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Start Over Resource Type Catalog Instrument Gaia Capability Type Table Access Protocol
1. Gaia catalog release 2
ID:
ivo://vopdc.obspm/gepi/gaia
Title:
Gaia catalog release 2
Short Name:
Gaia
Date:
14 Nov 2018 00:30:00
Publisher:
Paris Astronomical Data Centre - GEPI
Description:
The second Gaia data release, Gaia DR2, encompasses astrometry, photometry, radial velocities, astrophysical parameters (stellar effective temperature, extinction, reddening, radius, and luminosity), and variability information for up to 1.6 billion stars. Gaia DR2 is based on the first 22 months of the nominal, five-year mission, processed by the Gaia Data Processing and Analysis Consortium (DPAC).
2. Gaia DR3 Lite Distances Subset Cone Search
ID:
ivo://org.gavo.dc/gedr3dist/q/cone
Title:
Gaia DR3 Lite Distances Subset Cone Search
Short Name:
DR3 lite+dist
Date:
29 Aug 2022 10:46:03
Publisher:
The GAVO DC team
Description:
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.
3. Geometric and photogeometric distances to 1.47 billion stars in Gaia Early Data Release 3 (eDR3)
ID:
ivo://org.gavo.dc/gedr3dist/q/main
Title:
Geometric and photogeometric distances to 1.47 billion stars in Gaia Early Data Release 3 (eDR3)
Short Name:
gedr3dist.main
Date:
29 Aug 2022 10:46:03
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
4. The Gaia eDR3 Catalogue of Nearby Stars GCNS
ID:
ivo://org.gavo.dc/gcns/q/cone
Title:
The Gaia eDR3 Catalogue of Nearby Stars GCNS
Short Name:
eDR3 GCNS SCS
Date:
06 Feb 2024 09:10:02
Publisher:
The GAVO DC team
Description:
This is a clean and well characterised catalogue of objects within 100pc of the Sun from the Gaia early third data release. We characterise the catalogue using the full data release, and comparisons to other catalogues in literature and simulations. For all candidates (measured parallax < 8 mas), we calculate a distance probability function using Bayesian procedures and mock catalogues for the prediction of the priors. For each entry using a random forest classifier we attempt to remove sources with spurious astrometric solutions. This results in 331312 objects that should contain at least 92% of stars within 100 pc at spectral type M9. GCNS comes with several auxiliary tables, in particular lists of resolved stellar systems, of known neary stars not found in eDR3 and of candidates of Hyades and ComaBer cluster members.
5. The Gaia eDR3 Catalogue of Nearby Stars GCNS
ID:
ivo://org.gavo.dc/gcns/q/pub
Title:
The Gaia eDR3 Catalogue of Nearby Stars GCNS
Date:
06 Feb 2024 09:09:51
Publisher:
The GAVO DC team
Description:
This is a clean and well characterised catalogue of objects within 100pc of the Sun from the Gaia early third data release. We characterise the catalogue using the full data release, and comparisons to other catalogues in literature and simulations. For all candidates (measured parallax < 8 mas), we calculate a distance probability function using Bayesian procedures and mock catalogues for the prediction of the priors. For each entry using a random forest classifier we attempt to remove sources with spurious astrometric solutions. This results in 331312 objects that should contain at least 92% of stars within 100 pc at spectral type M9. GCNS comes with several auxiliary tables, in particular lists of resolved stellar systems, of known neary stars not found in eDR3 and of candidates of Hyades and ComaBer cluster members.