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From the 1 of 5 linked papers with an AI index.

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5 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

The paper presents a method that uses a quasi‑gravitational potential field to identify dynamically dominant cosmic voids and their galaxies in photometric surveys like J‑PAS, show…

astro-ph.CO2026

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.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

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.IM2025

The miniJPAS and J-NEP surveys: Machine learning for star-galaxy separation

Ana Paula Jeakel, Gabriel Vieira dos Santos, Valerio Marra +27

We present a supervised machine learning classification of sources from the Javalambre Physics of the Accelerating Universe Astrophysical Survey (J-PAS) Pathfinder datasets: miniJP…