A real neural network state for quantum chemistry
Quantum Physics
2023-01-11 v1
Abstract
The restricted Boltzmann machine (RBM) has been successfully applied to solve the many-electron Schrdinger equation. In this work we propose a single-layer fully connected neural network adapted from RBM and apply it to study ab initio quantum chemistry problems. Our contribution is two-fold: 1) our neural network only uses real numbers to represent the real electronic wave function, while we obtain comparable precision to RBM for various prototypical molecules; 2) we show that the knowledge of the Hartree-Fock reference state can be used to systematically accelerate the convergence of the variational Monte Carlo algorithm as well as to increase the precision of the final energy.
Cite
@article{arxiv.2301.03755,
title = {A real neural network state for quantum chemistry},
author = {Yangjun Wu and Xiansong Xu and Dario Poletti and Yi Fan and Chu Guo and Honghui Shang},
journal= {arXiv preprint arXiv:2301.03755},
year = {2023}
}