Fraction of broad absorption line quasars in different radio morphologies
Akhil Nair, M. Vivek

TL;DR
This study uses deep learning to classify radio morphologies of quasars and investigates the orientation model of BAL quasars, finding that BAL features are more common at equatorial viewing angles, suggesting a combined orientation and evolution model.
Contribution
Introduces a CNN-based classification of quasar radio morphologies and analyzes BAL fractions across orientations, advancing understanding of BAL quasar geometry.
Findings
High classification accuracy (>98%) for radio morphologies.
BAL fraction increases at high jet orientation angles.
BAL quasars are more likely viewed near the equatorial plane.
Abstract
In this study, we investigated the orientation model of Broad Absorption Line (BAL) quasars using a sample of sources that are common in Sloan Digital Sky Survey (SDSS) Data Release (DR)-16 quasar catalog and Very Large Array (VLA)-Faint Images of the Radio Sky at Twenty Centimeters (FIRST) survey. Using the radio cut-out images from the FIRST survey, we first designed a deep learning model using convolutional neural networks (CNN) to classify the quasar radio morphologies into the core-only, young jet, single lobe, or triples. These radio morphologies are further sub-classified into core-dominated and lobe-dominated sources. The CNN models can classify the sources with a high precision of >98% for all the morphological sub-classes. The average BAL fraction in the resolved core, core-dominated, and lobe-dominated quasars are consistent with the BAL fraction inferred from radio and…
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