<p>In relativistic heavy-ion collisions, the formation of a deconfined and thermalized state of partons, known as quark-gluon plasma (QGP), leads to enhanced production of strange hadrons in contrast to proton-proton (<math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>p</mi><mi>p</mi></mrow></math>) collisions, which are taken as baseline. This observation is known as strangeness enhancement in heavy-ion collisions and is considered one of the important signatures that can signify the formation of QGP. However, in addition to strangeness enhancement, recent measurements hint at observing several heavy-ion-like features in high multiplicity <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>p</mi><mi>p</mi></mrow></math> collisions at energies available at the CERN Large Hadron Collider. Alternatively, event shape observables, such as transverse spherocity, transverse sphericity, charged particle flattenicity, and relative transverse activity classifiers, can fundamentally separate hard interaction-dominated jetty events from soft isotropic events. These features of event shape observables can probe the observed heavy-ion-like features in <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>p</mi><mi>p</mi></mrow></math> collisions with significantly reduced selection bias and can bring all collision systems on equal footing. In this article, we present an extensive summary of the strange particle ratios to pions as a function of different event classifiers using the PYTHIA 8 model with color reconnection and rope hadronization mechanisms to understand the microscopic origin of strangeness enhancement in <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>p</mi><mi>p</mi></mrow></math> collisions and also prescribe the applicability of these event classifiers in the context of strangeness enhancement. Charged-particle flattenicity is found to be most suited for the study of strangeness enhancement, and it shows a quantitative enhancement similar to that seen for the analysis based on the number of multiparton interactions.</p>

India

Suraj Prasad

Bhagyarathi Sahoo

CERN

Sushanta Tripathy

Neelkamal Mallick

Raghunath Sahoo

Probing strangeness with event topology classifiers in <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>p</mi><mi>p</mi></mrow></math> collisions at energies available at the CERN Large Hadron Collider with the rope hadronization mechanism in PYTHIA

A microscopic understanding of (anti)deuteron production in hadron–hadron collisions is the subject of many experimental and theoretical efforts in nuclear physics. This topic is also very relevant for astrophysics, since the rare production of antinuclei in our Universe could be a doorway to discover new physics. In this work, we describe a new coalescence afterburner for event generators based on the Wigner function formalism and we apply it to the (anti)deuteron case, taking into account a realistic particle emitting source. The model performance is validated using the EPOS and PYTHIA event generators applied to proton–proton collisions at the centre-of-mass energy  $$\sqrt{s}= 13$$  <math> <mrow> <msqrt> <mi>s</mi> </msqrt> <mo>=</mo> <mn>13</mn> </mrow> </math>   TeV, triggered for high multiplicity events, and the experimental data measured by ALICE in the same collision system. The model relies on the direct measurement of the particle emitting source carried out by means of nucleon–nucleon femtoscopic correlations in the same collision system and energy. The resulting model is used to predict deuteron differential spectra assuming different deuteron wavefunctions within the Wigner function formalism. The predicted deuteron spectra show a clear sensitivity to the choice of the deuteron wavefunction. The Argonne  $$v_{18}$$  <math> <msub> <mi>v</mi> <mn>18</mn> </msub> </math>   wavefunction provides the best description of the experimental data. This model can now be used to study the production of (anti)deuterons over a wide range of collision energies and be extended to heavier nuclei.

