Monthly Notices of the Royal Astronomical Society · 2020 · 40 citations · 139 references
Natural SciencesAstronomyPhysicsAstrophysicsExtragalactic AstronomyStar FormationExtragalactic Infrared AstronomyExtragalactic X-ray SourcesMid-infrared AstronomyRedshift SurveysActive Galactic Nuclei ContributionActive Galactic Nuclei Infrared EmissionActive Galactic Nucleus ContributionExtragalactic SurveysObscured Active Galactic NucleiOptical Emission SpectroscopySpectral Energy Distribution ModelingX-ray Emission Spectroscopy
ABSTRACT The detection of X-ray emission constitutes a reliable and efficient tool for the selection of active galactic nuclei (AGNs), although it may be biased against the most heavily absorbed AGNs. Simple mid-infrared (IR) broad-band selection criteria identify a large number of luminous and absorbed AGNs, yet again host contamination could lead to non-uniform and incomplete samples. Spectral energy distribution (SED) decomposition is able to decouple the emission from the AGN versus that from star-forming regions, revealing weaker AGN components. We aim to identify the obscured AGN population in the VIMOS Public Extragalactic Redshift Survey in the Canada–France–Hawaii Telescope Legacy Survey W1 field through SED modelling. We construct SEDs for 6860 sources and identify 160 AGNs at a high confidence level using a Bayesian approach. Using optical spectroscopy, we confirm the nature of ∼85 per cent of the AGNs. Our AGN sample is highly complete (∼92 per cent) compared to mid-IR colour-selected AGNs, including a significant number of galaxy-dominated systems with lower luminosities. In addition to the lack of X-ray emission (80 per cent), the SED fitting results suggest that the majority of the sources are obscured. We use a number of diagnostic criteria in the optical, IR, and X-ray regimes to verify these results. Interestingly, only 35 per cent of the most luminous mid-IR-selected AGNs have X-ray counterparts suggesting strong absorption. Our work emphasizes the importance of using SED decomposition techniques to select a population of type II AGNs, which may remain undetected by either X-ray or IR colour surveys.
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R: A Language and Environment for Statistical Computing
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