2023 190 29 August

Prompt and non-prompt $\rm J/\psi$ production in Pb–Pb collisions

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

The transverse momentum ($p_{\rm T}$) and centrality dependence of the nuclear
modification factor $R_{\rm AA}$ of prompt and non-prompt $\rm J/\psi$, the
latter originating from the weak decays of beauty hadrons, have been measured
by the ALICE collaboration in Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}$ =
5.02 TeV. The measurements are carried out through the ${\rm e}^{+}{\rm
e}^{-}$ decay channel at midrapidity ($|y|<0.9$) in the transverse momentum
region $1.5<p_{\rm T}<10$ GeV/$c$. Both prompt and non-prompt $\rm J/\psi$
measurements indicate a significant suppression for $p_{\rm T}$ $>$ 5 GeV/$c$,
which becomes stronger with increasing collision centrality. The results are
consistent with similar LHC measurements in the overlapping $p_{\rm T}$
intervals, and cover the kinematic region down to $p_{\rm T}$ = 1.5 GeV/$c$ at
midrapidity, not accessible by other LHC experiments. The suppression of
prompt $\rm J/\psi$ in central and semicentral collisions exhibits a
decreasing trend towards lower transverse momentum, described within
uncertainties by models implementing $\rm J/\psi$ production from
recombination of c and $\overline{\rm c}$ quarks produced independently in
different partonic scatterings. At high transverse momentum, transport models
including quarkonium dissociation are able to describe the suppression for
prompt $\rm J/\psi$. For non-prompt $\rm J/\psi$, the suppression predicted by
models including both collisional and radiative processes for the computation
of the beauty-quark energy loss inside the quark–gluon plasma is consistent
with measurements within uncertainties.

##  1 Introduction

Quantum chromodynamics (QCD) calculations on the lattice [1, 2, 3, 4] predict
the existence of the quark–gluon plasma (QGP), a state of strongly-interacting
matter characterised by quark and gluon degrees of freedom, expected to be
produced at extremely high temperatures and energy densities. Such conditions
can be realised in the laboratory by colliding heavy ions at ultra-
relativistic energies, enabling the study of the properties of this state of
matter, as shown by multiple measurements carried out at the SPS [5, 6], RHIC
[7, 8, 9, 10] and LHC [11]. Heavy quarks, i.e. charm and beauty, are mainly
produced in hard parton–parton scatterings and on a shorter time scale than
the QGP formation time at LHC energies ($\tau_{\rm QGP}\approx 1.5{\rm fm}/c$)
[12, 13], thus experiencing the full QGP evolution. Charmonia, bound states of
a charm and an anti-charm quark, are interesting probes of the QGP. In fact,
it was predicted that their production would be suppressed in this medium due
to static colour screening resulting from the high density of colour charges
inside it [14] or due to dynamical dissociation [15]. A suppression of the
$\rm J/\psi$ yield in heavy-ion collisions relative to proton–proton
collisions was observed at the SPS [16, 17], RHIC [18, 19, 20, 21] and LHC
[22, 23, 24, 25, 26, 27, 28, 29, 30, 31]. However, at LHC energies, the $\rm
J/\psi$ suppression is significantly reduced compared to lower energy results,
in particular at low transverse momentum ($p_{\rm T}$) and in more central
collisions. These findings are interpreted by considering an additional
contribution to the $\rm J/\psi$ production, known as regeneration, according
to which the abundantly produced charm and anti-charm quarks from different
hard partonic scatterings can recombine to form charmonium states [32, 33].
Previous ALICE inclusive $\rm J/\psi$ measurements at both central and forward
rapidity, which have revealed significantly less suppression of $\rm J/\psi$
at low transverse momentum compared to lower energies [31, 27, 28] as well as
non-zero elliptic flow [34, 35], have clearly demonstrated the relevance of
this mechanism.

Different phenomenological scenarios are assumed for the description of
charmonium production in heavy-ion collisions. In the Statistical
Hadronisation model [32, 36], the abundances of all charmonium states are
determined by thermal weights at the chemical freeze-out. By contrast,
according to several partonic transport models [33, 37, 38] the charmonium
states can be produced via regeneration throughout the full evolution of the
QGP phase. Recent inclusive $\rm J/\psi$ results in Pb–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV indicate that both approaches can provide
a description of the measured suppression within uncertainties in the
low-$p_{\rm T}$ region [31, 27, 28]. Results of $\psi(2S)$ suppression
recently released by the ALICE collaboration [39] show that transport models
better reproduce charmonium measurements for central events compared to the
Statistical Hadronisation model. Besides providing a good description of the
production, transport models are also able to describe the elliptic flow of
inclusive $\rm J/\psi$ [34, 40]. As the $p_{\rm T}$ of the $\rm J/\psi$
increases, the contribution from regeneration becomes less relevant, while
charmonium dissociation and fragmentation of high-energy partons into
charmonia become dominant.

Inclusive $\rm J/\psi$ production in high-energy hadronic collisions consists
of several contributions: the $\rm J/\psi$ produced directly and from the
decays of higher mass charmonium states (e.g. $\psi$(2S) or $\chi_{\rm c}$),
known as the “prompt” contribution, and $\rm J/\psi$ originating from the weak
decays of beauty hadrons. The latter component, referred to as “non-prompt”,
is characterised by a production vertex displaced with respect to the primary
vertex of the collision, and this feature is exploited experimentally to
separate the two contributions. The measurement of prompt $\rm J/\psi$
production enables a direct comparison with prompt charmonium models. In
addition, the non-prompt $\rm J/\psi$ production measurement grants a direct
insight into the suppression of beauty hadrons, which are expected to be
sensitive to the properties of the medium created in heavy-ion collisions as
ancestor beauty quarks experience energy loss by interacting with QGP
constituents. The energy loss of partons inside the medium is expected to
happen via both radiative [41, 42] and elastic collisional processes [43, 44,
45]. The relative contribution of the former is expected to increase with
$p_{\rm T}$. The energy loss strongly depends on the colour charge of the
parton, being larger for gluons than for quarks, as well as on the parton mass
[46, 47, 48]. The production of open heavy-flavour hadrons in nuclear
collisions is also affected by in-medium hadronisation effects. Due to the
high quark density in the QGP, heavy quarks can also hadronise via
coalescence, by recombining with other light flavour quarks inside the medium
[49, 50, 51].

In order to interpret both prompt and non-prompt $\rm J/\psi$ results in
nuclear collisions, cold nuclear matter (CNM) effects need to be considered.
The main effect at LHC energies is represented by the modification of the
parton distribution functions of protons and neutrons inside nuclei compared
to the ones of the free nucleons [52]. These effects are usually addressed
through measurements in proton–nucleus collisions at the same centre-of-mass
energy and are expected to be effective below 3 GeV/$c$ for prompt $\rm
J/\psi$, as shown by recent $\rm J/\psi$ results in p–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV [53]. For non-prompt $\rm J/\psi$, a small
suppression with no significant $p_{\rm T}$ dependence is observed, although
with large uncertainties [53].

At LHC energies in heavy-ion collisions, the production of prompt and non-
prompt $\rm J/\psi$ was measured at midrapidity by the CMS [22] and ALICE [54]
collaborations in Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}$ = 2.76 TeV. At
the centre-of-mass energy of $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV in the
central rapidity region, the ATLAS [29] and CMS [30] collaborations measured
the suppression of prompt and non-prompt $\rm J/\psi$ at high transverse
momentum. At low $p_{\rm T}$, inclusive $\rm J/\psi$ measurements were carried
out by the ALICE collaboration [31, 28]. In this article, $p_{\rm T}$ and
centrality dependent measurements of prompt and non-prompt $\rm J/\psi$
production at midrapidity in Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}$ =
5.02 TeV are presented. These results, obtained down to $p_{\rm T}$ = 1.5
GeV/$c$, have a unique kinematic coverage at the LHC compared to existing
midrapidity measurements at the same centre-of-mass energy, which are
available only at high transverse momentum. Furthermore, they have a
significantly improved precision compared to previous published ALICE results
at lower energy.

This article is organised as follows: the ALICE apparatus and data samples are
described in Section 2, the analysis technique is presented in Section 3,
results and comparison with similar measurements from other experiments and
model calculations are discussed in Section 4, and finally the summary is
provided in Section 5.

##  2 Experimental apparatus and data sample

The ALICE detector consists of a central barrel with a pseudorapidity coverage
of $|\eta|<0.9$ and a forward rapidity muon spectrometer with a pseudorapidity
coverage for muons of $-4<\eta<-2.5$. It also includes forward and backward
pseudorapidity detectors employed for triggering, background rejection, and
event characterisation. Central barrel detectors are placed inside a magnetic
field $B$ = 0.5 T provided by a solenoidal magnet. A complete description of
the detector and an overview of its performance are discussed in Refs. [55,
56]. The main detectors employed for the analysis described in this article
are the Inner Tracking System (ITS) [56], the Time Projection Chamber (TPC)
[57] and the V0 detector [58]. Both ITS and TPC detectors enable the
measurement of inclusive $\rm J/\psi$ mesons via the dielectron decay channel
in the central rapidity region down to zero $p_{\rm T}$. The ITS consists of
six layers of silicon detectors, with the two innermost layers composed of
silicon pixel detectors (SPD) which provide the spatial resolution to separate
prompt and non-prompt $\rm J/\psi$ on a statistical basis. The TPC is the main
tracking detector of the central barrel. In addition, it allows for particle
identification via the measurement of the specific ionisation energy loss
d$E$/d$x$ in the detector gas. The V0 detector consists of two scintillator
arrays placed on each side of the interaction point (with pseudorapidity
coverage $2.8<\eta<5.1$ and $-3.7<\eta<-1.7$), and it is used to reject
offline beam-induced background events, to define a minimum bias trigger, and
to characterise the event centrality. The zero degree calorimeters [59],
located at $\pm$112.5 m on both sides of the interaction point, are used to
reject electromagnetic interactions and beam-induced background in Pb–Pb
collisions. The results presented in this article are based on the same data
samples of Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV employed
for the inclusive $\rm J/\psi$ analysis [31]. In particular, it consist of a
combination of the data samples collected during the years 2015 and 2018 of
the LHC Run 2. In order to obtain a uniform acceptance of the detectors, only
events with a reconstructed primary vertex position along the beam line
located within $\pm$10 cm from the centre of the detector were considered. In
addition, consecutive events triggered within a time interval smaller than the
readout time of the TPC were discarded as these are expected to have a high
total charge deposition in the active volume and consequently significantly
worse particle identification performance of the TPC. The datasets are
collected with a minimum bias triggered event sample, provided by the
coincidence of signals in the two scintillator arrays of the V0 detector. The
corresponding integrated luminosity is about 24 $\rm\mu b^{-1}$ [60]. In
addition, centrality triggered samples, whose trigger definition is based on
the amplitude of the signal collected in the V0 detector, were used. These
correspond to central (0–10%) and semicentral (30–50%) events, equivalent to
an integrated luminosity of 105 and 51 $\rm\mu b^{-1}$ [60], respectively.

##  3 Data analysis

In order to estimate hot nuclear matter effects, the nuclear modification
factor can be defined as the production yield in Pb–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV normalised to the reference production
cross section in pp collisions at the same energy and scaled by the average
nuclear overlap function $\langle T_{\rm AA}\rangle$ [60]:

$R_{\rm AA}=\frac{{\rm d}N/{{\rm d}p_{\rm T}{\rm d}{\it y}}}{\langle T_{\rm
AA}\rangle\times{\rm d}\sigma_{\rm pp}/{\rm d}p_{\rm T}{\rm d}y}.$ (1)

Inclusive $\rm J/\psi$ measurements with no separation between prompt and non-
prompt contributions are carried out by the ALICE collaboration at midrapidity
($|y|<0.9$) in Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV, as
discussed in Ref. [31]. The nuclear modification factors of prompt and non-
prompt $\rm J/\psi$ at midrapidity can be obtained by combining inclusive $\rm
J/\psi$ $R_{\rm AA}$ measurements with non-prompt $\rm J/\psi$ fractions
($f_{\rm B}$), the latter defined as the ratios of the production yields of
$\rm J/\psi$ mesons originating from beauty-hadron decays to that of inclusive
$\rm J/\psi$, estimated in both Pb–Pb collisions and pp collisions at the same
centre-of-mass energy.

###  3.1 Non-prompt $\rm J/\psi$ analysis in Pb–Pb collisions

#### Selection of $\rm J/\psi$ candidates

The event selection and track quality requirements used in the analysis
discussed in this article are identical to those used for the corresponding
midrapidity inclusive $\rm J/\psi$ $R_{\rm AA}$ analysis in Pb–Pb collisions
at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV [31]. Prompt and non-prompt $\rm
J/\psi$ measurements are carried out in the $\rm J/\psi$ transverse momentum
interval 1.5–10 GeV/$c$ and in four different centrality classes, namely
0–10%, 10–30%, 30–50%, and 50–90%. The results are presented as a function of
the transverse momentum of the $\rm J/\psi$, as well as of the average number
of participants ($\langle N_{\rm part}\rangle$). The latter can be estimated
via Glauber model calculations [61, 62, 63, 64] for the different centrality
intervals [60].

