2021 160 2 August

Inclusive $\text{J}/\psi$ production at midrapidity in pp collisions at
$\sqrt{s}~{}=~{}13$ TeV

ALICE collaboration††thanks: See Appendix A for the list of collaboration
members ALICE collaboration

We report on the inclusive $\text{J}/\psi$ production cross section measured
at the CERN Large Hadron Collider in proton–proton collisions at a centre-of-
mass energy $\sqrt{s}~{}=~{}13$ TeV. The $\text{J}/\psi$ mesons are
reconstructed in the $\text{e}^{+}\text{e}^{-}$ decay channel and the
measurements are performed at midrapidity ($|y|<0.9$) in the transverse-
momentum interval $0<p_{\rm T}<40$ GeV/$c$, using a minimum-bias data sample
corresponding to an integrated luminosity
$L_{\text{int}}=32.2~{}\text{nb}^{-1}$ and an Electromagnetic Calorimeter
triggered data sample with $L_{\text{int}}=8.3~{}\mathrm{pb}^{-1}$. The
$p_{\rm T}$-integrated $\text{J}/\psi$ production cross section at
midrapidity, computed using the minimum-bias data sample, is
$\text{d}\sigma/\text{d}y|_{y=0}=8.97\pm 0.24~{}(\text{stat})\pm
0.48~{}(\text{syst})\pm 0.15~{}(\text{lumi})~{}\mu\text{b}$. An approximate
logarithmic dependence with the collision energy is suggested by these results
and available world data, in agreement with model predictions. The integrated
and $p_{\rm T}$-differential measurements are compared with measurements in pp
collisions at lower energies and with several recent phenomenological
calculations based on the non-relativistic QCD and Color Evaporation models.

##  1 Introduction

Quarkonium production in hadronic interactions is an excellent case of study
for understanding hadronization in quantum chromodynamics (QCD), the theory of
strong interactions [1]. In particular, the production of the $\text{J}/\psi$
meson, a bound state of a charm and an anti-charm quark and the lightest
vector charmonium state, is the subject of many theoretical calculations. The
cornerstone of all the theoretical approaches is the factorization theorem,
according to which the $\text{J}/\psi$ production cross section can be
factorized into a short distance part describing the
$\text{c}\overline{\text{c}}$ production and a long distance part describing
the subsequent formation of the bound state. In this way, the
$\text{c}\overline{\text{c}}$ pair production cross section can be computed
perturbatively. The widely used Non-Relativistic QCD (NRQCD) approach [2]
describes the transition probabilities of the pre-resonant
$\text{c}\overline{\text{c}}$ pairs to bound states with a set of long-
distance matrix elements (LDME) fitted to experimental data, assumed to be
universal. Next-to-leading order (NLO) calculations involving collinear parton
densities are able to describe production yields for transverse momentum
($p_{\rm T}$) larger than the mass of the bound state [3, 4], but have
difficulties describing the measured polarization [5, 6]. Calculations
employing the $k_{\rm T}$-factorization approach [7] can reach lower $p_{\rm
T}$ but have similar difficulties when compared to data [8]. The low-$p_{\rm
T}$ range of quarkonium production is modelled also within the Color Glass
Condensate effective theory coupled to leading order NRQCD calculations [9],
which involves a saturation of the small Bjorken-$x$ gluon densities that
dampens the heavy-quark pair production yields. An alternative to the
universal LDME approach to hadronization used in the NRQCD framework is
provided by the Color Evaporation Model (CEM) [10, 11] and its more recent
implementation using the $k_{\rm T}$-factorization approach, the Improved CEM
(ICEM) [12]. In the ICEM, the transition probability to a given bound state is
proportional to the $\text{c}\overline{\text{c}}$ pair production cross
section integrated over an invariant-mass range spanning between the mass of
the bound state and twice the mass of the lightest charmed meson. Finally, in
the Color Singlet Model (CSM) [13, 14, 15], the pre-resonant
$\text{c}\overline{\text{c}}$ pair is produced directly in the color-singlet
state with the same quantum numbers as the bound state. Calculations within
this model at NLO precision are known to strongly underpredict the measured
production cross sections [16]. In this context, a $p_{\rm T}$-differential
measurement of $\text{J}/\psi$ production cross section covering a wide
$p_{\rm T}$ range, starting from $p_{\rm T}$ =0 and up to high-$p_{\rm T}$,
can discriminate between the different models of quarkonium production.

In this paper, we present the integrated, and the $p_{\rm T}$ and rapidity
($y$) differential production cross sections of inclusive $\text{J}/\psi$
production at midrapidity ($|y|<0.9$) in proton–proton (pp) collisions at the
center-of-mass energy $\sqrt{s}~{}=~{}13$ TeV. The inclusive $\text{J}/\psi$
yields include contributions from directly produced $\text{J}/\psi$, feed-down
from prompt decays of higher-mass charmonium states, and non-prompt
$\text{J}/\psi$ from the decays of beauty hadrons. The $p_{\rm
T}$-differential production cross section of inclusive $\text{J}/\psi$ is
measured in the $0<p_{\rm T}<15$ GeV/$c$ interval using a minimum-bias
triggered data sample and in the $15<p_{\rm T}<40$ GeV/$c$ interval using an
Electromagnetic Calorimeter triggered data sample. These results complement
existing measurements at midrapidity at $\sqrt{s}~{}=~{}13$ TeV performed by
the CMS Collaboration [17], which report the prompt $\text{J}/\psi$ production
cross section for $p_{\rm T}$ $>20$ GeV/$c$. Previous measurements of the
$\text{J}/\psi$ production cross section in pp collisions performed by the
ALICE Collaboration at midrapidity at lower energies were published in Refs.
[18, 19, 20]. The inclusive $\text{J}/\psi$ production cross section in pp
collisions at $\sqrt{s}~{}=~{}13$ TeV was published by the ALICE Collaboration
at forward rapidity in Ref. [21] and the prompt and non-prompt production
cross sections were reported by the LHCb Collaboration in Ref. [22].

In the next sections, the ALICE detector and the data sample are described in
Section 2, and the data analysis and the determination of the systematic
uncertainties are described in Section 3 and Section 4, respectively. The
results are presented and discussed together with recent model calculations in
Section 5 and conclusions are drawn in Section 6.

##  2 The ALICE detector, data set and event selection

A detailed description of the ALICE detector and its performance is provided
in Refs. [23, 24]. Here we mention only the detector systems used for the
reconstruction of the $\text{J}/\psi$ mesons decaying in the
$\text{e}^{+}\text{e}^{-}$ channel at midrapidity. Unless otherwise specified,
the term electrons will be used throughout the text to refer to both electrons
and positrons.

The reconstruction of charged-particle tracks is performed using the Inner
Tracking System (ITS) [25] and the Time Projection Chamber (TPC) [26], which
are placed inside a solenoidal magnet providing a uniform magnetic field of
$B=0.5~{}\text{T}$ oriented along the beam direction. The ITS is a silicon
detector consisting of six cylindrical layers surrounding the beam pipe at
radii between 3.9 and $43.0~{}\text{cm}$. The two innermost layers consist of
silicon pixel detectors (SPD), followed by two layers of silicon drift (SDD)
and two layers of silicon strip (SSD) detectors. The TPC is a cylindrical gas
drift chamber which extends radially between 85 and $250~{}\text{cm}$ and
longitudinally over $250~{}\text{cm}$ on each side of the nominal interaction
point. Both TPC and ITS have full coverage in azimuth and provide tracking in
the pseudorapidity range $|\eta|<0.9$. Additionally, the measurement of the
specific energy loss ($\textrm{d}E/\textrm{d}x$) in the TPC active gas volume
is used for electron identification. The Electromagnetic Calorimeter (EMCal)
and the Di-jet Calorimeter (DCal) [27, 28, 29] are employed for triggering and
electron identification. The EMCal/DCal is a Shashlik-type lead-scintillator
sampling calorimeter located at a radius of 4.5 m from the beam vacuum tube.
The EMCal detector covers a pseudorapidity range of $|\eta|<0.7$ over an
azimuthal angle of $80^{\circ}<\varphi<187^{\circ}$, and the DCal covers
$0.22<|\eta|<0.7$ for $260^{\circ}<\varphi<320^{\circ}$ and $|\eta|<0.7$ for
$320^{\circ}<\varphi<327^{\circ}$. The EMCal and DCal have identical
granularity and intrinsic energy resolution, and they form a two-arm
electromagnetic calorimeter, which in this paper will be referred to jointly
as EMCal.

In addition to these central barrel detectors, the V0 detectors, composed of
two scintillator arrays [30] placed along the beam line on either side of the
interaction point and covering the pseudorapidity intervals $-3.7<\eta<-1.7$
and $2.8<\eta<5.1$, respectively, are used for event triggering. Together with
the SPD detector, the V0 is also used to reject background from beam-gas
collisions and pileup events.

The measurement of the $p_{\rm T}$-integrated and $p_{\rm T}$-differential
production cross sections up to $p_{\rm T}=15$ GeV/$c$, the upper limit being
determined by the available integrated luminosity, utilizes the minimum-bias
(MB) trigger, defined as the coincidence of signals in both V0 scintillator
arrays. For the $p_{\rm T}$ interval from 15 up to 40 GeV/$c$, the EMCal
trigger is employed to select events with high-$p_{\rm T}$ electrons. The
lower $p_{\rm T}$ limit is chosen such that the trigger efficiency does not
vary with $p_{\rm T}$ above this value, thus avoiding systematic uncertainties
related to trigger threshold effects. The EMCal trigger is an online trigger
which includes a Level 0 (L0) and a Level 1 (L1) component [27]. The
calorimeter is segmented into towers and Trigger Region Units (TRUs), the
latter being composed of 384 towers each [27]. The L0 trigger is based on the
analog charge sum of $4\times 4$ groups of adjacent towers evaluated within
each TRU, in coincidence with the MB trigger. The L1 trigger decision requires
the L0 trigger and, in addition, scans for $4\times 4$ groups of adjacent
towers across the entire EMCal surface. The EMCal-triggered analysis presented
in this paper uses the L1 trigger, and requires that at least one of the
charge sums of the $4\times 4$ adjacent towers is above 9 GeV.

