Published May 19, 2022
| Version 1.0
Dataset
Open
Gaia EDR3 Catalogs of Machine-Learned Radial Velocities
Authors/Creators
- 1. Princeton University
- 2. New York University & Princeton University
- 3. Harvard University & The NSF AI Institute for Artificial Intelligence and Fundamental Interactions
- 4. Princeton University & Center for Computational Astrophysics, Flatiron Institute
Description
Gaia EDR3 Catalogs of Machine-Learned Radial Velocities
Spatially complete Test-Set and Machine-Learned Radial Velocity (ML-RV) Catalogs described in Dropulic et al., arXiv:2205.12278. The spatially complete Test-Set Catalog contains a total of 4,332,657 stars, while the spatially complete ML-RV Catalog contains 91,840,346 stars. We provide Gaia EDR3 Source IDs, the network-predicted line-of-sight velocity in km/s, and the network-predicted uncertainty in km/s.
We have included a simple Jupyter notebook demonstrating how to import the data, and make a simple histogram with it.
If you find this catalog useful in your work, please cite Dropulic et al. arXiv:2205.12278, as well as Dropulic et al. ApJL 915, L14 (2021) arXiv:2103.14039.