The VVV Templates Project. Towards an Automated Classification of VVV Light-Curves. I. Building a database of stellar variability in the near-infrared

Abstract

Context. The Vista Variables in the Vía Láctea (VVV) ESO Public Survey is a variability survey of the Milky Way bulge and an adjacent section of the disk carried out from 2010 on ESO Visible and Infrared Survey Telescope for Astronomy (VISTA). VVV will eventually deliver a deep near-IR atlas with photometry and positions in five passbands (ZYJHK_S) and a catalogue of 1-10 million variable point sources - mostly unknown - which require classifications. Aims. The main goal of the VVV Templates Project, that we introduce in this work, is to develop and test the machine-learning algorithms for the automated classification of the VVV light-curves. As VVV is the first massive, multi-epoch survey of stellar variability in the near-infrared, the template light-curves that are required for training the classification algorithms are not available. In the first paper of the series we describe the construction of this comprehensive database of infrared stellar variability. Methods. First we performed a systematic search in the literature and public data archives, second, we coordinated a worldwide observational campaign, and third we exploited the VVV variability database itself on (optically) well-known stars to gather high-quality infrared light-curves of several hundreds of variable stars. Results. We have now collected a significant (and still increasing) number of infrared template light-curves. This database will be used as a training-set for the machine-learning algorithms that will automatically classify the light-curves produced by VVV. The results of such an automated classification will be covered in forthcoming papers of the series.

arXiv comment12 pages, 16 figures, 3 tables, accepted for publication in A&A. Most of the data are now accessible through http://www.vvvtemplates.org/

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Cited by in corpus (28)

• Comparative performance of selected variability detection techniques in photometric time series
• Variable stars in the VVV globular clusters. I. 2MASS-GC02 and Terzan10
• Mapping the outer bulge with RRab stars from the VVV Survey
• A machine learned classifier for RR Lyrae in the VVV survey
• Discovery of 36 eclipsing EL CVn binaries found by the Palomar Transient Factory
• The VVV Survey RR Lyrae Population in the Galactic Centre Region
• A Data-driven Study of RR Lyrae Near-IR Light Curves: Principal Component Analysis, Robust Fits, and Metallicity Estimates
• Unsupervised Classification of Variable Stars
• Bulge RR Lyrae stars in the VVV tile $\text{b201}$
• An Updated Census of RR~Lyrae Stars in the Globular Cluster $\omega$~Centauri (NGC\,5139)
• The asymptotic evolution of the stellar merger V1309 Sco: a Blue Straggler in the making?
• The VVV Infrared Variability Catalog (VIVA-I)
• Near-IR period-luminosity relations for pulsating stars in $\omega$ Centauri (NGC 5139)
• An Automated tool to detect variable sources in the Vista Variables in the V\'ıa Láctea Survey. The VVV Variables (V${}^4$) catalog of tiles d001 and d002
• Generation of a Supervised Classification Algorithm for Time-Series Variable Stars with an Application to the LINEAR Dataset
• Near-Infrared Search for Fundamental-mode RR Lyrae Stars Toward the Inner Bulge by Deep Learning
• Long-term Stellar Variability in the Galactic Centre Region
• Semi-Supervised Classification and Clustering Analysis for Variable Stars
• Deep PSF photometric catalog of the VVV survey data
• Variable Star Classification Using Multi-View Metric Learning
• A Detection Metric Designed for O'Connell Effect Eclipsing Binaries
• The Hubble Catalog of Variables (HCV)
• Variable Star Signature Classification using Slotted Symbolic Markov Modeling
• Unveiling short period binaries in the inner VVV bulge
• Variability search in M 31 using Principal Component Analysis and the Hubble Source Catalog
• Variable stars in the VVV globular clusters. II. NGC6441, NGC6569, NGC6626 (M28), NGC6656 (M22), 2MASS-GC02, and Terzan10
• New Insights into Time Series Analysis IV: Panchromatic and Flux Independent Period Finding Methods
• Pulsating stars in $\omega$ Centauri: Near-IR properties and period-luminosity relations