Reconstructing AGN X-ray spectral parameter distributions with Bayesian methods II: Population inference [HEAP]

http://arxiv.org/abs/2111.15235


We present a new Bayesian method to reconstruct the parent distributions of X-ray spectral parameters of active galactic nuclei (AGN) in large surveys, using the probability distribution function (PDF) of posteriors obtained by fitting a consistent physical model to each object with a Bayesian method, presented in our companion paper. The PDFs are often broadly distributed and some present systematic biases, hence naive point estimators or even some standard parametric modelling are not sufficient to reconstruct the parent population without obvious bias. Our method uses a redistribution matrix computed from a large realistic simulation with the same selection as in the actual sample to redistribute the stacked PDF, and then forward-fit a non-parametric model to it in a Bayesian way, so that the biases in the PDFs are properly taken into account. In this way, we are able to get accurate uncertainties on the model parameters. We apply our spectral fitting and population inference methods to the XMM-COSMOS survey as a pilot study. For the 819 AGN detected in the COSMOS field, 663 (81\%) of which having spectroscopic redshifts (spec-z) and the others having high quality photometric redshifts (photo-z), we find prominent bi-modality with widely separated peaks in the distribution of the absorbing hydrogen column density ($N_\mathrm{H}$), and an indication that absorbed AGN have harder photon indices. A clear decreasing trend of the absorbed AGN fraction vs the intrinsic 2–10\,keV luminosity is presented, but there is no clear evolution trend of the absorbed fraction with redshift. Our method is designed to be readily applicable to large AGN samples like XXL, and eventually eROSITA.

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L. Ge, S. Paltani, D. Eckert, et. al.
Wed, 1 Dec 21
20/110

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