A machine learning algorithm for reliably predicting active galactic nucleus absorbing column densities

Abstract

We present a new method for predicting the line-of-sight column density (NH) values of active galactic nuclei (AGN) based on mid-infrared (MIR), soft X-ray, and hard X-ray data. We developed a multiple linear regression machine learning algorithm trained with WISE colors, Swift-BAT count rates, soft X-ray hardness ratios, and an MIR–soft X-ray flux ratio. Our algorithm was trained off 451 AGN from the Swift-BAT sample with known NH and has the ability to accurately predict NH values for AGN of all levels of obscuration, as evidenced by its Spearman correlation coefficient value of 0.86 and its 75% classification accuracy. This is significant as few other methods can be reliably applied to AGN with Log(NH < 22.5). It was determined that the two soft X-ray hardness ratios and the MIR–soft X-ray flux ratio were the largest contributors toward accurate NH determinations. We applied the algorithm to 487 AGN from the BAT 150 Month catalog with no previously measured NH values. This algorithm will continue to contribute significantly to finding Compton-thick (CT) AGN (NH ≥ 1024 cm−2), thus enabling us to determine the true intrinsic fraction of CT-AGN in the local Universe and their contribution to the cosmic X-ray background.

The High-Energy X-ray Probe (HEX-P): the circum-nuclear environment of growing supermassive black holes

“…NuSTAR (Harrison et al, 2013) provided the first focusing hard X-ray telescope in orbit, opening a new era into the pursuit and understanding of heavily obscured accretion onto supermassive black holes (see Section 2). To date, NuSTAR has provided the most sensitive insights into the X-ray obscuration of the brightest Compton-thick AGN known (Arévalo et al, 2014;Puccetti et al, 2014;Bauer et al, 2015;Puccetti et al, 2016), as well as the wider population identified previously with wide-field hard X-ray monitoring surveys (Annuar et al, 2015;Gandhi et al, 2017;Marchesi et al, 2017;2019b;Torres-Albà et al, 2021;Traina et al, 2021;Zhao et al, 2021;Pizzetti et al, 2022;Silver et al, 2022;Tanimoto et al, 2022). NuSTAR has also enabled unambiguous Compton-thick line-of-sight column density classifications for a bulk of the previously published candidate Compton-thick sources that had not been detected > 10 keV before (Baloković et al, 2014;Gandhi et al, 2014;Ptak et al, 2015;Boorman et al, 2016;Masini et al, 2016;Annuar et al, 2017;LaMassa et al, 2019;Kammoun et al, 2020).…”