$\rm J/\psi$ candidates are reconstructed at midrapidity ($|y|<0.9$) through
the dielectron decay channel. Electron candidates, reconstructed using both
ITS and TPC detectors, are required to have a pseudorapidity in the interval
$|\eta|<0.9$, a minimum transverse momentum of 1 GeV/$c$, and a minimum of 70
space points out of a maximum of 159 in the TPC. A hit in at least one of the
two SPD layers is also required to improve the tracking and the spatial
resolution. Several quality selection criteria, also employed for the
inclusive $\rm J/\psi$ analysis [31], are considered in order to ensure good
track resolution, as well as to reduce the contribution of electrons and
positrons originating from photon conversion in the detector material and to
reject secondary tracks originating from weak decays. The electron
identification relies on the measurement of d$\it E$/d$\it x$ in the TPC,
using stricter requirements than those considered for the inclusive $\rm
J/\psi$ analysis in order to increase the signal-to-background ratio, in
particular at low transverse momentum and in central events. For tracks
reconstructed in more peripheral centrality classes, namely 30–50% and 50–90%,
the TPC d$\it E$/d$\it x$ signal is required to lie within the interval
$[-3,3]\sigma_{\rm e}$ relative to the expectation for electrons, where
$\sigma_{\rm e}$ represents the specific energy-loss resolution for electrons
in the TPC. In addition, tracks consistent with the pion and proton
assumptions within 3.5$\sigma$ are rejected. For the centrality classes 0–10%
and 10–30%, the electron inclusion is requested to be $[-2,3]\sigma_{\rm e}$
$\left([-1,3]\sigma_{\rm e}\right)$ for the $p_{\rm T}$ of the electron below
(above) 5 GeV/$c$. A 4.5$\sigma$ rejection for protons and pions is applied
only below 5 GeV/$c$ of the electron momentum at the inner wall of the TPC,
while above 5 GeV/$c$ the rejection is not applied to avoid reductions in the
electron reconstruction efficiency. $\rm J/\psi$ candidates are then obtained
by considering all opposite-sign charged electron pairs. In 0–10% most central
collisions, only candidates where both electron decay tracks have a hit in the
first layer of the SPD are considered to optimise both the spatial resolution
and signal-to-background ratio. For other centrality classes as well as in the
highest $p_{\rm T}$ interval (7–10 GeV/$c$) in the 0–10% centrality class,
where the signal-to-background ratio is better, the condition is released to
increase the efficiency. Pair candidates where neither of the decay products
has a hit in the first layer of the SPD are excluded due to the poor
resolution of the secondary vertex.

#### Separation of prompt and non-prompt $\rm J/\psi$

The measurement of the non-prompt $\rm J/\psi$ fraction is obtained through an
unbinned two-dimensional likelihood fit procedure applied to reconstructed
$\rm J/\psi$ candidate pairs, following the same techniques employed in
previous publications [54, 53, 65, 66, 67]. A simultaneous unbinned log-
likelihood fit of the $\rm J/\psi$ candidate distribution as a function of
invariant mass ($m_{\rm ee}$) and pseudoproper decay length ($x$) values is
performed. The pseudoproper decay length is defined as $x=c\times L_{\rm
xy}\times m_{\rm\rm J/\psi}/p_{\rm T}$, where $L_{\rm
xy}=(\vec{L}\times\vec{p_{\rm T}})/p_{\rm T}$ represents the projection in the
transverse plane of the vector pointing from the primary vertex to the $\rm
J/\psi$ decay vertex ($\vec{L}$) and $m_{\rm\rm J/\psi}$ is the $\rm J/\psi$
mass provided by the Particle Data Group (PDG) [68]. The fit procedure
maximises the logarithm of a likelihood function

$\ln{\mathcal{L}}=\sum_{i=1}^{N}\ln{\left[f_{\rm Sig}\times F_{\rm
Sig}(x^{i})\times M_{\rm Sig}(m_{\rm ee}^{i})+(1-f_{\rm Sig})\times F_{\rm
Bkg}(x^{i})\times M_{\rm Bkg}(m_{\rm ee}^{i})\right]},$ (2)

where $N$ is the number of $\rm J/\psi$ candidates within the invariant mass
interval $2.72<m_{\rm ee}<3.40$ GeV/$c^{2}$ ($2.60<m_{\rm ee}<3.60$
GeV/$c^{2}$) in the centrality interval 0–10% (10–90%). A tighter invariant
mass window is considered in most central collisions in order to increase the
signal-to-background ratio in the fitting region, but still with a large
enough sample of candidates to constrain the background probability density
functions (PDFs). The relative amount of signal candidates, both prompt and
non-prompt $\rm J/\psi$, with respect to the total number of candidates is
quantified by the fit parameter $f_{\rm Sig}$. The PDFs entering in Eq. 2,
namely $F_{\rm Sig}(x)$ and $F_{\rm Bkg}(x)$ ($M_{\rm Sig}(x)$ and $M_{\rm
Bkg}(x)$), are used to describe the pseudoproper decay length (invariant mass)
distributions of signal and background, respectively. The pseudoproper decay
length PDF of the signal is defined as

$F_{\rm Sig}(x)=f^{\prime}_{\rm B}\times F_{\rm B}(x)+(1-f^{\prime}_{\rm
B})\times F_{\rm prompt}(x),$ (3)

where $F_{\rm B}(x)$ and $F_{\rm prompt}(x)$ are the $x$ PDFs for non-prompt
and prompt $\rm J/\psi$, respectively, while $f^{\prime}_{\rm B}$ represents
the fraction of $\rm J/\psi$ originating from beauty-hadron decays in the
sample of selected dielectron candidates. Both $f^{\prime}_{\rm B}$ and
$f_{\rm Sig}$ are left as free parameters in the fitting procedure. A
correction to the $f^{\prime}_{\rm B}$ fraction obtained from the fit is
applied to take into account the different average acceptance-times-
efficiencies of prompt and non-prompt $\rm J/\psi$, which is a consequence of
two effects: (i) different $\rm J/\psi$ $p_{\rm T}$ distributions inside the
wide $p_{\rm T}$ intervals where the measurements are provided; (ii)
different $\rm J/\psi$ polarisation, which can modify angular distributions of
decay products and thus the $\rm J/\psi$ acceptance. The corrected fraction of
non-prompt $\rm J/\psi$, $f_{\rm B}$, is obtained as

$f_{\rm B}=\left(1+\frac{1-f^{\prime}_{\rm B}}{f^{\prime}_{\rm
B}}\times\frac{\langle A\times\epsilon\rangle_{\rm
B~{}~{}~{}~{}~{}~{}}}{\langle A\times\epsilon\rangle_{\rm
prompt}}\right)^{-1},$ (4)

where $\langle A\times\epsilon\rangle_{\rm prompt}$ and $\langle
A\times\epsilon\rangle_{\rm B}$ represent the average acceptance-times-
efficiency values for prompt and non-prompt $\rm J/\psi$, respectively, in the
considered $p_{\rm T}$ interval. The functional forms of the different PDFs in
Eq. 2 are determined either based on data or on Monte Carlo (MC) simulations,
and are computed using the same procedures as in previous analyses [54, 53,
65, 66]. The PDFs corresponding to the signal component, namely $F_{\rm
prompt}(x)$, $F_{\rm B}(x)$, and $M_{\rm Sig}(m_{\rm ee})$, as well as
acceptance-times-efficiency corrections of prompt and non-prompt $\rm J/\psi$
in Eq. 4, are determined from MC simulations. These simulations consist of
prompt and non-prompt $\rm J/\psi$ meson signals embedded in a background
sample of Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV produced
with HIJING [69]. The intervals of centrality for the Pb–Pb collisions
considered in MC simulations are the same as those selected in experimental
data. The prompt $\rm J/\psi$ component is simulated with a $p_{\rm T}$
spectrum based on existing inclusive $\rm J/\psi$ Pb–Pb measurements at
midrapidity, while PYTHIA 6.4 [70] is used to generate beauty hadrons for non-
prompt $\rm J/\psi$ simulations. The decays of beauty hadrons into final
states containing a $\rm J/\psi$ meson are handled by the EvtGen [71] package,
while the $\rm J/\psi$ decay into the dielectron channel is performed using
the EvtGen package coupled with the PHOTOS model [72] for the treatment of
radiative decays ($\rm J/\psi\rightarrow e^{+}e^{-}\gamma$). Prompt $\rm
J/\psi$ are assumed to be unpolarised, while for the non-prompt $\rm J/\psi$ a
small residual polarisation as predicted by EvtGen [71] is considered. No
further assumptions on the polarisation of both components are accounted,
considering that existing measurements indicate small or no polarisation [73,
74]. The particle transport through the ALICE apparatus is handled by GEANT3
[75], considering a detailed description of the detector material and
geometry. Detector responses and calibrations in MC simulations are tuned to
data, taking into account time-dependent running conditions of all detectors
included in the data acquisition.

The $p_{\rm T}$ spectrum of prompt $\rm J/\psi$ in simulations is tuned to
match experimentally observed distributions, taking into account the
centrality dependence. In particular, the fits to measured inclusive $\rm
J/\psi$ yields from earlier publications [31, 28] are considered. To propagate
the associated experimental uncertainties to the systematic uncertainties on
acceptance-times-efficiency, all possible variations of the $p_{\rm T}$ shape
within the envelope obtained by varying the fitting parameters according to
their uncertainties are also considered. For non-prompt $\rm J/\psi$,
different hypotheses are considered for the $p_{\rm T}$ distributions,
including or excluding shadowing or suppression effects predicted by model
calculations, such as those discussed in Sec. 4. Taking into account all
hypotheses discussed above for prompt and non-prompt $\rm J/\psi$ $p_{\rm T}$
spectra, an average correction factor for $f^{\prime}_{\rm B}$ is evaluated.
As the acceptance-times-efficiency corrections are weakly dependent on $p_{\rm
T}$, the resulting correction applied on $f^{\prime}_{\rm B}$ according to Eq.
4 is small, being $\sim$5% for the $p_{\rm T}$ integrated case, while for the
different $p_{\rm T}$ intervals it ranges between 1% to 3%, depending on the
width of the interval.

The resolution function, $F_{\rm prompt}(x)$ in Eq. 3, defines the accuracy of
$x$ in the reconstruction, and affects all different PDFs related to the
pseudoproper decay length. It is described by the sum of two Gaussians and a
symmetric power law function. It is determined as a function of both $p_{\rm
T}$ and centrality from MC simulations. A tuning procedure is applied in MC
simulations to minimise the residual discrepancy with respect to data in the
average distance of closest approach (DCA) of the track to the reconstructed
interaction vertex in a plane perpendicular to the beam direction. A small
centrality dependence is found for the $x$ resolution, in particular the RMS
of the resolution function changes by about 5% across different centrality
classes, getting worse towards more central collisions. For the non-prompt
$\rm J/\psi$, the pseudoproper decay length distribution $F_{\rm B}(x)$ is
modelled by the kinematic distribution of $\rm J/\psi$ from beauty-hadron
decays obtained from the MC simulation described above, and convoluted with
the resolution function. Finally, MC simulations are also employed to
determine the shape of the invariant mass signal $M_{\rm Sig}(m_{\rm ee})$,
which is parametrised using a Crystal Ball function [76]. Background PDFs, for
both invariant mass and pseudoproper decay length distributions, are built
from data. The invariant mass background shape $M_{\rm Bkg}(m_{\rm ee})$,
parametrised by a third order polynomial function, is estimated using the
event-mixing technique, already used for the inclusive $\rm J/\psi$ analysis
at midrapidity [31], which also takes into account the residual background
originating from correlated semileptonic decays of heavy-flavour hadrons.

Figure 1: Invariant mass (left panel) and pseudoproper decay length (right
panel) distributions of $\rm J/\psi$ candidates with maximum likelihood fit
projections superimposed. The distributions in the figures correspond to
selected candidates with $1.5<p_{\rm T}<3.0$ GeV/$c$ in the centrality class
30–50%. The pseudoproper decay length distribution is shown for $\rm J/\psi$
candidates reconstructed under the $\rm J/\psi$ mass peak, i.e. for
$2.92<m_{\rm ee}<3.16$ GeV/$c^{2}$, for display purposes only. The $\chi^{2}$
values, obtained by comparing the binned distributions of data points and the
corresponding projections of the total fit function, are also reported.  Table
1:  Invariant mass and $p_{\rm T}$ intervals considered for the definition of
$F_{\rm Bkg}(x)$ in different centrality classes (see text for details).

Centrality class |  $m_{\rm ee}$ sidebands (GeV/$c^{2}$) |  $p_{\rm T}$ intervals (GeV/$c$)
---|---|---
0–10% | 2.72$-$2.8, 2.8$-$2.9, 3.2$-$3.3, 3.3$-$3.4 | 1.5$-$3, 3$-$5, 5$-$7, 7$-$10
10–30%,30–50%,50–90% | 2.64$-$2.75, 2.75$-$2.85, 3.2$-$3.35, 3.35$-$3.52 | 1.5$-$3, 3$-$5, 5$-$10

For the pseudoproper decay length background function, $F_{\rm Bkg}(x)$, the
same functional form and strategy described in Ref. [54] is used. The function
is determined for each centrality class by a fit to the data in four invariant
mass regions on the sidebands of the $\rm J/\psi$ mass peak and in different
$p_{\rm T}$ intervals, as summarised in Table 1. In each $p_{\rm T}$ interval,
the $x$ background function in the invariant mass region which contains the
nominal $\rm J/\psi$ mass value is obtained by an interpolation procedure as
the weighted combination of the PDFs determined in the other four invariant
mass regions. The weights are chosen inversely proportional to the absolute or
squared difference between the mean of the invariant mass distribution in the
given mass interval and that in the interpolated region. Both hypotheses for
the weights are considered for the study of the systematic uncertainty on the
pseudoproper decay length background PDF. Additionally, the internal edges
that define the invariant mass windows in Table 1 are shifted by $\pm$ 20
MeV/$c$, either in the same or opposite directions, and the interpolation
procedure inside the signal region is repeated. For each $p_{\rm T}$ interval,
a total of 9 (variations of mass intervals) $\times$ 2 (linear or quadratic
weights) = 18 attempts are obtained for $F_{\rm Bkg}(x)$, which are used in
turn in the unbinned likelihood fit procedure to determine $f^{\prime}_{\rm
B}$. As the choice of a specific definition of mass intervals is in principle
arbitrary, the central value of $f^{\prime}_{\rm B}$ is computed considering
the average of all the different attempts. Figure 1 shows an example of
invariant mass (left panel) and pseudoproper decay length (right panel)
distributions, corresponding to the centrality class 30–50% and transverse
momentum range $1.5<p_{\rm T}<3.0$ GeV/$c$, with superimposed projections of
the total maximum likelihood fit functions. The non-prompt $\rm J/\psi$
fraction is measured in four (three) $p_{\rm T}$ intervals in the centrality
class 0–10% (10–30% and 30–50%), as well as in the $p_{\rm T}$ integrated case
($1.5<p_{\rm T}<10$ GeV/$c$) in the centrality classes 0–10%, 10–30%, 30–50%,
and 50–90%.

