Fluctuation-Induced Phenomena in Nanoscale Systems: Harnessing the Power of Noise

TL;DR

This review discusses recent advances in computational modeling of fluctuation-induced phenomena like near-field heat transfer and Casimir forces, emphasizing new algorithms and predictions in complex nanostructures.

Contribution

It provides a comprehensive survey of computational techniques and recent predictions for fluctuation-induced phenomena in nanoscale systems.

Findings

Development of semi-analytical and numerical algorithms

Predictions of novel phenomena in complex geometries

Enhanced understanding of fluctuation-dissipation relations

Abstract

The famous Johnson-Nyquist formula relating noise current to conductance has a microscopic generalization relating noise current density to microscopic conductivity, with corollary relations governing noise in the components of the electromagnetic fields. These relations, known collectively in physics as fluctuation-dissipation relations, form the basis of the modern understanding of fluctuation-induced phenomena, a field of burgeoning importance in experimental physics and nanotechnology. In this review, we survey recent progress in computational techniques for modeling fluctuation-induced phenomena, focusing on two cases of particular interest: near-field radiative heat transfer and Casimir forces. In each case we review the basic physics of the phenomenon, discuss semi-analytical and numerical algorithms for theoretical analysis, and present recent predictions for novel phenomena in complex material and geometric configurations.