Z-boson production in p-Pb collisions at √sNN = 8.16 TeV and 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/ Z-boson production in p-Pb collisions at √sNN = 8.16 TeV and Pb-Pb collisions at √sNN = 5.02 TeV © CERN, for the benefit of the ALICE Collaboration. Article funded by SCOAP3 Published version ALICE collaboration ALICE collaboration. (2020). Z-boson production in p-Pb collisions at √sNN = 8.16 TeV and Pb-Pb collisions at √sNN = 5.02 TeV. Journal of High Energy Physics, 2020(9), Article 76. https://doi.org/10.1007/jhep09(2020)076 2020 JHEP09(2020)076 Published for SISSA by Springer Received:June 9, 2020 Accepted:August 6, 2020 Published:September 10, 2020 Z-boson production in p-Pb collisions at √sNN = 8.16 TeV and Pb-Pb collisions at √sNN = 5.02 TeV The ALICE collaboration E-mail: [email protected] Abstract: Measurement of Z-boson production in p-Pb collisions at √sNN = 8.16 TeV and Pb-Pb collisions at √sNN = 5.02 TeV is reported. It is performed in the dimuon decay channel, through the detection of muons with pseudorapidity −4< ηµ<−2.5 and transverse momentum pµ T>20 GeV/cin the laboratory frame. The invariant yield and nuclear modification factor are measured for opposite-sign dimuons with invariant mass 60 < mµµ <120 GeV/c2and rapidity 2.5< yµµ cms <4. They are presented as a function of rapidity and, for the Pb-Pb collisions, of centrality as well. The results are compared with theoretical calculations, both with and without nuclear modifications to the Parton Distribution Functions (PDFs). In p-Pb collisions the center-of-mass frame is boosted with respect to the laboratory frame, and the measurements cover the backward (−4.46 < yµµ cms <−2.96) and forward (2.03 < yµµ cms <3.53) rapidity regions. For the pPb collisions, the results are consistent within experimental and theoretical uncertainties with calculations that include both free-nucleon and nuclear-modified PDFs. For the Pb-Pb collisions, a 3.4σdeviation is seen in the integrated yield between the data and calculations based on the free-nucleon PDFs, while good agreement is found once nuclear modifications are considered. Keywords: Lepton-Nucleon Scattering (experiments), Heavy-ion collision, Electroweak interaction, Particle and resonance production ArXiv ePrint: 2005.11126 Open Access, Copyright CERN, for the benefit of the ALICE Collaboration. Article funded by SCOAP3. https://doi.org/10.1007/JHEP09(2020)076 JHEP09(2020)076 Contents 1 Introduction 1 2 ALICE detector and data samples 3 3 Analysis procedure 4 4 Results 9 5 Conclusions 13 The ALICE collaboration 19 1 Introduction Measurements of W and Z electroweak vector boson production are useful probes for studying the initial conditions of heavy-ion collisions. Their production occurs predominantly via the Drell-Yan process, in which a quark-antiquark pair annihilates into a lepton pair [1,2]. At leading order, this is an electroweak process although at higher orders gluon radiation must be accounted for. Due to the large masses of these resonances, vector boson production occurs in the early stages of the collisions and their cross section in elementary parton-parton interactions can be calculated within perturbative Quantum Chromodynamics (pQCD). The large masses also allow for high-precision theoretical calculations, currently reaching up to Next-to-Next-to-Leading Order (NNLO) accuracy [3,4]. Since neither the vector bosons nor their leptonic decay products carry color charge, they do not interact strongly with the dense QCD medium formed in heavy-ion collisions. There are hints that the muons undergo electromagnetic interactions with the dense QCD medium, seen by pTbroadening of dimuon spectra [5]. However, this broadening can also be described by photo-production [6]. Regardless of the physical origin, the scale of these pT-modifications is negligible compared to the average momentum of the muons, which is about half of the Z-boson mass. Thus, the information carried by the muons is not diluted due to final state interactions, allowing to probe the initial state directly. At the Large Hadron Collider (LHC), the center-of-mass energies and luminosities are large enough to allow the production of these bosons to be measured in heavy-ion collisions. Since the production of electroweak bosons occurs predominantly through quarkantiquark annihilation, it is dependent on the longitudinal momentum distributions of the quarks in the initial state of the collision. These distributions are parametrized by the Parton Distribution Functions (PDFs) fi(x, Q2) [7]. Here, figives the probability of finding a parton of type i (this could be either a gluon or a quark with a given flavor) with momentum fraction xof the parent nucleon (also known as Bjorken-x) and squared – 1 – JHEP09(2020)076 4-momentum transfer vector Q2. In general, PDFs are obtained through global fits to data, combining information from multiple experiments. Most of these data come from Deep Inelastic Scattering (DIS) experiments, although data from the Tevatron and the LHC have recently been included as well [8–11]. It has been observed that in a nucleus with mass number A, the distributions of partons fA i(x, Q2) differ from the free-nucleon PDFs scaled by the number of protons and neutrons Afnucleon i(x, Q2) [12]. The modified distributions can be described by means of so-called nuclear Parton Distribution Functions (nPDFs). The Bjorken-xdomain can be divided into four main regions, displaying various nuclear effects [13,14]. It should be noted that the precise values of the boundaries of the x-regions depend on the parton flavor, nPDF parametrization and Q2. The following values assume Q2=M2 Z[13]. At low x, up to x∼0.05, a depletion of partons is present in nPDFs compared to free-nucleon PDFs. This depletion is referred to as shadowing. Then, in x∼0.05 −0.3 an enhancement is seen, called antishadowing. Following this, another depletion region, the so-called EMC region, is present from x∼0.3 to x∼0.9. Lastly, x> ∼0.9 to unity is the so-called Fermi region, where again an enhancement is present. These nuclear modifications to the PDFs influence the production of electroweak bosons [15], but suffer from large uncertainties. Since the parametrizations are obtained through global fits to data, experimental uncertainties enter the nPDFs as well. Accurate measurements of W and Z bosons at the LHC can therefore help to constrain the nPDFs [13,16,17], which are fundamental ingredients to properly describe the initial state of heavy-ion collisions. An in-depth overview of nPDFs can be found in ref. [18]. The production of electroweak bosons at the LHC has already been studied in several collision systems, at various energies and rapidities [19–32]. At midrapidity, the data in different collision systems are generally well described by theoretical calculations both with and without nuclear modification of the PDFs [21–31]. In fact, the covered Bjorken-xrange at midrapidity extends over the antishadowing and shadowing region (depending on the transition value, even into the EMC region). As a result, their competing effects reduce the final effect of nuclear modifications. However, at larger rapidities and therefore lower x, there are increasingly stronger deviations between calculations with models that either do or do not include nuclear modification of the PDFs [20,31]. The data taken at the LHC are in a kinematic regime in (x, Q2) which is also sensitive to contributions coming from quark flavors such as charm and strange, present as sea quarks in the nucleons [33]. The uncertainties in both the nPDFs and the free-nucleon PDFs (where nuclear fixed-target data were also used for the fits) for these flavors are large and a combination of heavy-ion and proton data can help in reducing them [33]. This paper presents the measurement of the Z-boson production at forward rapidity through the dimuon decay channel in p-Pb collisions at √sNN = 8.16 TeV as well as in Pb-Pb collisions at √sNN = 5.02 TeV. The p-Pb measurement is the first at this energy, following an earlier ALICE publication with data taken at √sNN = 5.02 TeV [19]. The Z-boson production in Pb-Pb collisions at √sNN = 5.02 TeV has already been published by the ALICE Collaboration using data collected in 2015 [20]. In 2018, new Pb-Pb data were collected at the same collision energy, corresponding to an integrated luminosity – 2 – JHEP09(2020)076 twice that of 2015. The dataset used in this paper includes both the 2015 and 2018 samples and therefore supersedes the previous Pb-Pb results. The larger dataset allows for a more differential analysis as well as increased precision on the integrated cross section measurement. The paper is organized as follows: the ALICE detector and data samples are detailed in section 2, followed by the analysis procedure in section 3. The main results are then given in section 4and the conclusions are drawn in section 5. 