This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): ALICE Collaboration Title: Evidence of rescattering effect in Pb–Pb collisions at the LHC through production of K*(892)0 and ϕ(1020) mesons Year: 2020 Version: Published version Copyright: Rights: © 2020 The Authors. Published by Elsevier B.V. CC BY 4.0 Rights url: https://creativecommons.org/licenses/by/4.0/ Please cite the original version: ALICE Collaboration (2020). Evidence of rescattering effect in Pb–Pb collisions at the LHC through production of K*(892)0 and ϕ(1020) mesons. Physics Letters B, 802, 135225. DOI: 10.1016/j.physletb.2020.135225 Physics Letters B 802 (2020) 135225 Contents lists available at ScienceDirect Physics Letters B www.elsevier.com/locate/physletb Evidence of rescattering effect in Pb–Pb collisions at the LHC through production of K∗ (892)0 and φ(1020) mesons .ALICE Collaboration ⋆ a r t i c l e i n f o Article history: Received 21 November 2019 Received in revised form 10 January 2020 Accepted 13 January 2020 Available online 16 January 2020 Editor: L. Rolandi a b s t r a c t 1. Introduction Several measurements in high-energy heavy-ion collisions at the Large Hadron Collider (LHC) [1–3] and the Relativistic Heavy Ion Collider (RHIC) [4–9] have shown that a strongly-coupled Quark-Gluon Plasma (QGP) is formed that subsequently hadronizes. Resonances, short lived hadrons that decay via strong interactions, play an important role in characterizing the properties of hadronic matter formed in heavy-ion collisions [10–16]. Several resonances have been observed in pp and nuclear collisions [10–19]: f 2 (1270), ρ (770)0 , (1232)++ , f 0 (980), K∗ (892)0,± , (1385), (1520) and φ(1020) with lifetimes of the order of 1.1 fm/c, 1.3 fm/c, 1.6 fm/c, 2.6 fm/c, 4.16 fm/c, 5.5 fm/c, 12.6 fm/c and 46.3 fm/c, respectively [20]. The wide range of their lifetimes allows them to be good probes of the dynamics of the system formed in ultrarelativistic heavy-ion collisions [21–27]. In the hadronic phase of the evolution of the system formed in heavy-ion collisions, there are two important temperatures and corresponding timescales: the chemical freeze-out, when the inelastic collisions among the constituents are expected to cease, and the later kinetic freeze-out, when all (elastic) interactions ⋆ E-mail address: alice-publications@cern.ch. √ Measurements of K∗ (892)0 and φ(1020) resonance production in Pb–Pb and pp collisions at sNN = 5.02 TeV with the ALICE detector at the Large Hadron Collider are reported. The resonances are measured at midrapidity (| y | < 0.5) via their hadronic decay channels and the transverse momentum (p T ) distributions are obtained for various collision centrality classes up to p T = 20 GeV/c. The p T -integrated yield ratio K∗ (892)0 /K in Pb–Pb collisions shows significant suppression relative to pp collisions and decreases towards more central collisions. In contrast, the φ(1020)/K ratio does not show any suppression. Furthermore, the measured K∗ (892)0 /K ratio in central Pb–Pb collisions is significantly suppressed with respect to the expectations based on a thermal model calculation, while the φ(1020)/K ratio agrees with the model prediction. These measurements are an experimental demonstration of rescattering of K∗ (892)0 decay products in the hadronic phase of the collisions. The K∗ (892)0 /K yield ratios in Pb–Pb and pp collisions are used to estimate the time duration between chemical and kinetic freeze-out, which is found to be ∼ 4–7 fm/c for central collisions. The p T -differential ratios of K∗ (892)0 /K, φ(1020)/K, K∗ (892)0 /π , φ(1020)/π , p /K∗ (892)0 and p /φ(1020) are also presented √ sNN = 5.02 TeV. These ratios show that the rescattering effect is for Pb–Pb and pp collisions at predominantly a low-p T phenomenon.  2020 The Author(s). 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 . stop [28–30]. If resonances decay before kinetic freeze-out, then their decay products are subject to hadronic rescattering that alters their momentum distributions. This leads to inability to reconstruct the parent resonance using the invariant mass technique, resulting in a decrease in the measured yield relative to the primordial resonance yield, i.e. the yield at chemical freeze-out. The fraction of resonances that cannot be recovered depends on the lifetime of the hadronic phase (defined as the time between chemical and kinetic freeze-out), the hadronic interaction cross section of resonance decay products, the particle density in the medium and the resonance phase space distributions. For example, a pion from a K∗ (892)0 meson decay could scatter with another pion in the medium as π − π + → ρ 0 → π − π + . At the same time, after the chemical freeze-out, pseudoelastic interactions could regenerate resonances in the medium, leading to an enhancement of their yields. For example, interactions like π K → K∗ (892)0 → π K and K− K+ → φ(1020) → K− K+ could happen until kinetic freeze-out. Hence, resonances are probes of the rescattering and regeneration processes during the evolution of the fireball from chemical to kinetic freeze-out. Indeed, transport-based model calculations show that both rescattering and regeneration processes affect the final resonance yields [31,32]. Thermal statistical models, which have successfully explained a host of particle yields in heavy-ion collisions across a wide range of center-of-mass energies [33–36], are https://doi.org/10.1016/j.physletb.2020.135225 0370-2693/ 2020 The Author(s). 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 . 2 ALICE Collaboration / Physics Letters B 802 (2020) 135225 able to explain the measured resonance yields only after including rescattering effects [37,38]. In this paper, the measurement of the production of K∗ (892)0 and φ(1020) vector mesons at midrapidity in Pb–Pb and pp col√ lisions at sNN = 5.02 TeV is presented. Although both vector mesons have similar masses, their lifetime differs by a factor of larger than 10. This aspect is exploited to establish the dominance of rescattering in central Pb–Pb collisions at the LHC. The kaon and pion daughters of the short-lived K∗ (892)0 → Kπ rescatter with other hadrons in the medium. The magnitude of the effect is mainly determined by the pion-pion interaction cross section [39], which is measured to be significantly larger (factor 5) than the total kaon-pion interaction cross section [40]. The latter determines the magnitude of the regeneration effect [41]. Thus with rescattering dominating over regeneration, the observable K∗ (892)0 yields should decrease compared to the primordial yields, and therefore, a suppression of the K∗ (892)0 /K yield ratio is expected in heavy-ion collisions relative to pp collisions. Furthermore, this ratio is expected to decrease with increase in system size, which is determined by the collision centrality (maximum for central collisions). In contrast, because of a larger lifetime compared to that of the hadronic phase, the φ(1020) meson yields are not expected to be affected by rescattering [14,32]. The φ(1020) mesons are also expected not to be affected by the regeneration due to significantly lower KK cross section compared to Kπ and ππ cross sections [39,40]. Hence the independence of the φ(1020)/K yield ratio of the system size will act as a baseline for corresponding K∗ (892)0 /K measurements, thereby supporting the presence of the rescattering effect in heavy-ion collisions. The lower K∗ (892)0 /K √ yield ratio in Pb–Pb