This analysis includes all the data recorded by the ALICE Collaboration during
the LHC Run 2 data-taking campaigns of 2016, 2017 and 2018 for pp collisions
at $\sqrt{s}~{}=~{}13$ TeV. The maximum interaction rate for the dataset was
$260~{}\text{kHz}$, with a maximum pileup probability in the same bunch
crossing of 0.5$\times$10-3. The events selected for analysis were required to
have a reconstructed vertex within the interval
$|z_{\text{vtx}}|<10~{}\text{cm}$ to ensure a uniform detector acceptance.
Beam-gas events and pileup collisions occurring within the readout time of the
SPD were rejected offline using timing selections based on the V0 detector
information. Pileup collisions occurring within the same LHC bunch crossing
were rejected using offline algorithms which identify multiple vertices [24].
The remaining fraction of pileup events surviving the selections is negligible
for both the MB and EMCal data samples.

The analyzed MB sample, satisfying all the quality selections, consists of
about $2\times$109 events, corresponding to an integrated luminosity
$L_{\text{int}}=32.2~{}\text{nb}^{-1}\pm 1.6\%~{}(\text{syst})$, and the
EMCal-triggered sample consists of approximately $9\times$107 events which
corresponds to an integrated luminosity
$L_{\text{int}}=8.3~{}\mathrm{pb}^{-1}\pm 2.0\%~{}(\text{syst})$. The
integrated luminosities are obtained based on the MB trigger cross section
($\sigma_{\mathrm{MB}}$), measured in a van der Meer scan [31], separately for
each year, as described in Ref. [32]. For each of the used triggers, MB and
EMCal, the integrated luminosity is obtained as

$L_{\mathrm{int}}=\frac{N_{\mathrm{MB}}}{\sigma_{\mathrm{MB}}}\times\frac{ds_{\mathrm{trig}}}{ds_{\mathrm{MB}}}\times\frac{LT_{\mathrm{trig}}}{LT_{\mathrm{MB}}}$
(1)

where $N_{\mathrm{MB}}$ is the number of MB-triggered events in the triggered
sample, $ds_{\mathrm{trig}}$ is the downscaling factor applied to the
considered trigger by the ALICE trigger processor and $LT_{\mathrm{trig}}$ is
the trigger live time, i.e. the fraction of time where the detector cluster
111A detector cluster is a set of ALICE detectors readout with the same set of
triggers. All triggers assigned to a given cluster share the same live-time,
determined by the slowest detector in the cluster. assigned to the trigger was
available for readout.

##  3 $\text{J}/\psi$ reconstruction

In this work we study the integrated, and the rapidity- and $p_{\rm
T}$-differential inclusive $\text{J}/\psi$ production at midrapidity
($|y|<0.9$) reconstructing the $\text{J}/\psi$ from the
$\text{e}^{+}\text{e}^{-}$ decay channel. The MB sample analysis follows
closely the one performed in pp collisions at $\sqrt{s}~{}=~{}5.02$ TeV [20].

###  3.1 Track selection

Electron-track candidates are reconstructed employing the ITS and TPC. They
are required to be within the acceptance of the central barrel ($|\eta|<0.9$),
and to have a minimum transverse momentum of 1 GeV/$c$, which suppresses the
background with only a moderate $\text{J}/\psi$ efficiency loss. The tracks
are selected to have at least 2 hits in the ITS, one of which having to be in
one of the SPD layers, and share at most one hit with other tracks. A minimum
of 70 out of a maximum of 159 clusters are required in the TPC.

In order to reject tracks originating from weak decays and interactions with
the detector material, a selection based on the distance-of-closest approach
(DCA) to the primary vertex is applied to the tracks. For the MB analysis the
tracks are required to have a minimum DCA lower than 0.2 cm in the transverse
direction and 0.4 cm along the beam axis. Such tight selection criterion is
used in order to improve the signal-to-background ratio and the signal
significance. It was checked with Monte Carlo (MC) simulations that these
requirements do not lead to efficiency loss for the non-prompt $\text{J}/\psi$
relative to the prompt $\text{J}/\psi$. For the EMCal-triggered event
analysis, a looser selection on the DCA to the primary vertex at 1 and 3 cm is
applied to avoid rejecting non-prompt $\text{J}/\psi$ from highly boosted
beauty hadron decays.

The electrons are identified using the specific energy loss
$\textrm{d}E/\textrm{d}x$ in the TPC gas. Their $\textrm{d}E/\textrm{d}x$ is
required to be within a band of $[-2,3]~{}\sigma$ relative to the expectation
for electrons at the given track momentum, with $\sigma$ being the
$\textrm{d}E/\textrm{d}x$ resolution. The contamination from protons which
occurs in the momentum range $p<1.5$ GeV/$c$ and from pions for momenta above
2 GeV/$c$ is mitigated by rejecting tracks compatible with the proton or pion
hypothesis within $3\sigma$.

For the analysis of EMCal-triggered events, both the TPC and the EMCal are
used for electron identification. At least one of the $\text{J}/\psi$ decay-
electron tracks, initially identified by the TPC, is required to be matched to
an EMCal cluster (a group of adjacent towers belonging to the same
electromagnetic shower). In order to ensure a constant trigger efficiency on
the selected events, the matched clusters are selected to have a minimal
energy of 14 GeV, a value that is significantly higher than the applied online
threshold of 9 GeV. Electrons are identified by applying a selection on the
energy-to-momentum ratio of the EMCal matched track of $0.8<E/p<1.3$ and on
the $\textrm{d}E/\textrm{d}x$ in the TPC of $[-2.25,3]~{}\sigma$. Due to the
additional use of the EMCal for electron identification with respect to the MB
based analysis, no explicit hadron rejection was used for the EMCal sample.

Secondary electrons from photon conversions, the main background source for
both analyses, are rejected using the requirement of a hit in the SPD
detector. This requirement rejects most of the electrons from photon
conversions occurring beyond the SPD layers. An additional selection based on
track pairing, as described in details in Ref. [20], is applied to further
reject conversion electrons, especially those from photons converting in the
beam pipe or in the SPD.

###  3.2 Signal extraction

The number of reconstructed $\text{J}/\psi$ mesons is extracted from the
invariant mass ($m_{\rm ee}$) distribution of all possible opposite-sign (OS)
pairs constructed combining the selected electron tracks within the same event
(SE). Besides the $\text{J}/\psi$ signal, i.e. pairs of electrons originating
from the decay of a common $\text{J}/\psi$ mother, the invariant mass
distribution contains a background with contributions from combinatorial and
correlated sources.

In the MB analysis, the combinatorial background, i.e. pairs of electrons
originating from uncorrelated processes, is estimated using the event-mixing
technique (ME), in which pairs are built from opposite-sign electrons
belonging to different events. The mixing is done considering events from the
same run (a collection of events taken during a period of time of up to a few
hours) with a similar vertex position. The normalized combinatorial background
distribution $B_{\rm comb}(m_{\rm ee})$ is obtained as

$B_{\rm comb}(m_{\rm ee})=N_{\rm OS}^{\rm ME}(m_{\rm
ee})\times\frac{\sum_{m_{\rm i}}N_{\rm LS}^{\rm SE}(m_{\rm i})}{\sum_{m_{\rm
i}}N_{\rm LS}^{\rm ME}(m_{\rm i})}$ (2)

where $N_{\rm LS}^{\rm SE}$, $N_{\rm OS}^{\rm ME}$ and $N_{\rm LS}^{\rm ME}$
are the number of same-event like-sign (LS), mixed-event OS and mixed-event LS
pairs, respectively. Here, the mixed-event OS distribution is normalized using
the ratio of SE to ME like-sign pairs since these are not expected to contain
any significant correlated source. The summation extends over all the mass
bins $m_{\rm i}$ between 0 and 5 GeV/$c^{2}$ to minimize the statistical
uncertainty on the background matching. The correlated background in the mass
region relevant for this analysis originates mainly from semi-leptonic decays
of heavy-flavor hadrons [33]. In order to extract the number of reconstructed
$\text{J}/\psi$, $N_{\text{J}/\psi}$, the combinatorial background-subtracted
invariant mass distribution is fitted with a two-component function: one
empirical function to describe the correlated background shape, which is a
second order polynomial at low pair $p_{\rm T}$ ($p_{\rm T}^{\rm ee}<1$
GeV/$c$) and an exponential at high-$p_{\rm T}$ ($p_{\rm T}^{\rm ee}>1$
GeV/$c$), plus a template shape obtained from MC simulations, described in
Section 3.3, for the $\text{J}/\psi$ signal.

For the analysis of the EMCal-triggered event sample, due to the relatively
large contribution from correlated sources at high $p_{\rm T}$, the event
mixing technique is not used. Instead, a fit of the invariant mass
distribution is performed using the MC template for the signal and a third-
order polynomial function to describe both the combinatorial and correlated
background contributions.

In both analyses, the contribution from $\psi(2S)$ decaying in the dielectron
channel is not included in the fit as the expected number of such pairs is
$\sim$1% of the $\text{J}/\psi$ raw yield and it is statistically not
significant in the analyzed data samples. The number of $\text{J}/\psi$ is
obtained by counting the number of $\text{e}^{+}\text{e}^{-}$ pairs in the
mass range $2.92\leq m_{\text{ee}}\leq 3.16$ GeV/$c^{2}$ remaining after
subtracting the background. The SE-OS dielectron invariant mass distribution
for a few of the $p_{\rm T}$ intervals is shown in Fig. 1, together with the
estimated signal and background components.

Figure 1: (Color online) Invariant-mass distributions for SE
$\text{e}^{+}\text{e}^{-}$ pairs in two $p_{\rm T}^{\rm ee}$ intervals from
the MB event analysis (left panels) and two $p_{\rm T}^{\rm ee}$ intervals
from the EMCal-triggered event analysis (right panels). The signal and
background components obtained from the fit procedure are shown separately.
For the top-right panel, the distributions are scaled for convenience by a
factor of 2.

###  3.3 Corrections

The double differential $\text{J}/\psi$ production cross section is calculated
as

$\displaystyle\frac{\text{d}^{2}\sigma_{\text{J}/\psi}}{\text{d}y\text{d}p_{\rm
T}}=\frac{N_{\text{J}/\psi}}{\text{BR}(\text{J}/\psi\rightarrow\text{e}^{+}\text{e}^{-})\times\langle
A\times\epsilon\rangle\times\Delta y\times\Delta p_{\rm T}\times
L_{\text{int.}}}\,,$ (3)

where $N_{\text{J}/\psi}$ is the number of reconstructed $\text{J}/\psi$ in a
given interval of rapidity $\Delta y$ and transverse momentum $\Delta$$p_{\rm
T}$, $\text{BR}(\text{J}/\psi\rightarrow\text{e}^{+}\text{e}^{-})$ is the
decay branching ratio into the dielectron channel [34], $\langle
A\times\epsilon\rangle$ is the average acceptance and efficiency factor and
$L_{\text{int}}$ is the integrated luminosity of the data sample.