2 ALICE detector and data samples Z bosons are reconstructed via their dimuon decay channel using data from the ALICE muon spectrometer, which selects, identifies and reconstructs muons in the pseudorapidity range −4< ηµ<−2.5 [34]. The tracking system consists of five stations, each containing two multi-wire proportional cathode pad chambers. The third station is located inside a dipole magnet that provides an integrated magnetic field of 3 T ×m. A conical absorber of 10 interaction lengths (λi) made of carbon, concrete and steel, is located in front of the tracking system to filter out the hadrons and low-momentum muons from the decay of light particles (such as pions or kaons). The muon trigger system consists of four resistive plate chamber planes arranged in two stations placed downstream of an iron wall of ∼7.2 λithat reduces the contamination of residual hadrons leaking from the front absorber. Finally, a small-angle beam shield made of dense materials protects the whole spectrometer from secondary particles coming from beam-gas interactions and from interactions of large rapidity particles with the beam pipe. Primary vertex reconstruction is performed by the Silicon Pixel Detector (SPD), the two innermost cylindrical layer of the Inner Tracking System (ITS) [35]. The first and second layer cover the pseudorapidity regions |η|<2.0 and |η|<1.4, respectively. Two arrays of scintillator counters (V0A and V0C [36]) are used to trigger events and to reject events from beam-gas interactions. The V0A and V0C detectors are located on both sides of the interaction point at z= 3.4 m and z=−0.9 m and cover the pseudorapidity regions 2.8< η < 5.1 and −3.7< η < −1.7, respectively. The V0 detectors are also used to estimate the centrality in Pb-Pb collisions by using a Glauber model fit to the sum of their signal amplitudes [37]. The events are then distributed in classes corresponding to a percentile of the total inelastic hadronic cross section. Finally, the Zero Degree Calorimeters (ZDC) [38], placed on both sides of the interaction point at z=±112.5 m, are used to reject electromagnetic background. A complete description of the ALICE detector and its performance can be found in refs. [39,40]. The analysis in p-Pb collisions is performed on data collected in 2016 at a centerof-mass energy √sNN = 8.16 TeV. The data were taken in two beam configurations, with either the proton (p-going) or lead ion (Pb-going) moving towards the muon spectrometer. By convention, the proton moves toward positive rapidities. Because of the asymmetry in the proton and lead beam energies (Ep= 6.5 TeV and EPb = 2.56 TeV per nucleon), the resulting nucleon-nucleon center-of-mass system is boosted with respect to the laboratory frame by ∆ycms =±0.465. Therefore, the rapidity acceptance of the muon spectrometer – 3 – JHEP09(2020)076 in the center-of-mass system is 2.03 < yµµ cms <3.53 for the p-going configuration and −4.46 < yµµ cms <−2.96 for the Pb-going configuration. The data used in the Pb-Pb analysis were taken in 2015 and 2018 at √sNN = 5.02 TeV and cover the rapidity1interval 2.5< yµµ cms <4. The events selected for the analyses require two opposite-sign muon candidates in the muon trigger system, each with a transverse momentum above a configurable threshold, in coincidence with a minimum bias (MB) trigger. The latter was defined by the coincidence of signals in the two arrays of the V0 detector. In the Pb-Pb analysis, only the events corresponding to the most central 90% of the total inelastic cross section (0–90%) are used. For these events the MB trigger is fully efficient and the contamination by electromagnetic interactions is negligible. For p-Pb collisions, the Z-boson cross section is calculated using a luminosity normalization factor obtained via a reference process corresponding to the MB trigger condition itself. Therefore the MB trigger efficiency does not affect the cross section evaluation. Finally, the muon trigger threshold was pµ T&0.5 GeV/cfor p-Pb and pµ T&1 GeV/cfor Pb-Pb collisions. After the event selection, the integrated luminosity in Pb-Pb collisions is about 750 µb−1. In the p-Pb analysis, where a precise value of the luminosity is needed to compute the Z-boson cross section, dedicated Van der Meer scans were performed [41]. The values of the luminosity amount to 8.40 ±0.16 nb−1and 12.74 ±0.24 nb−1for the p-going and Pb-going configuration, respectively. 