2018 261 27 September $\Lambda_{\mathrm{c}}^{+}$ production in Pb–Pb
collisions at $\sqrt{s_{\rm\scriptscriptstyle NN}}=5.02$ TeV ALICE
Collaboration††thanks: See Appendix A for the list of collaboration members
ALICE Collaboration

A measurement of the production of prompt $\rm\Lambda_{c}^{+}$ baryons in
Pb–Pb collisions at $\sqrt{s_{\rm\scriptscriptstyle NN}}=5.02$ TeV with the
ALICE detector at the LHC is reported. The $\rm\Lambda_{c}^{+}$ and
$\rm{\overline{\Lambda}{}_{c}^{-}}$ were reconstructed at midrapidity
($|y|<0.5$) via the hadronic decay channel $\rm\Lambda_{c}^{+}\to pK_{S}^{0}$
(and charge conjugate) in the transverse momentum and centrality intervals
$6<p_{\rm T}<12$ GeV/$c$ and 0–80%. The $\rm\Lambda_{c}^{+}/\rm D^{0}$ ratio,
which is sensitive to the charm quark hadronisation mechanisms in the medium,
is measured and found to be larger than the ratio measured in minimum-bias
$\mathrm{p\kern-0.50003ptp}$ collisions at $\sqrt{s}=7$ TeV and in p–Pb
collisions at $\sqrt{s_{\rm\scriptscriptstyle NN}}=5.02$ TeV. In particular,
the values in p–Pb and Pb–Pb collisions differ by about two standard
deviations of the combined statistical and systematic uncertainties in the
common $p_{\rm T}$ interval covered by the measurements in the two collision
systems. The $\rm\Lambda_{c}^{+}/\rm D^{0}$ ratio is also compared with model
calculations including different implementations of charm quark hadronisation.
The measured ratio is reproduced by models implementing a pure coalescence
scenario, while adding a fragmentation contribution leads to an
underestimation. The $\rm\Lambda_{c}^{+}$ nuclear modification factor, $R_{\rm
AA}$, is also presented. The measured values of the $R_{\rm AA}$ of
$\rm\Lambda_{c}^{+}$, ${\rm D_{s}^{+}}$ and non-strange D mesons are
compatible within the combined statistical and systematic uncertainties. They
show, however, a hint of a hierarchy $(R_{\rm AA}^{\rm D^{0}}<R_{\rm AA}^{{\rm
D_{s}^{+}}}<R_{\rm AA}^{\rm\Lambda_{c}^{+}})$, conceivable with a contribution
from coalescence mechanisms to charm hadron formation in the medium.

##  1 Introduction

Measurements of the production of open-heavy flavour hadrons in heavy-ion
collisions provide important information on the properties of the Quark–Gluon
Plasma (QGP), the state of strongly-interacting matter formed at the very high
temperatures and energy densities reached in heavy-ion collisions [1, 2].
Several measurements of the production and elliptic flow of D mesons and
leptons from the decay of heavy-flavour hadrons in Pb–Pb collisions at the LHC
and in Au–Au collisions at RHIC [3, 4] indicate that charm quarks interact
strongly with the medium constituents. In-medium energy loss is studied via
the nuclear modification factor, $R_{\rm AA}$, defined as the ratio of the
yield in Pb–Pb collisions and that in $\mathrm{p\kern-0.50003ptp}$ collisions
scaled by the number of binary nucleon–nucleon collisions. A model [5, 6]
including a significant fraction of low and intermediate transverse momentum
($p_{\rm T}$) charm and beauty quarks hadronising via coalescence (or
recombination) with light quarks from the medium better describes the
experimental results. This mechanism is expected to also affect the production
of ${\rm D_{s}^{+}}$ given the strange-quark rich environment of the created
medium. At higher transverse momentum ($p_{\rm T}$ $>7$ GeV/$c$ at LHC
energies [7]) hadronisation by vacuum fragmentation is expected to be the
dominant production mechanism.

In this context, the study of charm baryons is essential to understand charm
hadronisation. Models including coalescence predict an enhanced baryon-to-
meson ratio at low and intermediate transverse momentum in comparison to that
expected in $\mathrm{p\kern-0.50003ptp}$ collisions. This effect adds to the
hadron-mass dependent transverse-momentum shift due to the presence of radial
flow in heavy-ion collisions, that is able to explain the observed increase of
the baryon-to-meson ratio in the light sector up to about 2 GeV/$c$ [8]. The
study of non-strange D-mesons, ${\rm D_{s}^{+}}$ and $\rm\Lambda_{c}^{+}$
could help to disentangle the role of coalescence and radial flow, because of
the smaller mass differences than for light-flavour hadrons.

For the particular case of charm baryons, the possible existence of light di-
quark bound states in the QGP could further enhance the
$\rm\Lambda_{c}^{+}$/$\rm D^{0}$ ratio in the coalescence model [9]. An
enhancement of the $p_{\rm T}$-integrated $\rm\Lambda_{c}^{+}$/$\rm D^{0}$
ratio in the presence of a QGP is also predicted by the statistical
hadronisation model [10], where at LHC energies the relative abundance of
hadrons depends on their masses, their flavour content and the freeze-out
temperature of the medium. In addition, an enhancement of charm-baryon
production in Pb–Pb collisions would make the charm baryons an important
fraction of the total charm production cross section.

The study of a potential enhancement effect in charm-baryon production in
relativistic heavy-ion collisions requires a baseline reference in smaller
collision systems. The $\rm\Lambda_{c}^{+}$-baryon production was measured by
the ALICE Collaboration in $\mathrm{p\kern-0.50003ptp}$ collisions at
$\sqrt{s}=7$ $\mathrm{TeV}$ in the transverse momentum and rapidity ($y$)
intervals $1<p_{\rm T}<8$ GeV/$c$ and $|y|<0.5$ [11]. The obtained baryon-to-
meson ratio is larger than previous measurements at lower centre-of-mass
energies and in different collision systems (see Ref. [11] and references
therein), and also higher than the results reported by the LHCb Collaboration
in $\mathrm{p\kern-0.50003ptp}$ collisions at $\sqrt{s}=7$ $\mathrm{TeV}$ in
the rapidity range $2.0<y<4.5$ [12]. Expectations from perturbative Quantum
Chromodynamics (pQCD) calculations and Monte Carlo event generators
underpredict the data, indicating that the fragmentation of charm quarks is
not fully understood [11] and partially challenged by data collected so far at
the LHC, as discussed extensively in Ref. [13]. The production of
$\rm\Lambda_{c}^{+}$ baryons was also measured by the ALICE Collaboration in
p–Pb collisions at $\sqrt{s_{\rm\scriptscriptstyle NN}}=5.02$ $\mathrm{TeV}$
in $2<p_{\rm T}<12$ GeV/$c$ and $-0.96<y<0.04$ [11], and a measurement in the
same collision system by the LHCb Collaboration [14] is also available. The
$\rm\Lambda_{c}^{+}$ nuclear modification factor $R_{\rm pPb}$ is compatible
with unity within statistical and systematic uncertainties. The baryon-to-
meson ratios $\rm\Lambda_{c}^{+}$/$\rm D^{0}$ measured in
$\mathrm{p\kern-0.50003ptp}$ and p–Pb collisions are compatible within
uncertainties. A model [15, 16] including hadronisation via coalescence in
these collision systems has been proposed to describe the measurements at LHC
energies.

