SUDARE-VOICE variability-selection of Active Galaxies in the Chandra Deep Field South and the SERVS/SWIRE region

TL;DR

This study demonstrates that variability-based selection effectively identifies active galactic nuclei (AGN) in the Chandra Deep Field South, with high purity when combined with multi-wavelength diagnostics, confirming its utility in future surveys.

Contribution

It introduces a variability-based AGN selection method using multi-epoch r-band data, validated with multi-wavelength diagnostics, and compares its effectiveness with infrared selection.

Findings

175 AGN candidates identified through variability.

Approximately 66% of candidates are confirmed AGNs with multi-wavelength data.

Purity of the variability-selected sample is about 80% with diagnostics.

Abstract

One of the most peculiar characteristics of Active Galactic Nuclei (AGN) is their variability over all wavelengths. This property has been used in the past to select AGN samples and is foreseen to be one of the detection techniques applied in future multi-epoch surveys, complementing photometric and spectroscopic methods. In this paper, we aim to construct and characterise an AGN sample using a multi-epoch dataset in the r band from the SUDARE-VOICE survey. Our work makes use of the VST monitoring program of an area surrounding the Chandra Deep Field South to select variable sources. We use data spanning a six month period over an area of 2 square degrees, to identify AGN based on their photometric variability. The selected sample includes 175 AGN candidates with magnitude r < 23 mag. We distinguish different classes of variable sources through their lightcurves, as well as X-ray, spectroscopic, SED, optical and IR information overlapping with our survey. We find that 12% of the sample (21/175) is represented by SN. Of the remaining sources, 4% (6/154) are stars, while 66% (102/154) are likely AGNs based on the available diagnostics. We estimate an upper limit to the contamination of the variability selected AGN sample of about 34%, but we point out that restricting the analysis to the sources with available multi-wavelength ancillary information, the purity of our sample is close to 80% (102 AGN out of 128 non-SN sources with multi-wavelength diagnostics). Our work thus confirms the efficiency of the variability selection method in agreement with our previous work on the COSMOS field; in addition we show that the variability approach is roughly consistent with the infrared selection.