collisions compared to pp at the same sNN can then be used to estimate the time span between chemical and kinetic freeze-out in heavy-ion collisions. Furthermore, due to the scattering of the decay products, the low-p T K∗ (892)0 are less likely to escape the hadronic medium before decaying, compared to high-p T K∗ (892)0 [32]. This could alter the K∗ (892)0 p T spectra in Pb–Pb collisions compared to pp, while no such effect is expected for φ mesons. Therefore, studying p T -differential ratios of K∗ (892)0 and φ(1020) mesons with respect to other non-strange (π ) and strange (K) mesons, and baryons (p) in Pb–Pb and pp collisions will help to establish the p T dependence of rescattering effects and disentangle them from other physics processes like radial flow that modifies the shapes of the p T distributions at low and intermediate transverse momenta. In addition, the measure√ ments at sNN = 5.02 TeV are compared to results from Pb–Pb √ collisions at sNN = 2.76 TeV [14,42]. Since production of particles and antiparticles is equal at midrapidity at LHC energies, the ∗ average of the yields of K∗ (892)0 and K (892)0 is presented in this paper and is denoted by the symbol K∗0 unless specified otherwise. The φ(1020) is denoted by the symbol φ . The paper is organized as follows: In section 2, the detectors used in the analysis are briefly described. In section 3, the dataset, the analysis techniques, the procedure for extraction of the yields of K∗0 and φ mesons and the study of the systematic uncertainties are presented. In section 4, the yields obtained by invariant mass reconstruction of K∗0 and φ mesons as a function of trans√ verse momentum in Pb–Pb and pp collisions at sNN = 5.02 TeV, the p T -integrated ratios of K∗0 and φ relative to charged kaons, and p T -differential ratios relative to charged π , K and protons are reported. Finally, in section 5 the findings are summarized. 2. Experimental apparatus The measurements of K∗0 and φ meson production in pp and Pb–Pb collisions have been performed using the data collected by the ALICE detector in the year 2015. The details of the ALICE de- tector can be found in Refs. [43–45]. So we briefly focus on the following main detectors used for this analysis. The forward V0 detector, a scintillator detector with a timing resolution less than 1 ns, is used for centrality selection, triggering and beam-induced background rejection. The V0 consists of two sub-detectors, V0A and V0C, placed at asymmetric positions, one on each side of the interaction point with full azimuthal acceptance and cover the pseudorapidity ranges 2.8 < η < 5.1 and -3.7 < η < -1.7, respectively. The centrality classes in Pb–Pb collisions are determined from the sum of the measured signal amplitudes in V0A and V0C, as discussed in Refs. [46,47]. The collision time information is provided by T0 which consist of two arrays of Cherenkov counters T0A and T0C, positioned on both sides of the interaction point [48]. The Zero Degree Calorimeter (ZDC) consists of two tungsten-quartz neutron and two brass-quartz proton calorimeter placed at a distance of 113 m on both sides of the interaction point. It is used to reject the background events and to measure the spectator nucleons. In the central barrel, the Inner Tracking System (ITS) and the Time Projection Chamber (TPC) are used for charged-particle tracking and primary collision vertex reconstruction. The ITS consists of three sub-detectors of two layers each, covering a central pseudorapidity range |η| < 0.9: Silicon Pixel Detector (SPD), Silicon Drift Detector (SDD) and Silicon Strip Detector (SSD). The TPC is the main charged particle tracking detector, and has full azimuthal coverage in the pseudorapidity range |η| < 0.9. Along with track reconstruction, it also provides a measurement of the momentum and excellent particle identification (PID). The TPC provides the measured specific energy loss (dE /dx) to identify the particles, especially in low momentum range (p < 1 GeV/c) where the dE /dx of particles are well separated. To extend the particle identification to higher p T , the Time of Flight (TOF) detector is used in addition to the TPC information. The TOF is based on the Multigap Resistive Plate Chamber (MRPC) technology and measures the arrival times of particles with a resolution of the order of 80 ps. It covers a pseudorapidity range |η| < 0.9 and provides excellent PID capabilities in the intermediate p T range by exploiting the time-of-flight information. 3. Data sample and analysis details The pp data were collected using a minimum bias (MB) trigger. The logic for MB trigger requires at least one hit in V0A or V0C and one hit in the central barrel detector SPD in coincidence with the LHC bunch crossing [49,50]. In pp collisions, a criterion based on the offline reconstruction of multiple primary vertices in the SPD [45] is applied to reduce the pileup, which is caused by multiple interactions in the same bunch crossing. The rejected pileup events are less than 1% of the total events. The Pb–Pb data were also collected using a MB trigger with a logic that requires a coincidence of signals in V0A and V0C. The MB-triggered events are analyzed if they have a reconstructed collision vertex whose position along the beam axis (V z , z is the longitudinal direction) is within 10 cm from the nominal interaction point in both pp and Pb–Pb collisions. Background events are rejected using the timing information from the Zero Degree Calorimeters (ZDCs) and V0 detectors. The Pb–Pb analysis is performed in 8 centrality classes defined in Ref. [46]: 0–10%, 10–20%, 20–30%, 30–40%, 40–50%, 50–60%, 60–70% and 70–80%. The 0–10% class corresponds to the most central Pb–Pb collisions, with small impact parameter, while the 70–80% class corresponds to peripheral Pb–Pb collisions, with large impact parameter. The total number of events that are analyzed after passing the event selection criteria are ∼110 million for pp and ∼30 million for Pb–Pb collisions. Charged tracks are selected 3 ALICE Collaboration / Physics Letters B 802 (2020) 135225 for analysis based on track selection criteria that ensure good track quality, as done in previous work [42]. In particular, a track in the TPC is requested to have a minimum of 70 crossed rows (horizontal segments along the transverse readout plane of the TPC) out of a maximum possible 159 [51]. A p T -dependent selection criterion on the distance of closest approach to the collision vertex in the transverse (xy) plane (DCAxy ) and along the longitudinal direction (DCA z ) is used to reduce the contamination from secondary charged particles coming from weakly decaying hadrons. In addition to these selection criteria, tracks are required to have p T > 0.15 GeV/c in both pp and Pb–Pb collisions. Charged particles are accepted in the pseudorapidity range |η| < 0.8, which ensures a uniform acceptance. The particle identification exploits both the TPC and the TOF. For K∗0 and φ reconstruction in Pb–Pb collisions, charged particles are identified as pion or kaon if the mean specific energy loss (dE /dx) measured by the TPC falls within two standard deviations (2σTPC ) from the expected dE /dx values for π or K over the entire momentum range. If the TOF information is available for the track, in addition to the TPC, a TOF-based selection criterion 3σTOF is applied over the measured momentum range, where σTOF is the standard deviation from the expected time-of-flight for a given species. These