Compton-thick AGN in the NuSTAR Era. XI. Analyzing 11 CT-AGN Candidates Selected with Machine Learning

Abstract

This work discusses the broadband X-ray spectral analysis of 11 candidate heavily-obscured active galactic nuclei (AGN) selected based on their infrared and X-ray properties by a recently published machine learning algorithm. This paper is part of a larger work to identify and characterize all AGN in the local universe (z < 0.1) with the largest line-of-sight (los) column densities (NH), the so-called Compton-thick (CT-, NH,los >= 1024 cm-2) AGN. We modeled the X-ray spectra using two physically- motivated models, UXClumpy and RXTorusD. Of the 11 AGN in our sample, we found three to be obscured with 22.7 < LogNH,los <= 23.0, five have 23.0 < LogNH,los <= 23.25, and three have 23.4 < LogNH,los <= 23.9, according to UXClumpy. Meanwhile, according to RXTorusD, we found three AGN to be obscured with 22.7 < LogNH,los <= 23.0, four with 23.0 < LogNH,los <= 23.4, and four with 23.85 < LogNH,los <= 23.96. Additionally, this work served as a comparison between UXClumpy and RXTorusD. We found broad agreement between the two, with 8/11 sources agreeing on the value of the photon index Gamma, while only 5/11 sources agreeing on the NH,los value within the 90% confidence level.