Review
Jul 2026
VAR-PZnn: A machine-learning framework for AGN photometric redshifts using color and variability-based features
Photometric redshift estimation for active galactic nuclei (AGNs) remains a fundamental challenge for current and upcoming large-scale photometric surveys. Traditional spectral energy distribution (SED) fitting suffers from color-redshift degeneracies, particularly for AGNs whose power-law continua hide the strong spec...
S. Satheesh-Sheeba, P. Sánchez-Sáez, R. Assef et al.
· 0 citations