requirements help in reducing the background under the signal peak over a large momentum range and provide a better separation between signal and background with respect to TPC PID only. For K∗0 reconstruction in pp collisions, the same PID selection criteria are applied to identify pion and kaon candidates as are used in Pb–Pb collisions. For the φ reconstruction in pp collisions, the kaon candidates are identified using a 6σTPC , 4σTPC and 2σTPC selection on the measured dE /dx distributions in the momentum ranges p < 0.3 GeV/c, 0.3 < p < 0.4 GeV/c and p > 0.4 GeV/c, respectively. On top of this, the TOF-based selection criterion of 3σTOF is applied over the entire measured momentum range in pp collisions if the TOF information is available. pairs that originate from jets and from the misidentification of particles. It is shown in Ref. [42] that the residual background has a smooth dependence on mass and the shape of the background is well described by a second order polynomial [14,42]. The invariant mass distributions after mixed-event background subtraction are fitted with a Breit-Wigner (resp. Voigtian) function for the signal peak of K∗0 (resp. φ ) plus a second order polynomial for the residual background [42]. The Voigtian function is a convolution of a Breit-Wigner distribution and a Gaussian, where the width σ of the Gaussian accounts for the mass resolution. The latter is p T -dependent and varies between 1 and 2 MeV/c 2 . The raw yields are measured as a function of p T for K∗0 and φ in pp collisions and in various centrality classes in Pb–Pb collisions. A detailed description of the yield extraction procedure is given in Ref. [42]. The measured yields are affected by the detector acceptance and reconstruction efficiency ( A × εrec ). This is estimated by means of dedicated Monte Carlo simulations using the PYTHIA (PYTHIA 6 Perugia 2011 tune and PYTHIA 8 Monash 2013 tune) [52,53] and HIJING [54] event generators for pp and Pb–Pb collisions, respectively. The generated particles are then propagated through the detector material using GEANT3 [55]. The A × εrec is calculated as a function of p T and is defined as the ratio of the reconstructed K∗0 (φ ) to the generated K∗0 (φ ), both within | y | < 0.5. For the reconstruction of resonances, the same track and PID selection criteria are applied to the simulations as used in the analysis of the measured data. The A × εrec is calculated for K∗0 (φ ) that decay through the hadronic channel K± π ∓ (K+ K− ), hence it does not include the correction for BR. In Pb–Pb collisions, the A × εrec has a weak centrality dependence and the raw yields are corrected using the A × εrec of the respective centrality class. The procedure to correct the raw yields is given by 3.1. Yield extraction, corrections and normalization The raw yields are normalized to the number of accepted events acc (N event ) and corrected for A × εrec , trigger efficiency (εtrig ), vertex reconstruction efficiency (εvert ), signal loss (εsig ) and the BR of the decay channel. The yields in pp are normalized to the number of inelastic collisions with a trigger efficiency correction, εtrig = 0.757 ± 0.019 [56]. The vertex reconstruction efficiency in pp collisions is found to be εvert = 0.958. The signal loss correction factor εsig is determined based on MC simulations as a function of p T and accounts for the resonance signal lost due to trigger inefficiencies. The εsig (p T ) correction is only significant for p T < 2.5 GeV/c and has a value of less than 5% both for K∗0 and φ in pp collisions. In Pb–Pb collisions, the yields of K∗0 and φ in a given centrality class are normalized by the number of events in the respective V0M (sum of V0A and V0C amplitude) event centrality class. The correction factors εtrig , εvert and εsig (p T ) are compatible with unity in the reported centrality classes in Pb–Pb collisions and hence are not used. The K∗0 and φ resonances are reconstructed by calculating the invariant mass of their decay products through the hadronic decay ∗0 channels K∗0 (K ) → K+ π − (K− π + ) (Branching Ratio, BR = 66.666 ± 0.006% [20]) and φ → K+ K− (BR = 49.2 ± 0.5% [20]), respectively. Oppositely charged K and π (or K) from the same event are paired to reconstruct the invariant mass distributions of K∗0 (φ ). The Kπ and KK pairs are selected in the rapidity range | y | < 0.5 in both pp and Pb–Pb collisions. The invariant mass distribution exhibits a signal peak and a large combinatorial background resulting from the uncorrelated Kπ (KK) pairs. The combinatorial background is estimated using a mixed-event technique in both collision systems. The mixed-event background is constructed by combining kaons from one event with the oppositely charged π (K) from different events for K∗0 (φ). The events which are mixed are required to have similar characteristics. In Pb–Pb, two events are mixed if they belong to the same centrality class and the difference between the collision vertex position is | V z | < 1 cm. In pp collisions, two events are mixed with a condition of | V z | < 1 cm and a difference in charged-particle density at midrapidity (| y | < 0.5) of less than 5. To minimize the statistical fluctuations in the background distribution, each event is mixed with five other ones. The invariant mass distribution from the mixed-event is normalized to the same-event oppositely-charged pair distribution in the mass region 1.1–1.3 (resp. 1.04–1.06) GeV/c 2 for K∗0 (resp. φ ), which is away from the mass peak (6Ŵ for K∗0 and 7Ŵ for φ , Ŵ is the width of the resonance). After the combinatorial background subtraction, the signal peak is observed on top of a residual background. The latter is due to the correlated Kπ or KK 1 d2 N N event d ydp T = 1 acc N event d2 N raw εtrig . εvert . εsig d ydp T ( A × εrec ) . BR . (1) 3.2. Systematic uncertainties The systematic uncertainties in the measurement of K∗0 and φ yields in pp and Pb–Pb collisions are summarized in Table 1. The sources of systematic uncertainties are related to the yield extraction method, PID and track selection criteria, global tracking efficiency, the knowledge of the ALICE material budget and of the interaction cross section of hadrons in the detector material. The uncertainties are reported for three transverse momentum values, low, mid and high p T . For Pb–Pb collisions all the systematic uncertainties except the one related to the yield extraction are common in the various centrality classes and the values given in the 4 ALICE Collaboration / Physics Letters B 802 (2020) 135225 Table 1 √ Systematic uncertainties in the measurement of K∗0 and φ yields in pp and Pb–Pb collisions at sNN = 5.02 TeV. These uncertainties are shown for three transverse momentum values, low, mid and high p T . For Pb–Pb collisions all the systematic uncertainties except yield extraction are common in various centrality classes and the values given in the table are averaged over all centrality classes. Systematic variation Pb–Pb pp K∗0 φ K∗0 p T (GeV/c) p T (GeV/c) p T (GeV/c) φ p T (GeV/c) 0.6 4.5 18 0.5 4.25 18 0.1 4.25 18 0.5 4.25 18 Yield extraction (%) Track selection (%) Particle identification (%) Global tracking efficiency (%) Material budget (%) Hadronic Interaction (%) 7.3 2.7 5.4 4.7 1.4 2.4 7.5 1.4 3.0 7.4 0 0 10.1 3.0 5.0 4.0 0 0 4.4 3.0 1.0 4.7 5.7 1.3 1.9 1.3 1.5 8.2 0 0 4.9 1.0 2.4 3.1 0 0 11.8 1.4 2.1 2.0 3.4 2.8 7.9 1.0 3.2 3.1 0 0 8.2 1.9 6.9 3.4 0 0 2.4 4.0 0.3 2.0 5.7 1.3 3.5 2.0 1.7 3.2 0 0 