Out-of-equilibrium Monte Carlo simulations of a classical gas with Bose-Einstein statistics

TL;DR

This paper evaluates various Monte Carlo algorithms for simulating a classical gas with Bose-Einstein statistics, focusing on out-of-equilibrium conditions and comparing their effectiveness and results.

Contribution

It introduces a testing framework for Monte Carlo transition probabilities using a classical Bose-Einstein system and compares multiple algorithms including Glauber, Metropolis, and interpolation methods.

Findings

Glauber and Metropolis algorithms produce different mobility results.

The interpolation algorithm provides results consistent with molecular dynamics at low concentrations.

The study highlights the importance of algorithm choice in out-of-equilibrium simulations.

Abstract

Algorithms to determine transition probabilities in Monte Carlo simulations are tested using a system of classical particles with effective interactions which reproduce Bose-Einstein statistics. The system is appropriate for testing different Monte Carlo simulation methods in out-of-equilibrium situations since non equivalent results are produced. We compare mobility numerical results obtained with transition probabilities derived from Glauber and Metropolis algorithms. Then, we compare these with a recent method, the interpolation algorithm, appropriate for non-equilibrium systems in homogeneous substrata and without phase transitions. The results of mobility obtained from the interpolation algorithm are qualitatively verified with molecular dynamics simulations for low concentrations.