4.6 Article

Si photonic crystal slow-light waveguides optimized through informatics technology

期刊

OPTICS LETTERS
卷 46, 期 17, 页码 4422-4425

出版社

Optica Publishing Group
DOI: 10.1364/OL.436118

关键词

-

类别

资金

  1. New Energy and Industrial Technology Development Organization [JPNP13004]

向作者/读者索取更多资源

Machine learning was used to model the photonic bands of SiO2-dadded Si lattice-shifted photonic crystal waveguides, leading to the discovery of a structure that can generate low-dispersion slow light with a group index of approximately 20 in the full C-band at telecom wavelengths. The transition structure between this waveguide and a Si-channel waveguide was designed using an evolutional optimization, resulting in a C-band average loss of 0.116 dB/transition. These results suggest the potential for further enhancing the versatility of slow light.
We modeled the photonic bands of SiO2-dadded Si lattice-shifted photonic crystal waveguides via machine learning and found a structure that generates low-dispersion slow light with a group index of approximately 20 in the full C-band at telecom wavelengths. The normalized delay-bandwidth product is as large as 0.45, which is close to the theoretical upper limit. The transition structure between this waveguide and a Si-channel waveguide was designed using an evolutional optimization, and a C-band average loss of 0.116 dB/transition was calculated. These results prove the possibility of further enhancing the versatility of slow light. (C) 2021 Optical Society of America

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据