77 citations · 112 across the 5 of their papers we have counts for
6 papers
Transport Model Comparison Studies of Intermediate-Energy Heavy-Ion Collisions
Hermann Wolter, Maria Colonna, Dan Cozma +49
Transport models are the main method to obtain physics information from low to relativistic-energy heavy-ion collisions. The Transport Model Evaluation Project (TMEP) has been purs…
Applying machine learning to determine impact parameter in nuclear physics experiments
C. Y. Tsang, Yongjia Wang, M. B. Tsang +14
Machine Learning (ML) algorithms have been demonstrated to be capable of predicting impact parameter in heavy-ion collisions from transport model simulation events with perfect det…
Finding signatures of the nuclear symmetry energy in heavy-ion collisions with deep learning
Yongjia Wang, Fupeng Li, Qingfeng Li +2
A deep convolutional neural network (CNN) is developed to study symmetry energy effects by learning the mapping between the symmetry energy and the two-dimensional…
Comparison of Heavy-Ion Transport Simulations: Mean-field Dynamics in a Box
Maria Colonna, Ying-Xun Zhang, Yong-Jia Wang +26
Within the transport model evaluation project (TMEP) of simulations for heavy-ion collisions, the mean-field response is examined here. Specifically, zero-sound propagation is cons…
Application of machine learning in the determination of impact parameter in the Sn+Sn system
Fupeng Li, Yongjia Wang, Zepeng Gao +5
Background: Sn+Sn collisions at the beam energy of 270 MeVnucleon have been performed at the Radioactive Isotope Beam Factory (RIBF) in RIKEN to investigate the…
Understanding transport simulations of heavy-ion collisions at 100 and 400 AMeV: Comparison of heavy ion transport codes under controlled conditions
Jun Xu, Lie-Wen Chen, ManYee Betty Tsang +28
Transport simulations are very valuable for extracting physics information from heavy-ion collision experiments. With the emergence of many different transport codes in recent year…