This letter reports measurements of the production of the prompt charm baryon
$\rm\Lambda_{c}^{+}$ and its charge conjugate in Pb–Pb collisions at
$\sqrt{s_{\rm\scriptscriptstyle NN}}=5.02$ $\mathrm{TeV}$ with the ALICE
detector [17] at the LHC. Hereafter, $\Lambda_{\rm c}$ refers indistinctly to
both particle and anti-particle, and all mentioned decay channels refer also
to their charge conjugates. The $\rm\Lambda_{c}^{+}$corrected yield is
obtained as the average of the particle and the anti-particle yield. The
notation $\rm\Lambda_{c}^{+}$is used when referring to this average, and thus
to indicate physics quantities such as the $\rm\Lambda_{c}^{+}$/$\rm D^{0}$
ratio. The measurement was performed in the 0–80% centrality class in the
transverse momentum and rapidity intervals $6<p_{\rm T}<12$ GeV/$c$ and
$|y|<0.5$. Only prompt $\mathrm{\Lambda_{c}}$-baryons were considered: the
beauty-hadron feed-down was subtracted, as described in the next section. The
$\rm D^{0}$-meson yield was obtained in the same transverse momentum and
centrality interval as the $\mathrm{\Lambda_{c}}$-baryon, following the
analysis procedure described in Ref. [18].

##  2 Data sample and analysis strategy

The measurement of the $\mathrm{\Lambda_{c}}$-baryon production was performed
by reconstructing the decays $\rm\Lambda_{c}^{+}\to pK_{S}^{0}$ with a
branching ratio (BR) equal to $(1.58\pm 0.08)\%$ and $\rm
K^{0}_{S}\to\pi^{+}\pi^{-}$ with BR = (69.20 $\pm$ 0.05)$\%$ [19]. The $\rm
D^{0}$ mesons were reconstructed in the decay channel ${\rm D}^{0}\to{\rm
K}^{-}\pi^{+}$ with $\mathrm{BR}=(3.93\pm 0.04)\%$ [19]. The
$\mathrm{\Lambda_{c}}$ and $\rm D^{0}$ candidates were reconstructed in the
same transverse momentum, rapidity and centrality intervals. The analysis
benefits from the tracking and particle identification capabilities of the
ALICE central barrel detectors located within a large solenoidal magnet that
provides a magnetic field of 0.5 T parallel to the LHC beam axis. A complete
description of the ALICE apparatus and its performance can be found in Refs.
[17, 20]. The main detectors used in this analysis include the Inner Tracking
System (ITS) [21], the Time Projection Chamber (TPC) [22], the Time-Of-Flight
detector (TOF) [23] and the V0 detector [24] located inside the solenoidal
magnet, as well as the Zero Degree Calorimeters (ZDC) [17] located in the LHC
tunnel at about $\pm 112.5$ m from the nominal interaction point and composed
of two proton and two neutron calorimeters.

The analysed data sample consists of about $83\times 10^{6}$ Pb–Pb collisions
at $\sqrt{s_{\rm\scriptscriptstyle NN}}=5.02$ TeV, corresponding to an
integrated luminosity of $\mathcal{L}_{\mathrm{int}}\approx
13.4\leavevmode\nobreak\ \mathrm{\mu b}^{-1}$. The interaction trigger was
provided by the coincident signals from the two arrays of the V0 detector,
covering the pseudorapidity intervals $-3.7<\eta<-1.7$ and $2.8<\eta<5.1$.
Background events from beam–gas interactions were removed in the offline
analysis using the timing information provided by the V0 and the neutron ZDC.
Only events with a primary vertex reconstructed within $\pm 10$ cm from the
centre of the detector along the beam line were considered for the analysis.
Events were selected in the centrality class 0–80%, defined in terms of
percentiles of the hadronic Pb–Pb cross section, using the amplitudes of the
signals in the V0 arrays [25].

The $\mathrm{\Lambda_{c}}$ candidates were constructed by combining a proton
candidate track with a $\rm K_{S}^{0}$ candidate identified through its
V-shaped neutral decay topology (${\rm V^{0}}$). The charged tracks and the
$\rm K_{S}^{0}$ candidates were selected as described in Ref. [11] for pp
collisions with additional requirements to reduce the larger combinatorial
background due to the higher charged-track multiplicity in Pb–Pb with respect
to pp collisions. In particular, candidate proton tracks were required to have
a hit in the innermost ITS layer and tighter selections on the $\rm K_{S}^{0}$
were applied: a maximum distance of closest approach between the ${\rm V^{0}}$
decay tracks of 0.4 cm, a minimum cosine of the ${\rm V^{0}}$ pointing angle
to the primary vertex of 0.9998, a minimum $p_{\rm T}$ of the $\rm K_{S}^{0}$
candidates of 1 GeV/$c$, and a cut in the Armenteros-Podolanski space [26] to
remove contributions from $\Lambda$ decays. The identification of protons was
based on the specific ionisation energy loss ${\rm d}E/{\rm d}x$ in the TPC
and on the time of flight measured with the TOF detector, using as a
discriminating variable ($n_{\sigma}$) the difference between the measured
value and the expected value for the proton mass hypothesis divided by the
detector resolution. A $|n_{\sigma}|<3$ selection was applied on the TPC ${\rm
d}E/{\rm d}x$ and TOF time-of-flight measurements for tracks with $p_{\rm
T}<3$ GeV/$c$. For tracks with $p_{\rm T}>3$ GeV/$c$ an asymmetric selection
was used to limit the contamination from pions in the TPC and from kaons in
the TOF and the requirements were $-3<n_{\sigma}^{\mathrm{TPC}}<2$ and
$-2<n_{\sigma}^{\mathrm{TOF}}<3$ for the TPC and TOF signals. Tracks without
TOF information were discarded. The $\mathrm{\Lambda_{c}}$ candidates were
selected requiring a cosine of the proton emission angle in the
$\mathrm{\Lambda_{c}}$ centre-of-mass system with respect to the
$\mathrm{\Lambda_{c}}$ momentum direction larger than 0.5. A selection on the
signed transverse impact parameter of the proton, i.e. the distance of closest
approach between the proton track and the primary vertex, larger than 0.003 cm
was also applied (the sign of the impact parameter is defined as positive when
the angle between the $\mathrm{\Lambda_{c}}$ flight line and the momentum
vector is smaller than $90^{\circ}$).

The $\rm D^{0}$ candidates were reconstructed by combining pairs of tracks
with the proper charge sign combination and selected in the interval $6<p_{\rm
T}<12$ GeV/$c$ using the same criteria described in Ref. [18] for the interval
$6<p_{\rm T}<7$ GeV/$c$ in the 10% most central Pb–Pb collisions.

After all selections, the acceptance in rapidity for $\mathrm{\Lambda_{c}}$
and $\rm D^{0}$ candidates drops steeply to zero for $|y|>0.8$ in the $p_{\rm
T}$ interval used for the analysis. Therefore, a fiducial acceptance cut
$|y|<0.8$ was applied as described in Refs. [11] and [18].

The $\mathrm{\Lambda_{c}}$ and $\rm D^{0}$ raw yields were extracted by
fitting the invariant mass distributions of the candidates passing the
selection criteria. The fit functions consist of a Gaussian to describe the
signal and an exponential to describe the background. In the case of the
$\mathrm{\Lambda_{c}}$, the width of the Gaussian was fixed to the value
obtained from Monte Carlo simulations. The stability of the
$\mathrm{\Lambda_{c}}$ signal extraction was verified by fitting the invariant
mass distribution after the subtraction of the background evaluated with an
event-mixing technique and no discrepancy between the two approaches was
observed. For the $\rm D^{0}$-meson yield, the contribution of signal
candidates with the wrong K–$\pi$ mass assignment (reflections) to the
invariant-mass distribution was taken into account by including an additional
term, parameterised from simulations with a double-Gaussian shape, in the fit
function [27].

The invariant mass distributions of the selected $\mathrm{\Lambda_{c}}$ and
$\rm D^{0}$ candidates are shown in Fig. 1.

Figure 1: Invariant-mass distributions for the $\mathrm{\Lambda_{c}}$ (left)
and $\rm D^{0}$ (right) candidates in the momentum interval $6<p_{\rm T}<12$
GeV/$c$ and for the 0–80% centrality class. The dashed curves represent the
fit to the background, while the solid curves represent the total fit
function.

