5 years ago

Machine Learning Phase Diagram in the Half-filled One-dimensional Extended Hubbard Model. (arXiv:1904.06032v2 [cond-mat.str-el] UPDATED)

Kazuya Shinjo, Kakeru Sasaki, Satoru Hase, Shigetoshi Sota, Satoshi Ejima, Seiji Yunoki, Takami Tohyama
We demonstrate that supervised machine learning (ML) with entanglement spectrum can give useful information for constructing phase diagram in the half-filled one-dimensional extended Hubbard model. Combining ML with infinite-size density-matrix renormalization group, we confirm that bond-order-wave phase remains stable in the thermodynamic limit.

Publisher URL: http://arxiv.org/abs/1904.06032

DOI: arXiv:1904.06032v2

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