Most mature wavefront-estimation algorithms for high-contrast imaging rely on a-priori knowledge of the deformable
mirror (DM) surface and thus are limited by uncertainty in the physics of the DM. In this paper, we
review the DM diversity wavefront estimation algorithm and introduce a DM-independent method of wavefront
estimation that utilizes two cameras and a Gerchberg-Saxton-based iterative phase retrieval scheme. We compare
the two estimation algorithms, and we present the creation of a dark hole in the image plane using the Stroke
Minimization correction algorithm and this two-camera estimation.
The past decade has seen a significant growth in research targeted at space based observatories for imaging exosolar planets. The challenge is in designing an imaging system for high-contrast. Even with a perfect coronagraph that modifies the point spread function to achieve high-contrast, wavefront sensing and control is needed to correct the errors in the optics and generate a "dark hole". The high-contrast imaging laboratory at Princeton University is equipped with two Boston Micromachines Kilo-DMs. We review here an algorithm
designed to achieve high-contrast on both sides of the image plane while minimizing the stroke necessary from each deformable mirror (DM). This algorithm uses the first DM to correct for amplitude aberrations and the second DM to create a flat wavefront in the pupil plane. We then show the first results obtained at Princeton
with this correction algorithm, and we demonstrate a symmetric dark hole in monochromatic light.
The detection of extra-solar terrestrial planets requires the use of space-based high-contrast imaging. Stellar
photon noise as well as light thrown about by system aberrations necessitate the use of a high quality light
suppression system and a method for wavefront correction. We present here a wavefront estimation scheme to
be used with estimate-based correction for the shaped pupil coronagraph. In order to properly estimate the field
in a reimaged pupil plane, we employ the use of the iterative Gerchberg-Saxton estimation algorithm between
it and a second-focus image plane. We utilize the correction algorithm to overcome an ambiguity inherent in
Gerchberg-Saxton estimation.
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