HIN-18-014

HIN-18-014

# First measurement of large area jet transverse momentum spectra in heavy-ion
collisions

###### Abstract

Jet production in lead-lead (PbPb) and proton-proton ($\Pp\Pp$) collisions at
a nucleon-nucleon center-of-mass energy of 5.02is studied with the CMS
detector at the LHC, using PbPb and $\Pp\Pp$ data samples corresponding to
integrated luminosities of 404and 27.4, respectively. Jets with different
areas are reconstructed using the anti- algorithm by varying the distance
parameter $R$. The measurements are performed using jets with transverse
momenta () greater than 200and in a pseudorapidity range of $\abs{\eta}<2$. To
reveal the medium modification of the jet spectra in PbPb collisions, the
properly normalized ratio of spectra from PbPb and $\Pp\Pp$ data is used to
extract jet nuclear modification factors as functions of the PbPb collision
centrality, and, for the first time, as a function of $R$ up to 1.0. For the
most central collisions, a strong suppression is observed for high-jets
reconstructed with all distance parameters, implying that a significant amount
of jet energy is scattered to large angles. The dependence of jet suppression
on $R$ is expected to be sensitive to both the jet energy loss mechanism and
the medium response, and so the data are compared to several modern event
generators and analytic calculations. The models considered do not fully
reproduce the data.

##  0.1 Introduction

Quantum Chromodynamics (QCD), the theory of the strong nuclear force, predicts
that a deconfined state of quarks and gluons, called the quark-gluon plasma
(QGP), should be produced at sufficiently high temperatures and densities [1].
In relativistic heavy ion collisions, the QGP is produced on an extremely
short time scale [2, 3]. A pair of partons (quarks or gluons) in the colliding
nuclei can undergo a high transverse momentum () scattering, a process that
occurs prior to the formation of the QGP. As the scattered partons pass
through and interact with the QGP, they lose some of their energy, thereby
acting as probes of the short-distance structure of the medium [4, 5, 6, 7,
8]. This parton energy loss, often referred to as “jet quenching”, is related
to the transport and thermodynamical properties of the QGP [9, 10, 11, 12].
However, the details of the parton’s interactions with the medium, as well as
the relative importance of each interaction mechanism, are not yet fully
understood [13, 14, 15, 16, 17, 18].

A hard-scattered parton fragments and hadronizes into a collimated spray of
particles. The fragmentation process coevolves with the QGP. The suppression
of inclusive high-hadrons in nucleus-nucleus collisions [19, 20, 21, 22, 23,
24, 25, 26] provides evidence for jet quenching. Experimentally, final-state
particles can be clustered into jets through the use of well-defined
algorithms such as anti- [27]. Various studies of jets and jet pairs, such as
dijet imbalance [28, 29, 30], modifications of the jet yield in the medium
[31, 32, 33, 34], electroweak boson-jet imbalance [35, 36], jet fragmentation
functions [37, 38, 39], missing in dijet systems [28, 29, 40], jet-track
correlations [41, 42], and the radial profile of tracks within jets [43, 44,
45] have been studied. Complementary to these measurements, inclusive jet
spectra reconstructed using different distance parameters $R$ in the anti-
algorithm are of great interest because they are less sensitive to
hadronization effects than observables involving individual final-state
hadrons. The value of $R$ defines the area of the reconstructed jet. By
varying $R$, different fractions of energy from the quenched jet and the
medium response will be included in the reconstructed jet. A differential
study of the suppression versus $R$ provides new sensitivity to the QGP
properties [46] and to the underlying jet quenching mechanism. In particular,
theoretical models and generators based on perturbative QCD [47, 46, 48] and
anti-de Sitter/conformal field theory correspondence [49] predict different
dependences of the jet suppression on $R$.

Modifications to jet production can be quantified by the ratio of the
inclusive jet yields per event in nucleus-nucleus (AA) collisions
($N^{\mathrm{AA}}$) to those in proton-proton ($\Pp\Pp$) collisions
($N^{\Pp\Pp}$), scaled by the mean number of binary nucleon-nucleon (NN)
collisions ($\langle N_{\text{coll}}\rangle$) [50]. This ratio is called the
nuclear modification factor $R_{\mathrm{AA}}$ and is defined as

$R_{\mathrm{AA}}(\pt^{\text{jet}})=\frac{\rd
N^{\mathrm{AA}}/\rd\pt^{\text{jet}}}{\langle N_{\text{coll}}\rangle\rd
N^{\Pp\Pp}/\rd\pt^{\text{jet}}}=\frac{\rd
N^{\mathrm{AA}}/\rd\pt^{\text{jet}}}{\langle
T_{\mathrm{AA}}\rangle\,\rd\sigma^{\Pp\Pp}_{\text{inel}}/\rd\pt^{\text{jet}}}\;,$
(1)

where $\pt^{\text{jet}}$ is the transverse momentum of the jet. The
$R_{\mathrm{AA}}$ is typically measured in bins of centrality, which
characterizes the degree of overlap of the two colliding lead nuclei [29, 51].
The nuclear overlap function $\langle T_{\mathrm{AA}}\rangle$ is defined as
the ratio of $\langle N_{\text{coll}}\rangle$ to the total inelastic $\Pp\Pp$
cross section, $\langle T_{\mathrm{AA}}\rangle=\langle
N_{\text{coll}}\rangle/\sigma^{\Pp\Pp}_{\text{inel}}$, and can be calculated
from a Glauber model of the nuclear collision geometry [51]. If the ratio is
less than one, it indicates a transfer of energy out of the jet cone.
Measurements of the dependence of jet spectra and nuclear modification factors
on the jet distance parameter $R$ can help differentiate between competing
models of parton energy loss mechanisms [52].

In studies of jet suppression from LHC Run 1 with lead-lead (PbPb) collisions
at a nucleon-nucleon center-of-mass energy of $\sqrtsNN=2.76\TeV$, it was
shown that the level of suppression is roughly independent of
$\pt^{\text{jet}}$ in the range $\pt^{\text{jet}}$ = 200–400 [33]. This
suggests that the shape of the spectra is not significantly modified, and the
modifications are predominantly through the overall number of jets. However,
these initial measurements were statistically limited. At $\sqrtsNN=5.02\TeV$,
this measurement can be extended to higher . Furthermore, at this higher
center-of-mass energy, partons traverse a medium of higher density and
temperature.

In this paper, measurements of jet $R_{\mathrm{AA}}$ at
$\pt^{\text{jet}}>200\GeV$ using PbPb collisions at $\sqrtsNN=5.02\TeV$ are
reported. The jets are reconstructed using the anti- algorithm [27] with $R$
varying between 0.2 and 1.0. The results are presented as a function of
$\pt^{\text{jet}}$ in bins of PbPb event centrality.

##  0.2 The CMS apparatus

The central feature of the CMS detector 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. Hadron
forward (HF) calorimeters extend the pseudorapidity coverage up to
$\abs{\eta}=5.2$ and are used for event selection. In the case of PbPb events,
the HF signals are also used to determine the centrality class of the event.
In the barrel section of the ECAL, an energy resolution of about 1% is
achieved for unconverted or late-converting photons that have energies in the
range of tens of GeV. The remaining barrel photons have a resolution of about
1.3% up to $\abs{\eta}=1$, rising to about 2.5% at $\abs{\eta}=1.4$. In the
endcaps, the resolution of unconverted or late-converting photons is about
2.5%, while the remaining endcap photons have a resolution between 3 and 4%
[53]. When combining information from the entire detector, the jet energy
resolution amounts typically to 15% at 10, 8% at 100, and 4% at 1, to be
compared to about 40, 12, and 5% obtained when the ECAL and HCAL calorimeters
alone are used [54]. Muons are detected in gas-ionization chambers embedded in
the steel flux-return yoke outside the solenoid. The silicon tracker measures
charged particles within $\abs{\eta}<2.5$. It consists of 1440 silicon pixel
and 15 148 silicon strip detector modules. For nonisolated particles of
$1<\pt<10\GeV$ and $\abs{\eta}<1.4$, the track resolutions are typically 1.5%
in and 25–90 (45–150)in the transverse (longitudinal) impact parameter [55].
Events of interest are selected using a two-tiered trigger system [56]. The
first level, composed of custom hardware processors, uses information from the
calorimeters and muon detectors to select events at a rate of around 100kHz
within a time interval of less than 4. The second level, known as the high-
level trigger, consists of a farm of processors running a version of the full
event reconstruction software optimized for fast processing, and reduces the
event rate to around 1kHz before data storage. A more detailed description of
the CMS detector, together with a definition of the coordinate system used and
the relevant kinematic variables, can be found in Ref. [57].

##  0.3 Event selection

The event samples are recorded with dedicated jet triggers with different
$\pt^{\text{jet}}$ thresholds, the smallest of which is
$\pt^{\text{jet}}>80\GeV$ [36]. The efficiencies of the triggering algorithms
are evaluated in data and are found to reach unity in both $\Pp\Pp$ and PbPb
collisions for jets considered in this paper ($\pt^{\text{jet}}>200\GeV$). A
number of requirements are made to the events to remove non-collision events
(, beam-gas interactions) and to select only inelastic hadronic collisions
[58, 36]. Both $\Pp\Pp$ and PbPb events are required to have at least one
reconstructed primary interaction vertex with a distance from the center of
the nominal interaction region of less than 15along the beam direction. In
addition, in PbPb collisions the shapes of the clusters in the pixel detector
have to be compatible with those produced by a genuine collision [59]. The
PbPb collision events are also required to have at least three towers in each
of the HF detectors with energy deposits of more than 3per tower. These
criteria select $99$% of inelastic hadronic PbPb collisions [29].

The collision centrality for PbPb events is determined using the total sum of
transverse energy from the calorimeter towers in the HF region. The transverse
energy distribution is used to divide the event sample into bins of percentage
of the total hadronic interaction cross section [29]. The results in this
paper are presented in four centrality intervals, where 0% corresponds to a
full overlap of the two nuclei: 0–10, 10–30, 30–50, and 50–90%. The
corresponding $\langle T_{\mathrm{AA}}\rangle$ and $\langle
N_{\text{coll}}\rangle$ values used in this paper for the centrality intervals
are listed in Table 0.3.

The values of $\langle N_{\text{coll}}\rangle$ and $\langle
T_{\mathrm{AA}}\rangle$, and their uncertainties in $\sqrtsNN=5.02\TeV$ PbPb
collisions for the centrality ranges used in this analysis [50].  Centrality
$\langle N_{\text{coll}}\rangle$ $\langle T_{\mathrm{AA}}\rangle$ [mb-1]
$0\text{--}10\%$ $1630{{}^{+120}_{-120}}$ $23.2{{}^{+0.4}_{-0.7}}$
$10\text{--}30\%$ $805{{}^{+55}_{-58}}$ $11.5{{}^{+0.3}_{-0.4}}$
$30\text{--}50\%$ $267{{}^{+20}_{-20}}$ $3.82{{}^{+0.21}_{-0.21}}$
$50\text{--}90\%$ $30.8{{}^{+3.5}_{-2.4}}$ $0.440{{}^{+0.049}_{-0.032}}$

##  0.4 Monte Carlo simulations

Several Monte Carlo (MC) simulated jet event samples are used to evaluate
background components, efficiencies, misreconstructed jet rates (arising from
upward fluctuations of the underlying event (UE) without a corresponding hard
parton), jet energy corrections and jet energy resolutions (JER). Proton-
proton collisions are generated with 8.212 [60], with the UE tune CUETP8M1
[61], as well as with 6 [62], with the UE tune Z2 [63] with PDF set CTEQ6L1
[64]. For the PbPb MC samples, each signal event is embedded into a PbPb
collision event generated with v1.8 [65], which is tuned to reproduce global
event properties such as the charged-hadron spectrum and particle
multiplicity. The detailed simulation of the CMS detector response is
performed using the package [66].

##  0.5 Analysis method

###  0.5.1 Jet reconstruction and underlying event subtraction

Particle candidates are reconstructed with the particle-flow (PF) algorithm
[54], where information from different parts of the detector are combined to
form an optimized description of the event. Jets are clustered from the PF
candidates using the anti- algorithm with distance parameters of
$R=0.2,0.3,0.4,0.6,0.8$, and 1.0, as implemented in the framework [27, 67].