3.5 5.5 6.5 2.4 0 0 Total (%) 10.9 11.0 12.3 9.2 8.6 6.4 13.0 9.1 11.4 7.7 5.4 9.5 Fig. 1. The p T distributions of (a) K∗0 and (b) φ mesons in pp collisions and various centrality classes in Pb–Pb collisions at center of each bin. The statistical and systematic uncertainties are shown as bars and boxes, respectively. table are averaged over all centralities. The yield extraction method includes the uncertainties due to variations of the fitting range, the choice of combinatorial background estimation technique, normalization range and residual background shape. The uncertainties due to yield extraction are estimated to be 7.9–11.8% for K∗0 (resp. 2.4–3.5% for the φ ) in pp and 7.3–10.1% (resp. 1.9–4.9%) in Pb–Pb collisions. The PID systematic uncertainties varies between 2.1–6.9% (0.3–6.5%) for K∗0 (φ ) in pp and Pb–Pb collisions. The contribution to the uncertainty from the global tracking efficiency is calculated from the corresponding values for single charged particles [51] and results in a 2.0–8.2% uncertainty by combining the two charged tracks used in the invariant mass reconstruction of K∗0 and φ . The contribution from variation of the track selection criteria is 1.0–5.5%. The systematic uncertainties due to the hadronic interaction cross section are estimated to be less than 2.8% and contribute only at low p T (< 2 GeV/c). The uncertainties in the description of the material budget of ALICE detector subsystems in GEANT3 (see Ref. [57] for details) give a contribution lower than 5.7% on the yields of K∗0 and φ in pp and Pb–Pb collisions. The material budget uncertainty is significant only at p T < 2 GeV/c and negligible at higher p T . The total p T -dependent systematic uncertainties on the K∗0 (φ ) yields are estimated to be 9.1–13.0% (5.4–9.5%) in pp collisions and 10.9–12.3% (6.4–9.2%) in Pb–Pb collisions. The common systematic uncertainties for different particles (global tracking efficiency, material budget and √ sNN = 5.02 TeV. The values are plotted at the hadronic interaction) are canceled out in calculating particle yield ratios like K∗0 /K and φ/K. 4. Results and discussion 4.1. Transverse momentum spectra in pp and Pb–Pb collisions The p T distributions of the K∗0 and φ mesons for | y | < 0.5, normalized to the number of events and corrected for efficiency, acceptance and branching ratio of the decay channel, are shown in Fig. 1. The results for Pb–Pb collisions are presented for eight different centrality classes (0–10% up to 70–80% in 10% wide centrality intervals) together with the results from inelastic pp collisions at the same energy. The p T -integrated particle yields have been extracted using the procedure described in Refs. [14,42]. The p T distributions are fitted with a Lévy-Tsallis function [58,59] in pp and a Boltzmann-Gibbs blast-wave function [60] in Pb–Pb collisions. The yields have been extracted from the data in the measured p T region and the fit functions have been used to extrapolate into the unmeasured (low and high p T ) region. The low-p T extrapolation covers p T < 0.4 GeV/c for K∗0 (φ ) and accounts for 8.6% (7.2%) and 12.5% (12.7%) of the total yield in the 0–10% and 70–80% centrality classes in Pb–Pb collisions, respectively. In pp collisions, the K∗0 is measured in the range 0 < p T < 20 GeV/c. For the φ meson, the low-p T extrapolation covers p T < 0.4 GeV/c, accounting for 15.7% of the total ALICE Collaboration / Physics Letters B 802 (2020) 135225 Fig. 2. p T -integrated particle yield ratios K∗0 /K− and φ/K− as a function of √ dN ch /dη1/3 measured at midrapidity in pp, p–Pb and Pb–Pb collisions at sNN √ − = 5.02 TeV. For Pb–Pb collisions at sNN = 2.76 TeV, the φ/K values are taken from Ref. [14] and the K∗0 /K− values are taken from Ref. [42]. The ratios for p– Pb collisions are taken from Ref. [17]. Statistical uncertainties (bars) are shown together with total (hollow boxes) and charged-particle multiplicity-uncorrelated (shaded boxes) systematic uncertainties. Thermal model calculations with chemical freeze-out temperature T ch = 156 MeV for the most central Pb–Pb collisions [34,64] are also shown. EPOS3 model predictions [32] of K∗0 /K and φ/K ratios in Pb–Pb collisions are also shown as violet lines. yield. The extrapolated fraction of the yield is negligible for p T > 20 GeV/c. 4.2. Particle ratios Fig. 2 shows the K∗0 /K and φ/K ratios as a function of √ dN ch /dη1/3 [46,47,51] for Pb–Pb collisions at sNN = 2.76 [14, √ 42] and 5.02 TeV, √ p–Pb collisions at sNN = 5.02 TeV [17] and √ pp collisions at s = 5.02 TeV. The kaon yields in Pb–Pb at sNN = 5.02 TeV are from Ref. [51]. The dN ch /dη1/3 measured at midrapidity, is used here as a proxy for the system size. This is supported by the observation of the linear increase in the HBT radii with dN ch /dη1/3 [61,62]. The K∗0 /K ratio decreases for rising dN ch /dη1/3 while the φ/K ratio is almost independent of dN ch /dη1/3 . The ratios exhibit a smooth trend across the different collision systems and collision energies studied. The K∗0 /K and √ φ/K ratios in Pb–Pb collisions at sNN = 2.76 and 5.02 TeV are in agreement within uncertainties. The resonance yields are modified during the hadronic phase by rescattering (which would reduce the measured yields) and regeneration (which would increase the measured yields). The observed dependence of the K∗0 /K ratio on the charged-particle multiplicity is consistent with the behavior that would be expected if rescattering is the cause of the suppression. The fact that the φ/K ratio does not exhibit suppression with charged-particle multiplicity suggests that the φ , which has a lifetime an order of magnitude larger than that of the K∗0 , decays predominantly outside the hadronic medium. Theoretical estimates suggest that about 55% of the of K∗0 mesons with momentum p = 1 GeV/c, decay within 5 fm/c of production (a typical estimate for the time between chemical and kinetic freeze-out in heavy-ion collisions [22,32,63]), while only 7% of φ mesons with p = 1 GeV/c decay within that time. This supports the hypothesis that the experimentally observed decrease of the K∗0 /K ratio with charged-particle multiplicity is caused by rescattering. A similar suppression has also been observed for ρ 0 /π [15] and ∗ / [13] in central Pb–Pb collisions √ relative to peripheral Pb–Pb and pp collisions at sNN = 2.76 TeV. ∗ 0 In addition, the K /K ratio from thermal model calculations without rescattering effects and with chemical freeze-out temperature 5 Fig. 3. Lower limit on the hadronic phase lifetime between chemical and kinetic √ freeze-out as a function of dN ch /dη1/3 in p–Pb [17] and Pb–Pb collisions at sNN = 5.02 TeV. The bars and bands represent the statistical and systematic uncertainties, respectively, propagated to the lifetime from the uncertainties associated with √ the measured K∗0 /K ratios in Pb–Pb (p–Pb) and pp collisions at sNN = 5.02 TeV. T ch = 156 MeV for the most central Pb–Pb collisions [34,64] is found to be higher than the corresponding measurements, while the measured φ/K ratio agrees with the thermal model predictions. The K∗0 /K and φ/K ratios in Pb–Pb collisions are also compared to EPOS3 model calculations with and without a hadronic cascade phase modeled by UrQMD [32]. The EPOS3 model predic√ tions shown in the figure are for Pb–Pb collisions at sNN = 2.76 TeV but no significant qualitative differences are expected between the two energies. The EPOS3 generator with UrQMD reproduces the observed trend of the K∗0 /K and φ/K ratios which further supports the experimental data. The fact that K∗0 /K− decreases with increasing dN ch /dη1/3 implies that rescattering of the decay products of K∗0 in the hadronic phase is dominant over K∗0 regeneration. This suggests that K∗0 ↔ Kπ is not in balance. Hence in Pb–Pb the K∗0 /K− ratio can be used to get an estimate of the time between chemical and kinetic freeze-out, τ , as, [K∗0 /K− ]kinetic = [K∗0 /K− ]chemical × e −τ /τK∗0 , where τK∗0 is the K∗0 lifetime. Here, τK∗0 is taken as 4.16 fm/c ignoring any medium modification of the width of the invariant mass distribution of K∗0 . Furthermore, it is assumed that [K∗0 /K− ]chemical is given by the values measured in pp collisions and the Pb–Pb collision data provides an estimate for [K∗0 /K− ]kinetic . This is equivalent to assuming that all K∗0 ’s that decay before kinetic freeze-out are lost due to rescattering effects and there is no regeneration effect between kinetic and chemical freeze-out which is supported by AMPT simulations [31]. All the assumptions listed above lead to an estimate of τ as a lower limit for the time span between chemical and kinetic freeze-outs. A decrease in the K∗0 /K ratio with increasing multiplicity has pre√ viously also been observed in p–Pb collisions at sNN = 5.02 TeV [17]. This might indicate the presence of rescattering effect in high multiplicity p–Pb collisions and is suggestive of a finite lifetime of the hadronic phase. For comparison we have also estimated the hadronic phase lifetime in p–Pb data. Fig. 3 shows the results for τ boosted by a Lorentz factor (∼ 1.65 for p–Pb collisions and 1.75 for Pb–Pb collision) as a function of dN ch /dη1/3 . Neglecting higher  order terms, the Lorentz factor is estimated as 1 + ( p T /mc )2 . Here m is the rest mass of the resonance and  p T  is used as an approximation for p for the measurements at midrapidity. The time interval between chemical and kinetic freeze-out increases with the system size as expected. For central Pb–Pb collisions at √ sNN = 5.02 TeV, the lower limit of time between chemical and 6 ALICE Collaboration / Physics Letters B 802 (2020) 135225 ∗0 Fig. 4. Particle yield ratios (K∗0 + K )/(K+ + K− ) in panel (a) and (2φ )/(K+ + K− ) in panel (b), both as a function of p T for centrality classes 0–10% and 70–80% in Pb–Pb √ √ collisions at sNN = 5.02 TeV. For comparison, the corresponding ratios are also shown for inelastic pp collisions at s = 5.02 TeV. The statistical uncertainties are shown ∗0 as bars and systematic uncertainties are shown as boxes. In the text (K∗0 + K ), (K+ + K− ) are denoted by K∗0 and K, respectively. ∗0 Fig. 5. Particle yield ratios (K∗0 + K )/(π + + π − ) in panel (a) and (2φ )/(π + + π − ) in panel (b), both as a function of p T for centrality classes 0–10% and 70–80% in Pb–Pb √ √ collisions at sNN = 5.02 TeV. For comparison, the corresponding ratios are also shown for inelastic pp collisions at s = 5.02 TeV. The statistical uncertainties are shown ∗0 as bars and systematic uncertainties are shown as boxes. In the text (K∗0 + K ), (π + + π − ) are denoted by K∗0 and π , respectively. kinetic freeze-out is about 4–7 fm/c. This is of the same order of magnitude as the K∗0 lifetime, but about an order of magnitude shorter than the φ lifetime. A smooth increase of τ with system size from p–Pb to Pb–Pb collisions is observed. The EPOS3 generator with UrQMD reproduces the increasing trend of τ with multiplicity qualitatively [32]. If a constant chemical freeze-out temperature is assumed, then the increase of τ with multiplicity in Pb–Pb collisions corresponds to a decrease of the kinetic freezeout temperature. This is in qualitative agreement with results from blast-wave fits to identified particle p T distributions [51], which are interpreted as decrease in the kinetic freeze-out temperature from peripheral to central collisions. Further, to quantify the p T -dependence of the rescattering effect observed in Pb–Pb collisions, a set of p T -differential yield ratios was studied: K∗0 /K, φ/K, K∗0 /π , φ/π , p /K∗0 and p /φ as shown in Figs. 4, 5 and 6. The choice of the ratios is motivated by the following reasons: (a) the ratio of resonance yields relative to the ones of kaons and pions can shed light on the shapes of the p T distributions of mesons with different mass and quark content, and (b) the ratios of the proton yield with respect to the yields of the resonances allow comparisons among hadrons of similar mass, but different baryon number and quark content to be made. For case (a), ratios in 0–10%, 70–80% Pb–Pb collisions and pp collisions at √ sNN = 5.02 TeV are compared. For case (b), ratios in 0–10% Pb– √ Pb collisions and pp collisions at sNN = 5.02 TeV are compared √ with 0–5% in Pb–Pb collisions at sNN = 2.76 TeV. The ratios for 70–80% in Pb–Pb collisions are closer to the corresponding results in pp collisions. Noticeably, there are distinct differences between central and peripheral (pp) collisions in the ratios for p T below ∼ 2 GeV/c and intermediate p T (between 2 and 6 GeV/c) but the ratios are consistent at higher p T [42]. At low p T , the K∗0 /K and K∗0 /π for central collisions are lower than in peripheral (pp) collisions, while the corresponding yield ratios for φ meson are comparable within the uncertainties. This observation is consistent with the suppression of K∗0 yields due to rescattering in the hadronic phase. It demonstrates that rescattering affects low momentum particles. At intermediate p T , both ratios show an enhancement for central Pb–Pb collisions relative to peripheral and pp collisions, which is more prominent for φ/K, φ/π and K∗0 /π . This is consistent with the presence of a larger ALICE Collaboration / Physics Letters B 802 (2020) 135225 7 ∗0 Fig. 6. Particle yield ratios (p + p)/(K∗0 + K ) in panel (a) and (p + p̄)/(2φ ) in panel (b), both as a function of p T for 0–10% central Pb–Pb collisions and inelastic pp √ √ collisions at sNN = 5.02 TeV. For comparison, similar ratios are also shown for 0–5% central Pb–Pb collisions at sNN = 2.76 TeV [42]. The statistical uncertainties are ∗0 shown as bars and systematic uncertainties are shown as boxes. In the text (K∗0 + K ) and (p + p) are denoted by K∗0 and p, respectively. radial flow in central collisions relative to peripheral and pp collisions [51]. Given that the masses of K∗0 and φ mesons are larger than those of the charged kaon and pion, the resonances experience a larger radial flow effect. In central Pb–Pb collisions, for p T below 5 GeV/c, the p /φ ratio is observed to be independent of p T and the p /K∗0 ratio exhibits a weak p T -dependence within the uncertainties, in contrast to the decrease of both ratios with p T observed in pp collisions. In turn, this suggests that the shapes of the p T distributions are similar for K∗0 , φ and p in this p T range. Although the quark contents are different, the masses of these hadrons are similar, indicating that this is the relevant quantity in determining spectra shapes. This is consistent with expectations from hydrodynamic-based models [65,66]. Within the uncertain√ ties, the p /K∗0 and p /φ ratios for central Pb–Pb collisions at sNN = 5.02 TeV and 2.76 TeV [42] are constant at intermediate p T . This is consistent with the observation of similar order radial flow at both energies, obtained from the analysis of p T spectra of pions, kaons and protons [51]. For p T > 6 GeV/c, the K∗0 /K, φ/K, K∗0 /π , φ/π , p /K∗0 and p /φ yield ratios in central collisions are similar to peripheral and pp collisions, indicating that fragmentation is the dominant hadron production mechanism in this p T region. This is √ consistent with previous measurements at sNN = 2.76 TeV [42]. 