A PCA approach to sourlas code analysis

Masato Inoue*, Koji Hukushima, Masato Okada

*この研究の対応する著者

研究成果: Article査読

3 被引用数 (Scopus)

抄録

The statistical mechanical approach is a powerful method for understanding large degrees of freedom problems, such as those related to the spin-glass model, but its application is usually limited to the class of mean-field models. We try a new general and computational approach - instead of an exact calculation of the Boltzmann distribution, we use an empirical spin state distribution obtained through simulation and extract potentially useful axes by principal component analysis (PCA). We adopted a three-body Sourlas code to evaluate this PCA approach compared with existing replica theory. The empirical spin distribution projected to these PCA axes showed distinctive patterns corresponding to the phase given by the replica method. Moreover, the first principal component roughly coincided with one of the order parameters (averaged spin) under a certain condition. These results suggest that this PCA approach could be effective even in more complicated systems that we cannot investigate analytically.

本文言語English
ページ(範囲)246-249
ページ数4
ジャーナルProgress of Theoretical Physics Supplement
157
DOI
出版ステータスPublished - 2005
外部発表はい

ASJC Scopus subject areas

  • 物理学および天文学(その他)

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