Wavefront reconstruction by machine learning using the delta rule

Details Wavefront reconstruction by machine learning using the delta rule Wavefront reconstruction by machine learning using the delta rule

May 1994

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1994spie.2201..629a&link_type=abstract

Proc. SPIE Vol. 2201, p. 629-635, Adaptive Optics in Astronomy, Mark A. Ealey; Fritz Merkle; Eds.

Physics

Optics

Scientific paper

In this paper we use phase screen models to illustrate the power of the delta rule, by obtaining the optimum reconstructor for a Shack-Hartmann sensor with just 6 subapertures in the form of pie segments. The dependence of the matrix elements and residual error on measurement noise is determined, and the accuracy compared with theoretical limits. Reconstructors for more complex problems involving time dependence and multiple laser spots are ideal applications for the method.

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