55 citations · 98 across the 15 of their papers we have counts for
15 papers
J-PAS & FLAMINGO: Cosmic voids and void galaxies in the gravitational landscape of photometric surveys
J. A. Mansour, B. McCarthy, L. J. Liivamägi +34
Photometric surveys offer a powerful way to map the large-scale structure of the Universe, but their redshift errors complicate the identification of cosmic voids, challenging stud…
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…
J-PAS: First Identification, Physical Properties and Ionization Efficiency of Extreme Emission Line Galaxies
A. Giménez-Alcázar, R. Amorín, J. M. Vílchez +32
Extreme emission line galaxies (EELGs) are key tracers of intense star formation and potential analogues of the sources that reionized the early Universe. Their low-redshift counte…
J-PAS: A value-added catalogue of optical line intensities for nebular emission galaxies (JOLINES)
J. A. Fernández-Ontiveros, C. López-Sanjuan, A. Hernán-Caballero +38
We present the value-added catalogue JOLINES (J-PAS optical line intensities for nebular emission galaxies), which provides emission-line fluxes in galaxies at from the spectrophot…
J-PAS: A Neural Network Approach to Single Stellar Population Characterization
H. Domínguez Sánchez, P. Coelho, G. Bruzual +28
J-PAS (Javalambre Physics of the Accelerating Universe Astrophysical Survey) will present a groundbreaking photometric survey covering 8500 deg of the visible sky from Javalamb…
Exploring the spatially-resolved capabilities of the J-PAS survey with Py2DJPAS
J. E. Rodríguez-Martín, L. A. Díaz-García, R. M. González Delgado +27
We present Py2DJPAS, a Python-based tool to automate the analysis of spatially resolved galaxies in the \textbf{miniJPAS} survey, a 1~deg precursor of the J-PAS survey, using t…
Unveiling the small-scale web around galaxies with miniJPAS and DESI
Daniela Galárraga-Espinosa, Guinevere Kauffmann, Silvia Bonoli +23
We present the first statistical observational study detecting filaments in the immediate surroundings of galaxies, i.e. the local web of galaxies. Simulations predict that cold ga…
The J-PAS survey: The effect of photometric redshift errors on cosmic voids
J. A. Mansour, L. J. Liivamägi, A. Tamm +23
We investigated the impact of photometric redshift errors in the ongoing Javalambre Physics of the Accelerating Universe Astrophysical Survey (J-PAS) on void identification and pro…
Multiwavelength exploration of Extreme Emission Line Galaxies detected in miniJPAS survey
Iris Breda, Stergios Amarantidis, José M. Vilchez +24
Extreme Emission Line Galaxies (EELGs) stand as remarkable objects due to their extremely metal poor environment and intense star formation. Considered as local analogues of high-r…
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…
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…
TOPz: Photometric redshifts for J-PAS
J. Laur, E. Tempel, A. Tamm +30
The importance of photometric galaxy redshift estimation is rapidly increasing with the development of specialised powerful observational facilities. We develop a new photometric r…
The miniJPAS survey: star-galaxy classification using machine learning
P. O. Baqui, V. Marra, L. Casarini +31
Future astrophysical surveys such as J-PAS will produce very large datasets, which will require the deployment of accurate and efficient Machine Learning (ML) methods. In this work…
Systems engineering applied to ELT instrumentation: The GMACS case
D. M. Faes, A. Souza, C. Froning +14
An important tool for the development of the next generation of extremely large telescopes (ELTs) is a robust Systems Engineering (SE) methodology. GMACS is a first-generation mult…
Galaxy properties from J-PAS narrow-band photometry
A. Mejía-Narváez, G. Bruzual, G. Magris C. +14
We study the consistency of the physical properties of galaxies retrieved from SED-fitting as a function of spectral resolution and signal-to-noise ratio (SNR). Using a selection o…