Design and optimization of optical passive elements using artificial neural networks
Artificial neural networks (ANNs) have been recognized as a fast and flexible tool for microwave modeling, design, and optimization. Similarly, ANNs can be utilized in the design and optimization of photonic devices to provide fast simulation and speed up the design process. ANN models can produce great efficiency in design and optimization processes when repetitive computationally intensive simulations are required for modeling of optical passive elements using commercial tools. In this paper we explore how trained ANNs can be utilized for the fast simulation of optical passive elements, while attaining high accuracy. We present the design of four fundamental optical passive elements using commercial tools and compare the results with our trained ANN model. In all four examples illustrated, the error ranges from 0.5% to 1.7% while the simulation time is in the range of milliseconds instead of minutes or hours. Finally, we discuss possible uses of these trained ANNs with respect to the design, optimization, and statistical validation of photonic devices.
|Journal||Journal of the Optical Society of America B|
Gabr, A.M. (Ahmed M.), Featherston, C. (Chris), Zhang, C. (Chao), Bonfil, C. (Cem), Zhang, Q.J, & Smy, T. (2019). Design and optimization of optical passive elements using artificial neural networks. Journal of the Optical Society of America B, 36(4), 999–1007. doi:10.1364/JOSAB.36.000999