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Aims. Contemporary large-scale surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) and Euclid present an unprecedented discovery potential for studying active galactic nuclei (AGNs) at the population level in the big data era. However, one major challenge is the accurate identification and classification of AGNs from optical and near-infrared photometry or variability data alone. To optimize active galactic nucleus (AGN) selection, classification, and systematics as well as to test different data analysis tools, we present AGILE (AGNs In the LSST Era), an LSST end-to-end simulation software. Developed as part of the INAF LSST in-kind contribution, AGILE is capable of simulating the anticipated AGN population in LSST and Euclid. Methods. We based AGILE on existing simulations of galaxies and stars, while we developed an AGN recipe based on empirical relations. AGILE populates complete galaxy samples with AGNs according to the observed AGN accretion rate distribution, and each AGN is assigned an optical/UV spectral energy distribution. Optical AGN variability is added using a damped random walk model connected to the AGN physical parameters. Finally, AGILE creates both LSST-like images and related data products. Results. Using AGILE, we built a 24 deg 2 complete mock truth catalog of AGNs, galaxies, and stars with 0.2 8.5 (AGNs and galaxies), and r < 27.5 mag (stars). We also performed a pilot simulation (AGILE DR1) consisting of 1 deg 2 of LSST operations in the COSMOS field observed up to three years in accordance with the survey strategy. We used AGILE DR1 to quantify the accuracy of the LSST Science Pipelines in recovering the true fluxes of AGNs, galaxies, and stars. We quantified the LSST completeness and purity in recovering Type 1 AGNs using typical color-color and variability selections. We share the AGILE DR1 dataset, as it represents an ideal test bench for further scientific exploitation and forecasts in the context of LSST AGNs.
Viitanen et al. (Wed,) studied this question.