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通过优化腔品质因数乘积的机器学习方法设计的低于100纳瓦阈值的拉曼硅激光器。

Sub-100-nW-threshold Raman silicon laser designed by a machine-learning method that optimizes the product of the cavity Q-factors.

作者信息

Kawakatsu Taro, Asano Takashi, Noda Susumu, Takahashi Yasushi

出版信息

Opt Express. 2021 May 24;29(11):17053-17068. doi: 10.1364/OE.423470.

DOI:10.1364/OE.423470
PMID:34154256
Abstract

Raman silicon lasers based on photonic crystal nanocavities with a threshold of several hundred microwatts for continuous-wave lasing have been realized. In particular, the threshold depends on the degree of confinement of the excitation light and the Raman scattering light in the two nanocavity modes. Here, we report lower threshold values for Raman silicon nanocavity lasers achieved by increasing the quality (Q) factors of the two cavity modes. By using an optimization method based on machine learning, we first increase the product of the two theoretical Q values by a factor of 17.0 compared to the conventional cavity. The experimental evaluation demonstrates that, on average, the actually achieved product is more than 2.5 times larger than that of the conventional cavity. The input-output characteristic of a Raman laser with a threshold of 90 nW is presented and the lowest threshold obtained in our experiments is 40 nW.

摘要

基于光子晶体纳米腔的拉曼硅激光器已实现连续波激射阈值为几百微瓦。特别是,阈值取决于两种纳米腔模式中激发光和拉曼散射光的限制程度。在此,我们报告通过提高两种腔模式的品质(Q)因数实现了拉曼硅纳米腔激光器的更低阈值。通过使用基于机器学习的优化方法,与传统腔相比,我们首先将两个理论Q值的乘积提高了17.0倍。实验评估表明,实际实现的乘积平均比传统腔大2.5倍以上。给出了阈值为90 nW的拉曼激光器的输入-输出特性,我们实验中获得的最低阈值为40 nW。

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Sub-100-nW-threshold Raman silicon laser designed by a machine-learning method that optimizes the product of the cavity Q-factors.通过优化腔品质因数乘积的机器学习方法设计的低于100纳瓦阈值的拉曼硅激光器。
Opt Express. 2021 May 24;29(11):17053-17068. doi: 10.1364/OE.423470.
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