Germany

Maximilian Mahlein

Italy

Luca Barioglio

Francesca Bellini

Laura Fabbietti

Chiara Pinto

Bhawani Singh

A realistic coalescence model for deuteron production

Event classifiers based either on the charged-particle multiplicity or the event shape have been extensively used in proton-proton (<math><mi>p</mi><mi>p</mi></math>) collisions by the ALICE Collaboration at the LHC. The use of these tools became very instrumental since the observation of fluidlike behavior in high-multiplicity <math><mi>p</mi><mi>p</mi></math> collisions. In particular, the study as a function of the charged-particle multiplicity registered in the forward V0 ALICE detector allowed for the discovery of strangeness enhancement in high-multiplicity <math><mi>p</mi><mi>p</mi></math> collisions. However, one drawback of the multiplicity-based event classifiers is that requiring a high charged-particle multiplicity biases the sample towards hard processes like multijet final states. These biases make it difficult to perform jet-quenching searches in high-multiplicity <math><mi>p</mi><mi>p</mi></math> collisions. In this context, the present paper explores the use of the new event classifier, flattenicity; which uses the multiplicity calculated in the forward pseudorapidity region. To illustrate how this tool works, pp collisions at <math><msqrt><mi>s</mi></msqrt><mo>=</mo><mn>13.6</mn><mtext> </mtext><mtext> </mtext><mi>TeV</mi></math> simulated with pythia 8 are explored. The sensitivity of flattencity to multipartonic interactions as well as to the “hardness” of the collision are discussed. pythia 8 predictions for the transverse momentum spectra of light- and heavy-flavored hadrons as a function of flattenicity are presented.

Antonio Ortiz

Czechia

Arvind Khuntia

United States

Omar Vázquez Rueda

Hungary

Gyula Bencédi

China

Feng Fan

Unveiling the effects of multiple soft partonic interactions in <math><mi>p</mi><mi>p</mi></math> collisions at <math><mrow><msqrt><mrow><mi>s</mi></mrow></msqrt><mo>=</mo><mn>13.6</mn><mtext> </mtext><mtext> </mtext><mi>TeV</mi></mrow></math> using a new event classifier

Anisotropic flow is accredited to have effects from the initial state geometry and fluctuations in the nuclear overlap region. The elliptic flow (<math><msub><mi>v</mi><mn>2</mn></msub></math>) and triangular flow (<math><msub><mi>v</mi><mn>3</mn></msub></math>) coefficients of the final state particles are expected to have influenced by eccentricity (<math><msub><mi>ϵ</mi><mn>2</mn></msub></math>) and triangularity (<math><msub><mi>ϵ</mi><mn>3</mn></msub></math>) of the participants, respectively. In this work, we study <math><msub><mi>v</mi><mn>2</mn></msub></math>, <math><msub><mi>v</mi><mn>3</mn></msub></math>, <math><msub><mi>ϵ</mi><mn>2</mn></msub></math>, <math><msub><mi>ϵ</mi><mn>3</mn></msub></math>, and the correlations among them with respect to event topology in the framework of a multiphase transport model (AMPT). We use transverse spherocity and reduced flow vector as event shape classifiers in this study. Transverse spherocity has the unique ability to separate events based on geometrical shapes, i.e., jetty and isotropic, which pertain to pQCD and non-pQCD domains of particle production in high-energy physics, respectively. We use the two-particle correlation method to study different anisotropic flow coefficients. We confront transverse spherocity with a more widely used event shape classifier–reduced flow vector (<math><msub><mi>q</mi><mi>n</mi></msub></math>) and they are found to have significant (anti)correlations among them. We observe significant spherocity dependence on <math><msub><mi>v</mi><mn>2</mn></msub></math>, <math><msub><mi>v</mi><mn>3</mn></msub></math>, and <math><msub><mi>ϵ</mi><mn>2</mn></msub></math>. This work also addresses transverse momentum dependent crossing points between <math><msub><mi>v</mi><mn>2</mn></msub></math> and <math><msub><mi>v</mi><mn>3</mn></msub></math>, which varies for different centrality and spherocity percentiles.

