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arXiv · 1406.3149

A Cascade Neural Network Architecture investigating Surface Plasmon Polaritons propagation for thin metals in OpenMP

Francesco Bonanno·Giacomo Capizzi·Grazia Lo Sciuto·Christian Napoli·Giuseppe Pappalardo·Emiliano Tramontana
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Abstract

Surface plasmon polaritons (SPPs) confined along metal-dielectric interface have attracted a relevant interest in the area of ultracompact photonic circuits, photovoltaic devices and other applications due to their strong field confinement and enhancement. This paper investigates a novel cascade neural network (NN) architecture to find the dependance of metal thickness on the SPP propagation. Additionally, a novel training procedure for the proposed cascade NN has been developed using an OpenMP-based framework, thus greatly reducing training time. The performed experiments confirm the effectiveness of the proposed NN architecture for the problem at hand.

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Francesco Bonanno, Giacomo Capizzi, Grazia Lo Sciuto, Christian Napoli, Giuseppe Pappalardo, Emiliano Tramontana. 2014-06-12. A Cascade Neural Network Architecture investigating Surface Plasmon Polaritons propagation for thin metals in OpenMP. https://arxiv.org/abs/1406.3149

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