From tensor-network quantum states to tensorial recurrent neural networks
We show that any matrix product state (MPS) can be exactly represented by a recurrent neural network (RNN) with a linear memory update. We generalize this RNN architecture to two-dimensional lattices using a multilinear memory update. It supports perfect sampling and wave-function evaluation in poly...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
American Physical Society
2023-07-01
|
Series: | Physical Review Research |
Online Access: | http://doi.org/10.1103/PhysRevResearch.5.L032001 |