The miniJPAS survey: The galaxy populations in the most massive cluster in miniJPAS, mJPC2470-1771
J.E. Rodr\'iguez Mart\'in, R. M. Gonz\'alez Delgado, G., Mart\'inez-Solaeche, L. A. D\'iaz-Garc\'ia, A. de Amorim, R. Garc\'ia-Benito,, E. P\'erez, R. Cid Fernandes, E. R. Carrasco, M. Maturi, A. Finoguenov, P. A., A. Lopes, A. Cortesi, G. Lucatelli, J. M. Diego

TL;DR
The miniJPAS survey studied the galaxy populations in the massive cluster mJPC2470-1771, revealing insights into star formation, galaxy evolution, and environmental effects using advanced spectral analysis techniques.
Contribution
This work is the first to analyze the stellar populations, star formation activity, and emission line galaxies in this specific cluster using miniJPAS data and neural network identification methods.
Findings
Red galaxy fraction increases with cluster-centric radius.
65.3% of emission line galaxies are likely star-forming, mostly blue.
24% of emission line galaxies host AGNs, indicating diverse galaxy activity.
Abstract
The miniJPAS is a 1 deg survey that uses the Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) filter system (54 narrow-band filters) with the Pathfinder camera. We study mJPC2470-1771, the most massive cluster detected in miniJPAS. We study the stellar population properties of the members, their star formation rates (SFR), star formation histories (SFH), the emission line galaxy (ELG) population, their spatial distribution, and the effect of the environment on them, showing the power of J-PAS to study the role of environment in galaxy evolution. We use a spectral energy distribution (SED) fitting code to derive the stellar population properties of the galaxy members: stellar mass, extinction, metallicity, colours, ages, SFH (a delayed- model), and SFRs. Artificial Neural Networks are used for the identification of the ELG population through the…
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Taxonomy
TopicsAstronomy and Astrophysical Research · Galaxies: Formation, Evolution, Phenomena · Stellar, planetary, and galactic studies
