4 papers
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…
4MOST ChANGES: Catalog of high-redshift quasar candidates (4.5 < < 7) selected with SED fitting
T. Mkrtchyan, C. Mazzucchelli, R. J. Assef +12
The identification of high-redshift quasars () is critical for studying the early Universe, supermassive black hole growth, and cosmic reionization. Most known high-redshi…
VAR-PZ: Constraining the Photometric Redshifts of Quasars using Variability
S. Satheesh-Sheeba, R. J. Assef, T. Anguita +33
The Vera C. Rubin Observatory LSST is expected to discover tens of millions of new Active Galactic Nuclei (AGNs). The survey's exceptional cadence and sensitivity will enable UV/op…
Discovery and characterization of 25 new quasars at 4.6 < z < 6.9 from wide-field multi-band surveys
Silvia Belladitta, Eduardo Bañados, Zhang-Liang Xie +18
Luminous quasars at provide key insights into the early Universe. Their rarity necessitates wide-field multi-band surveys to efficiently separate them from the main astrophys…