Probing initial geometrical anisotropy and final azimuthal anisotropy in heavy-ion collisions at Large Hadron Collider energies through event-shape engineering

Transverse spherocity is an event shape observable, which separates the events based on their geometrical shapes. In this work, we use transverse spherocity to study the identified light flavor production in heavy-ion collisions using A Multi-Phase Transport (AMPT) model. We obtain the elliptic flow coefficients for pions, kaons and protons in Pb+Pb collisions at  $$\sqrt{s_\mathrm{{NN}}} = 5.02$$  <math> <mrow> <msqrt> <msub> <mi>s</mi> <mi>NN</mi> </msub> </msqrt> <mo>=</mo> <mn>5.02</mn> </mrow> </math>   TeV as a function of transverse spherocity and collision centrality. Also, we study the number of constituent-quark (NCQ) scaling of elliptic flow which interprets the dominance of the quark degrees of freedom at the early stages of the collision. We observe a clear dependence of the elliptic flow for identified particles on transverse spherocity. It is found that the NCQ-scaling is strongly violated in events with low transverse spherocity compared to transverse spherocity-integrated events, confirming the fragmentation-based hadronization mechanism for high-momentum partons involved in the dynamics of jetty-like events.

Event topology and constituent-quark scaling of elliptic flow in heavy-ion collisions at the Large Hadron Collider using a multiphase transport model

Recently, machine learning (ML) techniques have led to a range of numerous developments in the field of nuclear and high-energy physics. In heavy-ion collisions, the impact parameter of a collision is one of the crucial observables that has a significant impact on the final state particle production. However, the calculation of such a quantity is nearly impossible in experiments as the length scale ranges in the level of a few fermi. In this work, we implement the ML-based regression technique via boosted decision trees to obtain a prediction of the impact parameter in Pb-Pb collisions at <math><mrow><msqrt><mrow><msub><mrow><mi>s</mi></mrow><mrow><mi>NN</mi></mrow></msub></mrow></msqrt><mo>=</mo><mn>5.02</mn><mtext> </mtext><mtext> </mtext><mi>TeV</mi></mrow></math> using a multiphase transport model. In addition, we predict an event shape observable, transverse spherocity in Pb-Pb collisions at <math><msqrt><msub><mi>s</mi><mrow><mi>NN</mi></mrow></msub></msqrt><mo>=</mo><mn>2.76</mn></math> and 5.02 TeV using a multiphase transport and pythia8 based on Angantyr model. After a successful implementation in small collision systems, the use of transverse spherocity in heavy-ion collisions has potential to reveal new results from heavy-ion collisions where the production of a quark gluon plasma medium is already established. We predict the centrality dependent spherocity distributions from the training of minimum bias simulated data and find that the predictions from the boosted decision trees based ML technique match with true simulated data. In the absence of experimental measurements, we propose to implement a machine learning based regression technique to obtain transverse spherocity from the known final state observables in heavy-ion collisions.

Aditya Nath Mishra

Suman Deb

Estimation of impact parameter and transverse spherocity in heavy-ion collisions at the LHC energies using machine learning

Recent observations of QGP-like conditions in high-multiplicity pp collisions from ALICE experiment at the LHC warrant an introspection whether to use pp collisions as a baseline measurement to characterize heavy-ion collisions for the possible formation of a Quark-Gluon Plasma. A double differential study of the particle spectra and thermodynamics of the produced system as a function of charged-particle multiplicity and transverse spherocity in pp collisions would shed light on the underlying event dynamics. Transverse spherocity, one of the event shape observables, allows to separate the events in terms of jetty and isotropic events. We analyse the identified particle transverse momentum (<math id="M2"><msub><mrow><mi>p</mi></mrow><mrow><mi>T</mi></mrow></msub></math>) spectra as a function of charged-particle multiplicity and transverse spherocity using Tsallis nonextensive statistics and Boltzmann-Gibbs Blast-Wave (BGBW) model in pp collisions at <math id="M3"><msqrt><mrow><mi>s</mi></mrow></msqrt><mo>=</mo><mn>13</mn><mtext> </mtext><mtext>TeV</mtext></math> using PYTHIA8 event generator. The extracted parameters such as temperature (<math id="M4"><mi>T</mi></math>), radial flow (<math id="M5"><mi>β</mi></math>), and nonextensive parameter (<math id="M6"><mi>q</mi></math>) are shown as a function of charged-particle multiplicity for different spherocity classes. We observe that the isotropic events approach thermal equilibrium while the jetty ones remain far from equilibrium. We argue that, while studying the QGP-like conditions in small systems, one should separate the isotropic events from the spherocity-integrated events, as the production dynamics are different.

