Related papers: A deep learning approach for predicting multiple o…
This study investigates the application of deep residual networks for predicting the dynamics of interacting three-dimensional rigid bodies. We present a framework combining a 3D physics simulator implemented in C++ with a deep learning…
We present different methods of unsupervised learning which can be used for outlier detection in high energy nuclear collisions. The UrQMD model is used to generate the bulk background of events as well as different variants of outlier…
According to first principle Lattice QCD calculations, the transition from quark-gluon plasma to hadronic matter is a smooth crossover in the region $\mu_{\rm B}\leq T_{c}$. In this range the ratio, $C_{6}/C_{2}$, of net-baryon…
Fluctuations of conserved quantities are sensitive observables to probe the signature of QCD phase transition and critical point in heavy-ion collisions. With the UrQMD model, we have studied the centrality and energy dependence of various…
The study of the multi-strange production in the final state of ultra-relativistic Au+Au collisions at top RHIC energy gives information on the freeze-out conditions and probably on earlier stages of the collision. The chemical freeze-out…
Many analyses in particle and nuclear physics use simulations to infer fundamental, effective, or phenomenological parameters of the underlying physics models. When the inference is performed with unfolded cross sections, the observables…
Balance functions have been measured in terms of relative pseudorapidity ($\Delta \eta$) for charged particle pairs at the Relativistic Heavy-Ion Collider (RHIC) from Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 7.7 GeV to 200 GeV using the…
We review the physics of nuclear matter at high energy density and the experimental search for the Quark-Gluon Plasma at the Relativistic Heavy Ion Collider (RHIC). The data obtained in the first three years of the RHIC physics program…
Dynamic fluctuations in the local density of non-identified hadron tracks reconstructed in the STAR TPC are studied using the discrete wavelet transform power spectrum technique which involves mixed event reference sample comparison. The…
Survival prediction is crucial for cancer patients as it provides early prognostic information for treatment planning. Recently, deep survival models based on deep learning and medical images have shown promising performance for survival…
This work presents a physics-informed neural network approach bridging deep-learning force field and electronic structure simulations, illustrated through twisted two-dimensional large-scale material systems. The deep potential molecular…
We report the first measurements of the moments -- mean ($M$), variance ($\sigma^{2}$), skewness ($S$) and kurtosis ($\kappa$) -- of the net-charge multiplicity distributions at mid-rapidity in Au+Au collisions at seven energies, ranging…
Recent work has provided the means to rigorously determine properties of super-hadronic matter from experimental data through the application of broad scale modeling of high-energy nuclear collisions within a Bayesian framework. These…
We present a fast simulation application based on a Deep Neural Network, designed to create large analysis-specific datasets. Taking as an example the generation of W+jet events produced in sqrt(s)= 13 TeV proton-proton collisions, we train…
The Large Hadron Collider at CERN produces immense volumes of complex data from high-energy particle collisions, demanding sophisticated analytical techniques for effective interpretation. Neural Networks, including Graph Neural Networks,…
The Beam Energy Scan (BES) program at the Relativistic Heavy Ion Collider (RHIC) was extended to energies below $\sqrt{\textit{s}_{NN}}$ = 7.7 GeV in 2015 by successful implementation of the fixed-target mode of operation in the STAR…
To study heavy ion collisions at energies available from the Relativistic Heavy Ion Collider, we have developed a multi-phase transport model that includes both initial partonic and final hadronic interactions. Specifically, the parton…
We present the directed flow measurement ($v_1$) from Au+Au collisions at $\sqrtsNN = 62$ GeV. Over the pseudorapidity range we have studied, which covers $\eta$ from -1.2 to 1.2 and $2.4 < |\eta| < 4$, the magnitude of $v_1$ for charged…
Jet quenching in the matter created in high energy nucleus-nucleus collisions provides a tomographic tool to probe the medium properties. Recent experimental results on jet production at the Relativistic Heavy-Ion Collider (RHIC) are…
Ultra-peripheral collisions (UPCs) of ions allow us to study photonuclear and two-photon interactions at energies above those available at fixed target accelerators. For heavy ions, the couplings are large enough so that multi-photon…