Performance of an iterative solver for atmospheric tomography on real-time hardware

Abstract

The new generation of ground-based extremely large telescopes rely on adaptive optics (AO). Many AO systems require the reconstruction of the turbulence profile, which is called atmospheric tomography. Due to the growth of telescope sizes the computational load for this problem is increasing drastically. Thus, the collaboration of state-of-the-art real-time hardware with an efficient solver that take advantage of the available hardware resources is of great importance. In this talk, we look at an iterative approach called FEWHA and its adaption to perform best on real-time hardware. We conclude our talk with a comparison between FEWHA and the frequently used MVM within the framework of MAORY.