#### Systematic uncertainties

Table 2: Systematic uncertainties on $f_{\rm B}$, expressed in %, for the
$p_{\rm T}$ integrated case, as well as for the lowest and the highest $p_{\rm
T}$ interval in each centrality class.

| Cent. 0–10% | Cent. 10–30% | Cent. 30–50% | Cent. 50–90%
---|---|---|---|---
$p_{\rm T}$ (GeV/$c$) | 1.5–10 | 1.5–3 | 7–10 | 1.5–10 | 1.5 | 5–10 | 1.5–10 | 1.5–3 | 5–10 | 1.5–10
Resolution function | 2.5 | 5.0 | 1.0 | 3.5 | 5.0 | 1.0 | 2.5 | 3.5 | 1.0 | 2.5
$x$ PDF of background | 11.0 | 15.0 | 5.0 | 6.0 | 14.0 | 5.0 | 5.0 | 8.0 | 3.0 | 4.0
MC $p_{\rm T}$ distribution | 6.0 | 1.5 | 3.0 | 6.0 | 1.5 | 4.0 | 6.0 | 1.5 | 3.0 | 6.0
$x$ PDF of non-prompt $\rm J/\psi$ | 2.0 | 2.0 | 1.5 | 2.0 | 4.0 | 1.0 | 2.0 | 2.5 | 1.0 | 3.0
$m_{\rm ee}$ PDF of signal | 0.5 | 1.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5
$m_{\rm ee}$ PDF of background | 0.5 | 2.5 | 0.5 | 1.0 | 2.5 | 0.5 | 0.5 | 1.5 | 0.5 | 0.5
Total | 13.0 | 16.3 | 6.1 | 9.6 | 15.3 | 6.6 | 8.5 | 9.3 | 4.5 | 8.2

The systematic uncertainties on the measured non-prompt $\rm J/\psi$ fractions
in different $p_{\rm T}$ intervals and centrality classes are summarised in
Table 2. Most of the contributions are due to the incomplete knowledge of the
different PDFs of $m_{\rm ee}$ and $x$ in the likelihood fit. An additional
contribution originates from the assumptions of the $p_{\rm T}$ distributions
of $\rm J/\psi$ in MC simulations.

The dominant uncertainty is represented by the PDF of the pseudoproper decay
length background, especially towards low $p_{\rm T}$ and more central
collisions. Other contributions which become dominant in some cases are those
originating from the resolution function, in particular in the lowest $p_{\rm
T}$ intervals of each centrality, and the assumptions of the $p_{\rm T}$
distributions of $\rm J/\psi$ used in simulations, the latter particularly
relevant for the $p_{\rm T}$ integrated case.

The uncertainty on the resolution function is computed by considering the
residual mismatch between data and MC simulations observed on the single track
DCA resolution after the tuning procedure. The RMS of the resolution function
is changed accordingly and the relative variation on $f_{\rm B}$ is taken as
systematic uncertainty. The corresponding values are found to be larger at low
$p_{\rm T}$ due to the worse pseudoproper decay length resolution and weakly
dependent on centrality.

The uncertainty due to the pseudoproper decay length background PDF is
estimated by computing the RMS of non-prompt $\rm J/\psi$ fraction values
obtained after changing the $F_{\rm Bkg}(x)$ in the likelihood fit,
considering the eighteen attempts previously mentioned, which depend on the
choice of the $m_{\rm ee}$ sidebands. The uncertainty on $f_{\rm B}$ due to
the $F_{\rm Bkg}(x)$ is the major contribution, especially at low-$p_{\rm T}$
and more central collisions where the signal-to-background ratio gets worse.

The systematic uncertainty related to the $p_{\rm T}$ distributions of prompt
and non-prompt $\rm J/\psi$ mesons in MC simulations, mainly affecting the
acceptance-times-efficiency correction on $f_{\rm B}$ according to Eq. 4, is
evaluated by varying the prompt and non-prompt $\rm J/\psi$ $p_{\rm T}$ shape
considering the variations previously discussed in this section. Taking into
account all combinations, an average correction factor for $f^{\prime}_{\rm
B}$ is evaluated, while the maximum variation with respect to the average
value is used to estimate the corresponding systematic uncertainty. This
contribution increases for wider $p_{\rm T}$ intervals, reaching about 6% for
the $p_{\rm T}$ integrated interval, and is relatively independent of
centrality.

To quantify the systematic uncertainty related to the shape of the $x$ PDF of
non-prompt $\rm J/\psi$, the $p_{\rm T}$ distribution of non-prompt $\rm
J/\psi$ is changed according to the same hypotheses considered for the
estimate of the systematic uncertainty on the $\langle A\times\epsilon\rangle$
correction on $f_{\rm B}$. Furthermore, the systematic uncertainty of the non-
prompt $\rm J/\psi$ $x$ PDF originating from the description of the $h_{\rm
b}\rightarrow\rm J/\psi+X$ decay kinematic, with $h_{\rm b}$ representing any
beauty mesons or baryons, is evaluated by considering PYTHIA 6.4 instead of
EvtGen for decaying beauty hadrons.

The uncertainty on the invariant mass PDF of the $\rm J/\psi$ signal is
evaluated by changing the width of the Crystal Ball function in order to vary
the fraction of candidates within the signal interval $2.92<m_{\rm ee}<3.16$
GeV/$c^{2}$ by $\pm$ 2.5%. The latter variation corresponds to the systematic
uncertainty on the MC signal shape assigned in the inclusive $\rm J/\psi$
analysis [31].

The uncertainty related to the invariant mass background PDF is evaluated by
taking the maximum variation obtained for $f_{\rm B}$ after using in the
likelihood fit procedure alternative functions, namely fourth and fifth order
polynomial functions, for fitting the event mixing based distribution used for
the determination of $M_{\rm Bkg}(x)$.

The overall systematic uncertainty on $f_{\rm B}$ reaches a maximum of about
16% in the lowest $p_{\rm T}$ interval and in 0–10% centrality class, mostly
as a consequence of both the increasing combinatorial background in more
central collisions and the worsening of the $x$ resolution at low transverse
momenta.

###  3.2 Non-prompt $\rm J/\psi$ fractions in pp collisions at $\sqrt{s}$ =
5.02 TeV

In pp collisions at $\sqrt{s}$ = 5.02 TeV, non-prompt $\rm J/\psi$ fractions
are measured at midrapidity by the ALICE collaboration [67] down to $p_{\rm
T}$ = 2 GeV/$c$. However, as the corresponding uncertainties are large and the
$p_{\rm T}$ intervals in pp collisions do not match those of the Pb–Pb
measurements, the $p_{\rm T}$-differential $f_{\rm B}$ fractions are obtained
via an interpolation procedure, already used in previous p–Pb and Pb–Pb
analyses [54, 53, 65, 66]. This procedure is based on available non-prompt
$\rm J/\psi$ fraction measurements in pp and p$\overline{\rm p}$ collisions at
midrapidity at several centre-of-mass energies, namely $\sqrt{s}$ = 1.96 TeV
(CDF [77]), 5.02 TeV (ALICE [67], CMS [78]), 7 TeV (ALICE [79], ATLAS [80,
81], CMS [82]) and 8 TeV (ATLAS [80]). In particular, using the semi-
phenomenological function described in Ref. [54], which employs FONLL to
describe the non-prompt $\rm J/\psi$ production cross section, the non-prompt
$\rm J/\psi$ fraction in pp collisions at $\sqrt{s}$ = 5.02 TeV ($f_{\rm
B}^{\rm pp}$) as a function of $p_{\rm T}$, needed for the computation of the
reference for prompt and non-prompt $\rm J/\psi$ $R_{\rm AA}$ measurements, is
derived via an energy interpolation. The average $f_{\rm B}^{\rm pp}$ in each
$p_{\rm T}$ interval considered in the Pb–Pb analysis is obtained by
reweighting the $p_{\rm T}$-differential $f_{\rm B}^{\rm pp}$ values by the
inclusive $p_{\rm T}$-differential $\rm J/\psi$ cross section in pp collisions
at $\sqrt{s}$ = 5.02 TeV [83].

Table 3: Fraction of non-prompt $\rm J/\psi$ with the corresponding
uncertainties in pp collisions at $\sqrt{s}$ = 5.02 TeV, obtained through the
interpolation procedure, in different $p_{\rm T}$ intervals (see text for
details).

$p_{\rm T}$ (GeV/$c$) |  $f_{\rm B}^{\rm pp}$ at $\sqrt{s}$ = 5.02 TeV
---|---
1.5–10 | 0.183 $\pm$ 0.004
1.5–3 | 0.110 $\pm$ 0.007
3–5 | 0.142 $\pm$ 0.004
5–7 | 0.190 $\pm$ 0.003
7–10 | 0.257 $\pm$ 0.005
5–10 | 0.227 $\pm$ 0.004

The values of $f_{\rm B}^{\rm pp}$ in the $p_{\rm T}$ intervals considered in
the Pb–Pb analysis are summarised in Table 3. The uncertainty, which amounts
to about 6.5% in the lowest $p_{\rm T}$ interval and decreases to about 1.5%
at higher $p_{\rm T}$, includes the contribution from experimental data and
FONLL predictions, as well as the systematic uncertainty due to the choice of
the functional form assumed for the energy interpolation (namely linear,
exponential, and power law function).

##  4 Results and discussion

###  4.1  Non-prompt $\rm J/\psi$ fractions and $\rm J/\psi$ yields

The non-prompt $\rm J/\psi$ fraction measured by the ALICE collaboration in
0–10% Pb–Pb collisions as a function of $p_{\rm T}$ in $|y|<0.9$ is shown in
the left hand panel of Fig. 2. It is compared with similar results obtained by
the ATLAS collaboration [29] at midrapidity, and available for $p_{\rm T}$
above 9.5 GeV/$c$. In the right hand panel, the $p_{\rm T}$-differential non-
prompt $\rm J/\psi$ fractions measured by the ALICE collaboration in different
centrality classes are compared with CMS results [30] available for $p_{\rm
T}$ $>$ 6.5 GeV/$c$ in the centrality class 0–100%. The ALICE results
complement the existing high-$p_{\rm T}$ measurements from ATLAS and CMS,
matching the decreasing trend observed from high towards low $p_{\rm T}$. The
results in the centrality interval 0–10% suggest a smaller $f_{\rm B}$
compared to other centralities, in particular at low transverse momentum. In
the left panel, non-prompt $\rm J/\psi$ fraction measurements in pp collisions
at $\sqrt{s}$ = 5.02 TeV obtained by the ALICE [67] and CMS [30]
collaborations are also shown for comparison, and exhibit a trend similar to
the one observed in Pb–Pb collisions. In the $p_{\rm T}$ range 10 to 20
GeV/$c$, the non-prompt $\rm J/\psi$ fractions are clearly higher in Pb–Pb
compared to pp collisions, possibly suggesting a stronger nuclear suppression
of prompt charmonia compared to beauty hadrons. On the other hand, at
low-$p_{\rm T}$ results in the two systems exhibit similar values within
uncertainties.

Figure 2: Non-prompt $\rm J/\psi$ fraction as a function of transverse
momentum measured by the ALICE collaboration in 0–10% most central Pb–Pb
collisions (left panel) and in all centrality classes (right panel). Results
in the left panel are compared with ATLAS midrapidity measurements [29] in the
centrality class 0–10%, and with ALICE [67] and CMS [30] measurements in pp
collisions at $\sqrt{s}$ = 5.02 TeV. The ALICE measurements in the right panel
are compared with similar midrapidity measurements from CMS [30], performed in
the centrality class 0–100%. In both panels, the error bars represent the
quadratic sum of statistical and systematic uncertainties.

Figure 3 presents the non-prompt $\rm J/\psi$ fraction as a function of
centrality, expressed in terms of the average number of participants $\langle
N_{\rm part}\rangle$, measured by ALICE in Pb–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV in the transverse momentum interval 1.5
$<$ $p_{\rm T}$ $<$ 10 GeV/$c$. Within uncertainties, no centrality dependence
is observed between peripheral and semicentral collisions, while the measured
$f_{\rm B}$ in 0–10% most central collisions decreases in comparison to an
average value computed by considering all other centralities with a
significance of about 2.5$\sigma$ considering both statistical and systematic
uncertainties. This is consistent with the observations for the $p_{\rm
T}$-dependent results shown in Fig. 2 and is compatible with the hypothesis of
a strong contribution of prompt $\rm J/\psi$ originating from regeneration,
which is expected to be larger in central compared to peripheral collisions.
Current results are compared with earlier ALICE measurements based on Pb–Pb
collisions at $\sqrt{s_{\mathrm{NN}}}$ = 2.76 TeV [54]. The statistical
precision is significantly improved thanks to the larger event sample
available from LHC Run 2. In the same figure, the $p_{\rm T}$-integrated non-
prompt $\rm J/\psi$ fraction in pp collisions at $\sqrt{s}$ = 5.02 TeV
obtained by the interpolation procedure described in Section 3.2 is also
shown. The corresponding value is found to be comparable with the non-prompt
$\rm J/\psi$ fractions measured in peripheral and semicentral Pb–Pb
collisions.

