2021 187 16 September

Prompt $\mathrm{D_{s}^{+}}$ mesons in Pb–Pb at
$\sqrt{s_{\mathrm{NN}}}=5.02~{}\mathrm{TeV}$

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

The production yield and angular anisotropy of prompt $\mathrm{D_{s}^{+}}$
mesons were measured as a function of transverse momentum ($p_{\mathrm{T}}$)
in Pb–Pb collisions at a centre-of-mass energy per nucleon pair
$\sqrt{s_{\mathrm{NN}}}=5.02~{}\mathrm{TeV}$ collected with the ALICE detector
at the LHC. $\mathrm{D_{s}^{+}}$ mesons and their charge conjugates were
reconstructed at midrapidity ($|y|<0.5$) from their hadronic decay channel
$\mathrm{D_{s}^{+}\to\upphi\uppi^{+}}$, with $\mathrm{\upphi\to K^{-}K^{+}}$,
in the $p_{\mathrm{T}}$ intervals $2<p_{\mathrm{T}}<50~{}\mathrm{GeV}/c$ and
$2<p_{\mathrm{T}}<36~{}\mathrm{GeV}/c$ for the 0–10% and 30–50% centrality
intervals. For $p_{\mathrm{T}}>10~{}\mathrm{GeV}/c$, the measured
$\mathrm{D_{s}^{+}}$-meson nuclear modification factor $R_{\mathrm{AA}}$ is
consistent with the one of non-strange D mesons within uncertainties, while at
lower $p_{\mathrm{T}}$ a hint for a $\mathrm{D_{s}^{+}}$-meson
$R_{\mathrm{AA}}$ larger than that of non-strange D mesons is seen. The
enhanced production of $\mathrm{D_{s}^{+}}$ relative to non-strange D mesons
is also studied by comparing the $p_{\mathrm{T}}$-dependent
$\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ production yield ratios in Pb–Pb and in pp
collisions. The ratio measured in Pb–Pb collisions is found to be on average
higher than that in pp collisions in the interval
$2<p_{\mathrm{T}}<8~{}\mathrm{GeV}/c$ with a significance of $2.3\sigma$ and
$2.4\sigma$ for the 0–10% and 30–50% centrality intervals. The azimuthal
anisotropy coefficient $v_{2}$ of prompt $\mathrm{D_{s}^{+}}$ mesons was
measured in Pb–Pb collisions in the 30–50% centrality interval and is found to
be compatible with that of non-strange D mesons. The main features of the
measured $R_{\mathrm{AA}}$, $\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ ratio, and
$v_{2}$ as a function of $p_{\mathrm{T}}$ are described by theoretical
calculations of charm-quark transport in a hydrodynamically expanding
quark–gluon plasma including hadronisation via charm-quark recombination with
light quarks from the medium. The $p_{\mathrm{T}}$-integrated production yield
of $\mathrm{D_{s}^{+}}$ mesons is compatible with the prediction of the
statistical hadronisation model.

##  1 Introduction

Strongly-interacting matter at temperatures exceeding the pseudo-critical
value of $T_{\rm pc}\approx 154\text{--}158~{}\mathrm{MeV}$ and at vanishing
baryon density is predicted to behave as a plasma of deconfined quarks and
gluons (QGP) [1, 2]. A QGP is formed and studied in ultrarelativistic heavy-
ion collisions at the CERN Large Hadron Collider (LHC) and existing
measurements indicate that it behaves as a strongly-coupled liquid-like system
[3]. The lifetime of the QGP produced at the energy densities reached at the
LHC is of the order of 10 $\mathrm{fm}/c$ [4]. Heavy quarks (charm and beauty)
are sensitive probes to investigate the properties of the medium formed in
these collisions. Due to their large masses, heavy quarks are produced
predominantly in hard partonic scattering processes occurring during the early
stages of the collision (i.e. on timescales shorter than the QGP formation
time) and therefore experience the entire evolution of the medium. Heavy
quarks propagate through the expanding hot and dense medium, interacting and
exchanging energy and momentum with its constituents via both inelastic and
elastic quantum chromodynamic (QCD) processes. At high momentum, the main
effect of these interactions is the energy loss of the heavy quarks in the QGP
due to medium-induced gluon radiation and collisional processes. On the other
hand, low-momentum heavy quarks, including those shifted to low momentum by
the energy loss, probe the diffusion regime dominated by elastic interactions.
Since the charm and beauty quark masses are large compared to the medium
temperature, the propagation of low-momentum heavy quarks through the fireball
can be treated as a “Brownian motion”, characterised by many elastic
collisions with relatively small momentum transfers [5, 6]. As a consequence
of the large number of soft collisions with the medium constituents, heavy
quarks can acquire significant collective flow when diffusing through the
expanding fireball. Due to their large masses, charm quarks have a
thermalisation time which is comparable to the fireball lifetime [7, 5], and
therefore they carry sensitive information on their coupling strength to the
expanding medium, preserving memory of the thermalisation process. The process
of hadronisation is also predicted to be modified in the presence of the QGP.
Once the fireball approaches the pseudo-critical temperature for the
transition to a hadron gas, a significant fraction of low- and intermediate-
momentum heavy quarks could hadronise via recombination with other quarks from
the medium [8, 9, 10, 11], in competition with the fragmentation mechanism,
which describes quark-to-hadron transitions in pp, $\mathrm{e}^{\pm}$p, and
$\mathrm{e}^{+}\mathrm{e}^{-}$ collisions [12, 13].

The effects of the interaction of heavy quarks with the medium are commonly
quantified by two main observables: the nuclear modification factor
$R_{\mathrm{AA}}$ and the elliptic flow $v_{2}$. The $R_{\mathrm{AA}}$ is
defined as the ratio of the transverse-momentum ($p_{\mathrm{T}}$)
differential yields in nucleus–nucleus (AA) collisions and the cross section
in proton–proton collisions, scaled by the average nuclear overlap function
$\left\langle T_{\rm AA}\right\rangle$

$R_{\rm AA}(p_{\mathrm{T}})={\frac{1}{\left\langle T_{\rm
AA}\right\rangle}}\times{\frac{{\rm d}N_{\rm AA}/{\rm d}p_{\mathrm{T}}}{{\rm
d}\sigma_{\rm pp}/{\rm d}p_{\mathrm{T}}}}\,,$ (1)

where the yield in nucleus–nucleus collisions ${\rm d}N_{\rm AA}/{\rm
d}p_{\mathrm{T}}$ is measured in a given centrality interval and the
$\left\langle T_{\rm AA}\right\rangle$ value is proportional to the average
number of nucleon–nucleon collisions [14]. The $\left\langle T_{\rm
AA}\right\rangle$ can be estimated via Glauber-model calculations tuned to
match the measured multiplicity distribution of charged particles [15]. The
elliptic flow $v_{2}$ is the second coefficient of the Fourier expansion of
the particle-yield distribution in the azimuthal direction $\varphi$ relative
to the initial-state symmetry plane angle $\Psi_{2}$: $v_{2}=\langle{\rm
cos}[2(\varphi-\Psi_{2})]\rangle$, where $\langle\rangle$ indicates the
average over all particles and all events [16, 17].

Measurements of non-strange D-meson production in heavy-ion collisions at RHIC
[18] and LHC [19, 20, 21] energies show a substantial suppression of the
D-meson yields compared to pp collisions at intermediate and high
$p_{\mathrm{T}}$. In central nucleus–nucleus collisions, the $R_{\mathrm{AA}}$
exhibits a pronounced drop for $p_{\mathrm{T}}>4\text{--}5~{}\mathrm{GeV}/c$,
reaches a minimum around $p_{\mathrm{T}}\approx 8~{}\mathrm{GeV}/c$, and
slightly increases at higher $p_{\mathrm{T}}$. This trend is described by
different state-of-the-art model calculations of charm-quark energy loss in
the QGP [22, 23, 24]. A positive D-meson $v_{2}$ is measured at
$p_{\mathrm{T}}>8\text{--}10~{}\mathrm{GeV}/c$ for semicentral Pb–Pb
collisions at the LHC [25, 26], and it is understood as originating from the
path-length dependence of the charm-quark energy loss in the geometrically
anisotropic medium created in collisions with finite impact parameter. At
lower $p_{\mathrm{T}}$, larger values of D-meson $v_{2}$ are observed
accompanied by a bump-like structure in the $R_{\mathrm{AA}}$ reflecting the
radial flow of the fireball [20, 19, 21]. In particular, the D-meson $v_{2}$
for semicentral collisions shows a maximum value at $p_{\mathrm{T}}\approx
3~{}\mathrm{GeV}/c$, a clear mass ordering $v_{2}({\rm D})<v_{2}({\rm
p})<v_{2}({\pi})$ at low $p_{\mathrm{T}}$
($p_{\mathrm{T}}<3~{}\mathrm{GeV}/c$), and a similar magnitude as the $v_{2}$
of charged pions at intermediate $p_{\mathrm{T}}$
($3<p_{\mathrm{T}}<6~{}\mathrm{GeV}/c$) [26, 25]. These features are
consistent with a scenario in which low-momentum charm quarks acquire a
significant collective flow when diffusing through the expanding QGP and
hadronise via recombination with light quarks from the medium. The measured
$R_{\mathrm{AA}}$ and $v_{2}$ in this $p_{\mathrm{T}}$ region are described
qualitatively, and to some extent also quantitatively, by transport models
including charm-quark interactions in a hydrodynamically expanding QGP and
hadronisation via both fragmentation and recombination [27, 28, 29, 30, 31,
32, 33, 34, 35, 36, 37, 38]. However, a simultaneous description of the
nuclear modification factor and the anisotropic flow of D mesons is still a
challenge for theoretical models.

Studies of the production of different charm-hadron species, dubbed heavy-
flavour hadrochemistry, can provide information on the hadronisation mechanism
of charm quarks. In particular, an enhancement of the ground-state charm-
strange meson yield relative to that of non-strange D mesons is expected in
nucleus–nucleus collisions at low and intermediate momenta as compared to pp
interactions, if the dominant process for D-meson formation is the
recombination of charm quarks with light quarks from the medium, due to the
large abundance of strange quarks in the QGP [39, 40, 41, 42, 43]. It was also
pointed out in Ref. [43] that the comparison of the $v_{2}$ of
$\mathrm{D_{s}^{+}}$ mesons to that of D mesons without strange-quark content
($\mathrm{D^{0}}$, $\mathrm{D^{+}}$, and $\mathrm{D^{*+}}$) could provide
sensitivity to the transport properties of the hadronic phase, since
$\mathrm{D_{s}^{+}}$ mesons are expected to decouple early from the hadron gas
and therefore do not pick up significant additional $v_{2}$ in the hadronic
phase.

The production of $\mathrm{D_{s}^{+}}$ mesons was measured at RHIC [44] and
the LHC [45, 20] in Au–Au and Pb–Pb collisions at different centralities. So
far, the results have shown that at low and intermediate $p_{\mathrm{T}}$ the
$\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ ratio in central, semicentral, and
peripheral collisions is larger than the value measured in pp collisions,
though the relatively large uncertainties do not allow firm conclusions. The
magnitude and the $p_{\mathrm{T}}$ dependence of the
$\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ ratio are captured, at least
qualitatively, by models including hadronisation via quark coalescence along
with strangeness enhancement in the QGP [46, 47, 43, 33], suggesting a
relevant role of recombination processes in the hadronisation of low-momentum
charm quarks in the QGP.

In this Letter, we report the measurements of the
$p_{\mathrm{T}}$-differential yield and the nuclear modification factor of
prompt $\mathrm{D_{s}^{+}}$ mesons in central (0–10$\%$) and semicentral
(30–50$\%$) Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02~{}\mathrm{TeV}$,
together with the measurement of the prompt $\mathrm{D_{s}^{+}}$-meson
elliptic flow in semicentral collisions. $\mathrm{D_{s}^{+}}$ mesons and their
charge conjugates were reconstructed at midrapidity, $|y|<0.5$, through their
hadronic decay channel $\mathrm{D_{s}^{+}\to\upphi\uppi^{+}}$ with a
subsequent decay $\mathrm{\upphi\to K^{-}K^{+}}$. Prompt $\mathrm{D_{s}^{+}}$
mesons are defined as those produced directly in the hadronisation of charm
quarks or originating from the decays of directly-produced excited open-charm
and charmonium states, hence excluding weak decays of beauty hadrons. The data
sample used for the analysis reported in this paper was collected with the
ALICE detector at the end of 2018 and is larger by a factor of about 8 (4) for
central (semicentral) collisions with respect to the sample collected in 2015,
used for the previous publications of $\mathrm{D_{s}^{+}}$-meson
$R_{\mathrm{AA}}$ and $v_{2}$ [20, 48].

