Jet-associated deuteron production in pp collisions at √s = 13 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/ Jet-associated deuteron production in pp collisions at √s = 13 TeV © 2021 the Authors Published version ALICE Collaboration ALICE Collaboration. (2021). Jet-associated deuteron production in pp collisions at √s = 13 TeV. Physics Letters B, 819, Article 136440. https://doi.org/10.1016/j.physletb.2021.136440 2021 Physics Letters B 819 (2021) 136440 Contents lists available at ScienceDirect Physics Letters B www.elsevier.com/locate/physletb Jet-associated deuteron production in pp collisions at √s=13 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 1 December 2020 Received in revised form 29 April 2021 Accepted 7 June 2021 Available online 8 June 2021 Editor: M. Doser Deuteron production in high-energy collisions is sensitive to the space–time evolution of the collision system, and is typically described by a coalescence mechanism. For the first time, we present results on jet-associated deuteron production in pp collisions at √s=13 TeV, providing an opportunity to test the established picture for deuteron production in events with a hard scattering. Using a trigger particle with high transverse-momentum (pT>5GeV/c) as a proxy for the presence of a jet at midrapidity, we observe a measurable population of deuterons being produced around the jet proxy. The associated deuteron yield measured in a narrow angular range around the trigger particle differs by 2.4–4.8 standard deviations from the uncorrelated background. The data are described by PYTHIA model calculations featuring baryon coalescence. ©2021 The Author. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3. 1. Introduction Measurements of deuterons in high-energy collisions provide insight into baryon production and baryon transport mechanisms which are sensitive to the space–time evolution of the collision system. Deuteron and anti-deuteron spectra were measured in pp collisions at the CERN ISR [1,2] and Tevatron [3], photo-production processes and deep inelastic scattering of electrons at HERA [4,5], electron-positron collisions at CLEO [6] and LEP [7], and most recently at the LHC in pp collisions at √s=0.9, 2.76, 7 and 13 TeV [8–11], as well as in nucleus–nucleus collisions at SPS [12], RHIC [13] and LHC [8,14,15]energies. Deuteron production can be described by phenomenological models, according to which an (anti-)neutron and (anti-)proton close in phase-space coalesce and bind together [16–18]. The coalescence mechanism is of broader interest, as it has been employed in describing the production of nuclei and anti-nuclei as large as 4He and 4He [19,20], nucleons and hyperons forming hypernuclei [21,22], searches for exotic states such as pentaquarks [23], and searches for colorless SUSY- hybrid states with gluinos [24]. Statistical hadronization models, which assume particle production in thermal equilibrium, were also successful in explaining the yields of light (anti-)nuclei along with other hadrons in Pb–Pb collisions, but have difficulties to describe the data in smaller systems [25,26]. New insights may be obtained by studying the production of deuterons from hard processes, which can be explored by their formation within jets. To investigate the effects of jets on deuteron production, we employ the two-particle correlation method, as suggested in Ref. [27]. Charged particles with transverse momen- E-mail address: alice -publications @cern .ch. tum (pT) above 5GeV/ care taken as trigger particles to approximate the jet direction. The azimuthal correlation of deuteron candidates with respect to the trigger particle is measured in five pTintervals between 1 and 4 GeV/c. Impurities are accounted for by using a sideband subtraction method, and deuterons oriented randomly with respect to the trigger particle are subtracted using the zero yield at minimum (ZYAM) method [28]. The integrated yields of associated deuterons obtained within an azimuthal range of 0.7rad relative to the trigger particle, representing the region of jet fragmentation, are reported as a function of deuteron pT. In the coalescence picture, the smaller phase space provided by the jet fragmentation may promote deuteron production. Hence, the data are compared to model calculations based on PYTHIA (v8) with a coalescence afterburner [29]. The remainder of the letter is organized as follows. Section 2briefly describes the various ALICE subsystems, the dataset and event selection criteria for the measurement presented. Section 3discusses the particle identification and correlation analysis methods. Section 4presents the measurement of the associated deuteron yields, discusses the systematic uncertainties, and provides the comparison with the PYTHIA-based coalescence afterburner model. Section 5concludes the letter. 2. Experimental setup and dataset ALICE is a general purpose detector at the LHC with cylindrical geometry and outer dimensions of 16 ×16 ×26 m3[30]. A large solenoid magnet provides an uniform magnetic field of 0.5T along the beam direction (zdirection) and encases the central barrel around the nominal interaction point (IP) at z=0. The measurements presented use a subset of the ALICE detector systems, including the V0 [31], the Inner Tracking System (ITS) [32], the https://doi.org/10.1016/j.physletb.2021.136440 0370-2693/©2021 The Author. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3. ALICE Collaboration Physics Letters B 819 (2021) 136440 Time Projection Chamber (TPC) [33], the T0, and the Time-of-Flight (TOF) [34]detectors. The V0 is a forward detector system used for event triggering. It consists of two circular planes of plastic scintillators at 87 and 329 cm on opposite sides of the IP covering a pseudorapidity of −3.7 <η<−1.7 and 2.8 <η<5.1, respectively. The ITS is composed of six layers of silicon detectors ranging from 3.9 to 43 cm radius around the beam pipe. Together with the TPC, it is used for precise reconstruction of the primary vertex position and tracking of charged particles with η<0.9. The TPC is a large tracking drift detector (inner radius 85 cm, outer radius 250 cm and length 500 cm) providing up to 159 space points per track for momentum reconstruction as well as energy loss (dE/dx) measurement for particle identification. The T0 consists of two sets of 12 Cherenkov counters around the beam pipe at −70 cm and 374 cm which provides a measurement of the collision time. The TOF detector is a cylindrical wall with inner radius 3.7 m from the beam-pipe. The arrival time of incident hadrons is measured using multi-gap resistive plate chambers with an intrinsic resolution of about 80 ps. The particle identification method using a combination of tracking, timing, and energy loss measurements is described in Sect. 3. Further details of the performance of the ALICE detector systems are given in Ref. [35]. The analysis is based on the data recorded in pp collisions at √s=13 TeV during the years 2015–2018. The minimum-bias event selection required a hit in both sides of the V0 detector, resulting in approximately 1.8 billion events corresponding to an integrated luminosity of about 30 nb−1. Additional event selection criteria required at least one track in the ITS with a projection to a vertex position within 0.5cm along the beam direction from the position estimated by the T0 collision time. This requirement suppressed events from out-of-bunch beam background. The z-vertex position was required to be within 10 cm of the nominal IP to ensure approximately constant ηacceptance within the detector for all events. Pile-up events were suppressed by rejecting events with multiple vertices reconstructed by the ITS that are separated by more than 0.8 cm (in the z-direction). Approximately 88% of the minimum-bias events were accepted for further analysis. 3. Analysis method Deuteron candidates in several pTintervals were correlated with charged trigger particles above 5GeV/c. The correlation was studied as a function of the azimuthal angle difference (ϕ) between deuteron and trigger particle. In events with multiple triggers and/or deuteron candidates, all combinations were taken into account. Events with more than one 5GeV/cparticle correspond to 9.7% of the selected event sample, while events with more than one deuteron candidate are 0.05% of the total number of events with a deuteron candidate. Deuteron candidates were selected from reconstructed tracks in the central barrel with a pseudorapidity range of |η| <0.9 that passed several quality criteria. Tracks were required to contain at least two ITS and 70 TPC clusters, as well as at least 80% of the maximum possible TPC clusters along its path. For particle identification, agreement with the expected TOF (TPC) signal for deuterons within two (three) standard deviations of the pT- dependent resolution was required, as explained further below. To suppress secondaries, the distance-of-closest-approach (DCA) projections of the track to the reconstructed vertex projected on the transverse plane and longitudinal direction, had to be less than 0.5 and 1cm, respectively. In order to maintain a uniform azimuthal (ϕ) distribution for trigger particles, the track quality criteria were relaxed. In particular, the requirements of having a TOF hit, two ITS clusters, and maximal DCA were not imposed. The trigger condition pT> Table 1 Deuteron purity estimates for coarse pTintervals. pT-range (GeV/c)1.0–1.35 1.35–1.8 1.8–2.4 2.4–3.0 3.0–4.0 Purity (%) 99.5±0.1 98.4±0.4 75.5±1.7 46.1±1.9 25.5±1.4 5GeV/ cresults in an average trigger particle transverse momentum of 6.7 GeV/c. The time-of-flight (t) of a charged particle was obtained using the difference between the event collision time and the arrival time at the TOF. Together with the momentum (p) and path length (L) from the track reconstruction, the mass-squared (m2), m2=p2 c2t2c2 L2−1(1) was calculated for deuteron candidates. Example m2distributions of deuteron candidates for different pTintervals are shown in Fig. 1. The signal component was fit using a Crystal Ball function [36]. The standard deviation was approximated by the width of its Gaussian core. An exponential was used for the background. An agreement within two standard deviations of the expected m2 value given by the fit was required. Removing candidates with dE/dxmeasured using the TPC outside of three standard deviations from the expected value of deuterons significantly reduced the background, especially in the pTregion below 2GeV/ c. The deuteron purity was estimated from integration over the signal and background components of the m2fit functions. The purity was measured in fine pTintervals and then averaged with statistical weights for the correlation measurement into five intervals, given in Table 1. The lower limit of the kinematic range was set to 1 GeV/cto reduce the contamination by secondary (knockout) deuterons from spallation in detector material to the percent level [8,9]. The purity is close to 100% for pT1.8GeV/ c. At larger pT, the background increases gradually and the purity drops to about 25% in the highest pTinterval. A mixed-event technique was applied to correct for pair efficiency effects caused by non-uniformities of the ϕacceptance. To this end, every deuteron candidate was correlated with 15 trigger particles selected from