Presentation + Paper
29 August 2022 Imaged-based adaptive optics wavefront sensor referencing for high contrast imaging
Author Affiliations +
Abstract
A key challenge of high contrast imaging (HCI) is to differentiate a speckle from an exoplanet signal. The sources of speckles are a combination of atmospheric residuals and aberrations in the non-common path. Those non-common path aberrations (NCPA) are particularly challenging to compensate for as they are not directly measured, and because they include static, quasi-static and dynamic components. The proposed method directly addresses the challenge of compensating the NCPA. The algorithm DrWHO - Direct Reinforcement Wavefront Heuristic Optimisation - is a quasi-real-time compensation of static and dynamic NCPA for boosting image contrast. It is an image-based lucky imaging approach, aimed at finding and continuously updating the ideal reference of the wavefront sensor (WFS) that includes the NCPA, and updating this new reference to the WFS. Doing so changes the point of convergence of the AO loop. We introduce here the upgrade concept of the algorithm. DrWHO does not rely on any model nor requires accurate wavefront sensor calibration, and is applicable to non-linear wavefront sensing situations. We present on-sky performances using a pyramid WFS sensor with the Subaru coronagraph extreme AO (SCExAO) instrument.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nour Skaf, Olivier Guyon, Anthony Boccaletti, Eric Gendron, Vincent Deo, Sébastien Vievard, Julien Lozi, Kyohoon Ahn, and Thayne Currie "Imaged-based adaptive optics wavefront sensor referencing for high contrast imaging", Proc. SPIE 12185, Adaptive Optics Systems VIII, 121851U (29 August 2022); https://doi.org/10.1117/12.2630732
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KEYWORDS
Adaptive optics

Wavefronts

Coronagraphy

Fourier transforms

Spatial frequencies

Wavefront sensors

Imaging systems

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