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Convergence and Performance Analysis of a Particle Swarm Optimization Algorithm for Optical Tuning of Gold Nanohole
Margherita Angelini1, Luca Zagaglia1, Franco Marabelli1
1Department of Physics, University of Pavia, Via Bassi 6, 27100 Pavia, Italy.
Materials (Basel, Switzerland)
|February 24, 2024
Summary
This study optically tunes gold nanohole arrays using particle swarm optimization for precise surface plasmon resonance control. The method enhances performance for hybrid metasurfaces in various optical applications.
Area of Science:
- Plasmonics and Nanophotonics
- Metasurface Optics
- Computational Electromagnetics
Background:
- Gold nanohole arrays are hybrid metasurfaces supporting localized and propagating surface plasmons.
- Precise optical tuning is crucial for surface plasmon resonance (SPR) applications.
- Existing methods may lack the precision required for advanced SPR applications.
Purpose of the Study:
- To optically tune gold nanohole arrays using a customized particle swarm optimization (PSO) algorithm.
- To investigate PSO convergence and evolution for metasurface optimization.
- To develop a mathematical model for interpreting PSO outcomes in optical tuning.
Main Methods:
- Utilized Ansys Lumerical FDTD for optical simulations.
- Implemented a customized particle swarm optimization algorithm.
- Considered both square and triangular array configurations for gold nanohole arrays.
Main Results:
- Successfully demonstrated optical tuning of gold nanohole arrays via PSO.
- Analyzed the convergence and evolutionary behavior of the PSO algorithm.
- Developed a mathematical model to explain the PSO tuning mechanism.
Conclusions:
- Particle swarm optimization provides an effective method for precise optical tuning of gold nanohole arrays.
- The developed mathematical model aids in understanding the optimization process.
- This approach advances the design and application of hybrid metasurfaces for SPR.