The correction for acceptance and efficiency is the product of the kinematical
acceptance factor, the reconstruction efficiency, which includes both tracking
and particle-identification (PID) efficiency, and the fraction of signal in
the signal counting mass window. For the EMCal-triggered events analysis, the
efficiency for the EMCal cluster reconstruction is also considered. The
efficiency related to the EMCal trigger is estimated using a parameterized
simulation of the L1 trigger which, includes decalibration and noise based on
measured data, and takes into account the time-dependent detector conditions.
With the exception of the PID efficiency, all the corrections are obtained
based on a MC simulation of unpolarized $\text{J}/\psi$ mesons embedded in
inelastic pp collisions simulated using PYTHIA 6.4 [35] with the Perugia 2011
tune [36]. The prompt $\text{J}/\psi$ are generated with a flat rapidity
distribution and a $p_{\rm T}$ spectrum obtained from a phenomenological
interpolation of $\text{J}/\psi$ measurements at RHIC, CDF and the LHC at
lower energies [37]. For the non-prompt $\text{J}/\psi$,
$\text{b}\overline{\text{b}}$ pairs are generated using the PYTHIA Perugia
2011 tune. The $\text{J}/\psi$ decays are simulated using PHOTOS [38], which
includes the radiative component of the $\text{J}/\psi$ decay. The generated
particles are transported through the ALICE detector setup using the GEANT3
package [39].

The PID efficiency is determined with a data-driven method by using a clean
sample of electrons from tagged photon conversion processes, passing the same
quality criteria as the electrons selected for the $\text{J}/\psi$
reconstruction. The PID selection efficiency for single electrons is
propagated to the $\text{J}/\psi$ level using a simulation of the
$\text{J}/\psi$ decay. The acceptance times efficiency correction factor for
the MB sample analysis varies with $p_{\rm T}$ between $7.6\%$ and $16\%$
while in the case of the EMCal-triggered sample analysis it increases with
$p_{\rm T}$ from 2 to 8%.

Due to the finite size of the $p_{\rm T}$ intervals, there is a mild
dependence of the correction factors on the shape of the inclusive
$\text{J}/\psi$ $p_{\rm T}$ distribution used in the simulation. This is
mitigated iteratively by using the corrected $\text{J}/\psi$ $p_{\rm
T}$-differential production cross section to reweight the acceptance times
efficiency correction factor and obtain an updated corrected cross section.
The procedure is stopped when the difference between the input and output
corrected $p_{\rm T}$-differential production cross section drops below 1%,
which typically occurs within 1 to 2 iterations, depending on the $p_{\rm T}$
interval. Additionally, to check if the default MC used in the analysis could
introduce a bias on the EMCal trigger efficiency, due to the enhancement of
$\text{J}/\psi$, another MC simulation, based on a di-jet production generated
by PYTHIA8 [40], at $\sqrt{s}~{}=~{}13$ TeV, is used as a cross-check. As a
result, the default MC and the di-jet MC lead to a compatible EMCal trigger
efficiency.

##  4 Systematic uncertainties

There are several sources of systematic uncertainties affecting this analysis,
namely the ITS-TPC tracking, the electron identification, the signal
extraction procedure, the $\text{J}/\psi$ input kinematic distributions used
in MC simulations, the determination of the integrated luminosity and the
branching ratio of the dielectron decay channel. A summary of these is given
in Table 1.

The uncertainty of the ITS-TPC tracking efficiency is one of the dominant
sources of systematic uncertainty and has two contributions: one due to the
TPC-ITS matching and one related to the track-quality requirements. The former
is obtained from the residual difference observed for the ITS-TPC single-track
matching between data and MC simulations [41], which is further propagated to
$\text{J}/\psi$ dielectron pairs. It varies between 2.8% and 5.4%, depending
on $p_{\rm T}$. The uncertainty related to the track-quality requirements is
estimated by repeating the analysis with variations of the selection criteria
and taking the root mean square (RMS) of the distribution of the results as
systematic uncertainty. This uncertainty also depends on $p_{\rm T}$ and is
equal to 3.7% for $p_{\rm T}<5$ GeV/$c$ and approximately 2% for $p_{\rm T}>5$
GeV/$c$. In Table 1, both contributions are added in quadrature and provided
as ranges for the $p_{\rm T}$\- and $y$-differential results.

As described in Section 3.3, the particle identification efficiency is
determined via a data-driven procedure using a sample of identified electrons
from tagged photon conversions. For the MB data sample, the uncertainty of
this procedure is estimated by repeating the analysis with a looser and a
tighter hadron (pion and proton combined) rejection criteria and taking the
largest deviation from the results obtained with the standard PID selection
divided by $\sqrt{12}$. In addition, the statistical uncertainty of the pure
electron sample used for the determination of the efficiency, which becomes
non-negligible at high $p_{\rm T}$, is propagated to the total uncertainty for
the PID. The total PID systematic uncertainty is larger than 1% only for
$p_{\rm T}>7$ GeV/$c$, reaching 4% in the $p_{\rm T}$ interval $10<p_{\rm
T}<15$ GeV/$c$. For the EMCal-triggered analysis, the particle identification
systematic uncertainty has contributions from the electron identification in
both the TPC and the EMCal. The values are estimated by varying the
$\textrm{d}E/\textrm{d}x$ range for the electron selection in the TPC, the
$E/p$ selection range in the EMCal, and the minimum energy of the matched
clusters. The total PID uncertainty, obtained in an analogous way as for the
MB sample, increases with $p_{\rm T}$ from 2.8% to 5.4%.

For $p_{\rm T}$ up to 15 GeV/$c$, the systematic uncertainties associated to
the $\text{J}/\psi$ signal extraction procedure is dominated by the
$\text{J}/\psi$ invariant mass signal shape template used to calculate the
fraction of reconstructed $\text{J}/\psi$ mesons within the signal counting
mass window. This uncertainty amounts to 1.9% and is evaluated by repeating
the extraction of the corrected yield with different invariant mass intervals
used for the signal counting and taking the RMS of the variations as a
systematic uncertainty. An additional source of uncertainty, due to the fit of
the correlated background, is determined by varying the fit mass range and is
typically below 1%. For $p_{\rm T}>$15 GeV/$c$, the systematic uncertainty
associated to the $\text{J}/\psi$ signal extraction are evaluated similarly to
the MB analysis, however, the components associated to the signal shape and
the background fit have similarly large contributions. This is one of the main
sources of uncertainty in this $p_{\rm T}$ range. The total uncertainty of the
signal extraction varies with $p_{\rm T}$ between about 2 and 7%.

The uncertainty on the EMCal trigger efficiency is studied varying the
contribution from random noise (evaluated using energy resolution measurements
in data) applied to the $4\times 4$ groups of adjacent towers. It was also
studied using the di-jet production generated by PYTHIA8 at
$\sqrt{s}~{}=~{}13$ TeV mentioned in Sec. 3.3. The latter study showed a
difference in the EMCal trigger efficiency of 0.5%, which is assigned as a
systematic uncertainty.

Since the $\text{J}/\psi$ efficiency has a dependence on $p_{\rm T}$, the
particular $\text{J}/\psi$ kinematic distribution used in the MC simulation,
from which efficiencies are derived, can have an impact on the average
efficiency computed for finite $p_{\rm T}$ intervals. As described in Section
3.3, this is mitigated via an iterative procedure and the remaining
uncertainty is related to the precision of the measured $\text{J}/\psi$
spectrum. This uncertainty is estimated by fitting the measured $p_{\rm T}$
spectrum with a power law function and allowing the fitted parameters to vary
according to the covariance matrix. For each of such a variation, the average
efficiency in a given kinematic interval is recomputed and the RMS of the
distribution obtained from the variation of efficiency with respect to the
central value is taken as a systematic uncertainty. This amounts to 1% for the
$p_{\rm T}$-integrated case and is smaller for all of the considered $p_{\rm
T}$ intervals.

The uncertainty of the integrated luminosity arising from the vdM-scan based
measurements amounts to $1.6\%$ for both the MB and EMCal-triggered data
samples, and is determined as described in Ref. [32]. For the EMCal-triggered
data sample only, an additional uncertainty of 1.1% arising from the precision
of the trigger downscaling is assigned. The uncertainty on the $\text{J}/\psi$
decay branching ratio to the dielectron channel amounts to 0.53% as reported
by the Particle Data Group [34].

The uncertainties of the integrated luminosity and branching ratio are treated
as global systematic uncertainties. All the other uncertainties are considered
as point to point correlated, with the exception of the one due to the
background fit which is considered to be fully uncorrelated. The systematic
uncertainties are thus dominated by correlated sources. The total correlated,
uncorrelated and global uncertainties obtained as the sum in quadrature of the
corresponding sources are given in Table 1.

Table 1: Summary of contributions to systematic uncertainties of the measured $\text{J}/\psi$ production cross section (in percentage). Source | ($p_{\rm T}$, $y$)-integrated |  $y$-differential |  $p_{\rm T}$-differential (MB) |  $p_{\rm T}$-differential (EMCal)
---|---|---|---|---
|  |  |  $0<p_{\rm T}<15$ (GeV/$c$) |  $15<p_{\rm T}<40$ (GeV/$c$)
Tracking | 4.9 | 4.7 – 6.5 | 5.7
PID | 0.6 | 0.0 – 4.1 | 2.8 – 5.4
Signal shape | 1.9 | 1.4 – 2.2 | 1.0 – 4.0
Background fit | 0.3 | 0.3 – 0.4 | 0.2 – 1.2 | 1.0 – 6.0
MC input | 1.0 | 0.0 – 0.9 | 0.9
EMCal trigger | not used | not used | not used | 0.5
Luminosity | 1.6 | 2.0
Branching ratio | 0.5
Total uncorrelated | 0.3 | 0.3 – 0.4 | 0.2 – 1.2 | 1.0 – 6.0
Total correlated | 5.4 | 5.4 | 5.2 – 7.4 | 6.5 – 8.8
Global | 1.7 | 2.0
Total (w/o global) | 5.4 | 5.4 | 5.3 – 7.5 | 7.0 – 11.0

##  5 Results

The inclusive $p_{\rm T}$-differential $\text{J}/\psi$ production cross
section in pp collisions at $\sqrt{s}~{}=~{}13$ TeV at midrapidity, obtained
from the combined analysis of the MB-triggered ($p_{\rm T}<15$ GeV/$c$) and
EMCal-triggered ($15<p_{\rm T}<40$ GeV/$c$) samples is shown in the upper
panels of Fig. 2. Statistical uncertainties are shown as error bars, while the
boxes around the data points represent the correlated and uncorrelated
systematic uncertainties added in quadrature, excluding the global uncertainty
from luminosity determination and branching ratio. The $x$-axis extent of the
boxes illustrates the size of the $p_{\rm T}$ interval with the data points
placed in the center. A simple power law function of the type

$f(p_{\rm T})=A\times p_{\rm T}/(1+(p_{\rm T}/p_{0})^{2})^{n},$ (4)

with $A$, $p_{0}$ and $n$ being free parameters, is used to fit the measured
distribution. Since the systematic uncertainties are largely correlated, only
the statistical ones are used in the fit. Due to the large $p_{\rm T}$
intervals, the fit is performed by considering the mean value of the function
in the $p_{\rm T}$ interval rather than its value at the center of the
interval. The values obtained for the fitted parameters are $A=2.15\pm
0.18~{}\mu\text{b}/(\text{GeV}/c)^{2}$, $p_{0}=4.09\pm 0.22$ GeV/$c$ and
$n=3.04\pm 0.09$. The fit function, shown in Fig. 2 as a dashed red line,
provides a good description of the data points measured with both MB and EMCal
data samples, and illustrates the consistency between the two analyses.