Figure 3: Centrality dependence (expressed in terms of average number of
participants) of the non-prompt $\rm J/\psi$ fraction measured by ALICE in
Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV in the transverse
momentum interval 1.5 $<$ $p_{\rm T}$ $<$ 10 GeV/$c$. Results are compared
with previous ALICE measurements performed in Pb–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}$ = 2.76 TeV [54]. The $p_{\rm T}$-integrated non-
prompt $\rm J/\psi$ fraction in pp collisions at $\sqrt{s}$ = 5.02 TeV
obtained from an interpolation procedure (see text for details) is also shown.
Statistical and systematic uncertainties are shown by error bars and boxes,
respectively.

The $p_{\rm T}$-differential production yields of prompt and non-prompt $\rm
J/\psi$ in a given centrality interval are computed by combining the non-
prompt $\rm J/\psi$ fractions with the measured yields of inclusive $\rm
J/\psi$ [31], ${\mathrm{d}N^{\rm incl.~{}\rm
J/\psi}/\mathrm{d}y\mathrm{d}p_{\rm T}}$, as

${\frac{\mathrm{d}N^{\rm J/\psi\leftarrow{\it h}_{\rm
B}}}{\mathrm{d}y\mathrm{d}p_{\rm T}}}=f_{\rm B}\times{\frac{\mathrm{d}N^{\rm
incl.~{}\rm J/\psi}}{\mathrm{d}y\mathrm{d}p_{\rm
T}}},~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}{\frac{\mathrm{d}N^{\rm
prompt~{}\rm J/\psi}}{\mathrm{d}y\mathrm{d}p_{\rm T}}}=(1-f_{\rm
B})\times{\frac{\mathrm{d}N^{\rm incl.~{}\rm
J/\psi}}{\mathrm{d}y\mathrm{d}p_{\rm T}}}.$ (5)

Figure 4 shows the $p_{\rm T}$-differential production yields of prompt and
non-prompt $\rm J/\psi$ in the centrality interval 0–10%. Statistical and
systematic uncertainties on prompt and non-prompt $\rm J/\psi$ yields are
evaluated by adding in quadrature the corresponding uncertainties on $f_{\rm
B}$ and inclusive $\rm J/\psi$ yields, the latter discussed in detail in Ref.
[31]. The statistical uncertainties of inclusive $\rm J/\psi$ yields vary from
about 5% to 10%, depending on the $p_{\rm T}$ and the centrality of the
collision. Regarding the systematic uncertainty of the inclusive $\rm J/\psi$
yield, it ranges within 10–12% (8–10%) in the centrality class 0–10% (30–50%)
and shows no significant $p_{\rm T}$ dependence. The measurements from ALICE
are compared with $p_{\rm T}$-differential production yields obtained by the
ATLAS collaboration [29], as well as with inclusive $\rm J/\psi$ measurements
performed by the ALICE collaboration [31]. As already observed for the non-
prompt $\rm J/\psi$ fraction, the ALICE measurements provide complementary
$p_{\rm T}$ coverage to ATLAS results, and they extend the measurement down to
$p_{\rm T}$ = 1.5 GeV/$c$. In addition, the ALICE and ATLAS results are
qualitatively compatible in the overlapping region and show similar slopes,
which result in an overall smooth trend over the full $p_{\rm T}$ range. Given
the relatively small non-prompt $\rm J/\psi$ fraction below 10 GeV/$c$, the
inclusive $\rm J/\psi$ yield and that of the prompt $\rm J/\psi$, both
measured by the ALICE collaboration, are found to be comparable. However, the
inclusive $\rm J/\psi$ yield is measured in finer $p_{\rm T}$ intervals and
subtends a wider range in $p_{\rm T}$.

Figure 4: Prompt and non-prompt $\rm J/\psi$ $p_{\rm T}$-differential
production yields measured by ALICE in the 0–10% centrality class at
midrapidity, compared with similar measurements from the ATLAS collaboration
[29] in the same centrality class. Inclusive $\rm J/\psi$ yields measured by
the ALICE collaboration in 0–10% [31] are shown for comparison. Error bars and
boxes represent statistical and systematic uncertainties, respectively.

###  4.2 $\rm J/\psi$ nuclear modification factors

The nuclear modification factor $R_{\rm AA}$ of prompt and non-prompt $\rm
J/\psi$ is obtained by combining the $R_{\rm AA}$ of inclusive $\rm J/\psi$
[31], with the non-prompt $\rm J/\psi$ fractions measured in Pb–Pb collisions
at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV normalised to those in pp collisions
obtained at the same centre-of-mass energy through the interpolation procedure
described in Section 3.2:

$R_{\rm AA}^{\rm J/\psi\leftarrow{\it h}_{\rm B}}=\frac{f_{\rm B}^{\rm Pb-
Pb}}{f_{\rm B}^{\rm pp}}\times R_{\rm AA}^{\rm inclusive~{}\rm
J/\psi},~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}~{}R_{\rm AA}^{\rm
prompt~{}\rm J/\psi}=\frac{1-f_{\rm B}^{\rm Pb-Pb}}{1-f_{\rm B}^{\rm
pp}}\times R_{\rm AA}^{\rm inclusive~{}\rm J/\psi}.$ (6)

Statistical and systematic uncertainties on prompt and non-prompt $\rm J/\psi$
$R_{\rm AA}$ are obtained by adding in quadrature the corresponding
uncertainties on inclusive $\rm J/\psi$ $R_{\rm AA}$ [31] and non-prompt $\rm
J/\psi$ fractions in Pb–Pb and in pp collisions, assuming all of them
uncorrelated from each other. Uncertainties on inclusive $\rm J/\psi$ $R_{\rm
AA}$, both statistical and systematic, include the corresponding contributions
due to inclusive $\rm J/\psi$ yields previously mentioned and inclusive $\rm
J/\psi$ cross section in pp collisions at $\sqrt{s}$ = 5.02 TeV [83], the
latter used as reference in the inclusive $\rm J/\psi$ $R_{\rm AA}$
computation. The statistical uncertainty on the pp reference cross section
increases with $p_{\rm T}$ from about 7% to 18%, while the systematic
uncertainty is poorly dependent on $p_{\rm T}$ and it amounts to about 6%. The
latter value do not include the normalisation uncertainty due to luminosity
determination, which is 2.2% and it is considered within the global
uncertainties when computing $R_{\rm AA}$.

Figure 5: Nuclear modification factor of prompt $\rm J/\psi$ as a function of
$p_{\rm T}$ in 0–10% (upper left panel), 10–30% (top right panel) and 30–50%
(bottom left panel) centrality classes. Results are compared with similar
measurements from the ATLAS [29] and CMS [30] collaborations. The centrality
dependent prompt $\rm J/\psi$ $R_{\rm AA}$ in 1.5 $<$ $p_{\rm T}$ $<$ 10
GeV/$c$ is shown in the bottom right panel (centrality is expressed in terms
of average number of participants). Error bars and boxes represent,
respectively, statistical and systematic uncertainties uncorrelated with
$p_{\rm T}$ (centrality, for the bottom right panel). Global uncertainties are
shown as boxes around unity.

Figure 6: Nuclear modification factor of non-prompt $\rm J/\psi$ as a function
of $p_{\rm T}$ in the 0–10% (upper left panel), 10–30% (top right panel) and
30–50% (bottom left panel). Results are compared with similar measurements
from the ATLAS [29] and CMS [30] collaborations. Results in 0–10% and 30–50%
are also compared to non-prompt D0 $R_{\rm AA}$ measurements [84] in the same
centrality classes. The centrality dependent non-prompt $\rm J/\psi$ $R_{\rm
AA}$ in 1.5 $<$ $p_{\rm T}$ $<$ 10 GeV/$c$ is shown in the bottom right panel
(centrality is expressed in terms of average number of participants). Error
bars and boxes represent statistical and systematic uncertainties uncorrelated
with $p_{\rm T}$ (centrality, for the bottom right panel). Global
uncertainties are shown as boxes around unity.

The $p_{\rm T}$-differential nuclear modification factor of prompt $\rm
J/\psi$ is shown in Fig. 5 in different centrality classes, namely 0–10% (top
left panel), 10–30% (top right panel) and 30–50% (bottom left panel). Global
uncertainties, shown as boxes around unity, include correlated uncertainties
on the pp reference due to normalisation as well as on the $\langle T_{\rm
AA}\rangle$ [31]. The latter uncertainty decreses with the collision
centrality, varying from 0.7% in 0–10% most central collisions to 2% in the
50–90% centrality class. The $R_{\rm AA}$ of prompt $\rm J/\psi$ in 1.5 $<$
$p_{\rm T}$ $<$ 10 GeV/$c$ and as a function of centrality is shown in the
bottom right panel of the same figure. The global uncertainty includes the
contributions from the inclusive $\rm J/\psi$ cross section and from $f_{\rm
B}^{\rm pp}$ in pp collisions, both integrated over $p_{\rm T}$ (1.5 $<$
$p_{\rm T}$ $<$ 10 GeV/$c$). For $p_{\rm T}$ $>$ 5 GeV/$c$, the prompt $\rm
J/\psi$ $R_{\rm AA}$ in the centrality classes 10–30% and 30–50% reaches a
value of about 0.4, while in 0–10% collisions it decreases to about 0.2,
indicating a stronger suppression. The prompt $\rm J/\psi$ $R_{\rm AA}$
increases towards low $p_{\rm T}$ and it exceeds unity in the lowest $p_{\rm
T}$ interval (1.5$-$3 GeV/$c$) of the 0–10% most central collisions. As a
consequence, the $p_{\rm T}$ integrated prompt $\rm J/\psi$ $R_{\rm AA}$ (1.5
$<$ $p_{\rm T}$ $<$ 10 GeV/$c$) also rises towards most central collisions, as
shown in the bottom right panel of Fig. 5. According to prompt $\rm J/\psi$
measurements performed by the ALICE collaboration in p–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV [53], the $R_{\rm pPb}$ is found to be
lower than unity within $1<p_{\rm T}<3$ GeV/$c$, suggesting significant CNM
effects at play in Pb–Pb collisions in this transverse momentum region, while
it becomes compatible with unity for $p_{\rm T}>3$ GeV/$c$. The results from
the ALICE collaboration are compared with similar measurements carried out by
the ATLAS [29] and CMS [30] collaborations in the rapidity intervals $|y|<2.0$
and $|y|<2.4$, respectively. In the centrality interval 0–10%, the results
from CMS and ATLAS are in good agreement with the ALICE measurements in the
overlapping $p_{\rm T}$ interval, while in semicentral collisions the
agreement is better with CMS than with ATLAS. It is worth noting that a
smaller suppression for ATLAS measurements is expected in semicentral events,
as the corresponding results use a significantly more peripheral collision
sample compared to ALICE and CMS.

Figure 6 shows the nuclear modification factor of non-prompt $\rm J/\psi$ as a
function of $p_{\rm T}$ in the same centrality classes discussed previously
for the prompt $\rm J/\psi$ $R_{\rm AA}$, namely 0–10%, 10–30% and 30–50%. The
boxes around unity represent global uncertainties due to the normalisation of
the pp reference cross section and $\langle T_{\rm AA}\rangle$. Unlike the
prompt $\rm J/\psi$ $R_{\rm AA}$, the $p_{\rm T}$-differential nuclear
modification factors of non-prompt $\rm J/\psi$ are similar in the different
centrality classes within experimental uncertainties below 5 GeV/$c$, while at
higher $p_{\rm T}$ the suppression is larger in 0–10% most central collisions.
The $p_{\rm T}$-integrated $R_{\rm AA}$ in the bottom right panel of Fig. 6
hints at a decreasing trend towards more central collisions, reaching an
$R_{\rm AA}$ value of about 0.6 in the 0–10% centrality class. In the case of
non-prompt $\rm J/\psi$, CNM effects are found to be small in the full
measured $p_{\rm T}$ interval, as non-prompt $\rm J/\psi$ $R_{\rm pPb}$
measurements at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV [53] are everywhere
compatible with unity, although uncertainties are large. Therefore, the
observed modification can be attributed to the QGP formation in Pb–Pb
collisions. Results as a function of $p_{\rm T}$ are shown together with non-
prompt $\rm J/\psi$ $R_{\rm AA}$ measurements from the ATLAS [29] and CMS [30]
collaborations, which are in good agreement with ALICE measurements in the
overlapping $p_{\rm T}$ region. In 0–10% most central collisions, the $R_{\rm
AA}$ from ALICE in the highest $p_{\rm T}$ interval shows a small tension of
about 1.4$\sigma$ and 2.5$\sigma$ with respect to ATLAS and CMS, respectively.
The non-prompt $\rm J/\psi$ $R_{\rm AA}$ measurements in 0–10% and 30–50%
centrality classes are also compared with non-prompt D0 results [84] measured
at midrapidity by the ALICE collaboration. The results are compatible within
uncertainties, despite possible differences that might originate from
different decay kinematics of beauty hadrons to $\rm J/\psi$ and D0.

###  4.3 Comparison with models for prompt $\rm J/\psi$ production

In the following, prompt $\rm J/\psi$ measurements are compared with different
phenomenological models in relativistic heavy-ion collisions.

Figure 7: Prompt $\rm J/\psi$ yields as a function of $p_{\rm T}$ in the 0–10%
(left panel) and 30–50% (right panel) centrality classes compared with models
[36, 37, 85]. Vertical error bars and boxes represent statistical and
systematic uncertainties, respectively. Shaded bands in the top panels
represent model uncertainties. Bottom panels show the ratios between models
and data, with the bands representing the relative uncertainties of the
models. Error bars around unity are the quadratic sum of statistical and
systematic uncertainties on the measured yields.

