Related papers: A Novel Deep Learning Method for Detecting Nucleon…
Modeling of the process of the formation of nuclear clusters in the hot nuclear matter is a challenging task. We present the novel n-body dynamical transport approach - PHQMD (Parton-Hadron-Quantum-Molecular Dynamics) [1] for the…
Studies of the ultrarelativistic collisions of hadrons and nuclei at different centrality and energy enable to explore the QCD phase diagram in a wide range of temperature and baryon density. Long-range correlation studies are considered as…
In this work, we perform a model-to-data comparison for U+U and Au+Au collisions performed at RHIC at $\sqrt{s_{\rm NN}}$ = $193$ GeV and $200$ GeV, using a multistage framework. Model calculations for various configurations of $^{238}$U…
Recent advances in scanning transmission electron and scanning probe microscopies have opened exciting opportunities in probing the materials structural parameters and various functional properties in real space with angstrom-level…
We report the largest scale deep learning with High Performance Computing (HPC) to physics analysis with the CMS simulation data in proton-proton collisions at 13 TeV. We build a Convolutional Neural Network (CNN) model that takes low-level…
Heavy-ion collisions covering a wide range of collision energies provide a vast amount of observables characterizing the properties of strongly-interacting matter. In particular collisions towards the high baryon-density regime of the QCD…
High-energy partons lose energy while propagating through the hot, strongly interacting medium produced in ultrarelativistic nucleus-nucleus collisions, leading to a suppression of particle production at high transverse momentum…
In this work, the production of photons through binary scattering processes is investigated for equilibrated hadronic systems. More precisely, a non-equilibrium hadronic transport approach to describe relativistic heavy-ion collisions is…
Sub-nuclear fluctuations in the initial state of heavy-ion collisions impact not only transverse long-range correlations of small systems, but also the creation of longitudinal structures, seen in particle detectors as longitudinal…
The neutron skin thickness in neutron-rich nuclei has traditionally been measured using elastic fixed target electron-nucleus scattering since the 1970s. In this paper, we propose a novel probe of the neutron skin thickness through deep…
The diffusion coefficient of heavy quarks in the deconfined medium is examined in this research using a deep convolutional neural network (CNN) trained with data from relativistic heavy ion collisions involving heavy flavor hadrons. The CNN…
While relativistic heavy-ion collisions become an alternative way of studying nucleus structure, the accurate extraction of nucleus structure could be hampered by the uncertainty of nucleon size, and the latter has attracted people's…
In this work, by using the machine learning methods, we study the sensitivities of heavy pseudo-Dirac neutrino $N$ in the inverse seesaw at the high-energy hadron colliders. The production process for the signal is $pp \to \ell N \to 3 \ell…
In this paper we propose a new strategy, based on anomaly detection methods, to search for new physics phenomena at colliders independently of the details of such new events. For this purpose, machine learning techniques are trained using…
We demonstrate high prediction accuracy of three important properties that determine the initial geometry of the heavy-ion collision (HIC) experiments by using supervised Machine Learning (ML) methods. These properties are the impact…
We report results of the first systematic simulation of proton and neutron density distributions in central heavy-ion collisions within the beam energy range of $ E_{\rm beam} \leq 800 \, \text{MeV/nucl}$ using pBUU and TDHF models. The…
In this review article, we first briefly introduce the transport theory and quantum molecular dynamics model applied in the study of the heavy ion collisions from low to intermediate energies. The developments of improved quantum molecular…
We use a Monte Carlo approach to study hadron azimuthal angular correlations in high energy proton-proton and central nucleus-nucleus collisions at the BNL Relativistic Heavy Ion Collider (RHIC) energies at mid-rapidity. We build a hadron…
A systematic study of charged hadron multiplicities ($n_{ch}$) at various collision energies is very much important in understanding the basic production mechanism of the hadrons in nucleus-nucleus collision experiments. Furthermore, the…
We review the effect of hadron structure changes in a nuclear medium using the quark-meson coupling (QMC) model, which is based on a mean field description of non-overlapping nucleon (or baryon) bags bound by the self-consistent exchange of…