Direction dependent Point spread function reconstruction for Multi-Conjugate Adaptive Optics on Giant Segmented Mirror Telescopes

TL;DR

This paper introduces a new algorithm for reconstructing the spatially varying point spread function in multi-conjugate adaptive optics systems for giant segmented mirror telescopes, improving image correction over wide fields.

Contribution

It combines existing algorithms for PSF reconstruction and atmospheric tomography to produce a direction-dependent PSF reconstruction method tailored for GSMTs.

Findings

Qualitative agreement with simulated PSFs

Efficient runtime and memory usage

Effective correction over wide fields of view

Abstract

Modern Giant Segmented Mirror Telescopes (GSMT) like the Extremely Large Telescope (ELT), currently under construction depend heavily on Adaptive Optics (AO) systems to correct for atmospheric turbulence. To be able to correct wider fields of view (FoV), Multi-Conjugate Adaptive Optics (MCAO) systems were introduced, which use multiple guide stars to obtain an almost uniform correction over the FoV. However, a residual blur remains in the astronmical images due to the time delay stemming from the wavefront sensor (WFS) integration time and temporal response of the deformable mirror(s) (DM). This results in a blur which can be mathematically described by a convolution of the true image with the point spread function (PSF). Due to the nature of the atmosphere and its correction, the PSF is spatially varying. In this paper, we present an algorithm for MCAO PSF reconstruction adapted to the needs of GSMTs in a storage efficient way. In particular, the PSF reconstruction algorithm for Single Conjugate Adaptive Optics (SCAO) from [40] is combined with an algorithm for atmospheric tomography from [33] to obtain a direction dependent reconstruction of the post-AO PSF. Results obtained in an end-to-end simulation tool show qualitatively good reconstruction of the PSF compared to the PSF calculated directly from the simulated incoming wavefront. Furthermore, the used algorithm has a reasonable runtime and memory consumption.