Density of states of a binary Lennard-Jones Glass

TL;DR

This paper employs a novel Monte Carlo algorithm to compute the density of states of a binary Lennard-Jones glass, enabling detailed analysis of its low-temperature thermodynamics.

Contribution

It introduces a self-consistent density of states sampling method combined with particle swaps and configurational bias techniques for glassy systems.

Findings

Energy and entropy are characterized below the mode coupling temperature.

The method provides uniform energy histograms for efficient sampling.

Results enhance understanding of low-temperature glass thermodynamics.

Abstract

We calculate the density of states of a binary Lennard-Jones glass using a recently proposed Monte Carlo algorithm. Unlike traditional molecular simulation approaches, the algorithm samples distinct configurations according to self-consistent estimates of the density of states, thereby giving rise to uniform internal-energy histograms. The method is applied to simulate the equilibrium, low-temperature thermodynamic properties of a widely studied glass former consisting of a binary mixture of Lennard-Jones particles. We show how a density-of-states algorithm can be combined with particle identity swaps and configurational bias techniques to study that system. Results are presented for the energy and entropy below the mode coupling temperature.