Deep Learning-Based Modelling of Complex Photonic Crystal Slow Light Waveguides-Reference-Cited by-同舟云学术

Deep Learning-Based Modelling of Complex Photonic Crystal Slow Light Waveguides

Published:2023-11 Issue:6: Photonic Signal Processing Volume:29 Page:1-6
ISSN:1077-260X
Container-title:IEEE Journal of Selected Topics in Quantum Electronics
language:
Short-container-title:IEEE J. Select. Topics Quantum Electron.

Author:

Chen Jianwei¹^ORCID,Hao Ran²^ORCID,Nasidi Ibrahim³,Zhang Huangjie¹,Wang Xilan¹,Jin Shangzhong¹

Affiliation:

1. Zhejiang Province Key Laboratory of Modern Measurement Technology and Instrument, College of Optical and Electronic Technology, China Jiliang University, Hangzhou, Zhejiang, China

2. College of Optical and Electronic Technology, China JiLiang University, Hangzhou, Zhejiang, China

3. College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, Zhejiang, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics

Link

http://xplorestaging.ieee.org/ielx7/2944/9967370/10218738.pdf?arnumber=10218738

Reference35 articles.

1. Designing synthetic optical media: photonic crystals

2. Improving Low-Dispersion Bandwidth of the Silicon Photonic Crystal Waveguides for Ultrafast Integrated Photonics

3. Experimental GVD engineering in slow light slot photonic crystal waveguides

4. Dispersion Engineering With Photonic Inverse Design

5. Inverse Design of Photonic Crystals through Automatic Differentiation

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