Λc+ production in Pb–Pb collisions at √sNN = 5.02 TeV

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ Λc+ production in Pb–Pb collisions at √sNN = 5.02 TeV © 2019 European Organization for Nuclear Research. Published version ALICE Collaboration ALICE Collaboration. (2019). Λc+ production in Pb–Pb collisions at √sNN = 5.02 TeV. Physics Letters B, 793, 212-223. https://doi.org/10.1016/j.physletb.2019.04.046 2019 Physics Letters B 793 (2019) 212–223 Contents lists available at ScienceDirect Physics Letters B www.elsevier.com/locate/physletb + cproduction in Pb–Pb collisions at √sNN =5.02 TeV .ALICE Collaboration a r t i c l e i n f o a b s t r a c t Article history: Received 12 October 2018 Received in revised form 26 March 2019 Accepted 17 April 2019 Available online 23 April 2019 Editor: L. Rolandi A measurement of the production of prompt + cbaryons in Pb–Pb collisions at √sNN =5.02 TeV with the ALICE detector at the LHC is reported. The + cand − cwere reconstructed at midrapidity (|y| <0.5) via the hadronic decay channel + c→pK0 S(and charge conjugate) in the transverse momentum and centrality intervals 6 <pT<12 GeV/cand 0–80%. The + c/D0ratio, 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 pp collisions at √s=7TeV and in p–Pb collisions at √sNN =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 pTinterval covered by the measurements in the two collision systems. The + c/D0ratio 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 + cnuclear modification factor, RAA, is also presented. The measured values of the RAA of + c, D+ sand non-strange D mesons are compatible within the combined statistical and systematic uncertainties. They show, however, a hint of a hierarchy (RD0 AA <RD+ s AA <R+ c AA ), conceivable with a contribution from coalescence mechanisms to charm hadron formation in the medium. ©2019 European Organization for Nuclear Research. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3. 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 stronglyinteracting 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. Inmedium energy loss is studied via the nuclear modification factor, RAA, defined as the ratio of the yield in Pb–Pb collisions and that in pp collisions scaled by the number of binary nucleon–nucleon collisions. A model [5,6] including a significant fraction of low and intermediate transverse momentum (pT) 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 D+ sgiven the strange-quark rich environment of the created medium. At higher transverse momentum (pT>7GeV/cat LHC E-mail address: alice -publications @cern .ch. 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 pp collisions. This effect adds to the hadron-mass dependent transversemomentum 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, D+ sand + ccould 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 + c/D0ratio in the coalescence model [9]. An enhancement of the pT-integrated + c/D0ratio 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 https://doi.org/10.1016/j.physletb.2019.04.046 0370-2693/©2019 European Organization for Nuclear Research. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3. ALICE Collaboration / Physics Letters B 793 (2019) 212–223 213 reference in smaller collision systems. The + c-baryon production was measured by the ALICE Collaboration in pp collisions at √s=7TeVin the transverse momentum and rapidity (y) intervals 1 <pT<8GeV/cand |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 pp collisions at √s=7TeVin 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 + cbaryons was also measured by the ALICE Collaboration in p–Pb collisions at √sNN =5.02 TeV in 2 <pT<12 GeV/cand −0.96 <y <0.04 [11], and a measurement in the same collision system by the LHCb Collaboration [14]is also available. The + cnuclear modification factor RpPb is compatible with unity within statistical and systematic uncertainties. The baryon-to-meson ratios + c/D0measured in pp 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 + cand its charge conjugate in Pb–Pb collisions at √sNN =5.02 TeV with the ALICE detector [17]at the LHC. Hereafter, crefers indistinctly to both particle and anti-particle, and all mentioned decay channels refer also to their charge conjugates. The + ccorrected yield is obtained as the average of the particle and the anti-particle yield. The notation + cis used when referring to this average, and thus to indicate physics quantities such as the + c/D0ratio. The measurement was performed in the 0–80% centrality class in the transverse momentum and rapidity intervals 6 <pT<12 GeV/cand |y| <0.5. Only prompt c-baryons were considered: the beauty-hadron feed-down was subtracted, as described in the next section. The D0-meson yield was obtained in the same transverse momentum and centrality interval as the c-baryon, following the analysis procedure described in Ref. [18]. 