In the left panel of Fig. 2, the production cross section measured at
midrapidity is compared with the forward rapidity measurement at the same
energy [21]. The bottom panel shows the ratio between the forward rapidity
data points and the mean cross section at midrapidity obtained by integrating
the fit function described above in the $p_{\rm T}$ intervals of the forward-
rapidity measurement. The displayed uncertainty boxes include the systematic
uncertainty of the forward rapidity measurement and the uncertainty of the
function mean, added in quadrature. A monotonic drop of this ratio can be
observed towards high $p_{\rm T}$, indicating a harder $\text{J}/\psi$ $p_{\rm
T}$ distribution at midrapidity.

Figure 2: Inclusive $\text{J}/\psi$ production cross section at midrapidity
($|y|<0.9$) in pp collisions at $\sqrt{s}~{}=~{}13$ TeV compared with the
ALICE forward-rapidity measurement at $\sqrt{s}~{}=~{}13$ TeV [21] (left
panel) and the scaled ALICE midrapidity measurements at $\sqrt{s}~{}=~{}5.02$
TeV [20] and $\sqrt{s}~{}=~{}7$ TeV [18] (right panel). The error bars
represent statistical uncertainties while the boxes around the data points
represent the total systematic uncertainty, excluding the global uncertainty
from the luminosity and branching ratio. The lower panels show the ratio
between the measurements at different rapidity and energies, and the power law
fit, discussed in the text, to the $\text{J}/\psi$ production cross section
(red dashed line) at midrapidity at $\sqrt{s}~{}=~{}13$ TeV. The boxes in the
lower panels include the systematic uncertainty of the data points and the
uncertainty of the integral of the fit function in the given $p_{\rm T}$
interval added in quadrature.

The right panel of Fig. 2 shows a comparison with midrapidity measurements
performed by the ALICE Collaboration in pp collisions at the lower collision
energies of $\sqrt{s}~{}=~{}7$ TeV [18] and 5.02 TeV [20]. In the bottom
panel, the ratio between the lower energy measurements and the fitted 13 TeV
results is shown. The displayed uncertainty boxes include the systematic
uncertainty of the lower energy data points and the uncertainty of the fit
function mean, added in quadrature. Although the uncertainties of the
measurement at 7 TeV are large, the data indicates an increase of the
production cross section with increasing collision energy. In addition, the
monotonic drop of the ratio between the 5.02 TeV and 13 TeV measurements
indicates a hardening of the $p_{\rm T}$ spectrum with increasing collision
energy, as also observed from the energy dependence of the inclusive
$\text{J}/\psi$ average $p_{\rm T}$ discussed in Ref. [20].

Figure 3: (Color online) Inclusive $\text{J}/\psi$ production cross section
compared with calculations for the prompt $\text{J}/\psi$ production cross
section using ICEM [42], NLO NRQCD [4, 3, 43], LO NRQCD+CGC [44] and for the
non-prompt $\text{J}/\psi$ from beauty-hadron feed-down using FONLL [45] (left
panel). Inclusive $\text{J}/\psi$ production cross section compared with the
corresponding calculations obtained as the sum of the prompt $\text{J}/\psi$
component shown in the left panel and the non-prompt contribution from FONLL
(right panel). The bottom panel shows the ratios between the model
calculations and a fit to the data points. The bands illustrate the
theoretical uncertainties centered around the ratio between the model
calculation and the power-law fit to the data (see text for details).

The measured inclusive $\text{J}/\psi$ production cross section is compared
with several phenomenological calculations of the prompt $\text{J}/\psi$
production in the left panel of Fig. 3. In addition, to illustrate the impact
of the unaccounted feed-down from beauty decays in the theory predictions, a
calculation of the non-prompt $\text{J}/\psi$ production by Cacciari et al.,
using the Fixed-Order Next-to-Leading-Logarithms approach (FONLL) [45], is
shown in the same panel. According to the FONLL calculations, the non-prompt
contribution to the inclusive $\text{J}/\psi$ yield is approximately 10% at
low-$p_{\rm T}$ and grows to approximately 50% at $p_{\rm T}$ =40 GeV/$c$. In
the right panel of Fig. 3, the measured inclusive production cross section is
compared to predictions for inclusive $\text{J}/\psi$ production obtained as
the sum of the prompt $\text{J}/\psi$ calculations listed above and the beauty
feed-down contribution calculated using FONLL. The bottom panel shows the
ratio between each theoretical calculation and the fit to the data. The
colored bands represent the theoretical uncertainties for each model, centered
around the model to data ratio. These uncertainties are typically due to the
variation of the renormalization and factorization scales, and of the charm
quark mass.

Several phenomenological approaches are used for the calculation of the
$\text{J}/\psi$ yields shown in Fig. 3. The green and blue dashed lines
represent NLO NRQCD calculations from Ma et al. [4] and Butenschoen et al.
[3], respectively, using collinear gluon parton distribution functions (PDFs).
Although the calculation of the short distance terms is very similar, the
predictions of these two approaches differ due to the LDME sets which are
obtained in separate fits of the Tevatron and HERA data with different
low-$p_{\rm T}$ cutoffs. In addition, the calculation from Ref. [3] does not
include the feed-down from higher mass charmonium states. The brown solid line
represents a calculation obtained with the MC generator PEGASUS [43] developed
by Lipatov et al. which employs a $k_{\rm T}$-factorization approach using
$p_{\rm T}$-dependent gluon distribution functions and NRQCD matrix elements
combined with LDMEs extracted from an NLO high-transverse momentum analysis
[8]. Using the KMR [46] technique to construct the unintegrated gluon PDFs,
this calculation can extend down to $\text{J}/\psi$ $p_{\rm T}=0$. A different
model to calculate the low $p_{\rm T}$ $\text{J}/\psi$ production cross
section, by Ma and Venugopalan [44] (green solid line) is based on a Color-
Glass Condensate (CGC) approach coupled to a Leading Order (LO) NRQCD
calculation which includes a soft-gluon resummation. The calculations obtained
using the ICEM model by Cheung and Vogt [42] within the $k_{\rm
T}$-factorization approach are shown by the violet solid line. In this
calculation, LDMEs are not used, however one normalization parameter per
charmonium state is used to account for long distance effects [47]. The feed
down from the higher mass charmonium states is taken into account in this
model.

As shown in the right panel of Fig. 3, all the models provide a reasonable
description of the inclusive $\text{J}/\psi$ production cross section within
the theoretical uncertainties over the entire $p_{\rm T}$ range covered by
this measurement. In particular, both the ICEM and NRQCD+CGC calculations show
very good agreement with the data in the low-$p_{\rm T}$ range. The NRQCD
calculation from Lipatov, which uses the $k_{\rm T}$-factorization approach,
also provides a good description of the data for $p_{\rm T}>2$ GeV/$c$, while
it overestimates the measured cross section at lower $p_{\rm T}$. However,
this is a significant progress compared to traditional collinear approaches
which tend to diverge towards $p_{\rm T}=0$.

Figure 4: (Color online) Inclusive $p_{\rm T}$-integrated $\text{J}/\psi$
production cross section as a function of collision energy (left panel) and
rapidity (right panel) compared with the ICEM [42] and NRQCD+CGC [44] model
calculations. The midrapidity $p_{\rm T}$-integrated production cross section
values are measured by the PHENIX [48], STAR [49], CDF [50] and ALICE [19, 20,
18] collaborations. The forward-rapidity production cross section shown in the
right panel is reported by ALICE in Ref. [21].

The measured $p_{\rm T}$-integrated inclusive $\text{J}/\psi$ production cross
section at midrapidity, obtained by performing the analysis on the MB data
sample without any explicit selection on the $\text{J}/\psi$ $p_{\rm T}$
($p_{\rm T}>0$), is

$\displaystyle\frac{\text{d}\sigma_{\text{J}/\psi}}{\text{d}y}=8.97\pm
0.24\;\text{(stat.)}\pm 0.48\;\text{(syst.)}\pm 0.15\;\text{(lumi)}\pm
0.05\;\text{(BR)}\;\mu\text{b}\;.$

The systematic uncertainty includes all the systematic sources mentioned in
Table 1 added in quadrature, with the exception of the global ones which are
given separately. The fraction of the total cross section covered by the
EMCal-triggered event analysis results ($p_{\rm T}>15$ GeV/$c$) is estimated
to be less than 0.5% and is not used in this measurement. A comparison of this
measurement with previous midrapidity measurements in pp collisions at lower
energies from PHENIX [48], STAR [49], CDF [50] and ALICE [19, 20, 18] is shown
in the left panel of Fig. 4. An approximate logarithmic increase of the cross
sections with the energy is observed. The collision energy-dependent
measurements are also compared with the calculations from the ICEM [42] and
the NRQCD+CGC [44] models. Both calculations provide a good description of the
energy dependent trend within large theoretical uncertainties, dominated by
the low-$p_{\rm T}$ region of the spectrum.

The right panel of Fig. 4 shows the rapidity-differential inclusive
$\text{J}/\psi$ production cross section which includes three data points
measured in this analysis around midrapidity and the previously published
ALICE measurement at forward rapidity [21]. While no rapidity dependence is
observed in the central rapidity range, a steep decrease towards forward
rapidity is seen. The two model calculations employed, using ICEM [42] and the
NRQCD+CGC [44], combined with non-prompt contributions calculated with FONLL
[45], exhibit rather different rapidity dependences. However, both are
compatible with the data owing to the large theoretical uncertainties, which
are at present much larger than the experimental uncertainties.

