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Workshop: Machine Learning Multiscale Processes
Exploring Thermodynamic Behavior of Spin Glasses with Machine Learning
Vitalii Kapitan · Dmitrii Kapitan · Petr Andriushchenko
Keywords: [ Ising model ] [ neural network ] [ spin glass ]
Abstract:
In this paper, we consider the regression problem of predicting the average energy $\langle E \rangle$ as a function of temperature $T$ for spin glasses on a square lattice using several machine learning methods. Representing the spin glass as a weighted graph with exchange interactions as edges, we explored the relationship between the spatial distribution of connections and $\langle E \rangle$ using them.
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