RX J1744.0+7015 , the SIMBAD biblio

RX J1744.0+7015 , the SIMBAD biblio (11 results) C.D.S. - SIMBAD4 rel 1.8 - 2026.10.18CEST05:05:21


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in a table in teXt, Caption, ... Nb occurence Nb objects in ref Citations
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Title First 3 Authors
2003ApJS..149...29G viz 477 58 The ROSAT north ecliptic pole survey: the optical identifications. GIOIA I.M., HENRY J.P., MULLIS C.R., et al.
2006AJ....131..621G viz 15       D               1 1033 125 A catalog of 1022 bright contact binary stars. GETTEL S.J., GESKE M.T. and McKAY T.A.
2006AJ....131..633G viz 15       D               143 11 A ROSAT survey of contact binary stars. GESKE M.T., GETTEL S.J. and McKAY T.A.
2008A&A...483..801A 15       D               1 62 4 The stellar population of the Rosat North Ecliptic Pole survey. II. Spectral analysis. AFFER L., MICELA G. and MOREL T.
2009AJ....138..466H viz 15       D               1 4127 116 Automated variable star classification using the Northern Sky Variability Survey. HOFFMAN D.I., HARRISON T.E. and McNAMARA B.J.
2012AJ....143...99T viz 15       D               1 612 34 A BVRCIC survey of W Ursae Majoris binaries. TERRELL D., GROSS J. and COONEY W.R.
2022AJ....163..152S viz 17       D               1 583193 11 APOGEE Net: An Expanded Spectral Model of Both Low-mass and High-mass Stars. SPRAGUE D., CULHANE C., KOUNKEL M., et al.
2022ApJS..259...35A viz 17       D               1 611005 320 The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar, and APOGEE-2 Data. ABDURRO'UF, ACCETTA K., AERTS C., 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.
2023A&A...674A..34G viz 17       D               1 307215 85 Gaia Data Release 3 Stellar multiplicity, a teaser for the hidden treasure. GAIA COLLABORATION, ARENOU F., BABUSIAUX C., 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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