##  6 Conclusions

The integrated, and the $p_{\rm T}$\- and $y$-differential inclusive
$\text{J}/\psi$ production cross sections at midrapidity ($|y|<0.9$) in pp
collisions at $\sqrt{s}~{}=~{}13$ TeV are presented in the $p_{\rm T}$ range
$0<p_{\rm T}<40$ GeV/$c$, exceeding the $p_{\rm T}$ range of all the previous
measurements reported by the ALICE Collaboration. The measurement up to 15
GeV/$c$ is performed using a minimum-bias triggered data sample and the one at
high-$p_{\rm T}$ is performed using an EMCal-triggered data sample, both
collected by ALICE during the LHC Run 2.

The data are compared with the ALICE lower collision energy measurements at
midrapidity [20, 18] and with the ALICE forward-rapidity results [21]. An
approximate logarithmic dependence of the integrated $\text{J}/\psi$
production cross section with collision energy is suggested by the data, in
agreement with the available predictions. The $p_{\rm T}$-differential cross
section measured in this analysis shows a significant hardening with respect
to both the forward-rapidity measurement at $\sqrt{s}~{}=~{}13$ TeV and the
midrapidity measurement at $\sqrt{s}~{}=~{}5.02$ TeV.

Several calculations within the NRQCD framework [4, 3, 43, 44] and one using
the ICEM approach [42] are compared with the measured inclusive
$\text{J}/\psi$ production cross section. In particular, the ICEM, the NRQCD
model based on the CGC approach and a new NRQCD calculation using the $k_{\rm
T}$-factorization approach provide a prediction for the $\text{J}/\psi$
production cross section down to $p_{\rm T}=0$. All models provide a good
description of the measured inclusive $\text{J}/\psi$ production cross
section, although with large theoretical uncertainties.

## Acknowledgements

We wish to thank Mathias Butenschoen, Vincent Cheung, Bernd A. Kniehl, Artem
V. Lipatov, Yan-Qing Ma, Raju Venugopalan and Ramona Vogt for kindly providing
their calculations.

The ALICE Collaboration would like to thank all its engineers and technicians for their invaluable contributions to the construction of the experiment and the CERN accelerator teams for the outstanding performance of the LHC complex. The ALICE Collaboration gratefully acknowledges the resources and support provided by all Grid centres and the Worldwide LHC Computing Grid (WLCG) collaboration. The ALICE Collaboration acknowledges the following funding agencies for their support in building and running the ALICE detector: A. I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation (ANSL), State Committee of Science and World Federation of Scientists (WFS), Armenia; Austrian Academy of Sciences, Austrian Science Fund (FWF): [M 2467-N36] and Nationalstiftung für Forschung, Technologie und Entwicklung, Austria; Ministry of Communications and High Technologies, National Nuclear Research Center, Azerbaijan; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Financiadora de Estudos e Projetos (Finep), Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and Universidade Federal do Rio Grande do Sul (UFRGS), Brazil; Ministry of Education of China (MOEC) , Ministry of Science & Technology of China (MSTC) and National Natural Science Foundation of China (NSFC), China; Ministry of Science and Education and Croatian Science Foundation, Croatia; Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Cubaenergía, Cuba; Ministry of Education, Youth and Sports of the Czech Republic, Czech Republic; The Danish Council for Independent Research | Natural Sciences, the VILLUM FONDEN and Danish National Research Foundation (DNRF), Denmark; Helsinki Institute of Physics (HIP), Finland; Commissariat à l’Energie Atomique (CEA) and Institut National de Physique Nucléaire et de Physique des Particules (IN2P3) and Centre National de la Recherche Scientifique (CNRS), France; Bundesministerium für Bildung und Forschung (BMBF) and GSI Helmholtzzentrum für Schwerionenforschung GmbH, Germany; General Secretariat for Research and Technology, Ministry of Education, Research and Religions, Greece; National Research, Development and Innovation Office, Hungary; Department of Atomic Energy Government of India (DAE), Department of Science and Technology, Government of India (DST), University Grants Commission, Government of India (UGC) and Council of Scientific and Industrial Research (CSIR), India; Indonesian Institute of Science, Indonesia; Istituto Nazionale di Fisica Nucleare (INFN), Italy; Institute for Innovative Science and Technology , Nagasaki Institute of Applied Science (IIST), Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) and Japan Society for the Promotion of Science (JSPS) KAKENHI, Japan; Consejo Nacional de Ciencia (CONACYT) y Tecnología, through Fondo de Cooperación Internacional en Ciencia y Tecnología (FONCICYT) and Dirección General de Asuntos del Personal Academico (DGAPA), Mexico; Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), Netherlands; The Research Council of Norway, Norway; Commission on Science and Technology for Sustainable Development in the South (COMSATS), Pakistan; Pontificia Universidad Católica del Perú, Peru; Ministry of Education and Science, National Science Centre and WUT ID-UB, Poland; Korea Institute of Science and Technology Information and National Research Foundation of Korea (NRF), Republic of Korea; Ministry of Education and Scientific Research, Institute of Atomic Physics and Ministry of Research and Innovation and Institute of Atomic Physics, Romania; Joint Institute for Nuclear Research (JINR), Ministry of Education and Science of the Russian Federation, National Research Centre Kurchatov Institute, Russian Science Foundation and Russian Foundation for Basic Research, Russia; Ministry of Education, Science, Research and Sport of the Slovak Republic, Slovakia; National Research Foundation of South Africa, South Africa; Swedish Research Council (VR) and Knut & Alice Wallenberg Foundation (KAW), Sweden; European Organization for Nuclear Research, Switzerland; Suranaree University of Technology (SUT), National Science and Technology Development Agency (NSDTA) and Office of the Higher Education Commission under NRU project of Thailand, Thailand; Turkish Energy, Nuclear and Mineral Research Agency (TENMAK), Turkey; National Academy of Sciences of Ukraine, Ukraine; Science and Technology Facilities Council (STFC), United Kingdom; National Science Foundation of the United States of America (NSF) and United States Department of Energy, Office of Nuclear Physics (DOE NP), United States of America.

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##  Appendix A The ALICE collaboration