5. Summary The transverse momentum distributions of K∗0 and φ mesons have been measured at midrapidity (| y | < 0.5) for various collision √ centralities in Pb–Pb and inelastic pp collisions at sNN = 5.02 ∗ 0 TeV using the ALICE detector. The K yields relative to charged kaons in Pb–Pb collisions show a suppression with respect to pp collisions, which increases with the system size, quantified using dN ch /dη1/3 measured at midrapidity. In contrast, no such suppression is observed for the φ mesons. The lack of suppression for the φ meson can be attributed to the fact that most of them decay outside the fireball because of its longer lifetime (τφ = 46.3 ± 0.4 fm/c). Because of a shorter lifetime (τK∗0 = 4.16 ± 0.05 fm/c), a significant number of produced K∗0 decays in the hadronic medium. The decay product(s) undergo interactions with other hadrons in the medium resulting in a significant change in their momentum, and no longer contributing to the K∗0 signal reconstructed in the experiment. Although both rescattering and regeneration are possible, the results presented here represent an experimental demonstration of the predominance of rescattering effects in the hadronic phase of the system produced in heavyion collisions. The effect of rescattering increases with the system size. Furthermore, the K∗0 /K yield ratios in central Pb–Pb collisions are significantly lower compared to the values from thermal model calculations without rescattering effects, while the measured φ/K yield ratio agrees with the model calculation. This further corroborates the hypothesis that rescattering affects the measured K∗0 yields in Pb–Pb collisions. A lower limit for the lifetime of the hadronic phase is determined by using the K∗0 /K ratios in Pb–Pb √ and pp collisions at sNN = 5.02 TeV. The lifetime, as expected, increases with system size. For central Pb–Pb collisions, it is about 4–7 fm/c. The p T -differential yield ratios of K∗0 /π and K∗0 /K are studied in central Pb–Pb, peripheral Pb–Pb and pp collisions to understand the p T -dependence of the rescattering effect. It is observed that rescattering dominantly affects the hadrons at p T < 2 GeV/c. At intermediate p T (2–6 GeV/c), the φ/K, φ/π , K∗0 /π , p /K∗0 and p /φ yield ratios are enhanced in central Pb–Pb collisions relative to peripheral Pb–Pb and pp collisions. In addition, the spectral shapes of K∗0 , φ and p, which have comparable masses, are similar within the uncertainties for p T below 5 GeV/c in Pb–Pb collisions. These measurements demonstrate the effect of higher radial flow in central Pb–Pb collisions relative to peripheral Pb–Pb and pp collisions. A comparison of the p /K∗0 and p /φ ratios for central Pb–Pb col√ lisions at sNN = 5.02 and 2.76 TeV shows the constancy of the ratios with p T . This is consistent with the observation of compa√ rable radial flow at sNN = 5.02 TeV and 2.76 TeV. For higher p T , above 6 GeV/c, all the ratios agree within the uncertainties for central and peripheral Pb–Pb, and pp collisions, indicating that particle production via fragmentation at high transverse momenta is not significantly modified in the presence of a medium. 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 centers and the Worldwide LHC Computing Grid (WLCG) collaboration. The ALICE Collaboration acknowledges the 8 ALICE Collaboration / Physics Letters B 802 (2020) 135225 following funding agencies for their support in building and running the ALICE detector: A. I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation (ANSL), State Committee of Science and World Federation of Scientists (WFS), Armenia; Austrian Academy of Sciences, Austrian Science Fund (FWF): [M 2467-N36] and Nationalstiftung für Forschung, Technologie und Entwicklung, Austria; Ministry of Communications and High Technologies, National Nuclear Research Center, Azerbaijan; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Financiadora de Estudos e Projetos (Finep), Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and Universidade Federal do Rio Grande do Sul (UFRGS), Brazil; Ministry of Education of China (MOEC), Ministry of Science & Technology of China (MSTC) and National Natural Science Foundation of China (NSFC), China; Ministry of Science and Education and Croatian Science Foundation, Croatia; Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Cubaenergía, Cuba; Ministry of Education, Youth and Sports of the Czech Republic, Czech Republic; The Danish Council for Independent Research | Natural Sciences, the Villum Fonden and Danish National Research Foundation (DNRF), Denmark; Helsinki Institute of Physics (HIP), Finland; Commissariat à l’Énergie Atomique (CEA), Institut National de Physique Nucléaire et de Physique des Particules (IN2P3) and Centre National de la Recherche Scientifique (CNRS) and Région des Pays de la Loire, France; Bundesministerium für Bildung und Forschung (BMBF) and GSI Helmholtzzentrum für Schwerionenforschung GmbH, Germany; General Secretariat for Research and Technology, Ministry of Education, Research and Religions, Greece; National Research Development and Innovation Office, Hungary; Department of Atomic Energy, Government of India (DAE), Department of Science and Technology, Government of India (DST), University Grants Commission, Government of India (UGC) and Council of Scientific and Industrial Research (CSIR), India; Indonesian Institute of Science, Indonesia; 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), Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) and Japan Society for the Promotion of Science (JSPS) KAKENHI, Japan; Consejo Nacional de Ciencia (CONACYT) y Tecnología, through Fondo de Cooperación Internacional en Ciencia y Tecnología (FONCICYT) and Dirección General de Asuntos del Personal Academico (DGAPA), Mexico; Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), Netherlands; The Research Council of Norway, Norway; Commission on Science and Technology for Sustainable Development in the South (COMSATS), Pakistan; Pontificia Universidad Católica del Perú, Peru; Ministry of 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 Ministry of Research and Innovation and Institute of Atomic Physics, Romania; Joint Institute for Nuclear Research (JINR), Ministry of Education and Science of the Russian Federation, National Research Centre Kurchatov Institute, Russian Science Foundation and Russian Foundation for Basic Research, Russia; Ministry of Education, Science, Research and Sport of the Slovak Republic, Slovakia; National Research Foundation of South Africa, South Africa; Swedish Research Council (VR) and Knut & Alice Wallenberg Foundation (KAW), Sweden; European Organization for Nuclear Research, Switzerland; Suranaree University of Technology (SUT), National Science and Technology Development Agency (NSDTA) and Office of the Higher Education Commission under NRU project of Thailand, Thailand; Turkish 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 (DOE NP), United States of America. 