Catalog of variability selected AGNs in GOODS

This makes variability selection a possible technique for identifying AGNs. Given that variability selection makes no prior assumption about spectral properties, it is a powerful technique for detecting both low-luminosity AGNs in which the host galaxy emission is dominating and AGNs 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 the 11 931 objects checked, we find 155 variable sources at a significance level of 99.9%, corresponding to about 1.3% of all objects.