Evaluation of memory effects at phase transitions and during relaxation processes

TL;DR

This paper models phase transition dynamics using a non-stationary Generalized Langevin Equation with memory effects, linking the memory kernel to observable quantities like induction time and transition duration, validated through molecular dynamics simulations.

Contribution

It introduces a method to relate the extent of memory effects in phase transitions to experimentally observable quantities, supported by simulations of various model systems.

Findings

Memory kernel extent correlates with transition duration.

Distribution of induction times does not significantly affect the kernel.

Model systems' behavior aligns with the theoretical predictions.

Abstract

We propose to describe the dynamics of phase transitions in terms of a non-stationary Generalized Langevin Equation for the order parameter. By construction, this equation is non-local in time, i.e.~it involves memory effects whose intensity is governed by a memory kernel. In general, it is a hard task to determine the physical origin and the extent of the memory effects based on the underlying microscopic equations of motion. Therefore we propose to relate the extent of the memory kernel to quantities that are experimentally observed such as the induction time and the duration of the phase transformation process. Using a simple kinematic model, we show that the extent of the memory kernel is positively correlated with the duration of the transition and of the same order of magnitude, while the distribution of induction times does not have an effect. This observation is tested at the example of several model systems, for which we have run Molecular Dynamics simulations: a modified Potts-model, a dipole gas, an anharmonic spring in a bath and a nucleation problem. All these cases are shown to be consistent with the simple theoretical model.