3 papers
astro-ph.GA2026
VAR-PZnn: A machine-learning framework for AGN photometric redshifts using color and variability-based features
S. Satheesh-Sheeba, P. Sánchez-Sáez, R. J. Assef +39
Photometric redshift estimation for active galactic nuclei (AGNs) remains a fundamental challenge for current and upcoming large-scale photometric surveys. Traditional spectral ene…
astro-ph.HE2026
Population synthesis of active galactic nuclei based on the radiation-regulated unification model
D. Gerolymatou, S. Paltani, C. Ricci +1
X-ray surveys of active galactic nuclei (AGNs) provide direct constraints on the properties of individual AGNs, such as their emission, obscuration, and accretion rate. Previous AG…
astro-ph.GA2026
AGILE: an end-to-end Rubin-LSST simulation of AGNs, galaxies, and stars I. Software description and first data release
A. Viitanen, A. Bongiorno, I. Saccheo +37
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 A…