One of the main challenges to reconstructing jets in heavy-ion collisions is
the additional soft UE coming from the QGP. In order to subtract the soft UE
in PbPb collisions on an event-by-event basis, an iterative algorithm [68] is
employed. The mean value, $\langle E_{\mathrm{PF}}\rangle$, and dispersion,
$\sigma(E_{\mathrm{PF}})$, of the transverse energies from the PF candidates
are calculated in a number of $\eta$ bins [29, 69, 35] for each event. Then, a
two-step procedure is employed to account for the azimuthal modulation of
background activity arising from the bulk properties of the QGP. In the first
step, the so-called event plane angles
($\Phi_{\mathrm{EP},2},\Phi_{\mathrm{EP},3}$) for the second- and third-order
harmonics of the azimuthal distribution are derived from the HF calorimeters
($3<\abs{\eta}<5$) [70]. This method of estimating the UE gives underlying
energy estimations that are consistent with a previous analysis of photon- and
-tagged jets in which event plane mixing was used [71]. The event plane angles
are not corrected for detector effects since the only goal of this procedure
is to obtain a better description of the modulation of the background level.
For the second step, a fit to the azimuthal angle ($\phi$, in radians)
distribution of charged-hadron PF candidates with $0.3<\pt<3.0\GeV$ and
$\abs{\eta}<1$ is performed. No explicit exclusion of regions close to the jet
is performed, since their effect on the extracted parameters is negligible.
The functional form of the fit is as follows:

$N(\phi)=N_{0}(1+2v_{2}\cos(2[\phi-\Phi_{\mathrm{EP},2}])+2v_{3}\cos(3[\phi-\Phi_{\mathrm{EP},3}])),$
(2)

where $N_{0}$ is the magnitude of average UE activity. The parameters $v_{2}$
and $v_{3}$ quantify the strengths of the collective behaviors of the UE known
as “elliptic” and “triangular” flow, respectively. The event plane angles
$\Phi_{\mathrm{EP},2}$ and $\Phi_{\mathrm{EP},3}$ are fixed to the result from
the first step. A fit is performed per event to extract the parameters
$N_{0}$, $v_{2}$, and $v_{3}$. The fit is discarded if the minimum required
number of candidates (at least 10 entries in each bin) are not met, or if the
reduced $\chi^{2}$ of the fit is greater than 2. In this case, the background
energy density is estimated as a flat distribution in $\phi$, without flow
modulations.

An example of this procedure is shown for data in Fig. 1. The left plot shows
the fit in the extraction region, along with a breakdown of the components of
the fit. The right plot takes parameters extracted from mid-rapidity
($\abs{\eta}<1$) and renormalizes the function to data at forward-rapidity
($1<\abs{\eta}<2$). A good agreement of the shape for background modulations
in the two $\eta$ ranges is observed.

Figure 1: (Color online) Azimuthal angle distributions for a single PbPb
event: $\phi$ modulations at mid-rapidity $\abs{\eta}<1$ (left) and forward
rapidity $1<\abs{\eta}<2$ (right) of charged-hadron PF candidates. The $v_{2}$
(blue curve) and $v_{3}$ (yellow curve) of the flow components are shown,
together with the total modulation used in the analysis to account for the
background (red curve). The flow coefficients are extracted from the left plot
and overlaid in the right plot.

Finally, the UE subtraction in PbPb collisions is performed using a
constituent subtraction method [72]. This is a particle-by-particle approach
that corrects the energy of each jet constituent based on the local average UE
density $\rho(\eta,\phi)$. This density is assumed to factorize in $\eta$ and
$\phi$ according to the form

$\rho(\eta,\phi)=\rho(\eta)(1+2v_{2}\cos(2[\phi-\Phi_{\mathrm{EP},2}])+2v_{3}\cos(3[\phi-\Phi_{\mathrm{EP},3}])).$
(3)

Here $\rho(\eta)$ encodes the variation of the UE density as a function of
$\eta$, and the flow parameters are determined in the previous fit. The
average UE density $\rho(\eta)$ is calculated as the average energy in given
$\eta$ bins, excluding regions overlapping with jets. In $\Pp\Pp$ collisions,
where the UE level is negligible, jets are reconstructed without UE
subtraction.

###  0.5.2 Jet energy scale and resolution

Jet energy corrections are derived from simulation separately for $\Pp\Pp$ and
PbPb data following methods outlined in Ref. [73]. The energy scales are
verified with an energy balance method applied to dijet and photon+jet events
in $\Pp\Pp$ data. For this study, jets with $\abs{\eta^{\text{jet}}}<2$ and
(corrected) $\pt^{\text{jet}}>160\GeV$ are selected.

The $\pt^{\text{jet}}$ binning of the analysis is chosen based on the JER for
each cone size and centrality. For $\Pp\Pp$ events, the JER varies by less
than $10\%$ for different values of $R$. These variations reflect how the
probability for energy to move into or out of the jet cone changes with cone
sizes. Figure 2 shows the PbPb jet energy scale (JES, upper), defined as the
reconstructed $\pt^{\text{jet}}$ divided by the generated $\pt^{\text{jet}}$,
and JER (lower), for $R=0.2$ (left) and $R=1.0$ (right) as functions of the
generated $\pt^{\text{jet}}$. The JES is rather flat vs. $\pt^{\text{jet}}$
while JER decreases with $\pt^{\text{jet}}$. As expected, the resolution is
worse for more central events and for larger values of $R$, because of the
larger UE contribution that must be subtracted. For $R\leq 0.4$ the difference
found in both $\Pp\Pp$ and PbPb simulations between the JES of generated and
reconstructed $\pt^{\text{jet}}$ is below 2% at mid-rapidity ($\abs{\eta}<1$)
and of order 4% for ($1<\abs{\eta}<2$).

Figure 2: The energy scale $\mu$ (upper) and resolution $\sigma/\mu$ (lower)
for PbPb anti- jets with $\abs{\eta^{\text{jet}}}<2$, as functions of
generated $\pt^{\text{jet}}$. The left (right) column shows jets with $R=0.2$
(1.0). Several different centrality classes are shown.

A small nonclosure of up to 2% was observed for all values of $R$ in the
peripheral 70–100% PbPb bin, where the nonclosure is defined as the deviation
of the corrected JES from unity. The UE in this bin is most comparable to that
in $\Pp\Pp$ collisions, and it is used to evaluate the performance of the jet
algorithm with heavy ion reconstruction and subtraction in the absence of UE.
This is necessary, as the difference in tracking and the subtraction of an UE
in PbPb, compared to $\Pp\Pp$, results in modest performance changes even
without a significant UE contribution.

The $\phi$-modulation of $\rho$ shown in Eq. (3) improves the jet resolution
without introducing any biases to the energy scale. However, as can be seen in
Fig. 2, there is evidence of over-subtraction for the largest values of $R$ at
low $\pt^{\text{jet}}$. This is because of uncertainties in the estimation of
$\rho$. Errors in the estimation of $\rho$ tend to be handled much better for
small $R$, as the subtraction scales with the multiplicative area. This over-
subtraction causes the nonclosure to reach up to 4% for $R=1.0$ jets, as seen
in Fig. 2. For smaller values of $R$ the nonclosure is below 2%.

Another source of over-subtraction is caused by the flow-modulated
subtraction. The minimum candidate count requirement for a good UE shape
estimation does not account for the fact that jets could bias the fit. The
over-subtraction occurs when a jet biases the flow modulation fit. While the
fitting for $\phi$ modulation is turned off for events with a small number of
tracks, events close to this threshold could still be affected by these
biases, resulting in a source of nonclosure.

Finally, for the most central events, where $\rho(\eta,\phi)$ ranges from
200–300per unit area and the fluctuations are the largest, there is a global
underestimation of the true UE, particularly in the forward region
($\abs{\eta}>1$). This occurs because towers within jets are nominally
excluded in the estimation of $\rho$ to avoid bias from the hard process. In
the most central events, upward fluctuations of the UE may cause some towers
to be included in the jet and excluded from the UE. If too many towers are
excluded, $\rho$ is underestimated. This underestimation of $\rho$ results in
the largest uncertainty in the final $R_{\mathrm{AA}}$ and spectra for the
most central bins. It is mitigated by setting an upper limit on the number of
excluded towers, with a cutoff that is tuned to achieve the best performance.

###  0.5.3 Unfolding

Raw spectra are unfolded according to response matrices constructed using + MC
for PbPb and pure for $\Pp\Pp$ results, in matched bins of $\pt^{\text{jet}}$,
$\eta^{\text{jet}}$, and for PbPb only, event centrality. The matrices are
constructed with an $N_{\text{coll}}$ distribution that matches the
expectations from data. The unfolding is done with the d’Agostini iteration
with early stopping [74] as implemented in the RooUnfold package [75].
Examples of response matrices are shown in Fig. 3 for $\Pp\Pp$ and 0–10% PbPb
collisions with $R=0.2$ and $1.0$. Underflow bins are shown to account for bin
migration. As expected, the matrices are more tightly diagonal for $\Pp\Pp$
events than for PbPb, and for $R=0.2$ than for $R=1.0$. The unfolded $\Pp\Pp$
and PbPb spectra are then used to construct the $R_{\mathrm{AA}}$
distribution.

Figure 3: Response matrices in (left) and + 0–10% PbPb (right) events for jets
reconstructed with $R=0.2$ (upper), $R=1.0$ (lower) and
$\abs{\eta^{\text{jet}}}<2$. The integral for each generated
$\pt^{\text{jet}}$ bin is normalized to unity.

##  0.6 Systematic uncertainties

The systematic uncertainties in the spectra are estimated by varying analysis
parameters one at a time within a reasonable range, propagating the change
through the full analysis chain, and then considering the deviation from the
nominal results. For $R_{\mathrm{AA}}$, any correlation between the
uncertainties in the $\Pp\Pp$ and PbPb spectra is accounted for by
simultaneously changing the same parameter in the $\Pp\Pp$ and PbPb analyses,
calculating a new $R_{\mathrm{AA}}$ and taking the difference from the nominal
result. This procedure produces a significant reduction in the uncertainty
from data-simulation differences that impact JES and JER since the $\Pp\Pp$
and PbPb were taken in run periods separated by just a few days. For ratios of
$R_{\mathrm{AA}}$ between different jet radii, the luminosity and the $\langle
T_{\mathrm{AA}}\rangle$ uncertainties cancel.

Finally, in the $R_{\mathrm{AA}}$ ratio between different radii, and the
$\Pp\Pp$ ratios of spectra between radii, there are statistical cancellations
as the same jet may contribute to multiple $R$ spectra. These are accounted
for by comparing ratios of spectra in pseudo-experiments generated
independently from the spectra and those generated with the correlation
between different $R$ taken from the data.

Figure 4 shows the principal systematic uncertainties as a function of
$\pt^{\text{jet}}$ for $R=0.2$ and $1.0$, and for $\Pp\Pp$ and PbPb collisions
as a function of centrality. The dominant uncertainty arises from the JES.
This tends to increase with $\pt^{\text{jet}}$ and centrality but does not
have a strong dependence upon $R$. The unfolding and JER uncertainties tend to
decrease with $\pt^{\text{jet}}$ and increase with centrality and $R$. The
$\langle T_{\mathrm{AA}}\rangle$ uncertainty decreases from peripheral to
central events and is independent of $\pt^{\text{jet}}$ and $R$.

Figure 4: Relative systematic uncertainties for the spectra of anti- jets
within $\abs{\eta^{\text{jet}}}<2.0$ for $\Pp\Pp$ collisions (left), and PbPb
with centrality classes 50–90%, 30–50%, 10–30%, and 0–10% (rightmost plot).
The upper plots are for jets with $R=0.2$ and the lower plots for jets with
$R=1.0$.

The origins of these uncertainties are listed below in order of importance for
$R_{\mathrm{AA}}$.

  1. 1.

Jet energy scale. The uncertainty ranges from 15 to 20% and is dominated by
the data-simulation difference. It consists of several components, summed in
quadrature:

    1. (a)

Nonclosure in simulation. This uncertainty is evaluated as a function of
centrality and $\eta$ but independently of $\pt^{\text{jet}}$. It is estimated
by varying data by the observed nonclosure in simulation, see Fig. 2, and then
propagating this change through the analysis chain. In $\Pp\Pp$ and peripheral
(50–90%) PbPb collisions, a 1% variation is made for all $\eta$. For 10–50%
centrality, the variation is 1% within $\abs{\eta^{\text{jet}}}<1$ and 2% for
$1<\abs{\eta^{\text{jet}}}<2$. For the most central (0–10%) events, a 2%
variation is made for jets within $\abs{\eta^{\text{jet}}}<1$ and a 4%
variation for $1<\abs{\eta^{\text{jet}}}<2$.

    2. (b)

Data-simulation differences. A flat 2% variation is performed in all bins
following the procedure used for the nonclosure uncertainties above. This
uncertainty is dominant in the $\Pp\Pp$ spectra, and comparable to the
nonclosure uncertainty in semicentral and semiperipheral PbPb bins.

    3. (c)

Differences from the UE description between data and simulation. These
differences are extracted by comparing random cone mean/widths between data
and simulation, and the full difference is taken as a systematic uncertainty.
As this is the centrality-dependent component of the JES, it does not cancel
in the ratios between $\Pp\Pp$ and PbPb data, and only cancels partially in
$R$-dependent ratios of $R_{\mathrm{AA}}$.

  2. 2.

Jet energy resolution.

    1. (a)

The JER uncertainty is extracted from simulation. This is subdominant compared
to the data-simulation differences for spectra, but does not cancel in
$R_{\mathrm{AA}}$.

    2. (b)

Jet energy resolution from data-simulation differences. The resolution in data
is found to be 10 to 15% worse than that in simulation. To propagate this
uncertainty, the simulation is first smeared by 10%, such that central values
are closer to those in data. The systematic uncertainty is estimated by
applying an additional smearing on top of these new central values such that
the resolution is increased by 10% in all bins. The effect is subdominant in
part because the $\pt^{\text{jet}}$ binning was chosen to minimize bin
migration. Furthermore, there is partial cancellation in $R_{\mathrm{AA}}$,
coming from the constant and stochastic terms of the resolution, which are
partially shared between the $\Pp\Pp$ and PbPb data.

  3. 3.

