A study of the scaling behavior of the two-dimensional Ising model by methods of machine learning

A study of the scaling behavior of the two-dimensional Ising model by methods of machine learning Научная публикация

Журнал

Journal of Siberian Federal University. Mathematics & Physics
ISSN: 1997-1397 , E-ISSN: 2313-6022

Вых. Данные

Год: 2024, Том: 17, Номер: 2, Страницы: 238-245 Страниц : 8

Ключевые слова

machine learning, convolutional neural networks, Monte Carlo methods, Ising model, scaling, correlation length, magnetic susceptibility

Авторы

Chubarova A.A. ¹ , Mamonova M.V. ¹ , Prudnikov P.V. ²

Организации

1	Dostoevsky Omsk State University, Omsk, Russian Federation
2	Center of New Chemical Technologies BIC Boreskov Institute of Catalysis SB RAS, Omsk, Russian Federation

Информация о финансировании (2)

1	Российский научный фонд	23-22-00093
2	Министерство науки и высшего образования Российской Федерации	FWUR-2024-0039

In the field of condensed matter physics, machine learning methods have become an increasingly important instrument for researching phase transitions. Here we present a method for calculating the universal characteristics of spin models using an Ising model that is exactly solvable in two dimensions. The method is based on a convolutional neural network (CNN) with controlled learning. The scaling functions prove the continuing type of phase transition for the 2D Ising model. As a result of the proposed technique, it has been possible to calculate correlation length directly

Chubarova A.A. , Mamonova M.V. , Prudnikov P.V.
A study of the scaling behavior of the two-dimensional Ising model by methods of machine learning
Journal of Siberian Federal University. Mathematics & Physics. 2024. V.17. N2. P.238-245. WOS РИНЦ

Поступила в редакцию:	10 сент. 2023 г.
Принята к публикации:	27 янв. 2024 г.

Web of science:	WOS:001203106200009
РИНЦ:	66229553

БД	Цитирований
РИНЦ	1