Applications of neural networks to the studies of phase transitions of two-dimensional Potts models

C. D. Li, D. R. Tan, F. J. Jiang

研究成果: 雜誌貢獻文章

12 引文 斯高帕斯(Scopus)

摘要

We study the phase transitions of two-dimensional (2D) Q-states Potts models on the square lattice, using the first principles Monte Carlo (MC) simulations as well as the techniques of neural networks (NN). We demonstrate that the ideas from NN can be adopted to study these considered phase transitions efficiently. In particular, even with a simple NN constructed in this investigation, we are able to obtain the relevant information of the nature of these phase transitions, namely whether they are first order or second order. Our results strengthen the potential applicability of machine learning in studying various states of matters. Subtlety of applying NN techniques to investigate many-body systems is briefly discussed as well.

原文英語
頁(從 - 到)312-331
頁數20
期刊Annals of Physics
391
DOIs
出版狀態已發佈 - 2018 四月

ASJC Scopus subject areas

  • Physics and Astronomy(all)

指紋 深入研究「Applications of neural networks to the studies of phase transitions of two-dimensional Potts models」主題。共同形成了獨特的指紋。

  • 引用此