arXiv · 2009.07746
Large-amplitude variables in Gaia Data Release 2. Multi-band variability characterization
Abstract
The second data release (DR2) of Gaia provides mean photometry in three bands for $\sim$1.4 billion sources, but light curves and variability properties are available for only $\sim$0.5 million of them. Here, we provide a census of large-amplitude variables with amplitudes larger than $\sim$0.2 mag in the $G$ band for objects with mean brightnesses between 5.5 and 19 mag. To achieve this, we rely on variability amplitude proxies in $G$, $G_{BP}$ and $G_{RP}$ computed from the uncertainties on the magnitudes published in DR2. We then apply successive filters to identify two subsets containing respectively sources with reliable mean $G_{BP}$ and $G_{RP}$ (for studies using colours) and sources having compatible amplitude proxies in $G$, $G_{BP}$ and $G_{RP}$ (for multi-band variability studies). The full catalogue gathers $23\,315\,874$ large-amplitude variable candidates, and the two subsets with increased levels of purity contain respectively $1\,148\,861$ and $618\,966$ sources. A multi-band variability analysis of the catalogue shows that different types of variable stars can be globally categorized in four groups according to their colour and blue-to-red amplitude ratios as determined from the $G$, $G_{BP}$ and $G_{RP}$ amplitude proxies. The catalogue constitutes the first census of Gaia large-amplitude variable candidates, extracted from the public DR2 archive. The overview presented here illustrates the added-value of the mission for multi-band variability studies even at this stage when epoch photometry is not yet available for all sources. (Abridged abstract)
Explore related subjects
Keep this discovery
N. Mowlavi, L. Rimoldini, D. W. Evans, M. Riello, F. De Angeli, L. Palaversa, M. Audard, L. Eyer, P. Garcia-Lario, P. Gavras, B. Holl, G. Jevardat de Fombelle, I. Lecœur-Taïbi, K. Nienartowicz. 2020-09-16. Large-amplitude variables in Gaia Data Release 2. Multi-band variability characterization. https://doi.org/10.1051/0004-6361/202039450
Cite the original work for its findings. Save a collection to share your selection of sources.