The 10 parsec sample in the Gaia era
Journal
ASTRONOMY & ASTROPHYSICS
Date Issued
2021
Author(s)
DOI
10.1051/0004-6361/202140985
Abstract
The nearest stars provide a fundamental constraint for our understanding of
stellar physics and the Galaxy. The nearby sample serves as an anchor where all
objects can be seen and understood with precise data. This work is triggered by
the most recent data release of the astrometric space mission Gaia and uses its
unprecedented high precision parallax measurements to review the census of
objects within 10 pc. The first aim of this work was to compile all stars and
brown dwarfs within 10 pc observable by Gaia, and compare it with the Gaia
Catalogue of Nearby Stars as a quality assurance test. We complement the list
to get a full 10 pc census, including bright stars, brown dwarfs, and
exoplanets. We started our compilation from a query on all objects with a
parallax larger than 100 mas using SIMBAD. We completed the census by adding
companions, brown dwarfs with recent parallax measurements not in SIMBAD yet,
and vetted exoplanets. The compilation combines astrometry and photometry from
the recent Gaia Early Data Release 3 with literature magnitudes, spectral types
and line-of-sight velocities. We give a description of the astrophysical
content of the 10 pc sample. We find a multiplicity frequency of around 28%.
Among the stars and brown dwarfs, we estimate that around 61% are M stars and
more than half of the M stars are within the range M3.0 V to M5.0 V. We give an
overview of the brown dwarfs and exoplanets that should be detected in the next
Gaia data releases along with future developments. We provide a catalogue of
540 stars, brown dwarfs, and exoplanets in 339 systems, within 10 pc from the
Sun. This list is as volume-complete as possible from current knowledge and
provides benchmark stars that can be used, for instance, to define calibration
samples and to test the quality of the forthcoming Gaia releases. It also has a
strong outreach potential.
Volume
650
Start page
A201
File(s)
Loading...
Name
Reyleetal.2021.pdf
Description
PDF editoriale
Size
2.53 MB
Format
Adobe PDF
Checksum (MD5)
c06480f0a1e135cec04169db7093eda2