Inverse design of an on-chip optical response predictor enabled by a deep neural network

We proposed inverse-designed nanophotonic waveguide devices which have the desired optical responses in the wide band of 1450-1650 nm. The proposed devices have an ultra-compact size of just 1.5 µm × 3.0 µm and are designed on a silicon-on-insulator (SOI) waveguide platform. Individual nano-pixels w...

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Bibliographic Details
Published in:Optics express 2023-01, Vol.31 (2), p.2049-2060
Main Authors: Kim, Junhyeong, Neseli, Berkay, Kim, Jae-Yong, Yoon, Jinhyeong, Yoon, Hyeonho, Park, Hyo-Hoon, Kurt, Hamza
Format: Article
Language:English
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Summary:We proposed inverse-designed nanophotonic waveguide devices which have the desired optical responses in the wide band of 1450-1650 nm. The proposed devices have an ultra-compact size of just 1.5 µm × 3.0 µm and are designed on a silicon-on-insulator (SOI) waveguide platform. Individual nano-pixels with dimensions of 150 nm × 150 nm were made of either silicon or silicon dioxide, and the materials for the 200 total cells were determined using a trained deep neural network. While training the two networks, the hyperparameter optimization method was applied to make the training process efficient. We then fabricated the proposed devices using a CMOS-compatible fabrication process, and experimentally verified the fabricated device performance.
ISSN:1094-4087
1094-4087
DOI:10.1364/OE.480644