Neural Quantum States in Variational Monte Carlo Method: A Brief Summary
Strongly Correlated Electrons
2024-06-04 v1 Quantum Physics
Abstract
In this note, variational Monte Carlo method based on neural quantum states for spin systems is reviewed. Using a neural network as the wave function allows for a more generalized expression of various types of interactions, including highly non-local interactions, which are closely related to its non-linear activation functions. Additionally, neural networks can represent relatively complex wave functions with relatively small computational resources when dealing with higher-dimensional systems, which is undoubtedly a "flattening" advantage. In quantum-state tomography, the representation method of neural quantum states has already achieved significant results, hinting at its potential in handling larger-sized systems.
Cite
@article{arxiv.2406.01017,
title = {Neural Quantum States in Variational Monte Carlo Method: A Brief Summary},
author = {Yuntai Song},
journal= {arXiv preprint arXiv:2406.01017},
year = {2024}
}