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

Conference ·
DOI:https://doi.org/10.1117/12.2567725· OSTI ID:1757947
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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.

Research Organization:
Argonne National Laboratory (ANL)
Sponsoring Organization:
USDOE Office of Science
DOE Contract Number:
AC02-06CH11357
OSTI ID:
1757947
Country of Publication:
United States
Language:
English

References (8)

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conference January 2016

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Related Subjects

adaptive optics
in-situ surface profiler
machine learning
neural network