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作 者:Dmitry O.Kudryavtsev Yulia V.Sotnikova Vladislav A.Stolyarov Timur V.Mufakharov Valery V.Vlasyuk Margarita L.Khabibullina Alexander G.Mikhailov Yulia V.Cherepkova
机构地区:[1]Special Astrophysical Observatory of the Russian Academy of Sciences,Nizhny Arkhyz 369167,Russia [2]Astrophysics Group,Cavendish Laboratory,University of Cambridge,Cambridge CB3 OHE,UK [3]Kazan Federal University,18 Kremlyovskaya St,Kazan 420008,Russia
出 处:《Research in Astronomy and Astrophysics》2024年第5期117-139,共23页天文和天体物理学研究(英文版)
摘 要:Based on the collected multiwavelength data, namely in the radio(NVSS, FIRST, RATAN-600), IR(WISE),optical(Pan-STARRS), UV(GALEX), and X-ray(ROSAT, Swift-XRT) ranges, we have performed a cluster analysis for the blazars of the Roma-BZCAT catalog. Using two machine learning methods, namely a combination of PCA with k-means clustering and Kohonen's self-organizing maps(SOMs), we have constructed an independent classification of the blazars(five classes) and compared the classes with the known Roma-BZCAT classification(FSRQs, BL Lacs, galaxy-dominated BL Lacs, and blazars of an uncertain type) as well as with the high synchrotron peaked(HSP) blazars from the 3HSP catalog and blazars from the TeVCat catalog. The obtained groups demonstrate concordance with the BL Lac/FSRQ classification along with a continuous character of the change in the properties. The group of HSP blazars stands out against the overall distribution. We examine the characteristics of the five groups and demonstrate distinctions in their spectral energy distribution shapes. The effectiveness of the clustering technique for objective analysis of multiparametric arrays of experimental data is demonstrated.
关 键 词:methods data analysis-galaxies active-(galaxies:)BL Lacertae objects GENERAL
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