Physics
Scientific paper
Oct 2010
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010lyot.confe..62j&link_type=abstract
Proceedings of the conference In the Spirit of Lyot 2010: Direct Detection of Exoplanets and Circumstellar Disks. October 25 -
Physics
Scientific paper
The main limitation to detecting planets in high-contrast images is confusion with quasi-static speckles formed due to aberrations in the optical system. This confusion is due to the speckles looking like the image of a planet. Nevertheless, we can use the fact that speckles will be coherent with the main starlight point spread function, while planet light will not, to differentiate the two. This property lends itself to the use of interference to distinguish speckle light from the image of a planet. We analyze two interferometric approaches to address this identification problem and present preliminary experimental results. Princeton University's High Contrast Imaging Laboratory, in partnership with Ball Aerospace, is working to create a speckle detection system using two possible techniques. Both techniques use a shaped pupil paired with a focal plane mask (FPM) for the coronagraph. Light that passes by the FPM consists of speckles and planet light. Using the reflection from the metallic surface of the FPM, the starlight is redirected to create a flat reference field. This reference field is then interfered with the speckle/planet light. Due to the coherence of the speckles with the reference field, as we change the phase of the interfering light we see an intensity change in the speckles. The parts of the image that are changing in intensity are now identified as speckles and the light that is unchanged from the phase sweep (incoherent light to the starlight) is a planet. Distinguishing speckles from the planet and incoherent zodi signals allows quicker speckle measurements against a zodi background. This generic technique will work with any type of coronagraph, ground or space-based. However, we illustrate the results with simulations and lab data designed for space-based AO and coronagraphy.
Carlotti Alexis
Jensen Eric
Kasdin Jeremy N.
Noecker Martin Charles
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