Design of photonic crystals and binary supergratings using Boolean particle swarm optimization

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dc.contributor.authorAfshinmanesh, Farzaneh
dc.contributor.supervisorSo, Poman P.M.
dc.contributor.supervisorGordon, Reuven
dc.date.accessioned2008-09-02T18:06:27Z
dc.date.available2008-09-02T18:06:27Z
dc.date.copyright2008en_US
dc.date.issued2008-09-02T18:06:27Z
dc.degree.departmentDepartment of Electrical and Computer Engineering
dc.degree.levelMaster of Applied Science M.A.Sc.en_US
dc.description.abstractPhotonic 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.en_US
dc.identifier.urihttp://hdl.handle.net/1828/1105
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subjectphotonicsen_US
dc.subject.lcshUVic Subject Index::Sciences and Engineering::Physics::Opticsen_US
dc.titleDesign of photonic crystals and binary supergratings using Boolean particle swarm optimizationen_US
dc.typeThesisen_US

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