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Petráček 36 , M. Petrovici 47 , R.P. Pezzi 70 , S. Piano 59 , M. Pikna 13 , P. Pillot 114 , O. Pinazza 33,53 , L. Pinsky 125 , C. Pinto 27 , S. Pisano 10,51 , D. Pistone 55 , M. Płoskoń 79 , M. Planinic 98 , F. Pliquett 68 , J. Pluta 142 , S. Pochybova 145,i , M.G. Poghosyan 95 , B. Polichtchouk 90 , N. Poljak 98 , A. Pop 47 , H. Poppenborg 144 , S. Porteboeuf-Houssais 134 , V. Pozdniakov 75 , S.K. Prasad 3 , R. Preghenella 53 , F. Prino 58 , C.A. Pruneau 143 , I. Pshenichnov 62 , M. Puccio 25,33 , J. Putschke 143 , R.E. Quishpe 125 , S. Ragoni 110 , S. Raha 3 , S. Rajput 100 , J. Rak 126 , A. Rakotozafindrabe 137 , L. Ramello 31 , F. Rami 136 , R. Raniwala 101 , S. Raniwala 101 , S.S. Räsänen 43 , R. Rath 49 , V. Ratza 42 , I. Ravasenga 30,89 , K.F. Read 95,130 , K. Redlich 84,v , A. Rehman 21 , P. Reichelt 68 , F. Reidt 33 , X. Ren 6 , R. Renfordt 68 , Z. Rescakova 37 , J.-P. Revol 10 , K. Reygers 103 , V. Riabov 97 , T. Richert 80,88 , M. 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Schmidt 102 , N.V. Schmidt 68,95 , A.R. Schmier 130 , J. Schukraft 88 , Y. Schutz 33,136 , K. Schwarz 106 , K. Schweda 106 , G. Scioli 26 , E. Scomparin 58 , M. Šefčík 37 , J.E. Seger 15 , Y. Sekiguchi 132 , D. Sekihata 132 , I. Selyuzhenkov 92,106 , S. Senyukov 136 , D. Serebryakov 62 , E. Serradilla 71 , A. Sevcenco 67 , A. Shabanov 62 , A. Shabetai 114 , R. Shahoyan 33 , W. Shaikh 109 , A. Shangaraev 90 , A. Sharma 99 , A. Sharma 100 , H. Sharma 118 , M. Sharma 100 , N. Sharma 99 , A.I. Sheikh 141 , K. Shigaki 45 , M. Shimomura 82 , S. Shirinkin 91 , Q. Shou 39 , Y. Sibiriak 87 , S. Siddhanta 54 , T. Siemiarczuk 84 , D. Silvermyr 80 , G. Simatovic 89 , G. Simonetti 33,104 , R. Singh 85 , R. Singh 100 , R. Singh 49 , V.K. Singh 141 , V. Singhal 141 , T. Sinha 109 , B. Sitar 13 , M. Sitta 31 , T.B. Skaali 20 , M. Slupecki 126 , N. Smirnov 146 , R.J.M. Snellings 63 , T.W. Snellman 43,126 , C. Soncco 111 , J. Song 60,125 , A. Songmoolnak 115 , F. Soramel 28 , S. Sorensen 130 , I. Sputowska 118 , J. Stachel 103 , I. Stan 67 , P. Stankus 95 , P.J. Steffanic 130 , E. Stenlund 80 , D. Stocco 114 , M.M. Storetvedt 35 , L.D. Stritto 29 , A.A.P. Suaide 121 , T. Sugitate 45 , C. Suire 61 , M. Suleymanov 14 , M. Suljic 33 , R. Sultanov 91 , M. Šumbera 94 , S. Sumowidagdo 50 , S. Swain 65 , A. Szabo 13 , I. Szarka 13 , U. Tabassam 14 , G. Taillepied 134 , J. Takahashi 122 , G.J. Tambave 21 , S. Tang 6,134 , M. Tarhini 114 , M.G. Tarzila 47 , A. Tauro 33 , G. Tejeda Muñoz 44 , A. Telesca 33 , C. Terrevoli 125 , D. Thakur 49 , S. Thakur 141 , D. Thomas 119 , F. Thoresen 88 , R. Tieulent 135 , A. Tikhonov 62 , A.R. Timmins 125 , A. Toia 68 , N. Topilskaya 62 , M. Toppi 51 , F. Torales-Acosta 19 , S.R. Torres 9,120 , A. Trifiro 55 , S. Tripathy 49 , T. Tripathy 48 , S. Trogolo 28 , G. Trombetta 32 , L. Tropp 37 , V. Trubnikov 2 , W.H. Trzaska 126 , T.P. Trzcinski 142 , B.A. Trzeciak 63 , T. Tsuji 132 , A. Tumkin 108 , R. Turrisi 56 , T.S. Tveter 20 , K. Ullaland 21 , E.N. Umaka 125 , A. Uras 135 , G.L. Usai 23 , A. Utrobicic 98 , M. Vala 37 , N. Valle 139 , S. Vallero 58 , N. van der Kolk 63 , L.V.R. van Doremalen 63 , M. van Leeuwen 63 , P. Vande Vyvre 33 , D. Varga 145 , Z. Varga 145 , M. Varga-Kofarago 145 , A. Vargas 44 , M. Vasileiou 83 , A. Vasiliev 87 , O. Vázquez Doce 104,117 , V. Vechernin 112 , A.M. Veen 63 , E. Vercellin 25 , S. Vergara Limón 44 , L. Vermunt 63 , R. Vernet 7 , R. Vértesi 145 , L. Vickovic 34 , Z. Vilakazi 131 , O. Villalobos Baillie 110 , A. Villatoro Tello 44 , G. Vino 52 , A. Vinogradov 87 , T. Virgili 29 , V. Vislavicius 88 , A. Vodopyanov 75 , B. Volkel 33 , M.A. Völkl 102 , K. Voloshin 91 , S.A. Voloshin 143 , G. Volpe 32 , B. von Haller 33 , I. Vorobyev 104 , D. Voscek 116 , J. Vrláková 37 , B. Wagner 21 , M. Weber 113 , S.G. Weber 144 , A. Wegrzynek 33 , D.F. Weiser 103 , S.C. Wenzel 33 , J.P. Wessels 144 , J. Wiechula 68 , J. Wikne 20 , G. Wilk 84 , J. Wilkinson 10,53 , G.A. Willems 33 , E. Willsher 110 , B. Windelband 103 , M. Winn 137 , W.E. Witt 130 , Y. Wu 128 , R. Xu 6 , S. Yalcin 77 , K. Yamakawa 45 , S. Yang 21 , S. Yano 137 , Z. Yin 6 , H. Yokoyama 63 , I.-K. Yoo 17 , J.H. Yoon 60 , S. Yuan 21 , A. Yuncu 103 , V. Yurchenko 2 , V. Zaccolo 24 , A. Zaman 14 , C. Zampolli 33 , H.J.C. Zanoli 63 , N. Zardoshti 33 , A. Zarochentsev 112 , P. Závada 66 , N. Zaviyalov 108 , H. Zbroszczyk 142 , M. Zhalov 97 , S. Zhang 39 , X. Zhang 6 , Z. Zhang 6 , V. Zherebchevskii 112 , D. Zhou 6 , Y. Zhou 88 , Z. Zhou 21 , J. Zhu 6,106 , Y. Zhu 6 , A. Zichichi 10,26 , M.B. Zimmermann 33 , G. Zinovjev 2 , N. Zurlo 140 1 A.I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation, Yerevan, Armenia Bogolyubov Institute for Theoretical Physics, National Academy of Sciences of Ukraine, Kiev, Ukraine Bose Institute, Department of Physics and Centre for Astroparticle Physics and Space Science (CAPSS), Kolkata, India 4 Budker Institute for Nuclear Physics, Novosibirsk, Russia 5 California Polytechnic State University, San Luis Obispo, CA, United States 6 Central China Normal University, Wuhan, China 7 Centre de Calcul de l’IN2P3, Villeurbanne, Lyon, France 8 Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Havana, Cuba 9 Centro de Investigación y de Estudios Avanzados (CINVESTAV), Mexico City and Mérida, Mexico 10 Centro Fermi – Museo Storico della Fisica e Centro Studi e Ricerche “Enrico Fermi”, Rome, Italy 11 Chicago State University, Chicago, IL, United States 12 China Institute of Atomic Energy, Beijing, China 13 Comenius University Bratislava, Faculty of Mathematics, Physics and Informatics, Bratislava, Slovakia 14 COMSATS University Islamabad, Islamabad, Pakistan 15 Creighton University, Omaha, NE, United States 16 Department of Physics, Aligarh Muslim University, Aligarh, India 2 3 ALICE Collaboration / Physics Letters B 802 (2020) 135225 17 13 Department of Physics, Pusan National University, Pusan, Republic of Korea Department of Physics, Sejong University, Seoul, Republic of Korea 19 Department of Physics, University of California, Berkeley, CA, United States 20 Department of Physics, University of Oslo, Oslo, Norway 21 Department of Physics and Technology, University of Bergen, Bergen, Norway 22 Dipartimento di Fisica dell’Università ‘La Sapienza’ and Sezione INFN, Rome, Italy 23 Dipartimento di Fisica dell’Università and Sezione INFN, Cagliari, Italy 24 Dipartimento di Fisica dell’Università and Sezione INFN, Trieste, Italy 25 Dipartimento di Fisica dell’Università and Sezione INFN, Turin, Italy 26 Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN, Bologna, Italy 27 Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN, Catania, Italy 28 Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN, Padova, Italy 29 Dipartimento di Fisica ‘E.R. Caianiello’ dell’Università and Gruppo Collegato INFN, Salerno, Italy 30 Dipartimento DISAT del Politecnico and Sezione INFN, Turin, Italy 31 Dipartimento di Scienze e Innovazione Tecnologica dell’Università del Piemonte Orientale and INFN Sezione di Torino, Alessandria, Italy 32 Dipartimento Interateneo di Fisica ‘M. Merlin’ and Sezione INFN, Bari, Italy 33 European Organization for Nuclear Research (CERN), Geneva, Switzerland 34 Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Split, Croatia 35 Faculty of Engineering and Science, Western Norway University of Applied Sciences, Bergen, Norway 36 Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Prague, Czech Republic 37 Faculty of Science, P.J. Šafárik University, Košice, Slovakia 38 Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-Universität Frankfurt, Frankfurt, Germany 39 Fudan University, Shanghai, China 40 Gangneung-Wonju National University, Gangneung, Republic of Korea 41 