activity
19942026
most citedA Multi-Phase Transport Model for Relativistic Heavy Ion Collisions

1.4k citations · 16.2k across the 224 of their papers we have counts for

collaborators
Showing 2022Show all

9 papers · 1 filter

nucl-th2022★ 18 cited

Long Range Plan: Dense matter theory for heavy-ion collisions and neutron stars

Alessandro Lovato, Travis Dore, Robert D. Pisarski +61

Since the release of the 2015 Long Range Plan in Nuclear Physics, major events have occurred that reshaped our understanding of quantum chromodynamics (QCD) and nuclear matter at l…

nucl-th2022

Nuclear Equation of State and Single-nucleon Potential from Gogny-like Energy Density Functionals Encapsulating Effects of Nucleon-nucleon Short-range Correlations

Bao-Jun Cai, Bao-An Li

Nucleon-nucleon short-range correlations (SRCs) induce a high momentum tail (HMT) in the single-nucleon momentum distribution function in cold neutron-rich matter. W…

nucl-th2022★ 25 cited

Impact of Symmetry Energy on Sound Speed and Spinodal Decomposition in Dense Neutron-Rich Matter

Nai-Bo Zhang, Bao-An Li

Using a meta model for nuclear Equation of State (EOS) with its parameters constrained by astrophysical observations and terrestrial nuclear experiments, we examine effects of nucl…

nucl-th2022★ 27 cited

Probing high-density nuclear symmetry energy with ratio in heavy-ion collisions at GeV

Gao-Chan Yong, Bao-An Li, Zhi-Gang Xiao +1

Recent beam energy scan (BES) experiments at RHIC by the STAR Collaboration (PLB {\bf 827},137003 (2022) and PRL {\bf 128}, 202303 (2022)) found that hadronic interactions dominate…

nucl-th2022★ 10 cited

Equation of State of Neutron-Rich Matter in -Dimensions

Bao-Jun Cai, Bao-An Li

Nuclear systems under constraints, with high degrees of symmetries and/or collectivities may be considered as moving effectively in spaces with reduced spatial dimensions. We first…

nucl-th2022★ 5 cited

Principal Component Analysis of Azimuthal Flow in Intermediate-Energy Heavy-Ion Reactions

Bao-An Li, Jake Richter

Principal Component Analysis (PCA) via Singular Value Decomposition (SVD) of large datasets is an adaptive exploratory method to uncover natural patterns underlying the data. Sever…