AGN in massive galaxies identified via optical broadband variability: lessons from VST-COSMOS for future LSST science

TL;DR

This study uses optical variability in the VST-COSMOS survey to identify AGN in massive galaxies at z<1, providing insights into future LSST AGN science and host galaxy properties.

Contribution

It demonstrates the effectiveness of optical broadband variability for AGN detection and compares host galaxy properties with non-variable controls, informing future LSST studies.

Findings

AGN hosts have similar morphologies and environments as non-variable galaxies.

Optical variability is a viable method for AGN identification in large surveys.

AGN triggering is not primarily driven by galaxy interactions.

Abstract

We study the properties of 56 massive (M$_{\rm{\star}}$ > 10$^{10}$ M$_{\odot}$) galaxies at $z<1$ that host AGN, detected via their broadband optical variability in the VST-COSMOS survey. VST-COSMOS provides a nearly-identical single visit depth ($r$ $\sim$ 24.6 mag) and temporal baseline (eleven years) as the forthcoming Legacy Survey of Space and Time (LSST), albeit in a much smaller 1 deg$^2$ footprint (four orders of magnitude smaller than that of the LSST). We compare the properties (morphologies, the presence of interactions, rest-frame colours and environment) of our AGN to galaxies in a control sample, which are drawn from the non-variable population and matched in redshift and stellar mass to their AGN counterparts. The fraction of AGN with early-type morphology ($\sim$55 per cent) and the fraction that is interacting ($\sim$23 per cent) are similar to what is observed in the controls, suggesting that these AGN are not primarily triggered by interactions. Similarly, the AGN and controls do not show strong differences in their rest-frame $(u-z)$ colours or local environment, suggesting that neither the recent star formation histories nor the surroundings of the AGN are strongly atypical of the general galaxy population. This study provides a glimpse into forthcoming AGN science using the LSST. With vastly improved statistics, LSST will offer unprecedented insights into AGN demographics, host-galaxy evolution and the processes that fuel supermassive black holes, potentially reshaping our understanding of their place in the Universe.