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V* V1062 Oph , the SIMBAD biblio (11 results) | C.D.S. - SIMBAD4 rel 1.8 - 2024.05.08CEST10:08:52 |
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 |
---|---|---|---|---|---|---|---|---|---|
1966AN....289....1H | 596 | 25 | Mitteilungen uber neuentdeckte veraenderliche Sterne. | HOFFMEISTER C. | |||||
1968IBVS..311....1K | 1646 | 13 | Identification list of the new variable stars nominated in 1968 (an extract from the 56th nominating list) | KUKARKIN B.V., KHOLOPOV P.N., EFREMOV Y.N., et al. | |||||
1986AJ.....91..354Y | 661 | 25 | On optical studies of high-velocity clouds. | YORK D.G., BURKS G.S. and GIBNEY T.B. | |||||
1999IBVS.4762....1K | 171 | 3 | Precise coordinates of variable stars. (2). | KATO T. | |||||
2008IBVS.5858....1H | O | 10 | 0 | Elements for 10 RR Lyrae stars. | HAUSSLER K., BERTHOLD T. and KROLL P. | ||||
2013ApJ...763...32D | 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. | ||
2014MNRAS.441..715G | 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 | 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 | 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. | ||
2020ApJS..249...18C | 17 | D | 1 | 652546 | 122 | The Zwicky Transient Facility catalog of periodic variable stars. | CHEN X., WANG S., DENG L., et al. | ||
2022ApJS..261...33D | 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. |