Figure 7 shows the $p_{\rm T}$-differential yields of prompt $\rm J/\psi$ in
the centrality classes 0–10% (left) and 30–50% (right), compared with
different models, namely the statistical hadronisation model (SHMc) by
Andronic et al. [36] and the Boltzmann transport model (BT) by Zhuang et al.
[37, 85]. The bottom panels present the ratio of models to data, with the
error bands representing the relative uncertainties originating from the
models. For the computation of the ratio, an average value of the model is
computed within the corresponding $p_{\rm T}$ intervals where the measurements
are performed. Error bars around unity are the sum in quadrature of
statistical and systematic uncertainties on the measured yields. In the SHMc
model, the totality of charm quarks are produced in the initial hard
parton–parton scatterings and thermalise inside the QGP. The total charm cross
section employed in the SHMc calculations is the one measured by the ALICE
collaboration in Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV,
extracted from open-charm meson production measurements [84]. Effects from CNM
are taken into account when calculating the total number of charm quarks in
Pb–Pb using rapidity dependent measurements of the nuclear modification factor
of D mesons in proton–nucleus collisions [86], where interpolations, if
necessary, are done via model calculations. The yield of the different bound
states is determined by thermal weights computed at a common chemical freeze-
out. The relative abundances of open and hidden charm hadrons are determined
using the equilibrium thermodynamical parameters obtained from fits to the
measured yields of light-flavoured hadrons and D-mesons, with the latter being
used to extract the charm fugacity. The spectra in the SHMc model are obtained
by coupling the hadron yields with a modified blast-wave function with input
from hydrodynamical calculations for the flow profiles [36]. In the BT model,
the total charm cross section in Pb–Pb collisions is evaluated from the charm-
production cross section measured in pp collisions [87] scaled by the number
of binary collisions, while to estimate CNM effects the EPS09 [88] gluon
distributions are used. The dynamical evolution of the prompt charmonium
states in the hot medium is described with a Boltzmann-type transport
equation, including terms of dissociation and regeneration. The dissociation
of charmonia inside the medium arises from the melting of the bound states due
to colour Debye screening, as well as from collisional processes of charmonia
with the medium constituents, and in particular from gluon dissociation. The
regeneration cross section is connected to the dissociation cross section via
the detailed balance between the gluon dissociation and reversed process. The
model employs the (2+1)-dimensional version of the ideal hydrodynamic
equations, including both a deconfined and a hadronic phase with a first order
phase transition between these two. The uncertainties plotted in Fig. 7 for
all models include contributions from total $\rm c\overline{\rm c}$ cross
section, as well as uncertainties from CNM assumptions. Both SHMc and BT
models show an overall good agreement with data within uncertainties, in
particular for $p_{\rm T}$ below 5 GeV/$c$. At higher $p_{\rm T}$, both models
tend to underpredict the data, with the SHMc model showing a larger
discrepancy, which is mainly due to the fact that in the SHMc model most of
the produced $\rm J/\psi$ yields are thermal, with only a small contribution
from the collision corona.

Figure 8: Prompt $\rm J/\psi$ $R_{\rm AA}$ as a function of $p_{\rm T}$ in the
0–10% (left panel) and 30–50% (right panel) centrality classes compared with
models [36, 89, 90, 37, 85]. Error bars and boxes represent statistical and
uncorrelated systematic uncertainties, respectively. Shaded bands represent
model uncertainties. The global uncertainty is shown around unity.  Figure 9:
Centrality dependence (expressed in terms of average number of participants)
of prompt $\rm J/\psi$ $R_{\rm AA}$ measured by ALICE in Pb–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV in the transverse momentum interval 1.5
$<$ $p_{\rm T}$ $<$ 10 GeV/$c$. Results are compared with the BT model by
Zhuang et al. [37, 85]. Error bars and boxes represent statistical and
uncorrelated systematic uncertainties, respectively. Shaded bands represent
model uncertainties. The global uncertainty is shown around unity.

Figure 8 presents the prompt $\rm J/\psi$ nuclear modification factor as a
function of $p_{\rm T}$ in the centrality class 0–10% (left panel) and 30–50%
(right panel) compared with model calculations. In addition to the SHMc and BT
models, prompt $\rm J/\psi$ $R_{\rm AA}$ measurements are also compared with
the dissociation model by Vitev et al. [89]. In this model, which employs rate
equations, the collisional dissociation of charmonia includes thermal effects
on the wave function due to the screening of the ${\rm c}\overline{\rm c}$
attractive potential from the free colour charges in the QGP. The medium is
modelled by a (2+1)-dimensional viscous hydrodynamic model. Non-relativistic
quantum chromodynamics (NRQCD) theory [91] is used to obtain the baseline
nucleon–nucleon cross sections for charmonia and the $p_{\rm T}$-dependent
feed-down from excited states. As this model provides predictions for $p_{\rm
T}$ $>$ 5 GeV/$c$, the contribution from CNM effects is assumed to be
negligible. The SHMc model reproduces the prompt $\rm J/\psi$ $R_{\rm AA}$
results at low $p_{\rm T}$ in both centrality classes, while it is
significantly below the data for $p_{\rm T}$ $>$ 5 GeV/$c$. The BT model
provides a good description of the measurements in the full $p_{\rm T}$ range
in 0–10% most central collisions, while the model underpredicts the data in
the centrality class 30–50%. The dissociation model, available only above 5
GeV/$c$, provides a good description of prompt $\rm J/\psi$ $R_{\rm AA}$
measurements within uncertainties.

The centrality dependence of the $p_{\rm T}$-integrated ($1.5<p_{\rm T}<10$
GeV/$c$) $R_{\rm AA}$ of prompt $\rm J/\psi$ is compared with calculations
from BT model in Fig. 9. The BT model, which shows a rising trend with
increasing number of participants from $\langle N_{\rm part}\rangle\sim 50$,
is in good agreement with experimental results in 0–10% and 10–30% centrality
classes. Below $\langle N_{\rm part}\rangle\sim 50$, both the data and the
model exhibit a similar increasing trend towards more peripheral collisions,
however the agreement between data and model worsens.

###  4.4 Comparison with models for non-prompt $\rm J/\psi$ production

In the following, the comparison of non-prompt $\rm J/\psi$ measurements with
models describing open heavy-flavour production is discussed. As both the
production mechanisms and the interaction with the medium are significantly
different for prompt charmonia and open heavy-flavour hadrons, non-prompt $\rm
J/\psi$ measurements are compared with a different set of models with respect
to those considered for prompt $\rm J/\psi$ results.

Figure 10: Non-prompt $\rm J/\psi$ yields as a function of $p_{\rm T}$ in the
0–10% (left panel) and 30–50% (right panel) centrality classes compared with
models [92, 93, 94, 95, 96]. Vertical error bars and boxes represent
statistical and systematic uncertainties, respectively. Shaded bands in the
top panels represent model uncertainties where applicable. Bottom panels show
the ratios between models and data, with the bands representing the relative
uncertainties from the models. Error bars around unity are the quadratic sum
of statistical and systematic uncertainties on the measured yields.

In Fig. 10, the yields of non-prompt $\rm J/\psi$ measured in the centralities
0–10% (left panel) and 30–50% (right panel), are compared with partonic
transport model calculations [92, 95, 96, 93, 94]. The ratios of the models to
data are depicted in the bottom panels, where the error bands are the model
uncertainties. For computing the ratio, an average value of the model is
considered within the corresponding $p_{\rm T}$ intervals where the
measurements are performed. Error bars around unity are the quadratic sum of
statistical and systematic uncertainties on the measured yields. In the
transport model by Chen et al. [92] (LT1), as well as in the POWLANG transport
model by Monteno et al. [93, 94], the Langevin equation is used for describing
the evolution of the ancestor beauty quarks through the QGP. In POWLANG,
transport coefficients are obtained either through perturbative calculations
using the hard thermal loop (HTL) approach or calculations based on lattice
QCD (LatQCD) simulations. The medium expansion is described by ideal
(2+1)-dimensional hydrodynamic equations in LT1. In POWLANG, the background
medium description is done via a (3+1)-dimensional hydrodynamic model,
assuming no invariance for longitudinal boosts as considered in the
(2+1)-dimensional case. The initial distribution of bottom quarks is
parametrised according to perturbative-QCD calculations at fixed order with
next-to-leading-log resummation (FONLL) [97] in LT1 and with the POWHEG-BOX
package [98] in POWLANG. In both models, CNM effects are accounted for by
using the EPS09 [88] gluon parton distribution functions, and at the
hadronisation hypersurface, bottom and light-flavour quarks hadronise into
beauty mesons via the coalescence model. In LT1, medium-induced gluon
radiation is also included in the energy loss of heavy quarks, and becomes the
dominant mechanism at large momentum, while in POWLANG the interactions of the
heavy quarks with the medium constituents happen solely via collisional
processes. In the calculations by Shi et al. [95, 96], the CUJET3.1 framework
is used to evaluate the jet energy loss in a (2+1)-dimensional hydrodynamic
background, implementing the contributions from collisional as well as from
radiative processes. A set of $R_{\rm AA}$ and elliptic flow results from
light hadrons in central and semicentral heavy-ion collisions is used to
constrain the model, which is then used to predict heavy-flavour observables.
For the initial $p_{\rm T}$ distribution of beauty quarks, FONLL calculations
[97] with CTEQ6M [99] parton distribution functions are used. The formation of
beauty hadrons happens via the classical vacuum-like fragmentation using the
Peterson parametrisation in Ref. [100]. The LT1 and POWLANG models show
systematically higher values compared to data, for both centrality classes in
the full measured transverse momentum range. The discrepancy looks larger for
POWLANG, especially in centrality class 0–10% and at higher $p_{\rm T}$, which
could be related to the absence of radiative processes in this model. The
CUJET3.1 model, available only for $p_{\rm T}$ above 5 GeV/$c$, is compatible
with the data within uncertainties.

Figure 11: Non-prompt $\rm J/\psi$ $R_{\rm AA}$ as a function of $p_{\rm T}$
in the 0–10% (left panel) and 30–50% (right panel) centrality classes compared
with models [92, 101, 102, 95, 96, 103, 104]. Error bars and boxes represent
statistical and uncorrelated systematic uncertainties, respectively. Shaded
bands represent model uncertainties where applicable. The global uncertainty
is shown around unity.  Figure 12: Centrality dependence (expressed in terms
of average number of participants) of non-prompt $\rm J/\psi$ $R_{\rm AA}$
measured by ALICE in Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV
in the transverse momentum interval 1.5 $<$ $p_{\rm T}$ $<$ 10 GeV/$c$.
Results are compared with several partonic transport models [92]. Error bars
and boxes represent statistical and uncorrelated systematic uncertainties,
respectively. Shaded bands represent model uncertainties where applicable. The
global uncertainty is shown around unity

The nuclear modification factor of non-prompt $\rm J/\psi$ is compared with
models in Fig. 11 in 0–10% (left panel) and 30–50% (right panel) centrality
intervals. The results are compared with the LT1, CUJET3.1, and POWLANG models
previously described as well as with additional ones [101, 102, 103, 104]. In
these additional calculations, the space–time evolution of the QGP is
simulated using a (3+1)-dimensional viscous hydrodynamic model and both
collisional and radiative energy loss mechanisms inside a thermal medium are
considered. In the calculation by Li et al. [101], marked as LT2, the
interactions between heavy quarks and the QGP are described by an improved
Langevin approach. The transport model by Xing et al. [102] employs an
extended linear Boltzmann transport (LBT) equation, which includes both short
and long-range interactions of heavy quarks with the QGP. In both LT2 and LBT
models, the initial heavy quark $p_{\rm T}$ distribution is simulated
according to FONLL calculations using CT14NLO [105] parton distribution
functions modified according to the EPPS16 [106] next-to-leading-order
parametrisation, while beauty hadrons are produced through a hybrid
fragmentation–coalescence model [107]. The calculation by Djordjevic et al.
[103, 104] employs a framework (DREENA-A) which combines the state-of-the-art
dynamical energy loss model with hydrodynamical simulations. The initial
heavy-quark spectrum is computed using next-to-leading-order calculations
described in Ref. [108] and KLP [109] fragmentation functions are used for the
formation of beauty mesons. In both centralities all available model
predictions except POWLANG show compatible values for $p_{\rm T}$ above 5
GeV/$c$, and within uncertainties are in an overall good agreement with the
data. The POWLANG model overpredicts the $R_{\rm AA}$ in the centrality class
0–10% and at high $p_{\rm T}$, which might be a consequence of the lack of
radiative energy loss contributions in this model. Below 5 GeV/$c$, the LT1
and POWLANG models sit on the upper side of the data points in both centrality
classes, still being compatible with them within uncertainties. Both LBT and
LT2 models are compatible with the measured $R_{\rm AA}$ within uncertainties
in the full measured $p_{\rm T}$ range, and in both centrality classes.

Figure 12 depicts the non-prompt $\rm J/\psi$ $R_{\rm AA}$, integrated over
$p_{\rm T}$ in the interval 1.5 $<$ $p_{\rm T}$ $<$ 10 GeV/$c$, as a function
of the number of participants in comparison with transport models. The LT1
model shows a slightly decreasing trend moving towards central collisions, and
is compatible with data within uncertainties for all centrality classes. The
LBT and LT2 models predict a similar decreasing trend for the non-prompt $\rm
J/\psi$ $R_{\rm AA}$ towards larger $\langle N_{\rm part}\rangle$. Both models
show good agreement with $R_{\rm AA}$ results in 0–10% most centrality class,
while for other centrality classes both models slightly underpredict the data.