The prompt $\rm\Lambda_{c}^{+}$ ($\rm D^{0}$) production yield was calculated
as

$\left.\frac{\mathrm{d}N_{\mathrm{prompt}}^{\rm\Lambda_{c}^{+}(\rm
D^{0})}}{\mathrm{d}p_{\mathrm{T}}}\right|_{|y|<0.5}=\frac{1}{2}\frac{1}{c_{\Delta
y}}\frac{1}{\Delta p_{\rm T}}\frac{f_{\mathrm{prompt}}\cdot
N_{\mathrm{raw}}|_{|y|<0.8}}{(\mathrm{Acc}\times\epsilon)_{\mathrm{prompt}}\cdot\mathrm{BR}\cdot
N_{\mathrm{evt}}},$ (1)

where $N_{\mathrm{raw}}$ is the raw yield (sum of particles and anti-
particles) in the transverse momentum interval of width $\Delta p_{\rm T}$,
$f_{\mathrm{prompt}}$ is the fraction of prompt $\Lambda_{\mathrm{c}}$ ($\rm
D^{0}$) in the raw yield, $(\mathrm{Acc}\times\epsilon)$ is the product of
acceptance and reconstruction efficiency for prompt $\Lambda_{\mathrm{c}}$
($\rm D^{0}$), BR is the branching ratio of the considered decay mode and
$N_{\mathrm{evt}}$ is the number of events considered for the analysis. The
correction factor for the rapidity coverage $c_{\Delta y}$ was computed as the
ratio of the generated $\Lambda_{\mathrm{c}}$ ($\rm D^{0}$) yield in $|y|<0.8$
and that in $|y|<0.5$. The factor $1/2$ takes into account that the raw yield
is the sum of particles and anti-particles, while the production yield is
reported as their average.

The correction for the detector acceptance and reconstruction efficiency was
determined by means of Monte Carlo (MC) simulations. The underlying Pb–Pb
events at $\sqrt{s_{\rm\scriptscriptstyle NN}}=5.02$ TeV were simulated using
the HIJING v1.383 [28] generator and prompt and feed-down
$\mathrm{\Lambda_{c}}$ ($\rm D^{0}$) were added using the PYTHIA v6.421 [29]
generator with Perugia 11 tune. The generated particles were transported
through the ALICE detector using the GEANT3 [30] package. A realistic detector
response was introduced in the simulations to reproduce the performance of the
ALICE detector system during data taking.

The $p_{\rm T}$ distributions of the $\mathrm{\Lambda_{c}}$ and $\rm D^{0}$ in
PYTHIA were corrected in order to obtain more realistic distributions. The
same $p_{\rm T}$-dependent weighting factor, calculated as the ratio of the
measured $\rm D^{0}$ $p_{\rm T}$ distribution in finer $p_{\rm T}$ bins [18]
and the one simulated with PYTHIA, was used for both particles. The
$\mathrm{\Lambda_{c}}$ and $\rm D^{0}$ reconstruction efficiency in the large
centrality class 0–80% was obtained as the weighted average of the
efficiencies in smaller centrality classes to take into account the variation
of the efficiency and the scaling of the yields of the $\mathrm{\Lambda_{c}}$
baryons and $\rm D^{0}$ mesons with centrality. The applied weights were
calculated as the product of the $R_{\rm AA}$ of the $\rm D^{0}$ and the
average number of nucleon–nucleon collisions ($<N_{\mathrm{coll}}>$) in the
centrality class considered [18]. The $(\mathrm{Acc}\times\epsilon)$ value is
about 6% for prompt and about 9% for feed-down $\mathrm{\Lambda_{c}}$ and
about 8% for prompt and about 11% for feed-down $\rm D^{0}$.

The prompt $\mathrm{\Lambda_{c}}$ ($\rm D^{0}$) fraction,
$f_{\mathrm{prompt}}$, was calculated as

$\displaystyle f_{\mathrm{prompt}}$
$\displaystyle=1-\left(\frac{N_{\mathrm{feed}\mathchar
45\relax\mathrm{down}}^{\Lambda_{\rm{c}}(\rm
D^{0})}}{N_{\mathrm{prompt}}^{\Lambda_{\rm{c}}(\rm D^{0})}}\right)=$
$\displaystyle=1-\left<T_{\rm
AA}\right>\cdot\left.\frac{\mathrm{d}^{2}\sigma}{\mathrm{d}y\mathrm{d}p_{\rm
T}}\right|^{\mathrm{FONLL}}_{\mathrm{feed}\mathchar
45\relax\mathrm{down}}\cdot R_{\mathrm{AA}}^{\mathrm{feed}\mathchar
45\relax\mathrm{down}}\cdot\frac{(\mathrm{Acc}\times\epsilon)_{\mathrm{feed}\mathchar
45\relax\mathrm{down}}\cdot c_{\Delta y}\cdot\Delta p_{\rm
T}\cdot\mathrm{BR}\cdot N_{\mathrm{evt}}}{N_{\mathrm{raw}}/2}.$ (2)

The contribution of $\mathrm{\Lambda_{c}}$ ($\rm D^{0}$) from beauty-hadron
decays was estimated using the FONLL [31, 32] beauty-production cross sections
as described in detail in Ref. [33]. The fraction of beauty quarks that
fragment to beauty hadrons and subsequently decay into $\mathrm{\Lambda_{c}}$
baryons $f(\mathrm{b}\to\mbox{$\mathrm{\Lambda_{c}}$})=0.073$ was taken from
Ref. [34]. The beauty-hadron decay kinematics were modeled using the EVTGEN
[35] package. The $(\mathrm{Acc}\times\epsilon)_{\mathrm{feed}\mathchar
45\relax\mathrm{down}}$ term for both particles was calculated from the Monte
Carlo simulations described above. The average nuclear overlap function,
$\left<T_{\rm AA}\right>$, was estimated via Glauber model calculations [36,
37]. In this formalism the nuclear modification factor $R_{\rm AA}$ is then
the ratio of the yield in Pb–Pb collisions and the production cross section in
$\mathrm{p\kern-0.50003ptp}$ collisions scaled by $\left<T_{\rm AA}\right>$.

A hypothesis on the $R_{\rm AA}^{\mathrm{\mathrm{feed}\mathchar
45\relax\mathrm{down}}}$ of feed-down $\mathrm{\Lambda_{c}}$ and $\rm D^{0}$
is used. For the $\rm D^{0}$, the hypothesis is the same as in other analyses
(e.g. in Ref. [18]): the central value is obtained by assuming $R_{\rm
AA}^{\mathrm{\mathrm{feed}\mathchar 45\relax\mathrm{down}\leavevmode\nobreak\
\rm D^{0}}}/R_{\rm AA}^{\mathrm{prompt\leavevmode\nobreak\ \rm D^{0}}}=2$,
justified by the CMS measurement of J/$\psi$ from B-meson decays [38] and by
the ALICE and CMS measurements of D mesons [18, 39] indicating that prompt
charm mesons are more suppressed than non-prompt charm mesons. The ratio is
varied in the interval $1<R_{\rm AA}^{\mathrm{\mathrm{feed}\mathchar
45\relax\mathrm{down}\leavevmode\nobreak\ \rm D^{0}}}/R_{\rm
AA}^{\mathrm{prompt\leavevmode\nobreak\ \rm D^{0}}}<3$ to estimate the
systematic uncertainty. Since no measurements of beauty-baryon production in
nucleus–nucleus collisions are available, for the $\mathrm{\Lambda_{c}}$ the
central hypothesis was taken from model calculations which predict $R_{\rm
AA}^{\mathrm{\mathrm{feed}\mathchar 45\relax\mathrm{down}\leavevmode\nobreak\
\rm\Lambda_{c}^{+}}}/R_{\rm AA}^{\mathrm{prompt\leavevmode\nobreak\
\rm\Lambda_{c}^{+}}}=2$ when considering c and b quark fragmentation and
energy loss in the medium [40]. The ratio $R_{\rm
AA}^{\mathrm{\mathrm{feed}\mathchar 45\relax\mathrm{down}\leavevmode\nobreak\
\rm\Lambda_{c}^{+}}}/R_{\rm AA}^{\mathrm{prompt\leavevmode\nobreak\
\rm\Lambda_{c}^{+}}}$ was decomposed into two terms to estimate the
uncertainty on the assumption:

