Topic: Bayesian Analysis of symmetry Energy of Nuclear Matter based on Finite Nuclear Properties

Speaker: Associate Professor Zhang Zhen (Sun Yat-sen University)

Presentation time: December 29, 2023 (Friday) 10:00-11:00 a.m

Address: Lecture Hall 211, Building 18 (Physics Building), South China University of Technology

Welcome teachers and students to attend!

School of Physics and Photonics

December 26, 2023

Abstract: Nuclear matter symmetry can represent the isospin correlation of nuclear matter equation of state, which is the frontier intersection hotspot of nuclear physics and astrophysics. In recent years, the rapid development of astronomical observations and ground-based experiments has provided abundant experimental and observational data for exploring the density correlation of symmetry energy. Bayesian inference provides a scientific and effective statistical analysis method for extracting physical information and quantifying uncertainty through experimental observations, and has been widely used in nuclear physics research. Based on the energy density functional theory of atomic nuclei, this paper introduces the constraint on the symmetry energy of saturated and subsaturated densities by using the ground state and collective excited state properties of atomic nuclei through Bayesian analysis.

Zhang Zhen, associate professor and master supervisor of the Sino-Legal School of Nuclear Engineering and Technology, Sun Yat-sen University, graduated from the School of Physics and Astronomy, Shanghai Jiao Tong University in 2015. From 2016 to 2018, he was engaged in postdoctoral research at the Cyclotron Institute of Texas A&M University in the United States. In 2018, he was introduced as an associate professor in the Hundred Talents Program of Sun Yat-sen University. He is engaged in theoretical research on the equation of state of asymmetric nuclear matter and the collision of heavy ions in medium energy, and has published more than 40 SCI papers, citing more than 1200 times.