different events, which were categorized into ten event classes employing five multiplicity and two z-vertex intervals. The integral of the resulting mixed-event ϕdistribution was normalized to one. The raw ϕdistribution of deuteron candidates relative to the trigger particle is divided by the normalized mixed-event distribution, resulting in the ratio Cdeut.cand.. The rather small number of events having both the trigger particle and a deuteron candidate did not permit a further separation into intervals of rapidity. As a result, triggers and deuterons on the edge of the pseudorapidity range (|η| < 0.9) have roughly half the probability of being paired compared to those in the central region, an effect that would be corrected for with mixing in two dimensions [37]. Depending on the purity (P) for a given pTinterval, a fraction of the ϕyield arises from misidentified tracks amongst the deuteron candidates. The contribution to the yield from misidentified tracks was subtracted using ϕ-correlations obtained in the sideband regions of the m2distributions with weights from purity estimates, according to Cdeuteron(ϕ) =Cdeut.cand.(ϕ)−(1−P)Ndeut.cand. Nsideband Csideband(ϕ), (2) where Ndeut.cand./Nsideband was used to normalize the number of associated counts in the sideband region (Csideband) to that of the deuteron candidate region (Cdeut.cand.). The distribution Cdeuteron represents the correlated yield with respect to ϕbetween the 2 ALICE Collaboration Physics Letters B 819 (2021) 136440 Fig. 1. Example m2-distributions for a) low, b) intermediate and c) high pTintervals. The signal plus background fit is shown as a solid (red) line, and the extracted background as a dotted (black) line. The ±2standard deviation candidate region around the mean from the fit is shown in blue. In (a) no sideband region is visible as the purity is essentially unity. In (b) and c) the sideband regions are the shaded (orange) areas between 3–5 standard deviations on both sides of the peak. In the candidate region, the signal is depicted in light blue, while the background is shown in dark blue. The purity in the candidate region is approximately 100% in (a), 60% in (b) and 25% in (c). trigger particle and associated deuterons. The sideband selection was chosen to be between 3–4 standard deviations on both sides of the peak. A Monte Carlo simulation, where (anti-)deuterons were injected into pp events generated by PYTHIA [38]was used to determine the momentum-dependent tracking efficiency (ε) and acceptance (A). Their product strongly rises from 0.2 at pT= 1GeV/ cand levels out at about 0.55 above 1.5GeV/ c. The corrected deuteron yield per trigger particle (Ydeuteron) was then obtained from Ydeuteron(ϕ)=Cdeuteron(ϕ) Ntrig 1 ε·A,(3) in the five intervals of deuteron pT, where Ntrig is the total number of trigger particles. A correction for efficiency and acceptance of the trigger particles, which are approximately constant above 5GeV/ c, was not applied because the related corrections would cancel in the ratio. The corrected per-trigger yield distributions were obtained independently for deuterons and anti-deuterons and then added for the final results. 4. Results The per-trigger associated yield Ydeuteron versus ϕ, which represents the probability of deuterons and anti-deuterons being found within a specified pTinterval and within ϕof a high-pT(>5GeV/c) trigger hadron, is shown in Fig. 2for five deuteron pTintervals. The markers represent the data points with statistical uncertainties, while the boxes show the total systematic uncertainty. Several independent sources of uncertainty associated with tracking, particle identification, sideband correction, and purity, as well as efficiency and acceptance were included into the total systematic uncertainty. Individual sources were estimated as follows: a) the DCA cut was narrowed from 0.5 (1.0) cm in the xy-plane (z-axis) to 0.1 (0.1) cm, b) the minimum number of TPC clusters for a track was increased from 70 to 90 hits, c) the TOF particle identification requirement on the mass-squared to be within 2 standard deviations of the mean mass was relaxed to 3 standard deviations, d) the mass-squared range used to select the sidebands was changed from 3–4 standard deviations from the mean to 4–5 standard deviations, e) the TPC particle identification requirement of agreement within three standard deviations was tightened to two standard deviations, f) the purity calculation from signal and background fit functions was compared to the purity found using bin-counting for the signal and a fit for the background, and g) the mixed-event correction in ϕwas not applied. In addition, a ϕ-independent uncertainty of 5% was applied to account for deficiencies in the deuteron efficiency and acceptance corrections. Table 2 Uncertainties for each associated pTinterval. Top: Statistical uncertainty averaged over all ϕ-intervals. Middle: Contributions to systematic uncertainties for the different sources described in the text as well as the total, which is obtained from adding the individual contributions in quadrature. Bottom: Uncertainty associated with the determination of the ZYAM value. pT-range (GeV/c)1.0–1.35 1.35–1.8 1.8–2.4 2.4–3.0 3.0–4.0 Statistical unc. 15.6% 13.4% 15.4% 31.7% 57.6% Sources of sys. unc. a) DCA cut 3.6% 3.5% 2.4% 0.4% 7.6% b) TPC clu. min. 13.2% 9.7% 0.5% 0.0% 25.2% c) TOF-PID 9.2% 7.3% 17.2% 5.6% 31.8% d) Sidebands 1.9% 0.5% 14.5% 24.8% 14.3% e) TPC-PID 7.0% 2.5% 3.4% 11.2% 20.6% f) Purity det. 0.0% 0.2% 5.0% 11.1% 3.8% g) Mixing 7.7% 11.2% 9.3% 12.7% 5.3% Tracking eff. 5% 5% 5% 5% 5% Total sys. unc. 20.3% 17.8% 25.7% 32.9% 49.0% ZYAM unc. 101.0% 19.6% 3.7% 27.4% 