lappeenranta University of
Technology, Lappeenranta, Finland
T. Tuuva IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
M. Besancon, F. Couderc, M. Dejardin, D. Denegri, J.L. Faure, F. Ferri, S.
Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, C. Leloup,
E. Locci, J. Malcles, G. Negro, J. Rander, A. Rosowsky, M.Ö. Sahin, M. Titov
Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Université
Paris-Saclay, Palaiseau, France
A. Abdulsalam11, 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. Agram12, J. Andrea, D. Bloch, G. Bourgatte, J.-M. Brom, E.C. Chabert, V.
Cherepanov, C. Collard, E. Conte12, J.-C. Fontaine12, D. Gelé, U. Goerlach, M.
Jansová, A.-C. Le Bihan, N. Tonon, P. Van Hove Centre de Calcul de l’Institut
National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3,
Villeurbanne, France
S. Gadrat Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3,
Institut de Physique Nucléaire de Lyon, Villeurbanne, France
S. Beauceron, C. Bernet, G. Boudoul, N. Chanon, R. Chierici, D. Contardo, P.
Depasse, H. El Mamouni, J. Fay, L. Finco, S. Gascon, M. Gouzevitch, G.
Grenier, B. Ille, F. Lagarde, I.B. Laktineh, H. Lattaud, M. Lethuillier, L.
Mirabito, S. Perries, A. Popov13, V. Sordini, G. Touquet, M. Vander Donckt, S.
Viret Georgian Technical University, Tbilisi, Georgia
A. Khvedelidze8 Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze8 RWTH Aachen University, I. Physikalisches Institut, Aachen,
Germany
C. Autermann, L. Feld, M.K. Kiesel, K. Klein, M. Lipinski, M. Preuten, M.P.
Rauch, C. Schomakers, J. Schulz, M. Teroerde, B. Wittmer RWTH Aachen
University, III. Physikalisches Institut A, Aachen, Germany
A. Albert, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, S. Ghosh, A. Güth, T.
Hebbeker, C. Heidemann, K. Hoepfner, H. Keller, L. Mastrolorenzo, M.
Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, T. Pook, M. Radziej, H.
Reithler, M. Rieger, A. Schmidt, D. Teyssier, S. Thüer RWTH Aachen University,
III. Physikalisches Institut B, Aachen, Germany
G. Flügge, O. Hlushchenko, T. Kress, T. Müller, A. Nehrkorn, A. Nowack, C.
Pistone, O. Pooth, D. Roy, H. Sert, A. Stahl14 Deutsches Elektronen-
Synchrotron, Hamburg, Germany
M. Aldaya Martin, T. Arndt, C. Asawatangtrakuldee, I. Babounikau, K.
Beernaert, O. Behnke, U. Behrens, A. Bermúdez Martínez, D. Bertsche, A.A. Bin
Anuar, K. Borras15, V. Botta, A. Campbell, P. Connor, C. Contreras-Campana, V.
Danilov, A. De Wit, M.M. Defranchis, C. Diez Pardos, D. Domínguez Damiani, G.
Eckerlin, T. Eichhorn, A. Elwood, E. Eren, E. Gallo16, A. Geiser, J.M. Grados
Luyando, A. Grohsjean, 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. Lohmann17, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer,
M. Meyer, M. Missiroli, G. Mittag, J. Mnich, V. Myronenko, S.K. Pflitsch, D.
Pitzl, A. Raspereza, 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. Hartmann14, S.M. Heindl, U. Husemann, I.
Katkov13, 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. Bartók18, 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. Horvath19, 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. Karancsi18, 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. Bahinipati21, C. Kar, P. Mal, K. Mandal, A. Nayak22, S. Roy Chowdhury, D.K.
Sahoo21, S.K. Swain Panjab University, Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, S. Chauhan, R. Chawla, N. Dhingra, R.
Gupta, A. Kaur, M. Kaur, S. Kaur, P. Kumari, M. Lohan, M. Meena, A. Mehta, K.
