Measurements of Chemical Potentials 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/ Measurements of Chemical Potentials in Pb-Pb Collisions at √NN=5.02 TeV © 2024 CERN Published version ALICE Collaboration ALICE Collaboration. (2024). Measurements of Chemical Potentials in Pb-Pb Collisions at √NN=5.02 TeV. Physical Review Letters, 133(9), Article 092301. https://doi.org/10.1103/physrevlett.133.092301 2024 Measurements of Chemical Potentials in Pb-Pb Collisions at ffiffiffiffiffiffiffiffi sNN p=5.02 TeV S. Acharya et al.* (ALICE Collaboration) (Received 13 January 2024; revised 26 March 2024; accepted 3 May 2024; published 26 August 2024) This Letter presents the most precise measurement to date of the matter-antimatter imbalance at midrapidity in Pb-Pb collisions at a center-of-mass energy per nucleon pair ffiffiffiffiffiffiffiffi sNN p¼5.02 TeV. Using the Statistical Hadronization framework, it is possible to obtain the value of the electric charge and baryon chemical potentials, μQ¼−0.18 0.90 MeV and μB¼0.71 0.45 MeV, with unprecedented precision. A centrality-differential study of the antiparticle-to-particle yield ratios of charged pions, protons, Ωbaryons, and light (hyper)nuclei is performed. These results indicate that the system created in Pb-Pb collisions at the LHC is on average baryon-free and electrically neutral at midrapidity. DOI: 10.1103/PhysRevLett.133.092301 Introduction.—Nuclear matter at extremely high energy densities can be generated in the laboratory through relativistic heavy-ion collisions [1–3]. At the LHC, the beam remnants from the collision are located at rapidities y≈6and a fraction of the collision energy is deposited at midrapidity [4]. In this region, particles are formed from a nearly baryon number and electric charge free medium. This process can be described in the color glass condensate model via gluon radiation by static quarks, frozen by time dilation [5]. Conversely, string-fragmentation models explain it through the breaking of color flux tubes. Part of the initial baryon number can be transported to midrapidity via either baryon junction formation [6] or diquark breaking [7]. This phenomenon, known as nuclear stopping, influences the net-baryon density of the system formed at midrapidity [8–10]. The baryon number transport is minimal at the LHC, and the nuclear transparency regime [11] is reached. In this regime, conditions akin to those of the early Universe are replicated, where nearly equal abundances of matter and antimatter were present, as described by the standard cosmological model [12]. Experimentally, one can gauge the extent to which heavy-ion collisions approach the early Universe conditions by measuring the antimatter-to-matter yield ratios across various hadron species. A comprehensive framework for interpreting these ratios is provided by the Statistical Hadronization Model (SHM) [13–18]. Among the several models that can be used to describe a heavy-ion collision, the SHM is the most successful in describing the yields of all light-flavor hadronic species, which are determined starting from the partition function of the fireball at the freeze-out of inelastic scatterings. This fireball is an equilibrated gas composed of hadrons and resonances. Because of the substantial particle multiplicity and the finite kinematical acceptance, a grand canonical (GC) ensemble description is employed for heavy-ion collisions. In this approach, the conservation of charges, namely the baryon number (B), the electric charge (Q), and strangeness (S), is regulated by the corresponding chemical potentials μB,μQ, and μS, respectively [19,20]. The baryon chemical potential μBrepresents the net-baryon density of the system, with μB¼0corresponding to an equilibrated gas composed of hadrons and resonances with same amount of baryons and antibaryons. The electric charge potential μQencodes the positive-negative charge imbalance of the gas; it is connected to μBby the atomic-to-mass-number ratio Z=A of the colliding ions [21,22]. The requirement of strangeness neutrality constrains μSthroughout the entire volume of the fireball [21,22]. Chemical potentials determine the abundance of hadrons through the fugacity, λi¼exp½ðBiμBþ QiμQþSiμSÞ=Tch, where Bi,Qi, and Sidenote the quantum numbers of the considered species i, and Tch is the