V* V492 And , the SIMBAD biblio

V* V492 And , the SIMBAD biblio (9 results) C.D.S. - SIMBAD4 rel 1.8 - 2024.04.18CEST06:00:50

Sort references on where and how often the object is cited
trying to find the most relevant references on this object.
More on score
Bibcode/DOI Score in Title|Abstract|
Keywords 		in a table in teXt, Caption, ... Nb occurence Nb objects in ref Citations
(from ADS) 		Title First 3 Authors
2006AJ....132.1202K viz 15       D               1185 88 Analysis of RR Lyrae stars in the northern sky variability survey. KINEMUCHI K., SMITH H.A., WOZNIAK P.R., et al.
2008AJ....135..564B viz 15       D               2416 28 The Century Survey Galactic Halo Project. III. A complete 4300°2 survey of blue horizontal branch stars in the metal-weak thick disk and inner halo. BROWN W.R., BEERS T.C., WILHELM R., et al.
2011IBVS.5969....1K viz 15       D               1 2040 27 The 80th name-list of variable stars. Part I - RA 0h to 6h. KAZAROVETS E.V., SAMUS N.N., DURLEVICH O.V., et al.
2013ApJ...763...32D viz 16       D               1 12288 202 Probing the outer galactic halo with RR Lyrae from the Catalina surveys. DRAKE A.J., CATELAN M., DJORGOVSKI S.G., et al.
2014IBVS.6106....1B viz 16       D               1 587 6 RR Lyrae stars in the GCVS observed by the Qatar Exoplanet Survey. BRAMICH D.M., ALSUBAI K.A., ARELLANO FERRO A., et al.
2014MNRAS.441..715G viz 16       D               1 13079 14 A mid-infrared study of RR Lyrae stars with the Wide-field Infrared Survey Explorer all-sky data release. GAVRILCHENKO T., KLEIN C.R., BLOOM J.S., et al.
2017AJ....153..204S viz 16       D               1 46977 123 Machine-learned identification of RR Lyrae stars from sparse, multi-band data: the PS1 sample. SESAR B., HERNITSCHEK N., MITROVIC S., et al.
2019A&A...622A..60C viz 17       D               1 150347 194 Gaia Data Release 2. Specific characterisation and validation of all-sky Cepheids and RR Lyrae stars. CLEMENTINI G., RIPEPI V., MOLINARO R., et al.
2022ApJS..261...33D viz 18       D               1 104673 3 Photometric Metallicity Prediction of Fundamental-mode RR Lyrae Stars in the Gaia Optical and Ks Infrared Wave Bands by Deep Learning. DEKANY I. and GREBEL E.K.

goto View the references in ADS