- 著者
- Haruka Yamada Akira Imakura Tetsuya Sakurai
- 出版者
- The Japan Society for Industrial and Applied Mathematics
- 雑誌
- JSIAM Letters (ISSN:18830609)
- 巻号頁・発行日
- vol.10, pp.61-64, 2018 (Released:2018-10-25)
- 参考文献数
- 8
Tensor renormalization group (TRG) is a coarse-graining algorithm for approximating the partition function using a tensor network in the field of elementary particle physics. Although the computational cost of TRG can be reduced using a randomized singular value decomposition, its computation time is still large. In this paper, we propose a cost-efficient cutoff method for calculating TRG by truncating small tensor elements. Numerical experiments showed that the proposed method is faster than the conventional one without degrading accuracy.