Variability-selected Active Galactic Nuclei in the VST-SUDARE/VOICE Survey of the COSMOS Field

TL;DR

This study evaluates optical variability as a method to identify AGNs in the COSMOS field using VST multi-epoch data, achieving an 81% purity in candidate selection and highlighting the potential for future wide-field surveys.

Contribution

It demonstrates the effectiveness and limitations of variability-based AGN detection in a large survey, providing insights into completeness and the nature of identified AGNs.

Findings

81% purity in AGN candidate selection

Type 1 AGNs are predominant (89%) among confirmed AGNs

Variability detection efficiency depends on source magnitude and type

Abstract

Optical variability has proven to be an effective way of detecting AGNs in imaging surveys, lasting from weeks to years. In the present work we test its use as a tool to identify AGNs in the VST multi-epoch survey of the COSMOS field, originally tailored to detect supernova events. We make use of the multi-wavelength data provided by other COSMOS surveys to discuss the reliability of the method and the nature of our AGN candidates. Our selection returns a sample of 83 AGN candidates; based on a number of diagnostics, we conclude that 67 of them are confirmed AGNs (81% purity), 12 are classified as supernovae, while the nature of the remaining 4 is unknown. For the subsample of AGNs with some spectroscopic classification, we find that Type 1 are prevalent (89%) compared to Type 2 AGNs (11%). Overall, our approach is able to retrieve on average 15% of all AGNs in the field identified by means of spectroscopic or X-ray classification, with a strong dependence on the source apparent magnitude. In particular, the completeness for Type 1 AGNs is 25%, while it drops to 6% for Type 2 AGNs. The rest of the X-ray selected AGN population presents on average a larger r.m.s. variability than the bulk of non variable sources, indicating that variability detection for at least some of these objects is prevented only by the photometric accuracy of the data. We show how a longer observing baseline would return a larger sample of AGN candidates. Our results allow us to assess the usefulness of this AGN selection technique in view of future wide-field surveys.