Applications of deep learning to relativistic hydrodynamics

Huang, HF; Xiao, BW; Liu, ZM; Wu, ZM; Mu, YD; Song, HC

Huang, HF (corresponding author), Peking Univ, Dept Phys, Beijing 100871, Peoples R China.; Huang, HF (corresponding author), Peking Univ, State Key Lab Nucl Phys & Technol, Beijing 100871, Peoples R China.; Huang, HF (corresponding author), Collaborat Innovat Ctr Quantum Matter, Beijing 100871, Peoples R China.

PHYSICAL REVIEW RESEARCH, 2021; 3 (2):

Abstract

Relativistic hydrodynamics is a powerful tool to simulate the evolution of the quark-gluon plasma in relativistic heavy-ion collisions. Using 10 000 i......

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