Catalogue of radial velocity predictions for Gaia DR3
dc.contributor.author | Naik, Aneesh | |
dc.contributor.other | Widmark, Axel | |
dc.date.accessioned | 2022-06-10T08:53:12Z | |
dc.date.available | 2022-06-10T08:53:12Z | |
dc.date.issued | 2022-06-10 | |
dc.identifier.uri | https://rdmc.nottingham.ac.uk/handle/internal/9534 | |
dc.description.abstract | This catalogue accompanies our article (Naik & Widmark, 2022), in which we demonstrate the use of Bayesian neural networks for predicting the missing radial (line-of-sight) velocities of stars observed by the Gaia satellite. The catalogue contains predictions for all Gaia stars in the magnitude range 6<G<14.5 which have distance estimates from StarHorse but do not have radial velocity measurements. This is around 17 million stars. The catalogue contains 2 files, a larger file containing the source_ids and 250 posterior samples for each star, and a smaller file containing just the source_ids and the 5th/16th/50th/84th/95th percentile values. | en_UK |
dc.language.iso | en | en_UK |
dc.publisher | University of Nottingham | en_UK |
dc.rights | CC-BY | * |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | * |
dc.subject.lcsh | Gaia hypothesis | en_UK |
dc.subject.lcsh | Astronomy | en_UK |
dc.subject.lcsh | Machine learning | en_UK |
dc.subject.lcsh | Stars | en_UK |
dc.title | Catalogue of radial velocity predictions for Gaia DR3 | en_UK |
dc.identifier.doi | http://doi.org/10.17639/nott.7216 | |
dc.subject.free | Gaia, radial velocity, stars, astronomy, machine learning, Bayesian neural network | en_UK |
dc.subject.jacs | Physical sciences::Astronomy::Astronomy observation | en_UK |
dc.subject.lc | Q Science::QB Astronomy | en_UK |
uon.division | University of Nottingham, UK Campus::Faculty of Science::School of Physics and Astronomy | en_UK |
uon.funder.controlled | Other | en_UK |
uon.datatype | Numerical data | en_UK |
uon.funder.free | Leverhulme Trust | en_UK |
uon.collectionmethod | Numerical predictions from Bayesian neural network | en_UK |
dc.relation.doi | 10.48550/arXiv.2206.04102 | en_UK |
Files in this item
This item appears in the following Collection(s)
-
Public Research Data
A collection of research data, held in this repository, that is publicly available, except where individual embargoes apply