Neural-network quantum states at finite temperature
Disordered Systems and Neural Networks
2020-03-18 v1 Quantum Gases
Quantum Physics
Abstract
We propose a method to obtain the thermal-equilibrium density matrix of a many-body quantum system using artificial neural networks. The variational function of the many-body density matrix is represented by a convolutional neural network with two input channels. We first prepare an infinite-temperature state, and the temperature is lowered by imaginary-time evolution. We apply this method to the one-dimensional Bose-Hubbard model and compare the results with those obtained by exact diagonalization.
Cite
@article{arxiv.1911.02774,
title = {Neural-network quantum states at finite temperature},
author = {Naoki Irikura and Hiroki Saito},
journal= {arXiv preprint arXiv:1911.02774},
year = {2020}
}
Comments
6 pages, 3 figures