##  5 Summary

Prompt and non-prompt $\rm J/\psi$ production is measured by the ALICE
collaboration in Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV in
the rapidity interval $|y|<0.9$ as a function of $p_{\rm T}$ and centrality.
In particular, $p_{\rm T}$-differential measurements of non-prompt $\rm
J/\psi$ fractions, production yields, and nuclear modification factors are
carried out. The ALICE results extend the existing CMS and ATLAS measurements
at midrapidity, available only at high $p_{\rm T}$, down to $p_{\rm T}$ = 1.5
GeV/$c$, and all measurements look compatible within uncertainties in the
common $p_{\rm T}$ intervals. Non-prompt $\rm J/\psi$ fractions show a rising
trend with increasing $p_{\rm T}$, similar to the one observed in pp
collisions, while no significant dependence on the centrality is observed
within uncertainties, with the exception of most central collisions where
$f_{\rm B}$ exhibits a significant decrease with respect to other centrality
classes. The comparison with earlier measurements in Pb–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}$ = 2.76 TeV shows compatible results at the two
centre-of-mass energies and highlights a significantly improved precision with
Run 2 data.

For $p_{\rm T}$ $>$ 5 GeV/$c$, the prompt $\rm J/\psi$ $R_{\rm AA}$ decreases
with increasing centrality, while at lower $p_{\rm T}$ the suppression is
smaller in 0–10% most central collisions, in particular in the lowest $p_{\rm
T}$ interval where the prompt $\rm J/\psi$ $R_{\rm AA}$ exceeds unity. These
results are consistent with $p_{\rm T}$-integrated measurements of prompt $\rm
J/\psi$ $R_{\rm AA}$, which rises with $\langle N_{\rm part}\rangle$, hinting
at an increasing contribution from regeneration at low $p_{\rm T}$ and more
central collisions. In 0–10% most central collisions, the SHMc model and
transport microscopic calculations that include a contribution from
regeneration are compatible with experimental data for $p_{\rm T}<5$ GeV/$c$.
However, at higher $p_{\rm T}$, transport models are compatible with the
measurements within uncertainties, while the SHMc model significantly
underpredicts the data. In semicentral collisions there is less agreement
between data and models. In particular, for $p_{\rm T}$ above 3 GeV/$c$ the
models either underpredict the data or sit at the lower edge of the
experimental uncertainty.

The non-prompt $\rm J/\psi$ $R_{\rm AA}$ integrated over $p_{\rm T}$ hints at
a decreasing trend towards more central collisions. As a function of $p_{\rm
T}$, the non-prompt $\rm J/\psi$ $R_{\rm AA}$ in different centrality classes
are compatible within uncertainties below 5 GeV/$c$, while at higher $p_{\rm
T}$ the suppression is larger in the centrality interval 0–10%. Results are
consistent within uncertainties with non-prompt ${\rm D}^{\rm 0}$ $R_{\rm AA}$
measurements in the centrality classes 0–10% and 30–50%. Several transport
models are able to describe the data within uncertainties. All calculations,
but POWLANG, implement both collisional and radiative energy loss processes
combined with a dynamically expanding QGP, considering different hypotheses on
transport dynamics, CNM effects, $p_{\rm T}$ distributions and hadronisation
of beauty quarks. Above 5 GeV/$c$, all calculations predict a similar
suppression for non-prompt $\rm J/\psi$ and are consistent with the data
within uncertainties, with the exception of POWLANG, which overpredicts the
data in most central events. This points to the importance of radiative energy
loss contributions in the high-$p_{\rm T}$ region. At lower $p_{\rm T}$ and
for the $p_{\rm T}$-integrated case, theoretical calculations predict
different magnitudes of the suppression. However, due to the current precision
of the measurements it is not possible to discriminate among them as all
calculations are compatible with the data within uncertainties.

Both prompt and non-prompt $\rm J/\psi$ measurements will improve
significantly taking advantage of the larger expected data sample and the
better spatial resolution provided at midrapidity by the upgraded ITS [110] in
the next LHC runs. In particular, further differential measurements in the
non-prompt charmonium sector, in addition to yet unmeasured observables such
as the elliptic flow, could allow further constraining different open beauty
hadron production models.

## Acknowledgements

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; Bulgarian Ministry of Education and Science, within the National Roadmap for Research Infrastructures 2020-2027 (object CERN), Bulgaria; 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; National Research and Innovation Agency - BRIN, Indonesia; Istituto Nazionale di Fisica Nucleare (INFN), Italy; 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, Ministry of Research and Innovation and Institute of Atomic Physics and University Politehnica of Bucharest, Romania; 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 (NSTDA), Thailand Science Research and Innovation (TSRI) and National Science, Research and Innovation Fund (NSRF), 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. In addition, individual groups or members have received support from: European Research Council, Strong 2020 - Horizon 2020 (grant nos. 950692, 824093), European Union; Academy of Finland (Center of Excellence in Quark Matter) (grant nos. 346327, 346328), Finland.

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##  Appendix A The ALICE Collaboration