10.5% A separate purity and track selection efficiency was estimated for each change associated with the deuteron candidate track selection. The resulting variation (i.e. p/ε×A) was found to differ by less than 10% from the baseline value obtained using the standard selection. Table 2summarizes the various systematic uncertainties for the five pTintervals. The resulting systematic uncertainties are largely point-to-point correlated in ϕ. Hence, the shape of the distributions shown in Fig. 2exhibits for all pT-intervals, except the lowest, a characteristic double-peak structure reminiscent of hard scattering, albeit sitting on a large pedestal value indicative of a large contribution of deuterons produced in the underlying event. To quantify the pertrigger associated yield of deuterons, the contribution of the uncorrelated background was estimated using the ZYAM method [28]. The ZYAM value was obtained by taking the average over the ranges π 2±π 9and 3π 2±π 9, which includes eight ϕintervals. To estimate the corresponding uncertainty, also reported in Table 2, we fit a parabola to the π 2±π 9region and use its vertex value as an alternative ZYAM estimate. The ZYAM uncertainty, constructed by these two ways, is as such subject to statistical fluctuations. The central ZYAM value along with its uncertainty are shown as a band in Fig. 2. In the lowest pT-interval the point-to-point statistical fluctuations in the data are greater in magnitude than the potential underlying trend, resulting in a large ZYAM uncertainty, which demonstrates that the separation between correlated yield and the uncorrelated background is not possible. In all other pT-intervals a pronounced jet–associated deuteron enhancement relative to the ZYAM value is visible. In Fig. 2, the data are also compared to model calculations, based on PYTHIA 8.2 (Monash) [39,40], including a coalescence af- 3 ALICE Collaboration Physics Letters B 819 (2021) 136440 Fig. 2. The per-trigger associated yield versus ϕfor charged particles with pT>5.0GeV/cand associate deuterons and anti-deuterons for different associate pTintervals: 1.0–1.35, 1.35–1.8, 1.8–2.4, 2.4–3.0, and 3.0–4.0 GeV/c. The markers represent the data points with statistical uncertainties, while the boxes represent the systematic uncertainties associated with tracking, purity, and sideband selection. The dotted line shows the ZYAM background estimate and the blue band is the uncertainty associated with the ZYAM estimate. Histogram lines are PYTHIA 8.2 (Monash) model calculations with a coalescence afterburner with p0=110 MeV/c. The calculation was scaled by 0.5and 0.75 in the first two intervals, required to approximately describe the measured deuteron spectrum at 13 TeV, as explained in the text. terburner (AB) following Ref. [29]for deuteron production, which otherwise is absent in PYTHIA. In the coalescence model, a (anti-) proton is combined with a (anti-)neutron if each of their momenta in their centre-of-mass frame is smaller than p0, the sole free parameter of the model. Using p0=110 MeV/c, the model describes the deuteron spectra in pp collisions at 7 TeV above 1.5GeV/c within uncertainties of about 10%, while it overpredicts the data by up to 50% between 1–1.5 GeV/c[9,29]. Using the same value of p0=110 MeV/c, a similar agreement is achieved for the data at 13 TeV [11]. The deviations at low pTof up to 50% originate from small differences of the level of 10–20% between the measured and calculation proton yields [41]. Since there is a large contribution from the underlying event, the calculation in Fig. 2was scaled by 0.5 and 0.75 in the lowest two intervals, to take into account the difference between the model and the data on inclusive deuteron production. The coalescence model calculation describes the data with the exception of the lowest two associated pTintervals, where it tends to overpredict the data. To extract the per-trigger correlated yield in the jet peak region, Ydeuteron above the ZYAM line is integrated within |ϕ| <0.7rad, Ynear side deuteron = +0.7  −0.7 (Ydeuteron(ϕ)−CZYAM)dϕ.(4) The per-trigger associated-deuteron integrated yield on the near side as a function of deuteron pTis presented in Fig. 3. The systematic uncertainties from the correlation measurement, which are largely correlated, and from the ZYAM determination, which are largely uncorrelated across deuteron pT, are shown separately. For every pTinterval except the first, the deuteron yield is between 2.4 and 4.8 standard deviations larger than zero (considering the quadratic sum of statistical, systematic and ZYAM uncertainties), indicating a contribution of deuterons produced in the vicinity of the trigger particle. The yield of deuterons in the jet peak relative to the production in the underlying event was estimated by 4 ALICE Collaboration Physics Letters B 819 (2021) 136440 Fig. 3. The per-trigger associated-deuteron integrated yield for trigger particles above 5GeV/con the near side versus pTof the associated deuterons and antideuterons. Vertical bars show statistical uncertainties, open boxes systematic uncertainties, and shaded (blue) boxes show the uncertainty related to the subtraction of the uncorrelated background using the ZYAM method. Square markers are calculations using PYTHIA 8.2 (Monash) with a coalescence afterburner, displaced by 30 MeV/cfor better visibility. computing the ratio of the per trigger yield to the ZYAM value multiplied by 2π. The resulting fraction of deuterons produced in the jet is about 8–15%, increasing with increasing pT, indicating that in the pTranges explored by the measurement, the majority of the deuterons are produced in the underlying event. The model calculations, integrated and corrected using ZYAM in the same way as the data, are in agreement with the data. The fore-mentioned trend of the calculation to overpredict the data in the two lowest pTintervals is still present, but not significant given the large uncertainty from the ZYAM method. 