Computing Optical Properties of Photonic Crystals by Using Multilayer Perceptron and Extreme Learning Machine

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Data

2018-09-15

Autores

Da Silva Ferreira, Adriano
Malheiros-Silveira, Gilliard Nardel [UNESP]
Hernandez-Figueroa, Hugo Enrique

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Resumo

In this paper, dispersion relations (DRs) of photonic crystals (PhCs) are computed by multilayer perceptron (MLP) and extreme learning machine (ELM) artificial neural networks (ANNs). Bi- and tri-dimensional optimized structures presenting distinct DRs and photonic band gaps (PBGs) were selected for case studies. Optical properties of a set of PhCs with similar geometries and different dimensions were calculated by an electromagnetic solver in order to provide input data for ANN training and testing. We demonstrate that simple- and fast-training ANN models are capable of providing accurate DRs' curves in a very short time.

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Dispersion relation, extreme learning machine, multilayer perceptron, photonic band gap, photonic crystal

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Journal of Lightwave Technology, v. 36, n. 18, p. 4066-4073, 2018.

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