Deep Learning enabled Forward Modeling and Inverse Design of Integrated Nanophotonic Gratings

Hussaina Ali Akbar; Anusha Rehman; Zeeshan Karim; Ahmad Usman; Syed Hasan Asim

doi:10.1364/FIO.2021.JTh5A.100

Frontiers in Optics + Laser Science 2021
Technical Digest Series (Optica Publishing Group, 2021),
paper JTh5A.100
•https://doi.org/10.1364/FIO.2021.JTh5A.100

Deep Learning enabled Forward Modeling and Inverse Design of Integrated Nanophotonic Gratings

Hussaina Ali Akbar, Anusha Rehman, Zeeshan Karim, Ahmad Usman, and Syed Hasan Asim

Frontiers in Optics 2021

Washington, DC United States
1–4 November 2021
ISBN: 978-1-55752-308-2

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Joint Poster Session III (JTh5A)

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H. A. Akbar, A. Rehman, Z. Karim, A. Usman, and S. H. Asim, "Deep Learning enabled Forward Modeling and Inverse Design of Integrated Nanophotonic Gratings," in Frontiers in Optics + Laser Science 2021, C. Mazzali, T. (T.-C.) Poon, R. Averitt, and R. Kaindl, eds., Technical Digest Series (Optica Publishing Group, 2021), paper JTh5A.100.

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Abstract

We demonstrate deep learning enabled forward modeling and inverse design of integrated silicon nanophotonic grating. Predicted response by the forward modeling and predicted response and geometries by inverse design algorithm are shown with a prediction mean-square-error of the order of 10⁻⁴.

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