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

Nikolaos G. Fytas, A. Malakis

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6 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)39-43
JournalThe European Physical Journal B - Condensed Matter and Complex Systems
Issue number1-2
Publication statusPublished - 8 Feb 2006


Bibliographical note

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  • 05.70.Jk Critical point phenomena
  • 64.60.Fr Equilibrium properties near critical points
  • critical exponents
  • 75.10.Hk Classical spin models
  • 75.50.Lk Spin glasses and other random magnets

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