$\frac{R_{\rm AA}^{\mathrm{feed}\mathchar
45\relax\mathrm{down}\leavevmode\nobreak\ \rm\Lambda_{c}^{+}}}{R_{\rm
AA}^{\mathrm{prompt\leavevmode\nobreak\ \rm\Lambda_{c}^{+}}}}=\frac{R_{\rm
AA}^{\mathrm{feed}\mathchar 45\relax\mathrm{down}\leavevmode\nobreak\ \rm
D^{0}}}{R_{\rm AA}^{\mathrm{prompt\leavevmode\nobreak\ \rm
D^{0}}}}\cdot\frac{\frac{(\rm\Lambda_{c}^{+}/\rm
D^{0})_{\mathrm{PbPb,}\mathrm{feed}\mathchar
45\relax\mathrm{down}}}{(\rm\Lambda_{c}^{+}/\rm
D^{0})_{\mathrm{pp,}\mathrm{feed}\mathchar
45\relax\mathrm{down}}}}{\frac{(\rm\Lambda_{c}^{+}/\rm
D^{0})_{\mathrm{PbPb,prompt}}}{(\rm\Lambda_{c}^{+}/\rm
D^{0})_{\mathrm{pp,prompt}}}}.$ (3)

The first term is the same as for the $\rm D^{0}$ and thus the same hypothesis
is adopted. The second term is varied in the range 0.5–1.5 to calculate the
systematic uncertainty. The upper limit is determined a-posteriori such that
$R_{\rm AA}^{\mathrm{\mathrm{feed}\mathchar
45\relax\mathrm{down}\leavevmode\nobreak\ \rm\Lambda_{c}^{+}}}<2$ as suggested
by the fact that no baryon $R_{\rm AA}$ exceeds this value. The uncertainties
on the two terms are added in quadrature. The resulting values of
$f_{\mathrm{prompt}}$ are about 0.93 and 0.81 for the $\mathrm{\Lambda_{c}}$
and $\rm D^{0}$, respectively.

A summary of the systematic uncertainties on the corrected
$\rm\Lambda_{c}^{+}$ and $\rm D^{0}$ yields is shown in Tab. 1. The $\rm
D^{0}$ systematic uncertainties on the particle identification (PID), tracking
and cut variation are taken from Ref. [18] and are not discussed in the
following.

Uncertainty | $\rm\Lambda_{c}^{+}$ | $\rm D^{0}$
---|---|---
Raw-yield extraction | 8% | 2%
Tracking efficiency | 3.6% | 5%
PID | 5% | negl.
Cut variation | 2% | 5%
MC $p_{\rm T}$ shape | 2% | negl.
MC centrality weights | 3% | negl.
Feed-down subtraction |  ${}^{+6}_{-12}$% |  ${}^{+12}_{-13}$%
Branching ratio | 5% | 1%
Table 1: Systematic uncertainties on the corrected yields. When the
uncertainty was found to be $<1$%, it was considered negligible (negl . in the
table).

The systematic uncertainty on the raw-yield extraction for
$\mathrm{\Lambda_{c}}$ and $\rm D^{0}$ was estimated by repeating the fits
several times varying (i) the lower and upper limits of the fit range, (ii)
the background fit function and (iii) only in the case of the
$\mathrm{\Lambda_{c}}$, considering the Gaussian mean and width as free
parameters in the fit. In addition, the signal yield was obtained by
integrating the invariant-mass distribution after subtracting the background
estimated from an exponential fit to the sidebands.

For the $\mathrm{\Lambda_{c}}$, the systematic uncertainty on the tracking
efficiency was evaluated by comparing the probability of matching tracks
reconstructed in the TPC to ITS hits in data and simulation and by varying the
quality cuts to select the tracks used in the analysis. The contribution due
to the variation of the quality cuts was evaluated using protons from
$\Lambda$ decays and an inclusive $\rm K_{S}^{0}$ sample and by calculating
the ratio of the corrected yields obtained using different selection criteria.
The uncertainty on the ITS-TPC matching efficiency is defined as the relative
difference of the matching efficiency in data and simulations after weighting
the relative abundances of primary and secondary particles in the simulations
to match those in data. The latter were estimated via fits to the track
impact-parameter distributions. The values calculated as a function of track
momentum were propagated to the $p_{\rm T}$-differential uncertainty of the
$\mathrm{\Lambda_{c}}$ using a Monte Carlo simulation. A 3% systematic
uncertainty on the ITS-TPC matching efficiency of proton tracks was assigned
while for the $\rm K_{S}^{0}$ the matching is not required. The uncertainty
resulting from these studies was added in quadrature to the uncertainty on the
track selection.

The systematic uncertainty on the $\mathrm{\Lambda_{c}}$ PID efficiency was
evaluated using protons from the decay of $\Lambda$ baryons. The ratio of the
$\Lambda$ yield measured with PID to that measured without PID was calculated
in both data and MC and their difference was used to estimate the systematic
uncertainty.

Systematic uncertainties on the efficiencies can also arise from possible
differences in the distributions and resolutions of selection variables
between data and simulation. The systematic effect induced by these
imperfections was estimated by repeating the analysis varying the main
selection criteria for the candidates. The efficiencies determined from the
simulations depend also on the generated $p_{\rm T}$ distributions of the
$\mathrm{\Lambda_{c}}$ and the $\rm D^{0}$. The central values of the
correction factors were obtained by re-weighting the $\mathrm{\Lambda_{c}}$
and $\rm D^{0}$ distributions generated by PYTHIA as described above. For the
$\rm D^{0}$, the efficiencies calculated with and without the $p_{\rm T}$
weights are compatible and therefore no uncertainty was assigned. For the
$\mathrm{\Lambda_{c}}$, the systematic uncertainty was defined by considering
the variation of the efficiencies determined with different generated $p_{\rm
T}$ shapes. The new $\mathrm{\Lambda_{c}}$ $p_{\rm T}$ shape was calculated by
multiplying the measured $\rm D^{0}$ $p_{\rm T}$ distribution with the
$\rm\Lambda_{c}^{+}/\rm D^{0}$ ratios predicted by the models [6] and [41].

Finally, the efficiencies in the centrality class 0–80% depend on the
centrality weights used to combine the efficiencies in the smaller centrality
classes. The stability of the efficiencies against the variation of the
centrality weights was tested by recalculating the efficiencies without
weighting for $\left<N_{\mathrm{coll}}\right>$ and, for the
$\mathrm{\Lambda_{c}}$, using as an alternative centrality weight the product
$\Lambda/{\rm K_{S}^{0}}\cdot\left<N_{\mathrm{coll}}\right>$, where the ratio
$\Lambda/\rm K_{S}^{0}$ is taken from Ref. [8].

The systematic uncertainty on the subtraction of feed-down from beauty-hadron
decays was estimated by varying (i) the $p_{\rm T}$-differential cross section
of feed-down $\mathrm{\Lambda_{c}}$ ($\rm D^{0}$) from FONLL calculations
within the theoretical uncertainties (see Ref. [11] for details on the
$\mathrm{\Lambda_{c}}$ and Ref. [33] for the $\rm D^{0}$) and (ii) the ratio
of prompt and feed-down $R_{\mathrm{AA}}$ as described above.

The production yields of $\mathrm{\Lambda_{c}}$ and $\rm D^{0}$ also have a
global systematic uncertainty due to the branching ratio.