2. Data sample and analysis strategy The measurement of the c-baryon production was performed by reconstructing the decays + c→pK0 Swith a branching ratio (BR) equal to (1.58 ±0.08)% and K0 S→π+π−with BR =(69.20 ±0.05)%[19]. The D0mesons were reconstructed in the decay channel D0→K−π+with BR =(3.93 ±0.04)%[19]. The cand D0candidates 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 ±112.5m from the nominal interaction point and composed of two proton and two neutron calorimeters. The analysed data sample consists of about 83 ×106Pb–Pb collisions at √sNN =5.02 TeV, corresponding to an integrated luminosity of Lint ≈13.4μb −1. The interaction trigger was provided by the coincident signals from the two arrays of the V0 detector, covering the pseudorapidity intervals −3.7 <η<−1.7 and 2.8 <η<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 ±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 ccandidates were constructed by combining a proton candidate track with a K0 Scandidate identified through its V- shaped neutral decay topology (V0). The charged tracks and the K0 S 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 K0 Swere applied: a maximum distance of closest approach between the V0decay tracks of 0.4 cm, a minimum cosine of the V0pointing angle to the primary vertex of 0.9998, a minimum pTof the K0 Scandidates of 1GeV/c, and a cut in the Armenteros-Podolanski space [26]to remove contributions from  decays. The identification of protons was based on the specific ionisation energy loss dE/dxin the TPC and on the time of flight measured with the TOF detector, using as a discriminating variable (nσ) the difference between the measured value and the expected value for the proton mass hypothesis divided by the detector resolution. A |nσ| <3 selection was applied on the TPC dE/dxand TOF time- of-flight measurements for tracks with pT<3 GeV/c. For tracks with pT>3 GeV/can asymmetric selection was used to limit the contamination from pions in the TPC and from kaons in the TOF and the requirements were −3 <nTPC σ<2 and −2 <nTOF σ<3for the TPC and TOF signals. Tracks without TOF information were discarded. The ccandidates were selected requiring a cosine of the proton emission angle in the ccentre-of-mass system with respect to the cmomentum direction smaller 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 cflight line and the momentum vector is smaller than 90◦). The D0candidates were reconstructed by combining pairs of tracks with the proper charge sign combination and selected in the interval 6 <pT<12 GeV/cusing the same criteria described in Ref. [18]for the interval 6 <pT<7GeV/cin the 10% most central Pb–Pb collisions. After all selections, the acceptance in rapidity for cand D0 candidates drops steeply to zero for |y| >0.8in the pTinterval used for the analysis. Therefore, a fiducial acceptance cut |y| <0.8 was applied as described in Refs. [11] and [18]. The cand D0raw 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 c, the width of the Gaussian was fixed to the value obtained from Monte Carlo simulations. The stability of the csignal 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 D0-meson yield, the contribution of signal candidates with the wrong K–πmass 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]. 214 ALICE Collaboration / Physics Letters B 793 (2019) 212–223 Fig. 1. Invariant-mass distributions for the c(left) and D0(right) candidates in the momentum interval 6 <pT<12 GeV/cand 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 invariant mass distributions of the selected cand D0can- didates are shown in Fig. 1. The prompt + c(D0) production yield was calculated as dN+ c(D0) prompt dpT      |y|<0.5=1 2 1 cy 1 pT fprompt ·Nraw||y|<0.8 (Acc ×ε)prompt ·BR ·Nevt ,(1) where Nraw is the raw yield (sum of particles and anti-particles) in the transverse momentum interval of width pT, fprompt is the fraction of prompt c(D0) in the raw yield, (Acc ×ε)is the product of acceptance and reconstruction efficiency for prompt c(D0), BR is the branching ratio of the considered decay mode and Nevt is the number of events considered for the analysis. The correction factor for the rapidity coverage cywas computed as the ratio of the generated c(D0) yield in |y| <0.8 and that in |y| <0.5. The factor 1/2takes 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 √sNN =5.02 TeV were simulated using the HIJING v1.383 [28] generator and prompt and feed-down c(D0) 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 pTdistributions of the cand D0in PYTHIA were corrected in order to obtain more realistic distributions. The same pT-dependent weighting factor, calculated as the ratio of the measured D0pTdistribution in finer pTbins [18] and the one simulated with PYTHIA, was used for both particles. The cand D0 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 cbaryons and D0mesons with centrality. The applied weights were calculated as the product of the RAA of the D0and the average number of nucleon–nucleon collisions (<Ncoll >) in the centrality class considered [18]. The (Acc×ε)value is about 6% for prompt and about 9% for feed-down cand about 8% for prompt and about 11% for feed-down D0. The prompt c(D0) fraction, fprompt, was calculated as fprompt =1−⎛ ⎝ Nc(D0) feed-down Nc(D0) prompt ⎞ ⎠= =1−TAA·d2σ dydpT    FONLL feed-down ·Rfeed-down AA ·(Acc ×ε)feed-down ·cy·pT·BR ·Nevt Nraw/2.