Multilayer Perceptron Models for Band Diagram Prediction in bi-dimensional Photonic Crystals

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Author(s):	Ferreira, Adriano da Silva ; Malheiros Silveira, Gilliard Nardel ; Hernandez Figueroa, Hugo Enrique ; IEEE Total Authors: 4
Document type:	Journal article
Source:	2018 SBFOTON INTERNATIONAL OPTICS AND PHOTONICS CONFERENCE (SBFOTON IOPC); v. N/A, p. 5-pg., 2018-01-01.
Abstract
We modeled Multilayer Perceptron (MLP) Artificial Neural Network for predicting band diagrams (BD) of bi-dimensional photonic crystals. Datasets for MLP training were created by relating geometric and material properties to BDs of triangular-and square-lattice photonic crystals. We demonstrate that fast-training MLP models are able to estimate accurate BDs and existing photonic band gaps through rapid computations. (AU)

FAPESP's process:	15/24517-8 - Photonics for next generation internet
Grantee:	Hugo Enrique Hernández Figueroa
Support Opportunities:	Research Projects - Thematic Grants