Saved in:
| Main Author: | |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.20546 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Table of Contents:
- Stimulated by the successful descriptions of strongly correlated electron systems by fractionalized fermions, correspondence between interacting fermions and non-interacting multi-component fermions is formulated in examples of the Hubbard model. The formalism enables constructions of the neural network for a quantum many-body solver represented by coupled noninteracting fermions. After showing the exact correspondence of 1- and 2-site Hubbard model to two-component noninteracting fermions, numerical algorithm of the quantum machine learning for the Hubbard model is proposed. Benchmark for the 4-site systems is successfully presented and promising future directions as well as implications are discussed.