A search for X-ray absorbed sources in the 3XMM catalogue, using photometric redshifts and Bayesian spectral fits
A. Ruiz, I. Georgantopoulos, A. Corral

TL;DR
This paper introduces XMMFITCAT-Z, a Bayesian spectral fit catalogue for X-ray sources in the 3XMM-DR6 survey, analyzing optical and IR properties of absorbed AGN and comparing selection criteria.
Contribution
It presents a new Bayesian spectral fitting catalogue for X-ray sources with photometric redshifts, enabling detailed analysis of obscured AGN properties and selection biases.
Findings
A significant fraction of X-ray absorbed AGN are missed by mid-IR W1-W2 color selection.
Only one third of X-ray obscured AGN show red optical-IR colors.
Different selection criteria yield substantially different samples of obscured AGN.
Abstract
Since its launch in 1999, the XMM-\textit{Newton} mission has compiled the largest catalogue of serendipitous X-ray sources, with the 3XMM being the third version of this catalogue. This is because of the combination of a large effective area (5000 at 1 keV) and a wide field of view (30 arcmin). The 3XMM-DR6 catalogue contains about 470,000 unique X-ray sources over an area of 982 . A significant fraction of these (100,178 sources) have reliable optical, near/mid-IR counterparts in the SDSS, PANSTARRS, VIDEO, UKIDSS and WISE surveys. In a previous paper we have presented photometric redshifts for these sources using the TPZ machine learning algorithm. About one fourth of these (22,677) have adequate photon statistics so that a reliable X-ray spectrum can be extracted. Obviously, owing to both the X-ray counts selection and the optical counterpart constraint, the…
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