Optimising Wavefront Sensing Super-Resolution in the Control of Tomographic Adaptive Optics

Abstract

In this work we propose to explore and optimise a novel concept in adaptive optics wavefront sensing. The notion being investigated is that of super-resolution, which is aimed at increasing spatial resolution in tomographic adaptive optics by introducing diversity in the alignment of different wavefront sensors. The optimisation of super-resolution requires efficient computation of the wavefront estimation error. A model of the wavefront sensor compatible with super-resolution is proposed in this paper, together with a suitable cost function to optimise the super-resolution geometry. We provide initial optimisation results verified by end-to-end simulations. In future work we will investigate the parallelisation of the optimisation routine, and alternative optimisation methods.