The Wang-Landau Algorithm and its Applications

Abstract

The Wang–Landau algorithm is one of the Monte Carlo techniques used in statistical physics. This algorithm is very efficient for approximating the density of states of discrete spin models, especially in a large system. Nowadays, the method has been widely accepted. There have been more than 1,000 research papers citing and using this method to solve various problems such as Potts models, Ising models, protein folding, homopolymers and multidimensional integrals. In this article, we focus on the main principle of the Wang-Landau algorithm, its advantages and limitations, improved algorithms and its applications.