Centrality dependence of the pseudorapidity density distribution for charged particles in Pb–Pb collisions at √sNN=5.02 TeV

Physics Letters B 772 (2017) 567–577 Contents lists available at ScienceDirect Physics Letters B www.elsevier.com/locate/physletb Centrality dependence of the pseudorapidity density distribution for charged particles in Pb–Pb collisions at √sNN =5.02 TeV .ALICE Collaboration a r t i c l e i n f o a b s t r a c t Article history: Received 9 January 2017 Received in revised form 19 June 2017 Accepted 9 July 2017 Available online 14 July 2017 Editor: L. Rolandi We present the charged-particle pseudorapidity density in Pb–Pb collisions at √sNN =5.02 TeV in centrality classes measured by ALICE. The measurement covers a wide pseudorapidity range from −3.5 to 5, which is sufficient for reliable estimates of the total number of charged particles produced in the collisions. For the most central (0–5%) collisions we find 21 400 ±1 300, while for the most peripheral (80–90%) we find 230 ±38. This corresponds to an increase of (27 ±4)%over the results at √sNN = 2.76 TeV previously reported by ALICE. The energy dependence of the total number of charged particles produced in heavy-ion collisions is found to obey a modified power-law like behaviour. The chargedparticle pseudorapidity density of the most central collisions is compared to model calculations — none of which fully describes the measured distribution. We also present an estimate of the rapidity density of charged particles. The width of that distribution is found to exhibit a remarkable proportionality to the beam rapidity, independent of the collision energy from the top SPS to LHC energies. ©2017 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. 1. Introduction In ultra-relativistic heavy-ion collisions a dense and hot phase of nuclear matter is created [1–4]. This phase of QCD matter is considered to be a plasma of strongly interacting quarks and gluons and is therefore labelled the sQGP [5]. The multiplicity of primary, charged particles produced in heavy-ion collisions is a key observable to characterise the properties of the matter created in these collisions [6]. The study of the primary charged-particle pseudorapidity density (dNch/dη) over a wide pseudorapidity (η) range and its dependence on colliding system, centre-of-mass energy, and collision geometry is important to understand the relative contributions to particle production from hard scatterings and soft processes, and may provide insight into the partonic structure of the interacting nuclei. We havepreviously reported measurementsonprimary chargedparticle pseudorapidity densities over a wide pseudorapidity range in Pb–Pb collisions at the centre-of-mass energy per nucleon pair √sNN =2.76 TeV [7]. In this Letter, we study these distributions in the pseudorapidity interval from −3.5to 5at a collision energy of √sNN =5.02 TeV as a function of the centrality. Pseudorapidity is defined as η≡− log(tan(ϑ/2)), where ϑis the angle between the charged-particle trajectory and the beam axis (z-axis). Nuclei are extended objects, and their collisions can be characterised by centrality — the experimental proxy for the un-measurable distance E-mail address: [email protected]. between the centres of the colliding nuclei (impact parameter). Aprimary particle is a particle with a mean proper lifetime τ larger than 1cm/c, which is either a) produced directly in the interaction, or b) from decays of particles with τsmaller than 1cm/c, restricted to decay chains leading to the interaction [8]. In this Letter, all quantities reported are for primary charged particles, though we will omit “primary” for brevity. With the large pseudorapidity coverage available in ALICE, we can reliably estimate, for all centrality classes, the total number of charged particles produced in the collisions. We therefore also present the first measurement of the total charged-particle multiplicity in Pb–Pb collisions at √sNN =5.02 TeV as a function of the number of nucleons participating in the collisions (Npart). Finally, we transform the measured dNch/dηdistribution for the 5% most central collisions into charged-particle rapidity density (dNch/dy), and we examine the centre-of-mass energy dependence of the width of that distribution. The rapidity (y) of a particle with energy Eand momentum component pzalong the beam axis is defined as y ≡1 2log([E+pz]/[E−pz]). The comparison of the width of the dNch/dyat different collision energies provides an insight into the constraints on the overall production mechanism of charged particles. 