Radio loudness and classification for radio sources. (30th January 2021)

• Record Type: Journal Article
• Authors: Zhang, Lixia; Fan, Junhui; Zhu, Jingtian
• Is Part Of: Publications of the Astronomical Society of Japan. Volume 73:Number 2(2021)
• Page Start: 313
• Page End: 325
• Publication Date: 2021-01-30
• Subjects: galaxies: active -- galaxies: jets -- quasars: general; Astronomy -- Periodicals; 520.5
• DOI: 10.1093/pasj/psaa122
• Languages: English
• ISSNs: 0004-6264

Abstract

Abstract: The extragalactic radio sources are divided into two subclasses (radio-loud and radio-quiet sources) in the literature using radio loudness ( R ), which is defined as the ratio of radio emission to optical emission, but the boundary R -value separating the two classes is different in various sources. In this work, a sample of 2419 objects from the 13th catalog of quasars and active nuclei is used to build a boundary for the two subclasses. To do so, we compiled the radio and optical data, calculated their radio and optical indexes, made K -correction, obtained the radio loudness, and adopted a Bayesian analysis method to the logarithm of radio loudness for classification. We also investigated the correlations of radio loudness with radio/optical luminosities. Our main conclusions are summarized as follows: (1) The distribution of the logarithm of radio loudness (log R ) is bimodal, the sources with log R < 1.26 are classified as radio-quiet sources, and those with log R > 1.26 are classified as radio-loud ones from the Bayesian analysis method. (2) The average radio-optical effective spectral index of radio-quiet sources is 〈α RO 〉 = 0.05, while that of radio-loud sources is 〈α RO 〉 = 0.55. (3) There are positive correlations between radio luminosity and radio loudness for both radio-loud sources and radio-quiet sources. (4) A dividing line of separating the distribution of the clusters on the diagram of radio loudness against radio luminosity was obtained statistically to set the boundary between radio-loud sources and radio-quiet sources, with an accuracy of $99.73\%$ based on the classification result from the Bayesian analysis method.