Related papers: Machine Learning model driven prediction of the in…
Basic problems of the semiclassical microscopic modelling of strongly interactingsystems are discussed within the framework of Quantum Molecular Dynamics (QMD). This model allows to study the influence of several types of nucleonic…
Knowledge of the mass composition of ultra-high-energy cosmic rays is crucial to understanding their origins; however, current approaches have limited event-by-event resolution. With fluorescence telescope measurements of the longitudinal…
Magnesium (Mg) alloys have shown great prospects as both structural and biomedical materials, while poor corrosion resistance limits their further application. In this work, to avoid the time-consuming and laborious experiment trial, a…
Heavy-ion collisions provide a window into the properties of many-body systems of deconfined quarks and gluons. Understanding the collective properties of quarks and gluons is possible by comparing models of heavy-ion collisions to…
The integrated HydroKinetic Model (iHKM) is applied to analyse the results of direct photon spectra and elliptic flow measurements in 200A GeV Au+Au collisions at RHIC for the three centrality bins. We detect the strong centrality…
In this paper we conduct a systematic study of the granularity of the initial state of hot and dense QCD matter produced in ultra-relativistic heavy-ion collisions and its influence on bulk observables like particle yields, $m_T$ spectra…
We present a fully three-dimensional model providing initial conditions for energy and conserved charge density distributions in heavy ion collisions at RHIC Beam Energy Scan (BES) collision energies. The model includes the dynamical…
The centrality of heavy-ion collisions is directly related to the medium created therein. A procedure to determine the centrality of collisions with the LHCb detector is implemented for lead-lead collisions at…
Despite successful use in a wide variety of disciplines for data analysis and prediction, machine learning (ML) methods suffer from a lack of understanding of the reliability of predictions due to the lack of transparency and black-box…
In non-central heavy ion collisions, identical two particle Hanbury-Brown/Twiss (HBT) correlations C(K,q) depend on the azimuthal direction of the pair momentum K. We investigate the consequences for a harmonic analysis of the corresponding…
In heavy-ion ({\it A-A}) collisions, the correlations among the particles produced across wide range in rapidity, probe the early stages of the reaction. The analyses of forward-backward multiplicity correlations in these collisions are…
In this study, we explore the applicability of Transfer Learning techniques for estimating collision centrality in terms of the number of participants ($N_{\rm part}$) in high-energy heavy-ion collisions. In the present work, we leverage…
Traditional atomistic machine learning (ML) models serve as surrogates for quantum mechanical (QM) properties, predicting quantities such as dipole moments and polarizabilities, directly from compositions and geometries of atomic…
Electrochemical hybrid battery models have major potential to enable advanced physics-based control, diagnostic, and prognostic features for next-generation lithium-ion battery management systems. This is due to the physical significance of…
Angular correlations of two and more particles are a sensitive probe of the initial state and the transport properties of the system produced in heavy-ion collisions. Two recent results of the ALICE collaboration are presented. Event-shape…
We present a new 3D resolved model for the initial state of ultrarelativistic heavy-ion collisions, based on the $k_\perp$-factorized Color Glass Condensate hybrid approach. The McDIPPER framework responds to the need for a…
Elliptic flow parameter, $v_{2}$ is consider as a sensitive probe for early dynamics of the heavy-ion collision. In this work we have discussed the effect of detector efficiency, procedure of centrality determination, effect of resonance…
A good understanding of the luminosity performance in a collider, as well as reliable tools to analyse, predict, and optimise the performance, are of great importance for the successful planning and execution of future runs. In this…
Ultra-Relativistic Heavy Ion Collisions at an energy $\sqrt{s_{NN}} = 65 {\rm GeV}$ are studied in a three-dimensional Fluid Dynamical model. The results of a hydrodynamical evolution using the PIC-method are shown. The importance and…
Understanding excitonic effects in two-dimensional (2D) materials is critical for advancing their potential in next-generation electronic and photonic devices. In this study, we introduce a machine learning (ML)-based framework to predict…