Ashish Bisht

Poland

Malavika Panikkassery Salvan

Event Shape and Multiplicity Dependence of Freeze-Out Scenario and System Thermodynamics in Proton+Proton Collisions at Using PYTHIA8

Multiparton interactions (MPI) in <math><mi>p</mi><mi>p</mi></math> collisions have attracted the attention of the heavy-ion community since they can help to elucidate the origin of collectivelike effects discovered in small collision systems at the LHC. In this work, we report that in pythia8.244, the charged-particle production in events with a large number of MPI (<math><msub><mi>N</mi><mrow><mi>mpi</mi></mrow></msub></math>) normalized to that obtained in minimum-bias <math><mi>p</mi><mi>p</mi></math> collisions shows interesting features. After the normalization to the corresponding <math><mo>⟨</mo><msub><mi>N</mi><mrow><mi>mpi</mi></mrow></msub><mo>⟩</mo></math>, the ratios as a function of <math><msub><mi>p</mi><mi>T</mi></msub></math> exhibit a bump at <math><mrow><msub><mrow><mi>p</mi></mrow><mrow><mi>T</mi></mrow></msub><mo>≈</mo><mn>3</mn><mtext> </mtext><mtext> </mtext><mi>GeV</mi><mo>/</mo><mi>c</mi></mrow></math>; and for higher <math><msub><mi>p</mi><mi>T</mi></msub></math> (<math><mrow><mo>&gt;</mo><mn>8</mn><mtext> </mtext><mtext> </mtext><mi>GeV</mi><mo>/</mo><mi>c</mi></mrow></math>), the ratios are independent of <math><msub><mi>N</mi><mrow><mi>mpi</mi></mrow></msub></math>. While the size of the bump increases with increasing <math><msub><mi>N</mi><mrow><mi>mpi</mi></mrow></msub></math>, the behavior at high <math><msub><mi>p</mi><mi>T</mi></msub></math> is expected from the “binary scaling” (parton-parton interactions), which holds given the absence of any parton-energy loss mechanism in pythia. The bump at intermediate <math><msub><mi>p</mi><mi>T</mi></msub></math> is reminiscent of the Cronin effect observed for the nuclear modification factor in <math><mrow><mi>p</mi></mrow></math>-Pb collisions. In order to unveil these effects in data, we propose a strategy to construct an event classifier sensitive to MPI using machine learning-based regression. The study is conducted using TMVA, and the regression is performed with boosted decision trees (BDT). Event properties like forward charged-particle multiplicity, transverse spherocity and the average transverse momentum (<math><mo>⟨</mo><msub><mi>p</mi><mi>T</mi></msub><mo>⟩</mo></math>) are used for training. The kinematic cuts are defined in accordance with the ALICE detector capabilities. For the validation of the method and to find possible model dependence, we also compare the results from pythia8.244 with herwig7.1. In addition, we also report that if we apply the trained BDT on existing (<math><mrow><mi>INEL</mi></mrow><mo>&gt;</mo><mn>0</mn></math>) <math><mi>p</mi><mi>p</mi></math> data, i.e., events with at least one primary charged-particle within <math><mo>|</mo><mi>η</mi><mo>|</mo><mo>&lt;</mo><mn>1</mn></math>, the average number of MPI in <math><mi>p</mi><mi>p</mi></math> collisions at <math><msqrt><mi>s</mi></msqrt><mo>=</mo><mn>5.02</mn></math> and 13 TeV are <math><mn>3.76</mn><mo>±</mo><mn>1.01</mn></math> and <math><mn>4.65</mn><mo>±</mo><mn>1.01</mn></math>, respectively.

