Speaker
Yongjia Wang
(Huzhou University)
Description
Our knowledge of the properties of dense nuclear matter is usually obtained indirectly via nuclear experiments, astrophysical observations, and nuclear theory calculations. Advancing our understanding of the nuclear equation of state (EOS, which is one of the most important properties and of central interest in nuclear physics) has relied on various data produced from experiments and calculations. In this talk, I will review how machine learning is revolutionizing the way we extract EOS from these data, and summarize the challenges and opportunities that come with the use ofmachine learning.
| Email Address | lzuwyj@hotmail.com |
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Primary author
Yongjia Wang
(Huzhou University)
