Minimum Bias Events Research Articles

Multiplicity dependence of charged-particle intra-jet properties in pp collisions at s = 13 TeV

The first measurement of the multiplicity dependence of intra-jet properties of leading charged-particle jets in proton–proton (pp) collisions is reported. The mean charged-particle multiplicity and jet fragmentation distributions are measured in minimum-bias and high-multiplicity pp collisions at center-of-mass energy s = 13 TeV using the ALICE detector. Jets are reconstructed from charged particles produced in the midrapidity region (|η|<0.9) using the sequential recombination anti-kT algorithm with jet resolution parameters R = 0.2, 0.3, and 0.4 for the transverse momentum (pT) interval 5–110 GeV/c. The high-multiplicity events are selected by the forward V0 scintillator detectors. The mean charged-particle multiplicity inside the leading jet cone rises monotonically with increasing jet pT in qualitative agreement with previous measurements at lower energies. The distributions of jet fragmentation function variables zch and ξch are measured for different jet-pT intervals. Jet-pT independent fragmentation of leading jets is observed for wider jets except at high- and low-zch values. The observed “hump-backed plateau” structure in the ξch distribution indicates suppression of low-pT particles. In high-multiplicity events, an enhancement of the fragmentation probability of low-zch particles accompanied by a suppression of high-zch particles is observed compared to minimum-bias events. This behavior becomes more prominent for low-pT jets with larger jet radius. The results are compared with predictions of QCD-inspired event generators, PYTHIA 8 with Monash 2013 tune and EPOS LHC. It is found that PYTHIA 8 qualitatively reproduces the jet modification in high-multiplicity events except at high jet pT. These measurements provide important constraints to models of jet fragmentation.

Tracking performances of the ePIC detector at the Electron-Ion Collider

The ePIC (electron–Proton/Ion Collider) experiment is a future facility at the Electron-Ion Collider (EIC) complex, located at the Brookhaven National Laboratory, USA. It will use ∼70% longitudinally polarized beam of electrons, protons, and light ions to study their collisions to understand the properties of the quarks, gluons, and the strong force responsible for the formation of the nucleus. The layout of the central detector of the ePIC experiment is not symmetric along the beams axis consisting of barrel, forward, and backward detectors to achieve a wide pseudorapidity (|η|< 3.5) coverage. There are further far-forward and far-backward tracking detectors to measure the luminosity and reconstruct the particles and fragments for the study of the exclusive deep-inelastic scattering (DIS) processes. The experiment has a challenging environment due to the presence of the background radiations (synchrotron radiation, beam-gas interactions, minimum-bias events, etc.) which will produce additional background hits on the tracker. The synchrotron radiation is suppressed to some extent by coating the beampipe with a 5μm gold layer. The experiment uses state-of-the-art bent wafer-scale silicon monolithic active pixel sensors (MAPS) with a ∼5μs acquisition window, micro-pattern gas detector (MPGD) with a good time resolution (∼20–30ns), and time-of-flight detectors based on AC-LGAD sensors (time resolution ∼30ps). The timing information of each detector will play a crucial role in track finding and rejecting the background hits utilizing the 4-dimensional tracking (space, time) to ensure the excellent performance of the experiment. The article presents the expected tracking performance of the ePIC detector using the modular ePIC software stack for simulation, reconstruction, and analysis. The Geant4 toolkit is employed for full detector simulations, alongside DD4hep (Detector Description for High Energy Physics) for geometry definition and exchange. The reconstruction incorporates the JANA2 framework, in addition to the tracking and vertexing algorithms inherited from A Common Tracking Software (ACTS).

Search for jet quenching effects in high-multiplicity pp collisions at s\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\sqrt{s} $$\\end{document} = 13 TeV via di-jet acoplanarity

The ALICE Collaboration reports a search for jet quenching effects in high-multiplicity (HM) proton-proton collisions at s\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\sqrt{s} $$\\end{document} = 13 TeV, using the semi-inclusive azimuthal-difference distribution ∆φ of charged-particle jets recoiling from a high transverse momentum (high-pT,trig) trigger hadron. Jet quenching may broaden the ∆φ distribution measured in HM events compared to that in minimum bias (MB) events. The measurement employs a pT,trig-differential observable for data-driven suppression of the contribution of multiple partonic interactions, which is the dominant background. While azimuthal broadening is indeed observed in HM compared to MB events, similar broadening for HM events is observed for simulations based on the PYTHIA 8 Monte Carlo generator, which does not incorporate jet quenching. Detailed analysis of these data and simulations show that the azimuthal broadening is due to bias of the HM selection towards events with multiple jets in the final state. The identification of this bias has implications for all jet quenching searches where selection is made on the event activity.

