• DocumentCode
    1436126
  • Title

    The multicanonical Monte Carlo method

  • Author

    Gubernatis, Jim ; Hatano, Naomichi

  • Author_Institution
    Los Alamos National Laboratory
  • Volume
    2
  • Issue
    2
  • fYear
    2000
  • Firstpage
    95
  • Lastpage
    102
  • Abstract
    In recent years, several new Monte Carlo methods have proven to be very effective for sampling from multimodal energy landscapes, like those found near a first-order phase transition or in a glassy material. In this column, we will summarize the theoretical structure of one of these methods, the multicanonical method,1,2 as it is perhaps the most enigmatic of the new algorithms. Special emphasis will be on the manner by which it is an importance-sampling method.
  • Keywords
    Boltzmann distribution; Clustering algorithms; Glass; Histograms; Modeling; Monte Carlo methods; Physics; Polymers; Sampling methods; Temperature;
  • fLanguage
    English
  • Journal_Title
    Computing in Science & Engineering
  • Publisher
    ieee
  • ISSN
    1521-9615
  • Type

    jour

  • DOI
    10.1109/MCISE.2000.5427643
  • Filename
    5427643