AGN Selection and Demographics in GOODS-S/HUDF from X-ray to Radio

TL;DR

This paper provides a comprehensive census of approximately 900 AGNs in the GOODS-S/HUDF region across multiple wavelengths, analyzing their demographics, selection methods, and properties to understand their distribution and characteristics.

Contribution

It introduces a multi-wavelength, Bayesian approach to identify and analyze AGNs, doubling previous counts and assessing selection completeness in the GOODS-S/HUDF field.

Findings

Approximately 900 AGNs identified, with 26% undetected in deep X-ray data.

No single observational band or technique fully captures the AGN population.

Characterized AGN demographics, including obscuration, luminosity, and density.

Abstract

We present a comprehensive census of the AGNs in the GOODS-S/HUDF region from the X-ray to the radio, covering both the obscured and unobscured populations. This work includes a robust analysis of the source optical-to-mid-IR SEDs featuring (semi-)empirical AGN and galaxy dust emission models and Baysian fitting techniques, ultra-deep VLA 3 and 6 GHz observations, and an integrated analysis of various AGN selection techniques, including X-ray properties, UV-to-MIR SED analysis, optical spectral features, mid-IR colors, radio loudness and spectral slope, and AGN variability. In total, we report $\sim$900 AGNs over the $\sim$170 arcmin$^2$ 3D-HST GOODS-S footprint, which has doubled the AGN number identified in the previous X-ray sample with $\sim$26\% of our sample undetected in the deepest Chandra image. With a summary of AGN demographics from different selection methods, we find that no one single band or technique comes close to selecting a complete AGN sample despite the great depth of the data in GOODS-S/HUDF. We estimate the yields of various approaches and explore the reasons for incompleteness. We characterize the statistical properties, such as source number density, obscuration fraction and luminosity function of the AGN sample in this field and discuss their immediate implications. We also provide some qualitative predictions of the AGN sample that might be discovered by the upcoming JWST surveys.