Publication: Accounting for inhomogeneous broadening in nano-optics by electromagnetic modeling based on Monte Carlo methods
Open/View Files
Date
2014
Published Version
Journal Title
Journal ISSN
Volume Title
Publisher
Proceedings of the National Academy of Sciences
The Harvard community has made this article openly available. Please share how this access benefits you.
Citation
Gudjonson, Herman, Mikhail A. Kats, Kun Liu, Zhihong Nie, Eugenia Kumacheva, and Federico Capasso. 2014. “Accounting for Inhomogeneous Broadening in Nano-Optics by Electromagnetic Modeling Based on Monte Carlo Methods.” Proceedings of the National Academy of Sciences 111 (6) (January 27): E639–E644. doi:10.1073/pnas.1323392111.
Research Data
Abstract
Many experimental systems consist of large ensembles of uncoupled or weakly interacting elements operating as a single whole; this is particularly the case for applications in nano-optics and plasmonics, including colloidal solutions, plasmonic or dielectric nanoparticles on a substrate, antenna arrays, and others. In such experiments, measurements of the optical spectra of ensembles will differ from measurements of the independent elements as a result of small variations from element to element (also known as polydispersity) even if these elements are designed to be identical. In particular, sharp spectral features arising from narrow-band resonances will tend to appear broader and can even be washed out completely. Here, we explore this effect of inhomogeneous broadening as it occurs in colloidal nanopolymers comprising self-assembled nanorod chains in solution. Using a technique combining finite-difference time-domain simulations and Monte Carlo sampling, we predict the inhomogeneously broadened optical spectra of these colloidal nanopolymers and observe significant qualitative differences compared with the unbroadened spectra. The approach combining an electromagnetic simulation technique with Monte Carlo sampling is widely applicable for quantifying the effects of inhomogeneous broadening in a variety of physical systems, including those with many degrees of freedom that are otherwise computationally intractable.
Description
Other Available Sources
Keywords
photonics, FDTD, random sampling, stochastic
Terms of Use
This article is made available under the terms and conditions applicable to Other Posted Material (LAA), as set forth at Terms of Service