Unfolding. This source of uncertainty is typically of order 5% with a maximum
of 10%. There are several components within this category:

    1. (a)

The choice of the prior. A variation of the nominal prior for the underlying
$\pt^{\text{jet}}$ spectrum is done and propagated through the full analysis
chain, including the response matrix.

    2. (b)

Unfolding algorithm. The result is cross-checked with singular value
decomposition unfolding [76].

  4. 4.

Integrated luminosity and $\langle T_{\mathrm{AA}}\rangle$. The uncertainty in
the integrated luminosity for $\Pp\Pp$ collisions is 2.3% [77]. For the
$\langle T_{\mathrm{AA}}\rangle$, the relative uncertainties vary between 3%
for the 0–10% bin, to 11% in the most peripheral 50–90% bin [50]. The absolute
uncertainties for each of the four values are listed in Table 0.3.

  5. 5.

Misreconstructed jets which arise from fluctuations of the UE. The
contamination from these jets is evaluated from simulation, and it is found to
be negligible in the considered kinematic range.

##  0.7 Results

The unfolded jet spectra as functions of $\pt^{\text{jet}}$ for $R=0.2$ and
$1.0$ for both $\Pp\Pp$ and PbPb collisions of various centralities are shown
in Fig. 5. The lower bound of $\pt^{\text{jet}}$ is chosen based on the
observed noise level for each centrality class, and the upper bound is driven
by the amount of statistics.

Figure 5: Spectra of jets with $\abs{\eta^{\text{jet}}}<2.0$ for $R=0.2$
(left) and $R=1.0$ (right), for $\Pp\Pp$ collisions and different centrality
classes of PbPb collisions. The spectra are multiplied by successive factors
of 10 for clarity. The statistical uncertainties are smaller than the marker
sizes, while the systematic uncertainties are shown as shaded boxes. The
markers are placed at the bin centers.

The upper plot of Fig. 6 shows the ratio of spectra of jets with different
radii in $\Pp\Pp$ collisions, normalized to the spectrum for $R=1.0$. The
number of jets with a given $\pt^{\text{jet}}$ increases with the size of the
jet cone. The increase of jet yield with $R$ becomes weaker at higher values
of $\pt^{\text{jet}}$ suggesting that jets become narrower as
$\pt^{\text{jet}}$ increases. Figure 6 also shows predictions using the 6 and
8 MC generators. Both generators capture the trends of the data but 8 is
closer to the scale of the data. The lower plot of Fig. 6 shows the ratios of
the jet spectra from to the data spectrum for $R=0.2$ and $0.4$. For 6 the
ratio rises with $\pt^{\text{jet}}$ for both values of $R$. The 8 ratios show
little dependence on $\pt^{\text{jet}}$ and are generally closer to unity than
those of 6.

Figure 6: The spectra ratio for jets from $\Pp\Pp$ collisions with
$\abs{\eta^{\text{jet}}}<2.0$ for $R=0.2$–$0.8$ with respect to $R=1.0$. The
statistical uncertainty of data is shown as vertical lines, whereas the
systematic uncertainties are shown as the shaded boxes. Markers for the data
are placed at the bin centers. Comparisons with 6 (solid line) and 8 (dotted
line) are plotted, along with ratios in the lower plot for $R=0.2$ and
$R=0.4$.

The $R_{\mathrm{AA}}$ factors compare PbPb data to the scaled $\Pp\Pp$
reference. Figure 7 shows $R_{\mathrm{AA}}$, the ratio of PbPb data to a
scaled $\Pp\Pp$ reference, as functions of $\pt^{\text{jet}}$, jet radius, and
centrality. Systematic uncertainties related to the JES and JER cancel
partially. The remaining systematic uncertainties are dominated by the
uncertainties in the integrated luminosity, $\langle T_{\mathrm{AA}}\rangle$,
and the JES uncertainty component from the UE.

Figure 7: The $R_{\mathrm{AA}}$ for jets with $\abs{\eta^{\text{jet}}}<2.0$ as
functions of $\pt^{\text{jet}}$ for various $R$ and centrality classes. The
statistical uncertainties are represented by vertical lines, and the
systematic uncertainties by shaded boxes. The markers are placed at the bin
centers. Global uncertainties (integrated luminosity for $\Pp\Pp$ and $\langle
T_{\mathrm{AA}}\rangle$ for PbPb data) are shown as colored boxes on the
dashed line at $R_{\mathrm{AA}}=1$ and are not included in the shaded boxes
around the points.

For all values of $R$, $R_{\mathrm{AA}}$ for the most peripheral collisions
(50–90%) is independent of $\pt^{\text{jet}}$ and consistent with unity after
considering the $\langle T_{\mathrm{AA}}\rangle$ uncertainty. In the most
central bin, a strong suppression of the PbPb data ($\approx$0.6–0.7) is
observed, which is well outside the systematic uncertainties. However, there
are hints of an increasing $R_{\mathrm{AA}}$ with $\pt^{\text{jet}}$ for the
smaller values of $R$ in the central bins, with values up to 0.8 for jets with
$\pt^{\text{jet}}>500\GeV$.

Figure 8: The $R_{\mathrm{AA}}$ ratio for jets with
$\abs{\eta^{\text{jet}}}<2.0$ as a function of $R$ for $R=0.3$–$1.0$ with
respect to $R=0.2$, in various event centrality classes and $\pt^{\text{jet}}$
ranges. The statistical uncertainties of data are shown as the vertical lines,
whereas the systematic uncertainties are shown as the shaded boxes.

To highlight the jet radius dependence of the jet $R_{\mathrm{AA}}$, the
ratios of $R_{\mathrm{AA}}$ for a given $R$ with respect to $R=0.2$ are
presented in Fig. 8. This observable is particularly sensitive to the recovery
of the quenched energy and the presence of the medium response [52]. For
$400<\pt^{\text{jet}}<500\GeV$, the $R_{\mathrm{AA}}$ ratios are above unity
and increase with $\pt^{\text{jet}}$ in both the 0–10% and 10–30% centrality
intervals. On the other hand, for $\pt^{\text{jet}}>500\GeV$, the
$R_{\mathrm{AA}}^{R}/R_{\mathrm{AA}}^{R=0.2}$ is close to unity or slightly
below it for the 0–10% and 10–30% centrality intervals, respectively.

Figure 9 shows $R_{\mathrm{AA}}$ for 0–10% central PbPb collisions, as a
function of $\pt^{\text{jet}}$ for several $R$ values. As $\pt^{\text{jet}}$
increases, $R_{\mathrm{AA}}$ increases. Also shown in Fig. 9 are predictions
from the Jewel [78] (v2.2.0) and pyquen [65] (v1.5.4) generators. The Jewel
predictions are made with (pink) and without (fuchsia) contributions from
recoil particles (scattered medium particles). The predictions without recoil
particles are in disagreement with the data, showing the importance of the
medium response. The importance of recoil particles within Jewel increases
greatly as $R$ increases. For $R=1.0$ the predictions without recoil are a
factor of four below the default mode with recoil. The Jewel predictions with
recoil are significantly below the data for $R=0.2$ but come increasingly
close to the data as $R$ increases.

Predictions from pyquen are shown with (the default, shown in teal) and
without (turquoise) medium-induced wide-angle radiation. The default pyquen
generator overpredicts $R_{\mathrm{AA}}$ particularly for smaller values of
$R$ and $\pt^{\text{jet}}$. The inclusion of wide-angle radiation lowers the
predictions for $R_{\mathrm{AA}}$ particularly for smaller $R$ sizes and
brings the pyquen predictions closer to the data, showing the importance of
the medium effects.

Figure 9: The $R_{\mathrm{AA}}$ for jets with $\abs{\eta^{\text{jet}}}<2.0$,
as a function of $\pt^{\text{jet}}$, for various $R$ and 0–10% centrality
class. The statistical uncertainties are represented by the vertical lines,
while the systematic uncertainties are shown as the shaded boxes. The markers
are placed at the bin centers. Global uncertainties (integrated luminosity for
$\Pp\Pp$ and $\langle T_{\mathrm{AA}}\rangle$ for PbPb collisions) are shown
as the colored boxes on the dashed line at $R_{\mathrm{AA}}=1$ and are not
included in the shaded bands around the points. The predictions from Jewel
(fuchsia and pink) and pyquen (teal and turquoise) generators, shown as
colored boxes, are compared to the data.

Figure 10 shows $R_{\mathrm{AA}}^{R}/R_{\mathrm{AA}}^{R=0.2}$ as a function of
$R$ for several values of $\pt^{\text{jet}}$. Monte Carlo predictions from the
Jewel and pyquen generators are also shown. For the data,
$R_{\mathrm{AA}}^{R}/R_{\mathrm{AA}}^{R=0.2}$ has little dependence upon $R$
and is consistent with unity for all values of $\pt^{\text{jet}}$ for both the
data and the pyquen predictions. The Jewel model is unable to capture the $R$
dependence of $R_{\mathrm{AA}}^{R}/R_{\mathrm{AA}}^{R=0.2}$. For the
predictions with recoil, $R_{\mathrm{AA}}^{R}/R_{\mathrm{AA}}^{R=0.2}$
increases as a function of $R$ but if recoil is ignored
$R_{\mathrm{AA}}^{R}/R_{\mathrm{AA}}^{R=0.2}$ decreases with $R$.

Figure 10: The $R_{\mathrm{AA}}$ ratio for jets with
$\abs{\eta^{\text{jet}}}<2.0$ as a function of $R$ for $R=0.3$–$1.0$ with
respect to $R=0.2$, in various $\pt^{\text{jet}}$ ranges for the 0–10%
centrality class. The statistical uncertainties of data are shown as the
vertical lines, whereas the systematic uncertainties are shown as the shaded
boxes. The width of the boxes carries no meaning. The predictions from Jewel
(fuchsia and pink) and pyquen (teal and turquoise) generators, shown with the
colored bands, are compared to the data.

Figure 11 shows a comparison of several models to $R_{\mathrm{AA}}$ as
functions of $\pt^{\text{jet}}$ and $R$. The Hybrid model [52] combines a
perturbative description of the weakly coupled physics of jet production and
evolution, with a gauge/gravity duality description of the strongly coupled
dynamics of the medium, and the soft-gluon exchanges between the jet and
medium. As the jet passes through and deposits energy into the hydrodynamic
medium, a wake is left behind the jet. The Hybrid model (dark orange) tends to
under-predict $R_{\mathrm{AA}}$ at high $\pt^{\text{jet}}$. Calculations
without a wake (brown) and with only the positive contribution of the wake
(yellow) are also shown. These two are not physical and are included here only
for better understanding of the effect of the wake contribution. The effect of
the wake is more important at large $R$ and lower $\pt^{\text{jet}}$.

In the Linear Boltzmann Transport (lbt) model [79], the effects of recoil
thermal partons and their propagation in the dense medium are described by a
3+1D viscous relativistic hydrodynamic model. Predictions from lbt are shown
in Fig. 11 with and without the medium response. It is clear that the medium
response becomes more and more dominant as the size of the jet cone increases.
A similar effect is seen for the jet-coupled fluid model [80, 48, 81] Ccnu.
Although predictions are only available for a limited $\pt^{\text{jet}}$
range, it is clear from comparing the blue and violet points in Fig. 11 that
the hydrodynamic component of Ccnu becomes increasingly important with
increasing $R$.

The predictions from Martini [82] (Modular Algorithm for Relativistic
Treatment of Heavy IoN Interactions) are shown as purple boxes in Fig. 11. The
model follows a hybrid approach where it embeds the high energy parton into an
evolving hydrodynamic medium, and the shower evolution of the jet is modified
following the McGill-AMY formalism [83, 84, 85, 86, 87]. The Martini generator
predicts a larger increase of jet $R_{\mathrm{AA}}$ ratio as a function of $R$
than what is observed in data.

From Fig. 11, it is striking that, for the small jet radius $R=0.2$,
$R_{\mathrm{AA}}$ rises with $\pt^{\text{jet}}$ but the Hybrid, lbt, Ccnu and
Martini models are all flat in $\pt^{\text{jet}}$. For all these models,
hydrodynamic or medium effects become increasingly important as $R$ increases
and are indeed dominant for $R=1.0$.

Figure 11: The $R_{\mathrm{AA}}$ for jets with $\abs{\eta^{\text{jet}}}<2.0$,
as a function of $\pt^{\text{jet}}$, for various $R$ values and the 0–10%
centrality class. The statistical uncertainties are represented by vertical
lines, while the systematic uncertainties are shown as shaded boxes. The
markers are placed at the bin centers. Global uncertainties (integrated
luminosity for $\Pp\Pp$ and $\langle T_{\mathrm{AA}}\rangle$ for PbPb
collisions) are shown as the colored boxes on the dashed line at
$R_{\mathrm{AA}}$ = 1 and are not included in the shaded bands around the
points. The predictions from Hybrid (dark orange, brown and yellow), Martini
(purple), lbt (lime and dark green), and Ccnu (blue and violet) models, shown
as the colored boxes and bands, are compared to the data.

