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

التفاصيل البيبلوغرافية
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
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
الوصف
تدمد:10637737
15626873
DOI:10.1134/s1063773723070022