Artificial neural networks approach for the analysis and synthesis of metamaterial waveguides

Anderson Dourado Sisnando; Juarez Caetano da Silva; V. F. Rodriguez-Esquerre; Zhaowei Liu

doi:10.1117/12.2567533

20 August 2020 Artificial neural networks approach for the analysis and synthesis of metamaterial waveguides

Anderson Dourado Sisnando, Juarez Caetano da Silva, V. F. Rodriguez-Esquerre, Zhaowei Liu

Proceedings Volume 11460, Metamaterials, Metadevices, and Metasystems 2020; 1146029 (2020) https://doi.org/10.1117/12.2567533
Event: SPIE Nanoscience + Engineering, 2020, Online Only

Conference Poster

Abstract

We implement an efficient artificial neural network (ANN), for the analysis and rapid inverse design of dielectric and planar hyperbolic metamaterial based waveguides operating in the infrared wavelength (λ) telecommunication spectrum (1200nm to 1700nm), where long propagation length and high confinement of the fields are desirables. We consider waveguides made of alternate metal-dielectric layers anisotropic claddings, surrounding a homogeneous core. The main device propagation properties to be computed by the proposed ANN are the length propagation (L) and the penetration depth (dp) associated to every design (outputs of the ANN). They are function of the λ excitation, metal (nm), dielectric (nd) refractive indexes of the layers and core refractive index (nc) as physical parameters. Our approach demonstrates high behavior prediction, design accuracy and minimal modeling parameters.

Conference Presentation

Citation Download Citation

Anderson Dourado Sisnando, Juarez Caetano da Silva, V. F. Rodriguez-Esquerre, and Zhaowei Liu "Artificial neural networks approach for the analysis and synthesis of metamaterial waveguides", Proc. SPIE 11460, Metamaterials, Metadevices, and Metasystems 2020, 1146029 (20 August 2020); https://doi.org/10.1117/12.2567533

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