Optimal design of nanoplasmonic materials using genetic algorithms as a multi-parameter optimization tool
Joseph Yelk, Maxim Sukharev, and Tamar Seideman

TL;DR
This paper presents a genetic algorithm-based method for designing nanoplasmonic materials with specific optical properties, enabling targeted control of light localization, polarization, and birefringence at the nanoscale.
Contribution
It introduces a multi-parameter genetic algorithm approach for optimizing nanoplasmonic structures with desired optical functionalities, revealing principles like symmetry breaking and dimeric constructs.
Findings
Design of nanoscale metallic lenses for focused light
Development of silver particle arrays for polarization control
Insights into structural features affecting birefringence
Abstract
An optimal control approach based on multiple parameter genetic algorithms is applied to the design of plasmonic nanoconstructs with pre-determined optical properties and functionalities. We first develop nanoscale metallic lenses that focus an incident plane wave onto a pre-specified, spatially confined spot. Our results illustrate the role of symmetry breaking and unravel the principles that favor dimeric constructs for optimal light localization. Next we design a periodic array of silver particles to modify the polarization of an incident, linearly-polarized plane wave in a desired fashion while localizing the light in space. The results provide insight into the structural features that determine the birefringence properties of metal nanoparticles and their arrays. Of the variety of potential applications that may be envisioned, we note the design of nanoscale light sources with…
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