Predictive Learn and Apply: MAVIS application - Learn

摘要

The Learn and Apply reconstruction scheme uses the knowledge of atmospheric turbulence to generate a tomo-graphic reconstructor, and its performance is enhanced by the real-t ime identification of the atmosphere and the wind profile, fn this paper we propose a turbulence profiling method that is driven by the atmospheric model. The vertical intensity distribution of turbulence, wind speed and wind direction can be simultaneously estimated from the Laser Guide Star measurements. We introduce the implementation of such a method on a GPU accelerated non-linear least-squares solver, which significantly increases the computation efficiency. Finally, we demonstrate the convergence quality from numerically generated telemetry, we provide the end-to-end Adaptive Optics simulation results, and we highlight a time-to-solution analysis, all based on the MAVIS system design.