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A new comprehensive study of the 3D random-field Ising model via sampling the density of states in dominant energy subspaces

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  • N. G. Fytas
  • A. Malakis

Abstract

The three-dimensional bimodal random-field Ising model is studied via a new finite temperature numerical approach. The methods of Wang-Landau sampling and broad histogram are implemented in a unified algorithm by using the N-fold version of the Wang-Landau algorithm. The simulations are performed in dominant energy subspaces, determined by the recently developed critical minimum energy subspace technique. The random-fields are obtained from a bimodal distribution, that is we consider the discrete (±Δ) case and the model is studied on cubic lattices with sizes 4≤L ≤20. In order to extract information for the relevant probability distributions of the specific heat and susceptibility peaks, large samples of random-field realizations are generated. The general aspects of the model's scaling behavior are discussed and the process of averaging finite-size anomalies in random systems is re-examined under the prism of the lack of self-averaging of the specific heat and susceptibility of the model. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2006

Suggested Citation

  • N. G. Fytas & A. Malakis, 2006. "A new comprehensive study of the 3D random-field Ising model via sampling the density of states in dominant energy subspaces," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 50(1), pages 39-43, March.
    • Handle: RePEc:spr:eurphb:v:50:y:2006:i:1:p:39-43
    DOI: 10.1140/epjb/e2006-00033-1
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