斯太尔率
自适应光学
光学
超音速
混合(物理)
计算机科学
光学像差
梯度下降
随机梯度下降算法
变形镜
波前
物理
机械
人工智能
人工神经网络
量子力学
作者
Qiong Gao,Zongfu Jiang,Shihe Yi,Wenke Xie,Liao Tian-He
出处
期刊:Applied Optics
[Optica Publishing Group]
日期:2012-06-07
卷期号:51 (17): 3922-3922
被引量:23
摘要
We describe an adaptive optics (AO) system for correcting the aero-optical aberration of the supersonic mixing layer and test its performance with numerical simulations. The AO system is based on the measurement of distributed Strehl ratios and the stochastic parallel gradient descent (SPGD) algorithm. The aero-optical aberration is computed by the direct numerical simulation of a two-dimensional supersonic mixing layer. When the SPGD algorithm is applied directly, the AO cannot give effective corrections. This paper suggests two strategies to improve the performance of the SPGD algorithm for use in aero-optics. The first one is using an iteration process keeping finite memory, and the second is based on the frozen hypothesis. With these modifications, the performance of AO is improved and the aero-optical aberration can be corrected to some noticeable extent. The possibility of experimental implementation is also discussed.
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