2. Experimental setup A detailed description of ALICE and its performance can be found elsewhere [9,10]. In the following, we briefly describe the detectors relevant to this analysis. http://dx.doi.org/10.1016/j.physletb.2017.07.017 0370-2693/©2017 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. 568 ALICE Collaboration / Physics Letters B 772 (2017) 567–577 The Silicon Pixel Detector (SPD), the innermost part of the Inner Tracking System (ITS), consists of two cylindrical layers of hybrid silicon pixel assemblies covering |η| <2 and |η| <1.4for the inner and outer layers, respectively. Combinations of hits on each of the two layers consistent with tracks originating from the interaction point form tracklets. The Forward Multiplicity Detector (FMD) is a silicon strip detector which, records the energy deposited by particles traversing the it. The detector covers the pseudorapidity regions −3.5 <η<−1.8 and 1.8 <η<5, and has almost full coverage in azimuth (ϕ), and high granularity in the radial (η) direction. The third detector system used in this analysis is the V0. It consists of two sub-detectors: V0-A and V0-C covering the pseudorapidity regions 2.8 <η<5.1 and −3.7 <η<−1.7, respectively, each made up of scintillator tiles with a timing resolution <1ns. The fast signals from either of V0-A or V0-C are combined in a programmable logic to form a trigger signal and to reject background events. Furthermore, the combined pulse height signal of both sub-detectors forms the basis for the classification of events into different centrality classes [11]. The Zero-Degree Calorimeter (ZDC) measures the energy of spectator (non-interacting) nucleons with two components: one measures protons and the other measures neutrons. The ZDC is located at about 112.5 m from the interaction point on both sides of the experiment [9]. The ZDC also provides timing information used to select collisions in the off-line data processing. 3. Data sample and analysis method The results presented here are based on data collected by ALICE in 2015 during the Pb–Pb collision run of the LHC at √sNN = 5.02 TeV. About 100 000 events with a minimum bias trigger requirement [12] were analysed in the centrality range from 0% to 90%. The minimum bias trigger for Pb–Pb collisions in ALICE, which defines the so-called visible cross-section, is defined as a coincidence between the A (z>0) and C (z<0) sides of the V0 detector. The standard ALICE event selection [13] and centrality estimator based on the V0–amplitude [11] are used in this analysis. The event selection consists of: exclusion of background events using the timing information from the ZDC and V0 detectors; verification of the trigger conditions; and a reconstructed position of the collision. As discussed elsewhere [11], the 90–100% centrality class has substantial contributions from QED processes and is therefore not included in the results presented here. The measurement of the charged-particle pseudorapidity density at mid-rapidity (|η| <2) is obtained from a tracklet analysis using the two layers of the SPD. The analysis method used is identical to what has previously been presented [12,14,15]. Note that no attempt is made to correct for known deficiencies, such as deviations in the number of strange particles or transverse momentum (pT) distributions compared to experimental measurements [11,16, 17], in the event generators used to obtain the corrections from simulations (e.g., HIJING). It is found, through simulation studies, that tracklet reconstruction first and foremost depends on the local hit density and only weakly on particle mix and transverse momentum. For example, the deficit of strange particles in the event generator effects the result by less than 2%. Since the event generators generally, after detector simulation, produce a local hit density that is consistent with what is observed in data, we observe a correspondence between the tracklet samples of both simulations and data. On the other hand, changing the number of tracklets corresponding to strange particles a postiori to match the measured relative yields dramatically biases the simulated tracklet sample away from the measured, thus entailing systematic uncertainties that are beyond the effect of the known event generator deficiencies, and Fig. 1. [Colour online.] Charged-particle pseudorapidity