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arXiv · astro-ph/0610658

A Reflective Gaussian Coronagraph for ExAO: Laboratory Performance

Abstract

We report laboratory results of a coronagraphic test bench to assess the intensity reduction differences between a "Gaussian" tapered focal plane coronagraphic mask and a classical hard-edged "Top Hat" function mask at Extreme Adaptive Optics (ExAO) Strehl ratios of ~94%. However, unlike a traditional coronagraph design, we insert a reflective focal plane mask at 45 degree to the optical axis. We also used an intermediate secondary mask ("Mask_2") before a final image in order to block additional mask-edge diffracted light. The test bench simulates the 8.1m Gemini North telescope. It includes one spider vane, different mask radii (r= 1.9, 3.7, 7.4 lambda/D) and two types of reflective focal plane masks (hard-edged "Top Hat" and "Gaussian" tapered profiles). In order to investigate the relative performance of these competing coronagraphic designs with regard to extra-solar planet detection sensitivity, we utilize the simulation of realistic extra-solar planet populations (Nielson et al. 2006). With an appropriate translation of our laboratory results to expected telescope performance, a "Gaussian" tapered mask radius of 3.7 lambda/D with an additional mask ("Mask_2") performs best (highest planet detection sensitivity). For a full survey with this optimal design, the simulation predicts ~30% more planets detected compared to a similar sized "Top Hat" function mask with "Mask_2." Using the best design, the point contrast ratio between the stellar PSF peak and the coronagraphic PSF at 10 lambda/D (0.4" in H band if D = 8.1m) is ~10 times higher than a classical Lyot "Top Hat" coronagraph. Hence, we find a Gaussian apodized mask with an additional blocking mask is a superior (~10x higher contrast) than use of a classical Lyot coronagraph for ExAO-like Strehls.

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BibTeXRIS

Ryeojin Park, Laird M. Close, Nick Siegler, Eric L. Nielsen, Thomas Stalcup. 2006-10-24. A Reflective Gaussian Coronagraph for ExAO: Laboratory Performance. https://doi.org/10.1117/12.670802

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