Abstract
We adopt a Bayesian X-ray spectral approach to investigate the accretion properties of unobscured (20 < log (NH/cm?2 <22) and obscured (22 < log (NH/cm -2 < 24) active galactic nuclei (AGNs) to shed light on the orientation versus evolution scenarios for the origin of the obscuring material. For a sample of 3882 X-ray-selected AGN from the Chandra COSMOS Legacy, AEGIS, and CDFS extragalactic surveys, we constrain their stellar masses, intrinsic X-ray luminosities, obscuring column densities, and specific accretion rates Λ ∝ LX/M∗. By combining these observables within a Bayesian non-parametric approach, we infer, for the first time, the specific accretion rate distribution (SARD) of obscured and unobscured AGN to, i.e. the probability of a galaxy with mass M∗ at redshift z hosting an AGN with column density and specific accretion rate Λ. Our findings indicate that (1) both obscured and unobscured SARDs share similar shapes, shifting towards higher accretion rates with redshift, (2) unobscured SARDs exhibit a systematic offset towards higher Λ compared to obscured SARD for all redshift intervals, (3) the obscured AGN fraction declines sharply at log Λbreak Λ-2 for z < 0. 5,, but shifts to higher Λ values with increasing redshift, (4) the incidence of AGN within the theoretically unstable blow-out region of the Λ-N H plane increases with redshift. These observations provide compelling evidence for AGN 'downsizing' and radiation-regulated nuclear-scale obscuration with an increasing host galaxy contribution towards higher redshifts.
| Original language | English |
|---|---|
| Pages (from-to) | 3459-3479 |
| Number of pages | 21 |
| Journal | Monthly Notices of the Royal Astronomical Society |
| Volume | 532 |
| Issue number | 3 |
| Early online date | 4 Jul 2024 |
| DOIs | |
| Publication status | Published - 31 Aug 2024 |
Data Availability Statement
We release the Stan products of the SARD calculations along with the scripts to exploit and display the data. The files are described and available at https://doi.org/10.5281/zenodo.10797147.All other data products used in this paper are available on-demand to the authors.
Funding
The research leading to these results has received funding from the EU H2020-MSCA-ITN-2019 Project 860744 BiD4BESt: Big Data applications for black hole Evolution STudies and the Hellenic Foundation for Research and Innovation (HFRI) project 4MOVE- U grant agreement 2688, which is part of the programme 2nd Call for HFRI Research Projects to support Faculty Members and Researchers . This research made use of ASTROPY , 3 a community-developed core Python package for Astronomy (Astropy Collaboration 2013 , 2018 ). This research has made use of data obtained from the Chandra Data Archive and the Chandra Source Catalogue, and software provided by the Chandra X-ray Center (CXC) in the application packages CIAO and SHERPA . For analysing X-ray spec- tra, we use the analysis software BXA (Buchner et al. 2014 ), which connects the nested sampling algorithm ULTRANEST (Buch- ner 2021 ) with the fitting environment CIAO/SHERPA (Fruscione et al. 2006 ). DMA additionally thanks the Science Technology Facilities Council (STFC) for support from the Durham consolidated grant (ST/T000244/1). AL was partially funded by Data Science meth- ods for MultiMessenger Astrophysics and Multi-Surv e y Cosmology funded by the Italian Ministry of University and Research, Pro- grammazione triennale 2021/2023 (DM n.2503 dd. 9 December 2019), Programma Congiunto Scuole. RCH acknowledges support from NASA through ADAP grant number 80NSSC23K0485. JA ac- knowledges support from United Kingdom Research and Innovation (UKRI) grant MR/T020989/1. For the purpose of open access, the authors have applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission. DMA additionally thanks the Science Technology Facilities Council (STFC) for support from the Durham consolidated grant (ST/T000244/1). AL was partially funded by \u2018Data Science methods for MultiMessenger Astrophysics & Multi-Survey Cosmology\u2019 funded by the Italian Ministry of University and Research, Programmazione triennale 2021/2023 (DM n.2503 dd. 9 December 2019), Programma Congiunto Scuole. RCH acknowledges support from NASA through ADAP grant number 80NSSC23K0485. JA acknowledges support from United Kingdom Research and Innovation (UKRI) grant MR/T020989/1. The research leading to these results has received funding from the EU H2020-MSCA-ITN-2019 Project 860744 \u2018BiD4BESt: Big Data applications for black hole Evolution STudies\u2019 and the Hellenic Foundation for Research and Innovation (HFRI) project \u20184MOVE-U\u2019 grant agreement 2688, which is part of the programme \u20182nd Call for HFRI Research Projects to support Faculty Members and Researchers\u2019.
| Funders | Funder number |
|---|---|
| CIAO | |
| Chandra X-ray Center | |
| United Kingdom Research and Innovation | MR/T020989/1 |
| NASA/LARC | 80NSSC23K0485 |
| Hellenic Foundation for Research and Innovation | 2688 |
| Hellenic Foundation for Research and Innovation | |
| Science and Technology Facilities Council | ST/T000244/1 |
| Science and Technology Facilities Council | |
| EU | 860744 |
| Ministero dell’Istruzione, dell’Università e della Ricerca | 2503 |
| Ministero dell’Istruzione, dell’Università e della Ricerca | |
| SHERPA | 2006 |
Keywords
- galaxies: active
- X-rays: galaxies-infrared: galaxies
ASJC Scopus subject areas
- Astronomy and Astrophysics
- Space and Planetary Science