5. Conclusions Using a high-momentum particle (pT>5GeV/c) as a proxy for the presence of a jet at midrapidity, we measured the per-trigger yield of associated deuterons and anti-deuterons in five pTbins, ranging from 1 to 4GeV/cin pp collisions at √s=13 TeV. The associated yield integrated within a narrow angular range of the trigger particle is between 2.4 and 4.8 standard deviations above the uncorrelated background in every deuteron pTinterval above 1.35 GeV/c. In the region of trigger and deuteron pTprobed by our measurement, the fraction of deuterons correlated with jets are about 10% of the number in the underlying event. The data are described by PYTHIA model calculations when deuteron production via coalescence is included. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 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, Austrian Science Fund (FWF): [M 2467-N36] and Österreichische Nationalstiftung für Forschung, Technologie und Entwicklung, Austria; Ministry of Communications and High Technologies, National Nuclear Research Center, Azerbaijan; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Financiadora de Estudos e Projetos (Finep), Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and Universidade Federal do Rio Grande do Sul (UFRGS), Brazil; Ministry of Education of China (MOEC), Ministry of Science & Technology of China (MSTC) and National Natural Science Foundation of China (NSFC), China; Ministry of Science and Education and Croatian Science Foundation, Croatia; Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear (CEADEN), Cubaenergía, Cuba; Ministry of Education, Youth and Sports of the Czech Republic, Czech Republic; The Danish Council for Independent Research | Natural Sciences, the Villum Fonden and Danish National Research Foundation (DNRF), Denmark; Helsinki Institute of Physics (HIP), Finland; Commissariat à l’Énergie Atomique (CEA) and Institut National de Physique Nucléaire 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, 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 Sciences, Indonesia; Istituto Nazionale di Fisica Nucleare (INFN), Italy; Institute for Innovative Science and Technology, Nagasaki Institute of Applied Science (IIST), Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) and Japan Society for the Promotion of Science (JSPS) KAKENHI, Japan; Consejo Nacional de Ciencia (CONACYT) y Tecnología, through Fondo de Cooperación Internacional en Ciencia y Tecnología (FONCICYT) and Dirección General de Asuntos del Personal Academico (DGAPA), Mexico; Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), Netherlands; The Research Council of Norway, Norway; Commission on Science and Technology for Sustainable Development in the South (COMSATS), Pakistan; Pontificia Universidad Católica del Perú, Peru; Ministry of Science and Higher Education, 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) 5 ALICE Collaboration Physics Letters B 819 (2021) 136440 and United States Department of Energy, Office of Nuclear Physics (DOE NP), United States of America. References [1] B. Alper, et al., Large angle production of stable particles heavier than the proton and a search for quarks at the CERN intersecting storage rings, Phys. Lett. B 46 (1973) 265–268. [2] British-Scandinavian-MIT Collaboration, S. Henning, et al., Production of deuterons and anti-deuterons in proton–proton collisions at the CERN ISR, Lett. Nuovo Cimento 21 (1978) 189. [3] T. Alexopoulos, et al., Cross-sections for deuterium, tritium, and helium production in pp collisions at √s=1.8TeV, Phys. Rev. D 62 (2000) 072004. [4] H1 Collaboration, A. Aktas, et al., Measurement of anti-deuteron photoproduction and a search for heavy stable charged particles at HERA, Eur. Phys. J. C 36 (2004) 413–423, arXiv:hep -ex /0403056 [hep -ex]. [5] ZEUS Collaboration, S. Chekanov, et al., Measurement of (anti)deuteron and (anti)proton production in DIS at HERA, Nucl. Phys. B 786 (2007) 181–205, arXiv:0705 .3770 [hep -ex]. [6] CLEO Collaboration, D.M. Asner, et al., Anti-deuteron production in Upsilon(nS) decays and the nearby continuum, Phys. Rev. D 75 (2007) 012009, arXiv:hep - ex /0612019 [hep -ex]. [7] ALEPH Collaboration, S. Schael, et al., Deuteron and anti-deuteron production in e+e−collisions at the Z resonance, Phys. Lett. B 639 (2006) 192–201, arXiv: hep -ex /0604023 [hep -ex]. [8] ALICE Collaboration, J. Adam, et al., Production of light nuclei and anti-nuclei in pp and Pb–Pb collisions at energies available at the CERN Large Hadron Collider, Phys. Rev. C 93 (2) (2016) 024917, arXiv:1506 .08951 [nucl -ex]. [9] ALICE Collaboration, S. Acharya, et al., Production of deuterons, tritons, 3He nuclei and their antinuclei in pp collisions at √s=0.9, 2.76 and 7 TeV, Phys. Rev. C 97 (2) (2018) 024615, arXiv:1709 .08522 [nucl -ex]. [10] ALICE Collaboration, S. Acharya, et al., Multiplicity dependence of (anti- )deuteron production in pp collisions at √s=7TeV, Phys. Lett. B 794 (2019) 50–63, arXiv:1902 .09290 [nucl -ex]. [11] ALICE Collaboration, S. Acharya, et al., (Anti-)Deuteron production in pp collisions at √s=13 TeV, arXiv:2003 .03184 [nucl -ex]. [12] NA49 Collaboration, T. Anticic, et al., Energy and centrality dependence of deuteron and proton production in Pb–Pb collisions at relativistic energies, Phys. Rev. C 69 (2004) 024902. [13] STAR Collaboration, B. Abelev, et al., Yields and