Towards the ground state of molecules via diffusion Monte Carlo on neural networks

Abstract

An accurate ab initio calculation of molecules is fundamental to chemical and physical sciences. Here, the authors integrate a neural-network wavefunction into the fixed-node diffusion Monte Carlo, resulting in accurate calculations of a diverse range of systems, offering insights into complex many-body electronic wave functions.