English

Unveiling Obscured Accretion in the Local Universe

High Energy Astrophysical Phenomena 2025-09-29 v1 Astrophysics of Galaxies

Abstract

Heavily obscured Active Galactic Nuclei (AGN), especially Compton-thick sources with line-of-sight column density (NH,losN_{\rm H,los}) >> 1024^{24} cm2^{-2}, are critical to understanding supermassive black hole (SMBH) growth and the origin of the Cosmic X-ray Background (CXB). However, their observed fraction remains significantly below model predictions, due to strong absorption bias, even in the hard X-ray (i.e., above 10 keV) band. We analyze a sample of 26 nearby (z<0.1z < 0.1) AGN from the Swift-BAT 150-month catalog, selected via mid-IR to X-ray diagnostics and observed with NuSTAR and soft X-ray telescopes (Xmm-Newton, Chandra, or Swift-xrt). Using self-consistent torus models (MyTorus, Borus02, and UXCLUMPY), we aim to constrain NH,losN_{\rm H,los}, the average torus column density, and other geometrical parameters of the obscuring medium. A comparative analysis among the three torus models showed that while estimates of NH,losN_{\rm{H,los}} were generally in agreement, Borus02 tended to classify a slightly larger number of sources as Compton-thick AGN (CT-AGN). Building on this comparison, we benchmark two prediction schemes -- a mid-IR/X-ray relation and a machine-learning model -- against our broadband best-fit NH,losN_{\rm H,los} measurements to assess which approach more effectively bridges the gap between predicted and measured obscuration, finding that while the former works effectively in the heavily obscured region (logNH\rm{N_H} \gtrsim 23.5 cm2\rm{cm^{-2}}), the latter provides improved accuracy, particularly for Compton-thin to moderately thick regimes (logNH\rm{N_H} \lesssim 23.5 cm2\rm{cm^{-2}}).

Keywords

Cite

@article{arxiv.2509.21532,
  title  = {Unveiling Obscured Accretion in the Local Universe},
  author = {Indrani Pal and Stefano Marchesi and Ross Silver and Marco Ajello and Vittoria Gianolli and Núria Torres-Albà and Isaiah Cox and Xiurui Zhao and Dhrubojyoti Sengupta and Anuvab Banerjee and Kouser Imam and Andrealuna Pizzetti},
  journal= {arXiv preprint arXiv:2509.21532},
  year   = {2025}
}

Comments

16 pages, 13 Figures, submitted to the journal