chemical freeze-out temperature, at which hadron yields are determined. Over the last three decades, the asymmetry between antimatter and matter of the fireball has been systematically studied at different experimental facilities [23–38]. The decreasing trend of μB, from about 400 MeV at the SPS to 20 MeV at the top RHIC energy of 200 GeV, and μB¼0.73.8MeV at the LHC is consistent with the decrease of baryon number transport to midrapidity with increasing beam rapidity [36,37,39–79]. The formation of baryon number free matter at midrapidity was first reported in pp collisions by ALICE, which observed that the ¯ p=p *Full author list given at the end of the Letter. Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Open access publication funded by CERN. PHYSICAL REVIEW LETTERS 133, 092301 (2024) 0031-9007=24=133(9)=092301(15) 092301-1 © 2024 CERN, for the ALICE Collaboration yield ratio is compatible with unity [80].Atfixed collision energy, it is also possible to explore nuclear transparency as a function of centrality, i.e., the transverse displacement between the centers of the colliding nuclei, as it affects the dynamics of the colliding nucleons. In particular, a slight increase in μBfrom peripheral to central (head-on) collisions was observed at low energies by STAR at the RHIC beam energy scan [79]. These results were obtained by either comparing the SHM predictions with the measured yields of hadrons and their antimatter counterparts [81] or by directly fitting antiparticle-to-particle yield ratios [76,79]. In this Letter, we report the most precise estimation to date of μBand μQobtained from a set of antiparticle-toparticle yield ratios. Compared to previous estimations, the precision of the current results has improved by about an order of magnitude. This improvement in precision is attributed to the proper treatment of the cancelation of particle-antiparticle correlated uncertainties and the reduced dependence on model parameters, such as the system volume, V, which is eliminated in the antiparticleto-particle yield ratios. The analyzed species are charged pions, protons, Ω−baryons, and light (hyper)nuclei. (Anti)protons are the most abundantly produced (anti) baryons at midrapidity (≈35 and ≈2protons on average in central and peripheral Pb-Pb collisions, respectively [83]). Consequently, the antiproton-to-proton yield ratio can probe the antibaryon-to-baryon imbalance [80,84] with high precision. On the other hand, the sensitivity to baryon asymmetry is enhanced when light (hyper)nuclei are included because of their larger baryon content. In this work, 3He, its isobar 3H, and hypertriton 3 ΛH, which is a bound state of a proton, a neutron, and a Λ, along with their antimatter counterparts, are considered. [(Anti)deuterons, dð¯ dÞare not considered in this Letter since the efficiency correction for ¯ d is based on the ¯ d absorption cross section extracted by the ALICE Collaboration from the measured ¯ d=d yield ratio itself [85] ]. The ratio of oppositely charged pions provides a precise constraint on the imbalance of electric charge, as the yield ratio depends predominantly on μQ. Finally, the dependence of antimatter-to-matter ratios on strangeness is probed with ðantiÞΩ−baryons, which, unlike ðantiÞΛand ðantiÞΞ−, have negligible contamination coming from heavier hadron decays. The ALICE detector and data analysis.—The results reported in this analysis are obtained from a sample of Pb-Pb collisions at ffiffiffiffiffiffiffiffi sNN p¼5.02 TeV collected in 2018 by ALICE at the LHC. The ALICE apparatus and its performance are described in detail in Refs. [86,87]. The minimum-bias collision and centrality triggers are provided by the V0 system [88], which is composed of two arrays of plastic scintillators covering the forward (2.8<η<5.1) and backward (−3.7<η<−1.7) regions of pseudorapidity. The coincidence of signals in both detectors determines the minimum bias trigger. The amplitude of the V0 signal is proportional to the charge deposited in the detectors, which is related to the produced charged-particle multiplicity that, in turn, is controlled by the collision centrality. The V0 amplitude is then used to trigger specific categories of central and semicentral events, and to estimate centrality [89]. Five centrality intervals are considered in this