Two-particle Bose-Einstein correlations and their Lévy parameters in PbPb collisions at sNN=5.02 TeV

Two-particle Bose–Einstein momentum correlation functions are studied for charged-hadron pairs in lead-lead collisions at a center-of-mass energy per nucleon pair of sNN=5.02TeV. The data sample, containing 4.27×109 minimum bias events corresponding to an integrated luminosity of 0.607 nb−1, was collected by the CMS experiment in 2018. The experimental results are discussed in terms of a Lévy-type source distribution. The parameters of this distribution are extracted as functions of particle pair average transverse mass and collision centrality. These parameters include the Lévy index or shape parameter α, the Lévy scale parameter R, and the correlation strength parameter λ. The source shape, characterized by α, is found to be neither Cauchy nor Gaussian, implying the need for a full Lévy analysis. Similarly to what was previously found for systems characterized by Gaussian source radii, a hydrodynamical scaling is observed for the Lévy R parameter. The λ parameter is studied in terms of the core-halo model. ©2024 CERN, for the CMS Collaboration 2024 CERN

RootInteractive tool for multidimensional statistical analysis, machine learning and analytical model validation

The ALICE experiment [1] at CERN’s LHC is specifically designed for investigating heavy ion collisions. The upgraded ALICE accommodates a tenfold increase in Pb–Pb luminosity and a two-order-of-magnitude surge in minimum bias events. To address the challenges of high detector occupancy and event pile-ups, advanced multidimensional data analysis techniques, including machine learning (ML), are indispensable. Despite ML’s popularity, the complexity of its models presents interpretation challenges, and oversimplification in analysis often leads to inaccuracies. Our objective was to develop RootInteractive, a tool for multidimensional statistical analysis. This tool simplifies data analysis across dimensions, visualizes functions with uncertainties, and validates assumptions and approximations. In RootInteractive, it is crucial to easily define the functional composition of analytical parametric and non-parametric functions, exploit symmetries, and define multidimensional "invariant" functions and corresponding alarms. RootInteractive [2] adopts a declarative programming paradigm, ensuring userfriendliness for experts, students, and educators. It facilitates interactive visualization, n-dimensional histogramming/projection, and information extraction on both Python/C++ server and Javascript client. The tool supports client/server applications in Jupyter or standalone client-side applications. Through data compression, datasets with O(107) entries and O(25) attributes can be interactively analyzed in a browser with O(0.500-1 GB) size. Representative downsampling and reweighting/pre-aggregation enable the effective analysis of one year of ALICE data for various purposes.

Jet modification in absence of QGP-medium: the role of multiparton interactions and color reconnection* *D. Banerjee acknowledges the Inspire Fellowship research grant (DST/INSPIRE Fellowship/2018/IF180285)

Recent studies on high-multiplicity events in small collision systems (proton-proton and proton-lead) have drawn considerable research interest toward the possibility of the formation of partonic medium in such systems. One of the important consequences of the formation of dense partonic medium is the quenching of high-momentum final-state particles, resulting in several experimental observations such as suppression in nuclear modification factor , modification of jet shape observable and jet fragmentation ( ) distributions, etc. In this work, we study and for inclusive charged-particle jets in proton-proton (pp) collisions at = 13 TeV using the PYTHIA 8 Monash 2013 Monte Carlo simulation. We show that the color reconnection (CR) and multiparton interaction (MPI) mechanisms in PYTHIA 8 can lead to an increased rate of jet production. We also find that the mechanisms of MPI and CR and change in the gluonic contribution in high-multiplicity events result in significant modification of and compared to those in minimum bias events for 10 20 GeV/c. We notice a direct connection of and gluonic contribution with the amount of modification in : the larger the number of MPIs and/or gluonic contribution, the larger the amount of modification of .

