119 citations · 172 across the 9 of their papers we have counts for
6 papers · 1 filter
The miniJPAS survey: Dissecting galaxy properties across environments with spatially resolved photometry
J. E. Rodríguez-Martín, R. M. González Delgado, L. A. Díaz-García +27
The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) is an ongoing survey mapping thousands of square degrees in the Northern Hemisphere using 56 narrow…
Spatially resolved stellar populations and emission lines properties in nearby galaxies with J-PLUS -- I. Method and first results for the M101 group
J. Thainá-Batista, R. Cid Fernandes, R. M. González Delgado +20
Spatially resolved maps of stellar populations and nebular emission are key tools for understanding the physical properties and evolutionary stages of galaxies. We aim to character…
Euclid Quick Data Release (Q1) Exploring galaxy properties with a multi-modal foundation model
Euclid Collaboration, M. Siudek, M. Huertas-Company +321
Modern astronomical surveys, such as the Euclid mission, produce high-dimensional, multi-modal data sets that include imaging and spectroscopic information for millions of galaxies…
The miniJPAS Survey: The radial distribution of star formation rates in faint X-ray active galactic nuclei
Nischal Acharya, Silvia Bonoli, Mara Salvato +35
We study the impact of black hole nuclear activity on both the global and radial star formation rate (SFR) profiles in X-ray-selected active galactic nuclei (AGN) in the field of m…
The miniJPAS survey quasar selection II: Machine learning classification with photometric measurements and uncertainties
Natália V. N. Rodrigues, L. Raul Abramo, Carolina Queiroz +23
Astrophysical surveys rely heavily on the classification of sources as stars, galaxies or quasars from multi-band photometry. Surveys in narrow-band filters allow for greater discr…
The miniJPAS survey quasar selection I: Mock catalogues for classification
Carolina Queiroz, L. Raul Abramo, Natália V. N. Rodrigues +27
In this series of papers, we employ several machine learning (ML) methods to classify the point-like sources from the miniJPAS catalogue, and identify quasar candidates. Since no r…