HD 42514B , the SIMBAD biblio

HD 42514B , the SIMBAD biblio (11 results) C.D.S. - SIMBAD4 rel 1.8 - 2026.10.14CEST19:24:37


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Title First 3 Authors
1984AJ.....89..515D 149 14 A sample of solar-type stars of known age. DUNCAN D.K.
2009ApJS..184..138H viz 15       D               1 20623 68 XID II: statistical cross-association of ROSAT bright source catalog X-ray sources with 2MASS point source catalog near-infrared sources. HAAKONSEN C.B. and RUTLEDGE R.E.
2012AcA....62...67K viz 15       D               1 2326 121 ASAS photometry of ROSAT sources. I. Periodic variable stars coincident with bright sources from the ROSAT All Sky Survey. KIRAGA M.
2015A&A...580A..23P viz 16       D               2 60854 134 A new catalogue of Stroemgren-Crawford uvbyβ photometry. PAUNZEN E.
2016ApJ...826..171G viz 16       D               1 20831 48 The correlation between metallicity and debris disk mass. GASPAR A., RIEKE G.H. and BALLERING N.
2014ASPC..485..223B viz 15       D               1 465820 45 The JMMC stellar diameters catalog v2 (JSDC): a new release based on SearchCal improvements BOURGES L., LAFRASSE S., MELLA G., et al.
2017MNRAS.472..675A viz 16       D               1 13582 89 Wide binaries in Tycho-Gaia: search method and the distribution of orbital separations. ANDREWS J.J., CHANAME J. and AGUEROS M.A.
2019MNRAS.490.3158C viz 16       D               1 465839 28 A catalogue of stellar diameters and fluxes for mid-infrared interferometry. CRUZALEBES P., PETROV R.G., ROBBE-DUBOIS S., et al.
2020MNRAS.497.2250H viz 16       D               1 620 ~ Very wide companion fraction from Gaia DR2: A weak or no enhancement for hot Jupiter hosts, and a strong enhancement for contact binaries. HWANG H.-C., HAMER J.H., ZAKAMSKA N.L., et al.
2023A&A...674A..16M viz 17       D               1 2184478 19 Gaia Data Release 3 The first Gaia catalogue of eclipsing-binary candidates. MOWLAVI N., HOLL B., LECOEUR-TAIBI I., et al.
2024AJ....167..192D viz 18       D               1 1374 ~ Detection of Contact Binary Candidates Observed By TESS Using the Autoencoder Neural Network. DING X., SONG Z., WANG C., et al.

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