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arXiv · 2009.01997

Global optimization of tensor renormalization group using the corner transfer matrix

Satoshi Morita·Naoki Kawashima
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Abstract

A tensor network renormalization algorithm with global optimization based on the corner transfer matrix is proposed. Since the environment is updated by the corner transfer matrix renormalization group method, the forward-backward iteration is unnecessary, which is a time-consuming part of other methods with global optimization. In addition, a further approximation reducing the order of the computational cost of contraction for the calculation of the coarse-grained tensor is proposed. The computational time of our algorithm in two dimensions scales as the sixth power of the bond dimension while the higher-order tensor renormalization group and the higher-order second renormalization group methods have the seventh power. We perform benchmark calculations in the Ising model on the square lattice and show that the time-to-solution of the proposed algorithm is faster than that of other methods.

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Satoshi Morita, Naoki Kawashima. 2020-12-15. Global optimization of tensor renormalization group using the corner transfer matrix. https://doi.org/10.1103/physrevb.103.045131

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