Deep learning predicted elliptic flow of identified particles in heavy-ion collisions at the RHIC and LHC energies

Recent developments on a deep learning feed-forward network for estimating elliptic flow ($v_2$) coefficients in heavy-ion collisions have shown us the prediction power of this technique. The success of the model is mainly the estimation of $v_2$ from final state particle kinematic information and learning the centrality and the transverse momentum ($p_{\rm T}$) dependence of $v_2$. The deep learning model is trained with Pb-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV minimum bias events simulated with a multiphase transport model (AMPT). We extend this work to estimate $v_2$ for light-flavor identified particles such as $\pi^{\pm}$, $\rm K^{\pm}$, and $\rm p+\bar{p}$ in heavy-ion collisions at RHIC and LHC energies. The number of constituent quark (NCQ) scaling is also shown. The evolution of $p_{\rm T}$-crossing point of $v_2(p_{\rm T})$, depicting a change in meson-baryon elliptic flow at intermediate-$p_{\rm T}$, is studied for various collision systems and energies. The model is further evaluated by training it for different $p_{\rm T}$ regions. These results are compared with the available experimental data wherever possible.

Search for fractality and phase transition in p–p collisions at LHC energy

In this paper, a detailed study of the multiplicities of charged particles produced in [Formula: see text]–[Formula: see text] collisions, at [Formula: see text][Formula: see text]TeV, has been carried out. Analysis of UrQMD generated events along pseudo–rapidity ([Formula: see text]), azimuthal angle ([Formula: see text]) and [Formula: see text]-[Formula: see text] phase spaces is made with the help of scaled factorial moment method. The results have also been compared with the UrQMD events with finite impact parameter ([Formula: see text]) and minimum bias (MB) conditions. From the intermittency exponent ([Formula: see text]), the anomalous fractal dimension [Formula: see text] is derived and the variations of [Formula: see text] with order [Formula: see text] are investigated. The observed intermittent fluctuations are manifested by various parameters such as anomalous fractal dimension [Formula: see text], degree of multifractality ([Formula: see text]), critical exponent ([Formula: see text]), Levy index ([Formula: see text]) and multifractal specific heat. In the framework of Ginzburg–Landau theory, the second-order phase transition in the light of scaled factorial moment method has also been carried out to search for the quark-hadron phase transition. It is observed that the intermittent type of fluctuations are strong enough in [Formula: see text]-[Formula: see text] space compared to the one-dimensional [Formula: see text] space and [Formula: see text] space. The data reflects the signature of multifractality in [Formula: see text] space and [Formula: see text]-[Formula: see text] space. Whereas in case of [Formula: see text] space, it shows the evidence of monofractality. It is also interesting to note that the values of critical exponents for all impact parameters indicate the apparent existence of quark hadron phase transition except for MB events. However, no such behaviour is observed in [Formula: see text] space. From the knowledge of generalized fractal dimension [Formula: see text], multifractal specific heat is derived from scale factorial moment analysis in case of one-dimensional [Formula: see text] space, [Formula: see text] space and two-dimensional [Formula: see text]-[Formula: see text] space.

The upgraded ALICE TPC

A large Time Projection Chamber (TPC) is the main device for tracking and particle identification in the ALICE experiment at the Large Hadron Collider (LHC) at CERN. In the upcoming Run 3, the LHC will deliver lead beams colliding at an interaction rate of up to 50kHz. In order to read out all minimum bias events in Pb–Pb collisions, the TPC was upgraded with an amplification stage based on Gas Electron Multipliers (GEM) and new front-end electronics. With the new amplification stage, a trigger-less operation of the TPC becomes possible, resulting in a continuous readout without dead time.The exchange of the readout chambers and front-end electronics took place in a dedicated clean room in 2019/20. The upgraded TPC was then moved back to its designated position at the interaction point 2 of the LHC and an extensive commissioning programme was carried out. It includes, inter alia, noise studies, measurements of laser tracks, irradiation of the TPC with an intense X-ray source, the flushing of radioactive 83mKr into the active volume and the operation during the first proton–proton collisions provided by the LHC. During these measurements, the TPC operated at nominal conditions and the continuous readout capability was tested successfully.

Estimating elliptic flow coefficient in heavy ion collisions using deep learning

Machine learning techniques have been employed for the high energy physics community since the early 80s to deal with a broad spectrum of problems. This work explores the prospects of using deep learning techniques to estimate elliptic flow (${v}_{2}$) in heavy-ion collisions at the RHIC and LHC energies. A novel method is developed to process the input observables from particle kinematic information. The proposed deep neural network (DNN) model is trained with Pb-Pb collisions at $\sqrt{{s}_{\mathrm{NN}}}=5.02\text{ }\text{ }\mathrm{TeV}$ minimum bias events simulated with a multiphase transport model. The predictions from the machine learning technique are compared to both simulation and experiment. The deep learning model seems to preserve the centrality and energy dependence of ${v}_{2}$ for the LHC and RHIC energies. The DNN model is also quite successful in predicting the ${p}_{\mathrm{T}}$ dependence of ${v}_{2}$. When subjected to event simulation with additional noise, the proposed DNN model still keeps the robustness and prediction accuracy intact up to a reasonable extent.

