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37 papers · 1 filter
Deep variational free energy prediction of dense hydrogen solid at 1200K
Xinyang Dong, Hao Xie, Yixiao Chen +4
We perform deep variational free energy calculations to investigate the dense hydrogen system at 1200 K and high pressures. In this computational framework, neural networks are use…
Projected gradient descent algorithm for crystal structure relaxation under a fixed unit cell volume
Yukuan Hu, Junlei Yin, Xingyu Gao +2
This paper is concerned with crystal structure relaxation under a fixed unit cell volume, which is a step in calculating the static equations of state and form…
Performance assessment of the effective core potentials under the Fermionic neural network: first and second row elements
Mengsa Wang, Yuzhi Zhou, Han Wang
The rapid development of deep learning techniques has driven the emergence of a neural network-based variational Monte Carlo method (referred to as FermiNet), which has manifested…
Theoretical evidence of H-He demixing under Jupiter and Saturn conditions
Xiaoju Chang, Bo Chen, Qiyu Zeng +12
The immiscibility of hydrogen-helium mixture under the temperature and pressure conditions of planetary interiors is crucial for understanding the structures of gas giant planets (…
Full-scale ab initio simulations of laser-driven atomistic dynamics
Qiyu Zeng, Bo Chen, Shen Zhang +4
The coupling of excited states and ionic dynamics is the basic and challenging point for the materials response at extreme conditions. In laboratory, the intense laser produces tra…
A force-based gradient descent method for atomic structure relaxation
Yukuan Hu, Xingyu Gao, Yafan Zhao +2
Force-based algorithms for atomic structure relaxation, such as conjugate gradient methods, usually get stuck in the line minimization processes along s…