##  2 Experimental apparatus and data sample

The ALICE apparatus comprises a central barrel, which is composed of a set of
detectors for charged particle reconstruction and identification at
midrapidity, a forward muon spectrometer, and various forward and backward
detectors for triggering and event characterisation. A detailed description of
the detectors and an overview of their typical performances can be found in
Refs. [49, 50].

The $\mathrm{D_{s}^{+}}$-meson decay candidates and charged conjugates were
reconstructed and identified with the central barrel detectors, which cover
the full azimuth in the pseudorapidity interval $|\eta|<0.9$ and are embedded
in a large solenoidal magnet providing a homogeneous magnetic field
$B=0.5~{}\mathrm{T}$ parallel to the beam direction. Charged-particle
trajectories are reconstructed from their hits in the Inner Tracking System
(ITS) and the Time Projection Chamber (TPC). The ITS is the innermost detector
of the ALICE central barrel, it consists of six cylindrical layers of silicon
detectors, allowing a precise determination of the track parameters in the
vicinity of the interaction point. The TPC provides track reconstruction with
up to 159 three-dimensional space points along the trajectory of a charged
particle and provides particle identification via the measurement of the
specific ionisation energy loss $\mathrm{d}E/\mathrm{d}x$. The Time-Of-Flight
(TOF) detector, positioned at a radial distance of about 4 m from the beam
axis, extends the particle-identification capabilities of the TPC by measuring
the flight time of the charged particles from the interaction point to the
TOF. The V0 detector is used for triggering and event selection, as well as
for the estimation of the collision centrality and the reference plane for the
elliptic flow measurement. It consists of two scintillator arrays, located on
both sides of the nominal interaction point and covering the full azimuth in
the pseudorapidity intervals $-3.7<\eta<-1.7$ (V0C) and $2.8<\eta<5.1$ (V0A).
The neutron Zero Degree Calorimeters (ZDC), located along the beam axis on
both sides of the central barrel at about 110 m distance from the interaction
point, are used for event selection, along with the V0 detector.

The events used in the analysis were recorded with a minimum bias (MB) trigger
which required coincident signals in the V0A and V0C detectors. Two additional
trigger classes were used to enrich the sample of central and semicentral
collisions via an online event selection based on the V0-signal amplitude.
Background events due to the interaction of one of the beams with residual gas
in the vacuum tube and other machine-induced backgrounds were rejected offline
using the V0 and the ZDC timing information [50]. In order to have a uniform
acceptance in pseudorapidity, only events with a primary vertex reconstructed
within $\pm 10$ cm from the centre of the detector along the beam-line
direction were considered in the analysis. Collisions were classified into
centrality intervals, defined in terms of percentiles of the hadronic Pb–Pb
cross section, based on the V0 signal amplitude, as described in detail in
Ref. [51]. Central and semicentral collisions were considered in the analysis
of the $\mathrm{D_{s}^{+}}$-meson production. The sample of central collisions
consists of about $100\times 10^{6}$ events in the 0–10% centrality interval,
corresponding to an integrated luminosity $\mathcal{L}_{\rm int}~{}\simeq
130~{}\upmu\mathrm{b}^{-1}$. For semicentral collisions, a sample of about
$85\times 10^{6}$ events in the 30–50% interval was utilised, corresponding to
$\mathcal{L}_{\rm int}~{}\simeq 56~{}\upmu\mathrm{b}^{-1}$. The average values
of the nuclear overlap function, $\left\langle T_{\mathrm{AA}}\right\rangle$,
for the considered central and semicentral event intervals were estimated via
Glauber-model simulations anchored to the measured charged-particle
multiplicity distribution, and are $23.26\pm 0.17$ mb-1 and $3.92\pm 0.06$
mb-1 [52], respectively.

The Monte Carlo samples utilised in the analysis were obtained simulating
Pb–Pb collisions with the HIJING 1.36 [53] event generator. In each simulated
event, additional $\mathrm{c\overline{c}}$\- and
$\mathrm{b\overline{b}}$-quark pairs were injected using the PYTHIA 8.243
event generator [54, 55] (Monash-13 tune [56]) and $\mathrm{D_{s}^{+}}{}$
mesons were forced to decay into the hadronic channel of interest for the
analysis. The generated particles were propagated through the detector using
the GEANT3 transport package [57]. The conditions of all the ALICE detectors
in terms of active channels, gain, noise level, and alignment, and their
evolution with time during the data taking period, were taken into account in
the simulations.

##  3 Analysis technique

$\mathrm{D_{s}^{+}}$ mesons and their charge conjugates were reconstructed via
the decay channel $\mathrm{D_{s}^{+}\to\upphi\uppi^{+}\to
K^{-}K^{+}\uppi^{+}}$ with branching ratio $\mathrm{BR}=(2.24\pm 0.08)\%$
[58]. The analysis was based on the reconstruction of decay-vertex topologies
displaced from the interaction vertex. The separation induced by the weak
decays of prompt $\mathrm{D_{s}^{+}}$ mesons is typically a few hundred of
$\mathrm{\upmu m}$, $c\tau\simeq 151~{}\mathrm{\upmu m}$ [58].

$\mathrm{D_{s}^{+}}$-meson candidates were built combining triplets of tracks
with the proper charge signs, each with $|\eta|<0.8$, at least 70 out of 159
crossed TPC pad rows, a fit quality $\chi^{2}/{\rm ndf}<1.25$ in the TPC
(where ndf is the number of degrees of freedom involved in the track fit
procedure), and a minimum of two (out of six) hits in the ITS, with at least
one in either of the two innermost layers, which provide the best pointing
resolution. Moreover, at least 50 clusters available for particle
identification (PID) in the TPC were required and only tracks with
$p_{\mathrm{T}}$ above $0.6~{}(0.4)~{}\mathrm{GeV}/c$ were considered for
central (semicentral) collisions. These track-selection criteria limit the
$\mathrm{D_{s}^{+}}$-meson acceptance in rapidity, which drops steeply to zero
for $|y|>0.5$ at low $p_{\mathrm{T}}$ and for $|y|>0.8$ at
$p_{\mathrm{T}}>5~{}\mathrm{GeV}/c$. Thus, only $\mathrm{D_{s}^{+}}$-meson
candidates within a $p_{\mathrm{T}}{}$-dependent fiducial acceptance region,
$|y|<y_{\rm fid}(p_{\mathrm{T}})$, were selected. The
$y_{\mathrm{fid}}(p_{\mathrm{T}})$ value was defined as a second-order
polynomial function, increasing from 0.5 to 0.8 in the transverse-momentum
range $0<p_{\mathrm{T}}<5~{}\mathrm{GeV}/c$, and as a constant term,
$y_{\mathrm{fid}}=0.8$, for $p_{\mathrm{T}}>5~{}\mathrm{GeV}/c$.

Unlike previous D-meson analyses based on linear selections [20, 26, 21], a
machine-learning (ML) approach based on Boosted Decision Trees (BDT) was
adopted for the candidate selection to reduce the large combinatorial
background [59]. In particular, the implementation of the BDT algorithm
provided by the XGBoost [60] library was employed. Signal samples of prompt
$\mathrm{D_{s}^{+}}$ mesons for the BDT training were obtained from Monte
Carlo simulations as described in Section 2. The background samples were
obtained from the sidebands of the candidate invariant-mass distributions in
the data. Before the training, loose kinematic and topological selections were
applied to the $\mathrm{D_{s}^{+}}$-meson candidates together with the PID of
decay-product tracks. Pions and kaons were selected by requiring compatibility
with the respective particle hypothesis within three times the detector
resolution between the measured and the expected signals for either the TPC
$\mathrm{d}E/\mathrm{d}x$ or the time of flight. Tracks without TOF hits were
identified using only the TPC information. In addition, the absolute
difference between the reconstructed ${\rm K^{+}K^{-}}$ invariant mass and the
PDG average mass for the $\upphi$ meson [58] ($\Delta M_{\mathrm{KK}}$) was
required to be below $15~{}\mathrm{MeV}/c^{2}$. The candidate information
provided to the BDTs, as an input for the models to distinguish among prompt
$\mathrm{D_{s}^{+}}$ mesons and background candidates, was mainly based on the
displacement of the tracks from the primary vertex, the distance between the
$\mathrm{D_{s}^{+}}$-meson decay vertex and the primary vertex, the
$\mathrm{D_{s}^{+}}$-meson impact parameter, and the cosine of the pointing
angle between the $\mathrm{D_{s}^{+}}$-meson candidate line of flight (the
vector connecting the primary and secondary vertex) and its reconstructed
momentum vector. The value of $\Delta M_{\mathrm{KK}}$ and additional
variables related to the PID of decay tracks were also included. Independent
BDTs were trained in the different $p_{\mathrm{T}}$ intervals of the analysis
and for the different centrality intervals. Subsequently, they were applied to
the real data sample in which the belonging class, i.e., prompt
$\mathrm{D_{s}^{+}}$ meson or combinatorial background, of particle candidates
is unknown. Selections on the BDT output, which is related to the candidate’s
probability to be a prompt $\mathrm{D_{s}^{+}}$ meson, were optimised to
reject a large fraction of the combinatorial background while maintaining high
signal-selection efficiency.

###  3.1 Nuclear modification factor measurement

The raw yields of $\mathrm{D_{s}^{+}}$ mesons, including both particles and
antiparticles, were extracted from binned maximum-likelihood fits to the
invariant-mass distributions. The raw yields could be extracted in transverse-
momentum intervals in the ranges $2<p_{\mathrm{T}}<50~{}\mathrm{GeV}/c$ and
$2<p_{\mathrm{T}}<36~{}\mathrm{GeV}/c$ for the 0–10% and the 30–50% centrality
intervals, respectively. The fit function was composed of a Gaussian for the
description of the signal and of an exponential term for the background. An
additional Gaussian was used to describe the peak due to the decay
$\mathrm{D^{+}\to K^{-}K^{+}\uppi^{+}}$, with a branching ratio of $(9.68\pm
0.18)\times 10^{-3}$ [58], present at a lower invariant-mass value than the
$\mathrm{D_{s}^{+}}$-meson signal peak. The statistical significance of the
observed signals $S/\sqrt{S+B}$, where $S$ is the raw signal yield obtained by
integrating the Gaussian function and $B$ is the background under the peak
within 3 standard deviations, varies from 4 to 24 depending on the
$p_{\mathrm{T}}$ and centrality intervals.

The $p_{\mathrm{T}}$-differential corrected yield of prompt
$\mathrm{D_{s}^{+}}$ mesons was computed for each $p_{\mathrm{T}}$ interval
according to

$\left.\frac{{\rm d}N}{{\rm
d}p_{\mathrm{T}}}\right|_{|y|<0.5}=\frac{1}{2}\times\frac{1}{\Delta
p_{\mathrm{T}}}\times\frac{\left.f_{\mathrm{prompt}}(p_{\mathrm{T}})\times
N^{\rm D+\overline{D},raw}(p_{\mathrm{T}})\right|_{|y|<y_{\rm
fid}(p_{\mathrm{T}})}}{c_{\Delta
y}(p_{\mathrm{T}})\times(\mathrm{Acc}\times\epsilon)_{\mathrm{prompt}}{}(p_{\mathrm{T}})\times\mathrm{BR}\times
N_{\mathrm{evt}}}\,.$ (2)

The raw-yield values $N^{\rm D+\overline{D},raw}$, which contain the
contribution of non-prompt $\mathrm{D_{s}^{+}}$ mesons from beauty-hadron
decays, were divided by a factor of two and multiplied by the prompt fraction
$f_{\mathrm{prompt}}$ to obtain the charge-averaged yields of prompt
$\mathrm{D_{s}^{+}}$ mesons. Furthermore, they were divided by the acceptance
times efficiency of prompt $\mathrm{D_{s}^{+}}$ mesons
$(\mathrm{Acc}\times\epsilon)_{\mathrm{prompt}}{}$, the BR of the decay
channel, the width of the $p_{\mathrm{T}}$ interval $\Delta p_{\mathrm{T}}$,
the correction factor for the rapidity coverage $c_{\Delta y}$, and the number
of analysed events $N_{\rm evt}$. The correction factor for the rapidity
acceptance $c_{\Delta y}$ was computed with FONLL perturbative QCD
calculations [61, 62]. It was defined as the ratio between the generated
D-meson yield in $\Delta y=2\,y_{\rm fid}$ and that in $|y|<0.5$. The
resulting values were in agreement within 1% with PYTHIA 8 simulations for pp
collisions. To account for possible differences in Pb–Pb collisions and as an
extreme variation, a flat rapidity distribution was also considered. The
discrepancies with respect to FONLL calculations were negligible in comparison
to other sources of systematic uncertainty described in Section 4.

