A Cascade Neural Network Architecture investigating Surface Plasmon   Polaritons propagation for thin metals in OpenMP
  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. 
Francesco Bonanno, Giacomo Capizzi, Grazia Lo Sciuto, Christian   Napoli, Giuseppe Pappalardo, Emiliano Tramontana
cs.NE cond-mat.mes-hall cond-mat.mtrl-sci cs.DC cs.LG