V* V524 Her , the SIMBAD biblio

V* V524 Her , the SIMBAD biblio (13 results) C.D.S. - SIMBAD4 rel 1.8 - 2024.04.25CEST12:25:52


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Title First 3 Authors
1966VeSon...7...61G 243 12 Die veranderlichen Sterne der nordlichen Milchstrasse. Teil XIII. GESSNER H.
1986AJ.....91..354Y 661 25 On optical studies of high-velocity clouds. YORK D.G., BURKS G.S. and GIBNEY T.B.
1987ATsir1489....8H 70 T                   1 1 0 Observations of
V524 Herculis.
HACKE G.
1988MitVS..11...97H 1 0 Photographische Beobachtungen von V524 Herculis. HACKE G. and RICHERT M.
1989MitVS..12....9G 227 0 Optical behaviour of the X-ray binary V1727 Cygni = 4U 2129+47 in the season 1988/1989. GOETZ W.
1992IBVS.3778....1S 7 0 NSV 07453 is a new short period Cepheid or a long period RR Lyrae star. SHUGAROV S.Y.
2000IBVS.4897....1K 253 3 Coordinates and identifications for Sonneberg variables on MVS 295-301. KINNUNEN T. and SKIFF B.A.
2007A&A...476..307L viz 15       D               127 85 Stellar evolution through the ages: period variations in galactic RRab stars as derived from the GEOS database and TAROT telescopes. LE BORGNE J.F., PASCHKE A., VANDENBROERE J., 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.
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.

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