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In the context of event-by-event hydrodynamic description, we analyze the implications of two models characterized by distinct initial conditions. The initial energy density of the first model adopts a Gaussian-type distribution, while…
The features of magnetic field in relativistic heavy-ion collisions are systematically studied by using a modified magnetic field model in this paper. The features of magnetic field distributions in the central point are studied in the RHIC…
A central challenge in high-energy nuclear physics is to extract informative features from the high-dimensional final-state data of heavy-ion collisions (HIC) in order to enable reliable downstream analyses. Traditional approaches often…
Since the start of the LHC heavy ion program, a multitude of rather different high transverse momentum (P_T) observables has become available to study the physics of the interaction of hard partons with a QCD medium. Similarly, multiple…
The quality of data taken at RHIC and LHC as well as the success and sophistication of computational models for the description of ultra-relativistic heavy-ion collisions have advanced to a level that allows for the quantitative extraction…
High-energy nuclear collisions encompass three key stages: the structure of the colliding nuclei informed by low-energy nuclear physics, the initial condition (IC) leading to the formation of quark-gluon plasma (QGP), and the hydrodynamic…
[Background:] A significant quenching of high energy jets was observed in the heavy ion collisions at the Relativistic Heavy Ion Collider (RHIC) facility, and is now confirmed at the Large Hadron Collider (LHC) facility. The RHIC plus LHC…
We study the prospects of characterising Dark Matter at colliders using Machine Learning (ML) techniques. We focus on the monojet and missing transverse energy (MET) channel and propose a set of benchmark models for the study: a typical…
Jet measurements in heavy ion collisions can provide constraints on the properties of the quark gluon plasma, but the kinematic reach is limited by a large, fluctuating background. We present a novel application of symbolic regression to…
We explore machine learning-based jet and event identification at the future Electron-Ion Collider (EIC). We study the effectiveness of machine learning-based classifiers at relatively low EIC energies, focusing on (i) identifying the…
An open question in the field of heavy-ion collisions is to what extent the size of initial inhomogeneities in the system affects measured observables. Here we present a method to smooth out these inhomogeneities with minimal effect on…
In ultrarelativistic heavy-ion experiments, one estimates the centrality of a collision by using a single observable, say $n$, typically given by the transverse energy or the number of tracks observed in a dedicated detector. The…
Despite their importance in a wide variety of applications, the estimation of ionization cross sections for large molecules continues to present challenges for both experiment and theory. Machine learning algorithms have been shown to be an…
Bayesian parameter estimation provides a systematic approach to compare heavy ion collision models with measurements, leading to constraints on the properties of nuclear matter with proper accounting of experimental and theoretical…
The ability to accurately compute the series of coefficients $v_n$ characterizing the momentum space anisotropies of particle production in ultrarelativistic heavy ion collisions as a function of centrality is widely regarded as a triumph…
We give a short review of hydrodynamic models at heavy ion collisions from the point of view of initial conditions, an equation of states (EoS) and freezeout process. Then we show our latest results of a combined fully three-dimensional…
We study within the IP-Glasma and two-component MC-Glauber models the effects of initial state geometry and fluctuations on multiplicities and eccentricities for several collision species at the Relativistic Heavy Ion Collider (RHIC). These…
The ALICE experiment at the LHC measures properties of the strongly interacting matter formed in ultrarelativistic heavy-ion collisions. Such studies require accurate particle identification (PID). ALICE provides PID information via several…
The Multi Module Model for Ultra-Relativistic Heavy Ion Collisions at RHIC and LHC energies is presented. It uses the Effective String Rope Model for the calculation of the initial stages of the reaction; the output of this model is used as…
High-entropy alloys (HEAs) with multiple constituent elements have been extensively studied in the past 20 years due to their promising engineering application. Previous experimental and computational studies of HEAs focused mainly on…