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Proceedings Paper

An end-to-end polychromatic Fresnel propagation model of GPI
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Paper Abstract

The Gemini Planet Imager (GPI) is a future high-order coronagraphic adaptive optics system optimized for the search and analysis of Jupiter-like exoplanets around nearby young 10-1000Myr stars. In this paper, an on-axis Fresnel wavefront propagation model of GPI is presented. The main goal of this work is to confirm that the current GPI design will reach its 10-7 contrast requirement. The model, assembled using the PROPER IDL library, is used to properly simulate out-of-pupil-plane and finite size optics. A spectral data cube at GPI spectral resolution R=45 in H-band is obtained to estimate the GPI contrast as a function of wavelength. This cube is then used to evaluate the speckle suppression performance of the Simultaneous Spectral Differential Imaging (SSDI) technique. It is shown that GPI should achieve a photon noise limited 10-7 contrast when using a simple SSDI post-processing on an H=5 star and a 1h observing sequence. Finally, a long exposure data cube is obtained by combining the speckle contributions of an average atmosphere and GPI optics. That final long-exposure contrast as a function of wavelength can be used to estimate the GPI exoplanet characterization accuracy, and to evaluate, using Monte-Carlo simulations, the expected exoplanet survey performance.

Paper Details

Date Published: 12 July 2008
PDF: 17 pages
Proc. SPIE 7015, Adaptive Optics Systems, 70151T (12 July 2008); doi: 10.1117/12.789899
Show Author Affiliations
Christian Marois, Herzberg Institute of Astrophysics (Canada)
Lawrence Livermore National Lab. (United States)
Bruce Macintosh, Lawrence Livermore National Lab. (United States)
Rémi Soummer, American Museum of Natural History (United States)
Lisa Poyneer, Lawrence Livermore National Lab. (United States)
Brian Bauman, Lawrence Livermore National Lab. (United States)


Published in SPIE Proceedings Vol. 7015:
Adaptive Optics Systems
Norbert Hubin; Claire E. Max; Peter L. Wizinowich, Editor(s)

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