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Tensor renormalization group algorithms with a projective truncation method
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DOI：10.1103/PhysRevB.99.155101.png)
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摘要
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We apply the projective truncation technique to the tensor renormalization group (TRG) algorithm in order to reduce the computational cost from O(chi(6)) to O(chi(5)), where. is the bond dimension, and propose three kinds of algorithms for demonstration. On the other hand, the technique causes a systematic error due to the incompleteness of a projector composed of isometries and in addition requires iteration steps to determine the isometries. Nevertheless, we find that the accuracy of the free energy for the Ising model on a square lattice is recovered to the level of TRG with a few iteration steps even at the critical temperature for chi = 32, 48, and 64.
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期刊
IF:
3.7
论文数:
15.4W
被引数:
41.0W
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Renormalization of tensor networks using graph-independent local truncations使用与图无关的局部截断对张量网络进行重新归一化.png)
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