density for ten centrality classes over a broad ηrange in Pb–Pb collisions at √sNN =5.02 TeV. Boxes around the points reflect the total uncorrelated systematic uncertainties, while the filled squares on the right reflect the correlated systematic uncertainty (evaluated at η=0). Statistical errors are generally insignificant and smaller than the markers. Also shown is the reflection of the 3.5 <η<5values around η=0(open circles). The line corresponds to fits of the difference between two Gaussians centred at η=0(fGG) [7] to the data. as such do not improve the accuracy of the measurements. Instead, variations on the event generators are used to estimate the systematic uncertainties as detailed elsewhere [12,14,15]. In the forward regions (−3.5 <η<−1.8 and 1.8 <η<5), the measurement is provided by the analysis of the deposited energy signal in the FMD. The analysis method used is identical to what has previously been presented [7,14]: astatistical approach to calculate the inclusive number of charged particles; and a data-driven correction — derived from previous satellite-main collisions — to remove the large background from secondary particles. 4. Systematic uncertainties For the measurements at mid-rapidity the sources and dependencies of the systematic uncertainties are detailed elsewhere [7,12,15]. The magnitude of the systematic uncertainties is unchanged with respect to previous results, and amounts to 2.6% at η=0 and 2.9% at η=2, most of which is correlated over |η| <2, and largely independent of centrality. The systematic uncertainty on the forward analysis is evaluated using the same technique as for previous results [7]. We find that the uncertainty is uncorrelated across ηan that it amounts to 6.9% for η>3.5and 6.4% elsewhere within the forward regions. The systematic uncertainty on dNch/dηdue to the centrality class definition is estimated as 0.6% for the most central and 9.5% for the most peripheral class [15]. The uncertainty is estimated by using alternative centrality definitions based on SPD hit multiplicities and by varying the fraction of the visible hadronic crosssection. The 80–90% centrality class has some residual contamination from electromagnetic processes detailed elsewhere [11], which gives rise to a 4% additional systematic uncertainty on the measurements. In summary, the total systematic uncertainty varies from 2.6% at mid-rapidity in the most central collisions to 12.4% at the very forward rapidities for the most peripheral collisions. 5. Results Fig. 1 presents the charged-particle pseudorapidity density as a function of pseudorapidity for ten centrality classes. The measurements from the SPD and FMD are combined in regions of overlap (1.8 <|η| <2) between the two detectors by taking the weighted average using the non-shared uncertainties as weights. Finally, based on the symmetry of the collision system, the result is symmetrised around η=0, and extended into the non-measured ALICE Collaboration / Physics Letters B 772 (2017) 567–577 569 Fig. 2. [Colour online.] Total number of charged particles as a function of the mean number of participating nucleons [11]. The total charged-particle multiplicity is given as the integral over dNch/dηover the measured region (−3.5 <η<5) and extrapolations from fitted functions in the unmeasured regions. The contribution from unmeasured ηregions amounts to ≈30% of the total number of charged particles. The uncertainty on the extrapolation to the unmeasured pseudorapidity region is smaller than the size of the markers. The contribution to the systematic uncertainties from the centrality determination and electromagnetic processes are vanishing compared to the contribution from the largest differences between the fitted functions. A function inspired by factorisation [18] is fitted to the data, and the best fit yields a =51.5 ±7.3, b =0.16 ±0.05. region −5 <η<−3.5by reflecting the 3.5 <η<5values around η=0. Complementing result previously reported at mid-rapidity [15], we find dNch/dη||η|<0.5=17.52 ±0.05(stat) ±1.84(sys)and Npart =7.3 ±0.1in the 80–90% centrality class. The measured distributions are fitted with four functions fGG, fP, fT, and fB[7], which are the difference of two Gaussian distributions centred at η=0; a parametrisation proposed by PHOBOS [18]; a trapezoidal form; and a plateau connected to Gaussian tails, respectively. To extract the total number of charged particles, we calculate the integral and uncertainty from the data in