Simultaneous exoplanet detection and instrument aberration retrieval in multispectral coronagraphic imaging
Marie Ygouf, Laurent M. Mugnier, David Mouillet, Thierry, Fusco, Jean-Luc Beuzit

TL;DR
This paper introduces a Bayesian inversion method that simultaneously detects exoplanets and retrieves instrument aberrations from multispectral coronagraphic images, improving contrast and leveraging prior knowledge of system optics.
Contribution
It presents a novel analytical imaging model and numerical techniques for joint speckle and object estimation, enhancing exoplanet detection capabilities in high-contrast imaging.
Findings
Achieved a contrast of 10^6 at 0.2 arcsec in simulations
Validated the method's effectiveness with simulated noisy data
Demonstrated potential for application to real data and future instrument design
Abstract
High-contrast imaging for the detection and characterization of exoplanets relies on the instrument's capability to block out the light of the host star. Some current post-processing methods for calibrating out the residual speckles use information redundancy offered by multispectral imaging but do not use any prior information on the origin of these speckles. We investigate whether additional information on the system and image formation process can be used to more finely exploit the multispectral information. We developed an inversion method in a Bayesian framework that is based on an analytical imaging model to estimate both the speckles and the object map. The model links the instrumental aberrations to the speckle pattern in the image focal plane, distinguishing between aberrations upstream and downstream of the coronagraph. We propose and validate several numerical techniques to…
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