Extending neural network quantum Monte Carlo towards condensed matter physics problems
Ji Chen, Peking University
I will discuss the latest developments to generalize the neural network wavefunction based methods to solid systems, and further improve the accuracy via diffusion Monte Carlo. I will discuss the implementation of effective core potentials within the neural network wavefunction to further reduce the computational cost of realistic chemical systems. How to compute interatomic force will also be discussed.