Sandeep, S. Sharma, J.B. Singh, A.K. Virdi, G. Walia University of Delhi,
Delhi, India
A. Bhardwaj, B.C. Choudhary, R.B. Garg, M. Gola, S. Keshri, Ashok Kumar, S.
Malhotra, M. Naimuddin, P. Priyanka, K. Ranjan, Aashaq Shah, R. Sharma Saha
Institute of Nuclear Physics, HBNI, Kolkata, India
R. Bhardwaj23, M. Bharti23, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep23,
D. Bhowmik, S. Dey, S. Dutt23, S. Dutta, S. Ghosh, M. Maity24, K. Mondal, S.
Nandan, A. Purohit, P.K. Rout, A. Roy, G. Saha, S. Sarkar, T. Sarkar24, M.
Sharan, B. Singh23, S. Thakur23 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. Chenarani25, E. Eskandari Tadavani, S.M. Etesami25, M. Khakzad, M.
Mohammadi Najafabadi, M. Naseri, F. Rezaei Hosseinabadi, B. Safarzadeh26, M.
Zeinali University College Dublin, Dublin, Ireland
M. Felcini, M. Grunewald INFN Sezione di Bari a, Università di Bari b,
Politecnico di Bari c, Bari, Italy
M. Abbresciaa,b, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L. Cristellaa,b,
N. De Filippisa,c, M. De Palmaa,b, A. Di Florioa,b, F. Erricoa,b, L. Fiorea,
A. Gelmia,b, G. Iasellia,c, 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,27, 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,28, G. Sguazzonia, D. Stroma, L. Viliania INFN Laboratori
Nazionali di Frascati, Frascati, Italy
L. Benussi, S. Bianco, F. Fabbri, D. Piccolo INFN Sezione di Genova a,
Università di Genova b, Genova, Italy
F. Ferroa, R. Mulargiaa,b, 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,14, S. Di Guidaa,b,14,
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,14, P. Paoluccia,14, C. Sciaccaa,b, E. Voevodinaa,b INFN Sezione di
Padova a, Università di Padova b, Padova, Italy, Università di Trento c,
Trento, Italy
P. Azzia, N. Bacchettaa, D. Biselloa,b, A. Bolettia,b, A. Bragagnolo, R.
Carlina,b, P. Checchiaa, M. Dall’Ossoa,b, P. De Castro Manzanoa, T. Dorigoa,
U. Dossellia, F. Gasparinia,b, U. Gasparinia,b, A. Gozzelinoa, S.Y. Hoh, S.
Lacapraraa, P. Lujan, M. Margonia,b, A.T. Meneguzzoa,b, J. Pazzinia,b, M.
Presillab, P. Ronchesea,b, R. Rossina,b, F. Simonettoa,b, A. Tiko, E.
Torassaa, M. Tosia,b, M. Zanettia,b, P. Zottoa,b, G. Zumerlea,b INFN Sezione
di Pavia a, Università di Pavia b, Pavia, Italy
A. Braghieria, A. Magnania, P. Montagnaa,b, S.P. Rattia,b, V. Rea, M.
Ressegottia,b, C. Riccardia,b, P. Salvinia, I. Vaia,b, P. Vituloa,b INFN
Sezione di Perugia a, Università di Perugia b, Perugia, Italy
M. Biasinia,b, G.M. Bileia, C. Cecchia,b, D. Ciangottinia,b, L. Fanòa,b, P.
Laricciaa,b, R. Leonardia,b, E. Manonia, G. Mantovania,b, V. Mariania,b, M.
Menichellia, A. Rossia,b, A. Santocchiaa,b, D. Spigaa INFN Sezione di Pisa a,
Università di Pisa b, Scuola Normale Superiore di Pisa c, Pisa, Italy
K. Androsova, P. Azzurria, G. Bagliesia, L. Bianchinia, T. Boccalia, L.
Borrello, R. Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, G. Fedia, F. Fioria,c,
L. Gianninia,c, A. Giassia, M.T. Grippoa, F. Ligabuea,c, E. Mancaa,c, G.
Mandorlia,c, A. Messineoa,b, F. Pallaa, A. Rizzia,b, G. Rolandi29, P.
