Abstract: In this paper we show new ways to improve the performance of ground-based coronagraphy. We introduce adaptive coronagraphic masks whose profile is a binary version of the instantaneous atmospherically degraded star image. We also propose the hyper-Gaussian profile masks obtained by averaging adaptive masks. In addition, adaptive Lyot stops and hyper-Gaussian Lyot stops are analyzed. Computer simulations show that all these masks outperform the circular hard-edged mask and that a proper mask and stop combination significantly reduces the angular separation at which a faint companion can be detected.

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