Wavelength Controllable Forward Prediction and Inverse Design of Nanophotonic Devices Using Deep Learning
Optics
2020-11-09 v3
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.
Keywords
Cite
@article{arxiv.2010.15547,
title = {Wavelength Controllable Forward Prediction and Inverse Design of Nanophotonic Devices Using Deep Learning},
author = {Yuchen Song and Danshi Wang and Han Ye and Jun Qin and Min Zhang},
journal= {arXiv preprint arXiv:2010.15547},
year = {2020}
}
Comments
Accepted by ECOC2020