Adaptive Boundaries in Multiscale Simulations

TL;DR

This paper introduces a novel framework for adaptive boundaries in multiscale molecular simulations, enabling dynamic adjustment of high-resolution regions to optimize accuracy and computational efficiency.

Contribution

It derives the Hamiltonian and distribution function for adaptive boundaries and proposes an efficient sampling algorithm for their dynamic adjustment.

Findings

Successfully applied to peptide in solvent simulation

Demonstrated improved efficiency over fixed boundaries

Maintained accuracy in molecular property predictions

Abstract

Combined-resolution simulations are an effective way to study molecular properties across a range of length- and time-scales. These simulations can benefit from adaptive boundaries that allow the high-resolution region to adapt (change size and/or shape) as the simulation progresses. The number of degrees of freedom required to accurately represent even a simple molecular process can vary by several orders of magnitude throughout the course of a simulation, and adaptive boundaries react to these changes to include an appropriate but not excessive amount of detail. Here, we derive the Hamiltonian and distribution function for such a molecular simulation. We also design an algorithm that can efficiently sample the boundary as a new coordinate of the system. We apply this framework to a mixed explicit/continuum representation of a peptide in solvent. We use this example to discuss the conditions necessary for a successful implementation of adaptive boundaries that is both efficient and accurate in reproducing molecular properties.