Dynamic Coarse-Graining of Linear and Non-Linear Systems: Mori-Zwanzig Formalism and Beyond

TL;DR

This paper explores how non-linear interactions affect dynamic coarse graining in complex systems, using a projection operator formalism and simulations to derive generalized Langevin equations and analyze the impact of non-linearities.

Contribution

It introduces a systematic comparison of linear and non-linear coarse-graining procedures, demonstrating the importance of non-linear projections for accurate dynamics reconstruction.

Findings

Non-Gaussian parameters are not correctly reproduced by linear projections.

Non-linear projections improve the accuracy of generalized Langevin equations.

Anharmonic coupling introduces additional trap-dependent contributions to the memory kernel.

Abstract

To investigate the impact of non-linear interactions on dynamic coarse graining, we study a simplified model system, featuring a tracer particle in a complex environment. Using a projection operator formalism and computer simulations, we systematically derive generalized Langevin equations describing the dynamics of this particle. We compare different kinds of linear and non-linear coarse-graining procedures to understand how non-linearities enter reconstructed generalized Langevin equations and how they influence the coarse-grained dynamics. For non-linear external potentials, we show analytically and numerically that the non-Gaussian parameter and the incoherent intermediate scattering function will not be correctly reproduced by the generalized Langevin equation if a linear projection is applied. This, however, can be overcome by using non-linear projection operators. We also study anharmonic coupling between the tracer and the environment and demonstrate that the reconstructed memory kernel develops an additional trap-dependent contribution. Our study highlights some open challenges and possible solutions in dynamic coarse graining.