INVESTIGADORES
DIAZ Rodrigo Fernando
artículos
Título:
PASTIS: Bayesian extrasolar planet validation. I. General framework, models, and performance
Autor/es:
R. F. DÍAZ; J. M. ALMENARA; A. SANTERNE; C. MOUTOU; A. LETHUILLIER; M. DELEUIL
Revista:
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Editorial:
WILEY-BLACKWELL PUBLISHING, INC
Referencias:
Lugar: Londres; Año: 2014 vol. 441 p. 983 - 1004
ISSN:
0035-8711
Resumen:
A large fraction of the smallest transiting planet candidates discovered by the Kepler and CoRoT space missions cannot be confirmed by a dynamical measurement of the mass using currently available observing facilities. To establish their planetary nature, the concept of planet validation has been advanced. This technique compares the probability of the planetary hypothesis against that of all reasonably conceivable alternative false-positive (FP) hypotheses. The candidate is considered as validated if the posterior probability of the planetary hypothesis is sufficiently larger than the sum of the probabilities of all FP scenarios. In this paper, we present PASTIS, the Planet Analysis and Small Transit Investigation Software, a tool designed to perform a rigorous model comparison of the hypotheses involved in the problem of planet validation, and to fully exploit the information available in the candidate light curves. PASTIS self-consistently models the transit light curves and follow-up observations. Its object-oriented structure offers a large flexibility for defining the scenarios to be compared. The performance is explored using artificial transit light curves of planets and FPs with a realistic error distribution obtained from a Kepler light curve. We find that data support for the correct hypothesis is strong only when the signal is high enough (transit signal-to-noise ratio above 50 for the planet case) and remains inconclusive otherwise. PLATO shall provide transits with high enough signal-to-noise ratio, but to establish the true nature of the vast majority of Kepler and CoRoT transit candidates additional data or strong reliance on hypotheses priors is needed.