V* V784 Cyg , the SIMBAD biblio

V* V784 Cyg , the SIMBAD biblio (23 results) C.D.S. - SIMBAD4 rel 1.8 - 2024.04.20CEST03:35:24

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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
1955AJ.....60..173M 5 ~ VV 21-25 and the Vatican variable star program. MILLER W.J.
1956RA......3..381M 65 T                   1 30 1 Five new RR Lyrae variables in the Cygnus cloud, VV 21
-25. 		MILLER W.J.S.J.
1968RA......7..313M 201 ~ Ten new variable stars in the Cygnus cloud, VV 191-200. MILLER W.J.
2010MNRAS.409.1585B 16       D               1 33 121 Flavours of variability: 29 RR Lyrae stars observed with Kepler. BENKO J.M., KOLENBERG K., SZABO R., et al.
2011MNRAS.417.1022N 1782       D     X C F     45 58 80 Fourier analysis of non-blazhko ab-type RR Lyrae stars observed with the Kepler space telescope. NEMEC J.M., SMOLEC R., BENKO J.M., et al.
2012MNRAS.426.2413B 15       D               2 62 18 A search for SX Phe stars among Kepler δ Scuti stars. BALONA L.A. and NEMEC J.M.
2013ApJ...773..181N 546     A D     X         15 68 131 Metal abundances, radial velocities, and other physical characteristics for the RR Lyrae stars in the Kepler field. NEMEC J.M., COHEN J.G., RIPEPI V., et al.
2014ApJS..211...24M viz 16       D               1 34022 573 Rotation periods of 34,030 Kepler main-sequence stars: the full autocorrelation sample. McQUILLAN A., MAZEH T. and AIGRAIN S.
2014AJ....147..119C viz 16       D               1 8010 91 Contamination in the Kepler field. Identification of 685 KOIs as false positives via ephemeris matching based on Q1-Q12 data. COUGHLIN J.L., THOMPSON S.E., BRYSON S.T., 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.
2016ApJ...829...23D viz 16       D               1 4044 212 The Kepler catalog of stellar flares. DAVENPORT J.R.A.
2016ApJS..227...30N 16       D               4 47 4 The Palomar Transient Factory and RR Lyrae: the metallicity-light curve relation based on ab-type RR Lyrae in the Kepler field. NGEOW C.-C., YU P.-C., BELLM E., et al.
2017MNRAS.466.1290N viz 41           X         1 66 14 Metal-rich SX Phe stars in the Kepler field. NEMEC J.M., BALONA L.A., MURPHY S.J., 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.
2018MNRAS.473..412B 16       D               1 37 3 On the connection between almost periodic functions and Blazhko light curves. BENKO J.M.
2018ApJ...864...57M viz 16       D               1 159 5 Chemical compositions of field and globular cluster RR Lyrae stars. I. NGC 3201. MAGURNO D., SNEDEN C., BRAGA V.F., et al.
2018AJ....156..241H viz 16       D               1 311114 199 A first catalog of variable stars measured by the Asteroid Terrestrial-impact Last Alert System (ATLAS). HEINZE A.N., TONRY J.L., DENNEAU L., 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.
2019MNRAS.485.5897B 351       D     X         9 35 2 Revisiting the Kepler non-Blazhko RR Lyrae sample: cycle-to-cyle variations and additional modes. BENKO J.M., JURCSIK J. and DEREKAS A.
2021MNRAS.500.5009M viz 17       D               1 168 ~ A theoretical scenario for Galactic RR Lyrae in the Gaia data base: constraints on the parallax offset. MARCONI M., MOLINARO R., RIPEPI V., et al.
2022AJ....164...45N viz 18       D               2 31 2 Evaluating the V-band Photometric Metallicity with Fundamental Mode RR Lyrae in the Kepler Field. NGEOW C.-C.
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.
2023AJ....166...83L 19       D               1 14 ~ Two Different Weak Modulations in ab-type RR Lyrae Variable V838 Cyg, and Potential Influence of Metal Abundance on Blazhko Modulation. LI L.-J., QIAN S.-B., SHI X.-D., et al.

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