Relative Resolution: A Multipole Approximation at Appropriate Distances

TL;DR

This paper develops the mathematical framework of Relative Resolution, a multiscale approach that combines fine-grained and coarse-grained models based on distance, effectively capturing static and dynamic properties of complex molecular systems.

Contribution

It introduces a multipole approximation formulation of Relative Resolution applicable to all molecular systems, enhancing multiscale simulation accuracy and efficiency.

Findings

Successfully reproduces static properties of liquids

Accurately captures dynamic behavior in simulations

Generalizes to polar and nonpolar molecules

Abstract

Recently, we introduced Relative Resolution as a hybrid formalism for fluid mixtures [1]. The essence of this approach is that it switches molecular resolution in terms or relative separation: While nearest neighbors are characterized by a detailed fine-grained model, other neighbors are characterized by a simplified coarse-grained model. Once the two models are analytically connected with each other via energy conservation, Relative Resolution can capture the structural and thermal behavior of (nonpolar) multi-component and multi-phase systems across state space. The current work is a natural continuation of our original communication [1]. Most importantly, we present the comprehensive mathematics of Relative Resolution, basically casting it as a multipole approximation at appropriate distances; the current set of equations importantly applies for all systems (e.g, polar molecules). Besides, we continue examining the capability of our multiscale approach in molecular simulations, importantly showing that we can successfully retrieve not just the statics but also the dynamics of liquid systems. We finally conclude by discussing how Relative Resolution is the inherent variant of the famous "cell-multipole" approach for molecular simulations.