Volume 598, February 2017
|Number of page(s)||35|
|Section||Planets and planetary systems|
|Published online||14 February 2017|
Radial-velocity fitting challenge
II. First results of the analysis of the data set⋆
1 Observatoire de Genève, Université de Genève, 51 ch. des Maillettes, 1290 Versoix, Switzerland
2 Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, Massachusetts 02138, USA
3 INAF−Osservatorio Astronomico di Brera, via E. Bianchi 46, 23807 Merate (LC), Italy
4 INAF−Osservatorio Astrofisico di Torino, via Osservatorio 20, 10025 Pino Torinese, Italy
5 Physics and Astronomy Department, University of British Columbia, 6224 Agricultural Rd., Vancouver, BC V6T 1Z1, Canada
6 ASD, IMCCE-CNRS UMR8028, Observatoire de Paris, UPMC, 77 Av. Denfert-Rochereau, 75014 Paris, France
7 Thüringer Landessternwarte Tautenburg, Sternwarte 5, 07778 Tautenburg, Germany
8 Sub-department of Astrophysics, Department of Physics, University of Oxford, Oxford, OX1 3RH, UK
9 University of Hertfordshire, Centre for Astrophysics Research, Science and Technology Research Institute, College Lane, AL10 9AB, Hatfield, UK
10 School of Physics and Astronomy, Queen Mary University of London, 327 Mile End Rd., E1 4NS, London, UK
11 Dipartimento di Fisica, Universita degli Studi di Trieste, via G. B.Tiepolo 11, 34143 Trieste, Italy
12 INAF−Osservatorio Astronomico di Trieste, via G. B. Tiepolo 11, 34143 Trieste, Italy
Received: 8 April 2016
Accepted: 12 September 2016
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 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.
Key words: techniques: radial velocities / planetary systems / stars: oscillations / stars: activity / methods: data analysis
Based on observations collected at the La Silla Parana Observatory, ESO (Chile), with the HARPS spectrograph at the 3.6-m telescope.
Society in Science – Branco Weiss Fellow (url: http://www.society-in-science.org).
© ESO, 2017
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.