Design of photonic crystals and binary supergratings using Boolean particle swarm optimization
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Date
2008-09-02T18:06:27Z
Authors
Afshinmanesh, Farzaneh
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Abstract
Photonic crystals (PCs) and binary supergratings (BSGs) with large refractive index steps are promising structures for designing new compact optical devices. This thesis presents an inverse design tool in these two important areas of photonics. The
tool consists of an optimization module and a simulation engine. Due to the binary
nature of PCs and BSGs, Boolean particle swarm optimization (Boolean PSO), a recently proposed binary stochastic optimization algorithm, is used in the optimization module. The simulation engine, on the other hand, is chosen according to the structure to be modeled. The proposed inverse design tool has been used to design
a very low F-number photonic crystal lens and compact BSG filters for applications
such as wavelength-division multiplexing, tunable lasers and intrachip optical networks. The inverse design tool allows designing optical filters with almost arbitrary wavelength filtering, in addition the proposed filters are more compact than previous demonstrations of BSG. Furthermore, it is found that Boolean PSO outperforms Genetic Algorithm (GA) as an optimization technique for use in the inverse design tool developed in this thesis.
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photonics