Seminars and Colloquia at ESO Garching and on the campus

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 AGNs. However, the major challenge is the accurate identification and classification of AGNs from photometry or variability data alone. In order to optimize 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 (Viitanen et al., 2026). AGILE -- developed as part of the INAF LSST in-kind contribution -- is capable of simulating the anticipated AGN population in LSST and Euclid. AGILE is based on existing simulations of galaxies and stars, while we developed an AGN recipe based on empirical relations including optical/UV spectral energy distributions and optical AGN variability. AGILE also is capable of simulating both LSST-like images and related data products. I will present the AGILE software pipeline, as well as the first AGILE data release (DR1). The DR1 consists of a 24 deg2 mock truth catalog, and 1 deg2 of simulated LSST operations in the COSMOS field observed up to three years. I will discuss our results in the context of recovering Type 1 AGNs in LSST from typical color-color and variability selection criteria.