The estimation of a phase aberration by observing a point spread function (PSF), known as wavefront estimation, is a critical problem in adaptive optics. Analogous to phase retrieval, wavefront estimation suffers from multiple ambiguous solutions. Many prior works require multiple structured measurements to overcome this fundamental challenge. In this paper, we use an asymmetric pupil to make what would otherwise be an impossible inverse problem to be possible. We combine this with an efficient machine learning algorithm to overcome remaining non-convexity. We empirically observe asymmetric pupils tend to outperform symmetric pupils.
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