A new extensive catalog of optically variable AGN in the GOODS Fields and a new statistical approach to variability selection
Carolin Villforth, Anton M. Koekemoer, Norman A. Grogin

TL;DR
This paper introduces a new catalog of optically variable AGN in the GOODS fields and presents a novel statistical method for variability detection that effectively identifies faint AGN without prior spectral assumptions.
Contribution
It develops and tests a new statistical approach for variability selection, enabling detection of faint AGN in sparsely sampled data, and provides an extensive catalog of variable sources in the GOODS fields.
Findings
Identified 139 variability-selected AGN in GOODS fields.
Detected AGN as faint as magnitude 25.5 in z-band.
Redshifts of selected AGN range from 0.046 to 3.7.
Abstract
Variability is a property shared by practically all AGN. This makes variability selection a possible technique for identifying AGN. Given that variability selection makes no prior assumption about spectral properties, it is a powerful technique for detecting both low-luminosity AGN in which the host galaxy emission is dominating and AGN with unusual spectral properties. In this paper, we will discuss and test different statistical methods for the detection of variability in sparsely sampled data that allow full control over the false positive rates. We will apply these methods to the GOODS North and South fields and present a catalog of variable sources in the z band in both GOODS fields. Out of 11931 objects checked, we find 155 variable sources at a significance level of 99.9%, corresponding to about 1.3% of all objects. After rejection of stars and supernovae, 139 variability…
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