3 Analysis procedure The Z-boson signal extraction is performed by combining muons of high transverse momentum in pairs with opposite charge. Muon track candidates are reconstructed in the tracking system of the spectrometer using the algorithm described in ref. [42]. In order to ensure a clean data sample, a selection is performed on the single muon tracks reconstructed in the muon spectrometer, requiring them to have a pseudorapidity −4< ηµ<−2.5 and a polar angle measured at the end of the front absorber of 170o< θabs <178o. This procedure removes tracks at the edge of the spectrometer acceptance, and rejects tracks crossing the high-density section of the absorber, which experience significant multiple scattering. The background from tracks not pointing to the nominal interaction vertex, mostly coming from beam-gas interactions and muons produced in the front absorber, is removed by applying a selection on the product of the track momentum and its distance of closest approach to the primary vertex (i.e. the distance to the primary vertex of the track trajectory projected in the plane transverse to the beam axis). Finally, a track is identified as a muon if the track reconstructed in the tracking system matches a track segment in the triggering stations. Only muons with pµ T>20 GeV/care used, to reduce the contribution from low-mass resonances and semileptonic decays of charm and beauty hadrons. The µ+µ−pairs are counted in the invariant mass range 60 < mµµ <120 GeV/c2, where the Z-boson contribution is dominant with respect to the Drell-Yan process. The invariant mass distributions of the Z-boson candidates are shown in figure 1for minimum bias p-Pb collisions in the 1In the ALICE reference frame the muon spectrometer covers negative η. However, due to the symmetric nature of the Pb-Pb collisions, we use positive values for the probed rapidity interval. – 4 – JHEP09(2020)076 p-going and Pb-going configurations, and Pb-Pb collisions in the centrality range 0–90%. Several background sources can contribute to the invariant mass distributions of oppositecharge dimuons. The combinatorial background from random pairing of muons in an event is evaluated by looking at the like-sign pairs (µ±µ±), applying the same selection criteria as for the signal extraction. In the Pb-Pb sample, one pair is found in the invariant mass range considered, which is subtracted from the signal distribution. In p-Pb collisions, no such pairs are found in the region of interest. An upper limit for this background contribution is evaluated by releasing the pµ Tselection, fitting the resulting invariant mass distribution between 2 and 50 GeV/c2and extrapolating the fit to the 60–120 GeV/c2range. Various functions of exponential and power law forms were tried. With this procedure, the number of same-charge events in the region of interest is much smaller than 1% of the opposite-charge one, and is therefore neglected. Contributions from cc, bb, tt and the muon decay of τpairs in the process Z →τ+τ−→ µ+µ−+Xwere estimated with Monte Carlo (MC) simulations using the POWHEG event generator [43]. In p-Pb collisions, the sum of these contributions amounts to 1% of the signal in the p-going configuration, which is taken as a systematic uncertainty from this background source. This contribution is negligible for the Pb-going configuration. In Pb-Pb collisions, a value of 1% is estimated as described in the previous publication [20]. The low amount of background allows the signal to be extracted by counting the candidates in the interval 60 < mµµ <120 GeV/c2in the distributions shown in figure 1. In the p-Pb data sample, 64 ±8 (34 ±6) good µ+µ−pairs are counted in the forward (backward) rapidity region. In Pb-Pb collisions, 208 ±14 Z bosons are counted after merging the 2015 and 2018 data samples. All quoted uncertainties are statistical. The dimuon invariant mass distributions are compared with the mass shapes obtained by detector-level simulations of the Z →µ+µ−process, generated using the POWHEG generator [43] paired with PYTHIA 6.425 [44] for the parton shower. The CT10 [45] freenucleon PDFs are used, with EPS09NLO [46] for nuclear modifications. The propagation of the particles through the detector is simulated with the GEANT3 transport code [47]. To account for the modification of the production due to the light-quark flavor content of the nucleus (isospin effect), the simulated distributions are obtained with a weighted average of all possible binary collisions: proton-proton, proton-neutron and for Pb-Pb collisions also neutron-neutron. At high pµ T, tracks are nearly straight so a small misalignment of the detector elements will generate large changes in the track parameters. Therefore, a detailed study of the alignment of the tracking