Abstract

Matching wavefront correctors and wavefront sensors by minimizing the condition number and mean wavefront variance is proposed. The particular cases of two continuous-sheet deformable mirrors and a Shack-Hartmann wavefront sensor with square packing geometry are studied in the presence of photon noise, background noise and electronics noise. Optimal number of lenslets across each actuator are obtained for both deformable mirrors, and a simple experimental procedure for optimal alignment is described. The results show that high-performance adaptive optics can be achieved even with low cost off-the-shelf Shack-Hartmann arrays with lenslet spacing that do not necessarily match those of the wavefront correcting elements.

Highlights

  • The design or selection of a wavefront corrector for an adaptive optics (AO) system is based on the spatial and temporal characteristics of the aberrations to be compensated for [1, 2]

  • One of the most noticeable features in the top six plots is that a one-actuator-to-one-lenslet configuration performs very poorly as indicated by the large condition numbers and wavefront variances

  • A surprising result illustrated by the plots, is the smooth variation of the condition number and the wavefront variance with lenslet size

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Summary

Introduction

The design or selection of a wavefront corrector for an adaptive optics (AO) system is based on the spatial and temporal characteristics of the aberrations to be compensated for [1, 2]. The matching can be achieved by minimizing the condition number of the AO response matrix and the noise propagation coefficient of the AO control matrix, provided the noise in all sensing elements is equal and uncorrelated [3,4,5,6,7]. The former is not always a valid hypothesis. The results show that, surprisingly, SH sensors with non-matching geometries can achieve comparable performances to matching ones, and that for the two DMs studied there is an optimal single range of number of SH lenslets across each actuator. It is shown that experimental minimization of the mean variance error can be used as a practical alignment method

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