Spagnoloa, R. Tenchinia, G. Tonellia,b, A. Venturia, P.G. Verdinia INFN
Sezione di Roma a, Sapienza Università di Roma b, Rome, Italy
L. Baronea,b, F. Cavallaria, M. Cipriania,b, D. Del Rea,b, E. Di Marcoa,b, M.
Diemoza, S. Gellia,b, E. Longoa,b, B. Marzocchia,b, P. Meridiania, G.
Organtinia,b, F. Pandolfia, R. Paramattia,b, F. Preiatoa,b, S. Rahatloua,b, C.
Rovellia, F. Santanastasioa,b INFN Sezione di Torino a, Università di Torino
b, Torino, Italy, Università del Piemonte Orientale c, Novara, Italy
N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, N. Bartosika,
R. Bellana,b, C. Biinoa, 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. Lee, S.W. Lee, C.S. Moon, Y.D. Oh,
S.I. Pak, S. Sekmen, D.C. Son, Y.C. Yang Chonnam National University,
Institute for Universe and Elementary Particles, Kwangju, Korea
H. Kim, D.H. Moon, G. Oh Hanyang University, Seoul, Korea
B. Francois, J. Goh30, T.J. Kim Korea University, Seoul, Korea
S. Cho, S. Choi, Y. Go, D. Gyun, S. Ha, B. Hong, Y. Jo, K. Lee, K.S. Lee, S.
Lee, J. Lim, S.K. Park, Y. Roh Sejong University, Seoul, Korea
H.S. Kim Seoul National University, Seoul, Korea
J. Almond, J. Kim, J.S. Kim, H. Lee, K. Lee, K. Nam, S.B. Oh, B.C. Radburn-
Smith, S.h. Seo, U.K. Yang, H.D. Yoo, G.B. Yu University of Seoul, Seoul,
Korea
D. Jeon, H. Kim, J.H. Kim, J.S.H. Lee, I.C. Park Sungkyunkwan University,
Suwon, Korea
Y. Choi, C. Hwang, J. Lee, I. Yu Riga Technical University, Riga, Latvia
V. Veckalns31 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 Ali32, F. Mohamad Idris33, W.A.T. Wan Abdullah, M.N.
Yusli, Z. Zolkapli Universidad de Sonora (UNISON), Hermosillo, Mexico
J.F. Benitez, A. Castaneda Hernandez, J.A. Murillo Quijada Centro de
Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico
H. Castilla-Valdez, E. De La Cruz-Burelo, M.C. Duran-Osuna, I. Heredia-De La
Cruz34, R. Lopez-Fernandez, 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. Byszuk35, K. Doroba, A. Kalinowski, M. Konecki, J.
Krolikowski, M. Misiura, M. Olszewski, A. Pyskir, M. Walczak Laboratório de
Instrumentação e Física Experimental de Partículas, Lisboa, Portugal
M. Araujo, P. Bargassa, 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. Matveev36,37, 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. Kim38, E. Kuznetsova39, 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
R. Chistov40, M. Danilov40, D. Philippov, E. Tarkovskii P.N. Lebedev Physical
Institute, Moscow, Russia
V. Andreev, M. Azarkin, I. Dremin37, M. Kirakosyan, A. Terkulov Skobeltsyn
Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow,
Russia
A. Baskakov, A. Belyaev, E. Boos, V. Bunichev, M. Dubinin41, L. Dudko, V.
Klyukhin, O. Kodolova, N. Korneeva, I. Lokhtin, S. Obraztsov, M. Perfilov, V.
Savrin Novosibirsk State University (NSU), Novosibirsk, Russia
A. Barnyakov42, V. Blinov42, T. Dimova42, L. Kardapoltsev42, Y. Skovpen42
Institute for High Energy Physics of National Research Centre ’Kurchatov
Institute’, Protvino, Russia
I. Azhgirey, I. Bayshev, S. Bitioukov, V. Kachanov, A. Kalinin, D.
Konstantinov, P. Mandrik, V. Petrov, R. Ryutin, S. Slabospitskii, A. Sobol, S.
