Browsing by Author "de Grijs, R"
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- ItemOpen AccessThe VMC survey: I. strategy and first data(2011) Cioni, M- R L; Clementini, G; Girardi, L; Guandalini, R; Gullieuszik, M; Miszalski, B; Moretti, M-I; Ripepi, V; Rubele, S; Bagheri, G; Bekki, K; Cross, N; de Blok, W J G; de Grijs, R; Emerson, J P; Evans, C J; Gibson, B; Gonzales-Solares, E; Groenewegen, M A T; Irwin, M; Ivanov, V D; Lewis, J; Marconi, M; Marquette, J-B; Mastropietro, C; Moore, B; Napiwotzki, R; Naylor, T; Oliveira, J M; Read, M; Sutorius, E; van Loon, J ThContext. The new VISual and Infrared Telescope for Astronomy (VISTA) has started operations. Over its first five years it will be collecting data for six public surveys, one of which is the near-infrared YJK(s) VISTA survey of the Magellanic Clouds system (VMC). This survey comprises the Large Magellanic Cloud (LMC), the Small Magellanic Cloud, the Magellanic Bridge connecting the two galaxies and two fields in the Magellanic Stream. Aims. This paper provides an overview of the VMC survey strategy and presents first science results. The main goals of the VMC survey are the determination of the spatially-resolved star-formation history and the three-dimensional structure of the Magellanic system. The VMC survey is therefore designed to reach stars as faint as the oldest main sequence turn-off point and to constrain the mean magnitude of pulsating variables such as RR Lyrae stars and Cepheids. This paper focuses on observations of VMC fields in the LMC obtained between November 2009 and March 2010. These observations correspond to a completeness of 7% of the planned LMC fields. Methods. The VMC data are comprised of multi-epoch observations which are executed following specific time constraints. The data were reduced using the VISTA Data Flow System pipeline with source catalogues, including astrometric and photometric corrections, produced and made available via the VISTA Science Archive. The VMC data will be released to the astronomical community following the European Southern Observatorys Public Survey policy. The analysis of the data shows that the sensitivity in each wave band agrees with expectations. Uncertainties and completeness of the data are also derived. Results. The first science results, aimed at assessing the scientific quality of the VMC data, include an overview of the distribution of stars in colour-magnitude and colour-colour diagrams, the detection of planetary nebulae and stellar clusters, and the K-s band light-curves of variable stars. Conclusions. The VMC survey represents a tremendous improvement, in spatial resolution and sensitivity, on previous panoramic observations of the Magellanic system in the near-infrared, providing a powerful complement to deep observations at other wavelengths.
- ItemOpen AccessThe VVV Templates Project Towards an automated classification of VVV light-curves: I. Building a database of stellar variability in the near-infrared(2014) Angeloni, R; Contreras Ramos, R; Catelan, M; Dékány, I; Gran, F; Alonso-García, J; Hempel, M; Navarrete, C; Andrews, H; Aparicio, A; Beamín, J C; Berger, C; Borissova, J; Contreras Peña, C; Cunial, A; de Grijs, R; Espinoza, N; Eyheramendy, S; Ferreira Lopes, C E; Fiaschi, M; Hajdu, G; Han, J; Hełminiak, K G; Hempel, A; Hidalgo, S L; Ita, Y; Jeon, Y-B; Jordán, A; Kwon, J; Lee, J T; Martín, E L; Masetti, NContext. The Vista Variables in the V'ia L'actea (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.