Figure 12 shows $R_{\mathrm{AA}}^{R}/R_{\mathrm{AA}}^{R=0.2}$ as a function of
$R$, for several values of $\pt^{\text{jet}}$. Monte Carlo predictions from
the Hybrid, Martini, and lbt generators are also shown. The Hybrid model
(orange) is able to describe the data. However if the wake contribution is
ignored (brown) the model gives a different trend. The Martini model (purple)
predicts that $R_{\mathrm{AA}}^{R}/R_{\mathrm{AA}}^{R=0.2}$ should increase
with $R$ in contrast to the data. The default lbt model (lime) is consistent
with the data but lbt with showers only and no medium response (dark green)
overpredicts $R_{\mathrm{AA}}^{R}/R_{\mathrm{AA}}^{R=0.2}$. Some of the models
which correctly predict the trend of
$R_{\mathrm{AA}}^{R}/R_{\mathrm{AA}}^{R=0.2}$ are off in the
$R_{\mathrm{AA}}$, as can be seen in Fig. 11.

Figure 12: The double ratio $R_{\mathrm{AA}}^{R}/R_{\mathrm{AA}}^{R=0.2}$ for
jets with $\abs{\eta^{\text{jet}}}<2.0$, as a function of $R$, for
$R=0.3$–$1.0$ with respect to $R=0.2$, in various $\pt^{\text{jet}}$ ranges
for the 0–10% centrality class. The statistical uncertainties of data are
shown as the vertical lines, whereas the systematic uncertainties are shown as
the shaded boxes. The width of the boxes carries no meaning. The predictions
from the Hybrid (dark orange, brown and yellow), Martini (purple), and lbt
(lime and dark green) models are compared to the data as colored bands.

The same data in Figs. 11 and 12 are also compared to additional models.
Figure 13 shows $R_{\mathrm{AA}}$ vs. $\pt^{\text{jet}}$ for several values of
$R$ and for the top 0–10% centrality class as well as several predictions from
generators and analytic calculations. The gray boxes in Fig. 13 are
predictions from a jet factorization model based on a phenomenological
approach to establish QCD factorization of jet cross sections in heavy ion
collisions [88]. Medium-modified jet functions are extracted from jet nuclear
modification factors at smaller jet distance parameter values ($R=0.2$ and
0.4) and predictions are made for larger distance parameter values. At
$R<0.4$, the data are described reasonably well by the factorization model.
However, the model tends to underpredict $R_{\mathrm{AA}}$ at larger $R$
values. The data are also compared to the coherent antenna bdmps calculations
[89] (orange), which is an analytical approach that resums multiple emissions
to leading-logarithmic accuracy including both radiative energy loss and color
coherence effects [90, 91, 92]. The predictions are in general agreement with
the $R_{\mathrm{AA}}$ data.

Finally, calculations based on a soft collinear effective theory with Glauber
gluon interactions Scet [46], are also compared to the data. The Scet
calculations with collisional energy loss [93, 94] (navy blue) are slightly
below the $R_{\mathrm{AA}}$ measurements while those without collisional
energy loss (sky blue) are consistent with the data.

Figure 13: The $R_{\mathrm{AA}}$ for jets with $\abs{\eta^{\text{jet}}}<2.0$,
as a function of $\pt^{\text{jet}}$, for various $R$ values and 0–10%
centrality class. The statistical uncertainties are represented by the
vertical lines, while the systematic uncertainties are shown as the shaded
boxes. The markers are placed at the bin centers. Global uncertainties
(integrated luminosity for $\Pp\Pp$ and $\langle T_{\mathrm{AA}}\rangle$ for
PbPb collisions) are shown as the colored boxes on the dashed line at
$R_{\mathrm{AA}}=1$ and are not included in the shaded bands around the
points. The calculations from Scet (sky blue and navy blue), coherent antenna
bdmps (orange) and jet factorization (gray) formalisms are compared to the
data, shown as the colored boxes and bands.

Figure 14 shows $R_{\mathrm{AA}}^{R}/R_{\mathrm{AA}}^{R=0.2}$ vs. $R$ for
several values of $\pt^{\text{jet}}$ together with predictions from the Scet,
bdmps and jet factorization models. The bdmps (orange) and Scet predictions
(sky blue and navy blue) are consistent with the data but the factorization
calculations (gray) decrease with $R$ in contrast to the data.

Figure 14: The double ratio $R_{\mathrm{AA}}^{R}/R_{\mathrm{AA}}^{R=0.2}$ for
jets with $\abs{\eta^{\text{jet}}}<2.0$ as a function of $R$ for $R=0.3$–$1.0$
with respect to $R=0.2$, in various $\pt^{\text{jet}}$ ranges for the 0–10%
centrality class. The statistical uncertainties of data are shown as the
vertical lines, whereas the systematic uncertainties are shown as the shaded
boxes. The width of the boxes carries no meaning. The calculations based from
Scet (sky blue and navy blue), coherent antenna bdmps (orange) and, jet
factorization (gray) formalisms, shown with the colored bands and boxes, are
compared to the data.

##  0.8 Summary

Measurements of jet nuclear modification factors based on proton-proton and
lead-lead collisions at $\sqrtsNN=5.02\TeV$ are presented. For the first time,
jet spectra measurements are extended to large area jets, with a anti-
distance parameter $R$ up to 1.0. For the most central PbPb collisions, a
strong suppression is observed for jets with high transverse momentum
reconstructed with all distance parameters. Predictions from quenched jet
event generators, theoretical models, and analytical calculations are compared
to these results. The new data place further constraints on the underlying jet
quenching mechanisms. While state of the art models have made important
progress, significant tension remains in view of the large area jet data
presented here.

###### 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 and other
centers 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, the CMS detector, and the supporting
computing infrastructure 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); RIF (Cyprus); SENESCYT
(Ecuador); MoER, ERC PUT 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 (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 Nos. 675440, 724704, 752730, and 765710 (European Union); the
Leventis Foundation; the Alfred 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 Beijing Municipal Science & Technology
Commission, No. Z191100007219010; the Ministry of Education, Youth and Sports
(MEYS) of the Czech Republic; the Deutsche Forschungsgemeinschaft (DFG), under
Germany’s Excellence Strategy – EXC 2121 “Quantum Universe” – 390833306, and
under project number 400140256 - GRK2497; the Lendület (“Momentum”) Program
and the János Bolyai Research Scholarship of the Hungarian Academy of
Sciences, the New National Excellence Program ÚNKP, the NKFIA research grants
123842, 123959, 124845, 124850, 125105, 128713, 128786, and 129058 (Hungary);
the Council of Science and Industrial Research, India; the Ministry of Science
and Higher Education and the National Science Center, contracts Opus
2014/15/B/ST2/03998 and 2015/19/B/ST2/02861 (Poland); the National Priorities
Research Program by Qatar National Research Fund; the Ministry of Science and
Higher Education, project no. 0723-2020-0041 (Russia); 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 Kavli Foundation; the Nvidia Corporation;
the SuperMicro Corporation; the Welch Foundation, contract C-1845; and the
Weston Havens Foundation (USA).

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##  .9 The CMS Collaboration

