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

被引：3

作者：

Song, Yuchen ^{[1
]}

Wang, Danshi ^{[1
]}

Ye, Han ^{[1
]}

Qin, Jun ^{[2
]}

Zhang, Min ^{[1
]}

机构：

[1] Beijing Univ Posts & Telecommun, State Key Lab Informat Photon & Opt Commun, Beijing 100876, Peoples R China

[2] Peking Univ, State Key Lab Adv Opt Commun Syst & Networks, Beijing 100871, Peoples R China

来源：

2020 EUROPEAN CONFERENCE ON OPTICAL COMMUNICATIONS (ECOC) | 2020年

基金：

中国国家自然科学基金;

关键词：

D O I：

10.1109/ECOC48923.2020.9333397

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页数：4

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