The $(\rm Acc\times\epsilon)$ correction was obtained from the simulations
described in Section 2 using samples not employed in the BDT training. The
$\mathrm{D_{s}^{+}}{}$-meson $p_{\mathrm{T}}{}$ distributions from simulations
were reweighted in order to use realistic momentum distributions in the
determination of the $(\rm Acc\times\epsilon)$ factor, which depends on
$p_{\mathrm{T}}{}$. In particular, the weights were defined to match the shape
given by FONLL calculations multiplied by the $R_{\mathrm{AA}}{}$ of
$\mathrm{D_{s}^{+}}$ mesons predicted by the TAMU [33] model. The $(\rm
Acc\times\epsilon)$ factors as a function of $p_{\mathrm{T}}$ for prompt and
non-prompt $\mathrm{D_{s}^{+}}$ mesons in the 0–10% and 30–50% centrality
intervals are shown in Fig. 1. The difference between the $(\rm
Acc\times\epsilon)$ factor for prompt and non-prompt $\mathrm{D_{s}^{+}}{}$
mesons arises from the BDT selections applied, given the different decay
topology of $\mathrm{D_{s}^{+}}{}$ mesons coming from beauty-hadron decays. In
particular, the non-prompt $\mathrm{D_{s}^{+}}{}$ mesons are on average more
displaced from the primary vertex due to the large beauty-hadron lifetime,
$c\tau\simeq 500~{}\mathrm{\upmu m}$ [58], and therefore are more efficiently
selected in the low-$p_{\mathrm{T}}{}$ region. At high $p_{\mathrm{T}}{}$,
where the candidate decay length is less important to separate signal from
background, the BDT selections are able to suppress the non-prompt efficiency
with respect to the prompt one. The $(\rm Acc\times\epsilon)$ is higher for
semicentral collisions, by up to a factor two at low $p_{\mathrm{T}}{}$, since
less stringent selections can be applied thanks to the lower combinatorial
background.

Figure 1: Acceptance-times-efficiency factor for $\mathrm{D_{s}^{+}}$ mesons
as a function of $p_{\mathrm{T}}$. The $(\rm Acc\times\epsilon)$ factors for
prompt (red) and non-prompt (blue) $\mathrm{D_{s}^{+}}{}$ mesons in Pb–Pb
collisions for the 0–10% centrality interval are shown, together with those
for prompt (orange) and non-prompt (green) $\mathrm{D_{s}^{+}}{}$ mesons for
the 30–50% centrality interval.

The $f_{\mathrm{prompt}}$ fraction in each $p_{\mathrm{T}}{}$ interval was
obtained following the procedure employed in Refs. [63, 20, 21]. The
calculation was based on the beauty-hadron production cross sections in pp
collisions at $\sqrt{s}=5.02~{}\mathrm{TeV}$ from FONLL calculations, the
beauty hadron to $\mathrm{D+X}$ decay kinematics from the PYTHIA 8 decayer,
the $(\rm Acc\times\epsilon)$ correction factor for non-prompt
$\mathrm{D_{s}^{+}}$ mesons, and the $\left\langle
T_{\mathrm{AA}}\right\rangle$ for the corresponding centrality interval. In
addition, the nuclear modification factor of $\mathrm{D_{s}^{+}}$ mesons from
beauty-hadron decays was accounted for and
$R_{\mathrm{AA}}^{\mathrm{prompt}}=R_{\mathrm{AA}}^{\mathrm{non\text{-}prompt}}$
was assumed as in Ref. [20]. The values of $f_{\mathrm{prompt}}$ range between
0.86 and 0.91 depending on the $p_{\mathrm{T}}$ interval and the centrality
interval.

The prompt $\mathrm{D_{s}^{+}}{}$-meson nuclear modification
$R_{\mathrm{AA}}{}$ factor was computed following Eq. 1. The measurement of
the $p_{\mathrm{T}}{}$-differential cross section of prompt
$\mathrm{D_{s}^{+}}{}$ mesons with $|y|<0.5$ in pp collisions at
$\sqrt{s}=5.02~{}\mathrm{TeV}$ from Ref. [64], which reaches up to
$p_{\mathrm{T}}{}=24~{}\mathrm{GeV}/c{}$, was used as a reference for the
$R_{\mathrm{AA}}{}$ computation. At higher $\mathrm{D_{s}^{+}}{}$-meson
$p_{\mathrm{T}}{}$, $24<p_{\mathrm{T}}{}<50~{}\mathrm{GeV}/c{}$, FONLL
calculations were used as a reference by scaling the predictions to match the
measured values at lower $p_{\mathrm{T}}{}$. The
$p_{\mathrm{T}}{}$-extrapolation procedure is the same as in Ref. [63]. As an
example, the total systematic uncertainty of the pp reference in the
$36<p_{\mathrm{T}}{}<50~{}\mathrm{GeV}/c{}$ interval is ${}^{+42}_{-33}\%$.

###  3.2 Elliptic flow measurement

The elliptic flow of prompt $\mathrm{D_{s}^{+}}{}$ mesons was measured for
semicentral events in transverse-momentum intervals in the range
$2<p_{\mathrm{T}}<24~{}\mathrm{GeV}/c$. The same ML models trained for the
$R_{\mathrm{AA}}{}$ measurement in the 30–50% centrality interval were used
and the same selections on the BDT output were applied. The analysis procedure
for the $v_{\mathrm{2}}$ determination followed closely with what was done in
Ref. [26] for the measurement of the non-strange D-meson elliptic flow. The
$\mathrm{D_{s}^{+}}{}$-meson $v_{\mathrm{2}}$ coefficients were measured using
the Scalar Product (SP) method [65, 66] and can be expressed as

$v_{\mathrm{2}}\\{\mathrm{SP}\\}=\langle\langle\boldsymbol{u}_{\mathrm{2}}\cdot\frac{\boldsymbol{Q}_{\mathrm{2}}^{\rm
A*}}{M^{\rm
A}}\rangle\rangle\bigg{/}\sqrt{\frac{\langle\frac{\boldsymbol{Q}_{\mathrm{2}}^{\rm
A}}{M^{\rm A}}\cdot\frac{\boldsymbol{Q}_{\mathrm{2}}^{\rm B*}}{M^{\rm
B}}\rangle\langle\frac{\boldsymbol{Q}_{\mathrm{2}}^{\rm A}}{M^{\rm
A}}\cdot\frac{\boldsymbol{Q}_{\mathrm{2}}^{\rm C*}}{M^{\rm
C}}\rangle}{\langle\frac{\boldsymbol{Q}_{\mathrm{2}}^{\rm B}}{M^{\rm
B}}\cdot\frac{\boldsymbol{Q}_{\mathrm{2}}^{\rm C*}}{M^{\rm C}}\rangle}},$ (3)

where u${}_{2}=e^{i2\varphi_{\mathrm{D}}}$ is the unit flow vector of the
D-meson candidate with azimuthal angle $\varphi_{\mathrm{D}}$,
$\boldsymbol{Q}^{k}_{2}$ is the subevent $2^{\mathrm{nd}}$-harmonic flow
vector for the subevent $k$, and $M^{k}$ represents the subevent multiplicity.
The SP denominator was calculated with the formula introduced in Ref. [66],
where the three subevents, indicated as A, B, and C, are defined by the
particles measured in the V0C, V0A, and TPC detectors, respectively. For the
TPC detector, the $\boldsymbol{Q}_{2}$ vector was computed from the azimuthal
angles of charged tracks reconstructed with $|\eta|<0.8$ and $M$ was the
number of measured tracks. For the V0A and V0C detectors, the
$\boldsymbol{Q}_{2}$ vectors were calculated from the azimuthal distribution
of the energy deposition in the detector sectors and $M$ was the sum of the
amplitudes measured in each channel [26]. The $\boldsymbol{Q}_{2}$ vectors
were corrected for detector effects arising from the non-uniform acceptance
[67]. The single bracket $\langle\rangle$ in Eq. 3 refers to an average over
all the events, while the double brackets $\langle\langle\rangle\rangle$
denote the average over all particles in the considered $p_{\mathrm{T}}$
interval and all events. The SP denominator was obtained as a function of the
collision centrality.

The elliptic flow of $\mathrm{D_{s}^{+}}{}$ mesons cannot be directly measured
using Eq. 3 as signal candidates cannot be identified on a particle-by-
particle basis. The measured anisotropic flow coefficient
$v^{\mathrm{tot}}_{\mathrm{2}}$ can be written as a weighted sum of the
$v_{\mathrm{2}}$ of candidates reconstructed from true
$\mathrm{D_{s}^{+}}{}$-meson decays ($v^{\mathrm{sig}}_{\mathrm{2}}$) and that
of the background ($v^{\mathrm{bkg}}_{\mathrm{2}}$) [68]

$v^{\mathrm{tot}}_{\mathrm{2}}(M_{\mathrm{D}})=\frac{1}{N^{\mathrm{sig}}+N^{\mathrm{bkg}}+N^{\mathrm{D^{+}}}}(M_{\mathrm{D}})\bigg{[}N^{\mathrm{sig}}(M_{\mathrm{D}})v^{\mathrm{sig}}_{\mathrm{2}}+N^{\mathrm{bkg}}(M_{\mathrm{D}})v^{\mathrm{bkg}}_{\mathrm{2}}(M_{\mathrm{D}})+N^{\mathrm{D^{+}}}(M_{\mathrm{D}})v^{\mathrm{D^{+}}}_{\mathrm{2}}\bigg{]},$
(4)

where $N^{\mathrm{sig}}$ and $N^{\mathrm{bkg}}$ are the raw signal and
background yields, respectively. An additional
$v^{\mathrm{D^{+}}}_{\mathrm{2}}$ free parameter and the corresponding raw
yield $N^{\mathrm{D^{+}}}$ were included to account for the $\mathrm{D^{+}\to
K^{-}K^{+}\uppi^{+}}$ contribution to the measured
$v^{\mathrm{tot}}_{\mathrm{2}}$ distribution. A simultaneous fit to the
invariant-mass spectrum and the $v^{\mathrm{tot}}_{\mathrm{2}}$ distribution
as a function of the invariant mass was performed in each $p_{\mathrm{T}}$
interval to extract the elliptic flow coefficients. The fit function for the
invariant-mass distributions was composed of two Gaussian terms to describe
the signal and the peak due to the decay $\mathrm{D^{+}\to
K^{-}K^{+}\uppi^{+}}$, and an exponential distribution for the background, as
for the $R_{\mathrm{AA}}{}$ measurement of Section 3.1. The
$v^{\mathrm{sig}}_{\mathrm{2}}$ was measured from a fit to the
$v^{\mathrm{tot}}_{\mathrm{2}}$ distribution with the function of Eq. 4, where
$v^{\mathrm{bkg}}_{\mathrm{2}}(M_{\mathrm{D}})$ was described by a linear
function. Figure 2 shows the simultaneous fit to the invariant-mass spectrum
and $v_{2}^{\mathrm{tot}}(M_{\mathrm{D}})$ of $\mathrm{D_{s}^{+}}{}$ mesons in
the $4<p_{\mathrm{T}}{}<6~{}\mathrm{GeV}/c{}$ interval for the 30–50%
centrality interval.

Figure 2: Simultaneous fit to the invariant-mass spectrum and
$v_{2}(M_{\mathrm{D}})$ of $\mathrm{D_{s}^{+}}{}$-meson candidates in the
$4<p_{\mathrm{T}}{}<6~{}\mathrm{GeV}/c{}$ interval for the 30–50% centrality
interval. The solid blue and the dotted red curves represent the total and
combinatorial-background fit functions, respectively.

The reconstructed $\mathrm{D_{s}^{+}}{}$-meson signal is a mixture of prompt
$\mathrm{D_{s}^{+}}{}$ mesons and non-prompt $\mathrm{D_{s}^{+}}{}$ mesons
from beauty-hadron decays. Therefore, the $v^{\mathrm{sig}}_{\mathrm{2}}$ can
be expressed as a linear combination of prompt
($v^{\mathrm{prompt}}_{\mathrm{2}}$) and non-prompt
($v^{\mathrm{non\text{-}prompt}}_{\mathrm{2}}$) contributions weighted by the
fraction of prompt ($f_{\mathrm{prompt}}$) and non-prompt
$(1-f_{\mathrm{prompt}}{})$ $\mathrm{D_{s}^{+}}{}$ mesons in the extracted
signal, respectively. The fraction of promptly produced $\mathrm{D_{s}^{+}}{}$
mesons was estimated as a function of $p_{\mathrm{T}}$ with the theory-driven
method described in Section 3.1. The $v_{\mathrm{2}}{}$ coefficients of prompt
$\mathrm{D_{s}^{+}}{}$ mesons were obtained assuming
$v^{\mathrm{non\text{-}prompt}}_{\mathrm{2}}=v^{\mathrm{prompt}}_{\mathrm{2}}/2$.
This hypothesis is based on the $v_{\mathrm{2}}{}$ measurements of the non-
prompt $\mathrm{J}/\uppsi$ performed by ATLAS and CMS [69, 70], and on the
available model calculations [71, 72, 73] that indicate
$0<v^{\mathrm{non\text{-}prompt}}_{\mathrm{2}}<v^{\mathrm{prompt}}_{\mathrm{2}}$.

