Compton-thick AGN in the NuSTAR Era. XI. Analyzing 11 CT-AGN Candidates Selected with Machine Learning
Ross Silver, Nuria Torres-Alba, Stefano Marchesi, Vittoria Gianolli, Isaiah Cox, Dhrubojyoti Sengupta, Indrani Pal, Marco Ajello, Xiurui Zhao, Kouser Imam, Anuvab Banerjee
arXiv:2603.17077v1 Announce Type: new
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 = 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 arXiv:2603.17077v1 Announce Type: new
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 = 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

Comments are closed, but trackbacks and pingbacks are open.