Direction dependent point spread function reconstruction for multi-conjugate adaptive optics on giant segmented mirror telescopes

Abstract

Modern Giant Segmented Mirror Telescopes (GSMTs) like the Extremely Large Telescope 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 astronomical images due to tomographic, fitting and bandwidth errors. This results in a blur, which can mathematically be described by a convolution of the true image with a point spread function (PSF). Due to the nature of the turbulent atmosphere and its correction, the PSF is spatially varying. The PSF serves as a quality measure for the science images and therefore needs to be known as accurately as possible.In this paper, we present an algorithm for MCAO PSF reconstruction adapted to the needs of GSMTs focused on estimating the contribution of the tomographic and generalized fitting error to the PSF. In particular, the PSF reconstruction algorithm for Single Conjugate Adaptive Optics by Wagner et al., (2018) is combined with an algorithm for atmospheric tomography by Saxenhuber and Ramlau, (2016) to obtain a direction dependent reconstruction of the post-AO PSF.Results obtained in an end-to-end simulation tool show a qualitatively good reconstruction of the PSF compared to the PSF calculated directly from the simulated incoming wavefront.