Multilayer Perceptron Models for Band Diagram Prediction in bi-dimensional Photonic Crystals - Da Silva Ferreira, Adriano; Nardel Malheiros Silveira, Gilliard [UNESP]; Hernandez Figueroa, Hugo Enrique (Institute of Electrical and Electronics Engineers (IEEE), 2019)
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.
Keywords: multilayer perceptron; photonic band gap; photonic crystal; prediction