Fraction of broad absorption line quasars in different radio morphologies

ABSTRACT In this study, we investigated the orientation model of Broad Absorption Line (BAL) quasars using a sample sources that are common in Sloan Digital Sky Survey (SDSS) Data Release (DR)-16 quasar catalogue and Very Large Array (VLA)-Faint Images Radio at Twenty Centimeters (FIRST) survey. Using radio cut-out images from FIRST survey, first designed deep-learning convolutional neural networks (CNN) to classify morphologies into core-only, young jet, single lobe, or triples. These further sub-classified core-dominated lobe-dominated sources. The CNN models can with high precision >98 ${{\ \rm per\ cent}}$ for all morphological sub-classes. average BAL fraction resolved core, core-dominated, consistent inferred infrared surveys. We also present distribution as function by core-dominance an indicator. A similar analysis is performed HiBALs, LoBALs, FeLoBALs. All sub-classes show increase angles jets respect line sight. Our suggests more likely be found viewing close equatorial plane quasar. However, pure inadequate, combination evolution probably best way explain complete phenomena.