chambers is of utmost importance in order to correctly reproduce the track reconstruction in the simulations. The absolute position of the detector elements was measured by photogrammetry before data taking. The relative position of the elements is then estimated using the MILLEPEDE [48] package, combining data taken with and without magnetic field, with a precision of about 100 µm. This residual misalignment is then taken into account in the simulations of the Z production and the efficiency computation. This method accounts for the relative misalignment of the detector elements but it is not sensitive to a global displacement of the entire muon spectrometer. The simulation of the response of the muon tracking system is based on a data-driven parametrization of the measured resolution of the clusters associated to a – 5 – JHEP09(2020)076 ) 2 c (GeV/ µµ m 20 40 60 80 100 120 ) 2 c (counts / 3.0 GeV/ µµ m/dNd 0 2 4 6 8 10 12 14 = 8.16 TeV NN sPb, −ALICE, p c > 20 GeV/ T µ p < 3.53 cms µµ y2.03 < Data POWHEG (a) ) 2 c (GeV/ µµ m 20 40 60 80 100 120 ) 2 c (counts / 3.0 GeV/ µµ m/dNd 0 2 4 6 8 10 12 = 8.16 TeV NN sPb, −ALICE, p c > 20 GeV/ T µ p < -2.96 cms µµ y-4.46 < Data POWHEG (b) ) 2 c (GeV/ µµ m 40 60 80 100 120 140 ) 2 c (counts / 2.5 GeV/ µµ m/dNd 0 5 10 15 20 25 30 35 40 45 = 5.02 TeV NN sPb, −90% Pb−ALICE, 0 c > 20 GeV/ T µ p < 4 cms µµ y2.5 < Data, opposite charge Data, same charge POWHEG (c) Figure 1. Invariant mass distribution of µ+µ−pairs for p-Pb collisions at √sNN = 8.16 TeV in (a) the p-going and (b) Pb-going data samples, and (c) Pb-Pb collisions at √sNN = 5.02 TeV. The distributions are obtained from muons with −4< ηµ<−2.5 and pµ T>20 GeV/c(black points) and compared with POWHEG simulations (red curves), which are normalized to the number of Z bosons in the data. The single like-sign dimuon entry is also shown (orange point) for Pb-Pb collisions, while no entries were found in the p-Pb samples. track [40], using extended Crystal-Ball (CB) functions [49] to reproduce the distribution of the difference between the cluster and the track positions in each chamber. The CB functions, having a Gaussian core and two power law tails, are first tuned to data and then used to simulate the smearing of the track parameters. The effect of a global misalignment of the spectrometer is implemented by applying a systematic shift, in opposite directions for positive and negative tracks, to the distribution of the angular deviation of the tracks in the magnetic field. This shift is tuned to reproduce the observed difference in the pµ T distributions of positive and negative tracks. In Pb-Pb collisions, the data were taken with two opposite magnetic field polarities of the muon spectrometer dipole magnet. In this case, the sign of the shift is inverted accordingly. – 6 – JHEP09(2020)076 The Z-boson raw yields are corrected for the acceptance times efficiency (A×) of the detector. It is evaluated with the MC simulations of the Z →µ+µ−process with POWHEG described above. The A×is estimated as the ratio of reconstructed Z bosons with the same selections as for the data, to the number of generated ones with 2.5< yµµ lab <4 for the dimuon pairs, and pµ T>20 GeV/cand −4< ηµ<−2.5 for the muons. The dimuon invariant mass selection 60 < mµµ <120 GeV/c2is applied to both reconstructed and generated distributions. In p-Pb collisions, the efficiency is 74% (72%) for the p-going (Pbgoing) sample. In Pb-Pb collisions, the efficiency depends on the detector occupancy and therefore on the centrality of the collision. To account for this effect, the generated signal is embedded in real Pb-Pb events. The efficiency is found to be stable from peripheral to semi-central collisions, with a value of about 77% (71%) in the 2015 (2018) data sample and decreases to 71% (66%) for the most central collisions. The centrality-integrated efficiency amounts to 73% in the 2015 dataset and 68% for the 2018 dataset. The Z-boson invariant yield is then computed by dividing the number of measured candidates, corrected for A×, by the corresponding number of minimum bias events. The latter is evaluated using the normalization factor Fµ−trig/MB, corresponding to the inverse of the probability to observe an opposite-sign dimuon triggered event in a MB event. The value of Fµ−trig/MB is evaluated with two methods: (i) by applying the opposite-sign dimuon trigger condition in the analysis of MB events, and (ii) by comparing the counting rate of the two triggers, both corrected for pile-up effects. The first