Replica-exchange Wang-Landau sampling: Pushing the limits of Monte Carlo simulations in materials sciences

2014/11/16 by Dilina Perera, Ying Wai Li, Perera, Dilina +7 · 1 citation
Materials Science · Physics and Astronomy · #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #Physics of Superconductivity and Magnetism #Theoretical and Computational Physics

paper · pdf · doi:10.48550/arxiv.1411.4212

openalex publication_date 2014/11/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/03

Abstract

We describe the study of thermodynamics of materials using replica-exchange Wang-Landau (REWL) sampling, a generic framework for massively parallel implementations of the Wang-Landau Monte Carlo method. To evaluate the performance and scalability of the method, we investigate the magnetic phase transition in body-centered cubic (bcc) iron using the classical Heisenberg model parametrized with first principles calculations. We demonstrate that our framework leads to a significant speedup without compromising the accuracy and precision and facilitates the study of much larger systems than is possible with its serial counterpart.

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