Browsing by Author "Pichara, K."

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    Informative Bayesian model selection for RR Lyrae star classifiers
    (2021) Pérez-Galarce, F.; Pichara, K.; Huijse, P.; Catelan, M.; Mery Quiroz, Domingo Arturo
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    The Vista Variables in the Vía Láctea (VVV) ESO Public Survey: Current Status and First Results
    (2011) Catelan, Marcio; Minniti, D.; Lucas, P. W.; Alonso-García, J.; Angeloni, R.; Beamín, J. C.; Bonatto, C.; Borissova, J.; Contreras, C.; Cross, N.; Dékáany, I.; Emerson, J. P.; Eyheramendy, S.; Geisler, D.; González-Solares, E.; Helminiak, K. G.; Hempel, M.; Irwin, M. J.; Ivanov, V. D.; Jordán, A.; Kerins, E.; Kurtev, R.; Mauro, F.; Moni Bidin, C.; Navarrete, C.; Pérez, P.; Pichara, K.; Read, M.; Rejkuba, M.; Saito, R. K.; Sale, S. E.; Toledo, I.
    Vista Variables in the Vía Láctea (VVV) is an ESO Public Survey that is performing a variability survey of the Galactic bulge and part of the inner disk using ESO's Visible and Infrared Survey Telescope for Astronomy (VISTA). The survey covers 520 { deg}^2 of sky area in the ZYJHK_S filters, for a total observing time of 1929 hours, including ∼ 10^9 point sources and an estimated ∼ 10^6 variable stars. Here we describe the current status of the VVV Survey, in addition to a variety of new results based on VVV data, including light curves for variable stars, newly discovered globular clusters, open clusters, and associations. A set of reddening-free indices based on the ZYJHK_S system is also introduced. Finally, we provide an overview of the VVV Templates Project, whose main goal is to derive well-defined light curve templates in the near-IR, for the automated classification of VVV light curves....
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    The VVV Infrared Variability Catalog (VIVA-I)
    (2020) Ferreira Lopes, E. C.; Cross, N. J. G.; Catelan, M.; Minniti, D.; Hempel, M.; Lucas, W. P.; Angeloni, R.; Jablonsky, F.; Braga, F. V.; Leao, C. I.; Herpich, F. R.; Alonso-Garcia, J.; Papageorgiou, A.; Pichara, K.; Saito, K. R.; Bradley, A.; Beamin Muhlenbrock Juan Carlos; Cortes, C.; De Medeiros, J. R.; Russell, Christopher
    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.
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    The VVV Templates Project
    (2014) Contreras Ramos, R.; Catelan, Marcio; Gran, F.; Navarrete, C.; Angeloni, R.; Alonso-García, J.; Dékány, I.; Hajdu, G.; Hempel, M.; Jordán, A.; Townsend, B.; Borissova, J.; Navarro, C.; Pichara, K.; Eyheramendy, S.
    Until now, stellar variability in the near-IR has been a relatively ill-explored research field. In particular, the number of high-quality light curves is very limited and, even worse, many variability classes have not yet been observed in a sufficiently extensive way in the near-IR, so that good light curves are entirely lacking for some such classes. Since VVV is the first ever large survey dedicated to stellar variability in the near-infrared, the first problem we had to face has thus been the construction of a proper statistically significant database of high-quality (i.e., template) near-IR light curves for a significant sample of stars taken to be representative of the different variability classes under study. The main purpose of the VVV Templates Project is thus to build a large database of well-defined, high-quality, near-IR light curves for variable stars of different types, which will form the basis of the VVV automated classification algorithms...
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    The VVV Templates Project Towards Automated Classification of VVV Light Curves
    (2011) Catelan, Marcio; Angeloni, R.; Dékány, I.; Pichara, K.; Eyheramendy, S.; Borissova, J.
    The main goal of the VVV Templates Project is to build a large database of well-defined, high-quality near-IR light curves for variable stars of different types, which will form the basis of the VVV automated classification algorithms.