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Wavelength Controllable Forward Prediction and Inverse Design of Nanophotonic Devices Using Deep Learning | IEEE Conference Publication | IEEE Xplore

Wavelength Controllable Forward Prediction and Inverse Design of Nanophotonic Devices Using Deep Learning


Abstract:

A deep learning-based wavelength controllable forward prediction and inverse design model of nanophotonic devices is proposed. Both the target time-domain and wavelength-...Show More

Abstract:

A deep learning-based wavelength controllable forward prediction and inverse design model of nanophotonic devices is proposed. Both the target time-domain and wavelength-domain information can be utilized simultaneously, which enables multiple functions, including power splitter and wavelength demultiplexer, to be implemented efficiently and flexibly.
Date of Conference: 06-10 December 2020
Date Added to IEEE Xplore: 04 February 2021
ISBN Information:
Conference Location: Brussels, Belgium

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