From the 1 of 5 linked papers with an AI index.
5 papers
Optimizing the extraction of information from redshift probability distribution functions
Rodrigo Duarte, Valerio Marra
The paper presents turboPDZ, a machine‑learning framework that extracts optimized point estimates and reliability scores directly from photometric redshift probability distribution…
Dark Degeneracy in DESI DR2: Interacting or Evolving Dark Energy?
Vitor Petri, Valerio Marra, Rodrigo von Marttens
The standard CDM model, despite its success, is challenged by persistent observational tensions in the Hubble constant () and the matter clustering amplitude (), moti…
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…
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…
The miniJPAS survey quasar selection V: combined algorithm
Ignasi Pérez-Rà fols, L. Raul Abramo, Ginés MartÃnez-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…