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Adaptive wavefront control with asynchronous stochastic parallel gradient descent clusters.

作者信息

Vorontsov Mikhail A, Carhart Gary W

机构信息

Computational and Information Sciences Directorate, Intelligent Optics Laboratory, Army Research Laboratory, Adelphi, Maryland 20783, USA.

出版信息

J Opt Soc Am A Opt Image Sci Vis. 2006 Oct;23(10):2613-22. doi: 10.1364/josaa.23.002613.

DOI:10.1364/josaa.23.002613
PMID:16985545
Abstract

A scalable adaptive optics (AO) control system architecture composed of asynchronous control clusters based on the stochastic parallel gradient descent (SPGD) optimization technique is discussed. It is shown that subdivision of the control channels into asynchronous SPGD clusters improves the AO system performance by better utilizing individual and/or group characteristics of adaptive system components. Results of numerical simulations are presented for two different adaptive receiver systems based on asynchronous SPGD clusters-one with a single deformable mirror with Zernike response functions and a second with tip-tilt and segmented wavefront correctors. We also discuss adaptive wavefront control based on asynchronous parallel optimization of several local performance metrics-a control architecture referred to as distributed adaptive optics (DAO). Analysis of the DAO system architecture demonstrated the potential for significant increase of the adaptation process convergence rate that occurs due to partial decoupling of the system control clusters optimizing individual performance metrics.

摘要

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