Production of Λ and [formula omitted] in jets in p–Pb collisions at [formula omitted] TeV and pp collisions at [formula omitted] TeV

The production of Λ baryons and KS0 mesons (V0 particles) was measured in p–Pb collisions at sNN=5.02 TeV and pp collisions at s=7 TeV with ALICE at the LHC. The production of these strange particles is studied separately for particles associated with hard scatterings and the underlying event to shed light on the baryon-to-meson ratio enhancement observed at intermediate transverse momentum (pT) in high multiplicity pp and p–Pb collisions. Hard scatterings are selected on an event-by-event basis with jets reconstructed with the anti-kT algorithm using charged particles. The production of strange particles associated with jets pT,jetch>10 and pT,jetch>20 GeV/c in p–Pb collisions, and with jet pT,jetch>10 GeV/c in pp collisions is reported as a function of pT. Its dependence on angular distance from the jet axis, R(V0,jet), for jets with pT,jetch>10 GeV/c in p–Pb collisions is reported as well. The pT-differential production spectra of strange particles associated with jets are found to be harder compared to that in the underlying event and both differ from the inclusive measurements. In events containing a jet, the density of the V0 particles in the underlying event is found to be larger than the density in the minimum bias events. The Λ/KS0 ratio associated with jets in p–Pb collisions is consistent with the ratio in pp collisions and follows the expectation of jets fragmenting in vacuum. On the other hand, this ratio within jets is consistently lower than the one obtained in the underlying event and it does not show the characteristic enhancement of baryons at intermediate pT often referred to as “baryon anomaly” in the inclusive measurements.

Implementation of ACTS into sPHENIX Track Reconstruction

sPHENIX is a high energy nuclear physics experiment under construction at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory (BNL). The primary physics goals of sPHENIX are to study the quark-gluon-plasma, as well as the partonic structure of protons and nuclei, by measuring jets, their substructure, and heavy flavor hadrons in p+p, p + Au, and Au + Au collisions. sPHENIX will collect approximately 300 PB of data over three run periods, to be analyzed using available computing resources at BNL; thus, performing track reconstruction in a timely manner is a challenge due to the high occupancy of heavy ion collision events. The sPHENIX experiment has recently implemented the A Common Tracking Software (ACTS) track reconstruction toolkit with the goal of reconstructing tracks with high efficiency and within a computational budget of 5 s per minimum bias event. This paper reports the performance status of ACTS as the default track fitting tool within sPHENIX, including discussion of the first implementation of a time projection chamber geometry within ACTS.

A large-N expansion for minimum bias

Despite being the overwhelming majority of events produced in hadron or heavy ion collisions, minimum bias events do not enjoy a robust first-principles theoretical description as their dynamics are dominated by low-energy quantum chromodynamics. In this paper, we present a novel expansion scheme of the cross section for minimum bias events that exploits an ergodic hypothesis for particles in the events and events in an ensemble of data. We identify power counting rules and symmetries of minimum bias from which the form of the squared matrix element can be expanded in symmetric polynomials of the phase space coordinates. This expansion is entirely defined in terms of observable quantities, in contrast to models of heavy ion collisions that rely on unmeasurable quantities like the number of nucleons participating in the collision, or tunes of parton shower parameters to describe the underlying event in proton collisions. The expansion parameter that we identify from our power counting is the number of detected particles N and as N → ∞ the variance of the squared matrix element about its mean, constant value on phase space vanishes. With this expansion, we show that the transverse momentum distribution of particles takes a universal form that only depends on a single parameter, has a fractional dispersion relation, and agrees with data in its realm of validity. We show that the constraint of positivity of the squared matrix element requires that all azimuthal correlations vanish in the N → ∞ limit at fixed center-of-mass energy, as observed in data. The approach we follow allows for a unified treatment of small and large system collective behavior, being equally applicable to describe, e.g., elliptic flow in PbPb collisions and the “ridge” in pp collisions. We also briefly comment on power counting and symmetries for minimum bias events in other collider environments and show that a possible ridge in e+e− collisions is highly suppressed as a consequence of its symmetries.