##  4 Systematic uncertainties

###  4.1 Nuclear modification factor measurement

The measurement of the $\mathrm{D_{s}^{+}}{}$-meson corrected yield is
affected by the following sources of systematic uncertainties: (i) the raw-
yield extraction from the invariant-mass distributions, (ii) the track-
reconstruction efficiency, (iii) the PID and selection efficiency, (iv) the
generated $\mathrm{D_{s}^{+}}{}$-meson $p_{\mathrm{T}}{}$ shape in the
simulation, and (v) the prompt fraction estimation. In addition, the
uncertainty due to the branching ratio of 3.6% [58], and that due to the
centrality-interval definition were considered. This last contribution arises
from the uncertainty of the fraction of the hadronic cross section used in the
Glauber fit to determine the centrality, and was estimated to be $<0.1$% and
2% for the 0–10% and 30–50% centrality intervals, respectively [63]. A
procedure similar to that described in Refs. [21, 20] was used to estimate the
uncertainties as a function of the $p_{\mathrm{T}}{}$ interval and the
centrality interval. The estimated values of the systematic uncertainties are
summarised in Table 1 for representative $p_{\mathrm{T}}{}$ intervals,
together with the total systematic uncertainty obtained from the sum in
quadrature of the different contributions.

Table 1: Relative systematic uncertainties of the prompt $\mathrm{D_{s}^{+}}{}$-meson corrected yield in Pb–Pb collisions for central and semicentral events in representative $p_{\mathrm{T}}{}$ intervals. Centrality interval | 0–10% | 30–50%
---|---|---
$p_{\mathrm{T}}~{}(\mathrm{GeV}/c)$ |  2–3 | 12–16 |  2–3 | 12–16
Yield extraction |  8% | 2% |  8% | 3%
Tracking efficiency |  12% | 12% |  10% | 8%
Selection efficiency |  9% | 4% |  5% | 3%
Prompt fraction |  ${}^{+8}_{-16}$% |  ${}^{+9}_{-18}$% |  ${}^{+8}_{-16}$% |  ${}^{+8}_{-17}$%
MC $p_{\mathrm{T}}$ shape |  5% | negl. |  3% | negl.
Centrality limits |  $<0.1$% | $2\%$
Branching ratio | 4%
Total syst. unc. |  ${}^{+20}_{-24}$% |  ${}^{+16}_{-23}$% |  ${}^{+17}_{-22}$% |  ${}^{+13}_{-20}$%

The systematic uncertainty of the raw-yield extraction was evaluated by
repeating the fit of the invariant- mass distribution varying the lower and
upper limits of the fit range, the bin width, and the functional form of the
background fit function. The systematic uncertainty was defined as the RMS of
the distribution of the signal yields obtained from all these variations and
ranges from 2% to 8% depending on the centrality interval and the
$p_{\mathrm{T}}{}$ interval.

The systematic uncertainty of the track-reconstruction efficiency was
estimated by varying the track- quality selection criteria and by comparing
the prolongation probability of the TPC tracks to the ITS hits in data and
simulation. The comparison was performed after weighting the relative
abundances of primary and secondary particles in the simulation to match those
observed in data [74]. The estimated uncertainty ranges from 5% to 14%.

The systematic uncertainty of the selection efficiency originates from
imperfections in the description of the detector resolutions and alignments in
the simulation. It was estimated by comparing the corrected yields obtained by
repeating the analysis with different selections on the BDT output, which
resulted in up to 50% higher and lower efficiencies with respect to the
central values. The assigned systematic uncertainty ranges from 3% to 9%.
Possible systematic effects due to the loose PID selection, applied prior to
the machine-learning one, were investigated comparing pion and kaon PID
selection efficiencies in data and in simulations. A pure sample of pions was
selected from $\mathrm{K^{0}_{S}}$ and $\mathrm{\Lambda}$ decays, while
samples of kaons in the TPC (TOF) were obtained applying a strict PID
selection using the TOF (TPC) information. Since no significant differences
were observed, no systematic uncertainty was assigned.

An additional contribution to the systematic uncertainty of the efficiency
originates from possible differences between the real and simulated
$\mathrm{D_{s}^{+}}{}$-meson $p_{\mathrm{T}}{}$ distributions. It was
estimated by calculating the efficiency using alternative
$\mathrm{D_{s}^{+}}{}$-meson $p_{\mathrm{T}}$ shapes obtained by re-weighting
the $p_{\mathrm{T}}$ distribution from MC simulations to match those predicted
by theoretical models. The $p_{\mathrm{T}}{}$ distributions from FONLL
calculations including or not hot-medium effects, parametrised using the
$p_{\mathrm{T}}{}$-differential $R_{\mathrm{AA}}{}$ from the LGR [34], PHSD
[75], TAMU [33], and Catania [35] models, were considered. The resulting
uncertainty was estimated to be about 5% and 3% for the 0–10% and 30–50%
centrality intervals, respectively, in the lowest $p_{\mathrm{T}}{}$ intervals
where the efficiency varies steeply with $p_{\mathrm{T}}{}$, and to decrease
to zero above $12~{}\mathrm{GeV}{}/c$.

The systematic uncertainty of the prompt fraction was estimated by varying the
FONLL parameters (b-quark mass, factorisation, and renormalisation scales,
according to the prescription reported in Ref. [76]) in the calculation of the
$p_{\mathrm{T}}{}$-differential production cross section of non-prompt
$\mathrm{D_{s}^{+}}{}$ mesons. In addition, the ratio of the non-prompt and
prompt $\mathrm{D_{s}^{+}}{}$-meson $R_{\mathrm{AA}}{}$ was varied in the
range
$\frac{1}{3}<R_{\mathrm{AA}}^{\mathrm{non\text{-}prompt}}/R_{\mathrm{AA}}^{\mathrm{prompt}}<3$
as done in Ref. [20]. The resulting uncertainty ranges between
${}^{+8}_{-16}$% and ${}^{+12}_{-23}$%.

In the $R_{\mathrm{AA}}{}$ calculation, the BR uncertainty of the
$\mathrm{D_{s}^{+}}{}$-meson yield in Pb–Pb collisions and of the pp reference
cross section cancels out in the ratio. The contribution due to the prompt
fraction uncertainty, estimated by the variation of the parameters of the
FONLL calculation, was considered to be fully correlated and the remaining
systematic uncertainties were propagated as uncorrelated. The uncertainties of
the $R_{\mathrm{AA}}{}$ normalisation are the quadratic sum of the pp
normalisation uncertainty, 2.1% [77], the $\left\langle
T_{\mathrm{AA}}{}\right\rangle$ uncertainty, 0.7% (1.5%) for the 0–10%
(30–50%) centrality interval [52], and the one related to the centrality-
interval definition described above.

###  4.2 Elliptic flow measurement

The systematic uncertainties of the measurement of the
$\mathrm{D_{s}^{+}}{}$-meson $v_{\mathrm{2}}$ coefficients were estimated with
procedures similar to those detailed in Ref. [26]. They include the following
sources: (i) the signal extraction from the invariant-mass and
$v^{\mathrm{tot}}_{\mathrm{2}}$ distributions, (ii) the non-prompt
$\mathrm{D_{s}^{+}}{}$ contribution, and (iii) the centrality dependence of
the SP denominator. The selection efficiency was observed to be independent of
the $\mathrm{D_{s}^{+}}{}$-meson azimuthal direction, therefore no
contribution to the systematic uncertainty was assigned. The non-flow effects
are naturally suppressed due to the pseudorapidity gap of at least 0.9 units
between the pseudorapidity interval used for the $\mathrm{D_{s}^{+}}$-meson
reconstruction, and the V0C used for the $\boldsymbol{Q}_{2}$-vector
determination. The estimated values of the systematic uncertainties are
summarised in Table 2 for representative $p_{\mathrm{T}}{}$ intervals.

Table 2: Systematic uncertainties of the prompt $\mathrm{D_{s}^{+}}{}$-meson $v_{\mathrm{2}}{}$ in Pb–Pb collisions for the 30–50% centrality interval in representative $p_{\mathrm{T}}{}$ intervals. The uncertainties of the fitting procedure and non-prompt contribution subtraction are quoted as absolute uncertainties, while that of the SP denominator as relative uncertainty. $p_{\mathrm{T}}~{}(\mathrm{GeV}/c)$ |  2–4 | 12–16
---|---|---
$M$ and $v_{\mathrm{2}}$ fits |  0.01 | 0.02
Non-prompt contribution |  ${}^{+0.031}_{-0.007}$ | ${}^{+0.028}_{-0.006}$
SP denominator | 0.5%

The uncertainty due to the simultaneous fit was estimated by repeating the fit
several times with different configurations, as done for the $R_{\mathrm{AA}}$
measurement. The RMS of the $v_{\mathrm{2}}$ distribution obtained from the
different trials, separately for each $p_{\mathrm{T}}$ interval, was assigned
as systematic uncertainty. The absolute systematic uncertainty values due to
the signal extraction range between 0.01 and 0.03 depending on
$p_{\mathrm{T}}{}$.

The systematic uncertainty related to the correction for the contribution of
non-prompt $\mathrm{D_{s}^{+}}{}$ to the measured $v_{\mathrm{2}}{}$ has two
main sources. The first one is due to the $f_{\mathrm{prompt}}$ calculation
and it was treated as described in Section 4.1 for the $R_{\mathrm{AA}}{}$
measurement. The second source is due to the assumption of
$v^{\mathrm{non\text{-}prompt}}_{\mathrm{2}}$ =
$v^{\mathrm{prompt}}_{\mathrm{2}}/2$. This was estimated by considering a flat
distribution of $v^{\mathrm{non\text{-}prompt}}_{\mathrm{2}}$ between 0 and
$v^{\mathrm{prompt}}_{\mathrm{2}}$ and by varying the central value of
$v^{\mathrm{non\text{-}prompt}}_{\mathrm{2}}$ by $\pm
v^{\mathrm{prompt}}_{\mathrm{2}}/\sqrt{12}$, corresponding to one standard
deviation. The values of the absolute systematic uncertainty from the non-
prompt correction range between ${}^{+0.020}_{-0.005}$ and
${}^{+0.039}_{-0.009}$ for the different $p_{\mathrm{T}}{}$ intervals.

The contribution of the SP denominator to the systematic uncertainty is due to
the centrality dependence. The uncertainty was evaluated as the difference of
the centrality integrated value, computed from the events in the 30–50%
interval, with that obtained as weighted average of SP-denominator values in
narrow centrality intervals using the $\mathrm{D_{s}^{+}}{}$-meson yields as
weights. A systematic uncertainty of 0.5$\%$ was assigned.

##  5 Results

Figure 3: $p_{\mathrm{T}}$-differential production yields of prompt
$\mathrm{D_{s}^{+}}$ mesons in the 0–10% and 30–50% centrality intervals in
Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02~{}\mathrm{TeV}$ compared to
the pp reference [64] scaled by the average nuclear overlap function
$\left\langle T_{\mathrm{AA}}\right\rangle$ of the corresponding centrality
interval. The open markers indicate where the pp reference is extrapolated
using FONLL calculations. The $p_{\mathrm{T}}$-differential yields in the
30–50% centrality interval and the corresponding pp reference are scaled by a
factor of $10^{-1}$ for better visibility. Statistical uncertainties (bars)
and systematic uncertainties (boxes) are shown.

The $p_{\mathrm{T}}$-differential production yields
$\mathrm{d}N/\mathrm{d}p_{\mathrm{T}}$ of prompt $\mathrm{D_{s}^{+}}$ mesons
measured in the 0–10% and 30–50% centrality intervals are shown in Fig. 3. For
the semicentral class of events, the measurements are scaled by $10^{-1}$ for
better visibility. The results are compared with the pp reference cross
section multiplied by the corresponding average nuclear overlap function
$\left\langle T_{\mathrm{AA}}\right\rangle$. The larger data sample and the
improved analysis technique enable an extended $p_{\mathrm{T}}$ coverage and
finer $p_{\mathrm{T}}$ intervals in the measured
$\mathrm{d}N/\mathrm{d}p_{\mathrm{T}}$ of prompt $\mathrm{D_{s}^{+}}$ mesons
compared to the previous measurement by the ALICE Collaboration in Pb–Pb
collisions at $\sqrt{s_{\mathrm{NN}}}=5.02~{}\mathrm{TeV}$ [20]. A strong
suppression of the $\mathrm{D_{s}^{+}}$ yields compared to the binary-scaled
pp reference is observed for both centrality intervals for
$p_{\mathrm{T}}>3\text{--}4~{}\mathrm{GeV}/c$, similarly as for the non-
strange D mesons [21]. This suppression is understood in terms of modification
of the charm-quark momentum spectra due to the interactions within the QGP.