S. Acharya143, D. Adamová98, A. Adler76, G. Aglieri Rinella35, M. Agnello31,
N. Agrawal55, Z. Ahammed143, S. Ahmad16, S.U. Ahn78, I. Ahuja39, Z. Akbar52,
A. Akindinov95, M. Al-Turany110, S.N. Alam16,41, D. Aleksandrov91, B.
Alessandro61, H.M. Alfanda7, R. Alfaro Molina73, B. Ali16, Y. Ali14, A.
Alici26, N. Alizadehvandchali127, A. Alkin35, J. Alme21, T. Alt70, L.
Altenkamper21, I. Altsybeev115, M.N. Anaam7, C. Andrei49, D. Andreou93, A.
Andronic146, M. Angeletti35, V. Anguelov107, F. Antinori58, P. Antonioli55, C.
Anuj16, N. Apadula82, L. Aphecetche117, H. Appelshäuser70, S. Arcelli26, R.
Arnaldi61, I.C. Arsene20, M. Arslandok148,107, A. Augustinus35, R.
Averbeck110, S. Aziz80, M.D. Azmi16, A. Badalà57, Y.W. Baek42, X. Bai131,110,
R. Bailhache70, Y. Bailung51, R. Bala104, A. Balbino31, A. Baldisseri140, B.
Balis2, M. Ball44, D. Banerjee4, R. Barbera27, L. Barioglio108, M. Barlou87,
G.G. Barnaföldi147, L.S. Barnby97, V. Barret137, C. Bartels130, K. Barth35, E.
Bartsch70, F. Baruffaldi28, N. Bastid137, S. Basu83, G. Batigne117, B.
Batyunya77, D. Bauri50, J.L. Bazo Alba114, I.G. Bearden92, C. Beattie148, I.
Belikov139, A.D.C. Bell Hechavarria146, F. Bellini26, R. Bellwied127, S.
Belokurova115, V. Belyaev96, G. Bencedi71, S. Beole25, A. Bercuci49, Y.
Berdnikov101, A. Berdnikova107, L. Bergmann107, M.G. Besoiu69, L. Betev35,
P.P. Bhaduri143, A. Bhasin104, I.R. Bhat104, M.A. Bhat4, B. Bhattacharjee43,
P. Bhattacharya23, L. Bianchi25, N. Bianchi53, J. Bielčík38, J. Bielčíková98,
J. Biernat120, A. Bilandzic108, G. Biro147, S. Biswas4, J.T. Blair121, D.
Blau91,84, M.B. Blidaru110, C. Blume70, G. Boca29,59, F. Bock99, A.
Bogdanov96, S. Boi23, J. Bok63, L. Boldizsár147, A. Bolozdynya96, M.
Bombara39, P.M. Bond35, G. Bonomi142,59, H. Borel140, A. Borissov84, H.
Bossi148, E. Botta25, L. Bratrud70, P. Braun-Munzinger110, M. Bregant123, M.
Broz38, G.E. Bruno109,34, M.D. Buckland130, D. Budnikov111, H. Buesching70, S.
Bufalino31, O. Bugnon117, P. Buhler116, Z. Buthelezi74,134, J.B. Butt14, A.
Bylinkin129, S.A. Bysiak120, M. Cai28,7, H. Caines148, A. Caliva110, E. Calvo
Villar114, J.M.M. Camacho122, R.S. Camacho46, P. Camerini24, F.D.M. Canedo123,
F. Carnesecchi35,26, R. Caron140, J. Castillo Castellanos140, E.A.R. Casula23,
F. Catalano31, C. Ceballos Sanchez77, P. Chakraborty50, S. Chandra143, S.
Chapeland35, M. Chartier130, S. Chattopadhyay143, S. Chattopadhyay112, A.
Chauvin23, T.G. Chavez46, T. Cheng7, C. Cheshkov138, B. Cheynis138, V.
Chibante Barroso35, D.D. Chinellato124, S. Cho63, P. Chochula35, P.
Christakoglou93, C.H. Christensen92, P. Christiansen83, T. Chujo136, C.
Cicalo56, L. Cifarelli26, F. Cindolo55, M.R. Ciupek110, G. ClaiII,55, J.
CleymansI,126, F. Colamaria54, J.S. Colburn113, D. Colella109,54,34,147, A.
Collu82, M. Colocci35, M. ConcasIII,61, G. Conesa Balbastre81, Z. Conesa del
Valle80, G. Contin24, J.G. Contreras38, M.L. Coquet140, T.M. Cormier99, P.
Cortese32, M.R. Cosentino125, F. Costa35, S. Costanza29,59, P. Crochet137, R.
Cruz-Torres82, E. Cuautle71, P. Cui7, L. Cunqueiro99, A. Dainese58, M.C.
Danisch107, A. Danu69, I. Das112, P. Das89, P. Das4, S. Das4, S. Dash50, S.
De89, A. De Caro30, G. de Cataldo54, L. De Cilladi25, J. de Cuveland40, A. De
Falco23, D. De Gruttola30, N. De Marco61, C. De Martin24, S. De Pasquale30, S.
Deb51, H.F. Degenhardt123, K.R. Deja144, L. Dello Stritto30, S. Delsanto25, W.
Deng7, P. Dhankher19, D. Di Bari34, A. Di Mauro35, R.A. Diaz8, T. Dietel126,
Y. Ding138,7, R. Divià35, D.U. Dixit19, Ø. Djuvsland21, U. Dmitrieva65, J.
Do63, A. Dobrin69, B. Dönigus70, O. Dordic20, A.K. Dubey143, A. Dubla110,93,
S. Dudi103, M. Dukhishyam89, P. Dupieux137, N. Dzalaiova13, T.M. Eder146, R.J.
Ehlers99, V.N. Eikeland21, F. Eisenhut70, D. Elia54, B. Erazmus117, F.
Ercolessi26, F. Erhardt102, A. Erokhin115, M.R. Ersdal21, B. Espagnon80, G.
Eulisse35, D. Evans113, S. Evdokimov94, L. Fabbietti108, M. Faggin28, J.
Faivre81, F. Fan7, A. Fantoni53, M. Fasel99, P. Fecchio31, A. Feliciello61, G.
Feofilov115, A. Fernández Téllez46, A. Ferrero140, A. Ferretti25, V.J.G.
Feuillard107, J. Figiel120, S. Filchagin111, D. Finogeev65, F.M. Fionda56,21,
G. Fiorenza35,109, F. Flor127, A.N. Flores121, S. Foertsch74, P. Foka110, S.
Fokin91, E. Fragiacomo62, E. Frajna147, U. Fuchs35, N. Funicello30, C.
Furget81, A. Furs65, J.J. Gaardhøje92, M. Gagliardi25, A.M. Gago114, A.
Gal139, C.D. Galvan122, P. Ganoti87, C. Garabatos110, J.R.A. Garcia46, E.
Garcia-Solis10, K. Garg117, C. Gargiulo35, A. Garibli90, K. Garner146, P.
Gasik110, E.F. Gauger121, A. Gautam129, M.B. Gay Ducati72, M. Germain117, P.
Ghosh143, S.K. Ghosh4, M. Giacalone26, P. Gianotti53, P. Giubellino110,61, P.
Giubilato28, A.M.C. Glaenzer140, P. Glässel107, D.J.Q. Goh85, V. Gonzalez145,
L.H. González-Trueba73, S. Gorbunov40, M. Gorgon2, L. Görlich120, S.
Gotovac36, V. Grabski73, L.K. Graczykowski144, L. Greiner82, A. Grelli64, C.
Grigoras35, V. Grigoriev96, S. Grigoryan77,1, O.S. Groettvik21, F. Grosa35,61,
J.F. Grosse-Oetringhaus35, R. Grosso110, G.G. Guardiano124, R. Guernane81, M.
Guilbaud117, K. Gulbrandsen92, T. Gunji135, W. Guo7, A. Gupta104, R. Gupta104,
S.P. Guzman46, L. Gyulai147, M.K. Habib110, C. Hadjidakis80, G. Halimoglu70,
H. Hamagaki85, G. Hamar147, M. Hamid7, R. Hannigan121, M.R. Haque144,89, A.
Harlenderova110, J.W. Harris148, A. Harton10, J.A. Hasenbichler35, H.
Hassan99, D. Hatzifotiadou55, P. Hauer44, L.B. Havener148, S. Hayashi135, S.T.
Heckel108, E. Hellbär110, H. Helstrup37, T. Herman38, E.G. Hernandez46, G.
Herrera Corral9, F. Herrmann146, K.F. Hetland37, H. Hillemanns35, C. Hills130,
B. Hippolyte139, B. Hofman64, B. Hohlweger93, J. Honermann146, G.H. Hong149,
D. Horak38, S. Hornung110, A. Horzyk2, R. Hosokawa15, Y. Hou7, P. Hristov35,
C. Hughes133, P. Huhn70, T.J. Humanic100, H. Hushnud112, L.A. Husova146, A.
Hutson127, D. Hutter40, J.P. Iddon35,130, R. Ilkaev111, H. Ilyas14, M.
Inaba136, G.M. Innocenti35, M. Ippolitov91, A. Isakov38,98, M.S. Islam112, M.
Ivanov110, V. Ivanov101, V. Izucheev94, M. Jablonski2, B. Jacak82, N.
Jacazio35, P.M. Jacobs82, S. Jadlovska119, J. Jadlovsky119, S. Jaelani64, C.
Jahnke124,123, M.J. Jakubowska144, A. Jalotra104, M.A. Janik144, T. Janson76,
M. Jercic102, O. Jevons113, A.A.P. Jimenez71, F. Jonas99,146, P.G. Jones113,
J.M. Jowett 35,110, J. Jung70, M. Jung70, A. Junique35, A. Jusko113, J.
Kaewjai118, P. Kalinak66, A.S. Kalteyer110, A. Kalweit35, V. Kaplin96, S.
Kar7, A. Karasu Uysal79, D. Karatovic102, O. Karavichev65, T. Karavicheva65,
P. Karczmarczyk144, E. Karpechev65, A. Kazantsev91, U. Kebschull76, R.
Keidel48, D.L.D. Keijdener64, M. Keil35, B. Ketzer44, Z. Khabanova93, A.M.
Khan7, S. Khan16, A. Khanzadeev101, Y. Kharlov94,84, A. Khatun16, A.
Khuntia120, B. Kileng37, B. Kim17,63, C. Kim17, D.J. Kim128, E.J. Kim75, J.
Kim149, J.S. Kim42, J. Kim107, J. Kim149, J. Kim75, M. Kim107, S. Kim18, T.
Kim149, S. Kirsch70, I. Kisel40, S. Kiselev95, A. Kisiel144, J.P. Kitowski2,
J.L. Klay6, J. Klein35, S. Klein82, C. Klein-Bösing146, M. Kleiner70, T.
Klemenz108, A. Kluge35, A.G. Knospe127, C. Kobdaj118, M.K. Köhler107, T.
Kollegger110, A. Kondratyev77, N. Kondratyeva96, E. Kondratyuk94, J. Konig70,
S.A. Konigstorfer108, P.J. Konopka35,2, G. Kornakov144, S.D. Koryciak2, L.
Koska119, A. Kotliarov98, O. Kovalenko88, V. Kovalenko115, M. Kowalski120, I.
Králik66, A. Kravčáková39, L. Kreis110, M. Krivda113,66, F. Krizek98, K.
Krizkova Gajdosova38, M. Kroesen107, M. Krüger70, E. Kryshen101, M.
Krzewicki40, V. Kučera35, C. Kuhn139, P.G. Kuijer93, T. Kumaoka136, D.
Kumar143, L. Kumar103, N. Kumar103, S. Kundu35, P. Kurashvili88, A. Kurepin65,
A.B. Kurepin65, A. Kuryakin111, S. Kushpil98, J. Kvapil113, M.J. Kweon63, J.Y.
Kwon63, Y. Kwon149, S.L. La Pointe40, P. La Rocca27, Y.S. Lai82, A.