Mathrm {K_S}^{0}- and (anti-)Lambda -hadron correlations in pp collisions at\xa0{sqrt{s}} = 13\xa0TeV

Two-particle Azimuthal correlations are measured with the ALICE apparatus in pp collisions at sqrt{s} = 13 TeV to explore strangeness- and multiplicity-related effects in the fragmentation of jets and the transition regime between bulk and hard production, probed with the condition that a strange meson (mathrm {K_S}^{0}) or baryon (Lambda ) with transverse momentum p_{mathrm T} >3 GeV/c is produced. Azimuthal correlations between kaons or Lambda hyperons with other hadrons are presented at midrapidity for a broad range of the trigger (3< p_mathrm {T}^mathrm {trigg} < 20 GeV/c) and associated particle p_{mathrm T} (1 GeV/c< p_mathrm {T}^mathrm {assoc} < p_mathrm {T}^mathrm {trigg} ), for minimum-bias events and as a function of the event multiplicity. The near- and away-side peak yields are compared for the case of either mathrm {K_S}^{0} or Lambda ({overline{Lambda }}) being the trigger particle with that of inclusive hadrons (a sample dominated by pions). In addition, the measurements are compared with predictions from PYTHIA 8 and EPOS LHC event generators.

Analysis of heavy-flavour particles in ALICE with the O2 analysis framework

Precise measurements of heavy-flavour hadrons down to very low pT represent the core of the physics program of the upgraded ALICE experiment in Run 3 [1]. These physics probes are characterised by a very small signal-to-background ratio requiring very large statistics of minimum-bias events. In Run 3, ALICE is expected to collect up to 13 nb−1 of lead–lead collisions, corresponding to about 1 × 1011 minimum-bias events. In order to analyse this unprecedented amount of data, which is about 100 times larger than the statistics collected in Run 1 and Run 2, the ALICE collaboration is developing a complex analysis framework that aims at maximising the processing speed and data volume reduction [2]. In this paper, the strategy of reconstruction, selection, skimming, and analysis of heavy-flavour events for Run 3 will be presented. Some preliminary results on the reconstruction of charm mesons and baryons will be shown and the prospects for future developments and optimisation discussed.

Further studies on the physics potential of an experiment using LHC neutrinos

We discuss an experiment to investigate neutrino physics at the LHC, with emphasis on tau flavour. As described in our previous paper Beni et al (2019 J. Phys. G: Nucl. Part. Phys. 46 115008), the detector can be installed in the decommissioned TI18 tunnel, ≈480 m downstream the ATLAS cavern, after the first bending dipoles of the LHC arc. The detector intercepts the intense neutrino flux, generated by the LHC beams colliding in IP1, at large pseudorapidity η, where neutrino energies can exceed a TeV. This paper focuses on exploring the neutrino pseudorapity versus energy phase space available in TI18 in order to optimize the detector location and acceptance for neutrinos originating at the pp interaction point, in contrast to neutrinos from pion and kaon decays. The studies are based on the comparison of simulated pp collisions at 13 TeV: PYTHIA events of heavy quark (c and b) production, compared to DPMJET minimum bias events (including charm) with produced particles traced through realistic LHC optics with FLUKA. Our studies favour a configuration where the detector is positioned off the beam axis, slightly above the ideal prolongation of the LHC beam from the straight section, covering 7.4 < η < 9.2. In this configuration, the flux at high energies (0.5–1.5 TeV and beyond) is found to be dominated by neutrinos originating directly from IP1, mostly from charm decays, of which ≈50% are electron neutrinos and ≈5% are tau neutrinos. The contribution of pion and kaon decays to the muon neutrino flux is found small at those high energies. With 150 fb−1 of delivered LHC luminosity in Run 3 the experiment can record a few thousand very high energy neutrino charged current (CC) interactions and over 50 tau neutrino CC events. These events provide useful information in view of a high statistics experiment at HL–LHC. The electron and muon neutrino samples can extend the knowledge of the charm PDF to a new region of x, which is dominated by theory uncertainties. The tau neutrino sample can provide first experience on reconstruction of tau neutrino events in a very boosted regime.