(2) The contribution of c(D0) 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 c baryons f(b →c) =0.073 was taken from Ref. [34]. The beautyhadron decay kinematics were modeled using the EVTGEN [35] package. The (Acc ×ε)feed-down term for both particles was calculated from the Monte Carlo simulations described above. The average nuclear overlap function, TAA, was estimated via Glauber model calculations [36,37]. In this formalism the nuclear modification factor RAA is then the ratio of the yield in Pb–Pb collisions and the production cross section in pp collisions scaled by TAA. A hypothesis on the Rfeed-down AA of feed-down cand D0is used. For the D0, the hypothesis is the same as in other analyses (e.g. in Ref. [18]): the central value is obtained by assuming Rfeed-down D0 AA /Rprompt D0 AA =2, justified by the CMS measurement of J/ψfrom 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 <Rfeed-down D0 AA /Rprompt D0 AA <3to estimate the systematic uncertainty. Since no measurements of beauty-baryon production in nucleus–nucleus collisions are available, for the cthe central hypothesis was taken from model calculations which predict Rfeed-down + c AA /Rprompt + c AA =2 when considering c and b quark fragmentation and energy loss in the medium [40]. The ratio Rfeed-down + c AA /Rprompt + c AA was decomposed into two terms to estimate the uncertainty on the assumption: Rfeed-down + c AA Rprompt + c AA =Rfeed-down D0 AA Rprompt D0 AA · (+ c/D0)PbPb,feed-down (+ c/D0)pp,feed-down (+ c/D0)PbPb,prompt (+ c/D0)pp,prompt .(3) The first term is the same as for the D0and thus the same hypothesis is adopted. The second term is varied in the range 0.5–1.5 ALICE Collaboration / Physics Letters B 793 (2019) 212–223 215 Fig. 2. + c/D0ratio as a function of pTin 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. Table 1 Systematic uncertainties on the corrected yields. When the uncertainty was found to be <1%, it was considered negligible (negl. in the table). Uncertainty + cD0 Raw-yield extraction 8% 2% Tracking efficiency 3.6% 5% PID 5% negl. Cut variation 2% 5% MC pTshape 2% negl. MC centrality weights 3% negl. Feed-down subtraction +6 −12%+12 −13% Branching ratio 5% 1% to calculate the systematic uncertainty. The upper limit is determined a-posteriori such that Rfeed-down + c AA <2as suggested by the fact that no baryon RAA exceeds this value. The uncertainties on the two terms are added in quadrature. The resulting values of fprompt are about 0.93 and 0.81 for the cand D0, respectively. A summary of the systematic uncertainties on the corrected + c and D0yields is shown in Table 1. The D0systematic uncertainties on the particle identification (PID), tracking and cut variation are taken from Ref. [18] and are not discussed in the following. The systematic uncertainty on the raw-yield extraction for c and D0was 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 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 a fit to the sidebands. For the 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 decays and an inclusive K0 Ssample 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 pT-differential uncertainty of the cusing a Monte Carlo simulation. A 3% systematic uncertainty on the ITS-TPC matching efficiency of proton tracks was assigned while for the K0 Sthe 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 cPID efficiency was evaluated using protons from the decay of baryons. The ratio of the 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 pTdistributions of the cand the D0. The central values of the correction factors were obtained by re-weighting the cand D0distributions generated by PYTHIA as described above. For the D0, the efficiencies calculated with and without the pTweights are compatible and therefore no uncertainty was assigned. For the c, the systematic uncertainty was defined by considering the variation of the efficiencies determined with different generated pT shapes. The new cpTshape was calculated by multiplying the measured D0pTdistribution with the + c/D0ratios 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 Ncolland, for the c, using as an alternative centrality weight the product /K0 S·Ncoll, where the ratio /K0 Sis taken from Ref. [8]. The systematic uncertainty on the subtraction of feed-down from beauty-hadron decays was estimated by varying (i) the pT-differential cross section of feed-down c(D0) from FONLL calculations within the theoretical uncertainties (see Ref. [11]for details on the cand Ref. [33]for the D0) and (ii) the ratio of prompt and feed-down RAA as described above. The production yields of cand D0also have a global systematic uncertainty due to the branching ratio. 3. Results The yield of prompt + cbaryons measured in Pb–Pb collisions at √sNN =5.02 TeV in the 0–80% centrality class in |y| <0.5 and 6 <pT<12 GeV/cis N+ c=(2.1 ±0.4(stat.)