Letter, namely 0%–5%, 5%–10%, 10%–30%, 30%–50%, and 50%–90%, expressed as percentiles of the total hadronic cross section for Pb-Pb collisions. The position of the primary interaction vertex is required to be within a 10 cm wide region centered at the nominal interaction point to profit from the full acceptance of the ALICE central barrel detectors. Events with multiple interaction vertices are rejected to ensure the correct association of reconstructed tracks and primary vertices. The number of events passing these selections is approximately 300 ×106. Charged pions, protons, 3He, and tritons produced at midrapidity, jyj<0.5, are tracked in the ALICE central barrel: hereafter, charge conjugates are implied unless stated otherwise. The tracks are reconstructed within jηj<0.8and in the full azimuth using the Inner Tracking System (ITS) [90] and the Time Projection Chamber (TPC) [91]. These detectors are placed in a solenoid that provides a uniform magnetic field of 0.5 T parallel to the beam axis. The antiparticle-to-particle yield ratios are measured as a function of the transverse momentum pTin the ranges 0.7≤pT<1.6GeV=c for π−=πþ,0.5≤pT<3GeV=c for ¯ p=p, 1.6≤pT< 3GeV=c for 3¯ H=3H, and 2≤pT<8GeV=c for 3He=3He to select the bulk of the production and ensure good identification performance. The analysis procedure for extracting particle yields is similar to the one adopted in previous analyses [83,92,93]. Standard selections on the χ2of the track fit, on the number of reconstructed track points in the ITS and the TPC, and on the distance of closest approach of the extrapolation of the track to the primary interaction vertex ensure a good reconstruction of tracks originating from the collisions. Particle identification is performed on a statistical basis by measuring the specific energy loss (dE=dx) in both the TPC and the ITS, and particle velocity depending on the transverse momentum of the measured particles with the time-of-flight detector. Further details about the particle identification are provided in the Supplemental Material [94]. The residual contamination due to hyperon weak decays and spallation reactions of primary particles in the apparatus is evaluated by fitting the measured distance of closest approach distribution in the plane transverse to the beam axis with templates computed via Monte Carlo (MC) simulations for the various processes involved [83,92,93]. The extracted yields are corrected for the detector acceptance and candidate selection efficiency, computed using MC simulations, as the fraction of particles reconstructed out of all MC-generated primary particles. PHYSICAL REVIEW LETTERS 133, 092301 (2024) 092301-2 The Pb-Pb event is generated with HIJING [96], while the particles are transported through a realistic model of the ALICE apparatus with GEANT 4[97]. To increase the simulated sample size protons, 3He nuclei, and tritons are injected on top of each HIJING event. The available measurements of hadron inelastic cross sections are used to correct the GEANT 4parametrizations of the corresponding reactions [98–112]. The 3 ΛH candidates are reconstructed from their two-body charged mesonic decay 3 ΛH→3He þπ−. The reconstruction algorithm is the same as the one applied in previous measurements [113–116]. The Ω−is reconstructed with a similar procedure from the decay into a charged kaon and a Λbaryon, that, in turn, is reconstructed from its charged two-body decay, Ω−→K−þΛð→π−þpÞ [117–119]. The ratios are extracted in intervals of proper decay length ct ¼cML=p, with M,L, and pbeing the mass, trajectory length, and candidate momentum, respectively. In particular, 2≤ct < 35 cm for 3 ΛH and 1≤ct < 10 cm for Ω−are used. The 3 ΛH and Ω−candidates are selected with boosted decision tree algorithms [120], which are applied on top of preliminary kinematic and topological selections to enhance the background rejection. The boosted decision tree internal parameters and selections are optimized using samples of correctly classified signal and background candidates, as explained in detail in the Supplemental Material [94]. The invariant mass distribution of the selected candidates is fitted with a probability density function built with a kernel density estimation [121,122] in the MC for 3 ΛH, whereas an extended crystal-ball function is used for the