##  3 Results

Figure 2: $\rm\Lambda_{c}^{+}/\rm D^{0}$ ratio as a function of $p_{\rm T}$ in
0–80% most central Pb–Pb collisions compared with the measurements in pp and
p–Pb collisions [11] (left), and model calculations [7] (right). Statistical
and systematic uncertainties are presented as vertical bars and boxes,
respectively.

The yield of prompt $\rm\Lambda_{c}^{+}$ baryons measured in Pb–Pb collisions
at $\sqrt{s_{\rm\scriptscriptstyle NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$
in the 0–80% centrality class in $|y|<0.5$ and $6<p_{\rm
T}<12\leavevmode\nobreak\ {\rm GeV}/c$ is $N^{\rm\Lambda_{c}^{+}}=(2.1\pm
0.4\leavevmode\nobreak\ {\rm(stat.)}^{+0.3}_{-0.4}\leavevmode\nobreak\
{\rm(syst.)})\times 10^{-2}$.

Figure 3: $R_{\rm AA}$ of prompt $\rm\Lambda_{c}^{+}$ compared with model
calculations [7, 15, 16] (left), and the non-strange D mesons, ${\rm
D_{s}^{+}}$, and charged particle $R_{\rm AA}$ in 0–10% most central Pb–Pb
collisions for $p_{\rm T}>1\leavevmode\nobreak\ {\rm GeV}/c$ [18, 42] (right).
Statistical, systematic and normalisation uncertainties are presented as
vertical bars, empty boxes and shaded boxes around unity, respectively.

The measured $\rm\Lambda_{c}^{+}/\rm D^{0}$ ratio is shown in Fig. 2. The
systematic uncertainty of the $\rm\Lambda_{c}^{+}$-baryon production arising
from the tracking efficiency was treated as fully correlated to that of the
$\rm D^{0}$ meson. The contribution to the feed-down uncertainty related to
heavy-quark energy loss and that originating from the FONLL uncertainty on the
feed-down $\rm\Lambda_{c}^{+}$ and $\rm D^{0}$ cross sections were treated as
fully correlated when propagated to the ratio. All the other sources of
uncertainty were considered as uncorrelated. In the left panel of Fig. 2, the
$\rm\Lambda_{c}^{+}/\rm D^{0}$ ratio measured in Pb–Pb collisions is compared
with the results obtained by the ALICE Collaboration in minimum-bias pp and
p–Pb collisions at $\sqrt{s}=7\leavevmode\nobreak\ \mathrm{TeV}$ and
$\sqrt{s_{\rm\scriptscriptstyle NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$
[11], respectively. The ratio measured in Pb–Pb collisions is higher than that
measured in pp and p–Pb collisions. In particular, the values in p–Pb and
Pb–Pb collisions differ by about two standard deviations of the combined
statistical and systematic uncertainties in $6<p_{\rm
T}<12\leavevmode\nobreak\ {\rm GeV}/c$.

The $\rm\Lambda_{c}^{+}/\rm D^{0}$ ratio in Pb–Pb collisions is compared with
theoretical model calculations in the right panel of Fig. 2. The Catania model
[7] provides two different treatments of hadronisation. In one case, charm
quarks hadronise via coalescence only. In the other case, a coalescence plus
vacuum fragmentation modelling of hadronisation is considered: at increasing
$p_{\rm T}$ the coalescence probability decreases and eventually vacuum
fragmentation takes over. For $\rm D^{0}$ mesons, the shape of the
fragmentation function is tuned assuring that the experimental results on
D-meson production in pp collisions are well described by a fragmentation
hadronisation mechanism. Data from $\mathrm{e^{+}e^{-}}$ collisions are used
to fix the shape of the fragmentation functions for $\rm\Lambda_{c}^{+}$. The
coalescence mechanism is treated as a three-quark process and implemented
through the Wigner formalism. The momentum spectrum of hadrons formed by
coalescence is obtained from the quark phase-space distributions and the
hadron wave function. The width parameters of the hadron wave functions are
calculated from the charge radius of the hadrons according to the quark model.
The hadron wave function normalisation is determined by requiring a total
coalescence probability for charm quarks equal to unity for zero-momentum
heavy quarks. Moreover, the contributions from the first excited states for D
and $\mathrm{\Lambda_{c}}$ hadrons were included in the calculations. The
experimental results are described by the model calculation including
coalescence only. The curve obtained by modelling charm hadronisation via
vacuum fragmentation plus coalescence, which describes the
$\rm\Lambda_{c}^{+}/\rm D^{0}$ ratio measured in Au–Au collisions at RHIC
energy [43], significantly underestimates the measurement in Pb–Pb collisions
at the LHC. In the Shao-Song model [15, 16], coalescence involves quarks which
are close in momentum space, and it takes place mainly for the quark with a
given fraction of the momentum of the hadron. It does not consider the Wigner
formalism to describe the spatial and momentum distribution of quarks in a
hadron. It can not directly predict the absolute magnitude of the
$\rm\Lambda_{c}^{+}/\rm D^{0}$ ratio because the relative production of
single-charm baryons and single-charm mesons ${\rm R_{BM}}$ is treated as a
parameter of the model. The curve obtained by considering ${\rm
R_{BM}}=0.425$, which is the value needed to describe the results in pp and
p–Pb collisions, underestimates the $\rm\Lambda_{c}^{+}/\rm D^{0}$ ratio
measured in Pb–Pb collisions. An ${\rm R_{BM}}=1.2$ is needed to achieve a
better description of the experimental results in Pb–Pb collisions. However,
the hadronisation mechanism via quark coalescence included in the model is
responsible of the $p_{\rm T}$ dependence of the $\rm\Lambda_{c}^{+}/\rm
D^{0}$ ratio, which needs to be verified by comparing to a measurement at
lower $p_{\rm T}$. The $R_{\rm AA}$ of prompt $\rm\Lambda_{c}^{+}$ was
obtained by considering as reference the $\rm\Lambda_{c}^{+}$ cross section
measured in p–Pb collisions at $\sqrt{s_{\rm\scriptscriptstyle
NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$ [11] scaled by $1/A$ ($A=208$) and
corrected for the different rapidity coverage of the p–Pb measurement. The
cross section measured in p–Pb was scaled in each $p_{\rm T}$ interval to
$|y|<0.5$ using a correction factor obtained with FONLL calculations [31, 32].
The correction factor was determined from the ratios of the cross sections
calculated with FONLL in the rapidity intervals $|y|<0.5$ and $-0.96<y<0.04$.
Since FONLL does not provide predictions for $\rm\Lambda_{c}^{+}$ baryons, the
average of the correction factors obtained for $\rm D^{0}$, ${\rm D}^{+}$ and
bare charm quarks, which was found to be $1.024\pm 0.008$, was used. The
choice of using the p–Pb cross section to obtain the reference for the $R_{\rm
AA}$ was motivated by the fact that it was measured up to $p_{\rm
T}=12\leavevmode\nobreak\ {\rm GeV}/c$, while the measurement in pp collisions
at $\sqrt{s}=7\leavevmode\nobreak\ \mathrm{TeV}$ in $|y|<0.5$ only reaches
$p_{\rm T}=8\leavevmode\nobreak\ {\rm GeV}/c$. In addition, the
$\rm\Lambda_{c}^{+}$ nuclear modification factor measured in p–Pb collisions
is consistent with unity for $p_{\rm T}>2\leavevmode\nobreak\ {\rm GeV}/c$
[11]. The $\rm\Lambda_{c}^{+}$ reference cross section in $6<p_{\rm
T}<12\leavevmode\nobreak\ {\rm GeV}/c$ was obtained by combining the results
in the transverse momentum intervals $6<p_{\rm T}<8\leavevmode\nobreak\ {\rm
GeV}/c$ and $8<p_{\rm T}<12\leavevmode\nobreak\ {\rm GeV}/c$. The
uncertainties were propagated treating the statistical and the systematic
uncertainties on the yield extraction as uncorrelated and the other sources of
systematic uncertainty as correlated in $p_{\rm T}$. The $\rm\Lambda_{c}^{+}$
$R_{\rm AA}$ also has a 3.75% uncertainty due to the normalisation of the
$\rm\Lambda_{c}^{+}$ p–Pb cross section at $\sqrt{s_{\rm\scriptscriptstyle
NN}}=5.02$ TeV [11] and a 2.4% uncertainty on the average nuclear overlap
function $\left<T_{\rm AA}\right>$, which were added in quadrature. In the
left panel of Fig. 3, the $R_{\rm AA}$ of prompt $\rm\Lambda_{c}^{+}$ is
compared with Catania model calculations [7]. The three curves are obtained by
considering different treatments of the hadronisation mechanisms in pp and
Pb–Pb collisions. The short-dashed curve represents the $\rm\Lambda_{c}^{+}$
$R_{\rm AA}$ as obtained by including both vacuum fragmentation and quark
coalescence for charm hadronisation in Pb–Pb and only fragmentation in pp
collisions. The long-dashed curve includes only coalescence in Pb–Pb and
fragmentation plus coalescence in pp collisions. The solid curve is obtained
by considering fragmentation plus coalescence in both collision systems. The
limited precision and the large $p_{\rm T}$ interval of this first measurement
prevent us to draw a firm conclusion on which combination of the hadronisation
mechanisms in the two collision systems better describes the result. Moreover,
the comparison between the different scenarios obtained from the Catania model
demonstrates that it is crucial to also understand the $\rm\Lambda_{c}^{+}$
production mechanism in pp collisions to interpret the $R_{\rm AA}$
measurement. The right panel of Fig. 3 shows the $R_{\rm AA}$ of prompt
$\rm\Lambda_{c}^{+}$ baryons measured in the 0–80% centrality class (that is
dominated by the 0–10% production given the scaling of the yields with $N_{\rm
coll}\cdot R_{\rm AA}$) compared with the average nuclear modification factors
of non-strange D mesons, ${\rm D_{s}^{+}}$ mesons, and charged particles
measured in the 0–10% centrality class [18]. The $R_{\rm AA}$ of charged
particles is smaller than that of D mesons by more than $2\sigma$ of the
combined statistical and systematic uncertainties up to $p_{\rm
T}=8\leavevmode\nobreak\ {\rm GeV}/c$, while they are compatible within
$1\sigma$ for $p_{\rm T}>10\leavevmode\nobreak\ {\rm GeV}/c$. The $R_{\rm AA}$
values of ${\rm D_{s}^{+}}$ mesons are larger than those of non-strange D
mesons, but the two measurements are compatible within one standard deviation
of the combined uncertainties [18]. A hint of a larger $\rm\Lambda_{c}^{+}$
$R_{\rm AA}$ with respect to non-strange D mesons is observed, although the
results are compared for different centrality classes. A $\rm D^{0}$ $R_{\rm
AA}=0.27\pm 0.01{\rm(stat.)\pm 0.04{\rm(syst.)}}$ was measured in $6<p_{\rm
T}<12\leavevmode\nobreak\ {\rm GeV}/c$ in the 0–80% centrality class. The $\rm
D^{0}$ $R_{\rm AA}$ has also a 3.5% uncertainty arising from the normalisation
of the cross section measured in pp collisions at $\sqrt{s}=7$ TeV, and a 2.4%
uncertainty on the average nuclear overlap function $\left<T_{\rm AA}\right>$.
The $p_{\rm T}$-differential cross section of prompt $\rm D^{0}$ mesons with
$|y|<0.5$ in pp collisions at $\sqrt{s}=5.02$ TeV, used as reference for the
nuclear modification factor, was obtained by scaling the measurement at
$\sqrt{s}=7$ TeV [44] to $\sqrt{s}=5.02$ TeV using FONLL calculations [31,
32]. The scaling was applied to the $\rm D^{0}$ cross section obtained in
$6<p_{\rm T}<12\leavevmode\nobreak\ {\rm GeV}/c$ by combining the results in
the $p_{\rm T}$ intervals of the measurement at $\sqrt{s}=7$ TeV. The
statistical and the systematic uncertainties on the yield extraction were
propagated as uncorrelated. The other contributions to the systematic
uncertainty were considered as fully correlated among the $p_{\rm T}$
intervals. A difference of about 1.7$\sigma$ is obtained when comparing the
$\rm\Lambda_{c}^{+}$ $R_{\rm AA}$ with that of the $\rm D^{0}$ in $6<p_{\rm
T}<12\leavevmode\nobreak\ {\rm GeV}/c$ and 0–80% centrality interval. This
observation is qualitatively in agreement with a scenario where a significant
fraction of charm quarks hadronise via coalescence with light quarks from the
medium leading to an enhanced baryon production with respect to that of
mesons.

