A Deep Reinforcement Learning Approach to Wavefront Control for Exoplanet Imaging

arXiv (Cornell University)

Abstract

Exoplanet imaging uses coronagraphs to block out the bright light from a star, allowing astronomers to observe the much fainter light from planets orbiting the star. However, these instruments are heavily impacted by small wavefront aberrations and require the minimization of starlight residuals directly in the focal plane. State-of-the art wavefront control methods suffer from errors in the underlying physical models, and often require several iterations to minimize the intensity in the dark hole, limiting performance and reducing effective observation time. This study aims at developing a data-driven method to create a dark hole in post-coronagraphic images. For this purpose, we leverage the model-free capabilities of reinforcement learning to train an agent to learn a control strategy directly from phase diversity images acquired around the focal plane. Initial findings demonstrate successful aberration correction in non-coronagraphic simulations and promising results for dark hole creation in post-coronagraphic scenarios. These results highlight the potential of model-free reinforcement learning for dark-hole creation, justifying further investigation and eventually experimental validation on a dedicated testbed.

Authors 6

1. Yann Gutierrez
2. Johan Mazoyer

   Université Paris Cité · Université Paris Sciences et Lettres · Observatoire de Paris · Sorbonne Université · Laboratoire d’études spatiales et d’instrumentation en astrophysique

   Affiliation as printed

   LESIA , Observatoire de Paris , Université PSL , Sorbonne Université , Université Paris Cité ,

3. Olivier Herscovici-Schiller

   Université Paris-Saclay · Centre Inria de Saclay

   Affiliation as printed

   DTIS , ONERA , Université Paris Saclay , 91120 Palaiseau , France

4. Laurent M. Mugnier

   Université Paris-Saclay · Office National d'Études et de Recherches Aérospatiales · Département Optique et Techniques Associées

   Affiliation as printed

   DOTA , ONERA , Université Paris Saclay , 92320 Châtillon , France

5. B. Abeloos

   Centre National de la Recherche Scientifique · Janssen (Belgium) · Université Paris-Saclay · Centre Inria de Saclay

   Affiliation as printed

   CNRS , 5 place Jules Janssen , 92195 Meudon , France

   DTIS , ONERA , Université Paris Saclay , 91120 Palaiseau , France

6. Iva Laginja Aachen

   Leiden University · Université Paris Cité · Université Paris Sciences et Lettres · Observatoire de Paris · Sorbonne Université · Laboratoire d’études spatiales et d’instrumentation en astrophysique

   Affiliation as printed

   LESIA , Observatoire de Paris , Université PSL , Sorbonne Université , Université Paris Cité ,

   NOVA/Leiden University , Einsteinweg 55 , 2333 CC Leiden , The Netherlands