Authors

A. Eggenberger (1), A. Cornia (2,3), L. M. Mugnier (2), D. Mouillet (1), G. Chauvin (1), A. Boccaletti (3), and G. Rousset (3)

Affiliations

(1) LAOG/CNRS; (2) ONERA; (3) LESIA/CNRS

Abstract

The detection of exoplanets with adaptive optics imaging requires advanced data processing techniques to disentangle potential planetary signals from bright quasi-static speckles. In the context of the SPHERE planet finder project, a novel planet detection method based on a maximum likelihood approach has been developed. This method, named ANDROMEDA, will exploit the improved contrast performance of the upcoming generation of adaptive optics imagers, along with the techniques of spectral and angular differential imaging. As a preparatory step towards the analysis of SPHERE observations, we are now testing ANDROMEDA on VLT/NACO data collected as part of an ongoing search for exoplanets and brown dwarfs at wide separations. We present here a series of results that demonstrate the ability of ANDROMEDA to detect substellar companions in NACO images taken in pupil-tracking mode in the H band. We also describe the impact of the algorithm’s key parameters on the detection performance and discuss how the method has been optimized for the analysis of NACO data. Further work will allow us to compare ANDROMEDA’s performance to those of other methods based on angular differential imaging.