Focal-plane wavefront sensing with high-order adaptive optics systems

TL;DR

This paper explores advanced focal-plane wavefront sensing techniques for high-resolution adaptive optics systems, comparing algorithms like Gerchberg-Saxton, Fast & Furious, and convex optimisation to improve calibration accuracy.

Contribution

It introduces and evaluates multiple phase-retrieval algorithms, highlighting the effectiveness of Fast & Furious-like methods for calibrating high-order adaptive optics systems.

Findings

Fast & Furious algorithm performs best in calibration tasks.

Convex optimisation methods are less efficient in this context.

Iterative correction converges reliably with the tested algorithms.

Abstract

We investigate methods to calibrate the non-common path aberrations at an adaptive optics system having a wavefront-correcting device working at an extremely high resolution (larger than 150x150). We use focal-plane images collected successively, the corresponding phase-diversity information and numerically efficient algorithms to calculate the required wavefront updates. The wavefront correction is applied iteratively until the algorithms converge. Different approaches are studied. In addition of the standard Gerchberg-Saxton algorithm, we test the extension of the Fast & Furious algorithm that uses three images and creates an estimate of the pupil amplitudes. We also test recently proposed phase-retrieval methods based on convex optimisation. The results indicate that in the framework we consider, the calibration task is easiest with algorithms similar to the Fast & Furious.