Multi time-step wave-front reconstruction for tomographic Adaptive-Optics systems

TL;DR

This paper introduces a multi time-step wave-front reconstruction method for tomographic adaptive optics systems, improving image quality by utilizing measurements from current and previous time-steps, and incorporating wind data for enhanced correction.

Contribution

It presents a novel multi time-step reconstruction technique that leverages wind information, significantly enhancing AO performance in large telescopes.

Findings

Increases Strehl ratio by 1.5-1.8 times in simulations.

Successfully measures wind speeds and directions with errors below 2 m/s in laboratory tests.

Improves AO correction effectiveness when using wind-aware reconstruction.

Abstract

In tomographic adaptive-optics (AO) systems, errors due to tomographic wave-front reconstruction limit the performance and angular size of the scientific field of view (FoV), where AO correction is effective. We propose a multi time-step tomographic wave-front reconstruction method to reduce the tomographic error by using the measurements from both the current and the previous time-steps simultaneously. We further outline the method to feed the reconstructor with both wind speed and direction of each turbulence layer. An end-to-end numerical simulation, assuming a multi-object AO (MOAO) system on a 30 m aperture telescope, shows that the multi time-step reconstruction increases the Strehl ratio (SR) over a scientific FoV of 10 arcminutes in diameter by a factor of 1.5--1.8 when compared to the classical tomographic reconstructor, depending on the guide star asterism and with perfect knowledge of wind speeds and directions. We also evaluate the multi time-step reconstruction method and the wind estimation method on the RAVEN demonstrator under laboratory setting conditions. The wind speeds and directions at multiple atmospheric layers are measured successfully in the laboratory experiment by our wind estimation method with errors below 2 \ms. With these wind estimates, the multi time-step reconstructor increases the SR value by a factor of 1.2--1.5, which is consistent with a prediction from end-to-end numerical simulation.