Triad second renormalization group

Abstract

We propose a second renormalization group (SRG) in the triad representation of tensor networks. The SRG method improves two parts of the triad tensor renormalization group, which are the decomposition of intermediate tensors and the preparation of isometries, taking the influence of environment tensors into account. Every fundamental tensor including environment tensor is given as a rank-3 tensor, and the computational cost of the proposed algorithm scales with $\mathcal{O}({\chi }^5)$ employing the randomized SVD where $\chi$ is the bond dimension of tensors. We test this method in the classical Ising model on the two dimensional square lattice, and find that numerical results are obtained in good accuracy for a fixed computational time.

arXiv comment29 pages, 27 figures

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Cited by in corpus (9)

• Toward tensor renormalization group study of three-dimensional non-Abelian gauge theory
• Critical endpoint of (3+1)-dimensional finite density $Z_3$ gauge-Higgs model with tensor renormalization group
• Improving efficiency of the path optimization method for a gauge theory
• Multi-impurity method for the bond-weighted tensor renormalization group
• Three-dimensional real space renormalization group with well-controlled approximations
• Quantum Field Theories with Tensor Renormalization Group
• Spectroscopy with the tensor renormalization group method
• Essential difference between 2D and 3D from the perspective of real-space renormalization group
• Tensor network approach to 2D Yang-Mills theories