method is performed on the smaller data sample of the recorded MB events. In the second method, information from the trigger counters was used. This means that the relative frequencies of MB and triggered events were counted, including events that were not stored. The pile-up correction accounts for the occurrence of multiple collisions in a time span smaller than the detector resolution. The latter is of the order of 2% in p-Pb collisions and is negligible in Pb-Pb due to a lower collision rate. The final value is the average over the two methods. In Pb-Pb collisions, the normalization factor is computed for all the centrality classes considered. In the p-Pb analysis, the invariant yield is multiplied by the MB cross section to obtain the Z-production cross section [41]. In the Pb-Pb analysis, results are given both integrated and differential with respect to centrality and rapidity. The production is expressed as the invariant yield, normalized by the nuclear overlap function hTAAi. The centrality is expressed as hNparti, the average number of participant nucleons. The hTAAiand hNparti quantities are estimated via a Glauber model fit of the signal amplitude in the two arrays of the V0 detector [37]. The nuclear modification of the production of a hard process, such as those producing the Z boson, is measured by RAA, the ratio of the observed normalized yield in Pb-Pb collisions to that in pp collisions. Due to the insufficient integrated luminosity for pp collisions at √sNN = 5 TeV, the pp reference is determined from pQCD theoretical calculations using the MCFM code with the CT14 PDF set [50]. The relative systematic uncertainties for the p-Pb analysis are summarized in table 1. The variation between the two methods for the computation of the normalization factor, which is less than 1%, is taken as its systematic uncertainty. The evaluation of A×is – 7 – JHEP09(2020)076 In the Pb-Pb data, the invariant yield normalized by the average nuclear overlap function has been evaluated in the rapidity range from 2.5< yµµ cms <4 and in the 0–90% centrality class. The results obtained in this paper supersede those from an earlier ALICE publication [20], where only part of the current dataset was used. The experimental data are, within uncertainties, in agreement with theoretical calculations that include various parametrizations of nuclear modification of the PDFs. On the contrary, the integrated yield deviates by 3.4σfrom the prediction obtained using free-nucleon PDFs. Comparisons with models of the measured differential yields versus centrality and rapidity were also carried out, generally showing agreement with nuclear modified PDFs. In contrast, a discrepancy with calculations based on free-nucleon PDFs was found. The differential measurements presented in this paper can provide additional constraints to the nPDFs. Acknowledgments The authors would like to extend special thanks to H. Paukkunen and I. Helenius for providing the CT14NLO, EPS09s and EPPS16 calculations, as well as K. Kovarik, A. Kusina, F. Olness, I. Schienbein and T. Tunks for the nCTEQ predictions. The ALICE Collaboration would like to thank all its engineers and technicians for their invaluable contributions to the construction of the experiment and the CERN accelerator teams for the outstanding performance of the LHC complex. The ALICE Collaboration gratefully acknowledges the resources and support provided by all Grid centres and the Worldwide LHC Computing Grid (WLCG) collaboration. The ALICE Collaboration acknowledges the following funding agencies for their support in building and running the ALICE detector: A. I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation (ANSL), State Committee of Science and World Federation of Scientists (WFS), Armenia; Austrian Academy of Sciences, Austrian Science Fund (FWF): [M 2467N36] and Nationalstiftung f¨ur Forschung, Technologie und Entwicklung, Austria; Ministry of Communications and High Technologies, National Nuclear Research Center, Azerbaijan; Conselho Nacional de Desenvolvimento Cient´ıfico e Tecnol´ogico (CNPq), Financiadora de Estudos e Projetos (Finep), Funda¸c˜ao de Amparo `a Pesquisa do Estado de S˜ao 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 Tecnol´ogicas y Desarrollo Nuclear (CEADEN), Cubaenerg´ıa, 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 `a l’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 f¨ur Bildung und Forschung (BMBF) and GSI Helmholtzzentrum f¨ur Schwerionenforschung GmbH, Germany; General Secretariat