3 citations · 3 across the 5 of their papers we have counts for
5 papers
Parton Fragmentation Functions Extracted with a Physics-Informed Neural Network
Si-Wei Dai, Fu-Peng Li, Long-Gang Pang +3
Reliable predictions of many high-energy strong interaction processes rely heavily on the non-perturbative parton fragmentation functions (FFs) extracted from existing experimental…
Impact of Initial-State Nuclear and Sub-Nucleon Structures on Ultra-Central Puzzle in Heavy Ion Collisions
Qi Wang, Long-Gang Pang, Xin-Nian Wang
Hydrodynamic models fail to describe the near-equal ratio observed in ultra-central heavy-ion collisions, despite their success in other centrality classes. This discrepa…
A Novel Deep Learning Method for Detecting Nucleon-Nucleon Correlations
Yu-Jing Huang, Zhu Meng, Long-Gang Pang +1
This study investigates the impact of nucleon-nucleon correlations on heavy-ion collisions using the hadronic transport model SMASH in GeV +$^…
Effects of Initial Nucleon-Nucleon Correlations on Light Nuclei Production in Au+Au Collisions at GeV
Qian-Ru Lin, Yu-Jing Huang, Long-Gang Pang +2
Light nuclei production in heavy-ion collisions serves as a sensitive probe of the QCD phase structure. In coalescence models, triton () and deuteron () yields depend on…
Report from the A.I. For Nuclear Physics Workshop
Paulo Bedaque, Amber Boehnlein, Mario Cromaz +15
This report is an outcome of the workshop "AI for Nuclear Physics" held at Thomas Jefferson National Accelerator Facility on March 4-6, 2020. The workshop brought together 184 scie…