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Register a new userThe VVV Templates Project. Towards an Automated Classification of VVV Light-Curves. I. Building a database of stellar variability in the near-infrared
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Context. The Vista Variables in the Via Lactea (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.
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Thanks to the VISTA Variables in the Via Lactea (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 approach. 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 (ZYJHKs), extinctions A(Ks), variability indices, periods, amplitudes, among other parameters to assess the science. Unfortunately, a side effect of having a highly complete sample, is also having a high level of contamination by non-variable (contamination ratio of non-variables to variables is slightly over 10:1). To deal with this, we also provide some flags and parameters that can be used by the community to de-crease the number of variable candidates without heavily decreasing the completeness of the sample. In particular, we cross-identified 339,601 of our sources with Simbad and AAVSO databases, which provide us with information for these objects at other wavelegths. This sub-sample 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 variability 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.
The Vista Variables in the Via Lactea (VVV) ESO Public Survey consists in a near-infrared time-series survey of the Galactic bulge and inner disk, covering 562 square degrees of the sky, over a total timespan of more than 5 years. In this paper, we provide an updated account of the current status of the survey, especially in the context of stellar variability studies. In this sense, we give a first description of our efforts towards the construction of the VVV Variable Star Catalog (VVV-VSC).
Numerous eruptive variable young stellar objects (YSOs), mostly Class I systems, were recently detected by the near-infrared Vista Variables in the Via Lactea (VVV) survey. We present an exploratory near-infrared spectroscopic variability study of 14 eruptive YSOs. The variations were sampled over 1-day and 1 to 2-year intervals and analysed in combination with VVV light curves. CO overtone absorption features are observed on 3 objects with FUor-like spectra: all show deeper absorption when they are brighter. This implies stronger emission from the circumstellar disc with a steeper vertical temperature gradient when the accretion rate is higher. This confirms the nature of fast VVV FUor-like events, in line with the accepted picture for classical FUors. The absence of Br$gamma$ emission in a FUor-like object declining to pre-outburst brightness suggests that reconstruction of the stellar magnetic field is a slow process. Within the 1-day timescale, 60% of H$_2$-emitting YSOs show significant but modest variation, and 2/6 sources have large variations in Br$gamma$. Over year-long timescales, H$_2$ flux variations remain modest despite up to 1.8 mag variation in $K_s$. This indicates that emission from the molecular outflow usually arises further from the protostar and is unaffected by relatively large changes in accretion rate on year-long timescales. Two objects show signs of on/off magnetospheric accretion traced by Br$gamma$ emission. In addition, a 60% inter-night brightening of the H$_2$ outflow is detected in one YSO.
The VISTA Variables in the Via Lactea (VVV) survey and its extension, have been monitoring about 560 square degrees of sky centred on the Galactic bulge and inner disc for nearly a decade. The photometric catalogue contains of order 10$^9$ sources monitored in the K$_s$ band down to 18 mag over hundreds of epochs from 2010-2019. Using these data we develop a decision tree classifier to identify microlensing events. As inputs to the tree, we extract a few physically motivated features as well as simple statistics ensuring a good fit to a microlensing model both on and off the event amplification. This produces a fast and efficient classifier trained on a set of simulated microlensing events and catacylsmic variables, together with flat baseline light curves randomly chosen from the VVV data. The classifier achieves 97 per cent accuracy in identifying simulated microlensing events in a validation set. We run the classifier over the VVV data set and then visually inspect the results, which produces a catalogue of 1,959 microlensing events. For these events, we provide the Einstein radius crossing time via a Bayesian analysis. The spatial dependence on recovery efficiency of our classifier is well characterised, and this allows us to compute spatially resolved completeness maps as a function of Einstein crossing time over the VVV footprint. We compare our approach to previous microlensing searches of the VVV. We highlight the importance of Bayesian fitting to determine the microlensing parameters for events with surveys like VVV with sparse data.
We present VIRAC version 1, a near-infrared proper motion and parallax catalogue of the VISTA VVV survey for 312,587,642 unique sources averaged across all overlapping pawprint and tile images covering 560 deg$^2$ of the bulge of the Milky Way and southern disk. The catalogue includes 119 million high quality proper motion measurements, of which 47 million have statistical uncertainties below 1 mas yr$^{-1}$. In the 11$<K_s<$14 magnitude range the high quality motions have a median uncertainty of 0.67 mas yr$^{-1}$. The catalogue also includes 6,935 sources with quality-controlled 5 $sigma$ parallaxes with a median uncertainty of 1.1 mas. The parallaxes show reasonable agreement with the TYCHO-Gaia Astrometric Solution (TGAS), though caution is advised for data with modest significance. The SQL database housing the data is made available via the web. We give example applications for studies of Galactic structure, nearby objects (low mass stars and brown dwarfs, subdwarfs, white dwarfs) and kinematic distance measurements of YSOs. Nearby objects discovered include LTT 7251 B, an L7 benchmark companion to a G dwarf with over 20 published elemental abundances, a bright L sub-dwarf, VVV 1256-6202, with extremely blue colours and nine new members of the 25 pc sample. We also demonstrate why this catalogue remains useful in the era of Gaia. Futur
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