Deep Variational Free Energy Approach to Dense Hydrogen.
Phys Rev Lett
; 131(12): 126501, 2023 Sep 22.
Article
em En
| MEDLINE
| ID: mdl-37802941
ABSTRACT
We developed a deep generative model-based variational free energy approach to the equations of state of dense hydrogen. We employ a normalizing flow network to model the proton Boltzmann distribution and a fermionic neural network to model the electron wave function at given proton positions. By jointly optimizing the two neural networks we reached a comparable variational free energy to the previous coupled electron-ion Monte Carlo calculation. The predicted equation of state of dense hydrogen under planetary conditions is denser than the findings of ab initio molecular dynamics calculation and empirical chemical model. Moreover, direct access to the entropy and free energy of dense hydrogen opens new opportunities in planetary modeling and high-pressure physics research.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Phys Rev Lett
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
China