CIMBA: Fast Monte Carlo generation using cubic interpolation

Monte Carlo generation of high energy particle collisions is a critical tool for both theoretical and experimental particle physics, connecting perturbative calculations to phenomenological models, and theory predictions to full detector simulation. The generation of minimum bias events can be particularly computationally expensive, where non-perturbative effects play an important role and specific processes and fiducial regions can no longer be well defined. In particular scenarios, particle guns can be used to quickly sample kinematics for single particles produced in minimum bias events. CIMBA (Cubic Interpolation for Minimum Bias Approximation) provides a comprehensive package to smoothly sample predefined kinematic grids, from any general purpose Monte Carlo generator, for all particles produced in minimum bias events. These grids are provided for a number of beam configurations including those of the Large Hadron Collider. Program summaryProgram title: CIMBA (Cubic Interpolation for Minimum Bias Approximation)CPC Library link to program files:http://dx.doi.org/10.17632/49m44md4ph.1Licensing provisions: GPL version 2 or laterProgramming language: Python, C++Nature of problem: generation of simulated events in high energy particle physics is quickly becoming a bottleneck in analysis development for collaborations on the Large Hadron Collider (LHC). With the expected long-term continuation of the high luminosity LHC, this problem must be solved in the near future. Significant progress has been made in designing new ways to perform detector simulation, including parametric detector models and machine learning techniques, e.g. calorimeter shower evolution with generative adversarial networks. Consequently, the efficiency of generating physics events using general purpose Monte Carlo event generators, rather than just detector simulation, needs to be improved.Solution method: in many cases, single particle generation from pre-sampled phase-space distributions can be used as a fast alternative to full event generation. Phase-space distributions sampled in particle pseudorapidity and transverse momentum are sampled from large, once-off, minimum bias samples generated with Pythia 8. A novel smooth sampling of these distributions is performed using piecewise cubic Hermite interpolating polynomials. Distributions are created for all generated particles, as well as particles produced directly from hadronisation. Interpolation grid libraries are provided for a number of common collider configurations, and code is provided which can produce custom interpolation grid libraries.Restrictions: Single particle generation

Comparative study of charged multiplicities and moments inppcollisions ats=7 TeVin the forward region at the LHC

Charged particle multiplicities in proton-proton collisions measured in the LHCb detector at a centre-of-mass energy of $\sqrt s$=7 TeV in different windows of pseudorapidity $\eta$, in the forward region of the vertex detector are studied by using different statistical distributions. Three distributions are compared with the data and the moments of the distributions are calculated. The data constituting two sets, one of minimum bias events and another of hard QCD events are analysed. The distributions considered derive from different functional forms based on underlying interaction dynamics. The analysis complements the multiplicity analysis done by LHCb in terms of Monte Carlo event generators. The present analysis is from a different perspective, using statistical distributions.

Multiplicity dependence of inclusive J/ψ production at midrapidity in pp collisions at [formula omitted] TeV

Measurements of the inclusive J/ψ yield as a function of charged-particle pseudorapidity density dNch/dη in pp collisions at s=13 TeV with ALICE at the LHC are reported. The J/ψ meson yield is measured at midrapidity (|y|<0.9) in the dielectron channel, for events selected based on the charged-particle multiplicity at midrapidity (|η|<1) and at forward rapidity (−3.7<η<−1.7 and 2.8<η<5.1); both observables are normalized to their corresponding averages in minimum bias events. The increase of the normalized J/ψ yield with normalized dNch/dη is significantly stronger than linear and dependent on the transverse momentum. The data are compared to theoretical predictions, which describe the observed trends well, albeit not always quantitatively.

(Anti-)deuteron production in pp collisions at sqrt{s}=13 text {TeV}

The study of (anti-)deuteron production in pp collisions has proven to be a powerful tool to investigate the formation mechanism of loosely bound states in high-energy hadronic collisions. In this paper the production of text {(anti-)deuterons} is studied as a function of the charged particle multiplicity in inelastic pp collisions at sqrt{s}=13 TeV using the ALICE experiment. Thanks to the large number of accumulated minimum bias events, it has been possible to measure (anti-)deuteron production in pp collisions up to the same charged particle multiplicity ({mathrm {d} N_{ch}/mathrm {d} eta } sim 26) as measured in p–Pb collisions at similar centre-of-mass energies. Within the uncertainties, the deuteron yield in pp collisions resembles the one in p–Pb interactions, suggesting a common formation mechanism behind the production of light nuclei in hadronic interactions. In this context the measurements are compared with the expectations of coalescence and statistical hadronisation models (SHM).