##  4 Summary

The measurement of the production of prompt $\rm\Lambda_{c}^{+}$ baryons in
the 0–80% most central Pb–Pb collisions at $\sqrt{s_{\rm\scriptscriptstyle
NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$ was presented. The result was
obtained at midrapidity, $|y|<0.5$, in the $6<p_{\rm T}<12\leavevmode\nobreak\
{\rm GeV}/c$ transverse momentum interval. The $\rm\Lambda_{c}^{+}/\rm D^{0}$
ratio is larger than the ratio measured in pp and p–Pb collisions at
$\sqrt{s}=7\leavevmode\nobreak\ \mathrm{TeV}$ and
$\sqrt{s_{\rm\scriptscriptstyle NN}}=5.02\leavevmode\nobreak\ \mathrm{TeV}$
[11], respectively. The $\rm\Lambda_{c}^{+}/\rm D^{0}$ ratio measured in Pb–Pb
collisions is described by a model calculation implementing only charm quark
hadronisation via quark coalescence and it is underestimated when also vacuum
fragmentation is included. The comparison of the $\rm\Lambda_{c}^{+}$ nuclear
modification factor with non-strange D and ${\rm D_{s}^{+}}$ meson results,
which were measured in 0–10% most central Pb–Pb collisions, suggests a hint of
a hierarchy, conceivable in a scenario where charm quark hadronisation can
occur via coalescence processes, thus enhancing the
$\rm\Lambda_{c}^{+}$-baryon and ${\rm D_{s}^{+}}$-meson production with
respect to non-strange D mesons. However, the limited precision of this first
measurement prevents us from drawing a firm conclusion.

A higher precision for a $\rm\Lambda_{c}^{+}$-baryon production measurement
with finer granularity in $p_{\rm T}$ and centrality will be achieved with
future datasets to be collected during LHC Run 2 and, in particular, during
the LHC Run 3 and 4, following the major upgrade of the ALICE apparatus [45,
46].

