Estimated distances to 1.33 billion stars in Gaia DR2
Short Name:
gdr2dist scs
Date:
27 Dec 2024 08:31:05
Publisher:
The GAVO DC team
Description:
This catalogue provides distances estimates (and uncertainties therein)
for 1.33 billion stars over the whole sky brighter than about G=20.7.
These have been estimated using the parallaxes (and their uncertainties)
from Gaia DR2. A Bayesian procedure was used involving a prior
with a single parameter L(l,b), which varies smoothly with Galactic
longitude and latitude according to a Galaxy model. The posterior is
summarized with a point estimate (usually the mode) and a confidence
interval (usually the 68% highest density interval). The estimation
procedure is described in detail in the `accompanying paper`_,
which also analyses the catalogue content.
.. _accompanying paper: http://www.mpia.de/homes/calj/gdr2_distances.html
This service returns the most important Gaia DR3 gaia_source columns
together with robust geometric and photogeometric distances for the
~1.47 billion objects in Bailer-Jones et al's distance catalogue.
Geometric and photogeometric distances to 1.47 billion stars in Gaia
Early Data Release 3 (eDR3)
Short Name:
gedr3dist.main
Date:
27 Dec 2024 08:31:06
Publisher:
The GAVO DC team
Description:
We estimate the distance from the Sun to sources in Gaia eDR3 that have
parallaxes. We provide two types of distance estimate, together with
their corresponding asymmetric uncertainties, using Bayesian posterior
density functions that we sample for each source. Our prior is based
on a detailed model of the 3D spatial, colour, and magnitude
distribution of stars in our Galaxy that includes a 3D map of
interstellar extinction.
The first type of distance estimate is purely geometric, in that it only
makes use of the Gaia parallax and parallax uncertainty. This uses a
direction-dependent distance prior derived from our Galaxy model. The
second type of distance estimate is photogeometric: in addition to
parallax it also uses the source's G-band magnitude and BP-RP
colour. This type of estimate uses the geometric prior together with a
direction-dependent and colour-dependent prior on the absolute magnitude
of the star.
Our distance estimate and uncertainties are quantiles, so are invariant
under logarithmic transformations. This means that our median estimate
of the distance can be used to give the median estimate of the distance
modulus, and likewise for the uncertainties.
For applications that cannot be satisfied through TAP, you can download
a `full table dump`_.
.. _full table dump: /gedr3dist/q/download/form