Figure 4: Nuclear modification factor $R_{\mathrm{AA}}$ of prompt
$\mathrm{D_{s}^{+}}$ mesons in the 0–10% (left panel) and 30–50% (right panel)
centrality intervals in Pb–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}=5.02~{}\mathrm{TeV}$ compared with the one of prompt
non-strange D mesons (average of $\mathrm{D^{0}}$, $\mathrm{D^{+}}$, and
$\mathrm{D^{*+}}$) [21]. The empty (filled) boxes represent the species
uncorrelated (correlated) systematic uncertainties. The normalisation
uncertainty is represented by a filled box at $R_{\mathrm{AA}}=1$.

The nuclear modification factor $R_{\mathrm{AA}}$ of prompt
$\mathrm{D_{s}^{+}}$ mesons is compared with the average $R_{\mathrm{AA}}$ of
prompt $\mathrm{D^{0}}$, $\mathrm{D^{+}}$, and $\mathrm{D^{*+}}$ mesons in
Fig. 4 for the 0–10% and 30–50% centrality intervals, in the left and right
panels, respectively. The systematic uncertainties related to the tracking
efficiency and the prompt-fraction estimation are considered as fully
correlated between the different D-meson species, and are reported separately
from the other sources of systematic uncertainty which are uncorrelated. The
$R_{\mathrm{AA}}$ of $\mathrm{D_{s}^{+}}$ and non-strange D mesons show a
minimum value of about 0.2 (0.4) around $p_{\mathrm{T}}\approx
10~{}\mathrm{GeV}/c$ in the 0–10% (30–50%) centrality interval. For lower
$p_{\mathrm{T}}$, the $R_{\mathrm{AA}}$ increases with decreasing
$p_{\mathrm{T}}$ reaching about unity around $p_{\mathrm{T}}\approx
2\text{--}3~{}\mathrm{GeV}/c$. In both centrality intervals, the
$R_{\mathrm{AA}}$ of prompt $\mathrm{D_{s}^{+}}$ and non-strange D mesons are
compatible within uncertainties for $p_{\mathrm{T}}\gtrsim
10~{}\mathrm{GeV}/c$. In this $p_{\mathrm{T}}$ region, the hadronisation is
expected to occur mainly via fragmentation and the dominant effect leading to
the observed suppression is the charm-quark energy loss in the QGP. For lower
$p_{\mathrm{T}}$, the measured $R_{\mathrm{AA}}$ of prompt
$\mathrm{D_{s}^{+}}$ mesons is systematically higher than that of non-strange
D mesons but compatible within about one standard deviation of the combined
statistical and systematic uncertainties.

In the left and right panels of Fig. 5, the $R_{\mathrm{AA}}$ of prompt
$\mathrm{D_{s}^{+}}$ and non-strange D mesons in the 0–10% centrality interval
are compared with theoretical calculations implementing charm-quark transport
in the QGP [78]. All the models include an enhancement of the strangeness
content of the QGP and the hadronisation of charm quarks is implemented either
via fragmentation, which is dominant at high $p_{\mathrm{T}}$, or via
coalescence with light quarks in the QGP. In the Catania [35, 47] and LGR [34]
models the coalescence occurs instantaneously at the phase boundary and is
implemented through the Wigner formalism [79]. In the PHSD model [38, 75], the
hadronisation in heavy-ion collisions is described via a Monte Carlo
simulation of the coalescence process in competition to fragmentation. In the
TAMU [33] model, the hadronisation via coalescence proceeds via formation of
resonant states when approaching the (pseudo)critical temperature within the
formalism of a Resonance Recombination Model [11]. For the description of the
D-meson $p_{\mathrm{T}}$ spectra in pp collisions, all the models use as
starting point FONLL calculations [61, 62, 76]. Charm quarks are hadronised in
pp collisions with fragmentation in the PHSD and LGR models, while in the
Catania model the charm-quark hadronisation via coalescence is also
implemented in addition to that via fragmentation [80]. In pp collisions, the
hadronisation in the TAMU model is instead determined with a statistical
hadronisation approach, in which the strangeness production is suppressed in
pp with respect to heavy-ion collisions. This is described with a suppression
factor for strange particles of $\gamma_{\mathrm{s}}=0.6$ [81], which is
instead unity in heavy-ion collisions.

Figure 5: Nuclear modification factor $R_{\mathrm{AA}}$ of prompt
$\mathrm{D_{s}^{+}}$ mesons (left panel) and non-strange D mesons [21] (right
panel) in the 0–10% centrality interval in Pb–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}=5.02~{}\mathrm{TeV}$ compared with theoretical
calculations based on charm-quark transport in a hydrodynamically expanding
QGP implementing strangeness enhancement and hadronisation of charm quarks via
coalescence in addition to fragmentation in the vacuum [38, 75, 33, 34, 35].
The boxes represent the total systematic uncertainties. The colour bands
represent the theoretical uncertainty when available.

All the models reproduce qualitatively the measured $R_{\mathrm{AA}}$ of
prompt $\mathrm{D_{s}^{+}}$ and non-strange D mesons. The Catania model
underestimates both measurements for $2<p_{\mathrm{T}}<5~{}\mathrm{GeV}/c$ by
about $2\,\sigma$ of the combined statistical and systematic uncertainties of
the measured points, while it overestimates the non-strange D-meson
$R_{\mathrm{AA}}$ for $p_{\mathrm{T}}<1.5~{}\mathrm{GeV}/c$, where no
measurement is available for strange mesons. In contrast, the PHSD model
describes well the measured nuclear modification factors for
$p_{\mathrm{T}}<5~{}\mathrm{GeV}/c$ and underestimates them by about
$2\,\sigma$ for higher $p_{\mathrm{T}}$. The TAMU model describes the
measurements within uncertainties, with a tension of about $2\,\sigma$ of the
combined statistical and systematic uncertainties of the
$\mathrm{D_{s}^{+}}$-meson measurement in
$2<p_{\mathrm{T}}<3~{}\mathrm{GeV}/c$. These three models do not include
charm-quark interactions with medium constituents via radiative processes,
hence are not expected to describe the $R_{\mathrm{AA}}$ of strange and non-
strange D mesons for $p_{\mathrm{T}}>6\text{--}8~{}\mathrm{GeV}/c$. The LGR
model, which instead includes gluon-radiation processes, provides a good
description of the $R_{\mathrm{AA}}$ up to high $p_{\mathrm{T}}$. All the
models predict a smaller suppression of the $\mathrm{D_{s}^{+}}$-meson
$R_{\mathrm{AA}}$ compared to non-strange D mesons at low and intermediate
$p_{\mathrm{T}}$.

Figure 6: Top panels: $\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$
$p_{\mathrm{T}}$-differential production ratios in the 0–10% (left panel) and
30–50% (middle panel) centrality intervals in Pb–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}=5.02~{}\mathrm{TeV}$ and in pp collisions (right
panel) at the same centre-of-mass energy compared with theoretical
calculations based on charm-quark transport in a hydrodynamically expanding
QGP [38, 75, 33, 34, 47, 81, 80] and on statistical hadronisation [82]. Bottom
panels: $\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ $p_{\mathrm{T}}$-differential
ratios in Pb–Pb collisions divided by those in pp collisions, in the 0–10%
(left panel) and 30–50% (right panel) centrality intervals, compared with
theoretical calculations.

The possible enhancement of the yield of D mesons with strange-quark content
with respect to that of non-strange D mesons was further investigated by
computing the ratio between the $p_{\mathrm{T}}$-differential production
yields of prompt $\mathrm{D_{s}^{+}}$ mesons and those of prompt
$\mathrm{D^{0}}$ mesons [21]. The systematic uncertainty related to the
determination of the tracking efficiency and the contribution due to the
subtraction of the component from beauty-hadron decays were propagated as
fully correlated in the ratios, while all the other sources of systematic
uncertainties were considered as uncorrelated between the measurements of
$\mathrm{D_{s}^{+}}$ and $\mathrm{D^{0}}$ mesons. The top row of Fig. 6 shows
the $\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ yield ratios in the 0–10% (left panel)
and 30–50% (middle panel) centrality intervals compared to the same quantity
measured in minimum-bias pp collisions [64] (right panel) and to theoretical
calculations. The $\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ yield ratios in Pb–Pb
collisions divided by those measured in pp collisions are shown in the bottom
row of the same figure. The average values of the
$\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ ratios in the
$2<p_{\mathrm{T}}<8~{}\mathrm{GeV}/c$ interval are higher in Pb–Pb collisions
than those in pp collisions by about $2.3\sigma$ and $2.4\sigma$ of the
combined statistical and systematic uncertainties, for the 0–10% and 30–50%
centrality intervals, respectively. In central collisions, the measured
$\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ ratio is compatible with the one measured
by the STAR Collaboration in Au–Au collisions at
$\sqrt{s_{\mathrm{NN}}}=200~{}\mathrm{GeV}$ [44]. The
$\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ ratios in pp and in central (central and
semicentral) Pb–Pb collisions are described within uncertainties by the
Catania (PHSD) model. The TAMU model significantly overestimates the measured
$\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ by a similar amount in the two colliding
systems, leading to a good description of the ratio of the
$\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ measured in Pb–Pb and pp collisions, as
shown in the bottom panels of Fig. 6. While the Catania and PHSD models
predict a $\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ ratio almost $p_{\mathrm{T}}$
independent for $p_{\mathrm{T}}<3~{}\mathrm{GeV}/c$ and then mildly decreasing
towards the pp value at higher $p_{\mathrm{T}}$, the TAMU and LGR models
predict a peak around $p_{\mathrm{T}}\approx 3\text{--}4~{}\mathrm{GeV}/c$.
The origin of such a peak would be motivated by the different masses of
$\mathrm{D_{s}^{+}}$ and $\mathrm{D^{0}}$ mesons and by the collective radial
expansion of the system with a common flow-velocity profile, which imposes an
equal velocity boost to all particles in case of complete thermalisation. In
addition, also the hadronisation via coalescence is expected to modify the
$p_{\mathrm{T}}$ shape of the $\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ ratio due to
the different masses of u and s quarks. A similar $p_{\mathrm{T}}$ shape is
predicted by the GSI-Heidelberg statistical hadronisation model (SHMc) [82],
which is reported in the top panels of Fig. 6 for central and semicentral
Pb–Pb collisions, where the $p_{\mathrm{T}}$ spectra of charm hadrons are
modelled with a core-corona approach. The low-$p_{\mathrm{T}}$ region is
dominated by the core contribution described with a Blast Wave function. The
corona contribution is instead parametrised from measurements in pp collisions
and is relevant at high $p_{\mathrm{T}}$. The $p_{\mathrm{T}}$-spectra
modification due to resonance decays is computed using the FastReso package
[83]. Within the current uncertainties of the measurement, no firm conclusions
can be drawn on the $p_{\mathrm{T}}$ shape of the
$\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ ratio in Pb–Pb collisions at low and
intermediate $p_{\mathrm{T}}$. These results however provide important
indications about the role of the charm-quark hadronisation via coalescence in
the QGP, complementary to those obtained via the simultaneous comparison of
the measured D-meson $R_{\mathrm{AA}}$ and $v_{\mathrm{n}}$ coefficients [21,
26].

