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Optical variability has proven to be an effective way of detecting AGNs inimaging surveys, lasting from weeks to years. In the present work we test itsuse as a tool to identify AGNs in the VST multi-epoch survey of the COSMOSfield, originally tailored to detect supernova events. We make use of themulti-wavelength data provided by other COSMOS surveys to discuss thereliability of the method and the nature of our AGN candidates. Our selectionreturns a sample of 83 AGN candidates; based on a number of diagnostics, weconclude that 67 of them are confirmed AGNs (81% purity), 12 are classified assupernovae, while the nature of the remaining 4 is unknown. For the subsampleof AGNs with some spectroscopic classification, we find that Type 1 areprevalent (89%) compared to Type 2 AGNs (11%). Overall, our approach is able toretrieve on average 15% of all AGNs in the field identified by means ofspectroscopic or X-ray classification, with a strong dependence on the sourceapparent 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 AGNpopulation presents on average a larger r.m.s. variability than the bulk of nonvariable sources, indicating that variability detection for at least some ofthese objects is prevented only by the photometric accuracy of the data. Weshow how a longer observing baseline would return a larger sample of AGNcandidates. Our results allow us to assess the usefulness of this AGN selectiontechnique in view of future wide-field surveys.

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