Yerevan Physics Institute, Yerevan, Armenia
A.M. Sirunyan${}^{\textrm{\textdagger}}$, A. Tumasyan Institut für
Hochenergiephysik, Wien, Austria
W. Adam, F. Ambrogi, T. Bergauer, M. Dragicevic, J. Erö, A. Escalante Del
Valle, M. Flechl, R. Frühwirth1, M. Jeitler1, N. Krammer, I. Krätschmer, D.
Liko, T. Madlener, I. Mikulec, N. Rad, J. Schieck1, R. Schöfbeck, M. Spanring,
W. Waltenberger, C.-E. Wulz1, M. Zarucki Institute for Nuclear Problems,
Minsk, Belarus
V. Drugakov, V. Mossolov, J. Suarez Gonzalez Universiteit Antwerpen,
Antwerpen, Belgium
M.R. Darwish, E.A. De Wolf, D. Di Croce, X. Janssen, T. Kello2, A. Lelek, M.
Pieters, H. Rejeb Sfar, H. Van Haevermaet, P. Van Mechelen, S. Van Putte, N.
Van Remortel Vrije Universiteit Brussel, Brussel, Belgium
F. Blekman, E.S. Bols, S.S. Chhibra, J. D’Hondt, J. De Clercq, D. Lontkovskyi,
S. Lowette, I. Marchesini, S. Moortgat, Q. Python, S. Tavernier, W. Van
Doninck, P. Van Mulders Université Libre de Bruxelles, Bruxelles, Belgium
D. Beghin, B. Bilin, B. Clerbaux, G. De Lentdecker, H. Delannoy, B. Dorney, L.
Favart, A. Grebenyuk, A.K. Kalsi, L. Moureaux, A. Popov, N. Postiau, E.
Starling, L. Thomas, C. Vander Velde, P. Vanlaer, D. Vannerom Ghent
University, Ghent, Belgium
T. Cornelis, D. Dobur, I. Khvastunov3, M. Niedziela, C. Roskas, K. Skovpen, M.
Tytgat, W. Verbeke, B. Vermassen, M. Vit Université Catholique de Louvain,
Louvain-la-Neuve, Belgium
G. Bruno, C. Caputo, P. David, C. Delaere, M. Delcourt, A. Giammanco, V.
Lemaitre, J. Prisciandaro, A. Saggio, P. Vischia, J. Zobec Centro Brasileiro
de Pesquisas Fisicas, Rio de Janeiro, Brazil
G.A. Alves, G. Correia Silva, C. Hensel, A. Moraes Universidade do Estado do
Rio de Janeiro, Rio de Janeiro, Brazil
E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato4, E. Coelho, E.M.
Da Costa, G.G. Da Silveira5, D. De Jesus Damiao, C. De Oliveira Martins, S.
Fonseca De Souza, H. Malbouisson, J. Martins6, D. Matos Figueiredo, M. Medina
Jaime7, M. Melo De Almeida, C. Mora Herrera, L. Mundim, H. Nogima, W.L. Prado
Da Silva, P. Rebello Teles, L.J. Sanchez Rosas, A. Santoro, A. Sznajder, M.
Thiel, E.J. Tonelli Manganote4, F. Torres Da Silva De Araujo, A. Vilela
Pereira Universidade Estadual Paulista a, Universidade Federal do ABC b, São
Paulo, Brazil
C.A. Bernardesa, L. Calligarisa, T.R. Fernandez Perez Tomeia, E.M. Gregoresb,
D.S. Lemosa, P.G. Mercadanteb, S.F. Novaesa, Sandra S. Padulaa Institute for
Nuclear Research and Nuclear Energy, Bulgarian Academy of Sciences, Sofia,
Bulgaria
A. Aleksandrov, G. Antchev, R. Hadjiiska, P. Iaydjiev, M. Misheva, M. Rodozov,
M. Shopova, G. Sultanov University of Sofia, Sofia, Bulgaria
M. Bonchev, A. Dimitrov, T. Ivanov, L. Litov, B. Pavlov, P. Petkov, A. Petrov
Beihang University, Beijing, China
W. Fang2, X. Gao2, L. Yuan Department of Physics, Tsinghua University,
Beijing, China
M. Ahmad, Z. Hu, Y. Wang Institute of High Energy Physics, Beijing, China
G.M. Chen8, H.S. Chen8, M. Chen, C.H. Jiang, D. Leggat, H. Liao, Z. Liu, A.
Spiezia, J. Tao, E. Yazgan, H. Zhang, S. Zhang8, J. Zhao State Key Laboratory
of Nuclear Physics and Technology, Peking University, Beijing, China
A. Agapitos, Y. Ban, G. Chen, A. Levin, J. Li, L. Li, Q. Li, Y. Mao, S.J.
Qian, D. Wang, Q. Wang Zhejiang University, Hangzhou, China
M. Xiao Universidad de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, C. Florez, C.F. González Hernández, M.A. Segura Delgado
Universidad de Antioquia, Medellin, Colombia
J. Mejia Guisao, J.D. Ruiz Alvarez, C.A. Salazar González, N. Vanegas Arbelaez
University of Split, Faculty of Electrical Engineering, Mechanical Engineering
and Naval Architecture, Split, Croatia
D. Giljanović, N. Godinovic, D. Lelas, I. Puljak, T. Sculac University of
Split, Faculty of Science, Split, Croatia
Z. Antunovic, M. Kovac Institute Rudjer Boskovic, Zagreb, Croatia
V. Brigljevic, D. Ferencek, K. Kadija, B. Mesic, M. Roguljic, A. Starodumov9,
T. Susa University of Cyprus, Nicosia, Cyprus
M.W. Ather, A. Attikis, E. Erodotou, A. Ioannou, M. Kolosova, S. Konstantinou,
G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H.
Rykaczewski, H. Saka, D. Tsiakkouri Charles University, Prague, Czech Republic
M. Finger10, M. Finger Jr.10, A. Kveton, J. Tomsa 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
M.A. Mahmoud11,12, Y. Mohammed11 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, L. Forthomme, H. Kirschenmann, K. Osterberg, M. Voutilainen
Helsinki Institute of Physics, Helsinki, Finland
F. Garcia, J. Havukainen, J.K. Heikkilä, V. Karimäki, M.S. Kim, R. Kinnunen,
T. Lampén, K. Lassila-Perini, S. Laurila, S. Lehti, T. Lindén, H. Siikonen, E.
Tuominen, J. Tuominiemi Lappeenranta University of Technology, Lappeenranta,
Finland
P. Luukka, T. Tuuva IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
M. Besancon, F. Couderc, M. Dejardin, D. Denegri, B. Fabbro, J.L. Faure, F.
Ferri, S. Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry,
C. Leloup, B. Lenzi, E. Locci, J. Malcles, J. Rander, A. Rosowsky, M.Ö. Sahin,
A. Savoy-Navarro13, M. Titov, G.B. Yu Laboratoire Leprince-Ringuet,
CNRS/IN2P3, Ecole Polytechnique, Institut Polytechnique de Paris, Palaiseau,
France
S. Ahuja, C. Amendola, F. Beaudette, M. Bonanomi, P. Busson, C. Charlot, B.
Diab, G. Falmagne, R. Granier de Cassagnac, I. Kucher, A. Lobanov, C. Martin
Perez, M. Nguyen, C. Ochando, P. Paganini, J. Rembser, R. Salerno, J.B.
Sauvan, Y. Sirois, A. Zabi, A. Zghiche Université de Strasbourg, CNRS, IPHC
UMR 7178, Strasbourg, France
J.-L. Agram14, J. Andrea, D. Bloch, G. Bourgatte, J.-M. Brom, E.C. Chabert, C.
Collard, E. Conte14, J.-C. Fontaine14, D. Gelé, U. Goerlach, C. Grimault,
A.-C. Le Bihan, N. Tonon, P. Van Hove Centre de Calcul de l’Institut National
de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne,
France
S. Gadrat Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3,
Institut de Physique Nucléaire de Lyon, Villeurbanne, France
S. Beauceron, C. Bernet, G. Boudoul, C. Camen, A. Carle, N. Chanon, R.
Chierici, D. Contardo, P. Depasse, H. El Mamouni, J. Fay, S. Gascon, M.
Gouzevitch, B. Ille, Sa. Jain, I.B. Laktineh, H. Lattaud, A. Lesauvage, M.
Lethuillier, L. Mirabito, S. Perries, V. Sordini, L. Torterotot, G. Touquet,
M. Vander Donckt, S. Viret Georgian Technical University, Tbilisi, Georgia
G. Adamov Tbilisi State University, Tbilisi, Georgia
I. Bagaturia15 RWTH Aachen University, I. Physikalisches Institut, Aachen,
Germany
C. Autermann, L. Feld, K. Klein, M. Lipinski, D. Meuser, A. Pauls, M. Preuten,
M.P. Rauch, J. Schulz, M. Teroerde RWTH Aachen University, III. Physikalisches
Institut A, Aachen, Germany
M. Erdmann, B. Fischer, S. Ghosh, T. Hebbeker, K. Hoepfner, H. Keller, L.
Mastrolorenzo, M. Merschmeyer, A. Meyer, P. Millet, G. Mocellin, S. Mondal, S.
Mukherjee, D. Noll, A. Novak, T. Pook, A. Pozdnyakov, T. Quast, M. Radziej, Y.
Rath, H. Reithler, J. Roemer, A. Schmidt, S.C. Schuler, A. Sharma, S.
Wiedenbeck, S. Zaleski RWTH Aachen University, III. Physikalisches Institut B,
Aachen, Germany
G. Flügge, W. Haj Ahmad16, O. Hlushchenko, T. Kress, T. Müller, A. Nowack, C.
Pistone, O. Pooth, D. Roy, H. Sert, A. Stahl17 Deutsches Elektronen-
Synchrotron, Hamburg, Germany
M. Aldaya Martin, P. Asmuss, I. Babounikau, H. Bakhshiansohi, K. Beernaert, O.
Behnke, A. Bermúdez Martínez, A.A. Bin Anuar, K. Borras18, V. Botta, A.
Campbell, A. Cardini, P. Connor, S. Consuegra Rodríguez, C. Contreras-Campana,
V. Danilov, A. De Wit, M.M. Defranchis, C. Diez Pardos, D. Domínguez Damiani,
G. Eckerlin, D. Eckstein, T. Eichhorn, A. Elwood, E. Eren, E. Gallo19, A.
Geiser, A. Grohsjean, M. Guthoff, M. Haranko, A. Harb, A. Jafari, N.Z.
Jomhari, H. Jung, A. Kasem18, M. Kasemann, H. Kaveh, J. Keaveney, C.
Kleinwort, J. Knolle, D. Krücker, W. Lange, T. Lenz, J. Lidrych, K. Lipka, W.
Lohmann20, R. Mankel, I.-A. Melzer-Pellmann, A.B. Meyer, M. Meyer, M.
Missiroli, J. Mnich, A. Mussgiller, V. Myronenko, D. Pérez Adán, S.K.
Pflitsch, D. Pitzl, A. Raspereza, A. Saibel, M. Savitskyi, V. Scheurer, P.
Schütze, C. Schwanenberger, R. Shevchenko, A. Singh, R.E. Sosa Ricardo, H.
Tholen, O. Turkot, A. Vagnerini, M. Van De Klundert, R. Walsh, Y. Wen, K.
Wichmann, C. Wissing, O. Zenaiev, R. Zlebcik University of Hamburg, Hamburg,
Germany
R. Aggleton, S. Bein, L. Benato, A. Benecke, T. Dreyer, A. Ebrahimi, F.
Feindt, A. Fröhlich, C. Garbers, E. Garutti, D. Gonzalez, P. Gunnellini, J.
Haller, A. Hinzmann, A. Karavdina, G. Kasieczka, R. Klanner, R. Kogler, N.
Kovalchuk, S. Kurz, V. Kutzner, J. Lange, T. Lange, A. Malara, J. Multhaup,
C.E.N. Niemeyer, A. Reimers, O. Rieger, P. Schleper, S. Schumann, J. Schwandt,
J. Sonneveld, H. Stadie, G. Steinbrück, B. Vormwald, I. Zoi Karlsruher
Institut fuer Technologie, Karlsruhe, Germany
M. Akbiyik, M. Baselga, S. Baur, T. Berger, E. Butz, R. Caspart, T. Chwalek,
W. De Boer, A. Dierlamm, K. El Morabit, N. Faltermann, M. Giffels, A.
Gottmann, F. Hartmann17, C. Heidecker, U. Husemann, M.A. Iqbal, S. Kudella, S.
Maier, S. Mitra, M.U. Mozer, D. Müller, Th. Müller, M. Musich, A. Nürnberg, G.
Quast, K. Rabbertz, D. Savoiu, D. Schäfer, M. Schnepf, M. Schröder, I.
Shvetsov, H.J. Simonis, R. Ulrich, M. Wassmer, M. Weber, C. Wöhrmann, R. Wolf,
S. Wozniewski Institute of Nuclear and Particle Physics (INPP), NCSR
Demokritos, Aghia Paraskevi, Greece
G. Anagnostou, P. Asenov, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas,
G. Paspalaki, A. Stakia National and Kapodistrian University of Athens,
Athens, Greece
M. Diamantopoulou, G. Karathanasis, P. Kontaxakis, A. Manousakis-katsikakis,
A. Panagiotou, I. Papavergou, N. Saoulidou, K. Theofilatos, K. Vellidis, E.
Vourliotis National Technical University of Athens, Athens, Greece
G. Bakas, K. Kousouris, I. Papakrivopoulos, G. Tsipolitis, A. Zacharopoulou
University of Ioánnina, Ioánnina, Greece
I. Evangelou, C. Foudas, P. Gianneios, P. Katsoulis, P. Kokkas, S. Mallios, K.
Manitara, N. Manthos, I. Papadopoulos, J. Strologas, F.A. Triantis, D.
Tsitsonis MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
M. Bartók21, R. Chudasama, M. Csanad, P. Major, K. Mandal, A. Mehta, G.
Pasztor, O. Surányi, G.I. Veres Wigner Research Centre for Physics, Budapest,
Hungary
G. Bencze, C. Hajdu, D. Horvath22, F. Sikler, V. Veszpremi, G.
Vesztergombi${}^{\textrm{\textdagger}}$ Institute of Nuclear Research ATOMKI,
Debrecen, Hungary
N. Beni, S. Czellar, J. Karancsi21, J. Molnar, Z. Szillasi Institute of
Physics, University of Debrecen, Debrecen, Hungary
P. Raics, D. Teyssier, Z.L. Trocsanyi, B. Ujvari Eszterhazy Karoly University,
Karoly Robert Campus, Gyongyos, Hungary
T. Csorgo, W.J. Metzger, F. Nemes, T. Novak Indian Institute of Science
(IISc), Bangalore, India
S. Choudhury, J.R. Komaragiri, P.C. Tiwari National Institute of Science
Education and Research, HBNI, Bhubaneswar, India
S. Bahinipati24, C. Kar, G. Kole, P. Mal, V.K. Muraleedharan Nair Bindhu, A.
Nayak25, D.K. Sahoo24, S.K. Swain Panjab University, Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, S. Chauhan, N. Dhingra26, R. Gupta, A.
