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Local, hierarchic, and iterative reconstructors for adaptive optics

MacMartin, Douglas G. (2003) Local, hierarchic, and iterative reconstructors for adaptive optics. Journal of the Optical Society of America A, 20 (6). pp. 1084-1093. ISSN 1084-7529.

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Adaptive optics systems for future large optical telescopes may require thousands of sensors and actuators. Optimal reconstruction of phase errors using relative measurements requires feedback from every sensor to each actuator, resulting in computational scaling for n actuators of n^2 . The optimum local reconstructor is investigated, wherein each actuator command depends only on sensor information in a neighboring region. The resulting performance degradation on global modes is quantified analytically, and two approaches are considered for recovering "global" performance. Combining local and global estimators in a two-layer hierarchic architecture yields computations scaling with n^4/3 ; extending this approach to multiple layers yields linear scaling. An alternative approach that maintains a local structure is to allow actuator commands to depend on both local sensors and prior local estimates. This iterative approach is equivalent to a temporal low-pass filter on global information and gives a scaling of n^3/2 . The algorithms are simulated by using data from the Palomar Observatory adaptive optics system. The analysis is general enough to also be applicable to active optics or other systems with many sensors and actuators.

Item Type:Article
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MacMartin, Douglas G.0000-0003-1987-9417
Additional Information:© 2003 Optical Society of America Received September 6, 2002; revised manuscript received January 31, 2003; accepted January 31, 2003
Subject Keywords:Adaptive optics; Astronomical optics
Issue or Number:6
Record Number:CaltechAUTHORS:MACMjosaa03
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:6757
Deposited By: Archive Administrator
Deposited On:20 Dec 2006
Last Modified:02 Oct 2019 23:35

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