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Efficient identification of exoplanetary transit candidates from SuperWASP light curves

2007· article· en· 365 citations· W1885258061 on OpenAlex· 10.1111/j.1365-2966.2007.12195.x

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Opus teacher head0.006
GPT teacher head0.194
Teacher spread
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Validation status
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Abstract

Transiting extrasolar planets constitute only a small fraction of the range of stellar systems found to display periodic, shallow dimmings in wide-field surveys employing small-aperture camera arrays. Here we present an efficient selection strategy for follow-up observations, derived from analysis of the light curves of a sample of 67 SuperWASP targets that passed the selection tests we used in earlier papers, but which have subsequently been identified either as planet hosts or as astrophysical false positives. We determine the system parameters using Markov-chain Monte Carlo analysis of the SuperWASP light curves. We use a constrained optimization of 2 combined with a Bayesian prior based on the main-sequence mass and radius expected from the Two Micron All Sky Survey J -H colour. The Bayesian nature of the analysis allows us to quantify both the departure of the host star from the main-sequence mass-radius relation and the probability that the companion radius is less than 1.5 Jupiter radii. When augmented by direct light-curve analyses that detect binaries with unequal primary and secondary eclipses, and objects with aperture blends that are resolved by SuperWASP, we find that only 13 of the original 67 stars, including the three known planets in the sample, would qualify for follow-up. This suggests that planet discovery 'hit rates' better than

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The record

Venue
Monthly Notices of the Royal Astronomical Society
Topic
Stellar, planetary, and galactic studies
Field
Physics and Astronomy
Canadian institutions
Funders
Centre National de la Recherche ScientifiqueNational Aeronautics and Space AdministrationCalifornia Institute of TechnologyQueen's University BelfastScience and Technology Facilities CouncilQueen's UniversityNational Science Foundation
Keywords
PhysicsLibrary scienceIdentification (biology)HumanitiesComputer scienceArt
Has abstract in OpenAlex
yes