[en] We present a numerical method to compute non-equilibrium memory kernels based on experimental data or molecular dynamics simulations. The procedure uses a recasting of the non-stationary generalized Langevin equation, in which we expand the memory kernel in a series that can be reconstructed iteratively. Each term in the series can be computed based solely on knowledge of the two-time auto-correlation function of the observable of interest. We discuss how to optimize this method in order to be the most numerically convenient. As a proof of principle, we test the method on the problem of crystallization from a super-cooled Lennard-Jones melt. We analyze the nucleation and growth dynamics of crystallites and observe that the memory kernel has a time extent that is about one order of magnitude larger than the typical timescale needed for a particle to be attached to the crystallite in the growth regime.
[University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