## 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 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), Universidade Federal do
Rio Grande do Sul (UFRGS), Financiadora de Estudos e Projetos (Finep) and
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), Brazil;
Ministry of Science & Technology of China (MSTC), National Natural Science
Foundation of China (NSFC) and Ministry of Education of China (MOEC) , China;
Ministry of Science and Education, 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 Carlsberg Foundation
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, Wissenschaft, Forschung und Technologie (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; Centro Fermi -
Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi and Istituto
Nazionale di Fisica Nucleare (INFN), Italy; Institute for Innovative Science
and Technology , Nagasaki Institute of Applied Science (IIST), Japan Society
for the Promotion of Science (JSPS) KAKENHI and Japanese Ministry of
Education, Culture, Sports, Science and Technology (MEXT), 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 Science and Higher Education and National Science Centre, 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 Romanian National Agency
for Science, Technology and Innovation, Romania; Joint Institute for Nuclear
Research (JINR), Ministry of Education and Science of the Russian Federation
and National Research Centre Kurchatov Institute, 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; National Science and
Technology Development Agency (NSDTA), Suranaree University of Technology
(SUT) and Office of the Higher Education Commission under NRU project of
Thailand, Thailand; Turkish Atomic Energy Agency (TAEK), 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. Acharyaorg140&F.T.-. Acostaorg20&D. Adamováorg93&S.P. Adhyaorg140&A.
Adlerorg74&J. Adolfssonorg80&M.M. Aggarwalorg98&G. Aglieri Rinellaorg34&M.
Agnelloorg31&N. Agrawalorg48&Z. Ahammedorg140&S. Ahmadorg17&S.U. Ahnorg76&S.
Aiolaorg145&A. Akindinovorg64&M. Al-Turanyorg104&S.N. Alamorg140&D.S.D.
Albuquerqueorg121&D. Aleksandrovorg87&B. Alessandroorg58&H.M. Alfandaorg6&R.
Alfaro Molinaorg72&Y. Aliorg15&A. Aliciorg10,org53,org27&A. Alkinorg2&J.
Almeorg22&T. Altorg69&L. Altenkamperorg22&I. Altsybeevorg111&M.N. Anaamorg6&C.
Andreiorg47&D. Andreouorg34&H.A. Andrewsorg108&A. Andronicorg104,org143&M.
Angelettiorg34&V. Anguelovorg102&C. Ansonorg16&T. Antičićorg105&F.
Antinoriorg56&P. Antonioliorg53&R. Anwarorg125&N. Apadulaorg79&L.
Aphecetcheorg113&H. Appelshäuserorg69&S. Arcelliorg27&R. Arnaldiorg58&M.
Arratiaorg79&I.C. Arseneorg21&M. Arslandokorg102&A. Augustinusorg34&R.
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Vergara Limónorg44&L. Vermuntorg63&R. Vernetorg7&R. Vértesiorg144&L.
Vickovicorg35&J. Viinikainenorg126&Z. Vilakaziorg130&O. Villalobos
Baillieorg108&A. Villatoro Telloorg44&G. Vinoorg52&A. Vinogradovorg87&T.
Virgiliorg30&V. Vislaviciusorg80,org88&A. Vodopyanovorg75&B. Volkelorg34&M.A.
Völklorg101&K. Voloshinorg64&S.A. Voloshinorg142&G. Volpeorg33&B. von
Hallerorg34&I. Vorobyevorg116,org103&D. Voscekorg115&J. Vrlákováorg38&B.
Wagnerorg22&M. Wangorg6&Y. Watanabeorg132&M. Weberorg112&S.G. Weberorg104&A.
Wegrzynekorg34&D.F. Weiserorg102&S.C. Wenzelorg34&J.P. Wesselsorg143&U.
Westerhofforg143&A.M. Whiteheadorg124&E. Widmannorg112&J. Wiechulaorg69&J.
Wikneorg21&G. Wilkorg84&J. Wilkinsonorg53&G.A. Willemsorg143,org34&E.
Willsherorg108&B. Windelbandorg102&W.E. Wittorg129&Y. Wuorg128&R. Xuorg6&S.
Yalcinorg77&K. Yamakawaorg45&S. Yanoorg136,org45&Z. Yinorg6&H.
Yokoyamaorg63,org132,org78&I.-K. Yooorg18&J.H. Yoonorg60&S. Yuanorg22&V.
Yurchenkoorg2&V. Zaccoloorg58,org25&A. Zamanorg15&C. Zampolliorg34&H.J.C.
Zanoliorg120&N. Zardoshtiorg108&A. Zarochentsevorg111&P. Závadaorg67&N.
Zaviyalovorg106&H. Zbroszczykorg141&M. Zhalovorg96&X. Zhangorg6&Y.
Zhangorg6&Z. Zhangorg6,org133&C. Zhaoorg21&V. Zherebchevskiiorg111&N.
Zhigarevaorg64&D. Zhouorg6&Y. Zhouorg88&Z. Zhouorg22&H. Zhuorg6&J. Zhuorg6&Y.
Zhuorg6&A. Zichichiorg27,org10&M.B. Zimmermannorg34&G. Zinovjevorg2&N.
Zurloorg139&

## Affiliation notes

org*Deceased

orgIDipartimento DET del Politecnico di Torino, Turin, Italy

orgIIM.V. Lomonosov Moscow State University, D.V. Skobeltsyn Institute of
Nuclear, Physics, Moscow, Russia

orgIIIDepartment of Applied Physics, Aligarh Muslim University, Aligarh, India

orgIVInstitute of Theoretical Physics, University of Wroclaw, Poland

## Collaboration Institutes

org1A.I. Alikhanyan National Science Laboratory (Yerevan Physics Institute)
Foundation, Yerevan, Armenia

org2Bogolyubov Institute for Theoretical Physics, National Academy of Sciences
of Ukraine, Kiev, Ukraine

org3Bose Institute, Department of Physics and Centre for Astroparticle Physics
and Space Science (CAPSS), Kolkata, India

org4Budker Institute for Nuclear Physics, Novosibirsk, Russia

org5California Polytechnic State University, San Luis Obispo, California,
United States

org6Central China Normal University, Wuhan, China

org7Centre de Calcul de l’IN2P3, Villeurbanne, Lyon, France

org8Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Havana,
Cuba

org9Centro de Investigación y de Estudios Avanzados (CINVESTAV), Mexico City
and Mérida, Mexico

org10Centro Fermi - Museo Storico della Fisica e Centro Studi e Ricerche
“Enrico Fermi’, Rome, Italy

org11Chicago State University, Chicago, Illinois, United States

org12China Institute of Atomic Energy, Beijing, China

org13Chonbuk National University, Jeonju, Republic of Korea

org14Comenius University Bratislava, Faculty of Mathematics, Physics and
Informatics, Bratislava, Slovakia

org15COMSATS Institute of Information Technology (CIIT), Islamabad, Pakistan

org16Creighton University, Omaha, Nebraska, United States

org17Department of Physics, Aligarh Muslim University, Aligarh, India

org18Department of Physics, Pusan National University, Pusan, Republic of
Korea

org19Department of Physics, Sejong University, Seoul, Republic of Korea

org20Department of Physics, University of California, Berkeley, California,
United States

org21Department of Physics, University of Oslo, Oslo, Norway

org22Department of Physics and Technology, University of Bergen, Bergen,
Norway

org23Dipartimento di Fisica dell’Università ’La Sapienza’ and Sezione INFN,
Rome, Italy

org24Dipartimento di Fisica dell’Università and Sezione INFN, Cagliari, Italy

org25Dipartimento di Fisica dell’Università and Sezione INFN, Trieste, Italy

org26Dipartimento di Fisica dell’Università and Sezione INFN, Turin, Italy

org27Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN,
Bologna, Italy

org28Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN,
Catania, Italy

org29Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN,
Padova, Italy

org30Dipartimento di Fisica ‘E.R. Caianiello’ dell’Università and Gruppo
Collegato INFN, Salerno, Italy

org31Dipartimento DISAT del Politecnico and Sezione INFN, Turin, Italy

org32Dipartimento di Scienze e Innovazione Tecnologica dell’Università del
Piemonte Orientale and INFN Sezione di Torino, Alessandria, Italy

org33Dipartimento Interateneo di Fisica ‘M. Merlin’ and Sezione INFN, Bari,
Italy

org34European Organization for Nuclear Research (CERN), Geneva, Switzerland

org35Faculty of Electrical Engineering, Mechanical Engineering and Naval
Architecture, University of Split, Split, Croatia

org36Faculty of Engineering and Science, Western Norway University of Applied
Sciences, Bergen, Norway

org37Faculty of Nuclear Sciences and Physical Engineering, Czech Technical
University in Prague, Prague, Czech Republic

org38Faculty of Science, P.J. Šafárik University, Košice, Slovakia

org39Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-
Universität Frankfurt, Frankfurt, Germany

org40Gangneung-Wonju National University, Gangneung, Republic of Korea

org41Gauhati University, Department of Physics, Guwahati, India

org42Helmholtz-Institut für Strahlen- und Kernphysik, Rheinische Friedrich-
Wilhelms-Universität Bonn, Bonn, Germany

