TY - JOUR
T1 - Radial-velocity fitting challenge
T2 - II. First results of the analysis of the data set
AU - Dumusque, X.
AU - Borsa, F.
AU - Damasso, M.
AU - Díaz, R. F.
AU - Gregory, P. C.
AU - Hara, N. C.
AU - Hatzes, A.
AU - Rajpaul, V.
AU - Tuomi, Mikko
AU - Aigrain, S.
AU - Anglada-Escudé, G.
AU - Bonomo, A. S.
AU - Boué, G.
AU - Dauvergne, F.
AU - Frustagli, G.
AU - Giacobbe, P.
AU - Haywood, R. D.
AU - Jones, Hugh
AU - Laskar, J.
AU - Pinamonti, M.
AU - Poretti, E.
AU - Rainer, M.
AU - Ségransan, D.
AU - Sozzetti, A.
AU - Udry, S.
N1 - This document is the Accepted Manuscript of the following article: X. Dumusque, et al, 'Radial-velocity fitting challenge II. First results of the analysis of the data set', Astronomy & Astrophysics, Vol. 598, A133, first published online 14 February 2017. The version of record is available online at DOI: https://doi.org/10.1051/0004-6361/201628671
© ESO 2017
Published by EDP Sciences.
PY - 2017/2/14
Y1 - 2017/2/14
N2 - Context. Radial-velocity (RV) signals arising from stellar photospheric phenomena are the main limitation for precise RV measurements. Those signals induce RV variations an order of magnitude larger than the signal created by the orbit of Earth-twins, thus preventing their detection. Aims. Different methods have been developed to mitigate the impact of stellar RV signals. The goal of this paper is to compare the efficiency of these different methods to recover extremely low-mass planets despite stellar RV signals. However, because observed RV variations at the meter-per-second precision level or below is a combination of signals induced by unresolved orbiting planets, by the star, and by the instrument, performing such a comparison using real data is extremely challenging. Methods. To circumvent this problem, we generated simulated RV measurements including realistic stellar and planetary signals. Different teams analyzed blindly those simulated RV measurements, using their own method to recover planetary signals despite stellar RV signals. By comparing the results obtained by the different teams with the planetary and stellar parameters used to generate the simulated RVs, it is therefore possible to compare the efficiency of these different methods. Results. The most efficient methods to recover planetary signals take into account the different activity indicators, use red-noise models to account for stellar RV signals and a Bayesian framework to provide model comparison in a robust statistical approach. Using the most efficient methodology, planets can be found down to K/N = Kpl/RVrms × √Nobs = 5 with a threshold of K/N = 7.5 at the level of 80-90% recovery rate found for a number of methods. These recovery rates drop dramatically for K/N smaller than this threshold. In addition, for the best teams, no false positives with K/N > 7.5 were detected, while a non-negligible fraction of them appear for smaller K/N. A limit of K/N = 7.5 seems therefore a safe threshold to attest the veracity of planetary signals for RV measurements with similar properties to those of the different RV fitting challenge systems.
AB - Context. Radial-velocity (RV) signals arising from stellar photospheric phenomena are the main limitation for precise RV measurements. Those signals induce RV variations an order of magnitude larger than the signal created by the orbit of Earth-twins, thus preventing their detection. Aims. Different methods have been developed to mitigate the impact of stellar RV signals. The goal of this paper is to compare the efficiency of these different methods to recover extremely low-mass planets despite stellar RV signals. However, because observed RV variations at the meter-per-second precision level or below is a combination of signals induced by unresolved orbiting planets, by the star, and by the instrument, performing such a comparison using real data is extremely challenging. Methods. To circumvent this problem, we generated simulated RV measurements including realistic stellar and planetary signals. Different teams analyzed blindly those simulated RV measurements, using their own method to recover planetary signals despite stellar RV signals. By comparing the results obtained by the different teams with the planetary and stellar parameters used to generate the simulated RVs, it is therefore possible to compare the efficiency of these different methods. Results. The most efficient methods to recover planetary signals take into account the different activity indicators, use red-noise models to account for stellar RV signals and a Bayesian framework to provide model comparison in a robust statistical approach. Using the most efficient methodology, planets can be found down to K/N = Kpl/RVrms × √Nobs = 5 with a threshold of K/N = 7.5 at the level of 80-90% recovery rate found for a number of methods. These recovery rates drop dramatically for K/N smaller than this threshold. In addition, for the best teams, no false positives with K/N > 7.5 were detected, while a non-negligible fraction of them appear for smaller K/N. A limit of K/N = 7.5 seems therefore a safe threshold to attest the veracity of planetary signals for RV measurements with similar properties to those of the different RV fitting challenge systems.
KW - Methods: data analysis
KW - Planetary systems
KW - Stars: activity
KW - Stars: oscillations
KW - Techniques: radial velocities
UR - http://www.scopus.com/inward/record.url?scp=85013058437&partnerID=8YFLogxK
U2 - 10.1051/0004-6361/201628671
DO - 10.1051/0004-6361/201628671
M3 - Article
AN - SCOPUS:85013058437
SN - 0004-6361
VL - 598
JO - Astronomy and Astrophysics
JF - Astronomy and Astrophysics
M1 - A133
ER -