Reconstructing AGN X-ray spectral parameter distributions with Bayesian methods II: Population inference
Lingsong Ge, St\'ephane Paltani, Dominique Eckert, Mara Salvato

TL;DR
This paper introduces a Bayesian population inference method to accurately reconstruct the distributions of X-ray spectral parameters in AGN surveys, accounting for biases and broad posteriors, demonstrated on the XMM-COSMOS dataset.
Contribution
The paper presents a novel Bayesian approach using transfer functions and nonparametric modeling to recover unbiased parent distributions of AGN spectral parameters.
Findings
Bi-modal distribution of hydrogen column density (N_H) in AGN
Absorbed AGN have harder photon indices
Decreasing absorbed AGN fraction with luminosity
Abstract
We present a new Bayesian method for reconstructing the parent distributions of X-ray spectral parameters of active galactic nuclei (AGN) in large surveys. The method uses the probability distribution function (PDF) of posteriors obtained by fitting a consistent physical model to each object with a Bayesian method. The PDFs are often broadly distributed and may present systematic biases, such that naive point estimators or even some standard parametric modeling are not sufficient to reconstruct the parent population without obvious bias. Our method uses a transfer function 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 nonparametric 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 accurately reconstruct the parent…
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Taxonomy
TopicsGamma-ray bursts and supernovae · Gaussian Processes and Bayesian Inference · Statistical and numerical algorithms
