Does the potential energy landscape of a supercooled liquid resemble a collection of traps?

TL;DR

This paper investigates whether the potential energy landscape of a supercooled liquid can be modeled as a collection of traps by extending the trap model to include interacting subsystems and comparing it with molecular dynamics simulations.

Contribution

The authors generalize the trap model to include multiple weakly interacting subsystems and validate it against molecular dynamics data for a Lennard-Jones system.

Findings

Optimal model with 3 subsystems matches simulation data

Subsystem sizes may fluctuate, indicating dynamic heterogeneities

Extended trap model captures key features of the energy landscape

Abstract

It is analyzed whether the potential energy landscape of a glass-forming system can be effectively mapped on a random model which is described in statistical terms. For this purpose we generalize the simple trap model of Bouchaud and coworkers by dividing the total system into M weakly interacting identical subsystems, each being described in terms of a trap model. The distribution of traps in this extended trap model (ETM) is fully determined by the thermodynamics of the glass-former. The dynamics is described by two adjustable parameters, one characterizing the common energy level of the barriers, the other the strength of the interaction. The comparison is performed for the standard binary mixture Lennard-Jones system with 65 particles. The metabasins, identified in our previous work, are chosen as traps. Comparing molecular dynamics simulations of the Lennard-Jones system with Monte Carlo calculations of the ETM allows one to determine the adjustable parameters. Analysis of the first moment of the waiting distribution yields an optimum agreement when choosing M=3 subsystems. Comparison with the second moment of the waiting time distribution, reflecting dynamic heterogeneities, indicates that the sizes of the subsystems may fluctuate.