the measured region and use the integrals of the fitted functions in the unmeasured regions up to the beam rapidity ±ybeam =±8.6. As for the previous measurements at √sNN =5.02 TeV, the central value in the unmeasured regions (−8.6 <η<−3.5 and 5 <η< 8.6) is taken from the fit of the function fT, while the uncertainty is evaluated as the largest difference between the fitted functions scaled by 1/√3[7,14]. The total charged-particle multiplicity is shown in Fig. 2 versus the mean number of participating nucleons (Npart) estimated from a Glauber calculation [11,15]. After removing correlated systematic uncertainties, we observe an increase in the total number of charged particles of (27 ±4)%with respect to the measurements at √sNN =2.76 TeV [7] for all centrality classes. The line shown in Fig. 2 corresponds to a fit of a function inspired by factorisation [18]. The function illustrates scaling by number of participant pairs, with a small perturbation proportional to the cubic root of the number of participants. As the number of nucleon–nucleon collisions (Ncoll) scales roughly like the square of the number of participants Ncoll ≈N2 part [19], we see no indication of scaling by number of nucleon–nucleon collisions. The observed total Nch dependence on Npartprovides no evidence of any significant increase in the number of hard scatterings between the participating nucleons and partons. In Fig. 3, we compare the charged-particle pseudorapidity density for the 0–5% most central collisions to three models: HIJING [20]; EPOS–LHC [21]; and KLN [22,23], also for the 0–5% most central, except for KLN which is shown for the 0–6% centrality class. Two versions of HIJING are used: version 1.383, with jet quenching disabled, shadowing enabled, and a hard pTcut-off of 2.3 GeV; and the newer version 2.1 [24]. Both are two-component models with a soft and hard sector defined by a pTcut-off separating the two. In the 2.1 implementation, HIJING uses an upgraded parametrisation of the nuclear parton distribution func- Fig. 3. [Colour online.] Comparison of dNch/dηin the 0–5% (0–6% for KLN) most central collisions of two versions of HIJING, KLN, and EPOS–LHC model calculations to the measured distribution. Fig. 4. [Colour online.] Total number of charged particles as a function of √sNN for the most central collisions at AGS (0–5% Au–Au) [25,26], SPS (0–5% Pb–Pb) [27,28], RHIC (0–5% and 0–6% Au–Au) [18,29,30], and LHC (0–5% Pb–Pb) [14]. The dotted, dashed, and full lines are extrapolations from fits to lower energy results [14], while the dash-dotted line is a fit over all energies, including √sNN =5.02 TeV. tions. This results in a larger cross section for soft processes and a smaller cross section for jet production. The KLN model is based on Colour-Glass-Condensate initial conditions, while EPOS-LHC uses so-called parton-ladders which hadronise in a medium. While none of the three models describe the measured charged-particle pseudorapidity density over the full pseudorapidity range, we observe some differences: HIJING 1.383 over-predicts the chargedparticle production especially away from η≈0; EPOS–LHC and HIJING 2.1 consistently under-predict the charge-particle production; whereas KLN, EPOS–LHC, and HIJING 2.1 give a shape reasonably close to the observed distribution. Not shown in Fig. 3, for both HIJING 1.383 and EPOS–LHC, these observations hold over all centrality classes i.e., HIJING 1.383 consistently produces far too many particles away from mid-rapidity and EPOS–LHC consistently under-predicts the charged-particle yield over the full ηrange. These trends become increasingly more pronounced for more peripheral collisions. Fig. 4 shows the total number of charged particles produced in the most central heavy-ion collisions as a function of the collision energy, ranging from √sNN =2.6GeVto 5.02 TeV [14]. The dotted, dashed, and full-drawn lines in the figure represent extrapolations from lower energy results to the current top LHC energy of √sNN =5.02 TeV. None of these predictions fully describe the data. Arefit of the simple model of a logarithmic-dampened power-law in the square collision energy (s) including from the lowest to the highest energy results, shown as the dash-dotted line, does accurately describe the total number of charged particles at all available energies. 