Lakrathok118, M. Lamanna35, R. Langoy132, K. Lapidus35, P. Larionov35,53, E.
Laudi35, L. Lautner35,108, R. Lavicka38, T. Lazareva115, R. Lea142,24,59, J.
Lehrbach40, R.C. Lemmon97, I. León Monzón122, E.D. Lesser19, M.
Lettrich35,108, P. Lévai147, X. Li11, X.L. Li7, J. Lien132, R. Lietava113, B.
Lim17, S.H. Lim17, V. Lindenstruth40, A. Lindner49, C. Lippmann110, A. Liu19,
D.H. Liu7, J. Liu130, I.M. Lofnes21, V. Loginov96, C. Loizides99, P. Loncar36,
J.A. Lopez107, X. Lopez137, E. López Torres8, J.R. Luhder146, M. Lunardon28,
G. Luparello62, Y.G. Ma41, A. Maevskaya65, M. Mager35, T. Mahmoud44, A.
Maire139, M. Malaev101, N.M. Malik104, Q.W. Malik20, L. MalininaIV,77, D.
Mal’Kevich95, N. Mallick51, P. Malzacher110, G. Mandaglio33,57, V. Manko91, F.
Manso137, V. Manzari54, Y. Mao7, J. Mareš68, G.V. Margagliotti24, A.
Margotti55, A. Marín110, C. Markert121, M. Marquard70, N.A. Martin107, P.
Martinengo35, J.L. Martinez127, M.I. Martínez46, G. Martínez García117, S.
Masciocchi110, M. Masera25, A. Masoni56, L. Massacrier80, A.
Mastroserio141,54, A.M. Mathis108, O. Matonoha83, P.F.T. Matuoka123, A.
Matyja120, C. Mayer120, A.L. Mazuecos35, F. Mazzaschi25, M. Mazzilli35, M.A.
MazzoniI,60, J.E. Mdhluli134, A.F. Mechler70, F. Meddi22, Y. Melikyan65, A.
Menchaca-Rocha73, E. Meninno116,30, A.S. Menon127, M. Meres13, S.
Mhlanga126,74, Y. Miake136, L. Micheletti61,25, L.C. Migliorin138, D.L.
Mihaylov108, K. Mikhaylov77,95, A.N. Mishra147, D. Miśkowiec110, A. Modak4,
A.P. Mohanty64, B. Mohanty89, M. Mohisin KhanV,16, M.A. Molander45, Z.
Moravcova92, C. Mordasini108, D.A. Moreira De Godoy146, L.A.P. Moreno46, I.
Morozov65, A. Morsch35, T. Mrnjavac35, V. Muccifora53, E. Mudnic36, D.
Mühlheim146, S. Muhuri143, J.D. Mulligan82, A. Mulliri23, M.G. Munhoz123, R.H.
Munzer70, H. Murakami135, S. Murray126, L. Musa35, J. Musinsky66, J.W.
Myrcha144, B. Naik134,50, R. Nair88, B.K. Nandi50, R. Nania55, E. Nappi54,
A.F. Nassirpour83, A. Nath107, C. Nattrass133, A. Neagu20, L. Nellen71, S.V.
Nesbo37, G. Neskovic40, D. Nesterov115, B.S. Nielsen92, S. Nikolaev91, S.
Nikulin91, V. Nikulin101, F. Noferini55, S. Noh12, P. Nomokonov77, J.
Norman130, N. Novitzky136, P. Nowakowski144, A. Nyanin91, J. Nystrand21, M.
Ogino85, A. Ohlson83, V.A. Okorokov96, J. Oleniacz144, A.C. Oliveira Da
Silva133, M.H. Oliver148, A. Onnerstad128, C. Oppedisano61, A. Ortiz
Velasquez71, T. Osako47, A. Oskarsson83, J. Otwinowski120, M. Oya47, K.
Oyama85, Y. Pachmayer107, S. Padhan50, D. Pagano142,59, G. Paić71, A.
Palasciano54, J. Pan145, S. Panebianco140, P. Pareek143, J. Park63, J.E.
Parkkila128, S.P. Pathak127, R.N. Patra104,35, B. Paul23, H. Pei7, T.
Peitzmann64, X. Peng7, L.G. Pereira72, H. Pereira Da Costa140, D.
Peresunko91,84, G.M. Perez8, S. Perrin140, Y. Pestov5, V. Petráček38, M.
Petrovici49, R.P. Pezzi117,72, S. Piano62, M. Pikna13, P. Pillot117, O.
Pinazza55,35, L. Pinsky127, C. Pinto27, S. Pisano53, M. Płoskoń82, M.
Planinic102, F. Pliquett70, M.G. Poghosyan99, B. Polichtchouk94, S.
Politano31, N. Poljak102, A. Pop49, S. Porteboeuf-Houssais137, J. Porter82, V.
Pozdniakov77, S.K. Prasad4, R. Preghenella55, F. Prino61, C.A. Pruneau145, I.
Pshenichnov65, M. Puccio35, S. Qiu93, L. Quaglia25, R.E. Quishpe127, S.
Ragoni113, A. Rakotozafindrabe140, L. Ramello32, F. Rami139, S.A.R. Ramirez46,
A.G.T. Ramos34, T.A. Rancien81, R. Raniwala105, S. Raniwala105, S.S.
Räsänen45, R. Rath51, I. Ravasenga93, K.F. Read99,133, A.R. Redelbach40, K.
RedlichVI,88, A. Rehman21, P. Reichelt70, F. Reidt35, H.A. Reme-ness37, R.
Renfordt70, Z. Rescakova39, K. Reygers107, A. Riabov101, V. Riabov101, T.
Richert83, M. Richter20, W. Riegler35, F. Riggi27, C. Ristea69, M. Rodríguez
Cahuantzi46, K. Røed20, R. Rogalev94, E. Rogochaya77, T.S. Rogoschinski70, D.
Rohr35, D. Röhrich21, P.F. Rojas46, P.S. Rokita144, F. Ronchetti53, A.
Rosano33,57, E.D. Rosas71, A. Rossi58, A. Rotondi29,59, A. Roy51, P. Roy112,
S. Roy50, N. Rubini26, O.V. Rueda83, R. Rui24, B. Rumyantsev77, P.G. Russek2,
A. Rustamov90, E. Ryabinkin91, Y. Ryabov101, A. Rybicki120, H. Rytkonen128, W.
Rzesa144, O.A.M. Saarimaki45, R. Sadek117, S. Sadovsky94, J. Saetre21, K.
Šafařík38, S.K. Saha143, S. Saha89, B. Sahoo50, P. Sahoo50, R. Sahoo51, S.
Sahoo67, D. Sahu51, P.K. Sahu67, J. Saini143, S. Sakai136, S. Sambyal104, V.
SamsonovI,101,96, D. Sarkar145, N. Sarkar143, P. Sarma43, V.M. Sarti108,
M.H.P. Sas148, J. Schambach99,121, H.S. Scheid70, C. Schiaua49, R.
Schicker107, A. Schmah107, C. Schmidt110, H.R. Schmidt106, M.O. Schmidt35, M.
Schmidt106, N.V. Schmidt99,70, A.R. Schmier133, R. Schotter139, J.
Schukraft35, Y. Schutz139, K. Schwarz110, K. Schweda110, G. Scioli26, E.
Scomparin61, J.E. Seger15, Y. Sekiguchi135, D. Sekihata135, I.
Selyuzhenkov110,96, S. Senyukov139, J.J. Seo63, D. Serebryakov65, L.
Šerkšnytė108, A. Sevcenco69, T.J. Shaba74, A. Shabanov65, A. Shabetai117, R.
Shahoyan35, W. Shaikh112, A. Shangaraev94, A. Sharma103, H. Sharma120, M.
Sharma104, N. Sharma103, S. Sharma104, U. Sharma104, O. Sheibani127, K.
Shigaki47, M. Shimomura86, S. Shirinkin95, Q. Shou41, Y. Sibiriak91, S.
Siddhanta56, T. Siemiarczuk88, T.F. Silva123, D. Silvermyr83, T.
Simantathammakul118, G. Simonetti35, B. Singh108, R. Singh89, R. Singh104, R.
Singh51, V.K. Singh143, V. Singhal143, T. Sinha112, B. Sitar13, M. Sitta32,
T.B. Skaali20, G. Skorodumovs107, M. Slupecki45, N. Smirnov148, R.J.M.
Snellings64, C. Soncco114, J. Song127, A. Songmoolnak118, F. Soramel28, S.
Sorensen133, I. Sputowska120, J. Stachel107, I. Stan69, P.J. Steffanic133,
S.F. Stiefelmaier107, D. Stocco117, I. Storehaug20, M.M. Storetvedt37, C.P.
Stylianidis93, A.A.P. Suaide123, T. Sugitate47, C. Suire80, M. Sukhanov65, M.
Suljic35, R. Sultanov95, M. Šumbera98, V. Sumberia104, S. Sumowidagdo52, S.
Swain67, A. Szabo13, I. Szarka13, U. Tabassam14, S.F. Taghavi108, G.
Taillepied137, J. Takahashi124, G.J. Tambave21, S. Tang137,7, Z. Tang131, J.D.
Tapia TakakiVII,129, M. Tarhini117, M.G. Tarzila49, A. Tauro35, G. Tejeda
Muñoz46, A. Telesca35, L. Terlizzi25, C. Terrevoli127, G. Tersimonov3, S.
Thakur143, D. Thomas121, R. Tieulent138, A. Tikhonov65, A.R. Timmins127, M.
Tkacik119, A. Toia70, N. Topilskaya65, M. Toppi53, F. Torales-Acosta19, T.
Tork80, S.R. Torres38, A. Trifiró33,57, S. Tripathy55,71, T. Tripathy50, S.
Trogolo35,28, V. Trubnikov3, W.H. Trzaska128, T.P. Trzcinski144, B.A.
Trzeciak38, A. Tumkin111, R. Turrisi58, T.S. Tveter20, K. Ullaland21, A.
Uras138, M. Urioni59,142, G.L. Usai23, M. Vala39, N. Valle59,29, S. Vallero61,
N. van der Kolk64, L.V.R. van Doremalen64, M. van Leeuwen93, P. Vande Vyvre35,
D. Varga147, Z. Varga147, M. Varga-Kofarago147, A. Vargas46, M. Vasileiou87,
A. Vasiliev91, O. Vázquez Doce53,108, V. Vechernin115, E. Vercellin25, S.
Vergara Limón46, L. Vermunt64, R. Vértesi147, M. Verweij64, L. Vickovic36, Z.
Vilakazi134, O. Villalobos Baillie113, G. Vino54, A. Vinogradov91, T.
Virgili30, V. Vislavicius92, A. Vodopyanov77, B. Volkel35, M.A. Völkl107, K.
Voloshin95, S.A. Voloshin145, G. Volpe34, B. von Haller35, I. Vorobyev108, D.
Voscek119, N. Vozniuk65, J. Vrláková39, B. Wagner21, C. Wang41, D. Wang41, M.
Weber116, R.J.G.V. Weelden93, A. Wegrzynek35, S.C. Wenzel35, J.P. Wessels146,
J. Wiechula70, J. Wikne20, G. Wilk88, J. Wilkinson110, G.A. Willems146, B.
Windelband107, M. Winn140, W.E. Witt133, J.R. Wright121, W. Wu41, Y. Wu131, R.
Xu7, A.K. Yadav143, S. Yalcin79, Y. Yamaguchi47, K. Yamakawa47, S. Yang21, S.
Yano47, Z. Yin7, H. Yokoyama64, I.-K. Yoo17, J.H. Yoon63, S. Yuan21, A.
Yuncu107, V. Zaccolo24, C. Zampolli35, H.J.C. Zanoli64, N. Zardoshti35, A.
Zarochentsev115, P. Závada68, N. Zaviyalov111, M. Zhalov101, B. Zhang7, S.
Zhang41, X. Zhang7, Y. Zhang131, V. Zherebchevskii115, Y. Zhi11, N.
Zhigareva95, D. Zhou7, Y. Zhou92, J. Zhu7,110, Y. Zhu7, A. Zichichi26, G.
Zinovjev3, N. Zurlo142,59

