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.
|Journal||The European Physical Journal B - Condensed Matter and Complex Systems|
|Publication status||Published - 8 Feb 2006|
Bibliographical noteThe full text is not available on the repository.
- 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