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.
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