Machine learning control of an elliptically bent hard X-ray mirror

被引:2
|
作者
Mashrafi, Sheikh [1 ]
Harder, Ross [1 ]
Shi, Xianbo [1 ]
Shu, Deming [1 ]
Qiao, Zhi [1 ]
Wyman, Max [1 ]
Mooney, Tim [1 ]
Anton, Jayson [1 ]
Kearney, Steven [1 ]
Rebuffi, Luca [1 ]
Qian, Jun [1 ]
Shi, Bing [1 ]
Assoufid, Lahsen [1 ]
机构
[1] Argonne Natl Lab, Adv Photon Source, 9700 S Cass Ave, Lemont, IL 60439 USA
关键词
Adaptive optics; in-situ surface profiler; machine learning; neural network; ADAPTIVE OPTICS;
D O I
10.1117/12.2567725
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This article showcases the high-resolution control of an elliptically bent hard X-ray mirror optics at the Advanced Photon Source. The mirror uses a compact laminar flexure bending mechanism to achieve elliptical shapes covering a large range of focal distances. An array of capacitive sensors are used as a surface profiler for in-situ monitoring of the mirror shape. Machine learning and control techniques were used to change the mirror shape and focus the incident X-ray at predefined focal planes. The mirror surface shape error can be controlled to be within 40 nm rms with high repeatability. This technique gives the capability to focus incident X-ray beam within a range of focal distances corresponding to shape deformation range of a mirror optics. This work would be beneficial for controlling similar adaptive optics for multiple adaptive optics systems.
引用
收藏
页数:9
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