elliptic flow of d(anti-d) and He-3(anti-He-3) in Au–Au collisions at √sNN =200 GeV, arXiv:0909 .0566 [nucl -ex]. [14] ALICE Collaboration, S. Acharya, et al., Measurement of deuteron spectra and elliptic flow in Pb–Pb collisions at √sNN =2.76 TeV at the LHC, Eur. Phys. J. C 77 (10) (2017) 658, arXiv:1707.07304 [nucl -ex]. [15] ALICE Collaboration, S. Acharya, et al., Multiplicity dependence of light (anti-) nuclei production in p–Pb collisions at √sNN =5.02 TeV, Phys. Lett. B 800 (2020) 135043, arXiv:1906 .03136 [nucl -ex]. [16] R. Hagedorn, Deuteron production in high-energy collisions, Phys. Rev. Lett. 5 (1960) 276–277. [17] H. Sato, K. Yazaki, On the coalescence model for high-energy nuclear reactions, Phys. Lett. B 98 (1981) 153–157. [18] H.H. Gutbrod, A. Sandoval, P.J. Johansen, A.M. Poskanzer, J. Gosset, W.G. Meyer, G.D. Westfall, R. Stock, Final state interactions in the production of hydrogen and helium isotopes by relativistic heavy ions on uranium, Phys. Rev. Lett. 37 (1976) 667–670. [19] STAR Collaboration, H. Agakishiev, et al., Observation of the antimatter helium- 4 nucleus, Nature 473 (2011) 353, arXiv:1103 .3312 [nucl -ex], Erratum: Nature 475 (2011) 412. [20] ALICE Collaboration, S. Acharya, et al., Production of 4He and 4He in Pb–Pb collisions at √sNN =2.76 TeV at the LHC, Nucl. Phys. A 971 (2018) 1–20, arXiv: 1710 .07531 [nucl -ex]. [21] ALICE Collaboration, J. Adam, et al., 3 Hand 3 ¯ Hproduction in Pb–Pb collisions at √sNN =2.76 TeV, Phys. Lett. B 754 (2016) 360–372, arXiv:1506 .08453 [nucl - ex]. [22] ALICE Collaboration, J. Adam, et al., Search for weakly decaying nand  exotic bound states in central Pb-Pb collisions at √sNN =2.76 TeV, Phys. Lett. B 752 (2016) 267–277, arXiv:1506 .07499 [nucl -ex]. [23] M. Karliner, B.R. Webber, Coalescence model for Theta(c) pentaquark formation, J. High Energy Phys. 12 (2004) 045, arXiv:hep -ph /0409121 [hep -ph]. [24] OPAL Collaboration, R. Akers, et al., Search for heavy charged particles and for particles with anomalous charge in e+e−collisions at LEP, Z. Phys. C 67 (1995) 203–212. [25] N. Sharma, J. Cleymans, B. Hippolyte, M. Paradza, A comparison of pp, p–Pb, Pb–Pb collisions in the thermal model: multiplicity dependence of thermal parameters, Phys. Rev. C 99 (4) (2019) 044914, arXiv:1811.00399 [hep -ph]. [26] V. Vovchenko, B. Dönigus, H. Stoecker, Multiplicity dependence of light nuclei production at LHC energies in the canonical statistical model, Phys. Lett. B 785 (2018) 171–174, arXiv:1808 .05245 [hep -ph]. [27] N. Sharma, T. Perez, A. Castro, L. Kumar, C. Nattrass, Methods for separation of deuterons produced in the medium and in jets in high energy collisions, Phys. Rev. C 98 (1) (2018) 014914, arXiv:1803 .02313 [hep -ph]. [28] PHENIX Collaboration, S.S. Adler, et al., Dense-medium modifications to jetinduced hadron pair distributions in Au–Au collisions at √sNN =200 GeV, Phys. Rev. Lett. 97 (2006) 052301, arXiv:nucl -ex /0507004 [nucl -ex]. [29] ALICE Collaboration, Supplemental material: afterburner for generating light (anti-)nuclei with QCD-inspired event generators in pp collisions, https:// cds .cern .ch /record /2285500. [30] ALICE Collaboration, K. Aamodt, et al., The ALICE experiment at the CERN LHC, J. Instrum. 3 (2008) S08002. [31] ALICE Collaboration, E. Abbas, et al., Performance of the ALICE VZERO system, J. Instrum. 8 (2013) P10016, arXiv:1306 .3130 [nucl -ex]. [32] ALICE Collaboration, K. Aamodt, et al., Alignment of the ALICE Inner Tracking System with cosmic-ray tracks, J. Instrum. 5 (2010) P03003, arXiv:1001.0502 [physics .ins -det]. [33] J. Alme, et al., The ALICE TPC, a large 3-dimensional tracking device with fast readout for ultra-high multiplicity events, Nucl. Instrum. Methods A 622 (2010) 316–367, arXiv:1001.1950 [physics .ins -det]. [34] ALICE Collaboration, J. Adam, et al., Determination of the event collision time with the ALICE detector at the LHC, Eur. Phys. J. Plus 132 (2) (2017) 99, arXiv: 1610 .03055 [physics .ins -det]. [35] ALICE Collaboration, B.B. Abelev, et al., Performance of the ALICE experiment at the CERN LHC, Int. J. Mod. Phys. A 29 (2014) 1430044, arXiv:1402 .4476 [nucl - ex]. [36] ALICE Collaboration, Quarkonium signal extraction in ALICE, https://cds .cern .ch / record /2060096. [37] S. Oh, A. Morsch, C. Loizides, T. Schuster, Correction methods for finiteacceptance effects in two-particle correlation analyses, Eur. Phys. J. Plus 131 (8) (2016) 278, arXiv:1604 .05332 [nucl -th]. [38] T. Sjostrand, S. Mrenna, P.Z. Skands, PYTHIA 6.4 physics and manual, J. High Energy Phys. 05 (2006) 026, arXiv:hep -ph /0603175 [hep -ph]. [39] T. Sjöstrand, S. Ask, J.R. Christiansen, R. Corke, N. Desai, P. Ilten, S. Mrenna, S. Prestel, C.O. Rasmussen, P.Z. Skands, An introduction to PYTHIA 8.2, Comput. Phys. Commun. 191 (2015) 159–177, arXiv:1410 .3012 [hep -ph]. [40] P. Skands, S. Carrazza, J. Rojo, Tuning PYTHIA 8.1: the Monash 2013 tune, Eur. Phys. J. C 74 (8) (2014) 3024, arXiv:1404 .5630 [hep -ph]. [41] ALICE Collaboration, S. Acharya, et al., Multiplicity dependence of π, K, and p production in pp collisions at √s=13 TeV, Eur. Phys. J. C 80 (8) (2020) 693, arXiv:2003 .02394 [nucl -ex]. ALICE Collaboration S. Acharya142, D. Adamová97, A. Adler75, J. Adolfsson82, G. Aglieri Rinella35, M. Agnello31, N. Agrawal 55, Z. Ahammed142, S. Ahmad16, S.U. Ahn77, Z. Akbar52, A. Akindinov 94, M. Al-Turany 109, D.S.D. Albuquerque124, D. Aleksandrov 90, B. Alessandro60, H.M. Alfanda7, R. Alfaro Molina 72, B. Ali 16, Y. Ali 14, A. Alici26, N. Alizadehvandchali127, A. Alkin 35, J. Alme21, T. Alt 69, L. Altenkamper 21, I. Altsybeev115, M.N. Anaam7, C. Andrei49, D. Andreou92, A. Andronic145, M. Angeletti35, V. Anguelov 