Speaker
Description
In the upcoming generation of Extremely Large Telescopes (ELT), with mirror diameters of up to 40 m, the impact of the turbulent atmosphere is corrected by Adaptive Optics (AO) systems, such as Single Conjugate Adaptive Optics (SCAO) within the Multi-AO Imaging Camera for Deep Observations (MICADO) of ESO's ELT. However, the quality of astronomical images still is degraded due to the time delay stemming from the wavefront sensor (WFS) integration time and adjustment of the deformable mirror(s) (DM). This results in a blur which can be mathematically described by a convolution of the original image with the point spread function (PSF) of the instrument, telescope and residual atmospheric perturbations. The PSF of an astronomical image varies with the position in the observed field, which is a crucial aspect in observations on ELTs.
We adapted the existing techniques to reconstruct the PSF from telemetry data and few atmospheric parameters only to make them feasible for the needs of MICADO and MORFEO. In particular, we use an approach for atmospheric tomography with a time series of AO telemetry data in SCAO mode. Additionally, with slight modifications, our method is feasible also for the Multi Conjugate Adatpive Opcits (MCAO) mode. As input our algorithm requires knowledge of the strength of the different turbulent atmospheric layers, their wind speeds and directions in order to perform the tomography step. To obtain the respective contribution to the PSF, we project the reconstructed layers in the direction of interest.
Our results are obtained for a simulated ELT setting two different end-to-end simulation tools as well as for on-sky data from ERIS@VLT. The reconstructed PSFs are accurate within approx 10% in the standard metrics and the reconstruction is stable for a variety of atmospheric and system parameters.
We also discuss the implementation strategy in order to have a computational and memory efficient software.