570 ALICE Collaboration / Physics Letters B 772 (2017) 567–577 Fig. 5. [Colour online.] Estimate of dNch/dyin the most central (0–5%) Pb–Pb collisions at √sNN =5.02 TeV. Also shown are the Landau–Wong [31], Landau– Carruthers [32], Gaussian, and double-Gaussian distributions. Fig. 6. [Colour online.] Scaling behaviour as a function √sNN of the width of the charged-particle or -pion rapidity-density distribution with respect to the Landau– Carruthers width (top) and rapidity range (bottom). Charged-pion points from AGS and SPS are adapted from the literature [33], while the PHOBOS (filled crosses) [34] and BRAHMS (open crosses) [30] charged-hadron points are translated from the corresponding dNch/dηresults. We can calculate the Jacobian transform from ηto rapidity yby assuming the same transverse momentum distribution of (anti-)protons, and charged kaons and pions, and the same particle ratios in Pb–Pb collisions at √sNN =5.02 TeV as in √sNN = 2.76 TeV. The result is presented in Fig. 5 for the 0–5% most central collisions. The effect on the Jacobian from the change of pT spectra and particle ratios when increasing the collision energy by almost a factor two is evaluated using the EPOS–LHC model [21]. It is found, that the effect is at most 3‰ on both dNch/dyand y— much smaller than the systematic uncertainty and ηresolution of the analysis. Fig. 5 also shows the expected charged-particle rapidity densities from the Landau–Carruthers [32] and Landau–Wong [31] models, both assuming Landau hydrodynamics i.e., based on a reaction scenario with full stopping of the reaction partners and a subsequent thermodynamic evolution. The measurements, however, are seen to be consistent with a Gaussian distribution with a width of 4.12 ±0.10, much wider than the width expected from the two models. A best parameter fit of the sum of two Gaussian distributions with means symmetric around y =0, is indistinguishable from the single Gaussian case. In the top part of Fig. 6 we compare the widths of the charged-particle or -pion rapidity density distribution extracted from measurements to the expected width σ2 L-C =log(√sNN/2mp) from Landau–Carruthers, where mpis the proton mass, at collision energies ranging from 2.6GeVup to 5.02 TeV. An increase of ≈7% of σdNX/dy/σL-C is seen from the √sNN =2.76 TeV ALICE measurements [14]. The full evolution is consistent with an almost linear rise as a function of log√sNN from the top SPS energy at √sNN =17.3GeV. It can be shown [35] that the width of the rapidity-density distribution in Landau hydrodynamics scales as σdNX/dy∝1/(1 −c2 s), where csis the speed of sound in the matter. The lifetime of the system scales inversely with cs, and given that the measured width is larger than the predicted by Landau hydrodynamics, it is an indication that, given the considerations above, the lifetime is shorter than suggested. In the bottom part of Fig. 6 we compare the width of the dNch/dydistribution to the available rapidity range (2ybeam). We observe no dependence of this ratio from √sNN =17.3 GeV and upward, indicating that the available phase–space constrains the width of that distribution. The charged-hadron measurements at RHIC (crosses) from the BRAHMS [30] and PHOBOS [34] measurements of dNch/dηare converted to dNch/dyusing the same method as applied to the ALICE data. Previously, charged-pion measurements from BRAHMS have been reported [33]. These data are not included because a re-evaluation using RHIC Run-4 Au–Au data has not been finalised [36]. From the observed spscaling of the charged-particle pseudorapidity density at mid-rapidity [15] we expect a 20% increase over √sNN =2.76 TeV in the level of dNch/dη||η|<0.5and from the extracted width of dNch/dywe observe an additional 7%, consistent with the increase of 27% over √sNN =2.76 TeV in the total number of charged particles produced in √sNN =5.02 TeV collisions. 6. Conclusions The charged-particle pseudorapidity density is measured in Pb– Pb collisions at √sNN =5.02 TeV over the psuedorapidity range −3.5 <η<5. The total number of charged particles produced is determined owing to the large pseudorapidity acceptance of ALICE. The latter increases by two orders of magnitude from the most peripheral to the most central collisions and scales approximately with the number of participating nucleons. The increase in the total number of charged particles relative to √sNN =2.76 TeV is estimated to be (27 ±4)%. The charged-particle rapidity density for the most central collisions is extracted, and the width of that distribution is compared to predictions from the Landau–Carruthers and Landau–Wong