Kaur, M. Kaur, S. Kaur, P. Kumari, M. Lohan, M. Meena, K. Sandeep, S. Sharma,
J.B. Singh, A.K. Virdi University of Delhi, Delhi, India
A. Bhardwaj, B.C. Choudhary, R.B. Garg, M. Gola, S. Keshri, Ashok Kumar, M.
Naimuddin, P. Priyanka, K. Ranjan, Aashaq Shah, R. Sharma Saha Institute of
Nuclear Physics, HBNI, Kolkata, India
R. Bhardwaj27, M. Bharti27, R. Bhattacharya, S. Bhattacharya, U. Bhawandeep27,
D. Bhowmik, S. Dutta, S. Ghosh, B. Gomber28, M. Maity29, K. Mondal, S. Nandan,
A. Purohit, P.K. Rout, G. Saha, S. Sarkar, M. Sharan, B. Singh27, S. Thakur27
Indian Institute of Technology Madras, Madras, India
P.K. Behera, S.C. Behera, P. Kalbhor, A. Muhammad, P.R. Pujahari, A. Sharma,
A.K. Sikdar Bhabha Atomic Research Centre, Mumbai, India
D. Dutta, V. Jha, D.K. Mishra, P.K. Netrakanti, L.M. Pant, P. Shukla Tata
Institute of Fundamental Research-A, Mumbai, India
T. Aziz, M.A. Bhat, S. Dugad, G.B. Mohanty, N. Sur, Ravindra Kumar Verma Tata
Institute of Fundamental Research-B, Mumbai, India
S. Banerjee, S. Bhattacharya, S. Chatterjee, P. Das, M. Guchait, S. Karmakar,
S. Kumar, G. Majumder, K. Mazumdar, N. Sahoo, S. Sawant Indian Institute of
Science Education and Research (IISER), Pune, India
S. Dube, B. Kansal, A. Kapoor, K. Kothekar, S. Pandey, A. Rane, A. Rastogi, S.
Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
S. Chenarani, S.M. Etesami, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, F.
Rezaei Hosseinabadi 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, R. Alya,b,30, C. Calabriaa,b, A. Colaleoa, D. Creanzaa,c, L.
Cristellaa,b, N. De Filippisa,c, M. De Palmaa,b, A. Di Florioa,b, W.
Elmetenaweea,b, L. Fiorea, A. Gelmia,b, G. Iasellia,c, M. Incea,b, S.
Lezkia,b, G. Maggia,c, M. Maggia, J.A. Merlina, G. Minielloa,b, S. Mya,b, S.
Nuzzoa,b, A. Pompilia,b, G. Pugliesea,c, R. Radognaa, A. Ranieria, G.
Selvaggia,b, L. Silvestrisa, F.M. Simonea,b, 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,
C. Cioccaa, G. Codispotia,b, M. Cuffiania,b, G.M. Dallavallea, F. Fabbria, A.
Fanfania,b, E. Fontanesia,b, P. Giacomellia, L. Giommia,b, C. Grandia, L.
Guiduccia,b, F. Iemmia,b, S. Lo Meoa,31, S. Marcellinia, G. Masettia, F.L.
Navarriaa,b, A. Perrottaa, F. Primaveraa,b, T. Rovellia,b, G.P. Sirolia,b, N.
Tosia INFN Sezione di Catania a, Università di Catania b, Catania, Italy
S. Albergoa,b,32, S. Costaa,b,32, A. Di Mattiaa, R. Potenzaa,b, A.
Tricomia,b,32, C. Tuvea,b INFN Sezione di Firenze a, Università di Firenze b,
Firenze, Italy
G. Barbaglia, A. Cassesea, R. Ceccarellia,b, V. Ciullia,b, C. Civininia, R.
D’Alessandroa,b, F. Fioria, E. Focardia,b, G. Latinoa,b, P. Lenzia,b, M.
Meschinia, S. Paolettia, G. Sguazzonia, L. Viliania INFN Laboratori Nazionali
di Frascati, Frascati, Italy
L. Benussi, S. Bianco, D. Piccolo INFN Sezione di Genova a, Università di
Genova b, Genova, Italy
M. Bozzoa,b, F. Ferroa, R. Mulargiaa,b, E. Robuttia, S. Tosia,b INFN Sezione
di Milano-Bicocca a, Università di Milano-Bicocca b, Milano, Italy
A. Benagliaa, A. Beschia,b, F. Brivioa,b, V. Cirioloa,b,17, M.E. Dinardoa,b,
P. Dinia, S. Gennaia, A. Ghezzia,b, P. Govonia,b, L. Guzzia,b, M. Malbertia,
S. Malvezzia, D. Menascea, F. Montia,b, L. Moronia, M. Paganonia,b, D.
Pedrinia, S. Ragazzia,b, T. Tabarelli de Fatisa,b, D. Valsecchia,b,17, 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. Layera,b, L. Listaa,b,
S. Meolaa,d,17, P. Paoluccia,17, B. Rossia, 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. Bragagnoloa,b, R.
Carlina,b, P. Checchiaa, P. De Castro Manzanoa, T. Dorigoa, U. Dossellia, F.
Gasparinia,b, U. Gasparinia,b, A. Gozzelinoa, S.Y. Hoha,b, M. Margonia,b, A.T.
Meneguzzoa,b, J. Pazzinia,b, M. Presillab, P. Ronchesea,b, R. Rossina,b, F.
Simonettoa,b, A. Tikoa, M. Tosia,b, M. Zanettia,b, P. Zottoa,b, A.
Zucchettaa,b, G. Zumerlea,b INFN Sezione di Pavia a, Università di Pavia b,
Pavia, Italy
A. Braghieria, D. Fiorinaa,b, P. Montagnaa,b, S.P. Rattia,b, V. Rea, M.
Ressegottia,b, C. Riccardia,b, P. Salvinia, I. Vaia, P. Vituloa,b INFN Sezione
di Perugia a, Università di Perugia b, Perugia, Italy
M. Biasinia,b, G.M. Bileia, 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, Università di Siena d,
Siena, Italy
K. Androsova, P. Azzurria, G. Bagliesia, V. Bertacchia,c, L. Bianchinia, T.
Boccalia, R. Castaldia, M.A. Cioccia,b, R. Dell’Orsoa, S. Donatoa, 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. Rolandia,c, S. Roy
Chowdhurya,c, A. Scribanoa, P. Spagnoloa, R. Tenchinia, G. Tonellia,b, N.
Turinia,d, A. Venturia, P.G. Verdinia INFN Sezione di Roma a, Sapienza
Università di Roma b, Rome, Italy
F. Cavallaria, M. Cipriania,b, D. Del Rea,b, E. Di Marcoa, M. Diemoza, E.
Longoa,b, P. Meridiania, G. Organtinia,b, F. Pandolfia, R. Paramattia,b, C.
Quarantaa,b, S. Rahatloua,b, C. Rovellia, F. Santanastasioa,b, L. Soffia,b, R.
Tramontanoa,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, A. Belloraa,b, C. Biinoa, A. Cappatia,b, N. Cartigliaa, S.
Comettia, M. Costaa,b, R. Covarellia,b, N. Demariaa, J.R. González Fernándeza,
B. Kiania,b, F. Leggera, C. Mariottia, S. Masellia, E. Migliorea,b, V.
Monacoa,b, E. Monteila,b, M. Montenoa, M.M. Obertinoa,b, G. Ortonaa, L.
Pachera,b, N. Pastronea, M. Pelliccionia, G.L. Pinna Angionia,b, A. Romeroa,b,
M. Ruspaa,c, R. Salvaticoa,b, V. Solaa, A. Solanoa,b, D. Soldia,b, A.
Staianoa, D. Trocinoa,b INFN Sezione di Trieste a, Università di Trieste b,
Trieste, Italy
S. Belfortea, V. Candelisea,b, M. Casarsaa, F. Cossuttia, A. Da Rolda,b, G.
Della Riccaa,b, F. Vazzolera,b, A. Zanettia Kyungpook National University,
Daegu, Korea
B. Kim, D.H. Kim, G.N. Kim, J. Lee, S.W. Lee, C.S. Moon, Y.D. Oh, S.I. Pak, S.
Sekmen, D.C. Son, Y.C. Yang Chonnam National University, Institute for
Universe and Elementary Particles, Kwangju, Korea
H. Kim, D.H. Moon Hanyang University, Seoul, Korea
B. Francois, T.J. Kim, J. Park Korea University, Seoul, Korea
S. Cho, S. Choi, Y. Go, S. Ha, B. Hong, K. Lee, K.S. Lee, J. Lim, J. Park,
S.K. Park, Y. Roh, J. Yoo Kyung Hee University, Department of Physics, Seoul,
Republic of Korea
J. Goh Sejong University, Seoul, Korea
H.S. Kim Seoul National University, Seoul, Korea
J. Almond, J.H. Bhyun, J. Choi, S. Jeon, J. Kim, J.S. Kim, H. Lee, K. Lee, S.
Lee, K. Nam, M. Oh, S.B. Oh, B.C. Radburn-Smith, U.K. Yang, H.D. Yoo, I. Yoon
University of Seoul, Seoul, Korea
D. Jeon, J.H. Kim, J.S.H. Lee, I.C. Park, I.J. Watson Sungkyunkwan University,
Suwon, Korea
Y. Choi, C. Hwang, Y. Jeong, J. Lee, Y. Lee, I. Yu Riga Technical University,
Riga, Latvia
V. Veckalns33 Vilnius University, Vilnius, Lithuania
V. Dudenas, A. Juodagalvis, A. Rinkevicius, G. Tamulaitis, J. Vaitkus National
Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, Malaysia
F. Mohamad Idris34, W.A.T. Wan Abdullah, M.N. Yusli, Z. Zolkapli Universidad
de Sonora (UNISON), Hermosillo, Mexico
J.F. Benitez, A. Castaneda Hernandez, J.A. Murillo Quijada, L. Valencia Palomo
Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico
H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz35, R. Lopez-
Fernandez, A. Sanchez-Hernandez Universidad Iberoamericana, Mexico City,
Mexico
S. Carrillo Moreno, C. Oropeza Barrera, M. Ramirez-Garcia, F. Vazquez Valencia
Benemerita Universidad Autonoma de Puebla, Puebla, Mexico
J. Eysermans, I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada Universidad
Autónoma de San Luis Potosí, San Luis Potosí, Mexico
A. Morelos Pineda University of Montenegro, Podgorica, Montenegro
J. Mijuskovic3, N. Raicevic University of Auckland, Auckland, New Zealand
D. Krofcheck University of Canterbury, Christchurch, New Zealand
S. Bheesette, P.H. Butler, P. Lujan National Centre for Physics, Quaid-I-Azam
University, Islamabad, Pakistan
A. Ahmad, M. Ahmad, M.I.M. Awan, Q. Hassan, H.R. Hoorani, W.A. Khan, M.A.
Shah, M. Shoaib, M. Waqas AGH University of Science and Technology Faculty of
Computer Science, Electronics and Telecommunications, Krakow, Poland
V. Avati, L. Grzanka, M. Malawski National Centre for Nuclear Research,
Swierk, Poland
H. Bialkowska, M. Bluj, B. Boimska, M. Górski, M. Kazana, M. Szleper, P.
Zalewski Institute of Experimental Physics, Faculty of Physics, University of
Warsaw, Warsaw, Poland
K. Bunkowski, A. Byszuk36, K. Doroba, A. Kalinowski, M. Konecki, J.
Krolikowski, M. Olszewski, M. Walczak Laboratório de Instrumentação e Física
Experimental de Partículas, Lisboa, Portugal
M. Araujo, P. Bargassa, D. Bastos, A. Di Francesco, P. Faccioli, B. Galinhas,
M. Gallinaro, J. Hollar, N. Leonardo, T. Niknejad, J. Seixas, K. Shchelina, G.
Strong, O. Toldaiev, J. Varela Joint Institute for Nuclear Research, Dubna,
Russia
S. Afanasiev, P. Bunin, Y. Ershov, M. Gavrilenko, A. Golunov, I. Golutvin, N.
Gorbounov, I. Gorbunov, A. Kamenev, V. Karjavine, A. Lanev, A. Malakhov, V.
Matveev37,38, P. Moisenz, V. Palichik, V. Perelygin, S. Shmatov, V. Smirnov,
A. Zarubin, V. Zhiltsov Petersburg Nuclear Physics Institute, Gatchina (St.
Petersburg), Russia
L. Chtchipounov, V. Golovtcov, Y. Ivanov, V. Kim39, E. Kuznetsova40, P.
Levchenko, V. Murzin, V. Oreshkin, I. Smirnov, D. Sosnov, V. Sulimov, L.
Uvarov, A. Vorobyev Institute for Nuclear Research, Moscow, Russia
Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov,
N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin Institute for Theoretical
and Experimental Physics named by A.I. Alikhanov of NRC ‘Kurchatov Institute’,
Moscow, Russia
V. Epshteyn, V. Gavrilov, N. Lychkovskaya, A. Nikitenko41, V. Popov, I.
Pozdnyakov, G. Safronov, A. Spiridonov, A. Stepennov, M. Toms, E. Vlasov, A.
Zhokin Moscow Institute of Physics and Technology, Moscow, Russia
T. Aushev National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
M. Chadeeva42, P. Parygin, D. Philippov, E. Popova, V. Rusinov P.N. Lebedev
Physical Institute, Moscow, Russia
V. Andreev, M. Azarkin, I. Dremin, M. Kirakosyan, A. Terkulov Skobeltsyn
Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow,
Russia
A. Belyaev, E. Boos, A. Ershov, A. Gribushin, A. Kaminskiy43, O. Kodolova, V.
Korotkikh, I. Lokhtin, S. Obraztsov, S. Petrushanko, V. Savrin, A. Snigirev,
I. Vardanyan Novosibirsk State University (NSU), Novosibirsk, Russia
A. Barnyakov44, V. Blinov44, T. Dimova44, L. Kardapoltsev44, Y. Skovpen44
Institute for High Energy Physics of National Research Centre ‘Kurchatov
Institute’, Protvino, Russia
I. Azhgirey, I. Bayshev, S. Bitioukov, V. Kachanov, D. Konstantinov, P.
Mandrik, V. Petrov, R. Ryutin, S. Slabospitskii, A. Sobol, S. Troshin, N.
Tyurin, A. Uzunian, A. Volkov National Research Tomsk Polytechnic University,
Tomsk, Russia
A. Babaev, A. Iuzhakov, V. Okhotnikov Tomsk State University, Tomsk, Russia
V. Borchsh, V. Ivanchenko, E. Tcherniaev University of Belgrade: Faculty of
Physics and VINCA Institute of Nuclear Sciences, Belgrade, Serbia
P. Adzic45, P. Cirkovic, M. Dordevic, P. Milenovic, J. Milosevic, M.
Stojanovic Centro de Investigaciones Energéticas Medioambientales y
Tecnológicas (CIEMAT), Madrid, Spain