The visible production yield of prompt $\mathrm{D_{s}^{+}}$ mesons was
evaluated by integrating the $p_{\mathrm{T}}$-differential yield over the
narrower $p_{\mathrm{T}}$ intervals of the measurement. The systematic
uncertainties were propagated as fully correlated among the measured
$p_{\mathrm{T}}$ intervals, except for the raw-yield extraction uncertainty,
which was treated as uncorrelated considering the variations of the signal-to-
background ratio and the shape of the combinatorial-background distribution as
a function of $p_{\mathrm{T}}$. In order to obtain the
$p_{\mathrm{T}}$-integrated production yield, the
$\mathrm{d}N/\mathrm{d}p_{\mathrm{T}}$ was extrapolated in
$0<p_{\mathrm{T}}<2~{}\mathrm{GeV}/c$. For this purpose, the measured
$p_{\mathrm{T}}$-differential $\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ ratio was
interpolated using the shape predicted by the PHSD model and leaving the
normalisation as a free parameter. The extrapolated
$\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ ratio for
$p_{\mathrm{T}}<2~{}\mathrm{GeV}/c$ was then multiplied by the
$\mathrm{d}N/\mathrm{d}p_{\mathrm{T}}$ of $\mathrm{D^{0}}$ mesons measured in
the same $p_{\mathrm{T}}$ interval [21] to obtain the extrapolated
$\mathrm{D_{s}^{+}}$ yield, which amounts to about 70% of the total production
yield. An additional uncertainty was assigned to the extrapolation procedure,
by repeating the computation using the TAMU and Catania transport models, and
the SHMc to extrapolate the $\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ ratio in the
unmeasured $p_{\mathrm{T}}$ interval. Finally, the $p_{\mathrm{T}}$-integrated
production yield was obtained as the sum of the extrapolated one for
$p_{\mathrm{T}}<2~{}\mathrm{GeV}/c$ and the measured one. The results for the
0–10% and 30–50% centrality intervals are reported in Table 3. As for the
$\mathrm{D^{0}}$, $\mathrm{D^{+}}$, and $\mathrm{D^{*+}}$ mesons [21], the
production yield of prompt $\mathrm{D_{s}^{+}}$ mesons at midrapidity is
compatible within uncertainties with the one predicted by the SHMc. This
suggests that low-$p_{\mathrm{T}}$ charm quarks, which determine the total
yield, are thermalised in the QGP.

Table 3: Production yields of prompt $\mathrm{D_{s}^{+}}$ mesons in $|y|<0.5$ in Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02~{}\mathrm{TeV}$ compared to the predictions of the GSI-Heidelberg SHMc [82]. Centrality |  $\mathrm{d}N/\mathrm{d}y|_{|y|<0.5}$ |  GSI-Heidelberg SHMc
---|---|---
0–10% |  $1.89\pm 0.07(\mathrm{stat})^{+0.13}_{-0.16}(\mathrm{syst})^{+0.36}_{-0.55}(\mathrm{extr})\pm 0.07(\mathrm{BR})$ |  $2.22\pm 0.38$
30–50% |  $0.34\pm 0.01(\mathrm{stat})^{+0.02}_{-0.03}(\mathrm{syst})^{+0.11}_{-0.09}(\mathrm{extr})\pm 0.01(\mathrm{BR})$ |  $0.344\pm 0.056$
Figure 7: Elliptic flow coefficient $v_{2}$ of prompt $\mathrm{D_{s}^{+}}$
mesons in the 30–50% centrality interval in Pb–Pb collisions at
$\sqrt{s_{\mathrm{NN}}}=5.02~{}\mathrm{TeV}$ compared with that of non-strange
D mesons [26] (left panel) and with theoretical calculations based on the
charm-quark transport in a hydrodynamically expanding QGP [38, 33] (right
panel).

The degree of thermalisation of charm quarks and their hadronisation in the
QGP were also studied via the measurement of the azimuthal anisotropy in the
prompt $\mathrm{D_{s}^{+}}$-meson production. Figure 7 shows the elliptic flow
coefficient $v_{2}$ of prompt $\mathrm{D_{s}^{+}}$ mesons for the 30–50%
centrality interval measured in the transverse-momentum interval
$2<p_{\mathrm{T}}<24~{}\mathrm{GeV}/c$, compared with that of prompt non-
strange D mesons (left panel) and with theoretical calculations (right panel).
The rapidity interval of the measurement, $|y|<0.8$, is wider than that quoted
for the $R_{\mathrm{AA}}$ since no correction for the rapidity acceptance was
applied. The measurement was carried out in finer $p_{\mathrm{T}}$ intervals
and has uncertainties reduced by a factor up to four with respect to the
previous measurement [48], thanks to the more advanced
$\mathrm{D_{s}^{+}}$-meson selection technique and the larger data sample.
Considering as null hypothesis $v_{2}=0$, the probability to observe the
measured positive $v_{2}$ in $2<p_{\mathrm{T}}<8~{}\mathrm{GeV}/c$ corresponds
to a significance of $6.4\sigma$, confirming the participation of the charm
quark in the collective motion of the system, as already observed for non-
strange D mesons [48, 26]. However, within the current uncertainties it is not
possible to draw a conclusion about a potential difference between the
elliptic flow of strange and non-strange D mesons, which would be motivated by
the different mass, the charm-quark hadronisation via recombination with
strange quarks in the medium instead of light quarks [84], and possible
differences in the hadronic phase [43]. The measured
$\mathrm{D_{s}^{+}}$-meson $v_{2}$ is compatible within uncertainties with the
predictions of the TAMU and PHSD models, which include charm-quark coalescence
with flowing strange quarks in the medium.

##  6 Summary

In this Letter, a comprehensive and high-precision set of measurements
regarding the prompt $\mathrm{D_{s}^{+}}$-meson production at midrapidity in
Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02~{}\mathrm{TeV}$ was reported.

The $p_{\mathrm{T}}$-differential production yields were measured in a wide
transverse-momentum interval between 2–50 (2–36) $\mathrm{GeV}/c$ in the 0–10%
(30–50%) centrality interval. They were used to compute the
$p_{\mathrm{T}}$-differential $R_{\mathrm{AA}}$ and the ratio of
$\mathrm{D_{s}^{+}}$-meson production relative to $\mathrm{D^{0}}$ mesons. The
measured $R_{\mathrm{AA}}$ shows a strong suppression of the
$\mathrm{D_{s}^{+}}$-meson production yield compared to the binary-scaled pp
reference, reaching a minimum of about 0.2 (0.4) around $p_{\mathrm{T}}\approx
10~{}\mathrm{GeV}/c$ in the 0–10% (30–50%) centrality interval. For lower
$p_{\mathrm{T}}$, the $R_{\mathrm{AA}}$ increases reaching about unity for
$p_{\mathrm{T}}\approx 2\text{--}3~{}\mathrm{GeV}/c$. The
$\mathrm{D_{s}^{+}}/\mathrm{D^{0}}$ yield ratios in Pb–Pb collisions are
higher than those measured in pp collisions for $p_{\mathrm{T}}\lesssim
8~{}\mathrm{GeV}/c$ with a significance of $2.3\sigma$ and $2.4\sigma$ in the
0–10% and 30–50% centrality intervals, respectively. This finding is
consistent with the predictions of theoretical calculations implementing the
charm-quark transport in a hydrodynamically expanding QGP, which include an
enhanced strange-quark production in the medium and the charm-quark
hadronisation via coalescence. The production yield of prompt
$\mathrm{D_{s}^{+}}$ mesons, extrapolated down to $p_{\mathrm{T}}=0$, in the
0–10% centrality interval is compatible with the prediction of the SHMc,
suggesting that the bulk of charm quarks are thermalised in the QGP.

The elliptic flow coefficient $v_{2}$ of prompt $\mathrm{D_{s}^{+}}$ mesons
was measured as a function of $p_{\mathrm{T}}$ in the 30–50% centrality
interval. The $\mathrm{D_{s}^{+}}$-meson $v_{2}$ in
$2<p_{\mathrm{T}}<8~{}\mathrm{GeV}/c$ is positive with a significance of
$6.4\sigma$ and is compatible within uncertainties with that of non-strange D
mesons. The measured $v_{2}$ is also described by several transport-model
calculations implementing the charm-quark hadronisation via coalescence.

The data reported in this Letter represent the most precise measurements of
prompt $\mathrm{D_{s}^{+}}$-meson production in heavy-ion collisions at LHC
energies to date, and provide stringent constraints to all models on the
production of charm quarks and their hadronisation in the QGP. Future data
samples that will be collected with the upgraded ALICE detector in Run 3 will
have the potential to further improve and extend to lower $p_{\mathrm{T}}$ the
measurement of $\mathrm{D_{s}^{+}}$ mesons in heavy-ion collisions [85].

## 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; Ministry of Education of China (MOEC) , Ministry of Science & Technology of China (MSTC) and National Natural Science Foundation of China (NSFC), China; Ministry of Science and Education and Croatian Science Foundation, Croatia; Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Cubaenergía, Cuba; Ministry of Education, Youth and Sports of the Czech Republic, Czech Republic; The Danish Council for Independent Research | Natural Sciences, the VILLUM FONDEN and Danish National Research Foundation (DNRF), Denmark; Helsinki Institute of Physics (HIP), Finland; Commissariat à l’Energie Atomique (CEA) and Institut National de Physique Nucléaire et de Physique des Particules (IN2P3) and Centre National de la Recherche Scientifique (CNRS), France; Bundesministerium für Bildung und Forschung (BMBF) and GSI Helmholtzzentrum für Schwerionenforschung GmbH, Germany; General Secretariat for Research and Technology, Ministry of Education, Research and Religions, Greece; National Research, Development and Innovation Office, Hungary; Department of Atomic Energy Government of India (DAE), Department of Science and Technology, Government of India (DST), University Grants Commission, Government of India (UGC) and Council of Scientific and Industrial Research (CSIR), India; Indonesian Institute of Science, Indonesia; Istituto Nazionale di Fisica Nucleare (INFN), Italy; Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan Society for the Promotion of Science (JSPS) KAKENHI and Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT)of Applied Science (IIST), Japan; Consejo Nacional de Ciencia (CONACYT) y Tecnología, through Fondo de Cooperación Internacional en Ciencia y Tecnología (FONCICYT) and Dirección General de Asuntos del Personal Academico (DGAPA), Mexico; Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), Netherlands; The Research Council of Norway, Norway; Commission on Science and Technology for Sustainable Development in the South (COMSATS), Pakistan; Pontificia Universidad Católica del Perú, Peru; Ministry of Education and Science, National Science Centre and WUT ID-UB, Poland; Korea Institute of Science and Technology Information and National Research Foundation of Korea (NRF), Republic of Korea; Ministry of Education and Scientific Research, Institute of Atomic Physics and Ministry of Research and Innovation and Institute of Atomic Physics, Romania; Joint Institute for Nuclear Research (JINR), Ministry of Education and Science of the Russian Federation, National Research Centre Kurchatov Institute, Russian Science Foundation and Russian Foundation for Basic Research, Russia; Ministry of Education, Science, Research and Sport of the Slovak Republic, Slovakia; National Research Foundation of South Africa, South Africa; Swedish Research Council (VR) and Knut & Alice Wallenberg Foundation (KAW), Sweden; European Organization for Nuclear Research, Switzerland; Suranaree University of Technology (SUT), National Science and Technology Development Agency (NSDTA) and Office of the Higher Education Commission under NRU project of Thailand, Thailand; Turkish Energy, Nuclear and Mineral Research Agency (TENMAK), Turkey; National Academy of Sciences of Ukraine, Ukraine; Science and Technology Facilities Council (STFC), United Kingdom; National Science Foundation of the United States of America (NSF) and United States Department of Energy, Office of Nuclear Physics (DOE NP), United States of America.

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##  Appendix A The ALICE Collaboration

