The VISTA Variables in the Vía Láctea infrared variability catalogue (VIVA-I)Revista : Monthly Notices of the Royal Astronomical Society
Volumen : 496
Número : 2
Páginas : 1730-1756
Tipo de publicación : ISI Ir a publicación
High extinction and crowding create a natural limitation for optical surveys towards the central regions of the Milky Way where the gas and dust are mainly confined. Large scale near-IR surveys of the Galactic Plane and Bulge are a good opportunity to explore open scientific questions as well as to test our capability to explore future datasets efficiently. Thanks to the VISTA Variables in the Vía Láctea (VVV) ESO Public Survey it is now possible to explore a large number of objects in those regions. This paper addresses the variability analysis of all VVV point sources having more than 10 observations in VVVDR4 using a novel appro- ach. In total, the near-IR light curves of 288,378,769 sources were analysed using methods developed in the New Insight Into Time Series Analysis project. As a result, we present a complete sample having 44,998,752 variable star candidates (VVV-CVSC), which include accurate individual coordinates, near-IR magnitudes (ZYJHs), extinctions A(Ks), variability indices, periods, amplitudes, among other parameters to assess the science. We show how astronomers can use the flags and available parameters to select reliable samples once the contamination hate should be bigger than 10. In particular, we identified that 339, 601 sources are known objects in the Simbad and AAVSO databases. This subsample constitutes a unique resource to study the corresponding near-IR variability of known sources as well as to assess the IR variability related with X-ray and Gamma-Ray sources. On the other hand, the other ∼ 99.5% sources in our sample constitutes a number of potentially new objects with va- riability information for the heavily crowded and reddened regions of the Galactic Plane and Bulge. The present results also provide an important queryable resource to perform variability analysis and to characterize ongoing and future surveys like TESS and LSST.