M. Aguilar-Benitez, J. Alcaraz Maestre, A. Álvarez Fernández, I. Bachiller, M.
Barrio Luna, Cristina F. Bedoya, J.A. Brochero Cifuentes, C.A. Carrillo
Montoya, M. Cepeda, M. Cerrada, N. Colino, B. De La Cruz, A. Delgado Peris,
J.P. Fernández Ramos, J. Flix, M.C. Fouz, O. Gonzalez Lopez, S. Goy Lopez,
J.M. Hernandez, M.I. Josa, D. Moran, Á. Navarro Tobar, A. Pérez-Calero
Yzquierdo, J. Puerta Pelayo, I. Redondo, L. Romero, S. Sánchez Navas, M.S.
Soares, A. Triossi, C. Willmott Universidad Autónoma de Madrid, Madrid, Spain
C. Albajar, J.F. de Trocóniz, R. Reyes-Almanza Universidad de Oviedo,
Instituto Universitario de Ciencias y Tecnologías Espaciales de Asturias
(ICTEA), Oviedo, Spain
B. Alvarez Gonzalez, J. Cuevas, C. Erice, J. Fernandez Menendez, S. Folgueras,
I. Gonzalez Caballero, E. Palencia Cortezon, C. Ramón Álvarez, V. Rodríguez
Bouza, S. Sanchez Cruz Instituto de Física de Cantabria (IFCA), CSIC-
Universidad de Cantabria, Santander, Spain
I.J. Cabrillo, A. Calderon, B. Chazin Quero, J. Duarte Campderros, M.
Fernandez, P.J. Fernández Manteca, A. García Alonso, G. Gomez, C. Martinez
Rivero, P. Martinez Ruiz del Arbol, F. Matorras, J. Piedra Gomez, C. Prieels,
F. Ricci-Tam, T. Rodrigo, A. Ruiz-Jimeno, L. Russo46, L. Scodellaro, I. Vila,
J.M. Vizan Garcia University of Colombo, Colombo, Sri Lanka
D.U.J. Sonnadara University of Ruhuna, Department of Physics, Matara, Sri
Lanka
W.G.D. Dharmaratna, N. Wickramage CERN, European Organization for Nuclear
Research, Geneva, Switzerland
T.K. Aarrestad, D. Abbaneo, B. Akgun, E. Auffray, G. Auzinger, J. Baechler, P.
Baillon, A.H. Ball, D. Barney, J. Bendavid, M. Bianco, A. Bocci, P. Bortignon,
E. Bossini, E. Brondolin, T. Camporesi, A. Caratelli, G. Cerminara, E. Chapon,
G. Cucciati, D. d’Enterria, A. Dabrowski, N. Daci, V. Daponte, A. David, O.
Davignon, A. De Roeck, M. Deile, R. Di Maria, M. Dobson, M. Dünser, N. Dupont,
A. Elliott-Peisert, N. Emriskova, F. Fallavollita47, D. Fasanella, S.
Fiorendi, G. Franzoni, J. Fulcher, W. Funk, S. Giani, D. Gigi, K. Gill, F.
Glege, L. Gouskos, M. Gruchala, M. Guilbaud, D. Gulhan, J. Hegeman, C.
Heidegger, Y. Iiyama, V. Innocente, T. James, P. Janot, O. Karacheban20, J.
Kaspar, J. Kieseler, M. Krammer1, N. Kratochwil, C. Lange, P. Lecoq, K. Long,
C. Lourenço, L. Malgeri, M. Mannelli, A. Massironi, F. Meijers, S. Mersi, E.
Meschi, F. Moortgat, M. Mulders, J. Ngadiuba, J. Niedziela, S. Nourbakhsh, S.
Orfanelli, L. Orsini, F. Pantaleo17, L. Pape, E. Perez, M. Peruzzi, A.
Petrilli, G. Petrucciani, A. Pfeiffer, M. Pierini, F.M. Pitters, D. Rabady, A.
Racz, M. Rieger, M. Rovere, H. Sakulin, J. Salfeld-Nebgen, S. Scarfi, C.
Schäfer, C. Schwick, M. Selvaggi, A. Sharma, P. Silva, W. Snoeys, P.
Sphicas48, J. Steggemann, S. Summers, V.R. Tavolaro, D. Treille, A. Tsirou,
G.P. Van Onsem, A. Vartak, M. Verzetti, K.A. Wozniak, W.D. Zeuner Paul
Scherrer Institut, Villigen, Switzerland
L. Caminada49, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H.C.
Kaestli, D. Kotlinski, U. Langenegger, T. Rohe ETH Zurich - Institute for
Particle Physics and Astrophysics (IPA), Zurich, Switzerland
M. Backhaus, P. Berger, A. Calandri, N. Chernyavskaya, G. Dissertori, M.
Dittmar, M. Donegà, C. Dorfer, T.A. Gómez Espinosa, C. Grab, D. Hits, W.
Lustermann, R.A. Manzoni, M.T. Meinhard, F. Micheli, P. Musella, F. Nessi-
Tedaldi, F. Pauss, V. Perovic, G. Perrin, L. Perrozzi, S. Pigazzini, M.G.
Ratti, M. Reichmann, C. Reissel, T. Reitenspiess, B. Ristic, D. Ruini, D.A.
Sanz Becerra, M. Schönenberger, L. Shchutska, M.L. Vesterbacka Olsson, R.
Wallny, D.H. Zhu Universität Zürich, Zurich, Switzerland
C. Amsler50, C. Botta, D. Brzhechko, M.F. Canelli, A. De Cosa, R. Del Burgo,
B. Kilminster, S. Leontsinis, V.M. Mikuni, I. Neutelings, G. Rauco, P.
Robmann, K. Schweiger, Y. Takahashi, S. Wertz National Central University,
Chung-Li, Taiwan
C.M. Kuo, W. Lin, A. Roy, T. Sarkar29, S.S. Yu National Taiwan University
(NTU), Taipei, Taiwan
P. Chang, Y. Chao, K.F. Chen, P.H. Chen, W.-S. Hou, Y.y. Li, R.-S. Lu, E.
Paganis, A. Psallidas, A. Steen Chulalongkorn University, Faculty of Science,
Department of Physics, Bangkok, Thailand
B. Asavapibhop, C. Asawatangtrakuldee, N. Srimanobhas, N. Suwonjandee Çukurova
University, Physics Department, Science and Art Faculty, Adana, Turkey
A. Bat, F. Boran, A. Celik51, S. Damarseckin52, Z.S. Demiroglu, F. Dolek, C.
Dozen53, I. Dumanoglu54, G. Gokbulut, Emine Gurpinar Guler55, Y. Guler, I.
Hos56, C. Isik, E.E. Kangal57, O. Kara, A. Kayis Topaksu, U. Kiminsu, G.
Onengut, K. Ozdemir58, A.E. Simsek, U.G. Tok, S. Turkcapar, I.S. Zorbakir, C.
Zorbilmez Middle East Technical University, Physics Department, Ankara, Turkey
B. Isildak59, G. Karapinar60, M. Yalvac61 Bogazici University, Istanbul,
Turkey
I.O. Atakisi, E. Gülmez, M. Kaya62, O. Kaya63, Ö. Özçelik, S. Tekten64, E.A.
Yetkin65 Istanbul Technical University, Istanbul, Turkey
A. Cakir, K. Cankocak54, Y. Komurcu, S. Sen66 Istanbul University, Istanbul,
Turkey
S. Cerci67, B. Kaynak, S. Ozkorucuklu, D. Sunar Cerci67 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
E. Bhal, S. Bologna, J.J. Brooke, D. Burns68, E. Clement, D. Cussans, H.
Flacher, J. Goldstein, G.P. Heath, H.F. Heath, L. Kreczko, B. Krikler, S.
Paramesvaran, T. Sakuma, S. Seif El Nasr-Storey, V.J. Smith, J. Taylor, A.
Titterton Rutherford Appleton Laboratory, Didcot, United Kingdom
K.W. Bell, A. Belyaev69, C. Brew, R.M. Brown, D.J.A. Cockerill, J.A. Coughlan,
K. Harder, S. Harper, J. Linacre, K. Manolopoulos, D.M. Newbold, E. Olaiya, D.
Petyt, T. Reis, T. Schuh, C.H. Shepherd-Themistocleous, A. Thea, I.R. Tomalin,
T. Williams Imperial College, London, United Kingdom
R. Bainbridge, P. Bloch, S. Bonomally, J. Borg, S. Breeze, O. Buchmuller, A.
Bundock, Gurpreet Singh CHAHAL70, D. Colling, P. Dauncey, G. Davies, M. Della
Negra, P. Everaerts, G. Hall, G. Iles, M. Komm, J. Langford, L. Lyons, A.-M.
Magnan, S. Malik, A. Martelli, V. Milosevic, A. Morton, J. Nash71, V.
Palladino, M. Pesaresi, D.M. Raymond, A. Richards, A. Rose, E. Scott, C. Seez,
A. Shtipliyski, M. Stoye, T. Strebler, A. Tapper, K. Uchida, T. Virdee17, N.
Wardle, S.N. Webb, D. Winterbottom, A.G. Zecchinelli, S.C. Zenz Brunel
University, Uxbridge, United Kingdom
J.E. Cole, P.R. Hobson, A. Khan, P. Kyberd, C.K. Mackay, I.D. Reid, L.
Teodorescu, S. Zahid Baylor University, Waco, USA
A. Brinkerhoff, K. Call, B. Caraway, J. Dittmann, K. Hatakeyama, C. Madrid, B.
McMaster, N. Pastika, C. Smith Catholic University of America, Washington, DC,
USA
R. Bartek, A. Dominguez, R. Uniyal, A.M. Vargas Hernandez The University of
Alabama, Tuscaloosa, USA
A. Buccilli, S.I. Cooper, S.V. Gleyzer, C. Henderson, P. Rumerio, C. West
Boston University, Boston, USA
A. Albert, D. Arcaro, Z. Demiragli, D. Gastler, C. Richardson, J. Rohlf, D.
Sperka, D. Spitzbart, I. Suarez, L. Sulak, D. Zou Brown University,
Providence, USA
G. Benelli, B. Burkle, X. Coubez18, D. Cutts, Y.t. Duh, M. Hadley, U. Heintz,
J.M. Hogan72, K.H.M. Kwok, E. Laird, G. Landsberg, K.T. Lau, J. Lee, M.
Narain, S. Sagir73, R. Syarif, E. Usai, W.Y. Wong, D. Yu, W. Zhang University
of California, Davis, Davis, USA
R. Band, C. Brainerd, R. Breedon, M. Calderon De La Barca Sanchez, M. Chertok,
J. Conway, R. Conway, P.T. Cox, R. Erbacher, C. Flores, G. Funk, F. Jensen, W.
Ko${}^{\textrm{\textdagger}}$, O. Kukral, R. Lander, M. Mulhearn, D. Pellett,
J. Pilot, M. Shi, D. Taylor, K. Tos, M. Tripathi, Z. Wang, F. Zhang University
of California, Los Angeles, USA
M. Bachtis, C. Bravo, R. Cousins, A. Dasgupta, A. Florent, J. Hauser, M.
Ignatenko, N. Mccoll, W.A. Nash, S. Regnard, D. Saltzberg, C. Schnaible, B.
Stone, V. Valuev University of California, Riverside, Riverside, USA
K. Burt, Y. Chen, R. Clare, J.W. Gary, S.M.A. Ghiasi Shirazi, G. Hanson, G.
Karapostoli, O.R. Long, N. Manganelli, M. Olmedo Negrete, M.I. Paneva, W. Si,
S. Wimpenny, B.R. Yates, Y. Zhang University of California, San Diego, La
Jolla, USA
J.G. Branson, P. Chang, S. Cittolin, S. Cooperstein, N. Deelen, M. Derdzinski,
J. Duarte, R. Gerosa, D. Gilbert, B. Hashemi, D. Klein, V. Krutelyov, J.
Letts, M. Masciovecchio, S. May, S. Padhi, M. Pieri, V. Sharma, M. Tadel, F.
Würthwein, A. Yagil, G. Zevi Della Porta University of California, Santa
Barbara - Department of Physics, Santa Barbara, USA
N. Amin, R. Bhandari, C. Campagnari, M. Citron, V. Dutta, J. Incandela, B.
Marsh, H. Mei, A. Ovcharova, H. Qu, J. Richman, U. Sarica, D. Stuart, S. Wang
California Institute of Technology, Pasadena, USA
D. Anderson, A. Bornheim, O. Cerri, I. Dutta, J.M. Lawhorn, N. Lu, J. Mao,
H.B. Newman, T.Q. Nguyen, J. Pata, M. Spiropulu, J.R. Vlimant, S. Xie, Z.
Zhang, R.Y. Zhu Carnegie Mellon University, Pittsburgh, USA
J. Alison, 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, E. MacDonald, T. Mulholland, R. Patel, A. Perloff, K.
Stenson, K.A. Ulmer, S.R. Wagner Cornell University, Ithaca, USA
J. Alexander, Y. Cheng, J. Chu, A. Datta, A. Frankenthal, K. Mcdermott, J.R.
Patterson, D. Quach, A. Ryd, S.M. Tan, Z. Tao, J. Thom, P. Wittich, M. Zientek
Fermi National Accelerator Laboratory, Batavia, USA
S. Abdullin, M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, A. Apyan, S.
Banerjee, L.A.T. Bauerdick, A. Beretvas, D. Berry, J. Berryhill, P.C. Bhat, K.
Burkett, J.N. Butler, A. Canepa, G.B. Cerati, H.W.K. Cheung, F. Chlebana, M.
Cremonesi, V.D. Elvira, J. Freeman, Z. Gecse, E. Gottschalk, L. Gray, D.
Green, S. Grünendahl, O. Gutsche, J. Hanlon, R.M. Harris, S. Hasegawa, R.
Heller, J. Hirschauer, B. Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, T.
Klijnsma, B. Klima, M.J. Kortelainen, B. Kreis, S. Lammel, J. Lewis, D.
Lincoln, R. Lipton, M. Liu, T. Liu, J. Lykken, K. Maeshima, J.M. Marraffino,
D. Mason, P. McBride, P. Merkel, S. Mrenna, S. Nahn, V. O’Dell, V.
Papadimitriou, K. Pedro, C. Pena74, F. Ravera, A. Reinsvold Hall, L. Ristori,
B. Schneider, E. Sexton-Kennedy, N. Smith, A. Soha, W.J. Spalding, L. Spiegel,
S. Stoynev, J. Strait, L. Taylor, S. Tkaczyk, N.V. Tran, L. Uplegger, E.W.
Vaandering, R. Vidal, M. Wang, H.A. Weber, A. Woodard University of Florida,
Gainesville, USA
D. Acosta, P. Avery, D. Bourilkov, L. Cadamuro, V. Cherepanov, F. Errico, R.D.
Field, D. Guerrero, B.M. Joshi, M. Kim, J. Konigsberg, A. Korytov, K.H. Lo, K.
Matchev, N. Menendez, G. Mitselmakher, D. Rosenzweig, K. Shi, J. Wang, S.
Wang, X. Zuo Florida International University, Miami, USA
Y.R. Joshi Florida State University, Tallahassee, USA
T. Adams, A. Askew, S. Hagopian, V. Hagopian, K.F. Johnson, R. Khurana, T.
Kolberg, G. Martinez, T. Perry, H. Prosper, C. Schiber, R. Yohay, J. Zhang
Florida Institute of Technology, Melbourne, USA
M.M. Baarmand, M. Hohlmann, D. Noonan, M. Rahmani, M. Saunders, F. Yumiceva
University of Illinois at Chicago (UIC), Chicago, USA
M.R. Adams, L. Apanasevich, R.R. Betts, R. Cavanaugh, X. Chen, S. Dittmer, O.
Evdokimov, C.E. Gerber, D.A. Hangal, D.J. Hofman, V. Kumar, C. Mills, G. Oh,
T. Roy, M.B. Tonjes, N. Varelas, J. Viinikainen, H. Wang, X. Wang, Z. Wu The
