151 citations · 563 across the 13 of their papers we have counts for
13 papers
Further exploration of the machine-learning-based nuclear mass table
Liu Yaqi, Li Zhilong, Wang Yongjia +1
The mass of the atomic nucleus, as one of the fundamental physical quantities of the atomic nucleus, plays an important role in understanding and researching the structure of the a…
Bayesian inferences on covariant density functionals from multimessenger astrophysical data: Influences of parametrizations of density dependent couplings
Guo-Jun Wei, Jia-Jie Li, Armen Sedrakian +3
Covariant density functionals have been successfully applied to the description of finite nuclei and dense nuclear matter. These functionals are often constructed by introducing de…
Effects of sequential decay on collective flows and nuclear stopping power in heavy-ion collisions at intermediate energies
Kui Xiao, PengCheng Li, YongJia Wang +2
In this study, the rapidity distribution, collective flows, and nuclear stopping power in collisions at intermediate energies were investigate…
Decoding the nuclear symmetry energy event-by-event in heavy-ion collisions with machine learning
Yongjia Wang, Zepeng Gao, Hongliang Lü +1
Inferences of the nuclear symmetry energy from heavy-ion collisions are currently based on the comparison of measured observables and transport model simulations. Only the expectat…
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…
Machine learning the nuclear mass
Zepeng Gao, Yongjia Wang, Hongliang Lü +3
Background: The masses of about 2500 nuclei have been measured experimentally, however more than 7000 isotopes are predicted to exist in the nuclear landscape from H (Z=1) to Og (Z…
Comparison of heavy-ion transport simulations: Collision integral in a box
Ying-Xun Zhang, Yong-Jia Wang, Maria Colonna +27
Simulations by transport codes are indispensable to extract valuable physics information from heavy ion collisions. In order to understand the origins of discrepancies between diff…
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…
The influence of the symmetry energy on the cone-azimuthal emission
Yuan Gao, Gao-Chan Yong, Yong-Jia Wang +2
In the framework of the isospin-dependent Boltzmann-Uehling-Uhlenbeck transport model, effects of the symmetry energy on the evolutions of free n/p ratio and charged pion ratio in…