2000/06/16 by J. Machta, Jon Machta, M. E. J. Newman +3 · 62 citations
Mathematics · Physics and Astronomy · #Algorithm #Complex Network Analysis Techniques #Computer science #Field (mathematics) #Geography #Ising model #Mathematics #Physics #Random field #Replica #Statistical physics #Statistics #Stochastic processes and statistical mechanics #Theoretical and Computational Physics #cond-mat.stat-mech
paper · pdf · doi:10.1103/physreve.62.8782
published in Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics 62(6), 8782-8789 (American Physical Society) · 24 pages, 23 figures
arxiv created 2000/06/16 · openalex publication_date 2000/12/01 · arxiv updated 2009/11/30 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
The random field Ising model with Gaussian disorder is studied using a different Monte Carlo algorithm. The algorithm combines the advantages of the replica-exchange method and the two-replica cluster method and is much more efficient than the Metropolis algorithm for some disorder realizations. Three-dimensional systems of size 24(3) are studied. Each realization of disorder is simulated at a value of temperature and uniform field that is adjusted to the phase-transition region for that disorder realization. Energy and magnetization distributions show large variations from one realization of disorder to another. For some realizations of disorder there are three well separated peaks in the magnetization distribution and two well separated peaks in the energy distribution suggesting a first-order transition.