University of Iowa, Iowa City, USA
M. Alhusseini, B. Bilki55, K. Dilsiz75, S. Durgut, R.P. Gandrajula, M.
Haytmyradov, V. Khristenko, O.K. Köseyan, J.-P. Merlo, A. Mestvirishvili76, A.
Moeller, J. Nachtman, H. Ogul77, Y. Onel, F. Ozok78, A. Penzo, C. Snyder, E.
Tiras, J. Wetzel, K. Yi79 Johns Hopkins University, Baltimore, USA
B. Blumenfeld, A. Cocoros, N. Eminizer, A.V. Gritsan, W.T. Hung, S. Kyriacou,
P. Maksimovic, C. Mantilla, J. Roskes, M. Swartz, T.Á. Vámi The University of
Kansas, Lawrence, USA
C. Baldenegro Barrera, P. Baringer, A. Bean, S. Boren, A. Bylinkin, T.
Isidori, S. Khalil, J. King, G. Krintiras, A. Kropivnitskaya, C. Lindsey, D.
Majumder, W. Mcbrayer, N. Minafra, M. Murray, C. Rogan, C. Royon, S. Sanders,
E. Schmitz, J.D. Tapia Takaki, Q. Wang, J. Williams, G. Wilson 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, N.J. Hadley, S. Jabeen,
G.Y. Jeng, R.G. Kellogg, A.C. Mignerey, S. Nabili, M. Seidel, A. Skuja, S.C.
Tonwar, L. Wang, K. Wong Massachusetts Institute of Technology, Cambridge, USA
D. Abercrombie, B. Allen, R. Bi, S. Brandt, W. Busza, I.A. Cali, M. D’Alfonso,
G. Gomez Ceballos, M. Goncharov, P. Harris, D. Hsu, M. Hu, M. Klute, D.
Kovalskyi, Y.-J. Lee, P.D. Luckey, B. Maier, A.C. Marini, C. Mcginn, C.
Mironov, S. Narayanan, X. Niu, C. Paus, D. Rankin, C. Roland, G. Roland, Z.
Shi, G.S.F. Stephans, K. Sumorok, K. Tatar, D. Velicanu, J. Wang, T.W. Wang,
B. Wyslouch University of Minnesota, Minneapolis, USA
R.M. Chatterjee, A. Evans, S. Guts${}^{\textrm{\textdagger}}$, P. Hansen, J.
Hiltbrand, Sh. Jain, Y. Kubota, Z. Lesko, J. Mans, M. Revering, R. Rusack, R.
Saradhy, N. Schroeder, N. Strobbe, M.A. Wadud University of Mississippi,
Oxford, USA
J.G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA
K. Bloom, S. Chauhan, D.R. Claes, C. Fangmeier, L. Finco, F. Golf, R.
Kamalieddin, I. Kravchenko, J.E. Siado, G.R. Snow${}^{\textrm{\textdagger}}$,
B. Stieger, W. Tabb State University of New York at Buffalo, Buffalo, USA
G. Agarwal, C. Harrington, I. Iashvili, A. Kharchilava, C. McLean, D. Nguyen,
A. Parker, J. Pekkanen, S. Rappoccio, B. Roozbahani Northeastern University,
Boston, USA
G. Alverson, E. Barberis, C. Freer, Y. Haddad, A. Hortiangtham, G. Madigan, B.
Marzocchi, D.M. Morse, V. Nguyen, T. Orimoto, L. Skinnari, A. Tishelman-
Charny, T. Wamorkar, B. Wang, A. Wisecarver, D. Wood Northwestern University,
Evanston, USA
S. Bhattacharya, J. Bueghly, G. Fedi, A. Gilbert, T. Gunter, K.A. Hahn, N.
Odell, M.H. Schmitt, K. Sung, M. Velasco University of Notre Dame, Notre Dame,
USA
R. Bucci, N. Dev, R. Goldouzian, M. Hildreth, K. Hurtado Anampa, C. Jessop,
D.J. Karmgard, K. Lannon, W. Li, N. Loukas, N. Marinelli, I. Mcalister, F.
Meng, Y. Musienko37, R. Ruchti, P. Siddireddy, G. Smith, S. Taroni, M. Wayne,
A. Wightman, M. Wolf The Ohio State University, Columbus, USA
J. Alimena, B. Bylsma, B. Cardwell, L.S. Durkin, B. Francis, C. Hill, W. Ji,
A. Lefeld, T.Y. Ling, B.L. Winer Princeton University, Princeton, USA
G. Dezoort, P. Elmer, J. Hardenbrook, N. Haubrich, S. Higginbotham, A.
Kalogeropoulos, S. Kwan, D. Lange, M.T. Lucchini, J. Luo, D. Marlow, K. Mei,
I. Ojalvo, J. Olsen, C. Palmer, P. Piroué, D. Stickland, C. Tully University
of Puerto Rico, Mayaguez, USA
S. Malik, S. Norberg Purdue University, West Lafayette, USA
A. Barker, V.E. Barnes, R. Chawla, S. Das, L. Gutay, M. Jones, A.W. Jung, B.
Mahakud, D.H. Miller, G. Negro, N. Neumeister, C.C. Peng, S. Piperov, H. Qiu,
J.F. Schulte, N. Trevisani, F. Wang, R. Xiao, W. Xie Purdue University
Northwest, Hammond, USA
T. Cheng, J. Dolen, N. Parashar Rice University, Houston, USA
A. Baty, U. Behrens, S. Dildick, K.M. Ecklund, S. Freed, F.J.M. Geurts, M.
Kilpatrick, Arun Kumar, W. Li, B.P. Padley, R. Redjimi, J. Roberts, J. Rorie,
W. Shi, A.G. Stahl Leiton, Z. Tu, A. Zhang University of Rochester, Rochester,
USA
A. Bodek, P. de Barbaro, R. Demina, J.L. Dulemba, C. Fallon, T. Ferbel, M.
Galanti, A. Garcia-Bellido, O. Hindrichs, A. Khukhunaishvili, E. Ranken, R.
Taus Rutgers, The State University of New Jersey, Piscataway, USA
B. Chiarito, J.P. Chou, A. Gandrakota, Y. Gershtein, E. Halkiadakis, A. Hart,
M. Heindl, E. Hughes, S. Kaplan, I. Laflotte, A. Lath, R. Montalvo, K. Nash,
M. Osherson, S. Salur, S. Schnetzer, S. Somalwar, R. Stone, S. Thomas
University of Tennessee, Knoxville, USA
H. Acharya, A.G. Delannoy, S. Spanier Texas A&M University, College Station,
USA
O. Bouhali80, M. Dalchenko, M. De Mattia, A. Delgado, R. Eusebi, J. Gilmore,
T. Huang, T. Kamon81, H. Kim, S. Luo, S. Malhotra, D. Marley, R. Mueller, D.
Overton, L. Perniè, D. Rathjens, A. Safonov Texas Tech University, Lubbock,
USA
N. Akchurin, J. Damgov, F. De Guio, V. Hegde, S. Kunori, K. Lamichhane, S.W.
Lee, T. Mengke, S. Muthumuni, T. Peltola, S. Undleeb, I. Volobouev, Z. Wang,
A. Whitbeck Vanderbilt University, Nashville, USA
S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, K.
Padeken, F. Romeo, P. Sheldon, S. Tuo, J. Velkovska, M. Verweij University of
Virginia, Charlottesville, USA
M.W. Arenton, P. Barria, B. Cox, G. Cummings, J. Hakala, R. Hirosky, M. Joyce,
A. Ledovskoy, C. Neu, B. Tannenwald, Y. Wang, E. Wolfe, F. Xia Wayne State
University, Detroit, USA
R. Harr, P.E. Karchin, N. Poudyal, J. Sturdy, P. Thapa University of Wisconsin
- Madison, Madison, WI, USA
K. Black, T. Bose, J. Buchanan, C. Caillol, D. Carlsmith, S. Dasu, I. De
Bruyn, L. Dodd, C. Galloni, H. He, M. Herndon, A. Hervé, U. Hussain, A.
Lanaro, A. Loeliger, R. Loveless, J. Madhusudanan Sreekala, A. Mallampalli, D.
Pinna, T. Ruggles, A. Savin, V. Sharma, W.H. Smith, D. Teague, S. Trembath-
reichert †: Deceased
1: Also at Vienna University of Technology, Vienna, Austria
2: Also at Université Libre de Bruxelles, Bruxelles, Belgium
3: Also at IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
4: Also at Universidade Estadual de Campinas, Campinas, Brazil
5: Also at Federal University of Rio Grande do Sul, Porto Alegre, Brazil
6: Also at UFMS, Nova Andradina, Brazil
7: Also at Universidade Federal de Pelotas, Pelotas, Brazil
8: Also at University of Chinese Academy of Sciences, Beijing, China
9: Also at Institute for Theoretical and Experimental Physics named by A.I.
Alikhanov of NRC ‘Kurchatov Institute’, Moscow, Russia
10: Also at Joint Institute for Nuclear Research, Dubna, Russia
11: Also at Fayoum University, El-Fayoum, Egypt
12: Now at British University in Egypt, Cairo, Egypt
13: Also at Purdue University, West Lafayette, USA
14: Also at Université de Haute Alsace, Mulhouse, France
15: Also at Ilia State University, Tbilisi, Georgia
16: Also at Erzincan Binali Yildirim University, Erzincan, Turkey
17: Also at CERN, European Organization for Nuclear Research, Geneva,
Switzerland
18: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
19: Also at University of Hamburg, Hamburg, Germany
20: Also at Brandenburg University of Technology, Cottbus, Germany
21: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary,
Debrecen, Hungary
22: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
23: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary, Budapest, Hungary
24: Also at IIT Bhubaneswar, Bhubaneswar, India, Bhubaneswar, India
25: Also at Institute of Physics, Bhubaneswar, India
26: Also at G.H.G. Khalsa College, Punjab, India
27: Also at Shoolini University, Solan, India
28: Also at University of Hyderabad, Hyderabad, India
29: Also at University of Visva-Bharati, Santiniketan, India
30: Now at INFN Sezione di Bari a, Università di Bari b, Politecnico di Bari
c, Bari, Italy
31: Also at Italian National Agency for New Technologies, Energy and
Sustainable Economic Development, Bologna, Italy
32: Also at Centro Siciliano di Fisica Nucleare e di Struttura Della Materia,
Catania, Italy
33: Also at Riga Technical University, Riga, Latvia, Riga, Latvia
34: Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia
35: Also at Consejo Nacional de Ciencia y Tecnología, Mexico City, Mexico
36: Also at Warsaw University of Technology, Institute of Electronic Systems,
Warsaw, Poland
37: Also at Institute for Nuclear Research, Moscow, Russia
38: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
39: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
40: Also at University of Florida, Gainesville, USA
41: Also at Imperial College, London, United Kingdom
42: Also at P.N. Lebedev Physical Institute, Moscow, Russia
43: Also at INFN Sezione di Padova a, Università di Padova b, Padova, Italy,
Università di Trento c, Trento, Italy, Padova, Italy
44: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
45: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
46: Also at Università degli Studi di Siena, Siena, Italy, Siena, Italy
47: Also at INFN Sezione di Pavia a, Università di Pavia b, Pavia, Italy,
Pavia, Italy
48: Also at National and Kapodistrian University of Athens, Athens, Greece
49: Also at Universität Zürich, Zurich, Switzerland
50: Also at Stefan Meyer Institute for Subatomic Physics, Vienna, Austria,
Vienna, Austria
51: Also at Burdur Mehmet Akif Ersoy University, BURDUR, Turkey
52: Also at Şırnak University, Sirnak, Turkey
53: Also at Department of Physics, Tsinghua University, Beijing, China,
Beijing, China
54: Also at Near East University, Research Center of Experimental Health
Science, Nicosia, Turkey
55: Also at Beykent University, Istanbul, Turkey, Istanbul, Turkey
56: Also at Istanbul Aydin University, Application and Research Center for
Advanced Studies (App. & Res. Cent. for Advanced Studies), Istanbul, Turkey
57: Also at Mersin University, Mersin, Turkey
58: Also at Piri Reis University, Istanbul, Turkey
59: Also at Ozyegin University, Istanbul, Turkey
60: Also at Izmir Institute of Technology, Izmir, Turkey
61: Also at Bozok Universitetesi Rektörlügü, Yozgat, Turkey, Yozgat, Turkey
62: Also at Marmara University, Istanbul, Turkey
63: Also at Milli Savunma University, Istanbul, Turkey
64: Also at Kafkas University, Kars, Turkey
65: Also at Istanbul Bilgi University, Istanbul, Turkey
66: Also at Hacettepe University, Ankara, Turkey
67: Also at Adiyaman University, Adiyaman, Turkey
68: Also at Vrije Universiteit Brussel, Brussel, Belgium
69: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
70: Also at IPPP Durham University, Durham, United Kingdom
71: Also at Monash University, Faculty of Science, Clayton, Australia
72: Also at Bethel University, St. Paul, Minneapolis, USA, St. Paul, USA
73: Also at Karamanoğlu Mehmetbey University, Karaman, Turkey
74: Also at California Institute of Technology, Pasadena, USA
75: Also at Bingol University, Bingol, Turkey
76: Also at Georgian Technical University, Tbilisi, Georgia
77: Also at Sinop University, Sinop, Turkey
78: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey
79: Also at Nanjing Normal University Department of Physics, Nanjing, China
80: Also at Texas A&M University at Qatar, Doha, Qatar
81: Also at Kyungpook National University, Daegu, Korea, Daegu, Korea