V* HN Dra , the SIMBAD biblio

V* HN Dra , the SIMBAD biblio (23 results) C.D.S. - SIMBAD4 rel 1.8 - 2026.10.17CEST07:34:38

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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
1997A&A...323L..49P viz 14       D               1 118341 2498 The Hipparcos Catalogue. PERRYMAN M.A.C., LINDEGREN L., KOVALEVSKY J., et al.
1999MNRAS.309L..19H 82 129 The domain of gamma Doradus variables in the Hertzsprung-Russell diagram. HANDLER G.
1999IBVS.4659....1K 3203 170 The 74th special name-list of variable stars. KAZAROVETS E.V., SAMUS N.N., DURLEVICH O.V., et al.
2003AJ....125.2196F 48 25 Spectroscopy of early F stars: γ Doradus candidates and possible metallic shell stars. FEKEL F.C., WARNER P.B. and KAYE A.B.
2004A&A...417..189M         O           47 59 Multi-site, multi-technique survey of γDoradus candidates. I. Spectroscopic results for 59 stars. MATHIAS P., LE CONTEL J.-M., CHAPELLIER E., et al.
2004A&A...426..247C viz 96 T   A   O           3 9
HD 173977: An ellipsoidal δ Scuti star variable. 		CHAPELLIER E., MATHIAS P., GARRIDO R., et al.
2007A&A...474..653V viz 15       D               1 118085 3051 Validation of the new Hipparcos reduction. VAN LEEUWEN F.
2010AJ....139..757K 15       D               1 50 8 The Taiwan-American Occultation Survey project stellar variability. I. Detection of low-amplitude δ Scuti stars. KIM D.-W., PROTOPAPAS P., ALCOCK C., et al.
2011MNRAS.414.2602D viz 2567 132 Random forest automated supervised classification of Hipparcos periodic variable stars. DUBATH P., RIMOLDINI L., SUVEGES M., et al.
2012MNRAS.427..343M viz 15       D               1 95691 216 Fundamental parameters and infrared excesses of Hipparcos stars. McDONALD I., ZIJLSTRA A.A. and BOYER M.L.
2013ApJ...777...77Z 15       D               1 82 52 On the pulsational-orbital-period relation of eclipsing binaries with δ-Sct components. ZHANG X.B., LUO C.Q. and FU J.N.
2014MNRAS.441..715G viz 15       D               1 13086 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.
1993yCat.3135....0C viz 14       D               1 252979 52 VizieR Online Data Catalog: Henry Draper Catalogue and Extension, published in Ann. Harvard Obs. 91-100 (1918-1925) CANNON A.J. and PICKERING E.C.
2017MNRAS.470..915K 16       D               2 94 49 Eclipsing binary stars with a δ Scuti component. KAHRAMAN ALICAVUS F., SOYDUGAN E., SMALLEY B., et al.
2017MNRAS.465.1181L 95       D       C       2 301 80 Catalogue and properties of δ Scuti stars in binaries. LIAKOS A. and NIARCHOS P.
2017A&A...605A..79G viz 16       D               1 735 92 Gaia Data Release 1. Testing parallaxes with local Cepheids and RR Lyrae stars. GAIA COLLABORATION, CLEMENTINI G., EYER L., et al.
2018A&A...620A.172Z viz 16       D               1 127610 99 3D mapping of young stars in the solar neighbourhood with Gaia DR2. ZARI E., HASHEMI H., BROWN A.G.A., et al.
2019A&A...623A..72K viz 16       D               1 117375 256 Stellar and substellar companions of nearby stars from Gaia DR2. Binarity from proper motion anomaly. KERVELLA P., ARENOU F., MIGNARD F., et al.
2019A&A...623A.116K viz 41           X         1 463 51 Multiplicity of Galactic Cepheids and RR Lyrae stars from Gaia DR2. I. Binarity from proper motion anomaly. KERVELLA P., GALLENNE A., EVANS N.R., et al.
2020ApJS..247...11R viz 16       D               1 46229 22 Radial velocity photon limits for the dwarf stars of spectral classes F-M. REINERS A. and ZECHMEISTER M.
2021ApJS..254...42B viz 17       D               1 115489 112 The Hipparcos-Gaia Catalog of Accelerations: Gaia EDR3 edition. BRANDT T.D.
2022MNRAS.516.2080B viz 17       D               3 436 7 Revisiting bright δ Scuti stars and their period-luminosity relation with TESS and Gaia DR3. BARAC N., BEDDING T.R., MURPHY S.J., et al.
2025A&A...695A..81U 93             C       2 80 ~ Detection of oscillation-like patterns in eclipsing binary light curves using neural network-based object detection algorithms. ULAS B., SZKLENAR T. and SZABO R.

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