2021/01/20 by M. A. Timirgazin, Timirgazin, M. A., А. К. Аржников +1
Computer Science · Physics and Astronomy · #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Physical sciences #Generative Adversarial Networks and Image Synthesis #Model Reduction and Neural Networks #Theoretical and Computational Physics
paper · pdf · doi:10.48550/arxiv.2101.08089
openalex publication_date 2021/01/20 · openalex created_date 2022/11/27 · openalex updated_date 2026/07/28
The restricted Boltzmann machine (RBM) is used to investigate short-range order in binary alloys. The network is trained on the data collected by Monte Carlo simulations for a simple Ising-like binary alloy model and used to calculate the Warren--Cowley short-range order parameter and other thermodynamic properties. We demonstrate that RBM not only reproduces the order parameters for the alloy concentration at which it was trained, but can also predict them for any other concentrations.