BD+29 575 , the SIMBAD biblio

BD+29 575 , the SIMBAD biblio (12 results) C.D.S. - SIMBAD4 rel 1.8 - 2024.04.19CEST14:21:04


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Title First 3 Authors
1997A&A...323L..49P viz 14       D               1 118337 2498 The Hipparcos Catalogue. PERRYMAN M.A.C., LINDEGREN L., KOVALEVSKY J., et al.
2007A&A...474..653V viz 15       D               1 118081 3051 Validation of the new Hipparcos reduction. VAN LEEUWEN F.
2012A&A...546A..61D viz 15       D               1 88079 48 Radial velocities for the HIPPARCOS-Gaia Hundred-Thousand-Proper-Motion project. DE BRUIJNE J.H.J. and EILERS A.-C.
2012MNRAS.427..343M viz 15       D               1 95690 216 Fundamental parameters and infrared excesses of Hipparcos stars. McDONALD I., ZIJLSTRA A.A. and BOYER M.L.
2015MNRAS.449.1401H viz 16       D               1 3011 6 A large sample of metallic-line star candidates from LAMOST Data Release 1. HOU W., LUO A., YANG H., et al.
2017AJ....153..257O viz 16       D               1 10625 142 Comoving stars in Gaia DR1: an abundance of very wide separation comoving pairs. OH S., PRICE-WHELAN A.M., HOGG D.W., et al.
2018AJ....155..149B viz 16       D               1 9764 5 Fundamental properties of co-moving stars observed by Gaia. BOCHANSKI J.J., FAHERTY J.K., GAGNE J., et al.
2019A&A...623A..72K viz 17       D               1 117368 256 Stellar and substellar companions of nearby stars from Gaia DR2. Binarity from proper motion anomaly. KERVELLA P., ARENOU F., MIGNARD F., et al.
2019MNRAS.490.3158C viz 17       D               1 465834 28 A catalogue of stellar diameters and fluxes for mid-infrared interferometry. CRUZALEBES P., PETROV R.G., ROBBE-DUBOIS S., et al.
2020ApJS..247...11R viz 17       D               1 46227 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 115486 112 The Hipparcos-Gaia Catalog of Accelerations: Gaia EDR3 edition. BRANDT T.D.
2022ApJS..259...63S viz 18       D               1 10264 2 Objective Separation between CP1 and CP2 Based on Feature Extraction with Machine Learning. SHANG L.-H., LUO A.-L., WANG L., et al.

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