DMRG Approach to Optimizing Two-Dimensional Tensor Networks
Strongly Correlated Electrons
2020-04-22 v2 Quantum Physics
Abstract
Tensor network algorithms have been remarkably successful solving a variety of problems in quantum many-body physics. However, algorithms to optimize two-dimensional tensor networks known as PEPS lack many of the aspects that make the seminal density matrix renormalization group (DMRG) algorithm so powerful for optimizing one-dimensional tensor networks known as matrix product states. We implement a framework for optimizing two-dimensional PEPS tensor networks which includes all of steps that make DMRG so successful for optimizing one-dimension tensor networks. We present results for several 2D spin models and discuss possible extensions and applications.
Cite
@article{arxiv.1908.08833,
title = {DMRG Approach to Optimizing Two-Dimensional Tensor Networks},
author = {Katharine Hyatt and E. M. Stoudenmire},
journal= {arXiv preprint arXiv:1908.08833},
year = {2020}
}