Relaxation dynamics in reverse Monte Carlo

TL;DR

This paper investigates the relaxation behavior in reverse Monte Carlo simulations, revealing both fast and slow dynamics, and introduces a metric to assess equilibration, with implications for improving convergence and analysis.

Contribution

It provides a detailed analysis of relaxation dynamics in RMC, introduces a new metric for quasi-equilibration, and characterizes slow relaxation using stretched exponential functions.

Findings

Identifies fast and slow relaxation components in RMC.

Proposes a metric to evaluate equilibration in RMC.

Characterizes slow relaxation with KWW functions.

Abstract

The reverse Monte Carlo (RMC) method is widely used in structural modelling and analysis of experimental data. More recently, RMC has been applied to the calculation of equilibrium thermodynamic properties and dynamic problems. These studies point to the importance of properly converging RMC calculations and understanding the relaxation behavior in RMC. From our detailed RMC calculations, we show that the relaxation comprises of both fast and slow aspects. A metric is introduced to assess whether fast equilibration is achieved, i.e., detailed balance condition is satisfied. The metric, essentially an equilibrium constant for RMC, is used as a test for quasi-equilibration. The slow evolution is analogous to glassy materials, i.e., it is characterized empirically in terms of the Kohlrausch-Williams-Watts (KWW) function, i.e., stretched exponentials. This feature can be exploited to estimate the convergence error or to extrapolate statistical quantities from short RMC calculations.