S. Acharya143, D. Adamová98, A. Adler76, J. Adolfsson83, G. Aglieri Rinella35,
M. Agnello31, N. Agrawal55, Z. Ahammed143, S. Ahmad16, S.U. Ahn78, I. Ahuja39,
Z. Akbar52, A. Akindinov95, M. Al-Turany110, S.N. Alam16,41, D. Aleksandrov91,
B. Alessandro61, H.M. Alfanda7, R. Alfaro Molina73, B. Ali16, Y. Ali14, A.
Alici26, N. Alizadehvandchali127, A. Alkin35, J. Alme21, T. Alt70, L.
Altenkamper21, I. Altsybeev115, M.N. Anaam7, C. Andrei49, D. Andreou93, A.
Andronic146, M. Angeletti35, V. Anguelov107, F. Antinori58, P. Antonioli55, C.
Anuj16, N. Apadula82, L. Aphecetche117, H. Appelshäuser70, S. Arcelli26, R.
Arnaldi61, I.C. Arsene20, M. Arslandok148,107, A. Augustinus35, R.
Averbeck110, S. Aziz80, M.D. Azmi16, A. Badalà57, Y.W. Baek42, X. Bai131,110,
R. Bailhache70, Y. Bailung51, R. Bala104, A. Balbino31, A. Baldisseri140, B.
Balis2, D. Banerjee4, R. Barbera27, L. Barioglio108, M. Barlou87, G.G.
Barnaföldi147, L.S. Barnby97, V. Barret137, C. Bartels130, K. Barth35, E.
Bartsch70, F. Baruffaldi28, N. Bastid137, S. Basu83, G. Batigne117, B.
Batyunya77, D. Bauri50, J.L. Bazo Alba114, I.G. Bearden92, C. Beattie148, I.
Belikov139, A.D.C. Bell Hechavarria146, F. Bellini26, R. Bellwied127, S.
Belokurova115, V. Belyaev96, G. Bencedi147,71, S. Beole25, A. Bercuci49, Y.
Berdnikov101, A. Berdnikova107, L. Bergmann107, M.G. Besoiu69, L. Betev35,
P.P. Bhaduri143, A. Bhasin104, I.R. Bhat104, M.A. Bhat4, B. Bhattacharjee43,
P. Bhattacharya23, L. Bianchi25, N. Bianchi53, J. Bielčík38, J. Bielčíková98,
J. Biernat120, A. Bilandzic108, G. Biro147, S. Biswas4, J.T. Blair121, D.
Blau91,84, M.B. Blidaru110, C. Blume70, G. Boca29,59, F. Bock99, A.
Bogdanov96, S. Boi23, J. Bok63, L. Boldizsár147, A. Bolozdynya96, M.
Bombara39, P.M. Bond35, G. Bonomi142,59, H. Borel140, A. Borissov84, H.
Bossi148, E. Botta25, L. Bratrud70, P. Braun-Munzinger110, M. Bregant123, M.
Broz38, G.E. Bruno109,34, M.D. Buckland130, D. Budnikov111, H. Buesching70, S.
Bufalino31, O. Bugnon117, P. Buhler116, Z. Buthelezi74,134, J.B. Butt14, A.
Bylinkin129, S.A. Bysiak120, M. Cai28,7, H. Caines148, A. Caliva110, E. Calvo
Villar114, J.M.M. Camacho122, R.S. Camacho46, P. Camerini24, F.D.M. Canedo123,
F. Carnesecchi35,26, R. Caron140, J. Castillo Castellanos140, E.A.R. Casula23,
F. Catalano31, C. Ceballos Sanchez77, P. Chakraborty50, S. Chandra143, S.
Chapeland35, M. Chartier130, S. Chattopadhyay143, S. Chattopadhyay112, A.
Chauvin23, T.G. Chavez46, T. Cheng7, C. Cheshkov138, B. Cheynis138, V.
Chibante Barroso35, D.D. Chinellato124, S. Cho63, P. Chochula35, P.
Christakoglou93, C.H. Christensen92, P. Christiansen83, T. Chujo136, C.
Cicalo56, L. Cifarelli26, F. Cindolo55, M.R. Ciupek110, G. ClaiII,55, J.
CleymansI,126, F. Colamaria54, J.S. Colburn113, D. Colella109,54,34,147, A.
Collu82, M. Colocci35, M. ConcasIII,61, G. Conesa Balbastre81, Z. Conesa del
Valle80, G. Contin24, J.G. Contreras38, M.L. Coquet140, T.M. Cormier99, P.
Cortese32, M.R. Cosentino125, F. Costa35, S. Costanza29,59, P. Crochet137, R.
Cruz-Torres82, E. Cuautle71, P. Cui7, L. Cunqueiro99, A. Dainese58, M.C.
Danisch107, A. Danu69, I. Das112, P. Das89, P. Das4, S. Das4, S. Dash50, S.
De89, A. De Caro30, G. de Cataldo54, L. De Cilladi25, J. de Cuveland40, A. De
Falco23, D. De Gruttola30, N. De Marco61, C. De Martin24, S. De Pasquale30, S.
Deb51, H.F. Degenhardt123, K.R. Deja144, L. Dello Stritto30, W. Deng7, P.
Dhankher19, D. Di Bari34, A. Di Mauro35, R.A. Diaz8, T. Dietel126, Y.
Ding138,7, R. Divià35, D.U. Dixit19, Ø. Djuvsland21, U. Dmitrieva65, J. Do63,
A. Dobrin69, B. Dönigus70, O. Dordic20, A.K. Dubey143, A. Dubla110,93, S.
Dudi103, P. Dupieux137, N. Dzalaiova13, T.M. Eder146, R.J. Ehlers99, V.N.
Eikeland21, F. Eisenhut70, D. Elia54, B. Erazmus117, F. Ercolessi26, F.
Erhardt102, A. Erokhin115, M.R. Ersdal21, B. Espagnon80, G. Eulisse35, D.
Evans113, S. Evdokimov94, L. Fabbietti108, M. Faggin28, J. Faivre81, F. Fan7,
A. Fantoni53, M. Fasel99, P. Fecchio31, A. Feliciello61, G. Feofilov115, A.
Fernández Téllez46, A. Ferrero140, A. Ferretti25, V.J.G. Feuillard107, J.
Figiel120, S. Filchagin111, D. Finogeev65, F.M. Fionda56,21, G.
Fiorenza35,109, F. Flor127, A.N. Flores121, S. Foertsch74, P. Foka110, S.
Fokin91, E. Fragiacomo62, E. Frajna147, A. Francisco137, U. Fuchs35, N.
Funicello30, C. Furget81, A. Furs65, J.J. Gaardhøje92, M. Gagliardi25, A.M.
Gago114, A. Gal139, C.D. Galvan122, P. Ganoti87, C. Garabatos110, J.R.A.
Garcia46, E. Garcia-Solis10, K. Garg117, C. Gargiulo35, A. Garibli90, K.
Garner146, P. Gasik110, E.F. Gauger121, A. Gautam129, M.B. Gay Ducati72, M.
Germain117, P. Ghosh143, S.K. Ghosh4, M. Giacalone26, P. Gianotti53, P.
Giubellino110,61, P. Giubilato28, A.M.C. Glaenzer140, P. Glässel107, D.J.Q.
Goh85, V. Gonzalez145, L.H. González-Trueba73, S. Gorbunov40, M. Gorgon2, L.
Görlich120, S. Gotovac36, V. Grabski73, L.K. Graczykowski144, L. Greiner82, A.
Grelli64, C. Grigoras35, V. Grigoriev96, S. Grigoryan77,1, F. Grosa35,61, J.F.
Grosse-Oetringhaus35, R. Grosso110, G.G. Guardiano124, R. Guernane81, M.
Guilbaud117, K. Gulbrandsen92, T. Gunji135, W. Guo7, A. Gupta104, R. Gupta104,
S.P. Guzman46, L. Gyulai147, M.K. Habib110, C. Hadjidakis80, G. Halimoglu70,
H. Hamagaki85, G. Hamar147, M. Hamid7, R. Hannigan121, M.R. Haque144,89, A.
Harlenderova110, J.W. Harris148, A. Harton10, J.A. Hasenbichler35, H.
Hassan99, D. Hatzifotiadou55, P. Hauer44, L.B. Havener148, S.T. Heckel108, E.
Hellbär110, H. Helstrup37, T. Herman38, E.G. Hernandez46, G. Herrera Corral9,
F. Herrmann146, K.F. Hetland37, H. Hillemanns35, C. Hills130, B. Hippolyte139,
B. Hofman64, B. Hohlweger93, J. Honermann146, G.H. Hong149, D. Horak38, S.
Hornung110, A. Horzyk2, R. Hosokawa15, Y. Hou7, P. Hristov35, C. Hughes133, P.
Huhn70, L.M. Huhta128, T.J. Humanic100, H. Hushnud112, L.A. Husova146, A.
Hutson127, D. Hutter40, J.P. Iddon35,130, R. Ilkaev111, H. Ilyas14, M.
Inaba136, G.M. Innocenti35, M. Ippolitov91, A. Isakov38,98, M.S. Islam112, M.
Ivanov110, V. Ivanov101, V. Izucheev94, M. Jablonski2, B. Jacak82, N.
Jacazio35, P.M. Jacobs82, S. Jadlovska119, J. Jadlovsky119, S. Jaelani64, C.
Jahnke124,123, M.J. Jakubowska144, A. Jalotra104, M.A. Janik144, T. Janson76,
M. Jercic102, O. Jevons113, A.A.P. Jimenez71, F. Jonas99,146, P.G. Jones113,
J.M. Jowett 35,110, J. Jung70, M. Jung70, A. Junique35, A. Jusko113, J.
Kaewjai118, P. Kalinak66, A.S. Kalteyer110, A. Kalweit35, V. Kaplin96, A.
Karasu Uysal79, D. Karatovic102, O. Karavichev65, T. Karavicheva65, P.
Karczmarczyk144, E. Karpechev65, A. Kazantsev91, U. Kebschull76, R. Keidel48,
D.L.D. Keijdener64, M. Keil35, B. Ketzer44, Z. Khabanova93, A.M. Khan7, S.
Khan16, A. Khanzadeev101, Y. Kharlov94,84, A. Khatun16, A. Khuntia120, B.
Kileng37, B. Kim17,63, C. Kim17, D.J. Kim128, E.J. Kim75, J. Kim149, J.S.
Kim42, J. Kim107, J. Kim149, J. Kim75, M. Kim107, S. Kim18, T. Kim149, S.
Kirsch70, I. Kisel40, S. Kiselev95, A. Kisiel144, J.P. Kitowski2, J.L. Klay6,
J. Klein35, S. Klein82, C. Klein-Bösing146, M. Kleiner70, T. Klemenz108, A.
Kluge35, A.G. Knospe127, C. Kobdaj118, M.K. Köhler107, T. Kollegger110, A.
Kondratyev77, N. Kondratyeva96, E. Kondratyuk94, J. Konig70, S.A.
Konigstorfer108, P.J. Konopka35, G. Kornakov144, S.D. Koryciak2, A.
Kotliarov98, O. Kovalenko88, V. Kovalenko115, M. Kowalski120, I. Králik66, A.
Kravčáková39, L. Kreis110, M. Krivda113,66, F. Krizek98, K. Krizkova
Gajdosova38, M. Kroesen107, M. Krüger70, E. Kryshen101, M. Krzewicki40, V.
Kučera35, C. Kuhn139, P.G. Kuijer93, T. Kumaoka136, D. Kumar143, L. Kumar103,
N. Kumar103, S. Kundu35, P. Kurashvili88, A. Kurepin65, A.B. Kurepin65, A.
Kuryakin111, S. Kushpil98, J. Kvapil113, M.J. Kweon63, J.Y. Kwon63, Y.
Kwon149, S.L. La Pointe40, P. La Rocca27, Y.S. Lai82, A. Lakrathok118, M.
Lamanna35, R. Langoy132, K. Lapidus35, P. Larionov35,53, E. Laudi35, L.
Lautner35,108, R. Lavicka116,38, T. Lazareva115, R. Lea142,24,59, J.
Lehrbach40, R.C. Lemmon97, I. León Monzón122, E.D. Lesser19, M.
Lettrich35,108, P. Lévai147, X. Li11, X.L. Li7, J. Lien132, R. Lietava113, B.
Lim17, S.H. Lim17, V. Lindenstruth40, A. Lindner49, C. Lippmann110, A. Liu19,
D.H. Liu7, J. Liu130, I.M. Lofnes21, V. Loginov96, C. Loizides99, P. Loncar36,
J.A. Lopez107, X. Lopez137, E. López Torres8, J.R. Luhder146, M. Lunardon28,
G. Luparello62, Y.G. Ma41, A. Maevskaya65, M. Mager35, T. Mahmoud44, A.
Maire139, M. Malaev101, N.M. Malik104, Q.W. Malik20, L. MalininaIV,77, D.
Mal’Kevich95, D. Mallick89, N. Mallick51, P. Malzacher110, G. Mandaglio33,57,
V. Manko91, F. Manso137, V. Manzari54, Y. Mao7, J. Mareš68, G.V.
Margagliotti24, A. Margotti55, A. Marín110, C. Markert121, M. Marquard70, N.A.
Martin107, P. Martinengo35, J.L. Martinez127, M.I. Martínez46, G. Martínez
García117, S. Masciocchi110, M. Masera25, A. Masoni56, L. Massacrier80, A.
Mastroserio141,54, A.M. Mathis108, O. Matonoha83, P.F.T. Matuoka123, A.
Matyja120, C. Mayer120, A.L. Mazuecos35, F. Mazzaschi25, M. Mazzilli35, M.A.
MazzoniI,60, J.E. Mdhluli134, A.F. Mechler70, F. Meddi22, Y. Melikyan65, A.
Menchaca-Rocha73, E. Meninno116,30, A.S. Menon127, M. Meres13, S.
Mhlanga126,74, Y. Miake136, L. Micheletti61, L.C. Migliorin138, D.L.
Mihaylov108, K. Mikhaylov77,95, A.N. Mishra147, D. Miśkowiec110, A. Modak4,
A.P. Mohanty64, B. Mohanty89, M. Mohisin KhanV,16, M.A. Molander45, Z.
Moravcova92, C. Mordasini108, D.A. Moreira De Godoy146, I. Morozov65, A.
Morsch35, T. Mrnjavac35, V. Muccifora53, E. Mudnic36, D. Mühlheim146, S.
Muhuri143, J.D. Mulligan82, A. Mulliri23, M.G. Munhoz123, R.H. Munzer70, H.
Murakami135, S. Murray126, L. Musa35, J. Musinsky66, J.W. Myrcha144, B.
Naik134,50, R. Nair88, B.K. Nandi50, R. Nania55, E. Nappi54, A.F.
Nassirpour83, A. Nath107, C. Nattrass133, A. Neagu20, L. Nellen71, S.V.
Nesbo37, G. Neskovic40, D. Nesterov115, B.S. Nielsen92, S. Nikolaev91, S.
Nikulin91, V. Nikulin101, F. Noferini55, S. Noh12, P. Nomokonov77, J.
Norman130, N. Novitzky136, P. Nowakowski144, A. Nyanin91, J. Nystrand21, M.
Ogino85, A. Ohlson83, V.A. Okorokov96, J. Oleniacz144, A.C. Oliveira Da
Silva133, M.H. Oliver148, A. Onnerstad128, C. Oppedisano61, A. Ortiz
Velasquez71, T. Osako47, A. Oskarsson83, J. Otwinowski120, M. Oya47, K.
Oyama85, Y. Pachmayer107, S. Padhan50, D. Pagano142,59, G. Paić71, A.
Palasciano54, J. Pan145, S. Panebianco140, P. Pareek143, J. Park63, J.E.
Parkkila128, S.P. Pathak127, R.N. Patra104,35, B. Paul23, H. Pei7, T.
Peitzmann64, X. Peng7, L.G. Pereira72, H. Pereira Da Costa140, D.
Peresunko91,84, G.M. Perez8, S. Perrin140, Y. Pestov5, V. Petráček38, M.
Petrovici49, R.P. Pezzi117,72, S. Piano62, M. Pikna13, P. Pillot117, O.
Pinazza55,35, L. Pinsky127, C. Pinto27, S. Pisano53, M. Płoskoń82, M.
Planinic102, F. Pliquett70, M.G. Poghosyan99, B. Polichtchouk94, S.
Politano31, N. Poljak102, A. Pop49, S. Porteboeuf-Houssais137, J. Porter82, V.
Pozdniakov77, S.K. Prasad4, R. Preghenella55, F. Prino61, C.A. Pruneau145, I.
Pshenichnov65, M. Puccio35, S. Qiu93, L. Quaglia25, R.E. Quishpe127, S.
Ragoni113, A. Rakotozafindrabe140, L. Ramello32, F. Rami139, S.A.R. Ramirez46,
A.G.T. Ramos34, T.A. Rancien81, R. Raniwala105, S. Raniwala105, S.S.
Räsänen45, R. Rath51, I. Ravasenga93, K.F. Read99,133, A.R. Redelbach40, K.
RedlichVI,88, A. Rehman21, P. Reichelt70, F. Reidt35, H.A. Reme-ness37, R.
Renfordt70, Z. Rescakova39, K. Reygers107, A. Riabov101, V. Riabov101, T.
Richert83, M. Richter20, W. Riegler35, F. Riggi27, C. Ristea69, M. Rodríguez
Cahuantzi46, K. Røed20, R. Rogalev94, E. Rogochaya77, T.S. Rogoschinski70, D.
Rohr35, D. Röhrich21, P.F. Rojas46, P.S. Rokita144, F. Ronchetti53, A.
Rosano33,57, E.D. Rosas71, A. Rossi58, A. Rotondi29,59, A. Roy51, P. Roy112,
S. Roy50, N. Rubini26, O.V. Rueda83, R. Rui24, B. Rumyantsev77, P.G. Russek2,
R. Russo93, A. Rustamov90, E. Ryabinkin91, Y. Ryabov101, A. Rybicki120, H.
Rytkonen128, W. Rzesa144, O.A.M. Saarimaki45, R. Sadek117, S. Sadovsky94, J.
Saetre21, K. Šafařík38, S.K. Saha143, S. Saha89, B. Sahoo50, P. Sahoo50, R.
Sahoo51, S. Sahoo67, D. Sahu51, P.K. Sahu67, J. Saini143, S. Sakai136, M.P.
Salvan110, S. Sambyal104, V. SamsonovI,101,96, D. Sarkar145, N. Sarkar143, P.
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Schiaua49, R. Schicker107, A. Schmah107, C. Schmidt110, H.R. Schmidt106, M.O.
Schmidt35,107, M. Schmidt106, N.V. Schmidt99,70, A.R. Schmier133, R.
Schotter139, J. Schukraft35, K. Schwarz110, K. Schweda110, G. Scioli26, E.
Scomparin61, J.E. Seger15, Y. Sekiguchi135, D. Sekihata135, I.
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Šerkšnytė108, A. Sevcenco69, T.J. Shaba74, A. Shabanov65, A. Shabetai117, R.
Shahoyan35, W. Shaikh112, A. Shangaraev94, A. Sharma103, H. Sharma120, M.
Sharma104, N. Sharma103, S. Sharma104, U. Sharma104, O. Sheibani127, K.
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T.B. Skaali20, G. Skorodumovs107, M. Slupecki45, N. Smirnov148, R.J.M.
Snellings64, C. Soncco114, J. Song127, A. Songmoolnak118, F. Soramel28, S.
Sorensen133, I. Sputowska120, J. Stachel107, I. Stan69, P.J. Steffanic133,
S.F. Stiefelmaier107, D. Stocco117, I. Storehaug20, M.M. Storetvedt37, P.
Stratmann146, C.P. Stylianidis93, A.A.P. Suaide123, T. Sugitate47, C. Suire80,
M. Sukhanov65, M. Suljic35, R. Sultanov95, V. Sumberia104, S. Sumowidagdo52,
S. Swain67, A. Szabo13, I. Szarka13, U. Tabassam14, S.F. Taghavi108, G.
Taillepied137, J. Takahashi124, G.J. Tambave21, S. Tang137,7, Z. Tang131, J.D.
Tapia TakakiVII,129, M. Tarhini117, M.G. Tarzila49, A. Tauro35, G. Tejeda
Muñoz46, A. Telesca35, L. Terlizzi25, C. Terrevoli127, G. Tersimonov3, S.
Thakur143, D. Thomas121, R. Tieulent138, A. Tikhonov65, A.R. Timmins127, M.
Tkacik119, A. Toia70, N. Topilskaya65, M. Toppi53, F. Torales-Acosta19, T.
Tork80, S.R. Torres38, A. Trifiró33,57, S. Tripathy55,71, T. Tripathy50, S.
Trogolo35,28, V. Trubnikov3, W.H. Trzaska128, T.P. Trzcinski144, B.A.
Trzeciak38, A. Tumkin111, R. Turrisi58, T.S. Tveter20, K. Ullaland21, A.
Uras138, M. Urioni59,142, G.L. Usai23, M. Vala39, N. Valle29,59, S. Vallero61,
N. van der Kolk64, L.V.R. van Doremalen64, M. van Leeuwen93, P. Vande Vyvre35,
D. Varga147, Z. Varga147, M. Varga-Kofarago147, M. Vasileiou87, A. Vasiliev91,
O. Vázquez Doce53,108, V. Vechernin115, A. Velure21, E. Vercellin25, S.
Vergara Limón46, L. Vermunt64, R. Vértesi147, M. Verweij64, L. Vickovic36, Z.
Vilakazi134, O. Villalobos Baillie113, G. Vino54, A. Vinogradov91, T.
Virgili30, V. Vislavicius92, A. Vodopyanov77, B. Volkel35,107, M.A. Völkl107,
K. Voloshin95, S.A. Voloshin145, G. Volpe34, B. von Haller35, I. Vorobyev108,
D. Voscek119, N. Vozniuk65, J. Vrláková39, B. Wagner21, C. Wang41, D. Wang41,
M. Weber116, R.J.G.V. Weelden93, A. Wegrzynek35, S.C. Wenzel35, J.P.
Wessels146, J. Wiechula70, J. Wikne20, G. Wilk88, J. Wilkinson110, G.A.
Willems146, B. Windelband107, M. Winn140, W.E. Witt133, J.R. Wright121, W.
Wu41, Y. Wu131, R. Xu7, A.K. Yadav143, S. Yalcin79, Y. Yamaguchi47, K.
Yamakawa47, S. Yang21, S. Yano47, Z. Yin7, H. Yokoyama64, I.-K. Yoo17, J.H.
Yoon63, S. Yuan21, A. Yuncu107, V. Zaccolo24, C. Zampolli35, H.J.C. Zanoli64,
N. Zardoshti35, A. Zarochentsev115, P. Závada68, N. Zaviyalov111, M.
Zhalov101, B. Zhang7, S. Zhang41, X. Zhang7, Y. Zhang131, V.
Zherebchevskii115, Y. Zhi11, N. Zhigareva95, D. Zhou7, Y. Zhou92, J. Zhu7,110,
Y. Zhu7, A. Zichichi26, G. Zinovjev3, N. Zurlo142,59

