Wavelength Controllable Forward Prediction and Inverse Design of Nanophotonic Devices Using Deep Learning
arXiv:2010.15547
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.
Accepted by ECOC2020