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

TL;DR

This study analyzes 11 candidate heavily-obscured AGN selected via machine learning, using broadband X-ray spectral models to determine their column densities and compare modeling approaches, advancing the understanding of Compton-thick AGN.

Contribution

It provides the first detailed spectral analysis of ML-selected CT-AGN candidates and compares two physically-motivated models, UXClumpy and RXTorusD, for estimating obscuration.

Findings

Three AGN are mildly obscured with LogNH,los between 22.7 and 23.0.

Five AGN have LogNH,los between 23.0 and 23.25.

Broad agreement between models on photon index, less so on NH,los.

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.