S. Acharya 126, D. Adamová 86, G. Aglieri Rinella 33, M. Agnello 30, N.
Agrawal 51, Z. Ahammed 134, S. Ahmad16, S.U. Ahn 71, I. Ahuja 38, A. Akindinov
142, M. Al-Turany 97, D. Aleksandrov 142, B. Alessandro 56, H.M. Alfanda 6, R.
Alfaro Molina 67, B. Ali 16, A. Alici 26, N. Alizadehvandchali 115, A. Alkin
33, J. Alme 21, G. Alocco 52, T. Alt 64, A.R. Altamura 50, I. Altsybeev 95,
M.N. Anaam 6, C. Andrei 46, N. Andreou 114, A. Andronic 137, V. Anguelov 94,
F. Antinori 54, P. Antonioli 51, N. Apadula 74, L. Aphecetche 103, H.
Appelshäuser 64, C. Arata 73, S. Arcelli 26, M. Aresti 23, R. Arnaldi 56,
J.G.M.C.A. Arneiro 110, I.C. Arsene 20, M. Arslandok 139, A. Augustinus 33, R.
Averbeck 97, M.D. Azmi16, H. Baba123, A. Badalà 53, J. Bae 104, Y.W. Baek 41,
X. Bai 119, R. Bailhache 64, Y. Bailung 48, A. Balbino 30, A. Baldisseri 129,
B. Balis 2, D. Banerjee 4, Z. Banoo 91, R. Barbera 27, F. Barile 32, L.
Barioglio 95, M. Barlou78, B. Barman42, G.G. Barnaföldi 138, L.S. Barnby 85,
V. Barret 126, L. Barreto 110, C. Bartels 118, K. Barth 33, E. Bartsch 64, N.
Bastid 126, S. Basu 75, G. Batigne 103, D. Battistini 95, B. Batyunya 143, D.
Bauri47, J.L. Bazo Alba 101, I.G. Bearden 83, C. Beattie 139, P. Becht 97, D.
Behera 48, I. Belikov 128, A.D.C. Bell Hechavarria 137, F. Bellini 26, R.
Bellwied 115, S. Belokurova 142, Y.A.V. Beltran 45, G. Bencedi 138, S. Beole
25, Y. Berdnikov 142, A. Berdnikova 94, L. Bergmann 94, M.G. Besoiu 63, L.
Betev 33, P.P. Bhaduri 134, A. Bhasin 91, M.A. Bhat 4, B. Bhattacharjee 42, L.
Bianchi 25, N. Bianchi 49, J. Bielčík 36, J. Bielčíková 86, J. Biernat 107,
A.P. Bigot 128, A. Bilandzic 95, G. Biro 138, S. Biswas 4, N. Bize 103, J.T.
Blair 108, D. Blau 142, M.B. Blidaru 97, N. Bluhme39, C. Blume 64, G. Boca
22,55, F. Bock 87, T. Bodova 21, A. Bogdanov142, S. Boi 23, J. Bok 58, L.
Boldizsár 138, M. Bombara 38, P.M. Bond 33, G. Bonomi 133,55, H. Borel 129, A.
Borissov 142, A.G. Borquez Carcamo 94, H. Bossi 139, E. Botta 25, Y.E.M.
Bouziani 64, L. Bratrud 64, P. Braun-Munzinger 97, M. Bregant 110, M. Broz 36,
G.E. Bruno 96,32, M.D. Buckland 24, D. Budnikov 142, H. Buesching 64, S.
Bufalino 30, P. Buhler 102, N. Burmasov 142, Z. Buthelezi 68,122, A. Bylinkin
21, S.A. Bysiak107, M. Cai 6, H. Caines 139, A. Caliva 29, E. Calvo Villar
101, J.M.M. Camacho 109, P. Camerini 24, F.D.M. Canedo 110, M. Carabas 125,
A.A. Carballo 33, F. Carnesecchi 33, R. Caron 127, L.A.D. Carvalho 110, J.
Castillo Castellanos 129, F. Catalano 33,25, C. Ceballos Sanchez 143, I.
Chakaberia 74, P. Chakraborty 47, S. Chandra 134, S. Chapeland 33, M. Chartier
118, S. Chattopadhyay 134, S. Chattopadhyay 99, T.G. Chavez 45, T. Cheng 97,6,
C. Cheshkov 127, B. Cheynis 127, V. Chibante Barroso 33, D.D. Chinellato 111,
E.S. Chizzali I,95, J. Cho 58, S. Cho 58, P. Chochula 33, D. Choudhury42, P.
Christakoglou 84, C.H. Christensen 83, P. Christiansen 75, T. Chujo 124, M.
Ciacco 30, C. Cicalo 52, F. Cindolo 51, M.R. Ciupek97, G. ClaiII,51, F.
Colamaria 50, J.S. Colburn100, D. Colella 96,32, M. Colocci 26, M. Concas
III,33, G. Conesa Balbastre 73, Z. Conesa del Valle 130, G. Contin 24, J.G.
Contreras 36, M.L. Coquet 129, P. Cortese 132,56, M.R. Cosentino 112, F. Costa
33, S. Costanza 22,55, C. Cot 130, J. Crkovská 94, P. Crochet 126, R. Cruz-
Torres 74, P. Cui 6, A. Dainese 54, M.C. Danisch 94, A. Danu 63, P. Das 80, P.
Das 4, S. Das 4, A.R. Dash 137, S. Dash 47, R.M.H. David45, A. De Caro 29, G.
de Cataldo 50, J. de Cuveland39, A. De Falco 23, D. De Gruttola 29, N. De
Marco 56, C. De Martin 24, S. De Pasquale 29, R. Deb 133, R. Del Grande 95, L.
Dello Stritto 29, W. Deng 6, P. Dhankher 19, D. Di Bari 32, A. Di Mauro 33, B.
Diab 129, R.A. Diaz 143,7, T. Dietel 113, Y. Ding 6, J. Ditzel 64, R. Divià
33, D.U. Dixit 19, Ø. Djuvsland21, U. Dmitrieva 142, A. Dobrin 63, B. Dönigus
64, J.M. Dubinski 135, A. Dubla 97, S. Dudi 90, P. Dupieux 126, M. Durkac106,
N. Dzalaiova13, T.M. Eder 137, R.J. Ehlers 74, F. Eisenhut 64, R. Ejima92, D.
Elia 50, B. Erazmus 103, F. Ercolessi 26, B. Espagnon 130, G. Eulisse 33, D.
Evans 100, S. Evdokimov 142, L. Fabbietti 95, M. Faggin 28, J. Faivre 73, F.
Fan 6, W. Fan 74, A. Fantoni 49, M. Fasel 87, A. Feliciello 56, G. Feofilov
142, A. Fernández Téllez 45, L. Ferrandi 110, M.B. Ferrer 33, A. Ferrero 129,
C. Ferrero 56, A. Ferretti 25, V.J.G. Feuillard 94, V. Filova 36, D. Finogeev
142, F.M. Fionda 52, E. Flatland33, F. Flor 115, A.N. Flores 108, S. Foertsch
68, I. Fokin 94, S. Fokin 142, E. Fragiacomo 57, E. Frajna 138, U. Fuchs 33,
N. Funicello 29, C. Furget 73, A. Furs 142, T. Fusayasu 98, J.J. Gaardhøje 83,
M. Gagliardi 25, A.M. Gago 101, T. Gahlaut47, C.D. Galvan 109, D.R.
Gangadharan 115, P. Ganoti 78, C. Garabatos 97, A.T. Garcia 130, J.R.A. Garcia
45, E. Garcia-Solis 9, C. Gargiulo 33, P. Gasik 97, A. Gautam 117, M.B. Gay
Ducati 66, M. Germain 103, A. Ghimouz124, C. Ghosh134, M. Giacalone 51, G.
Gioachin 30, P. Giubellino 97,56, P. Giubilato 28, A.M.C. Glaenzer 129, P.
Glässel 94, E. Glimos 121, D.J.Q. Goh76, V. Gonzalez 136, P. Gordeev142, M.
Gorgon 2, K. Goswami 48, S. Gotovac34, V. Grabski 67, L.K. Graczykowski 135,
E. Grecka 86, A. Grelli 59, C. Grigoras 33, V. Grigoriev 142, S. Grigoryan
143,1, F. Grosa 33, J.F. Grosse-Oetringhaus 33, R. Grosso 97, D. Grund 36,
N.A. Grunwald94, G.G. Guardiano 111, R. Guernane 73, M. Guilbaud 103, K.
Gulbrandsen 83, T. Gündem 64, T. Gunji 123, W. Guo 6, A. Gupta 91, R. Gupta
91, R. Gupta 48, S.P. Guzman 45, K. Gwizdziel 135, L. Gyulai 138, C.
Hadjidakis 130, F.U. Haider 91, S. Haidlova 36, H. Hamagaki 76, A. Hamdi 74,
Y. Han 140, B.G. Hanley 136, R. Hannigan 108, J. Hansen 75, M.R. Haque 135,
J.W. Harris 139, A. Harton 9, H. Hassan 116, D. Hatzifotiadou 51, P. Hauer 43,
L.B. Havener 139, S.T. Heckel 95, E. Hellbär 97, H. Helstrup 35, M. Hemmer 64,
T. Herman 36, G. Herrera Corral 8, F. Herrmann137, S. Herrmann 127, K.F.
Hetland 35, B. Heybeck 64, H. Hillemanns 33, B. Hippolyte 128, F.W. Hoffmann
70, B. Hofman 59, G.H. Hong 140, M. Horst 95, A. Horzyk2, Y. Hou 6, P. Hristov
33, C. Hughes 121, P. Huhn64, L.M. Huhta 116, T.J. Humanic 88, A. Hutson 115,
D. Hutter 39, R. Ilkaev142, H. Ilyas 14, M. Inaba 124, G.M. Innocenti 33, M.
Ippolitov 142, A. Isakov 84,86, T. Isidori 117, M.S. Islam 99, M. Ivanov 97,
M. Ivanov13, V. Ivanov 142, K.E. Iversen 75, M. Jablonski 2, B. Jacak 74, N.
Jacazio 26, P.M. Jacobs 74, S. Jadlovska106, J. Jadlovsky106, S. Jaelani 82,
C. Jahnke 110, M.J. Jakubowska 135, M.A. Janik 135, T. Janson70, S. Ji 17, S.
Jia 10, A.A.P. Jimenez 65, F. Jonas 87, D.M. Jones 118, J.M. Jowett 33,97, J.
Jung 64, M. Jung 64, A. Junique 33, A. Jusko 100, M.J. Kabus 33,135, J.
Kaewjai105, P. Kalinak 60, A.S. Kalteyer 97, A. Kalweit 33, V. Kaplin 142, A.
Karasu Uysal 72, D. Karatovic 89, O. Karavichev 142, T. Karavicheva 142, P.
Karczmarczyk 135, E. Karpechev 142, U. Kebschull 70, R. Keidel 141, D.L.D.
Keijdener59, M. Keil 33, B. Ketzer 43, S.S. Khade 48, A.M. Khan 119, S. Khan
16, A. Khanzadeev 142, Y. Kharlov 142, A. Khatun 117, A. Khuntia 36, B. Kileng
35, B. Kim 104, C. Kim 17, D.J. Kim 116, E.J. Kim 69, J. Kim 140, J.S. Kim 41,
J. Kim 58, J. Kim69, M. Kim 19, S. Kim 18, T. Kim 140, K. Kimura 92, S. Kirsch
64, I. Kisel 39, S. Kiselev 142, A. Kisiel 135, J.P. Kitowski 2, J.L. Klay 5,
J. Klein 33, S. Klein 74, C. Klein-Bösing 137, M. Kleiner 64, T. Klemenz 95,
A. Kluge 33, A.G. Knospe 115, C. Kobdaj 105, T. Kollegger97, A. Kondratyev
143, N. Kondratyeva 142, E. Kondratyuk 142, J. Konig 64, S.A. Konigstorfer 95,
P.J. Konopka 33, G. Kornakov 135, S.D. Koryciak 2, A. Kotliarov 86, V.
Kovalenko 142, M. Kowalski 107, V. Kozhuharov 37, I. Králik 60, A. Kravčáková
38, L. Krcal 33,39, M. Krivda 100,60, F. Krizek 86, K. Krizkova Gajdosova 33,
M. Kroesen 94, M. Krüger 64, D.M. Krupova 36, E. Kryshen 142, V. Kučera 58, C.
Kuhn 128, P.G. Kuijer 84, T. Kumaoka124, D. Kumar134, L. Kumar 90, N. Kumar90,
S. Kumar 32, S. Kundu 33, P. Kurashvili 79, A. Kurepin 142, A.B. Kurepin 142,
A. Kuryakin 142, S. Kushpil 86, V. Kuskov142, M.J. Kweon 58, Y. Kwon 140, S.L.
La Pointe 39, P. La Rocca 27, A. Lakrathok105, M. Lamanna 33, R. Langoy 120,
P. Larionov 33, E. Laudi 33, L. Lautner 33,95, R. Lavicka 102, R. Lea 133,55,
H. Lee 104, I. Legrand 46, G. Legras 137, J. Lehrbach 39, T.M. Lelek2, R.C.
Lemmon 85, I. León Monzón 109, M.M. Lesch 95, E.D. Lesser 19, P. Lévai 138, X.
Li10, J. Lien 120, R. Lietava 100, I. Likmeta 115, B. Lim 25, S.H. Lim 17, V.
Lindenstruth 39, A. Lindner46, C. Lippmann 97, D.H. Liu 6, J. Liu 118, G.S.S.
Liveraro 111, I.M. Lofnes 21, C. Loizides 87, S. Lokos 107, J. Lomker 59, P.
Loncar 34, X. Lopez 126, E. López Torres 7, P. Lu 97,119, F.V. Lugo 67, J.R.
Luhder 137, M. Lunardon 28, G. Luparello 57, Y.G. Ma 40, M. Mager 33, A. Maire
128, M.V. Makariev 37, M. Malaev 142, G. Malfattore 26, N.M. Malik 91, Q.W.
Malik20, S.K. Malik 91, L. Malinina VI,143, D. Mallick 130,80, N. Mallick 48,
G. Mandaglio 31,53, S.K. Mandal 79, V. Manko 142, F. Manso 126, V. Manzari 50,
Y. Mao 6, R.W. Marcjan 2, G.V. Margagliotti 24, A. Margotti 51, A. Marín 97,
C. Markert 108, P. Martinengo 33, M.I. Martínez 45, G. Martínez García 103,
M.P.P. Martins 110, S. Masciocchi 97, M. Masera 25, A. Masoni 52, L.
Massacrier 130, O. Massen 59, A. Mastroserio 131,50, O. Matonoha 75, S.
Mattiazzo 28, A. Matyja 107, C. Mayer 107, A.L. Mazuecos 33, F. Mazzaschi 25,
M. Mazzilli 33, J.E. Mdhluli 122, Y. Melikyan 44, A. Menchaca-Rocha 67, J.E.M.
Mendez 65, E. Meninno 102,29, A.S. Menon 115, M. Meres 13, S. Mhlanga113,68,
Y. Miake124, L. Micheletti 33, D.L. Mihaylov 95, K. Mikhaylov 143,142, A.N.
Mishra 138, D. Miśkowiec 97, A. Modak 4, B. Mohanty80, M. Mohisin KhanIV,16,
M.A. Molander 44, S. Monira 135, C. Mordasini 116, D.A. Moreira De Godoy 137,
I. Morozov 142, A. Morsch 33, T. Mrnjavac 33, V. Muccifora 49, S. Muhuri 134,
J.D. Mulligan 74, A. Mulliri23, M.G. Munhoz 110, R.H. Munzer 64, H. Murakami
123, S. Murray 113, L. Musa 33, J. Musinsky 60, J.W. Myrcha 135, B. Naik 122,
A.I. Nambrath 19, B.K. Nandi 47, R. Nania 51, E. Nappi 50, A.F. Nassirpour 18,
A. Nath 94, C. Nattrass 121, M.N. Naydenov 37, A. Neagu20, A. Negru125, E.
Nekrasova142, L. Nellen 65, R. Nepeivoda 75, S. Nese 20, G. Neskovic 39, N.
Nicassio 50, B.S. Nielsen 83, E.G. Nielsen 83, S. Nikolaev 142, S. Nikulin
142, V. Nikulin 142, F. Noferini 51, S. Noh 12, P. Nomokonov 143, J. Norman
118, N. Novitzky 87, P. Nowakowski 135, A. Nyanin 142, J. Nystrand 21, M.
Ogino 76, S. Oh 18, A. Ohlson 75, V.A. Okorokov 142, J. Oleniacz 135, A.C.
Oliveira Da Silva 121, A. Onnerstad 116, C. Oppedisano 56, A. Ortiz Velasquez
65, J. Otwinowski 107, M. Oya92, K. Oyama 76, Y. Pachmayer 94, S. Padhan 47,
D. Pagano 133,55, G. Paić 65, A. Palasciano 50, S. Panebianco 129, H. Park
124, H. Park 104, J. Park 58, J.E. Parkkila 33, Y. Patley 47, R.N. Patra91, B.
Paul 23, H. Pei 6, T. Peitzmann 59, X. Peng 11, M. Pennisi 25, S. Perciballi
25, D. Peresunko 142, G.M. Perez 7, Y. Pestov142, V. Petrov 142, M. Petrovici
46, R.P. Pezzi 103,66, S. Piano 57, M. Pikna 13, P. Pillot 103, O. Pinazza
51,33, L. Pinsky115, C. Pinto 95, S. Pisano 49, M. Płoskoń 74, M. Planinic89,
F. Pliquett64, M.G. Poghosyan 87, B. Polichtchouk 142, S. Politano 30, N.
Poljak 89, A. Pop 46, S. Porteboeuf-Houssais 126, V. Pozdniakov 143, I.Y.
Pozos 45, K.K. Pradhan 48, S.K. Prasad 4, S. Prasad 48, R. Preghenella 51, F.
Prino 56, C.A. Pruneau 136, I. Pshenichnov 142, M. Puccio 33, S. Pucillo 25,
Z. Pugelova106, S. Qiu 84, L. Quaglia 25, S. Ragoni 15, A. Rai 139, A.
Rakotozafindrabe 129, L. Ramello 132,56, F. Rami 128, S.A.R. Ramirez 45, T.A.
Rancien73, M. Rasa 27, S.S. Räsänen 44, R. Rath 51, M.P. Rauch 21, I.
Ravasenga 84, K.F. Read 87,121, C. Reckziegel 112, A.R. Redelbach 39, K.
Redlich V,79, C.A. Reetz 97, A. Rehman21, F. Reidt 33, H.A. Reme-Ness 35, Z.
Rescakova38, K. Reygers 94, A. Riabov 142, V. Riabov 142, R. Ricci 29, M.
Richter 20, A.A. Riedel 95, W. Riegler 33, A.G. Riffero 25, C. Ristea 63, M.V.
Rodriguez 33, M. Rodríguez Cahuantzi 45, K. Røed 20, R. Rogalev 142, E.
Rogochaya 143, T.S. Rogoschinski 64, D. Rohr 33, D. Röhrich 21, P.F. Rojas45,
S. Rojas Torres 36, P.S. Rokita 135, G. Romanenko 26, F. Ronchetti 49, A.
Rosano 31,53, E.D. Rosas65, K. Roslon 135, A. Rossi 54, A. Roy 48, S. Roy 47,
N. Rubini 26, D. Ruggiano 135, R. Rui 24, P.G. Russek 2, R. Russo 84, A.
Rustamov 81, E. Ryabinkin 142, Y. Ryabov 142, A. Rybicki 107, H. Rytkonen 116,
J. Ryu 17, W. Rzesa 135, O.A.M. Saarimaki 44, S. Sadhu 32, S. Sadovsky 142, J.
Saetre 21, K. Šafařík 36, P. Saha42, S.K. Saha 4, S. Saha 80, B. Sahoo 47, B.
Sahoo 48, R. Sahoo 48, S. Sahoo61, D. Sahu 48, P.K. Sahu 61, J. Saini 134, K.
Sajdakova38, S. Sakai 124, M.P. Salvan 97, S. Sambyal 91, D. Samitz 102, I.
Sanna 33,95, T.B. Saramela110, P. Sarma 42, V. Sarritzu 23, V.M. Sarti 95,
M.H.P. Sas 33, S. Sawan80, J. Schambach 87, H.S. Scheid 64, C. Schiaua 46, R.
Schicker 94, F. Schlepper 94, A. Schmah97, C. Schmidt 97, H.R. Schmidt93, M.O.
Schmidt 33, M. Schmidt93, N.V. Schmidt 87, A.R. Schmier 121, R. Schotter 128,
A. Schröter 39, J. Schukraft 33, K. Schweda 97, G. Scioli 26, E. Scomparin 56,
J.E. Seger 15, Y. Sekiguchi123, D. Sekihata 123, M. Selina 84, I. Selyuzhenkov
97, S. Senyukov 128, J.J. Seo 94,58, D. Serebryakov 142, L. Šerkšnytė 95, A.
Sevcenco 63, T.J. Shaba 68, A. Shabetai 103, R. Shahoyan33, A. Shangaraev 142,
A. Sharma90, B. Sharma 91, D. Sharma 47, H. Sharma 54, M. Sharma 91, S. Sharma
76, S. Sharma 91, U. Sharma 91, A. Shatat 130, O. Sheibani115, K. Shigaki 92,
M. Shimomura77, J. Shin12, S. Shirinkin 142, Q. Shou 40, Y. Sibiriak 142, S.
Siddhanta 52, T. Siemiarczuk 79, T.F. Silva 110, D. Silvermyr 75, T.
Simantathammakul105, R. Simeonov 37, B. Singh91, B. Singh 95, K. Singh 48, R.
Singh 80, R. Singh 91, R. Singh 48, S. Singh 16, V.K. Singh 134, V. Singhal
134, T. Sinha 99, B. Sitar 13, M. Sitta 132,56, T.B. Skaali20, G. Skorodumovs
94, M. Slupecki 44, N. Smirnov 139, R.J.M. Snellings 59, E.H. Solheim 20, J.
Song 17, C. Sonnabend 33,97, F. Soramel 28, A.B. Soto-hernandez 88, R.
Spijkers 84, I. Sputowska 107, J. Staa 75, J. Stachel 94, I. Stan 63, P.J.
Steffanic 121, S.F. Stiefelmaier 94, D. Stocco 103, I. Storehaug 20, P.
Stratmann 137, S. Strazzi 26, A. Sturniolo 31,53, C.P. Stylianidis84, A.A.P.
Suaide 110, C. Suire 130, M. Sukhanov 142, M. Suljic 33, R. Sultanov 142, V.
Sumberia 91, S. Sumowidagdo 82, S. Swain61, I. Szarka 13, M. Szymkowski 135,
S.F. Taghavi 95, G. Taillepied 97, J. Takahashi 111, G.J. Tambave 80, S. Tang
6, Z. Tang 119, J.D. Tapia Takaki 117, N. Tapus125, L.A. Tarasovicova 137,
M.G. Tarzila 46, G.F. Tassielli 32, A. Tauro 33, G. Tejeda Muñoz 45, A.
Telesca 33, L. Terlizzi 25, C. Terrevoli 115, S. Thakur 4, D. Thomas 108, A.
Tikhonov 142, N. Tiltmann 33,137, A.R. Timmins 115, M. Tkacik106, T. Tkacik
106, A. Toia 64, R. Tokumoto92, K. Tomohiro92, N. Topilskaya 142, M. Toppi 49,
T. Tork 130, P.V. Torres65, V.V. Torres 103, A.G. Torres Ramos 32, A. Trifiró
31,53, A.S. Triolo 33,31,53, S. Tripathy 51, T. Tripathy 47, S. Trogolo 33, V.
Trubnikov 3, W.H. Trzaska 116, T.P. Trzcinski 135, A. Tumkin 142, R. Turrisi
54, T.S. Tveter 20, K. Ullaland 21, B. Ulukutlu 95, A. Uras 127, G.L. Usai 23,
M. Vala38, N. Valle 22, L.V.R. van Doremalen59, M. van Leeuwen 84, C.A. van
Veen 94, R.J.G. van Weelden 84, P. Vande Vyvre 33, D. Varga 138, Z. Varga 138,
M. Vasileiou 78, A. Vasiliev 142, O. Vázquez Doce 49, O. Vazquez Rueda 115, V.
Vechernin 142, E. Vercellin 25, S. Vergara Limón45, R. Verma47, L. Vermunt 97,
R. Vértesi 138, M. Verweij 59, L. Vickovic34, Z. Vilakazi122, O. Villalobos
Baillie 100, A. Villani 24, A. Vinogradov 142, T. Virgili 29, M.M.O. Virta
116, V. Vislavicius75, A. Vodopyanov 143, B. Volkel 33, M.A. Völkl 94, K.
Voloshin142, S.A. Voloshin 136, G. Volpe 32, B. von Haller 33, I. Vorobyev 95,
N. Vozniuk 142, J. Vrláková 38, J. Wan40, C. Wang 40, D. Wang40, Y. Wang 40,
Y. Wang 6, A. Wegrzynek 33, F.T. Weiglhofer39, S.C. Wenzel 33, J.P. Wessels
137, S.L. Weyhmiller 139, J. Wiechula 64, J. Wikne 20, G. Wilk 79, J.
Wilkinson 97, G.A. Willems 137, B. Windelband 94, M. Winn 129, J.R. Wright
108, W. Wu40, Y. Wu 119, R. Xu 6, A. Yadav 43, A.K. Yadav 134, S. Yalcin 72,
Y. Yamaguchi 92, S. Yang21, S. Yano 92, Z. Yin 6, I.-K. Yoo 17, J.H. Yoon 58,
H. Yu12, S. Yuan21, A. Yuncu 94, V. Zaccolo 24, C. Zampolli 33, F. Zanone 94,
N. Zardoshti 33, A. Zarochentsev 142, P. Závada 62, N. Zaviyalov142, M. Zhalov
142, B. Zhang 6, C. Zhang 129, L. Zhang 40, S. Zhang 40, X. Zhang 6, Y.
Zhang119, Z. Zhang 6, M. Zhao 10, V. Zherebchevskii 142, Y. Zhi10, D. Zhou 6,
Y. Zhou 83, J. Zhu 97,6, Y. Zhu6, S.C. Zugravel 56, N. Zurlo 133,55