+0.3 −0.4(syst.)) ×10−2. The measured + c/D0ratio is shown in Fig. 2. The systematic uncertainty of the + c-baryon production arising from the track- 216 ALICE Collaboration / Physics Letters B 793 (2019) 212–223 Fig. 3. RAA of prompt + ccompared with model calculations [7,15,16](left), and the non-strange D mesons, D+ s, and charged particle RAA in 0–10% most central Pb–Pb collisions for pT>1GeV/c[18,42](right). Statistical, systematic and normalisation uncertainties are presented as vertical bars, empty boxes and shaded boxes around unity, respectively. ing efficiency was treated as fully correlated to that of the D0 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 + cand D0cross 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 + c/D0ratio measured in Pb–Pb collisions is compared with the results obtained by the ALICE Collaboration in minimum-bias pp and p–Pb collisions at √s=7 TeV and √sNN =5.02 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 <pT<12 GeV/c. The + c/D0ratio 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 pTthe coalescence probability decreases and eventually vacuum fragmentation takes over. For D0mesons, 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 e+e−collisions are used to fix the shape of the fragmentation functions for + 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 chadrons 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 + c/D0ratio 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 + c/D0ra- tio because the relative production of single-charm baryons and single-charm mesons RBM is treated as a parameter of the model. The curve obtained by considering RBM =0.425, which is the value needed to describe the results in pp and p–Pb collisions, underestimates the + c/D0ratio measured in Pb–Pb collisions. An RBM =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 pTdependence of the + c/D0ratio, which needs to be verified by comparing to a measurement at lower pT. The RAA of prompt + cwas obtained by considering as reference the + ccross section measured in p–Pb collisions at √sNN =5.02 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 pTinterval to |y| <0.5using 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 + cbaryons, the average of the correction factors obtained for D0, D+and bare charm quarks, which was found to be 1.024 ±0.008, was used. The choice of using the p–Pb cross section to obtain the reference for the RAA was motivated by the fact that it was measured up to pT=12 GeV/c, while the measurement in pp collisions at √s=7TeVin |y| <0.5only reaches pT=8GeV/c. In addition, the + cnuclear modification factor measured in p–Pb collisions is consistent with unity for pT>2GeV/c[11]. The + creference cross section in 6 <pT<12 GeV/cwas obtained by combining the results in the transverse momentum intervals 6 <pT<8GeV/c and 8 <pT<12 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 pT. The + cRAA also has a 3.75% uncertainty due to the normalisation of the + cp–Pb cross section at √sNN =5.02 TeV [11] and a 2.4% uncertainty on the average nuclear overlap function TAA, which were added in quadrature. In the left panel of Fig. 3, the RAA of prompt + cis 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 + cRAA 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 pTinterval of this first measurement prevent us to ALICE Collaboration / Physics Letters B 793 (2019) 212–223 217 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 + cproduction mechanism in pp collisions to interpret the RAA measurement. The right panel of Fig. 3shows the RAA of prompt + cbaryons measured in the 0–80% centrality class (that is dominated by the 0–10% production given the scaling of the yields with Ncoll ·RAA) compared with the average nuclear modification factors of non-strange D mesons, D+ smesons, and charged particles measured in the 0–10% centrality class [18]. The RAA of charged particles is smaller than that of D mesons by more than 2σof the combined statistical and systematic uncertainties up to pT=8GeV/c, while they are compatible within 1σ for pT>10 GeV/c. The RAA values of D+ smesons 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 + cRAA with respect to non-strange D mesons is observed, although the results are compared for different centrality classes. A D0RAA =0.27 ±0.01(stat.) ±0.04(syst.) was measured in 6 <pT<12 GeV/cin the 0–80% centrality class. The D0RAA has also a 3.5% uncertainty arising from the normalisation of the cross section measured in pp collisions at √s=7TeV, and a 2.4% uncertainty on the average nuclear overlap function TAA. The pT-differential cross section of prompt D0mesons with |y| <0.5in pp collisions at √s=5.02 TeV, used as reference for the nuclear modification factor, was obtained by scaling the measurement at √s=7TeV[44]to √s=5.02 TeV using FONLL calculations [31,32]. The scaling was applied to the D0cross section obtained in 6 <pT<12 GeV/cby combining the results in the pTintervals of the measurement at √s=7TeV. 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 pT intervals. A difference of about 1.7σis obtained when comparing the + cRAA with that of the D0in 6 <pT<12 GeV/cand 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 + cbaryons in the 0–80% most central Pb–Pb collisions at √sNN =5.02 TeV was presented. The result was obtained at midrapidity, |y| <0.5, in the 6 <pT<12 GeV/ctransverse momentum interval. The + c/D0ratio is larger than the ratio measured in pp and p–Pb collisions at √s=7 TeV and √sNN =5.02 TeV [11], respectively. The + c/D0ratio 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 + cnuclear modification factor with non-strange D and D+ smeson 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 + c-baryon and 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 + c-baryon production measurement with finer granularity in pTand 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 218 ALICE Collaboration / Physics Letters B 793 (2019) 212–223 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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