SV* HV 1738 , the SIMBAD biblio

SV* HV 1738 , the SIMBAD biblio (10 results) C.D.S. - SIMBAD4 rel 1.8 - 2024.04.25CEST10:57:33


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Keywords
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Title First 3 Authors
2004MNRAS.353..601E viz 4200 120 A 2dF survey of the Small Magellanic Cloud. EVANS C.J., HOWARTH I.D., IRWIN M.J., et al.
2008MNRAS.386..826E viz 15       D               2056 44 Kinematics of massive stars in the Small Magellanic Cloud. EVANS C.J. and HOWARTH I.D.
2010AJ....140..416B viz 15       D               1 5311 140 Spitzer SAGE-SMC infrared photometry of massive stars in the Small Magellanic Cloud. BONANOS A.Z., LENNON D.J., KOHLINGER F., et al.
2010AcA....60..165S viz 15       D               1 2480 68 The Optical Gravitational Lensing Experiment. The OGLE-III Catalog of Variable Stars. IX. RR Lyr stars in the Small Magellanic Cloud. SOSZYNSKI I., UDALSKI A., SZYMANSKI M.K., et al.
2016AcA....66..131S viz 16       D               1 46551 96 The OGLE Collection of Variable Stars. Over 45 000 RR Lyrae Stars in the Magellanic System. SOSZYNSKI I., UDALSKI A., SZYMANSKI M.K., et al.
2018MNRAS.480..669P viz 16       D               1 3119 2 Photometric study of the SMCNOD using variable stars from the OGLE-IV survey. PRUDIL Z., GREBEL E.K., DEKANY I., 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.
2019AcA....69...87S 17       D               1 47837 ~ Final Release of the OGLE Collection of Cepheids and RR Lyrae Stars in the Magellanic System. The Outer Regions. SOSZYNSKI I., UDALSKI A., SZYMANSKI M.K., et al.
2020MNRAS.491.4752B viz 17       D               1 13884 ~ When a period is not a full stop: Light-curve structure reveals fundamental parameters of Cepheid and RR Lyrae stars. BELLINGER E.P., KANBUR S.M., BHARDWAJ A., 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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