activity
20022023
most citedThe evolution of the star formation activity in galaxies and its dependence on environment

308 citations · 3.6k across the 90 of their papers we have counts for

collaborators

90 papers

astro-ph.CO2023★ 1 cited

The miniJPAS survey: Optical detection of galaxy clusters with PZWav

L. Doubrawa, E. S. Cypriano, A. Finoguenov +21

Galaxy clusters are an essential tool to understand and constrain the cosmological parameters of our Universe. Thanks to its multi-band design, J-PAS offers a unique group and clus…

astro-ph.GA2023★ 5 cited

The miniJPAS survey. Evolution of the luminosity and stellar mass functions of galaxies up to

L. A. Díaz-García, R. M. González Delgado, R. García-Benito +22

We aim at developing a robust methodology for constraining the luminosity and stellar mass functions (LMFs) of galaxies by solely using data from multi-filter surveys and testing t…

astro-ph.GA2023★ 4 cited

The miniJPAS survey: Maximising the photo-z accuracy from multi-survey datasets with probability conflation

A. Hernán-Caballero, M. Akhlaghi, C. López-Sanjuan +35

We present a new method for obtaining photometric redshifts (photo-z) for sources observed by multiple photometric surveys using a combination (conflation) of the redshift probabil…

astro-ph.CO2023★ 16 cited

The miniJPAS survey: clusters and galaxy groups detection with AMICO

M. Maturi, A. Finoguenov, P. A. A. Lopes +31

Samples of galaxy clusters allow us to better understand the physics at play in galaxy formation and to constrain cosmological models once their mass, position (for clustering stud…

astro-ph.GA2023★ 5 cited

The miniJPAS & J-NEP surveys: Identification and characterization of the Ly Emitter population and the Ly Luminosity Function

Alberto Torralba-Torregrosa, Siddhartha Gurung-López, Pablo Arnalte-Mur +27

We present the Lyman- (Lya) Luminosity Function (LF) at , estimated from a sample of 67 Lya-emitter (LAE) candidates in the J-PAS Pathfinder surveys: miniJPAS and J…

astro-ph.GA2023★ 12 cited

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…