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

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 (N_H), the so-called Compton-thick (N_H,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 3 to be obscured with 22.7 < LogN_H,los ≤ 23.0, 5 with 23.0 < LogN_H,los ≤ 23.25, and 3 with 23.4 < LogN_H,los ≤ 23.9, according to UXClumpy. Meanwhile, according to RXTorusD, we found 3 AGN to be obscured with 22.7 < LogN_H,los ≤ 23.0, 4 with 23.0 < LogN_H,los ≤ 23.4, and 4 with 23.85 < LogN_H,los ≤ 23.96. Additionally, this work served as a comparison between UXClumpy and RXTorusD. We found broad agreement between the two, with 8 of 11 sources agreeing on the value of the photon index Γ, while only 5 of 11 sources agree on the N_H,los value within the 90% confidence level.