Issue |
A&A
Volume 682, February 2024
|
|
---|---|---|
Article Number | A92 | |
Number of page(s) | 14 | |
Section | Planets and planetary systems | |
DOI | https://doi.org/10.1051/0004-6361/202348496 | |
Published online | 07 February 2024 |
Distinguishing exoplanet companions from field stars in direct imaging using Gaia astrometry★
Max-Planck-Institut für Astronomie,
Königstuhl 17,
69117
Heidelberg,
Germany
e-mail: calj@mpia.de
Received:
5
November
2023
Accepted:
7
December
2023
Direct imaging searches for exoplanets around stars detect many spurious candidates that are in fact background field stars. To help distinguish these from genuine companions, multi-epoch astrometry can be used to identify a common proper motion with the host star. Although this is frequently done, many approaches lack an appropriate model for the motions of the background population, or do not use a statistical framework to properly quantify the results. For this study we used Gαìα astrometry combined with 2MASS photometry to model the parallax and proper motion distributions of field stars around exoplanet host stars as a function of candidate magnitude. We developed a likelihood-based method that compares the positions of a candidate at multiple epochs with the positions expected under both this field star model and a co-moving companion model. Our method propagates the covariances in the Gαìα astrometry and the candidate positions. True companions are assumed to have long periods compared to the observational baseline, so we currently neglect orbital motion. We applied our method to a sample of 23 host stars with 263 candidates identified in the B-Star Exoplanet Abundance Study (BEAST) survey on VLT/SPHERE. We identified seven candidates in which the odds ratio favours the co-moving companion model by a factor of 100 or more. Most of these detections are based on only two or three epochs separated by less than three years, so further epochs should be obtained to reassess the companion probabilities. Our method is publicly available as an open-source python package from GitHub to use with any data.
Key words: methods: statistical / techniques: high angular resolution / planets and satellites: detection / stars: early-type
Full Table 1 is available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5) or via https://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/682/A92
© The Authors 2024
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This article is published in open access under the Subscribe to Open model.
Open Access funding provided by Max Planck Society.
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