Accurate estimation of dynamical quantities for nonequilibrium nanoscale system

TL;DR

This paper introduces a new theoretical method to accurately estimate dynamical quantities in nanoscale systems by constructing auxiliary paths, significantly reducing sampling requirements and validated through molecular dynamics simulations and experiments.

Contribution

A novel theory constructing auxiliary paths for each real path to improve statistical efficiency in estimating nanoscale dynamical quantities.

Findings

Achieved 0.2 μm/s accuracy in nanoscale flow with <0.1 relative error.

Reduced sample size by 12 orders of magnitude compared to traditional methods.

Validated thermolubric behavior of water on self-assembled surfaces experimentally.

Abstract

Fluctuations of dynamical quantities are fundamental and inevitable. For the booming research in nanotechnology, huge relative fluctuation comes with the reduction of system size, leading to large uncertainty for the estimates of dynamical quantities. Thus, increasing statistical efficiency, i.e., reducing the number of samples required to achieve a given accuracy, is of great significance for accurate estimation. Here we propose a theory as a fundamental solution for such problem by constructing auxiliary path for each real path. The states on auxiliary paths constitute canonical ensemble and share the same macroscopic properties with the initial states of the real path. By implementing the theory in molecular dynamics simulations, we obtain a nanoscale Couette flow field with an accuracy of 0.2 {\mu}m/s with relative standard error < 0.1. The required number of samples is reduced by 12 orders compared to conventional method. The predicted thermolubric behavior of water sliding on a self-assembled surface is directly validated by experiment under the same velocity. As the theory only assumes the system is initially in thermal equilibrium then driven from that equilibrium by an external perturbation, we believe it could serve as a general approach for extracting the accurate estimate of dynamical quantities from large fluctuations to provide insights on atomic level under experimental conditions, and benefit the studies on mass transport across (biological) nanochannels and fluid film lubrication of nanometer thickness.