hydrodynamic models. It is found that the measured charged-particle rapidity density becomes increasingly wider as a function of collision energy than predicted by Landau hydrodynamics. The width of the charged-particle rapidity density is seen to scale with the beam rapidity, which implies that the available phase space determines the longitudinal extend of the charged-particle production. The phase space dominance starts at the top SPS energy and persist for two orders of magnitude up to the top LHC energy. Acknowledgements The ALICE Collaboration would like to thank all its engineers and technicians for their invaluable contributions to the construction of the experiment and the CERN accelerator teams for the outstanding performance of the LHC complex. The ALICE Collaboration gratefully acknowledges the resources and support provided by all Grid centres and the Worldwide LHC Computing Grid (WLCG) collaboration. The ALICE Collaboration acknowledges the following funding agencies for their support in building and running the ALICE detector: A.I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation (ANSL), State Committee of Science and World Federation of Scientists (WFS), Armenia; Austrian Academy of Sciences and Nationalstiftung für Forschung, Technologie und Entwicklung, Austria; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Universidade Federal do Rio Grande do Sul (UFRGS), Financiadora de Estudos e Projetos (Finep) and Fundação de Amparo à Pesquisa do Estado ALICE Collaboration / Physics Letters B 772 (2017) 567–577 571 de São Paulo (FAPESP), Brazil; Ministry of Science & Technology of China (MSTC), National Natural Science Foundation of China (NSFC) and Ministry of Education of China (MOEC), China; Ministry of Science, Education and Sport and Croatian Science Foundation, Croatia; Ministry of Education, Youth and Sports of the Czech Republic, Czech Republic; The Danish Council for Independent Research– Natural Sciences, the Carlsberg Foundation and Danish National Research Foundation (DNRF), Denmark; Helsinki Institute of Physics (HIP), Finland; Commissariat à l’Energie Atomique (CEA) and Institut National de Physique Nucléaire et de Physique des Particules (IN2P3) and Centre National de la Recherche Scientifique (CNRS), France; Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie (BMBF) and GSI Helmholtzzentrum für Schwerionenforschung GmbH, Germany; Ministry of Education, Research and Religious Affairs, Greece; National Research, Development and Innovation Office, Hungary; Department of Atomic Energy, Government of India (DAE) and Council of Scientific and Industrial Research (CSIR), New Delhi, India; Indonesian Institute of Science, Indonesia; Centro Fermi -Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi and Istituto Nazionale di Fisica Nucleare (INFN), Italy; Institute for Innovative Science and Technology, Nagasaki Institute of Applied Science (IIST), Japan Society for the Promotion of Science (JSPS) KAKENHI and Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan; Consejo Nacional de Ciencia y Tecnología (CONACYT), through Fondo de Cooperación Internacional en Ciencia y Tecnología (FONCICYT) and Dirección General de Asuntos del Personal Academico (DGAPA), Mexico; Nationaal instituut voor subatomaire fysica (Nikhef), Netherlands; The Research Council of Norway, Norway; Commission on Science and Technology for Sustainable Development in the South (COMSATS), Pakistan; Pontificia Universidad Católica del Perú, Peru; Ministry of Science and Higher Education and National Science Centre, Poland; Korea Institute of Science and Technology Information and National Research Foundation of Korea (NRF), Republic of Korea; Ministry of Education and Scientific Research, Institute of Atomic Physics and Romanian National Agency for Science, Technology and Innovation, Romania; Joint Institute for Nuclear Research (JINR), Ministry of Education and Science of the Russian Federation and National Research Centre Kurchatov Institute, Russia; Ministry of Education, Science, Research and Sport of the Slovak Republic, Slovakia; National Research Foundation of South Africa, South Africa; Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Cubaenergía, Cuba, Ministerio de Ciencia e Innovacion and Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Spain; Swedish Research Council (VR) and Knut & Alice Wallenberg Foundation (KAW), Sweden; European Organization for Nuclear Research, Switzerland; National Science and Technology Development Agency (NSDTA), Suranaree University of Technology (SUT) and Office of the Higher Education Commission under NRU project of Thailand, Thailand; Turkish Atomic Energy Agency (TAEK), Turkey; National Academy of Sciences of Ukraine, Ukraine; Science and Technology Facilities Council (STFC), United Kingdom; National Science Foundation of the United States of America (NSF) and United States Department of Energy, Office of Nuclear Physics (DOE NP), United States of America. 