Scinovex
article Open AccessTop 1% cited

X-ray spectral modelling of the AGN obscuring region in the CDFS: Bayesian model selection and catalogue

Astronomy and Astrophysics · 2014 · Vol. 564 · pp. A125–A125
Johannes BüchnerA. GeorgakakisK. NandraLi-Ting HsuC. RangelMurray BrightmanA. MerloniM. SalvatoJ. L. DonleyDale D. Kocevski

Abstract

Aims. Active galactic nuclei are known to have complex X-ray spectra that depend on both the properties of the accreting super-massive black hole (e.g. mass, accretion rate) and the distribution of obscuring material in its vicinity (i.e. the "torus"). Often however, simple and even unphysical models are adopted to represent the X-ray spectra of AGN, which do not capture the complexity and diversity of the observations. In the case of blank field surveys in particular, this should have an impact on e.g. the determination of the AGN luminosity function, the inferred accretion history of the Universe and also on our understanding of the relation between AGN and their host galaxies. Methods. We develop a Bayesian framework for model comparison and parameter estimation of X-ray spectra. We take into account uncertainties associated with both the Poisson nature of X-ray data and the determination of source redshift using photometric methods. We also demonstrate how Bayesian model comparison can be used to select among ten different physically motivated X-ray spectral models the one that provides a better representation of the observations. This methodology is applied to X-ray AGN in the 4 Ms Chandra Deep Field South. Results. For the 350 AGN in that field, our analysis identifies four components needed to represent the diversity of the observed X-ray spectra: (1) an intrinsic power law; (2) a cold obscurer which reprocesses the radiation due to photo-electric absorption, Compton scattering and Fe-K fluorescence; (3) an unabsorbed power law associated with Thomson scattering off ionised clouds; and (4) Compton reflection, most noticeable from a stronger-than-expected Fe-K line. Simpler models, such as a photo-electrically absorbed power law with a Thomson scattering component, are ruled out with decisive evidence (B > 100). We also find that ignoring the Thomson scattering component results in underestimation of the inferred column density, N H , of the obscurer. Regarding the geometry of the obscurer, there is strong evidence against both a completely closed (e.g. sphere), or entirely open (e.g. blob of material along the line of sight), toroidal geometry in favour of an intermediate case.

Astrophysical Phenomena and ObservationsGalaxies: Formation, Evolution, PhenomenaGamma-ray bursts and supernovaePhysicsAstrophysicsChandra Deep Field SouthSpectral lineRedshiftTorusGalaxyAccretion (finance)Active galactic nucleusLuminosity

Funding

  • European Commission
  • Max-Planck-Gesellschaft
Citations
1,570
FWCI
22.54
field-weighted impact
References
111
Percentile
100%
vs. same field & year
Citations per year
Cited by
New binary black hole mergers in the second observing run of Advanced LIGO and Advanced Virgo
Physical review. D/Physical review. D. · 2020 · 352 citations
Bilby: A User-friendly Bayesian Inference Library forGravitational-wave Astronomy
The Astrophysical Journal Supplement Series · 2019 · 1,006 citations
A NICER View of PSR J0030+0451: Millisecond Pulsar Parameter Estimation
The Astrophysical Journal Letters · 2019 · 1,555 citations
References
Angle-dependent Compton reflection of X-rays and gamma-rays
Monthly Notices of the Royal Astronomical Society · 1995 · 1,347 citations
Parameter estimation in astronomy through application of the likelihood ratio
The Astrophysical Journal · 1979 · 2,913 citations
MultiNest: an efficient and robust Bayesian inference tool for cosmology and particle physics
Monthly Notices of the Royal Astronomical Society · 2009 · 2,796 citations
A new look at the statistical model identification
IEEE Transactions on Automatic Control · 1974 · 49,965 citations
Nested Sampling
AIP conference proceedings · 2004 · 860 citations
Citation Network

How this paper connects to the literature. Drag to explore, click any node to open that paper.