Estimation of critical behavior from the density of states in classical statistical models

A. Malakis, A. Peratzakis, Nikolaos Fytas

    Research output: Contribution to journalArticle

    54 Citations (Scopus)


    We present a simple and efficient approximation scheme which greatly facilitates the extension of Wang-Landau sampling (or similar techniques) in large systems for the estimation of critical behavior. The method, presented in an algorithmic approach, is based on a very simple idea, familiar in statistical mechanics from the notion of thermodynamic equivalence of ensembles and the central limit theorem. It is illustrated that we can predict with high accuracy the critical part of the energy space and by using this restricted part we can extend our simulations to larger systems and improve the accuracy of critical parameters. It is proposed that the extensions of the finite-size critical part of the energy space, determining the specific heat, satisfy a scaling law involving the thermal critical exponent. The method is applied successfully for the estimation of the scaling behavior of specific heat of both square and simple cubic Ising lattices. The proposed scaling law is verified by estimating the thermal critical exponent from the finite-size behavior of the critical part of the energy space. The density of states of the zero-field Ising model on these lattices is obtained via a multirange Wang-Landau sampling.
    Original languageEnglish
    Article number066128
    JournalPhysical Review E
    Publication statusPublished - 22 Dec 2004

    Bibliographical note

    The full text is currently unavailable on the repository.


    Dive into the research topics of 'Estimation of critical behavior from the density of states in classical statistical models'. Together they form a unique fingerprint.

    Cite this