for Research and Technol- – 14 – JHEP09(2020)076 ogy, 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 Tecnolog´ıa, through Fondo de Cooperaci´on Internacional en Ciencia y Tecnolog´ıa (FONCICYT) and Direcci´on 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 Cat´olica del Per´u, Peru; Ministry of Science and Higher Education, National Science Centre and WUT ID-UB, Poland; Korea Institute of Science and Technology Information and National Research Foundation of Korea (NRF), Republic of Korea; Ministry of Education and Scientific Research, Institute of Atomic Physics and Ministry of Research and Innovation and Institute of Atomic Physics, Romania; Joint Institute for Nuclear Research (JINR), Ministry of Education and Science of the Russian Federation, National Research Centre Kurchatov Institute, Russian Science Foundation and Russian Foundation for Basic Research, Russia; Ministry of Education, Science, Research and Sport of the Slovak Republic, Slovakia; National Research Foundation of South Africa, South Africa; Swedish Research Council (VR) and Knut & Alice Wallenberg Foundation (KAW), Sweden; European Organization for Nuclear Research, Switzerland; Suranaree University of Technology (SUT), National Science and Technology Development Agency (NSDTA) and Office of the Higher Education Commission under NRU project of Thailand, Thailand; Turkish Atomic Energy Agency (TAEK), Turkey; National Academy of Sciences of Ukraine, Ukraine; Science and Technology Facilities Council (STFC), United Kingdom; National Science Foundation of the United States of America (NSF) and United States Department of Energy, Office of Nuclear Physics (DOE NP), United States of America. 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Nair85, B.K. Nandi49, R. Nania10,54, E. Nappi53, M.U. Naru14, A.F. Nassirpour81, C. Nattrass130, R. Nayak49, T.K. Nayak86, S. Nazarenko109, A. Neagu20, R.A. Negrao De Oliveira68, L. Nellen69, S.V. Nesbo36, G. Neskovic39, D. Nesterov113, L.T. Neumann142, B.S. Nielsen89, S. Nikolaev88, S. Nikulin88, V. Nikulin98, F. Noferini10,54, P. Nomokonov75, J. Norman79,127, N. Novitzky133, P. Nowakowski142, A. Nyanin88, J. Nystrand21, M. Ogino82, A. Ohlson81,104, J. Oleniacz142, A.C. Oliveira Da Silva130, M.H. Oliver146, C. Oppedisano59, A. Ortiz Velasquez69, A. Oskarsson81, J. Otwinowski118, K. Oyama82, Y. Pachmayer104, V. Pacik89, S. Padhan49, D. Pagano140, G. Pai´c69, J. Pan143, S. Panebianco137, P. Pareek50,141, J. Park61, J.E. Parkkila126, S. Parmar100, S.P. Pathak125, B. Paul23, J. Pazzini140, H. Pei6, T. Peitzmann63, X. Peng6, L.G. Pereira70, H. Pereira Da Costa137, D. Peresunko88, G.M. Perez8, S. Perrin137, Y. Pestov4, V. Petr´aˇcek37, M. Petrovici48, R.P. Pezzi70, S. Piano60, M. Pikna13, P. Pillot115, O. Pinazza34,54, L. Pinsky125, C. Pinto27, S. Pisano10,52, D. Pistone56, M. P losko´n80, M. Planinic99, F. Pliquett68, M.G. Poghosyan96, B. Polichtchouk91, N. Poljak99, A. Pop48, S. Porteboeuf-Houssais134, V. Pozdniakov75, S.K. Prasad3, R. Preghenella54, F. Prino59, C.A. Pruneau143, I. Pshenichnov62, M. Puccio34, J. Putschke143, S. Qiu90, L. Quaglia25, R.E. Quishpe125, S. Ragoni111, S. Raha3, S. Rajput101, J. Rak126, A. Rakotozafindrabe137, L. Ramello31, F. Rami136, S.A.R. Ramirez45, R. Raniwala102, S. Raniwala102, S.S. R¨as¨anen44, R. Rath50, V. Ratza43, I. Ravasenga90, K.F. Read96,130, A.R. Redelbach39, K. Redlich85,vi, A. Rehman21, P. Reichelt68, F. Reidt34, X. Ren6, R. Renfordt68, Z. Rescakova38, K. Reygers104, A. Riabov98, V. Riabov98, T. Richert81,89, M. Richter20, P. Riedler34, W. Riegler34, F. Riggi27, C. Ristea67, S.P. Rode50, M. Rodr´ıguez Cahuantzi45, K. Røed20, R. Rogalev91, E. Rogochaya75, D. Rohr34, D. R¨ohrich21, P.F. Rojas45, P.S. Rokita142, F. 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Tejeda Mu˜noz45, A. Telesca34, L. Terlizzi25, C. Terrevoli125, D. Thakur50, S. Thakur141, D. Thomas119, F. Thoresen89, R. Tieulent135, A. Tikhonov62, A.R. Timmins125, A. Toia68, N. Topilskaya62, M. Toppi52, F. Torales-Acosta19, S.R. Torres37, A. Trifir´o32,56, S. Tripathy50,69, T. Tripathy49, S. Trogolo28, G. Trombetta33, L. Tropp38, V. Trubnikov2, W.H. Trzaska126, T.P. Trzcinski142, B.A. Trzeciak37,63, A. Tumkin109, R. Turrisi57, T.S. Tveter20, K. Ullaland21, E.N. Umaka125, A. Uras135, G.L. Usai23, M. Vala38, N. Valle139, S. Vallero59, N. van der Kolk63, L.V.R. van Doremalen63, M. van Leeuwen63, P. Vande Vyvre34, D. Varga145, Z. Varga145, M. Varga-Kofarago145, A. Vargas45, M. Vasileiou84, A. Vasiliev88, O. V´azquez Doce105, V. Vechernin113, E. Vercellin25, S. Vergara Lim´on45, L. Vermunt63, R. Vernet7, R. V´ertesi145, L. Vickovic35, Z. Vilakazi131, O. Villalobos Baillie111, G. Vino53, A. Vinogradov88, T. Virgili29, V. Vislavicius89, A. Vodopyanov75, B. Volkel34, M.A. V¨olkl103, K. 