Mexico

Antonio Paz

José D. Romo

Erik A. Zepeda

Irais Bautista

Multiparton interactions in <math><mi>p</mi><mi>p</mi></math> collisions from machine learning-based regression

Elliptic flow of hadrons observed at relativistic heavy ion collision experiments at relativistic heavy ion collider (RHIC) and large hadron collider (LHC) provides us an important signature of possible deconfinement transition from the hadronic phase to partonic phase. However, hadronization processes of deconfined partons back into final hadrons are found to play a vital role in the observed hadronic flow. In the present work, we use a coalescence mechanism also known as recombination (ReCo) to combine quarks into hadrons. To get there, we have used the Boltzmann transport equation in relaxation time approximation to transport the quarks into equilibration and finally to freeze-out the surface, before coalescence takes place. A Boltzmann-Gibbs blast wave (BGBW) function is taken as an equilibrium function to get the final distribution and a power-like function to describe the initial distributions of partons produced in heavy ion collisions. In the present work, we try to estimate the elliptic flow of identified hadrons such as <math id="M2"><mi>π</mi></math>, <math id="M3"><mi>K</mi></math>, and <math id="M4"><mi>p</mi></math>, produced in Pb+Pb collisions at <math id="M5"><msqrt><mrow><msub><mrow><mi>s</mi></mrow><mrow><mi>N</mi><mi>N</mi></mrow></msub></mrow></msqrt><mo>=</mo><mn>2.76</mn><mtext> </mtext><mtext>TeV</mtext></math> at the LHC for different centralities. The elliptic flow (<math id="M6"><msub><mrow><mi>v</mi></mrow><mrow><mn>2</mn></mrow></msub></math>) of identified hadrons seems to be described quite well in the available <math id="M7"><msub><mrow><mi>p</mi></mrow><mrow><mtext>T</mtext></mrow></msub></math> range. After the evolution of quarks until freeze-out time has been calculated using BTE-RTA, the approach used in this paper consists of combining two or more quarks to explain the produced hadrons at intermediate momenta regions. The formalism is found to describe the elliptic flow of hadrons produced in Pb+Pb collisions to a large extent.

Mohammed Younus

Swatantra Kumar Tiwari

Elliptic Flow of Hadrons via Quark Coalescence Mechanism Using the Boltzmann Transport Equation for Pb+Pb Collision at

Hadronic resonances, having very short lifetimes, like <math><msup><mrow><mi>K</mi></mrow><mrow><mo>*</mo><mn>0</mn></mrow></msup></math>, can act as useful probes to understand and estimate the lifetimes of hadronic phases in ultrarelativistic proton-proton, <math><mi>p</mi></math>-Pb, and heavy-ion collisions. Resonances with relatively longer lifetime, like <math><mi>ϕ</mi></math> mesons, can serve as tools to locate the quark-gluon plasma (QGP) phase boundary. We estimate a lower limit of hadronic phase lifetime in Cu-Cu and Au-Au collisions at the Relativistic Heavy Ion Collider (RHIC) and in <math><mrow><mi>p</mi><mi>p</mi></mrow><mo>,</mo><mo> </mo><mi>p</mi></math>-Pb, and Pb-Pb collisions at different Large Hadron Collider (LHC) collision energies. Also, we obtain the effective temperature of <math><mi>ϕ</mi></math> mesons using the Boltzmann-Gibbs blast-wave function, which gives insight into locating the QGP phase boundary. We observe that the hadronic phase lifetime strongly depends on final-state charged-particle multiplicity, whereas the QGP phase and hence the QCD phase boundary shows very weak multiplicity dependence. This suggests that the hadronization from a QGP state starts at a similar temperature irrespective of charged-particle multiplicity, collision system, and collision energy, while the endurance of hadronic phase is strongly dependent on final-state charged-particle multiplicity, system size, and collision energy.

Dushmanta Sahu

Girija Sankar Pradhan

Role of event multiplicity on hadronic phase lifetime and QCD phase boundary in ultrarelativistic collisions at energies available at the BNL Relativistic Heavy Ion Collider and CERN Large Hadron Collider