Battle of the Predictive Wavefront Controls: Comparing Data and Model-Driven Predictive Control for High Contrast Imaging
J. Fowler, Maaike A. M. Van Kooten, Rebecca Jensen-Clem

TL;DR
This paper compares data-driven and model-driven predictive control methods for adaptive optics in high contrast exoplanet imaging, evaluating their performance through simulations and on-sky data to improve wavefront correction.
Contribution
It provides the first side-by-side comparison of empirical orthogonal functions and predictive Fourier control for wavefront prediction in extreme AO systems.
Findings
Data-driven and model-driven methods perform differently under various atmospheric conditions.
Predictive Fourier control shows robustness at higher wind speeds.
Empirical orthogonal functions adapt well to changing turbulence profiles.
Abstract
Ground-based high contrast exoplanet imaging requires state-of-the-art adaptive optics (AO) systems in order to detect extremely faint planets next to their brighter host stars. For such extreme AO systems (with high actuator count deformable mirrors over a small field of view), the lag time of the correction (which can impact our system by the amount the wavefront has changed by the time the system is able to apply the correction) which can be anywhere from ~1-5 milliseconds, can cause wavefront errors on spatial scales that lead to speckles at small angular separations from the central star in the final science image. One avenue for correcting these aberrations is predictive control, wherein previous wavefront information is used to predict the future state of the wavefront in one-system-lag's time, and this predicted state is applied as a correction with a deformable mirror. Here, we…
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Taxonomy
TopicsAdaptive optics and wavefront sensing · Astronomy and Astrophysical Research · Stellar, planetary, and galactic studies
