Simultaneous exoplanet detection and instrument aberration retrieval in multispectral coronagraphic imaging

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 handle the difficult minimization problems of phase retrieval and achieve a contrast of 10^6 at 0.2 arcsec from simulated images, in the presence of photon noise. This opens up the the possibility of tests on real data where the ultimate performance may override the current techniques if the instrument has good and stable coronagraphic imaging quality. This paves the way for new astrophysical exploitations or even new designs for future instruments.