Multi-body wave function of ground and low-lying excited states using unornamented deep neural networks
Computational Physics
2023-12-07 v3 Other Condensed Matter
High Energy Physics - Theory
Nuclear Theory
Quantum Physics
Abstract
We propose a method to calculate wave functions and energies not only of the ground state but also of low-lying excited states using a deep neural network and the unsupervised machine learning technique. For systems composed of identical particles, a simple method to perform symmetrization for bosonic systems and antisymmetrization for fermionic systems is also proposed.
Keywords
Cite
@article{arxiv.2302.08965,
title = {Multi-body wave function of ground and low-lying excited states using unornamented deep neural networks},
author = {Tomoya Naito and Hisashi Naito and Koji Hashimoto},
journal= {arXiv preprint arXiv:2302.08965},
year = {2023}
}
Comments
23 pages, 18 figures, 8 tables; Typo of Eq. (25) corrected