Ω− signal [123]. An exponential function is used to model the residual background in both cases. The yields extracted as the integral of the signal functions obtained from the fits are corrected by the overall selection efficiency and acceptance computed in the MC simulations. As in previous 3 ΛH analyses [116], an absorption correction factor is included to account for undetected candidates absorbed in the detector material before their decay. The following systematic uncertainty contributions are estimated for the antiparticle-to-particle yield ratios: candidate selection and signal extraction, MC data sample size, material budget uncertainty, absorption cross section uncertainties, and magnetic field polarity. The details about the estimation and values of such contributions are reported in the Supplemental Material [94]. Results.—The fully corrected antiparticle-to-particle yield ratios do not exhibit any significant dependence on pTand ct (see the Supplemental Material [94]). This observation, which is consistent across particle species and centrality intervals, implies that the production spectra of charge-conjugate species only differ by normalization factors proportional to their yields. The antiparticle-toparticle yield ratios of each species are obtained as the averages weighted with the total uncorrelated uncertainties of the pTand ct-differential ratios in each centrality interval. For 3 ΛH, no statistically significant signal is observed in the 50%–90% centrality range. The chemical potentials μBand μQare extracted by fitting the antiparticle-to-particle yield ratios with the predictions of the GC statistical hadronization model using the T hermalFIST code [22]. The measured ratios and the SHM fit results are reported in Fig. 1. The chemical freezeout temperature is set to Tch ¼155 2MeV, as obtained from a fit to the ALICE data [124,125]: its value is compatible with the pseudocritical temperature extracted with lattice QCD calculations [126]. This value is fixed for all centralities, since in heavy-ion collisions only a mild dependence of Tch on centrality is observed (less than 3% [35,79,124,127]); additionally, antiparticle-to-particle yield ratios show a negligible dependence on Tch for μB≈ 1MeV [81]. The uncertainty on Tch, which is compatible with the range of variations of Tch observed as a function of centrality, is considered as a centrality-correlated source of systematic uncertainty. The strangeness chemical potential μSis constrained in the fit from strangeness conservation. The contribution of strongly decaying resonances is accounted in the model predictions as it cannot be directly disentangled in the data. For the χ2 minimization, the quadratic sum of statistical and uncorrelated systematic uncertainty is considered. The effect of the centrality-correlated sources is evaluated by repeating the fit to ratios coherently increased or decreased by their uncertainties. The uncertainty assigned to μBand μQis half of the difference between the results obtained in the two cases. In this Letter, yield ratios are analyzed within the GC statistical model also in the most peripheral events, where canonical ensemble formulation is needed for an accurate description of hadron yields by requiring exact conservation of charges over a finite volume [128,129]. It is known, however, that effects connected to the canonical conservation of charges cancel out when considering antiparticle-toparticle yield ratios, and their values are well described by the GC ensemble [15,130]. Indeed, good fit quality is obtained across the 0%–90% centrality range using the GC model to quantify these ratios. In addition, the yield ratio ¯ Ωþ=Ω−is compatible with unity as expected in the SHM, where it is weakly dependent of μBand μSfor μB∼0[16]. The chemical potentials obtained in different centrality intervals are shown in the left panel of Fig. 2. The contours show a negative correlation between μBand μQ, which is connected to the approximate exponential dependence of antiparticle-to-particle yield ratios on the linear combination of the chemical potentials. The centrality dependence of μBand μQis studied by fitting independently the centrality-differential μBand μQresults with a constant function, taking into account the full correlation matrix of the measurements. Both the