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Open AccessJournal ArticleDOI

Estimating distances from parallaxes IV: Distances to 1.33 billion stars in Gaia Data Release 2

TLDR
In this paper, the authors used a weak distance prior that varies smoothly as a function of Galactic longitude and latitude according to a Galaxy model to infer distances to essentially all 1.33 billion stars with parallaxes published in the second Gaia data release.
Abstract
For the vast 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 essentially 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. We analyse the characteristics of the catalogue and validate it using clusters. The catalogue can be queried on the Gaia archive using ADQL at this http URL and downloaded from this http URL .

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Citations
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Evidence of Dust Grain Evolution from Extinction Mapping in the IC 63 Photodissociation Region

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HR 6819 is a binary system with no black hole

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Mirror, mirror on the outflow cavity wall: Near-infrared CO overtone disc emission of the high-mass YSO IRAS 11101-5829

TL;DR: In this article, the inner gaseous disc of IRAS 11101-5829 through scattered light from the outflow cavity walls was investigated, and the line profiles were modelled as a Keplerian rotating disc assuming a single ring in local thermodynamic equilibrium.
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Chemical analysis of very metal-poor turn-off stars from SDSS-DR12

TL;DR: In this article, a sample of extremely metal-poor stars (EMP stars) was selected from the Sloan Digital Sky Survey Data Release 12 (SDSS DR12) and the authors used ATLAS models to compute the abundances.
References
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Journal ArticleDOI

Gaia Data Release 2: Observational Hertzsprung-Russell diagrams

C. Babusiaux, +451 more
TL;DR: In this article, the power of the Gaia DR2 in studying many fine structures of the Hertzsprung-Russell diagram (HRD) was highlighted, depending in particular on stellar population selections.
Journal ArticleDOI

Gaia Early Data Release 3: Summary of the contents and survey properties

TL;DR: Gaia DR2 as mentioned in this paper is the second Gaia data release, consisting of astrometry, photometry, radial velocities, and information on astrophysical parameters and variability, for sources brighter than magnitude 21.
Journal ArticleDOI

Gaia Data Release 2: Catalogue validation

TL;DR: The second Gaia data release (DR2) contains very precise astrometric and photometric properties for more than one billion sources, astrophysical parameters for dozens of millions, radial velocities for millions, variability information for half a million of stellar sources and orbits for thousands of solar system objects as discussed by the authors.
Journal ArticleDOI

Estimating Distances from Parallaxes

TL;DR: In this paper, the authors investigate the properties and performance of various prior assumptions and examine their implications, and demonstrate that a simple prior which decreases asymptotically to zero at infinite distance has good performance, accommodates nonpositive parallaxes, and does not require a bias correction.
Journal ArticleDOI

Gaia Data Release 2: using Gaia parallaxes

TL;DR: The main recommendation is to always treat the derivation of (astro-)physical parameters from astrometric data, in particular when parallaxes are involved, as an inference problem which should preferably be handled with a full Bayesian approach.
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