Estimating distances from parallaxes. IV. Distances to 1.33 billion stars in Gaia data release 2

C.A.L. Bailer-Jones, J. Rybizki, M. Fouesneau, G. Mantelet, R. Andrae

For the majority of stars in the second Gaia data release, reliable distances cannot be obtained by inverting the parallax. A correct inference procedure must instead be used to account for the nonlinearity of the transformation and the asymmetry of the resulting probability distribution. Here we infer distances to almost all 1.33 billion stars with parallaxes published in the second Gaia data release. This is done using a weak distance prior that varies smoothly as a function of Galactic longitude and latitude according to a Galaxy model. The irreducible uncertainty in the distance estimate is characterized by the lower and upper bounds of an asymmetric confidence interval. Although more precise distances can be estimated for a subset of the stars using additional data (such as photometry), our goal is to provide purely geometric distance estimates, independent of assumptions about the physical properties of, or interstellar extinction towards, individual stars. The catalogue is available from http://gaia.ari.uni-heidelberg.de/tap.html (which also hosts the Gaia catalogue) as the table geometric_distance in the schema gaiadr2_complements.

The first three papers in this series are:

Estimating distances from parallaxes: a tutorial. 2015.
C.A.L. Bailer-Jones
Publications of the Astronomical Society of the Pacific, 127, 994
[abstract] [PDF] [ADS] [arXiv] [journal link]

Estimating distances from parallaxes II. Performance of Bayesian distance estimators on a Gaia-like catalogue. 2016.
T. Astraatmadja, C.A.L. Bailer-Jones
Astrophysical Journal 832, 137
[ADS] [journal] [arXiv]

Estimating distances from parallaxes III. Distances of two million stars in the Gaia DR1 catalogue. 2016.
T. Astraatmadja, C.A.L. Bailer-Jones
Astrophysical Journal, 833, 119
[abstract, paper, and catalogue] [ADS] [arXiv] [journal link]

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Coryn Bailer-Jones, calj at mpia.de
Last modified: 8 January 2020