Loop Optimization for Tensor Network Renormalization
Name
PhysRevLett.118.110504.pdf
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583.2 KB
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Author(s)
Yang, Shuo
Gu, Zheng-Cheng
Wen, Xiao-Gang
Date Issued
March 2017
Journal
Physical Review Letters
Publisher
American Physical Society
Citation
Yang, Shuo, Zheng-Cheng Gu, and Xiao-Gang Wen. “Loop Optimization for Tensor Network Renormalization.” Physical Review Letters 118.11 (2017): n. pag. © 2017 American Physical Society
Version
Final published version
Abstract
We introduce a tensor renormalization group scheme for coarse graining a two-dimensional tensor network that can be successfully applied to both classical and quantum systems on and off criticality. The key innovation in our scheme is to deform a 2D tensor network into small loops and then optimize the tensors on each loop. In this way, we remove short-range entanglement at each iteration step and significantly improve the accuracy and stability of the renormalization flow. We demonstrate our algorithm in the classical Ising model and a frustrated 2D quantum model.
MIT Department
Massachusetts Institute of Technology. Department of Physics
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1103/PhysRevLett.118.110504