correlation matrices and the χ2profiles of the fits are reported in the Supplemental PHYSICAL REVIEW LETTERS 133, 092301 (2024) 092301-3 Material [94]. The fit probability is P¼0.97 for μBand P¼0.64 for μQ: therefore, no evidence of centrality dependence is found, even if a larger μBwould be expected in more central collisions due to a potentially larger baryon stopping [4]. The fit of the centralitydifferential values yields chemical potentials μB¼0.71  0.45 MeV and μQ¼−0.18 0.90 MeV, which are compatible with zero within 1.6σand 0.2σ,respectively. The comparison with the previous data point of μBat the LHC [35–38] shows a significant improvement in the precision by a factor larger than 8 (no direct value of μQ was provided in that study, see below). These results imply that the system created at midrapidity in Pb-Pb collisions is baryon and electrically neutral on average. FIG. 1. Upper panels: SHM fits to the measured antiparticle-to-particle yield ratios in different centrality intervals. Error bars show the sum in quadrature of statistical and centrality-uncorrelated systematic uncertainties. When not visible, error bars are hidden by the marker. Lower panels: pull distribution, defined as the difference between data and fit values, normalized to the uncertainty in the data. 1.51.00.50.0 0.5 1.0 1.5 (MeV) B 1.5 1.0 0.5 0.0 0.5 1.0 1.5 (MeV) Q ALICE Pb Pb = 5.02 TeV NN s Thermal-FIST 2 MeV = 155 ch T constrained S 0%-5% 5%-10% 10%-30% 30%-50% 50%-90% Uncorr. uncert. Corr. uncert. FIG. 2. Left panel: μBand μQobtained with T hermalFIST [22] in different centrality intervals. The centrality-correlated and centralityuncorrelated uncertainties are represented with error bars and ellipses, respectively. Right panel: μBextracted from data collected in Au-Au and Pb-Pb collisions at the AGS (E802, E866, E877, E895, E896, E917 Collaborations), SPS (NA44, NA49, NA47 Collaborations), RHIC (BRAHMS, PHENIX, STAR Collaboration), and LHC (ALICE Collaboration) as a function of the center-ofmass energy per nucleon-nucleon pair [76,78,79], and phenomenological parametrization of μBðffiffiffiffiffiffiffiffi sNN pÞ[36]. The inset shows more in detail the results obtained at the LHC [36]. PHYSICAL REVIEW LETTERS 133, 092301 (2024) 092301-4 As a consequence, this observation shows that the nuclear transparency regime is reached, i.e., baryon transport from the colliding ions to the interaction region is negligible. Because of the absence of any centrality dependence, it is also concluded that nuclear transparency is achieved even in central Pb-Pb collisions, where a larger-than-zero μB could be expected from a more significant baryon number transport at midrapidity. As a cross check, the SHM fits described above are repeated by also constraining μQfrom initial conditions via conservation laws, as it was done also in past measurements [36,76,79]. Specifically, the μQ=μBratio is fixed by requiring that the average charge-to-baryon density ratio of the created hadron system, hnQi=hnBi, is equivalent to the Z=A ratio of colliding nuclei, i.e., hnQi=hnBi¼Z=A ≈ 0.4for 208Pb [21]. The μBvalues extracted from the fits in each centrality interval are successfully fitted with a constant function (fit probability P¼0.09). The resulting μBvalue is compatible with the one reported above within uncertainties. Similar results are obtained by fitting the antiparticle-to-particle yield ratios using the GSIHeidelberg model [15,37,76], with Tch ¼156.6 1.7MeV [38] and μQis fixed to initial conditions: the average value across centrality is μB¼0.90 0.43 MeV. The χ2profile of the fit is reported in the Supplemental Material [94]. Using the values of μBand μQextracted in the 5% most central collisions, the inclusive net-proton density at midrapidity, 2=hNpartidNp−¯ p=dy, can be computed in the SHM framework. The value extracted with T hermalFIST is ð3.41.4Þ×10−3, while using the GSIHeidelberg model, a value of 5.9þ2.2 −2.8×10−3is obtained. In both cases, the obtained results agree with the exponential trend as a function of beam rapidity predicted by the baryon-junction mechanism [131]. The right panel of Fig. 2shows the comparison of the current with past estimations of μBas a function of the center-of-mass energy of the collision [36,76,78,79]. The comparison with the previous LHC data point is highlighted in the inset of the figure. The result reported in this Letter is compatible with the extrapolation of the phenomenological parametrization based on previous data and reported in Ref. [36]. Conclusions.