Gauhati University, Department of Physics, Guwahati, India 42 Helmholtz-Institut für Strahlen- und Kernphysik, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany 43 Helsinki Institute of Physics (HIP), Helsinki, Finland 44 High Energy Physics Group, Universidad Autónoma de Puebla, Puebla, Mexico 45 Hiroshima University, Hiroshima, Japan 46 Hochschule Worms, Zentrum für Technologietransfer und Telekommunikation (ZTT), Worms, Germany 47 Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania 48 Indian Institute of Technology Bombay (IIT), Mumbai, India 49 Indian Institute of Technology Indore, Indore, India 50 Indonesian Institute of Sciences, Jakarta, Indonesia 51 INFN, Laboratori Nazionali di Frascati, Frascati, Italy 52 INFN, Sezione di Bari, Bari, Italy 53 INFN, Sezione di Bologna, Bologna, Italy 54 INFN, Sezione di Cagliari, Cagliari, Italy 55 INFN, Sezione di Catania, Catania, Italy 56 INFN, Sezione di Padova, Padova, Italy 57 INFN, Sezione di Roma, Rome, Italy 58 INFN, Sezione di Torino, Turin, Italy 59 INFN, Sezione di Trieste, Trieste, Italy 60 Inha University, Incheon, Republic of Korea 61 Institut 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 62 Institute for Nuclear Research, Academy of Sciences, Moscow, Russia 63 Institute for Subatomic Physics, Utrecht University/Nikhef, Utrecht, Netherlands 64 Institute of Experimental Physics, Slovak Academy of Sciences, Košice, Slovakia 65 Institute of Physics, Homi Bhabha National Institute, Bhubaneswar, India 66 Institute of Physics of the Czech Academy of Sciences, Prague, Czech Republic 67 Institute of Space Science (ISS), Bucharest, Romania 68 Institut für Kernphysik, Johann Wolfgang Goethe-Universität Frankfurt, Frankfurt, Germany 69 Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Mexico City, Mexico 70 Instituto de Física, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil 71 Instituto de Física, Universidad Nacional Autónoma de México, Mexico City, Mexico 72 iThemba LABS, National Research Foundation, Somerset West, South Africa 73 Jeonbuk National University, Jeonju, Republic of Korea 74 Johann-Wolfgang-Goethe Universität Frankfurt Institut für Informatik, Fachbereich Informatik und Mathematik, Frankfurt, Germany 75 Joint Institute for Nuclear Research (JINR), Dubna, Russia 76 Korea Institute of Science and Technology Information, Daejeon, Republic of Korea 77 KTO Karatay University, Konya, Turkey 78 Laboratoire de Physique Subatomique et de Cosmologie, Université Grenoble-Alpes, CNRS-IN2P3, Grenoble, France 79 Lawrence Berkeley National Laboratory, Berkeley, CA, United States 80 Lund University Department of Physics, Division of Particle Physics, Lund, Sweden 81 Nagasaki Institute of Applied Science, Nagasaki, Japan 82 Nara Women’s University (NWU), Nara, Japan 83 National and Kapodistrian University of Athens, School of Science, Department of Physics, Athens, Greece 84 National Centre for Nuclear Research, Warsaw, Poland 85 National Institute of Science Education and Research, Homi Bhabha National Institute, Jatni, India 86 National Nuclear Research Center, Baku, Azerbaijan 87 National Research Centre Kurchatov Institute, Moscow, Russia 88 Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark 89 Nikhef, National institute for subatomic physics, Amsterdam, Netherlands 90 NRC Kurchatov Institute IHEP, Protvino, Russia 91 NRC “Kurchatov Institute” – ITEP, Moscow, Russia 92 NRNU Moscow Engineering Physics Institute, Moscow, Russia 93 Nuclear Physics Group, STFC Daresbury Laboratory, Daresbury, United Kingdom 94 Nuclear Physics Institute of the Czech Academy of Sciences, Řež u Prahy, Czech Republic 18 14 ALICE Collaboration / Physics Letters B 802 (2020) 135225 95 Oak Ridge National Laboratory, Oak Ridge, TN, United States Ohio State University, Columbus, OH, United States 97 Petersburg Nuclear Physics Institute, Gatchina, Russia 98 Physics department, Faculty of science, University of Zagreb, Zagreb, Croatia 99 Physics Department, Panjab University, Chandigarh, India 100 Physics Department, University of Jammu, Jammu, India 101 Physics Department, University of Rajasthan, Jaipur, India 102 Physikalisches Institut, Eberhard-Karls-Universität Tübingen, Tübingen, Germany 103 Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany 104 Physik Department, Technische Universität München, Munich, Germany 105 Politecnico di Bari, Bari, Italy 106 Research Division and ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum für Schwerionenforschung GmbH, Darmstadt, Germany 107 Rudjer Bošković Institute, Zagreb, Croatia 108 Russian Federal Nuclear Center (VNIIEF), Sarov, Russia 109 Saha Institute of Nuclear Physics, Homi Bhabha National Institute, Kolkata, India 110 School of Physics and Astronomy, University of Birmingham, Birmingham, United Kingdom 111 Sección Física, Departamento de Ciencias, Pontificia Universidad Católica del Perú, Lima, Peru 112 St. Petersburg State University, St. Petersburg, Russia 113 Stefan Meyer Institut für Subatomare Physik (SMI), Vienna, Austria 114 SUBATECH, IMT Atlantique, Université de Nantes, CNRS-IN2P3, Nantes, France 115 Suranaree University of Technology, Nakhon Ratchasima, Thailand 116 Technical University of Košice, Košice, Slovakia 117 Technische Universität München, Excellence Cluster ‘Universe’, Munich, Germany 118 The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy of Sciences, Cracow, Poland 119 The University of Texas at Austin, Austin, TX, United States 120 Universidad Autónoma de Sinaloa, Culiacán, Mexico 121 Universidade de São Paulo (USP), São Paulo, Brazil 122 Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil 123 Universidade Federal do ABC, Santo Andre, Brazil 124 University of Cape Town, Cape Town, South Africa 125 University of Houston, Houston, TX, United States 126 University of Jyväskylä, Jyväskylä, Finland 127 University of Liverpool, Liverpool, United Kingdom 128 University of Science and Techonology of China, Hefei, China 129 University of South-Eastern Norway, Tonsberg, Norway 130 University of Tennessee, Knoxville, TN, United States 131 University of the Witwatersrand, Johannesburg, South Africa 132 University of Tokyo, Tokyo, Japan 133 University of Tsukuba, Tsukuba, Japan 134 Université Clermont Auvergne, CNRS/IN2P3, LPC, Clermont-Ferrand, France 135 Université de Lyon, Université Lyon 1, CNRS/IN2P3, IPN-Lyon, Villeurbanne, Lyon, France 136 Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France, Strasbourg, France 137 Université Paris-Saclay Centre d’Etudes de Saclay (CEA), IRFU, Départment de Physique Nucléaire (DPhN), Saclay, France 138 Università degli Studi di Foggia, Foggia, Italy 139 Università degli Studi di Pavia, Pavia, Italy 140 Università di Brescia, Brescia, Italy 141 Variable Energy Cyclotron Centre, Homi Bhabha National Institute, Kolkata, India 142 Warsaw University of Technology, Warsaw, Poland 143 Wayne State University, Detroit, MI, United States 144 Westfälische Wilhelms-Universität Münster, Institut für Kernphysik, Münster, Germany 145 Wigner Research Centre for Physics, Budapest, Hungary 146 Yale University, New Haven, CT, United States 147 Yonsei University, Seoul, Republic of Korea 96 i ii Deceased. Dipartimento DET del Politecnico di Torino, Turin, Italy. iii M.V. Lomonosov Moscow State University, D.V. Skobeltsyn Institute of Nuclear, Physics, Moscow, Russia. iv Department of Applied Physics, Aligarh Muslim University, Aligarh, India. Institute of Theoretical Physics, University of Wroclaw, Poland. v