Troshin, N. Tyurin, A. Uzunian, A. Volkov National Research Tomsk Polytechnic
University, Tomsk, Russia
A. Babaev, S. Baidali, V. Okhotnikov University of Belgrade, Faculty of
Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia
P. Adzic43, P. Cirkovic, D. Devetak, M. Dordevic, P. Milenovic44, 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.
Fallavollita45, D. Fasanella, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, A.
Gilbert, K. Gill, F. Glege, M. Gruchala, M. Guilbaud, D. Gulhan, J. Hegeman,
C. Heidegger, V. Innocente, G.M. Innocenti, A. Jafari, P. Janot, O.
Karacheban17, 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. Pantaleo14, L. Pape, E. Perez, M. Peruzzi, A.
Petrilli, G. Petrucciani, A. Pfeiffer, M. Pierini, F.M. Pitters, D. Rabady, A.
Racz, T. Reis, M. Rovere, H. Sakulin, C. Schäfer, C. Schwick, M. Selvaggi, A.
Sharma, P. Silva, P. Sphicas46, A. Stakia, J. Steggemann, D. Treille, A.
Tsirou, A. Vartak, M. Verzetti, W.D. Zeuner Paul Scherrer Institut, Villigen,
Switzerland
L. Caminada47, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C.
Kaestli, D. Kotlinski, U. Langenegger, T. Rohe, S.A. Wiederkehr ETH Zurich -
Institute for Particle Physics and Astrophysics (IPA), Zurich, Switzerland
M. Backhaus, 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. Amsler48, D. Brzhechko, M.F. Canelli, A. De Cosa, R. Del
Burgo, S. Donato, C. Galloni, T. Hreus, B. Kilminster, S. Leontsinis, I.
Neutelings, G. Rauco, P. Robmann, D. Salerno, K. Schweiger, C. Seitz, Y.
Takahashi, S. Wertz, A. Zucchetta National Central University, Chung-Li,
Taiwan
T.H. Doan, R. Khurana, C.M. Kuo, W. Lin, A. Pozdnyakov, S.S. Yu National
Taiwan University (NTU), Taipei, Taiwan
P. Chang, Y. Chao, K.F. Chen, P.H. Chen, W.-S. Hou, Y.F. Liu, R.-S. Lu, E.
Paganis, A. Psallidas, A. Steen Chulalongkorn University, Faculty of Science,
Department of Physics, Bangkok, Thailand
B. Asavapibhop, N. Srimanobhas, N. Suwonjandee Çukurova University, Physics
Department, Science and Art Faculty, Adana, Turkey
A. Bat, F. Boran, S. Cerci49, S. Damarseckin, Z.S. Demiroglu, F. Dolek, C.
Dozen, I. Dumanoglu, G. Gokbulut, Y. Guler, E. Gurpinar, I. Hos50, C. Isik,
E.E. Kangal51, O. Kara, A. Kayis Topaksu, U. Kiminsu, M. Oglakci, G. Onengut,
K. Ozdemir52, S. Ozturk53, D. Sunar Cerci49, B. Tali49, U.G. Tok, S.
Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East Technical University,
Physics Department, Ankara, Turkey
B. Isildak54, G. Karapinar55, M. Yalvac, M. Zeyrek Bogazici University,
Istanbul, Turkey
I.O. Atakisi, E. Gülmez, M. Kaya56, O. Kaya57, S. Ozkorucuklu58, S. Tekten,
E.A. Yetkin59 Istanbul Technical University, Istanbul, Turkey
M.N. Agaras, A. Cakir, K. Cankocak, Y. Komurcu, S. Sen60 Institute for
Scintillation Materials of National Academy of Science of Ukraine, Kharkov,
Ukraine
B. Grynyov National Scientific Center, Kharkov Institute of Physics and
Technology, Kharkov, Ukraine
L. Levchuk University of Bristol, Bristol, United Kingdom
F. Ball, J.J. Brooke, D. Burns, E. Clement, D. Cussans, O. Davignon, H.
Flacher, J. Goldstein, G.P. Heath, H.F. Heath, L. Kreczko, D.M. Newbold61, S.