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Zurlo140, iDeceased ii Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Bologna, Italy iii Dipartimento DET del Politecnico di Torino, Turin, Italy iv M.V. Lomonosov Moscow State University, D.V. Skobeltsyn Institute of Nuclear, Physics, Moscow, Russia vDepartment of Applied Physics, Aligarh Muslim University, Aligarh, India vi Institute of Theoretical Physics, University of Wroclaw, Poland 1A.I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation, Yerevan, Armenia 2Bogolyubov Institute for Theoretical Physics, National Academy of Sciences of Ukraine, Kiev, Ukraine 3Bose Institute, Department of Physics and Centre for Astroparticle Physics and Space Science (CAPSS), Kolkata, India 4Budker Institute for Nuclear Physics, Novosibirsk, Russia 5California Polytechnic State University, San Luis Obispo, California, United States 6Central China Normal University, Wuhan, China 7Centre de Calcul de l’IN2P3, Villeurbanne, Lyon, France 8Centro de Aplicaciones Tecnol´ogicas y Desarrollo Nuclear (CEADEN), Havana, Cuba 9Centro de Investigaci´on y de Estudios Avanzados (CINVESTAV), Mexico City and M´erida, Mexico – 22 – JHEP09(2020)076 10 Centro Fermi - Museo Storico della Fisica e Centro Studi e Ricerche “Enrico Fermi’, Rome, Italy 11 Chicago State University, Chicago, Illinois, 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, Nebraska, United States 16 Department of Physics, Aligarh Muslim University, Aligarh, India 17 Department of Physics, Pusan National University, Pusan, Republic of Korea 18 Department of Physics, Sejong University, Seoul, Republic of Korea 19 Department of Physics, University of California, Berkeley, California, United States 20 Department of Physics, University of Oslo, Oslo, Norway 21 Department of Physics and Technology, University of Bergen, Bergen, Norway 22 Dipartimento di Fisica dell’Universit`a ’La Sapienza’ and Sezione INFN, Rome, Italy 23 Dipartimento di Fisica dell’Universit`a and Sezione INFN, Cagliari, Italy 24 Dipartimento di Fisica dell’Universit`a and Sezione INFN, Trieste, Italy 25 Dipartimento di Fisica dell’Universit`a and Sezione INFN, Turin, Italy 26 Dipartimento di Fisica e Astronomia dell’Universit`a and Sezione INFN, Bologna, Italy 27 Dipartimento di Fisica e Astronomia dell’Universit`a and Sezione INFN, Catania, Italy 28 Dipartimento di Fisica e Astronomia dell’Universit`a and Sezione INFN, Padova, Italy 29 Dipartimento di Fisica ‘E.R. Caianiello’ dell’Universit`a and Gruppo Collegato INFN, Salerno, Italy 30 Dipartimento DISAT del Politecnico and Sezione INFN, Turin, Italy 31 Dipartimento di Scienze e Innovazione Tecnologica dell’Universit`a del Piemonte Orientale and INFN Sezione di Torino, Alessandria, Italy 32 Dipartimento di Scienze MIFT, Universit`a di Messina, Messina, Italy 33 Dipartimento Interateneo di Fisica ‘M. Merlin’ and Sezione INFN, Bari, Italy 34 European Organization for Nuclear Research (CERN), Geneva, Switzerland 35 Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Split, Croatia 36 Faculty of Engineering and Science, Western Norway University of Applied Sciences, Bergen, Norway 37 Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Prague, Czech Republic 38 Faculty of Science, P.J. ˇ Saf´arik University, Koˇsice, Slovakia 39 Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-Universit¨at Frankfurt, Frankfurt, Germany 40 Fudan University, Shanghai, China 41 Gangneung-Wonju National University, Gangneung, Republic of Korea 42 Gauhati University, Department of Physics, Guwahati, India 43 Helmholtz-Institut f¨ur Strahlenund Kernphysik, Rheinische Friedrich-Wilhelms-Universit¨at Bonn, Bonn, Germany 44 Helsinki Institute of Physics (HIP), Helsinki, Finland 45 High Energy Physics Group, Universidad Aut´onoma de Puebla, Puebla, Mexico 46 Hiroshima University, Hiroshima, Japan 47 Hochschule Worms, Zentrum f¨ur Technologietransfer und Telekommunikation (ZTT), Worms, Germany 48 Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest, Romania 49 Indian Institute of Technology Bombay (IIT), Mumbai, India 50 Indian Institute of Technology Indore, Indore, India 51 Indonesian Institute of Sciences, Jakarta, Indonesia 52 INFN, Laboratori Nazionali di Frascati, Frascati, Italy 53 INFN, Sezione di Bari, Bari, Italy – 23 –