106, T. Antiˇ ci´ c110, F. Antinori58, P. Antonioli 55, N. Apadula 81, L. Aphecetche117, H. Appelshäuser69, S. Arcelli26, R. Arnaldi60, M. Arratia81, I.C. Arsene20, M. Arslandok147,106, A. Augustinus35, R. Averbeck109, S. Aziz 79, M.D. Azmi16, A. Badalà57, Y.W. Baek 42, X. Bai 109, R. Bailhache69, R. Bala 103, A. Balbino 31, A. Baldisseri139, M. Ball44, D. Banerjee4, R. Barbera27, L. Barioglio25, M. Barlou 86, G.G. Barnaföldi 146, L.S. Barnby96, V. Barret136, C. Bartels129, K. Barth35, 6 ALICE Collaboration Physics Letters B 819 (2021) 136440 E. Bartsch69, F. Baruffaldi 28, N. Bastid136, S. Basu82,144, G. Batigne117, B. Batyunya76, D. Bauri50, J.L. Bazo Alba114, I.G. Bearden 91, C. Beattie 147, I. Belikov 138, A.D.C. Bell Hechavarria145, F. Bellini 35, R. Bellwied 127, S. Belokurova115, V. Belyaev95, G. Bencedi70,146, S. Beole25, A. Bercuci49, Y. Berdnikov 100, A. Berdnikova106, D. Berenyi146, L. Bergmann106, M.G. Besoiu68, L. Betev 35, P.P. Bhaduri 142, A. Bhasin103, I.R. Bhat103, M.A. Bhat4, B. Bhattacharjee43, P. Bhattacharya23, A. Bianchi25, L. Bianchi25, N. Bianchi53, J. Bielˇ cík38, J. Bielˇ cíková97, A. Bilandzic107, G. Biro146, S. Biswas4, J.T. Blair 121, D. Blau90, M.B. Blidaru109, C. Blume69, G. Boca 29, F. Bock 98, A. Bogdanov95, S. Boi23, J. Bok62, L. Boldizsár146, A. Bolozdynya95, M. Bombara39, G. Bonomi141, H. Borel139, A. Borissov83,95, H. Bossi147, E. Botta25, L. Bratrud69, P. Braun-Munzinger109, M. Bregant123, M. Broz38, G.E. Bruno108,34, M.D. Buckland 129, D. Budnikov 111, H. Buesching69, S. Bufalino31, O. Bugnon117, P. Buhler 116, P. Buncic 35, Z. Buthelezi73,133, J.B. Butt 14, S.A. Bysiak120, D. Caffarri92, A. Caliva109, E. Calvo Villar114, J.M.M. Camacho122, R.S. Camacho46, P. Camerini24, F.D.M. Canedo 123, A.A. Capon116, F. Carnesecchi26, R. Caron139, J. Castillo Castellanos139, E.A.R. Casula56, F. Catalano 31, C. Ceballos Sanchez76, P. Chakraborty 50, S. Chandra 142, W. Chang 7, S. Chapeland35, M. Chartier129, S. Chattopadhyay142, S. Chattopadhyay112, A. Chauvin23, C. Cheshkov137, B. Cheynis137, V. Chibante Barroso 35, D.D. Chinellato124, S. Cho 62, P. Chochula 35, P. Christakoglou92, C.H. Christensen91, P. Christiansen82, T. Chujo 135, C. Cicalo 56, L. Cifarelli26, F. Cindolo 55, M.R. Ciupek109, G. Clai55,II, J. Cleymans126, F. Colamaria 54, J.S. Colburn 113, D. Colella54, A. Collu 81, M. Colocci35,26, M. Concas60,III, G. Conesa Balbastre80, Z. Conesa del Valle 79, G. Contin24, J.G. Contreras38, T.M. Cormier98, P. Cortese 32, M.R. Cosentino125, F. Costa 35, S. Costanza29, P. Crochet 136, E. Cuautle70, P. Cui 7, L. Cunqueiro98, T. Dahms 107, A. Dainese 58, F.P.A. Damas 117,139, M.C. Danisch106, A. Danu68, D. Das112, I. Das112, P. Das 88, P. Das 4, S. Das 4, S. Dash 50, S. De88, A. De Caro30, G. de Cataldo 54, L. De Cilladi25, J. de Cuveland40, A. De Falco23, D. De Gruttola30, N. De Marco60, C. De Martin24, S. De Pasquale30, S. Deb51, H.F. Degenhardt123, K.R. Deja143, S. Delsanto25, W. Deng 7, P. Dhankher 19,50, D. Di Bari34, A. Di Mauro35, R.A. Diaz8, T. Dietel 126, P. Dillenseger69, Y. Ding 7, R. Divià35, D.U. Dixit 19, Ø. Djuvsland21, U. Dmitrieva 64, J. Do62, A. Dobrin68, B. Dönigus69, O. Dordic20, A.K. Dubey142, A. Dubla109,92, S. Dudi102, M. Dukhishyam88, P. Dupieux136, T.M. Eder 145, R.J. Ehlers98, V.N. Eikeland21, D. Elia54, B. Erazmus 117, F. Erhardt 101, A. Erokhin115, M.R. Ersdal21, B. Espagnon 79, G. Eulisse35, D. Evans113, S. Evdokimov93, L. Fabbietti107, M. Faggin28, J. Faivre80, F. Fan 7, A. Fantoni53, M. Fasel 98, P. Fecchio 31, A. Feliciello60, G. Feofilov 115, A. Fernández Téllez46, A. Ferrero139, A. Ferretti25, A. Festanti35, V.J.G. Feuillard106, J. Figiel120, S. Filchagin111, D. Finogeev 64, F.M. Fionda 21, G. Fiorenza54, F. Flor127, A.N. Flores121, S. Foertsch73, P. Foka 109, S. Fokin90, E. Fragiacomo61, U. Fuchs 35, C. Furget80, A. Furs64, M. Fusco Girard30, J.J. Gaardhøje91, M. Gagliardi 25, A.M. Gago114, A. Gal138, C.D. Galvan 122, P. Ganoti 86, C. Garabatos109, J.R.A. Garcia46, E. Garcia-Solis10, K. Garg117, C. Gargiulo35, A. Garibli89, K. Garner145, P. Gasik 107, E.F. Gauger 121, M.B. Gay Ducati71, M. Germain 117, J. Ghosh112, P. Ghosh142, S.K. Ghosh4, M. Giacalone26, P. Gianotti53, P. Giubellino109,60, P. Giubilato28, A.M.C. Glaenzer139, P. Glässel106, V. Gonzalez 144, L.H. González-Trueba72, S. Gorbunov40, L. Görlich 120, S. Gotovac36, V. Grabski72, L.K. Graczykowski 143, K.L. Graham113, L. Greiner81, A. Grelli63, C. Grigoras35, V. Grigoriev95, A. Grigoryan1,I, S. Grigoryan76, O.S. Groettvik21, F. Grosa60, J.F. Grosse-Oetringhaus35, R. Grosso109, R. Guernane80, M. Guilbaud117, M. Guittiere117, K. Gulbrandsen91, T. Gunji134, A. Gupta103, R. Gupta103, I.B. Guzman 46, R. Haake147, M.K. Habib109, C. Hadjidakis 79, H. Hamagaki84, G. Hamar146, M. Hamid7, R. Hannigan121, M.R. Haque 143,88, A. Harlenderova109, J.W. Harris147, A. Harton10, J.A. Hasenbichler35, H. Hassan98, D. Hatzifotiadou55, P. Hauer44, L.B. Havener147, S. Hayashi134, S.T. Heckel107, E. Hellbär69, H. Helstrup37, T. Herman 38, E.G. Hernandez46, G. Herrera Corral 9, F. Herrmann 145, K.F. Hetland37, H. Hillemanns35, C. Hills 129, B. Hippolyte138, B. Hohlweger107, J. Honermann145, G.H. Hong 148, D. Horak38, S. Hornung109, R. Hosokawa15, P. Hristov35, C. Huang79, C. Hughes132, P. Huhn 69, T.J. Humanic 99, H. Hushnud112, L.A. Husova 145, N. Hussain43, D. Hutter 40, J.P. Iddon35,129, R. Ilkaev111, H. Ilyas14, M. Inaba135, G.M. Innocenti35, M. Ippolitov90, A. Isakov38,97, M.S. Islam 112, M. Ivanov109, V. Ivanov100, V. Izucheev93, B. Jacak81, N. Jacazio35,55, P.M. Jacobs81, S. Jadlovska 119, J. Jadlovsky 119, S. Jaelani63, C. Jahnke123, M.J. Jakubowska143, M.A. Janik143, T. Janson75, M. Jercic 