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
- Article: Astronomical Journal, 156, 58 (2018)
- Catalogue access:
- It is available on the Gaia archive under "Other", "External catalogues" in the table
external.gaiadr2_geometric_distance, where it can be queried using ADQL.
See the paper for a query example of how to join it to the gaia_source table. If you want to get the distance information for a list of GDR2 source_ids, the upload this as a single column file (here called "sourceids") with header "source_id" to the Gaia archive, and use the following query:
SELECT source_id, dist.r_est, dist.r_lo, dist.r_hi, dist.r_len, dist.result_flag, dist.modality_flag, src.ra, src.dec
FROM external.gaiadr2_geometric_distance as dist
JOIN user_cbj.sourceids USING (source_id)
JOIN gaiadr2.gaia_source AS src USING (source_id)
where you should replace "user_cbj" with whatever the name of your userspace is.
In this example I also join to the gaia_source table to get the RA and Dec of the source.
- The catalogue is also available at Vizier at CDS as catalogue I/347.
- If you want to download the entire catalogue (114GB spread over 6660 CSV files), email me, and I will put it online.
- The catalogue can also be queried using ADQL on the ARI TAP server (table geometric_distance in schema gaiadr2_complements), but this is quite slow.
Code for computing the distance estimates and plotting the posterior and prior for individual sources is available on github.
A tutorial on estimating distances from parallaxes, also for clusters and what to do with correlated uncertainties, is available on github.
As of 8 January 2020, this paper has 514 citations, making it the 9th most highly cited astronomy paper of 2018, and the most highly cited astronomy paper in 2018 with fewer than 90 authors. Source: ADS.
The first three papers in this series are:
Estimating distances from parallaxes: a tutorial. 2015.
Publications of the Astronomical Society of the Pacific, 127, 994
[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
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]
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