activity
20172026
most citedThe miniJPAS survey: star-galaxy classification using machine learning

55 citations · 115 across the 24 of their papers we have counts for

collaborators

25 papers

astro-ph.CO2026

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…

astro-ph.GA2026

J-PAS: unprecedented precision in stellar populations of diffuse tidal features

Sepideh Eskandarlou, Mohammad Akhlaghi, Francisco Arizo-Borillo +38

Galaxies frequently interact with nearby systems, a process that can significantly alter their morphology and star formation activity. However, spectroscopic studies of their faint…

astro-ph.GA2026

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…

astro-ph.IM2026

J-PAS: Semi-Supervised Sim-to-Obs Transfer for Robust Star--Galaxy--Quasar Classification

Daniel López-Cano, L. Raul Abramo, L. Nakazono +28

Modern studies in astrophysics and cosmology increasingly rely on simulations and cross-survey analyses, yet differences in data generation, instrumentation, calibration, and unmod…

astro-ph.GA2025★ 1 cited

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…

astro-ph.GA2025

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…

astro-ph.GA2025★ 1 cited

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…

astro-ph.GA2025★ 1 cited

J-PAS: Discovery of RaJav, a bright spatially extended Ly Nebula at z=2.25

P. T. Rahna, M. Akhlaghi, J. A. Fernández-Ontiveros +29

We report the discovery of a massive and potentially largest Ly Nebula, RaJav, at z=2.25, associated with a quasar pair: the bright SDSS~J162029.07+433451.1 (hereafter J1620+433…

astro-ph.CO2025

J-PAS: forecast on the primordial power spectrum reconstruction

Guillermo Martínez-Somonte, Airam Marcos-Caballero, Enrique Martínez-González +27

We investigate the capability of the J-PAS survey to constrain the primordial power spectrum using a non-parametric Bayesian method. Specifically, we analyze simulated power spectr…

astro-ph.GA2025★ 2 cited

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…

astro-ph.CO2025★ 1 cited

The miniJPAS survey quasar selection V: combined algorithm

Ignasi Pérez-Ràfols, L. Raul Abramo, Ginés Martínez-Solaeche +27

Aims. Quasar catalogues from narrow-band photometric data are used in a variety of applications, including targeting for spectroscopic follow-up, measurements of supermassive black…

astro-ph.CO2025

J-PAS: Forecasting constraints on Neutrino Masses

Gabriel Rodrigues, Antonio J. Cuesta, Jailson Alcaniz +30

The large-scale structure survey J-PAS is taking data since October 2023. In this work, we present a forecast based on the Fisher matrix method to establish its sensitivity to the…

astro-ph.CO2025★ 2 cited

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…

hep-ph2025

Brazilian Report on Dark Matter 2024

I. F. M. Albuquerque, J. Alcaniz, A. Alves +51

One of the key scientific objectives for the next decade is to uncover the nature of dark matter (DM). We should continue prioritizing targets such as weakly-interacting massive pa…

astro-ph.CO2025

J-PAS and PFS surveys in the era of dark energy and neutrino mass measurements

Fuxing Qin, Yuting Wang, Gong-Bo Zhao +28

Fisher-matrix forecasts are presented for the cosmological surveys of the Javalambre Physics of the Accelerating Universe Astrophysical Survey (J-PAS) and the Subaru Prime Focus Sp…

astro-ph.CO2025

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…

astro-ph.GA2024★ 5 cited

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…

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.IM2023★ 2 cited

The miniJPAS survey quasar selection IV: Classification and redshift estimation with SQUEzE

Ignasi Pérez-Ràfols, L. Raul Abramo, Ginés Martínez-Solaeche +24

We present a list of quasar candidates including photometric redshift estimates from the miniJPAS Data Release constructed using SQUEzE. This work is based on machine-learning clas…

astro-ph.IM2022★ 16 cited

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…

astro-ph.GA2022★ 5 cited

The miniJPAS Survey: Detection of double-core Lyα morphology of two high-redshift (z>3) QSOs

P. T. Rahna, Zhen-Ya Zheng, Ana L. Chies-Santos +30

The Ly emission is an important tracer of neutral gas in a circum-galactic medium (CGM) around high-z QSOs. The origin of Lya emission around QSOs is still under debate which ha…

astro-ph.IM2020★ 55 cited

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…