Browsing by Author "Hajdu, G."

Now showing 1 - 4 of 4
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    A machine learned classifier for RR Lyrae in the VVV survey
    (2016) Elorrieta López, Felipe; Eyheramendy Duerr, Susana; Jordán Colzani, Andrés Cristóbal; Dekany, Istvan; Catelan, Márcio; Angeloni, Rodolfo; Alonso, J.; Contreras, R.; Gran, F.; Hajdu, G.; Espinoza, N.; Saito, R.; Minniti, D.
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    An UXor among FUors: Extinction-related Brightness Variations of the Young Eruptive Star V582 Aur
    (2018) Abraham, P.; Kospal, A.; Kun, M.; Feher, O.; Zsidi, G.; Acosta-Pulido, J. A.; Carnerero, M. I.; Garcia-Alvarez, D.; Moor, A.; Cseh, B.; Hajdu, G.; Hanyecz, O.; Kelemen, J.; Kriskovics, L.; Marton, G.; Mezo, Gy.; Molnar, L.; Ordasi, A.; R
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    Milky Way metallicity gradient from Gaia DR2 F/1O double-mode Cepheids
    (2018) Lemasle, B.; Hajdu, G.; Kovtyukh, V.; Inno, L.; Grebel, E. K.; Catelan, Márcio; Bono, G.; François, P.; Kniazev, A.; da Silva, R.; Storm, J.
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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...