On advanced estimation techniques for exoplanet detection and characterization using ground-based coronagraphs

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DOIResolve DOI: http://doi.org/10.1117/12.925099
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TypeArticle
Proceedings titleAdaptive Optics Systems III
Series titleProceedings of SPIE; Volume 8447
ConferenceAdaptive Optics Systems III, July 1-6, 2012, Amsterdam, Netherlands
ISSN0277-786X
ISBN9780819491480
Article number844722
SubjectCoronagraphs; Data challenges; Detectability; Direct imaging; Earth-like planets; Estimation techniques; Exo-planets; Ground based; Hotelling observers; Ideal observers; Instrumentation; Jupiters; Localization rocs; Measurement Noise; Receiver operating characteristics; State of the art; Adaptive optics; Planets
AbstractThe direct imaging of planets around nearby stars is exceedingly difficult. Only about 14 exoplanets have been imaged to date that have masses less than 13 times that of Jupiter. The next generation of planet-finding coronagraphs, including VLT-SPHERE, the Gemini Planet Imager, Palomar P1640, and Subaru HiCIAO have predicted contrast performance of roughly a thousand times less than would be needed to detect Earth-like planets. In this paper we review the state of the art in exoplanet imaging, most notably the method of Locally Optimized Combination of Images (LOCI), and we investigate the potential of improving the detectability of faint exoplanets through the use of advanced statistical methods based on the concepts of the ideal observer and the Hotelling observer. We propose a formal comparison of techniques using a blind data challenge with an evaluation of performance using the Receiver Operating Characteristic (ROC) and Localization ROC (LROC) curves. We place particular emphasis on the understanding and modeling of realistic sources of measurement noise in ground-based AO-corrected coronagraphs. The work reported in this paper is the result of interactions between the co-authors during a week-long workshop on exoplanet imaging that was held in Squaw Valley, California, in March of 2012.
Publication date
LanguageEnglish
AffiliationNational Research Council Canada (NRC-CNRC); National Science Infrastructure
Peer reviewedYes
NPARC number21270309
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Record identifier5e58d6be-a78a-47cf-aeda-dded0ede98f9
Record created2014-01-23
Record modified2017-09-13
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