梯度下降
极化(电化学)
计算机科学
光子学
硅光子学
算法
光学
物理
人工神经网络
机器学习
物理化学
化学
作者
Minglei Ma,Hossam A. Shoman,Keyi Tang,Sudip Shekhar,Nicolas A. F. Jaeger,Lukas Chrostowski
出处
期刊:Optics Express
[Optica Publishing Group]
日期:2020-01-03
卷期号:28 (2): 1885-1885
被引量:49
摘要
We demonstrate greedy linear descent-based, basic gradient descent-based, two-point step size gradient descent-based, and two-stage optimization method-based automated control algorithms and examine their performance for use with a silicon photonic polarization receiver. With an active feedback loop control process, time-varying arbitrary polarization states from an optical fiber can be automatically adapted and stabilized to the transverse-electric (TE) mode of a single-mode silicon waveguide. Using the proposed control algorithms, we successfully realize automated adaptations for a 10 Gb/s on-off keying signal in the polarization receiver. Based on the large-signal measurement results, the control algorithms are examined and compared with regard to the iteration number and the output response. In addition, we implemented a long-duration experiment to track, adapt, and stabilize arbitrary input polarization states using the two-point step size gradient descent-based and two-stage optimization method-based control algorithms. The experimental results show that these control algorithms enable the polarization receiver to achieve real-time and continuous polarization management.
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