org43Helsinki Institute of Physics (HIP), Helsinki, Finland

org44High Energy Physics Group, Universidad Autónoma de Puebla, Puebla, Mexico

org45Hiroshima University, Hiroshima, Japan

org46Hochschule Worms, Zentrum für Technologietransfer und Telekommunikation
(ZTT), Worms, Germany

org47Horia Hulubei National Institute of Physics and Nuclear Engineering,
Bucharest, Romania

org48Indian Institute of Technology Bombay (IIT), Mumbai, India

org49Indian Institute of Technology Indore, Indore, India

org50Indonesian Institute of Sciences, Jakarta, Indonesia

org51INFN, Laboratori Nazionali di Frascati, Frascati, Italy

org52INFN, Sezione di Bari, Bari, Italy

org53INFN, Sezione di Bologna, Bologna, Italy

org54INFN, Sezione di Cagliari, Cagliari, Italy

org55INFN, Sezione di Catania, Catania, Italy

org56INFN, Sezione di Padova, Padova, Italy

org57INFN, Sezione di Roma, Rome, Italy

org58INFN, Sezione di Torino, Turin, Italy

org59INFN, Sezione di Trieste, Trieste, Italy

org60Inha University, Incheon, Republic of Korea

org61Institut de Physique Nucléaire d’Orsay (IPNO), Institut National de
Physique Nucléaire et de Physique des Particules (IN2P3/CNRS), Université de
Paris-Sud, Université Paris-Saclay, Orsay, France

org62Institute for Nuclear Research, Academy of Sciences, Moscow, Russia

org63Institute for Subatomic Physics, Utrecht University/Nikhef, Utrecht,
Netherlands

org64Institute for Theoretical and Experimental Physics, Moscow, Russia

org65Institute of Experimental Physics, Slovak Academy of Sciences, Košice,
Slovakia

org66Institute of Physics, Homi Bhabha National Institute, Bhubaneswar, India

org67Institute of Physics of the Czech Academy of Sciences, Prague, Czech
Republic

org68Institute of Space Science (ISS), Bucharest, Romania

org69Institut für Kernphysik, Johann Wolfgang Goethe-Universität Frankfurt,
Frankfurt, Germany

org70Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México,
Mexico City, Mexico

org71Instituto de Física, Universidade Federal do Rio Grande do Sul (UFRGS),
Porto Alegre, Brazil

org72Instituto de Física, Universidad Nacional Autónoma de México, Mexico
City, Mexico

org73iThemba LABS, National Research Foundation, Somerset West, South Africa

org74Johann-Wolfgang-Goethe Universität Frankfurt Institut für Informatik,
Fachbereich Informatik und Mathematik, Frankfurt, Germany

org75Joint Institute for Nuclear Research (JINR), Dubna, Russia

org76Korea Institute of Science and Technology Information, Daejeon, Republic
of Korea

org77KTO Karatay University, Konya, Turkey

org78Laboratoire de Physique Subatomique et de Cosmologie, Université
Grenoble-Alpes, CNRS-IN2P3, Grenoble, France

org79Lawrence Berkeley National Laboratory, Berkeley, California, United
States

org80Lund University Department of Physics, Division of Particle Physics,
Lund, Sweden

org81Nagasaki Institute of Applied Science, Nagasaki, Japan

org82Nara Women’s University (NWU), Nara, Japan

org83National and Kapodistrian University of Athens, School of Science,
Department of Physics , Athens, Greece

org84National Centre for Nuclear Research, Warsaw, Poland

org85National Institute of Science Education and Research, Homi Bhabha
National Institute, Jatni, India

org86National Nuclear Research Center, Baku, Azerbaijan

org87National Research Centre Kurchatov Institute, Moscow, Russia

org88Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark

org89Nikhef, National institute for subatomic physics, Amsterdam, Netherlands

org90NRC Kurchatov Institute IHEP, Protvino, Russia

org91NRNU Moscow Engineering Physics Institute, Moscow, Russia

org92Nuclear Physics Group, STFC Daresbury Laboratory, Daresbury, United
Kingdom

org93Nuclear Physics Institute of the Czech Academy of Sciences, Řež u Prahy,
Czech Republic

org94Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States

org95Ohio State University, Columbus, Ohio, United States

org96Petersburg Nuclear Physics Institute, Gatchina, Russia

org97Physics department, Faculty of science, University of Zagreb, Zagreb,
Croatia

org98Physics Department, Panjab University, Chandigarh, India

org99Physics Department, University of Jammu, Jammu, India

org100Physics Department, University of Rajasthan, Jaipur, India

org101Physikalisches Institut, Eberhard-Karls-Universität Tübingen, Tübingen,
Germany

org102Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg,
Heidelberg, Germany

org103Physik Department, Technische Universität München, Munich, Germany

org104Research Division and ExtreMe Matter Institute EMMI, GSI
Helmholtzzentrum für Schwerionenforschung GmbH, Darmstadt, Germany

org105Rudjer Bošković Institute, Zagreb, Croatia

org106Russian Federal Nuclear Center (VNIIEF), Sarov, Russia

org107Saha Institute of Nuclear Physics, Homi Bhabha National Institute,
Kolkata, India

org108School of Physics and Astronomy, University of Birmingham, Birmingham,
United Kingdom

org109Sección Física, Departamento de Ciencias, Pontificia Universidad
Católica del Perú, Lima, Peru

org110Shanghai Institute of Applied Physics, Shanghai, China

org111St. Petersburg State University, St. Petersburg, Russia

org112Stefan Meyer Institut für Subatomare Physik (SMI), Vienna, Austria

org113SUBATECH, IMT Atlantique, Université de Nantes, CNRS-IN2P3, Nantes,
France

org114Suranaree University of Technology, Nakhon Ratchasima, Thailand

org115Technical University of Košice, Košice, Slovakia

org116Technische Universität München, Excellence Cluster ’Universe’, Munich,
Germany

org117The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy
of Sciences, Cracow, Poland

org118The University of Texas at Austin, Austin, Texas, United States

org119Universidad Autónoma de Sinaloa, Culiacán, Mexico

org120Universidade de São Paulo (USP), São Paulo, Brazil

org121Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil

org122Universidade Federal do ABC, Santo Andre, Brazil

org123University College of Southeast Norway, Tonsberg, Norway

org124University of Cape Town, Cape Town, South Africa

org125University of Houston, Houston, Texas, United States

org126University of Jyväskylä, Jyväskylä, Finland

org127University of Liverpool, Liverpool, United Kingdom

org128University of Science and Techonology of China, Hefei, China

org129University of Tennessee, Knoxville, Tennessee, United States

org130University of the Witwatersrand, Johannesburg, South Africa

org131University of Tokyo, Tokyo, Japan

org132University of Tsukuba, Tsukuba, Japan

org133Université Clermont Auvergne, CNRS/IN2P3, LPC, Clermont-Ferrand, France

org134Université de Lyon, Université Lyon 1, CNRS/IN2P3, IPN-Lyon,
Villeurbanne, Lyon, France

org135Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg,
France, Strasbourg, France

org136 Université Paris-Saclay Centre d¿Études de Saclay (CEA), IRFU,
Department de Physique Nucléaire (DPhN), Saclay, France

org137Università degli Studi di Foggia, Foggia, Italy

org138Università degli Studi di Pavia, Pavia, Italy

org139Università di Brescia, Brescia, Italy

org140Variable Energy Cyclotron Centre, Homi Bhabha National Institute,
Kolkata, India

org141Warsaw University of Technology, Warsaw, Poland

org142Wayne State University, Detroit, Michigan, United States

org143Westfälische Wilhelms-Universität Münster, Institut für Kernphysik,
Münster, Germany

org144Wigner Research Centre for Physics, Hungarian Academy of Sciences,
Budapest, Hungary

org145Yale University, New Haven, Connecticut, United States

org146Yonsei University, Seoul, Republic of Korea