Loop Optimization for Tensor Network Renormalization
Author(s)
Yang, Shuo; Gu, Zheng-Cheng; Wen, Xiao-Gang
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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.
Date issued
2017-03Department
Massachusetts Institute of Technology. Department of PhysicsJournal
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
ISSN
0031-9007
1079-7114