Affiliation Notes

I Deceased

II Also at: Italian National Agency for New Technologies, Energy and
Sustainable Economic Development (ENEA), Bologna, Italy

III Also at: Dipartimento DET del Politecnico di Torino, Turin, Italy

IV Also at: M.V. Lomonosov Moscow State University, D.V. Skobeltsyn Institute
of Nuclear, Physics, Moscow, Russia

V Also at: Department of Applied Physics, Aligarh Muslim University, Aligarh,
India

VI Also at: Institute of Theoretical Physics, University of Wroclaw, Poland

VII Also at: University of Kansas, Lawrence, Kansas, United States

Collaboration Institutes

1 A.I. Alikhanyan National Science Laboratory (Yerevan Physics Institute)
Foundation, Yerevan, Armenia

2 AGH University of Science and Technology, Cracow, Poland

3 Bogolyubov Institute for Theoretical Physics, National Academy of Sciences
of Ukraine, Kiev, Ukraine

4 Bose Institute, Department of Physics and Centre for Astroparticle Physics
and Space Science (CAPSS), Kolkata, India

5 Budker Institute for Nuclear Physics, Novosibirsk, Russia

6 California Polytechnic State University, San Luis Obispo, California, United
States

7 Central China Normal University, Wuhan, China

8 Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Havana,
Cuba

9 Centro de Investigación y de Estudios Avanzados (CINVESTAV), Mexico City and
Mérida, Mexico

10 Chicago State University, Chicago, Illinois, United States

11 China Institute of Atomic Energy, Beijing, China

12 Chungbuk National University, Cheongju, Republic of Korea

13 Comenius University Bratislava, Faculty of Mathematics, Physics and
Informatics, Bratislava, Slovakia

14 COMSATS University Islamabad, Islamabad, Pakistan

15 Creighton University, Omaha, Nebraska, United States

16 Department of Physics, Aligarh Muslim University, Aligarh, India

17 Department of Physics, Pusan National University, Pusan, Republic of Korea

18 Department of Physics, Sejong University, Seoul, Republic of Korea

19 Department of Physics, University of California, Berkeley, California,
United States

20 Department of Physics, University of Oslo, Oslo, Norway

21 Department of Physics and Technology, University of Bergen, Bergen, Norway

22 Dipartimento di Fisica dell’Università ’La Sapienza’ and Sezione INFN,
Rome, Italy

23 Dipartimento di Fisica dell’Università and Sezione INFN, Cagliari, Italy

24 Dipartimento di Fisica dell’Università and Sezione INFN, Trieste, Italy

25 Dipartimento di Fisica dell’Università and Sezione INFN, Turin, Italy

26 Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN,
Bologna, Italy

27 Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN,
Catania, Italy

28 Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN,
Padova, Italy

29 Dipartimento di Fisica e Nucleare e Teorica, Università di Pavia, Pavia,
Italy

30 Dipartimento di Fisica ‘E.R. Caianiello’ dell’Università and Gruppo
Collegato INFN, Salerno, Italy

31 Dipartimento DISAT del Politecnico and Sezione INFN, Turin, Italy

32 Dipartimento di Scienze e Innovazione Tecnologica dell’Università del
Piemonte Orientale and INFN Sezione di Torino, Alessandria, Italy

33 Dipartimento di Scienze MIFT, Università di Messina, Messina, Italy

34 Dipartimento Interateneo di Fisica ‘M. Merlin’ and Sezione INFN, Bari,
Italy

35 European Organization for Nuclear Research (CERN), Geneva, Switzerland

36 Faculty of Electrical Engineering, Mechanical Engineering and Naval
Architecture, University of Split, Split, Croatia

37 Faculty of Engineering and Science, Western Norway University of Applied
Sciences, Bergen, Norway

38 Faculty of Nuclear Sciences and Physical Engineering, Czech Technical
University in Prague, Prague, Czech Republic

39 Faculty of Science, P.J. Šafárik University, Košice, Slovakia

40 Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-
Universität Frankfurt, Frankfurt, Germany

41 Fudan University, Shanghai, China

42 Gangneung-Wonju National University, Gangneung, Republic of Korea

43 Gauhati University, Department of Physics, Guwahati, India

44 Helmholtz-Institut für Strahlen- und Kernphysik, Rheinische Friedrich-
Wilhelms-Universität Bonn, Bonn, Germany

45 Helsinki Institute of Physics (HIP), Helsinki, Finland

46 High Energy Physics Group, Universidad Autónoma de Puebla, Puebla, Mexico

47 Hiroshima University, Hiroshima, Japan

48 Hochschule Worms, Zentrum für Technologietransfer und Telekommunikation
(ZTT), Worms, Germany

49 Horia Hulubei National Institute of Physics and Nuclear Engineering,
Bucharest, Romania

50 Indian Institute of Technology Bombay (IIT), Mumbai, India

51 Indian Institute of Technology Indore, Indore, India

52 Indonesian Institute of Sciences, Jakarta, Indonesia

53 INFN, Laboratori Nazionali di Frascati, Frascati, Italy

54 INFN, Sezione di Bari, Bari, Italy

55 INFN, Sezione di Bologna, Bologna, Italy

56 INFN, Sezione di Cagliari, Cagliari, Italy

57 INFN, Sezione di Catania, Catania, Italy

58 INFN, Sezione di Padova, Padova, Italy

59 INFN, Sezione di Pavia, Pavia, Italy

60 INFN, Sezione di Roma, Rome, Italy

61 INFN, Sezione di Torino, Turin, Italy

62 INFN, Sezione di Trieste, Trieste, Italy

63 Inha University, Incheon, Republic of Korea

64 Institute for Gravitational and Subatomic Physics (GRASP), Utrecht
University/Nikhef, Utrecht, Netherlands

65 Institute for Nuclear Research, Academy of Sciences, Moscow, Russia

66 Institute of Experimental Physics, Slovak Academy of Sciences, Košice,
Slovakia

67 Institute of Physics, Homi Bhabha National Institute, Bhubaneswar, India

68 Institute of Physics of the Czech Academy of Sciences, Prague, Czech
Republic

69 Institute of Space Science (ISS), Bucharest, Romania

70 Institut für Kernphysik, Johann Wolfgang Goethe-Universität Frankfurt,
Frankfurt, Germany

71 Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México,
Mexico City, Mexico

72 Instituto de Física, Universidade Federal do Rio Grande do Sul (UFRGS),
Porto Alegre, Brazil

73 Instituto de Física, Universidad Nacional Autónoma de México, Mexico City,
Mexico

74 iThemba LABS, National Research Foundation, Somerset West, South Africa

75 Jeonbuk National University, Jeonju, Republic of Korea

76 Johann-Wolfgang-Goethe Universität Frankfurt Institut für Informatik,
Fachbereich Informatik und Mathematik, Frankfurt, Germany

77 Joint Institute for Nuclear Research (JINR), Dubna, Russia

78 Korea Institute of Science and Technology Information, Daejeon, Republic of
Korea

79 KTO Karatay University, Konya, Turkey

80 Laboratoire de Physique des 2 Infinis, Irène Joliot-Curie, Orsay, France

81 Laboratoire de Physique Subatomique et de Cosmologie, Université Grenoble-
Alpes, CNRS-IN2P3, Grenoble, France

82 Lawrence Berkeley National Laboratory, Berkeley, California, United States

83 Lund University Department of Physics, Division of Particle Physics, Lund,
Sweden

84 Moscow Institute for Physics and Technology, Moscow, Russia

85 Nagasaki Institute of Applied Science, Nagasaki, Japan

86 Nara Women’s University (NWU), Nara, Japan

87 National and Kapodistrian University of Athens, School of Science,
Department of Physics , Athens, Greece

88 National Centre for Nuclear Research, Warsaw, Poland

89 National Institute of Science Education and Research, Homi Bhabha National
Institute, Jatni, India

90 National Nuclear Research Center, Baku, Azerbaijan

91 National Research Centre Kurchatov Institute, Moscow, Russia

92 Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark

93 Nikhef, National institute for subatomic physics, Amsterdam, Netherlands

94 NRC Kurchatov Institute IHEP, Protvino, Russia

95 NRC «Kurchatov»Institute - ITEP, Moscow, Russia

96 NRNU Moscow Engineering Physics Institute, Moscow, Russia

97 Nuclear Physics Group, STFC Daresbury Laboratory, Daresbury, United Kingdom

98 Nuclear Physics Institute of the Czech Academy of Sciences, Řež u Prahy,
Czech Republic

99 Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States

100 Ohio State University, Columbus, Ohio, United States

101 Petersburg Nuclear Physics Institute, Gatchina, Russia

102 Physics department, Faculty of science, University of Zagreb, Zagreb,
Croatia

103 Physics Department, Panjab University, Chandigarh, India

104 Physics Department, University of Jammu, Jammu, India

105 Physics Department, University of Rajasthan, Jaipur, India

106 Physikalisches Institut, Eberhard-Karls-Universität Tübingen, Tübingen,
Germany

107 Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg,
Heidelberg, Germany

108 Physik Department, Technische Universität München, Munich, Germany

109 Politecnico di Bari and Sezione INFN, Bari, Italy

110 Research Division and ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum
für Schwerionenforschung GmbH, Darmstadt, Germany

111 Russian Federal Nuclear Center (VNIIEF), Sarov, Russia

112 Saha Institute of Nuclear Physics, Homi Bhabha National Institute,
Kolkata, India

113 School of Physics and Astronomy, University of Birmingham, Birmingham,
United Kingdom

114 Sección Física, Departamento de Ciencias, Pontificia Universidad Católica
del Perú, Lima, Peru

115 St. Petersburg State University, St. Petersburg, Russia

116 Stefan Meyer Institut für Subatomare Physik (SMI), Vienna, Austria

117 SUBATECH, IMT Atlantique, Université de Nantes, CNRS-IN2P3, Nantes, France

118 Suranaree University of Technology, Nakhon Ratchasima, Thailand

119 Technical University of Košice, Košice, Slovakia

120 The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy of
Sciences, Cracow, Poland

121 The University of Texas at Austin, Austin, Texas, United States

122 Universidad Autónoma de Sinaloa, Culiacán, Mexico

123 Universidade de São Paulo (USP), São Paulo, Brazil

124 Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil

125 Universidade Federal do ABC, Santo Andre, Brazil

126 University of Cape Town, Cape Town, South Africa

127 University of Houston, Houston, Texas, United States

128 University of Jyväskylä, Jyväskylä, Finland

129 University of Kansas, Lawrence, Kansas, United States

130 University of Liverpool, Liverpool, United Kingdom

131 University of Science and Technology of China, Hefei, China

132 University of South-Eastern Norway, Tonsberg, Norway

133 University of Tennessee, Knoxville, Tennessee, United States

134 University of the Witwatersrand, Johannesburg, South Africa

135 University of Tokyo, Tokyo, Japan

136 University of Tsukuba, Tsukuba, Japan

137 Université Clermont Auvergne, CNRS/IN2P3, LPC, Clermont-Ferrand, France

138 Université de Lyon, CNRS/IN2P3, Institut de Physique des 2 Infinis de Lyon
, Lyon, France

139 Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France,
Strasbourg, France

140 Université Paris-Saclay Centre d’Etudes de Saclay (CEA), IRFU, Départment
de Physique Nucléaire (DPhN), Saclay, France

141 Università degli Studi di Foggia, Foggia, Italy

142 Università di Brescia, Brescia, Italy

143 Variable Energy Cyclotron Centre, Homi Bhabha National Institute, Kolkata,
India

144 Warsaw University of Technology, Warsaw, Poland

145 Wayne State University, Detroit, Michigan, United States

146 Westfälische Wilhelms-Universität Münster, Institut für Kernphysik,
Münster, Germany

147 Wigner Research Centre for Physics, Budapest, Hungary

148 Yale University, New Haven, Connecticut, United States

149 Yonsei University, Seoul, Republic of Korea