Affiliation Notes

I Deceased

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

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

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

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

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

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

Collaboration Institutes

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

2 AGH University of Science and Technology, Cracow, Poland

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

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

5 Budker Institute for Nuclear Physics, Novosibirsk, Russia

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

7 Central China Normal University, Wuhan, China

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

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

10 Chicago State University, Chicago, Illinois, United States

11 China Institute of Atomic Energy, Beijing, China

12 Chungbuk National University, Cheongju, Republic of Korea

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

14 COMSATS University Islamabad, Islamabad, Pakistan

15 Creighton University, Omaha, Nebraska, United States

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

41 Fudan University, Shanghai, China

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

43 Gauhati University, Department of Physics, Guwahati, India

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

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

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

47 Hiroshima University, Hiroshima, Japan

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

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

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

51 Indian Institute of Technology Indore, Indore, India

52 Indonesian Institute of Sciences, Jakarta, Indonesia

53 INFN, Laboratori Nazionali di Frascati, Frascati, Italy

54 INFN, Sezione di Bari, Bari, Italy

55 INFN, Sezione di Bologna, Bologna, Italy

56 INFN, Sezione di Cagliari, Cagliari, Italy

57 INFN, Sezione di Catania, Catania, Italy

58 INFN, Sezione di Padova, Padova, Italy

59 INFN, Sezione di Pavia, Pavia, Italy

60 INFN, Sezione di Roma, Rome, Italy

61 INFN, Sezione di Torino, Turin, Italy

62 INFN, Sezione di Trieste, Trieste, Italy

63 Inha University, Incheon, Republic of Korea

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

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

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

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

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

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

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

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

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

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

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

75 Jeonbuk National University, Jeonju, Republic of Korea

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

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

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

79 KTO Karatay University, Konya, Turkey

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

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

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

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

84 Moscow Institute for Physics and Technology, Moscow, Russia

85 Nagasaki Institute of Applied Science, Nagasaki, Japan

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

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

88 National Centre for Nuclear Research, Warsaw, Poland

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

90 National Nuclear Research Center, Baku, Azerbaijan

91 National Research Centre Kurchatov Institute, Moscow, Russia

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

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

94 NRC Kurchatov Institute IHEP, Protvino, Russia

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

96 NRNU Moscow Engineering Physics Institute, Moscow, Russia

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

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

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

100 Ohio State University, Columbus, Ohio, United States

101 Petersburg Nuclear Physics Institute, Gatchina, Russia

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

103 Physics Department, Panjab University, Chandigarh, India

104 Physics Department, University of Jammu, Jammu, India

105 Physics Department, University of Rajasthan, Jaipur, India

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

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

108 Physik Department, Technische Universität München, Munich, Germany

109 Politecnico di Bari and Sezione INFN, Bari, Italy

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

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

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

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

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

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

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

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

118 Suranaree University of Technology, Nakhon Ratchasima, Thailand

119 Technical University of Košice, Košice, Slovakia

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

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

122 Universidad Autónoma de Sinaloa, Culiacán, Mexico

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

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

125 Universidade Federal do ABC, Santo Andre, Brazil

126 University of Cape Town, Cape Town, South Africa

127 University of Houston, Houston, Texas, United States

128 University of Jyväskylä, Jyväskylä, Finland

129 University of Kansas, Lawrence, Kansas, United States

130 University of Liverpool, Liverpool, United Kingdom

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

132 University of South-Eastern Norway, Tonsberg, Norway

133 University of Tennessee, Knoxville, Tennessee, United States

134 University of the Witwatersrand, Johannesburg, South Africa

135 University of Tokyo, Tokyo, Japan

136 University of Tsukuba, Tsukuba, Japan

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

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

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

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

141 Università degli Studi di Foggia, Foggia, Italy

142 Università di Brescia, Brescia, Italy

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

144 Warsaw University of Technology, Warsaw, Poland

145 Wayne State University, Detroit, Michigan, United States

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

147 Wigner Research Centre for Physics, Budapest, Hungary

148 Yale University, New Haven, Connecticut, United States

149 Yonsei University, Seoul, Republic of Korea