A portable and flexible implementation of the Wang--Landau algorithm in order to determine the Density of States

TL;DR

This paper presents a flexible, Python-based implementation of the Wang--Landau algorithm for calculating the density of states, optimized with parallelization and validated on standard physical models.

Contribution

The authors develop a portable, efficient, and parallelized Python implementation of the Wang--Landau algorithm that integrates with existing energy computation libraries.

Findings

Accurately computes the density of states for well-known models

Demonstrates efficiency and flexibility of the implementation

Validates results against established systems

Abstract

In this work we develop an implementation of the Wang--Landau algorithm [Phys. Rev. Lett. \textbf{86}, 2050-2053 (2001)]. This algorithm allows us to find the density of states (DOS), a function that, for a given system, describes the proportion of states that have a certain energy. The implementation uses the Python language for the algorithm itself, and it can take advantage of any library, such as the powerful LAMMPS library, for the computation of energy. Therefore, the resulting implementation is simple and flexible without sacrificing efficiency. This implementation also considers recent developments in the parallelization of the code for faster computation. We establish the soundness and effectiveness of our implementation by studying well-known systems such as the Ising model, the Lennard--Jones and EAM solids. We have found that our implementation can find the DOS with very good precision in a reasonable amount of time. Therefore, we are equipped with a very powerful and flexible implementation that can be easily used in order to study more realistic models of matter.