Paramesvaran, B. Penning, T. Sakuma, D. Smith, V.J. Smith, J. Taylor, A.
Titterton Rutherford Appleton Laboratory, Didcot, United Kingdom
K.W. Bell, A. Belyaev62, C. Brew, R.M. Brown, D. Cieri, D.J.A. Cockerill, J.A.
Coughlan, K. Harder, S. Harper, J. Linacre, K. Manolopoulos, E. Olaiya, D.
Petyt, 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. Nash63, A. Nikitenko7, V. Palladino, M. Pesaresi, D.M.
Raymond, A. Richards, A. Rose, E. Scott, C. Seez, A. Shtipliyski, G. Singh, M.
Stoye, T. Strebler, S. Summers, A. Tapper, K. Uchida, T. Virdee14, N. Wardle,
D. Winterbottom, J. Wright, S.C. Zenz Brunel University, Uxbridge, United
Kingdom
J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, C.K. Mackay, A. Morton, I.D. Reid,
L. Teodorescu, S. Zahid Baylor University, Waco, USA
K. Call, J. Dittmann, K. Hatakeyama, H. Liu, C. Madrid, B. McMaster, N.
Pastika, C. Smith Catholic University of America, Washington, DC, USA
R. Bartek, A. Dominguez The University of Alabama, Tuscaloosa, USA
A. Buccilli, S.I. Cooper, C. Henderson, P. Rumerio, C. West Boston University,
Boston, USA
D. Arcaro, T. Bose, D. Gastler, S. Girgis, D. Pinna, C. Richardson, J. Rohlf,
L. Sulak, D. Zou Brown University, Providence, USA
G. Benelli, B. Burkle, X. Coubez, D. Cutts, M. Hadley, J. Hakala, U. Heintz,
J.M. Hogan64, K.H.M. Kwok, E. Laird, G. Landsberg, J. Lee, Z. Mao, M. Narain,
S. Sagir65, R. Syarif, E. Usai, D. Yu University of California, Davis, Davis,
USA
R. Band, C. Brainerd, R. Breedon, D. Burns, M. Calderon De La Barca Sanchez,
M. Chertok, J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk,
W. Ko, O. Kukral, R. Lander, M. Mulhearn, D. Pellett, J. Pilot, S. Shalhout,
M. Shi, D. Stolp, D. Taylor, K. Tos, M. Tripathi, Z. Wang, F. Zhang University
of California, Los Angeles, USA
M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, 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, I. Suarez, S. Wang, J. Yoo California Institute of Technology,
Pasadena, USA
D. Anderson, A. Bornheim, J.M. Lawhorn, N. Lu, H.B. Newman, T.Q. Nguyen, 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-Navarro66, 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, D. Sperka, J. Wang, S. Wang, X. Zuo Florida International
University, Miami, USA
Y.R. Joshi, S. Linn Florida State University, Tallahassee, USA
A. Ackert, T. Adams, A. Askew, S. Hagopian, V. Hagopian, K.F. Johnson, T.
Kolberg, G. Martinez, T. Perry, H. Prosper, A. Saha, C. Schiber, R. Yohay
Florida Institute of Technology, Melbourne, USA
M.M. Baarmand, V. Bhopatkar, S. Colafranceschi, M. Hohlmann, D. Noonan, M.
Rahmani, T. Roy, 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. Bilki67, W. Clarida, K. Dilsiz68, S. Durgut, R.P.
Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, A. Mestvirishvili, A.
Moeller, J. Nachtman, H. Ogul69, Y. Onel, F. Ozok70, 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, Z. Demiragli, G. Gomez Ceballos, M. Goncharov, P.
Harris, D. Hsu, M. Hu, Y. Iiyama, 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. Musienko36, M. Planer, R. Ruchti, P. Siddireddy, G. Smith, S. Taroni, M.