101, O. Jevons113, M. Jin 127, F. Jonas 98,145, P.G. Jones113, J. Jung 69, M. Jung69, A. Jusko113, P. Kalinak 65, A. Kalweit35, V. Kaplin95, S. Kar7, A. Karasu Uysal78, D. Karatovic101, O. Karavichev64, T. Karavicheva64, P. Karczmarczyk 143, 7 ALICE Collaboration Physics Letters B 819 (2021) 136440 E. Karpechev 64, A. Kazantsev90, U. Kebschull 75, R. Keidel 48, M. Keil35, B. Ketzer44, Z. Khabanova92, A.M. Khan7, S. Khan16, A. Khanzadeev100, Y. Kharlov 93, A. Khatun16, A. Khuntia120, B. Kileng37, B. Kim62, D. Kim148, D.J. Kim128, E.J. Kim74, H. Kim 17, J. Kim 148, J.S. Kim42, J. Kim106, J. Kim148, J. Kim74, M. Kim106, S. Kim18, T. Kim 148, T. Kim 148, S. Kirsch69, I. Kisel40, S. Kiselev94, A. Kisiel143, J.L. Klay6, J. Klein 35,60, S. Klein81, C. Klein-Bösing145, M. Kleiner69, T. Klemenz107, A. Kluge35, A.G. Knospe127, C. Kobdaj 118, M.K. Köhler 106, T. Kollegger109, A. Kondratyev76, N. Kondratyeva 95, E. Kondratyuk93, J. Konig69, S.A. Konigstorfer107, P.J. Konopka 2,35, G. Kornakov 143, S.D. Koryciak2, L. Koska119, O. Kovalenko87, V. Kovalenko115, M. Kowalski120, I. Králik65, A. Kravˇ cáková39, L. Kreis109, M. Krivda 113,65, F. Krizek 97, K. Krizkova Gajdosova38, M. Kroesen 106, M. Krüger69, E. Kryshen100, M. Krzewicki 40, V. Kuˇ cera35, C. Kuhn138, P.G. Kuijer 92, T. Kumaoka 135, L. Kumar102, S. Kundu88, P. Kurashvili87, A. Kurepin64, A.B. Kurepin64, A. Kuryakin111, S. Kushpil97, J. Kvapil 113, M.J. Kweon62, J.Y. Kwon62, Y. Kwon 148, S.L. La Pointe40, P. La Rocca27, Y.S. Lai 81, A. Lakrathok118, M. Lamanna35, R. Langoy131, K. Lapidus35, P. Larionov 53, E. Laudi 35, L. Lautner35, R. Lavicka38, T. Lazareva115, R. Lea24, J. Lee135, S. Lee148, J. Lehrbach40, R.C. Lemmon96, I. León Monzón122, E.D. Lesser19, M. Lettrich35, P. Lévai 146, X. Li11, X.L. Li7, J. Lien131, R. Lietava 113, B. Lim 17, S.H. Lim17, V. Lindenstruth40, A. Lindner49, C. Lippmann109, A. Liu19, J. Liu129, I.M. Lofnes21, V. Loginov 95, C. Loizides98, P. Loncar 36, J.A. Lopez106, X. Lopez136, E. López Torres8, J.R. Luhder145, M. Lunardon28, G. Luparello61, Y.G. Ma 41, A. Maevskaya64, M. Mager35, S.M. Mahmood20, T. Mahmoud44, A. Maire138, R.D. Majka147,I, M. Malaev100, Q.W. Malik20, L. Malinina76,IV, D. Mal’Kevich94, N. Mallick 51, P. Malzacher109, G. Mandaglio33,57, V. Manko90, F. Manso 136, V. Manzari54, Y. Mao 7, M. Marchisone137, J. Mareš67, G.V. Margagliotti24, A. Margotti55, A. Marín109, C. Markert121, M. Marquard69, N.A. Martin 106, P. Martinengo35, J.L. Martinez127, M.I. Martínez46, G. Martínez García117, S. Masciocchi109, M. Masera25, A. Masoni56, L. Massacrier79, A. Mastroserio140,54, A.M. Mathis107, O. Matonoha82, P.F.T. Matuoka123, A. Matyja120, C. Mayer120, F. Mazzaschi25, M. Mazzilli54, M.A. Mazzoni59, A.F. Mechler69, F. Meddi 22, Y. Melikyan 64, A. Menchaca-Rocha72, C. Mengke 7, E. Meninno 116,30, A.S. Menon127, M. Meres13, S. Mhlanga 126, Y. Miake135, L. Micheletti25, L.C. Migliorin 137, D.L. Mihaylov107, K. Mikhaylov76,94, A.N. Mishra 146,70, D. Mi´ skowiec109, A. Modak4, N. Mohammadi35, A.P. Mohanty63, B. Mohanty 88, M. Mohisin Khan 16, Z. Moravcova 91, C. Mordasini107, D.A. Moreira De Godoy145, L.A.P. Moreno46, I. Morozov64, A. Morsch35, T. Mrnjavac35, V. Muccifora53, E. Mudnic36, D. Mühlheim145, S. Muhuri 142, J.D. Mulligan81, A. Mulliri 23,56, M.G. Munhoz123, R.H. Munzer69, H. Murakami 134, S. Murray 126, L. Musa35, J. Musinsky65, C.J. Myers127, J.W. Myrcha 143, B. Naik 50, R. Nair 87, B.K. Nandi50, R. Nania55, E. Nappi54, M.U. Naru14, A.F. Nassirpour82, C. Nattrass132, R. Nayak50, S. Nazarenko 111, A. Neagu20, L. Nellen70, S.V. Nesbo 37, G. Neskovic40, D. Nesterov115, B.S. Nielsen 91, S. Nikolaev90, S. Nikulin90, V. Nikulin100, F. Noferini55, S. Noh12, P. Nomokonov 76, J. Norman129, N. Novitzky135, P. Nowakowski 143, A. Nyanin90, J. Nystrand21, M. Ogino84, A. Ohlson 82, J. Oleniacz 143, A.C. Oliveira Da Silva132, M.H. Oliver147, B.S. Onnerstad128, C. Oppedisano 60, A. Ortiz Velasquez70, T. Osako 47, A. Oskarsson82, J. Otwinowski120, K. Oyama84, Y. Pachmayer 106, S. Padhan50, D. Pagano141, G. Pai´ c70, J. Pan144, S. Panebianco139, P. Pareek 142, J. Park 62, J.E. Parkkila 128, S. Parmar102, S.P. Pathak127, B. Paul 23, J. Pazzini141, H. Pei7, T. Peitzmann63, X. Peng7, L.G. Pereira71, H. Pereira Da Costa139, D. Peresunko90, G.M. Perez8, S. Perrin139, Y. Pestov 5, V. Petrᡠcek38, M. Petrovici49, R.P. Pezzi 71, S. Piano61, M. Pikna13, P. Pillot 117, O. Pinazza55,35, L. Pinsky127, C. Pinto 27, S. Pisano53, M. Płosko´ n81, M. Planinic101, F. Pliquett 69, M.G. Poghosyan 98, B. Polichtchouk93, N. Poljak101, A. Pop49, S. Porteboeuf-Houssais136, J. Porter81, V. Pozdniakov76, S.K. Prasad4, R. Preghenella55, F. Prino60, C.A. Pruneau144, I. Pshenichnov64, M. Puccio 35, S. Qiu92, L. Quaglia25, R.E. Quishpe127, S. Ragoni113, J. Rak 128, A. Rakotozafindrabe139, L. Ramello 32, F. Rami 138, S.A.R. Ramirez46, A.G.T. Ramos34, R. Raniwala104, S. Raniwala104, S.S. Räsänen45, R. Rath51, I. Ravasenga92, K.F. Read98,132, A.R. Redelbach40, K. Redlich87,V, A. Rehman21, P. Reichelt 69, F. Reidt 35, R. Renfordt69, Z. Rescakova39, K. Reygers106, A. Riabov100, V. Riabov100, T. Richert82,91, M. Richter20, P. Riedler 35, W. Riegler35, F. Riggi 27, C. Ristea68, S.P. Rode 51, M. Rodríguez Cahuantzi46, K. Røed20, R. Rogalev93, E. Rogochaya76, T.S. Rogoschinski69, D. Rohr35, D. Röhrich21, P.F. Rojas 46, P.S. Rokita 143, F. Ronchetti53, A. Rosano33,57, E.D. Rosas70, A. Rossi58, A. Rotondi29, A. Roy51, P. Roy 112, O.V. Rueda82, R. Rui 24, B. Rumyantsev76, A. Rustamov89, E. Ryabinkin90, Y. Ryabov 100, A. Rybicki120, H. Rytkonen128, O.A.M. Saarimaki45, R. Sadek117, S. Sadovsky93, J. Saetre21, K. Šafaˇ rík38, S.K. Saha142, S. Saha 88, 8