دورية أكاديمية
SRGz: Machine Learning Methods and Properties of the Catalog of SRG/eROSITA Point X-ray Source Optical Counterparts in the DESI Legacy Imaging Surveys Footprint
العنوان: | SRGz: Machine Learning Methods and Properties of the Catalog of SRG/eROSITA Point X-ray Source Optical Counterparts in the DESI Legacy Imaging Surveys Footprint |
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المؤلفون: | Meshcheryakov, A. V.Aff1, Aff2, IDS1063773723070022_cor1, Borisov, V. D.Aff2, Aff1, Khorunzhev, G. A., Medvedev, P. A., Gilfanov, M. R.Aff1, Aff3, Belvedersky, M. I., Sazonov, S. Yu., Burenin, R. A., Krivonos, R. A., Bikmaev, I. F., Khamitov, I. M., Gerasimov, S. V., Mashechkin, I. V., Sunyaev, R. A.Aff1, Aff3 |
المصدر: | Astronomy Letters: A Journal of Astronomy and Space Astrophysics. 49(7):359-409 |
قاعدة البيانات: | Springer Nature Journals |
تدمد: | 10637737 15626873 |
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DOI: | 10.1134/s1063773723070022 |