## Affiliation Notes

I Also at: Max-Planck-Institut für Physik, Munich, Germany
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: Department of Applied Physics, Aligarh Muslim University, Aligarh,
India
V Also at: Institute of Theoretical Physics, University of Wroclaw, Poland
VI Also at: An institution covered by a cooperation agreement with CERN

## Collaboration Institutes

1 A.I. Alikhanyan National Science Laboratory (Yerevan Physics Institute)
Foundation, Yerevan, Armenia
2 AGH University of Krakow, 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 California Polytechnic State University, San Luis Obispo, California, United
States
6 Central China Normal University, Wuhan, China
7 Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Havana,
Cuba
8 Centro de Investigación y de Estudios Avanzados (CINVESTAV), Mexico City and
Mérida, Mexico
9 Chicago State University, Chicago, Illinois, United States
10 China Institute of Atomic Energy, Beijing, China
11 China University of Geosciences, Wuhan, China
12 Chungbuk National University, Cheongju, Republic of Korea
13 Comenius University Bratislava, Faculty of Mathematics, Physics and
Informatics, Bratislava, Slovak Republic
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, Università di Pavia, Pavia, 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.R. Caianiello’ dell’Università and Gruppo
Collegato INFN, Salerno, Italy
30 Dipartimento DISAT del Politecnico and Sezione INFN, Turin, Italy
31 Dipartimento di Scienze MIFT, Università di Messina, Messina, Italy
32 Dipartimento Interateneo di Fisica ‘M. Merlin’ and Sezione INFN, Bari,
Italy
33 European Organization for Nuclear Research (CERN), Geneva, Switzerland
34 Faculty of Electrical Engineering, Mechanical Engineering and Naval
Architecture, University of Split, Split, Croatia
35 Faculty of Engineering and Science, Western Norway University of Applied
Sciences, Bergen, Norway
36 Faculty of Nuclear Sciences and Physical Engineering, Czech Technical
University in Prague, Prague, Czech Republic
37 Faculty of Physics, Sofia University, Sofia, Bulgaria
38 Faculty of Science, P.J. Šafárik University, Košice, Slovak Republic
39 Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-
Universität Frankfurt, Frankfurt, Germany
40 Fudan University, Shanghai, China
41 Gangneung-Wonju National University, Gangneung, Republic of Korea
42 Gauhati University, Department of Physics, Guwahati, India
43 Helmholtz-Institut für Strahlen- und Kernphysik, Rheinische Friedrich-
Wilhelms-Universität Bonn, Bonn, Germany
44 Helsinki Institute of Physics (HIP), Helsinki, Finland
45 High Energy Physics Group, Universidad Autónoma de Puebla, Puebla, Mexico
46 Horia Hulubei National Institute of Physics and Nuclear Engineering,
Bucharest, Romania
47 Indian Institute of Technology Bombay (IIT), Mumbai, India
48 Indian Institute of Technology Indore, Indore, India
49 INFN, Laboratori Nazionali di Frascati, Frascati, Italy
50 INFN, Sezione di Bari, Bari, Italy
51 INFN, Sezione di Bologna, Bologna, Italy
52 INFN, Sezione di Cagliari, Cagliari, Italy
53 INFN, Sezione di Catania, Catania, Italy
54 INFN, Sezione di Padova, Padova, Italy
55 INFN, Sezione di Pavia, Pavia, Italy
56 INFN, Sezione di Torino, Turin, Italy
57 INFN, Sezione di Trieste, Trieste, Italy
58 Inha University, Incheon, Republic of Korea
59 Institute for Gravitational and Subatomic Physics (GRASP), Utrecht
University/Nikhef, Utrecht, Netherlands
60 Institute of Experimental Physics, Slovak Academy of Sciences, Košice,
Slovak Republic
61 Institute of Physics, Homi Bhabha National Institute, Bhubaneswar, India
62 Institute of Physics of the Czech Academy of Sciences, Prague, Czech
Republic
63 Institute of Space Science (ISS), Bucharest, Romania
64 Institut für Kernphysik, Johann Wolfgang Goethe-Universität Frankfurt,
Frankfurt, Germany
65 Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México,
Mexico City, Mexico
66 Instituto de Física, Universidade Federal do Rio Grande do Sul (UFRGS),
Porto Alegre, Brazil
67 Instituto de Física, Universidad Nacional Autónoma de México, Mexico City,
Mexico
68 iThemba LABS, National Research Foundation, Somerset West, South Africa
69 Jeonbuk National University, Jeonju, Republic of Korea
70 Johann-Wolfgang-Goethe Universität Frankfurt Institut für Informatik,
Fachbereich Informatik und Mathematik, Frankfurt, Germany
71 Korea Institute of Science and Technology Information, Daejeon, Republic of
Korea
72 KTO Karatay University, Konya, Turkey
73 Laboratoire de Physique Subatomique et de Cosmologie, Université Grenoble-
Alpes, CNRS-IN2P3, Grenoble, France
74 Lawrence Berkeley National Laboratory, Berkeley, California, United States
75 Lund University Department of Physics, Division of Particle Physics, Lund,
Sweden
76 Nagasaki Institute of Applied Science, Nagasaki, Japan
77 Nara Women’s University (NWU), Nara, Japan
78 National and Kapodistrian University of Athens, School of Science,
Department of Physics , Athens, Greece
79 National Centre for Nuclear Research, Warsaw, Poland
80 National Institute of Science Education and Research, Homi Bhabha National
Institute, Jatni, India
81 National Nuclear Research Center, Baku, Azerbaijan
82 National Research and Innovation Agency - BRIN, Jakarta, Indonesia
83 Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
84 Nikhef, National institute for subatomic physics, Amsterdam, Netherlands
85 Nuclear Physics Group, STFC Daresbury Laboratory, Daresbury, United Kingdom
86 Nuclear Physics Institute of the Czech Academy of Sciences, Husinec-Řež,
Czech Republic
87 Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States
88 Ohio State University, Columbus, Ohio, United States
89 Physics department, Faculty of science, University of Zagreb, Zagreb,
Croatia
90 Physics Department, Panjab University, Chandigarh, India
91 Physics Department, University of Jammu, Jammu, India
92 Physics Program and International Institute for Sustainability with Knotted
Chiral Meta Matter (SKCM2), Hiroshima University, Hiroshima, Japan
93 Physikalisches Institut, Eberhard-Karls-Universität Tübingen, Tübingen,
Germany
94 Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg,
Germany
95 Physik Department, Technische Universität München, Munich, Germany
96 Politecnico di Bari and Sezione INFN, Bari, Italy
97 Research Division and ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum
für Schwerionenforschung GmbH, Darmstadt, Germany
98 Saga University, Saga, Japan
99 Saha Institute of Nuclear Physics, Homi Bhabha National Institute, Kolkata,
India
100 School of Physics and Astronomy, University of Birmingham, Birmingham,
United Kingdom
101 Sección Física, Departamento de Ciencias, Pontificia Universidad Católica
del Perú, Lima, Peru
102 Stefan Meyer Institut für Subatomare Physik (SMI), Vienna, Austria
103 SUBATECH, IMT Atlantique, Nantes Université, CNRS-IN2P3, Nantes, France
104 Sungkyunkwan University, Suwon City, Republic of Korea
105 Suranaree University of Technology, Nakhon Ratchasima, Thailand
106 Technical University of Košice, Košice, Slovak Republic
107 The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy of
Sciences, Cracow, Poland
108 The University of Texas at Austin, Austin, Texas, United States
109 Universidad Autónoma de Sinaloa, Culiacán, Mexico
110 Universidade de São Paulo (USP), São Paulo, Brazil
111 Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil
112 Universidade Federal do ABC, Santo Andre, Brazil
113 University of Cape Town, Cape Town, South Africa
114 University of Derby, Derby, United Kingdom
115 University of Houston, Houston, Texas, United States
116 University of Jyväskylä, Jyväskylä, Finland
117 University of Kansas, Lawrence, Kansas, United States
118 University of Liverpool, Liverpool, United Kingdom
119 University of Science and Technology of China, Hefei, China
120 University of South-Eastern Norway, Kongsberg, Norway
121 University of Tennessee, Knoxville, Tennessee, United States
122 University of the Witwatersrand, Johannesburg, South Africa
123 University of Tokyo, Tokyo, Japan
124 University of Tsukuba, Tsukuba, Japan
125 University Politehnica of Bucharest, Bucharest, Romania
126 Université Clermont Auvergne, CNRS/IN2P3, LPC, Clermont-Ferrand, France
127 Université de Lyon, CNRS/IN2P3, Institut de Physique des 2 Infinis de
Lyon, Lyon, France
128 Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France,
Strasbourg, France
129 Université Paris-Saclay, Centre d’Etudes de Saclay (CEA), IRFU, Départment
de Physique Nucléaire (DPhN), Saclay, France
130 Université Paris-Saclay, CNRS/IN2P3, IJCLab, Orsay, France
131 Università degli Studi di Foggia, Foggia, Italy
132 Università del Piemonte Orientale, Vercelli, Italy
133 Università di Brescia, Brescia, Italy
134 Variable Energy Cyclotron Centre, Homi Bhabha National Institute, Kolkata,
India
135 Warsaw University of Technology, Warsaw, Poland
136 Wayne State University, Detroit, Michigan, United States
137 Westfälische Wilhelms-Universität Münster, Institut für Kernphysik,
Münster, Germany
138 Wigner Research Centre for Physics, Budapest, Hungary
139 Yale University, New Haven, Connecticut, United States
140 Yonsei University, Seoul, Republic of Korea
141 Zentrum für Technologie und Transfer (ZTT), Worms, Germany
142 Affiliated with an institute covered by a cooperation agreement with CERN
143 Affiliated with an international laboratory covered by a cooperation
agreement with CERN.