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Start Over Publisher The GAVO DC team Instrument Gaia Validation Level 2
1. Astrometric Microlensing Events Predicted from Gaia DR2
ID:
ivo://org.gavo.dc/amlensing/q2/q
Title:
Astrometric Microlensing Events Predicted from Gaia DR2
Short Name:
am lensing 2
Date:
23 Mar 2022 13:13:04
Publisher:
The GAVO DC team
Description:
From the Gaia DR2 catalogue we predict astrometric microlensing events by foreground stars with high proper motion (µ_tot >150mas/yr) passing a background source in the next decades. Using Gaia DR2 photometry we determine an approximate mass of the lens, which we use to calculate the expected microlensing effects. This yields 3914 microlensing events by 2875 different lenses between 2010 and 2065 with expected shifts larger than 0.1 mas between the lensed and unlensed positions of the source. 513 of those are expected to happen between 2014.5 - 2026.5 and might be measured by Gaia. For 127 events we also expect a magnification between 1 mmag and 3 mag.
2. Astrometric Microlensing Events Predicted from Gaia eDR3
ID:
ivo://org.gavo.dc/amlensing/q3/q
Title:
Astrometric Microlensing Events Predicted from Gaia eDR3
Short Name:
am lensing 2
Date:
23 Mar 2022 13:13:11
Publisher:
The GAVO DC team
Description:
From the Gaia eDR3 catalogue we predict astrometric microlensing events by foreground stars with high proper motion (μ > 100 mas/yr) passing a background source in the next decades. Using Gaia DR3 photometry we determine an approximate mass of the lens, which we use to calculate the expected microlensing effects. This yields 4842 microlensing events by 3791 different lenses between 2010 and 2066 with expected shifts larger than 0.1 mas between the lensed and unlensed positions of the source. The past events might be interested when analyzing the individual Gaia measurements). 685 of those are expected to happen within the next decade (2021-2031). For 140 events we also expect a magnification between 1 mmag and 0.6 mag.
3. Estimated distances to 1.33 billion stars in Gaia DR2
ID:
ivo://org.gavo.dc/gdr2dist/q/cone
Title:
Estimated distances to 1.33 billion stars in Gaia DR2
Short Name:
gdr2dist scs
Date:
04 Apr 2022 15:48:41
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
4. 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.
5. 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
6. 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.
7. 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.
8. The HSOY Catalog
ID:
ivo://org.gavo.dc/hsoy/q/q
Title:
The HSOY Catalog
Short Name:
HSOY SCS
Date:
23 Mar 2022 13:13:13
Publisher:
The GAVO DC team
Description:
HSOY is a catalog of 583'001'653 objects with precise astrometry based on PPMXL and Gaia DR1. Typical formal errors at mean epoch in proper motion are below 1 mas/yr for objects brighter than 10 mag, and about 5 mas/yr at the faint end (about 20 mag). South of -30 degrees, astrometry is significantly worse. HSOY also contains, where available, USNO-B, Gaia, and 2MASS photometry. HSOY's positions and proper motions are given for epoch J2000. The catalog becomes severely incomplete faintwards of 16 mag in the G-band. The mean epochs are typically very close to Gaia's J2015. HSOY still contains about 0.7% spurious close "binaries" (non-matched stars) from the original USNO-B (marked with non-NULL clone). Also, failed matches within Gaia DR1 contribute another 1.5% spurious pairs (marked with non-NULL comp). In both cases, astrometry presumably is sub-standard. More information is available at http://dc.g-vo.org/hsoy.

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