Estimating effective wind speed from Gemini Planet Imager's adaptive optics data using covariance maps by Daniel M. Levinstein et al. on Wednesday 30 November

The Earth's turbulent atmosphere results in speckled and blurred images of

astronomical objects when observed by ground based visible and near-infrared

telescopes. Adaptive optics (AO) systems are employed to reduce these

atmospheric effects by using wavefront sensors (WFS) and deformable mirrors.

Some AO systems are not fast enough to correct for strong, fast, high

turbulence wind layers leading to the wind butterfly effect, or wind-driven

halo, reducing contrast capabilities in coronagraphic images. Estimating the

effective wind speed of the atmosphere allows us to calculate the atmospheric

coherence time. This is not only an important parameter to understand for site

characterization but could be used to help remove the wind butterfly in post

processing. Here we present a method for estimating the atmospheric effective

wind speed from spatio-temporal covariance maps generated from pseudo open-loop

(POL) WFS data. POL WFS data is used as it aims to reconstruct the full

wavefront information when operating in closed-loop. The covariance maps show

how different atmospheric turbulent layers traverse the telescope. Our method

successfully recovered the effective wind speed from simulated WFS data

generated with the soapy python library. The simulated atmospheric turbulence

profiles consist of two turbulent layers of ranging strengths and velocities.

The method has also been applied to Gemini Planet Imager (GPI) AO WFS data.

This gives insight into how the effective wind speed can affect the wind-driven

halo seen in the AO image point spread function. In this paper, we will present

results from simulated and GPI WFS data.

arXiv: http://arxiv.org/abs/http://arxiv.org/abs/2211.16441v1