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arXiv · 1505.02663

PASTIS: Bayesian extrasolar planet validation II. Constraining exoplanet blend scenarios using spectroscopic diagnoses

Abstract

The statistical validation of transiting exoplanets proved to be an efficient technique to secure the nature of small exoplanet signals which cannot be established by purely spectroscopic means. However, the spectroscopic diagnoses are providing us with useful constraints on the presence of blended stellar contaminants. In this paper, we present how a contaminating star affects the measurements of the various spectroscopic diagnoses as function of the parameters of the target and contaminating stars using the model implemented into the PASTIS planet-validation software. We find particular cases for which a blend might produce a large radial velocity signal but no bisector variation. It might also produce a bisector variation anti-correlated with the radial velocity one, as in the case of stellar spots. In those cases, the full width half maximum variation provides complementary constraints. These results can be used to constrain blend scenarios for transiting planet candidates or radial velocity planets. We review all the spectroscopic diagnoses reported in the literature so far, especially the ones to monitor the line asymmetry. We estimate their uncertainty and compare their sensitivity to blends. Based on that, we recommend the use of BiGauss which is the most sensitive diagnosis to monitor line-profile asymmetry. In this paper, we also investigate the sensitivity of the radial velocities to constrain blend scenarios and develop a formalism to estimate the level of dilution of a blended signal. Finally, we apply our blend model to re-analyse the spectroscopic diagnoses of HD16702, an unresolved face-on binary which exhibits bisector variations.

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BibTeXRIS

A. Santerne, R. F. Díaz, J. -M. Almenara, F. Bouchy, M. Deleuil, P. Figueira, G. Hébrard, C. Moutou, S. Rodionov, N. C. Santos. 2015-05-11. PASTIS: Bayesian extrasolar planet validation II. Constraining exoplanet blend scenarios using spectroscopic diagnoses. https://arxiv.org/abs/1505.02663

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