Wayne, A. Wightman, M. Wolf, A. Woodard The Ohio State University, Columbus,
USA
J. Alimena, L. Antonelli, B. Bylsma, L.S. Durkin, S. Flowers, B. Francis, C.
Hill, W. Ji, T.Y. Ling, W. Luo, B.L. Winer Princeton University, Princeton,
USA
S. Cooperstein, P. Elmer, J. Hardenbrook, 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. Bouhali71, A. Celik, M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R.
Eusebi, J. Gilmore, T. Huang, T. Kamon72, 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.
Gomber73, 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 Cairo University, Cairo, Egypt
10: Also at Zewail City of Science and Technology, Zewail, Egypt
11: Also at Department of Physics, King Abdulaziz University, Jeddah, Saudi
Arabia
12: Also at Université de Haute Alsace, Mulhouse, France
13: Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State
University, Moscow, Russia
14: Also at CERN, European Organization for Nuclear Research, Geneva,
Switzerland
15: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
16: Also at University of Hamburg, Hamburg, Germany
17: Also at Brandenburg University of Technology, Cottbus, Germany
18: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary
19: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
20: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
21: Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India
22: Also at Institute of Physics, Bhubaneswar, India
23: Also at Shoolini University, Solan, India
24: Also at University of Visva-Bharati, Santiniketan, India
25: Also at Isfahan University of Technology, Isfahan, Iran
26: Also at Plasma Physics Research Center, Science and Research Branch,
Islamic Azad University, Tehran, Iran
27: Also at ITALIAN NATIONAL AGENCY FOR NEW TECHNOLOGIES, ENERGY AND
SUSTAINABLE ECONOMIC DEVELOPMENT, Bologna, Italy
28: Also at Università degli Studi di Siena, Siena, Italy
29: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy
30: Also at Kyunghee University, Seoul, Korea
31: Also at Riga Technical University, Riga, Latvia
32: Also at International Islamic University of Malaysia, Kuala Lumpur,
Malaysia
33: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia
34: Also at Consejo Nacional de Ciencia y Tecnología, Mexico City, Mexico
35: Also at Warsaw University of Technology, Institute of Electronic Systems,
Warsaw, Poland
36: Also at Institute for Nuclear Research, Moscow, Russia
37: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
38: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
39: Also at University of Florida, Gainesville, USA
40: Also at P.N. Lebedev Physical Institute, Moscow, Russia
41: Also at California Institute of Technology, Pasadena, USA
42: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
43: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
44: Also at University of Belgrade, Faculty of Physics and Vinca Institute of
Nuclear Sciences, Belgrade, Serbia
45: Also at INFN Sezione di Pavia a, Università di Pavia b, Pavia, Italy
46: Also at National and Kapodistrian University of Athens, Athens, Greece
47: Also at Universität Zürich, Zurich, Switzerland
48: Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna,
Austria
49: Also at Adiyaman University, Adiyaman, Turkey
50: Also at Istanbul Aydin University, Istanbul, Turkey
51: Also at Mersin University, Mersin, Turkey
52: Also at Piri Reis University, Istanbul, Turkey
53: Also at Gaziosmanpasa University, Tokat, Turkey
54: Also at Ozyegin University, Istanbul, Turkey
55: Also at Izmir Institute of Technology, Izmir, Turkey
56: Also at Marmara University, Istanbul, Turkey
57: Also at Kafkas University, Kars, Turkey
58: Also at Istanbul University, Faculty of Science, Istanbul, Turkey
59: Also at Istanbul Bilgi University, Istanbul, Turkey
60: Also at Hacettepe University, Ankara, Turkey
61: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom
62: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
63: Also at Monash University, Faculty of Science, Clayton, Australia
64: Also at Bethel University, St. Paul, USA
65: Also at Karamanoğlu Mehmetbey University, Karaman, Turkey
66: Also at Purdue University, West Lafayette, USA
67: Also at Beykent University, Istanbul, Turkey
68: Also at Bingol University, Bingol, Turkey
69: Also at Sinop University, Sinop, Turkey
70: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey
71: Also at Texas A&M University at Qatar, Doha, Qatar
72: Also at Kyungpook National University, Daegu, Korea
73: Also at University of Hyderabad, Hyderabad, India