This project is used for the paper Differentiable Programming of Isometric Tensor Network

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Deep LearningIsoTensor
Overview

Isometric Tensor Network

This project is used for the paper "Differentiable Programming of Isometric Tensor Network". (arXiv:2110.03898)

Main features:

  • Auto-gradient based isometric tensor network construction (MERA and TNR).
  • Several built-in spin models
  • Multiple optimizers and retraction methods
  • Compatible with the graduate lifting bond dimension trick
  • Dynamical switching optimizers
  • Computing scaling dimensions

In future:

  • More models, optimizers and retraction methods
  • Layers for variation structures of MERA and TNR
  • Quantum machine learning
  • ...

Dependencies

The code requires Python and PyTorch, with optional CUDA support.

Gallery

Computation process of MERA

Computation process of TNR

Comparing methods

The comparison of Evenbly-Vidal method and random mixed method in MERA. Cusps here indicate the position of lifting bond dimensions.

Scaling dimensions

The scaling dimensions extracted from TNR.
Owner
Chenhua Geng
Chenhua Geng
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