—In summary, the most precise measurement of the asymmetry between matter and antimatter at the LHC is reported in this Letter. The asymmetry is quantified through antiparticle-to-particle yield ratios of different hadrons, which are analyzed within the Statistical Hadronization framework to extract the chemical potentials μBand μQ. The GC version of the model accurately describes the antiparticle-to-particle yield ratios across centrality, indicating the elimination of effects from canonical charge conservation in peripheral events. The cancelation of correlated uncertainties in these ratios leads to a significant improvement in the μBprecision: the uncertainty on the obtained value is about 1 order of magnitude smaller than the previously published one [36]. In addition, a direct estimation of μQis provided. Furthermore, the first centrality-differential study of chemical potentials at the LHC is reported in this Letter. The obtained chemical potentials are consistent with zero, i.e., with the nuclear transparency regime being reached across the full centrality range, thus indicating that baryon transport to midrapidity is negligible even in the most central events at the LHC. 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 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 `a Pesquisa do Estado de São Paulo (FAPESP), and Universidade Federal do Rio Grande do Sul (UFRGS), Brazil; Bulgarian Ministry of Education and Science, within the National Roadmap for Research Infrastructures 2020-2027 (object CERN), Bulgaria; Ministry of Education of China (MOEC), Ministry of Science & Technology of China (MSTC), and National Natural Science Foundation of China (NSFC), China; Ministry of Science and Education and Croatian Science Foundation, Croatia; Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Cubaenergía, Cuba; Ministry of Education, Youth and Sports of the Czech Republic, Czech Republic; The Danish Council for Independent Research | Natural Sciences, the VILLUM FONDEN and Danish National Research Foundation (DNRF), Denmark; Helsinki Institute of Physics (HIP), Finland; Commissariat `al’Energie Atomique (CEA) and Institut National de Physique Nucl´eaire et de Physique des Particules (IN2P3), and Centre National de la Recherche Scientifique (CNRS), France; Bundesministerium für Bildung und Forschung (BMBF) and GSI Helmholtzzentrum für Schwerionenforschung GmbH, Germany; General Secretariat for Research and Technology, Ministry of Education, Research and Religions, Greece; National Research, Development and Innovation Office, Hungary; Department of Atomic Energy PHYSICAL REVIEW LETTERS 133, 092301 (2024) 092301-5 Government of India (DAE), Department of Science and Technology, Government of India (DST), University Grants Commission, Government of India (UGC), and Council of Scientific and Industrial Research (CSIR), India; National Research and Innovation Agency—BRIN, Indonesia; Istituto Nazionale di Fisica Nucleare (INFN), Italy; Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) and Japan Society for the Promotion of Science (JSPS) KAKENHI, Japan; Consejo Nacional de Ciencia (CONACYT) y Tecnología, through Fondo de Cooperación Internacional en Ciencia y Tecnología (FONCICYT), and Dirección General de Asuntos del Personal Academico (DGAPA), Mexico; Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), Netherlands; The Research Council of Norway, Norway; Commission on Science and Technology for Sustainable Development in the South (COMSATS), Pakistan; Pontificia Universidad Católica del Perú, Peru; Ministry of Education and Science, National Science Centre and WUT ID-UB, Poland; Korea Institute of Science and Technology Information and National Research Foundation of Korea (NRF), Republic of Korea; Ministry of Education and Scientific Research, Institute of Atomic Physics, Ministry of Research and Innovation and Institute of Atomic Physics and Universitatea Nationala de Stiinta si Tehnologie Politehnica Bucuresti, Romania; Ministry of Education, Science, Research and Sport of the Slovak Republic, Slovakia; National Research Foundation of South