Wavefront super-resolution for Adaptive Optics systems on ground-based telescopes

TL;DR

This paper introduces a novel wavefront reconstruction model for adaptive optics systems using multiple wavefront sensors, leveraging turbulence statistics and regularization to improve high-resolution phase estimation in ground-based telescopes.

Contribution

It proposes a multi-WFS wavefront reconstruction method incorporating turbulence models, wind velocities, and $H_2$ regularization, advancing high-resolution phase recovery in adaptive optics.

Findings

The model effectively reconstructs high-resolution wavefronts in simulations.

Regularization improves robustness against atmospheric turbulence.

Multi-WFS approach enhances phase accuracy over single-WFS methods.

Abstract

In ground-based astronomy, Adaptive Optics (AO) is a pivotal technique, engineered to correct wavefront phase distortions and thereby enhance the quality of the observed images. Integral to an AO system is the wavefront sensor (WFS), which is crucial for detecting wavefront aberrations from guide stars, essential for phase calculations. Many models based on a single-WFS model have been proposed to obtain the high-resolution phase of the incoming wavefront. In this paper, we delve into the realm of multiple WFSs within the framework of state-of-the-art telescope setups for high-resolution phase reconstruction. We propose a model for reconstructing a high-resolution wavefront from a sequence of wavefront gradient data from multiple WFSs in a multi-frame post-processing setting. Our model is based on the turbulence statistics and the Taylor frozen flow hypothesis, incorporating knowledge of the wind velocities in atmospheric turbulence layers. We also introduce an $H_2$ regularization term, especially for atmospheric characteristics under von Karman statistics, and provide a theoretical analysis for $H^2$ space within $H^{11/6}$. Numerical simulations are conducted to demonstrate the robustness and effectiveness of our regularization term and multi-WFS reconstruction strategy under identical experimental conditions.