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Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation, Yerevan, Armenia 2Benemérita Universidad Autónoma de Puebla, Puebla, Mexico 3Bogolyubov Institute for Theoretical Physics, Kiev, Ukraine 4Bose Institute, Department of Physics and Centre for Astroparticle Physics and Space Science (CAPSS), Kolkata, India 5Budker Institute for Nuclear Physics, Novosibirsk, Russia 6California Polytechnic State University, San Luis Obispo, CA, United States 7Central China Normal University, Wuhan, China 8Centre de Calcul de l’IN2P3, Villeurbanne, Lyon, France 9Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Havana, Cuba 10 Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain 11 Centro de Investigación y de Estudios Avanzados (CINVESTAV), Mexico City and Mérida, Mexico 12 Centro Fermi -Museo Storico della Fisica e Centro Studi e Ricerche “Enrico Fermi”, Rome, Italy 13 Chicago State University, Chicago, IL, United States 14 China Institute of Atomic Energy, Beijing, China 15 COMSATS Institute of Information Technology (CIIT), Islamabad, Pakistan 16 Departamento de Física de Partículas and IGFAE, Universidad de Santiago de Compostela, Santiago de Compostela, Spain 17 Department of Physics, Aligarh Muslim University, Aligarh, India 18 Department of Physics, Ohio State University, Columbus, OH, United States 19 Department of Physics, Sejong University, Seoul, South Korea 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 Division of Experimental High Energy Physics, University of Lund, Lund, Sweden 34 European Organization for Nuclear Research (CERN), Geneva, Switzerland 35 Excellence Cluster Universe, Technische Universität München, Munich, Germany 36 Faculty of Engineering, Bergen University College, Bergen, Norway 37 Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava, Slovakia 38 Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Prague, Czech Republic 39 Faculty of Science, P.J. Šafárik University, Košice, Slovakia 40 Faculty of Technology, Buskerud and Vestfold University College, Tonsberg, Norway 41 Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-Universität Frankfurt, Frankfurt, Germany 42 Gangneung-Wonju National University, Gangneung, South Korea 43 Gauhati University, Department of Physics, Guwahati, India 44 Helmholtz-Institut für Strahlen- und Kernphysik, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany 45 Helsinki Institute of Physics (HIP), Helsinki, Finland 46 Hiroshima University, Hiroshima, Japan 47 Indian Institute of Technology Bombay (IIT), Mumbai, India 48 Indian Institute of Technology Indore, Indore, India 49 Indonesian Institute of Sciences, Jakarta, Indonesia 50 Inha University, Incheon, South Korea 51 Institut de Physique Nucléaire d’Orsay (IPNO), Université Paris-Sud, CNRS-IN2P3, Orsay, France 52 Institute for Nuclear Research, Academy of Sciences, Moscow, Russia 53 Institute for Subatomic Physics of Utrecht University, Utrecht, Netherlands 54 Institute for Theoretical and Experimental Physics, Moscow, Russia 55 Institute of Experimental Physics, Slovak Academy of Sciences, Košice, Slovakia 56 Institute of Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic 57 Institute of Physics, Bhubaneswar, India 58 Institute of Space Science (ISS), Bucharest, Romania 59 Institut für Informatik, Johann Wolfgang Goethe-Universität Frankfurt, Frankfurt, Germany 60 Institut für Kernphysik, Johann Wolfgang Goethe-Universität Frankfurt, Frankfurt, Germany 61 Institut für Kernphysik, Westfälische Wilhelms-Universität Münster, Münster, Germany 62 Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Mexico City, Mexico 63 Instituto de Física, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil 64 Instituto de Física, Universidad Nacional Autónoma de México, Mexico City, Mexico 65 IRFU, CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France, Saclay, France 66 iThemba LABS, National Research Foundation, Somerset West, South Africa