Africa, South Africa; Swedish Research Council (VR) and Knut & Alice Wallenberg Foundation (KAW), Sweden; European Organization for Nuclear Research, Switzerland; Suranaree University of Technology (SUT), National Science and Technology Development Agency (NSTDA), and National Science, Research and Innovation Fund (NSRF via PMU-B B05F650021), Thailand; Turkish Energy, Nuclear and Mineral Research Agency (TENMAK), Turkey; National Academy of Sciences of Ukraine, Ukraine; Science and Technology Facilities Council (STFC), United Kingdom; National Science Foundation of the United States of America (NSF) and United States Department of Energy, Office of Nuclear Physics (DOE NP), USA. 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PHYSICAL REVIEW LETTERS 133, 092301 (2024) 092301-8 98Research Division and ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum für Schwerionenforschung GmbH, Darmstadt, Germany 99Saga University, Saga, Japan 100Saha Institute of Nuclear Physics, Homi Bhabha National Institute, Kolkata, India 101School of Physics and Astronomy, University of Birmingham, Birmingham, United Kingdom 102Sección Física, Departamento de Ciencias, Pontificia Universidad Católica del Perú, Lima, Peru 103Stefan Meyer Institut für Subatomare Physik (SMI), Vienna, Austria 104SUBATECH, IMT Atlantique, Nantes Universit´e, CNRS-IN2P3, Nantes, France 105Sungkyunkwan University, Suwon City, Republic of Korea 106Suranaree University of Technology, Nakhon Ratchasima, Thailand 107Technical University of Košice, Košice, Slovak Republic 108The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy of Sciences, Cracow, Poland 109The University of Texas at Austin, Austin, Texas, USA 110Universidad Autónoma de Sinaloa, Culiacán, Mexico 111Universidade de São Paulo (USP), São Paulo, Brazil 112Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil 113Universidade Federal do ABC, Santo Andre, Brazil 114Universitatea Nationala de Stiinta si Tehnologie Politehnica Bucuresti, Bucharest, Romania 115University of Cape Town, Cape Town, South Africa 116University of Derby, Derby, United Kingdom 117University of Houston, Houston, Texas, USA 118University of Jyväskylä, Jyvaskyla, Finland 119University of Kansas, Lawrence, Kansas, USA 120University of Liverpool, Liverpool, United Kingdom 121University of Science and Technology of China, Hefei, China 122University of South-Eastern Norway, Kongsberg, Norway 123University of Tennessee, Knoxville, Tennessee, USA 124University of the Witwatersrand, Johannesburg, South Africa 125University of Tokyo, Tokyo, Japan 126University of Tsukuba, Tsukuba, Japan 127Universität Münster, Institut für Kernphysik, Munster, Germany 128Universit´e Clermont Auvergne, CNRS/IN2P3, LPC, Clermont-Ferrand, France 129Universit´e de Lyon, CNRS/IN2P3, Institut de Physique des 2 Infinis de Lyon, Lyon, France 130Universit´e de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France, Strasbourg, France 131Universit´e Paris-Saclay, Centre d’Etudes de Saclay (CEA), IRFU, D´epartment de Physique Nucl´eaire (DPhN), Saclay, France 132Universit´e Paris-Saclay, CNRS/IN2P3, IJCLab, Orsay, France 133Universit`a degli Studi di Foggia, Foggia, Italy 134Universit`a del Piemonte Orientale, Vercelli, Italy 135Universit`a di Brescia, Brescia, Italy 136Variable Energy Cyclotron Centre, Homi Bhabha National Institute, Kolkata, India 137Warsaw University of Technology, Warsaw, Poland 138Wayne State University, Detroit, Michigan, USA 139Yale University, New Haven, Connecticut, USA 140Yonsei University, Seoul, Republic of Korea 141Zentrum für Technologie und Transfer (ZTT), Worms, Germany 142Affiliated with an institute covered by a cooperation agreement with CERN 143Affiliated with an international laboratory covered by a cooperation agreement with CERN aDeceased. bAlso at Max-Planck-Institut fur Physik, Munich, Germany. cAlso at Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Bologna, Italy. dAlso at Dipartimento DET del Politecnico di Torino, Turin, Italy. eAlso at Yildiz Technical University, Istanbul, Türkiye. fAlso at An institution covered by a cooperation agreement with CERN. gAlso at Department of Applied Physics, Aligarh Muslim University, Aligarh, India. hAlso at Institute of Theoretical Physics, University of Wroclaw, Poland. PHYSICAL REVIEW LETTERS 133, 092301 (2024) 092301-15