collaborators

5 papers

cs.DC2026

Bringing Computation to the data: Interoperable serverless function execution for astrophysical data analysis in the SRCNet

Manuel Parra-Royón, Julián Garrido-Sánchez, Susana Sánchez-Expósito +10

Serverless computing is a paradigm in which the underlying infrastructure is fully managed by the provider, enabling applications and services to be executed with elastic resource…

astro-ph.IM2025

Open Science and Artificial Intelligence for supporting the sustainability of the SRC Network: The espSRC case

J. Garrido, S. Sánchez-Expósito, A. Ruiz-Falcó +11

The SKA Observatory (SKAO), a landmark project in radio astronomy, seeks to address fundamental questions in astronomy. To process its immense data output, approximately 700 PB/yea…

astro-ph.GA2025

MeerKAT view of Hickson Compact Groups: II. HI deficiency in the core and surrounding regions

A. Sorgho, L. Verdes-Montenegro, R. Ianjamasimanana +25

Hickson compact groups (HCGs) offer an ideal environment for investigating galaxy transformation as a result of interactions. It has been established that the evolutionary sequence…

astro-ph.GA2025

MeerKAT view of Hickson Compact Groups:I. Data description and release

R. Ianjamasimanana, L. Verdes-Montenegro, A. Sorgho +25

Context: Hickson Compact Groups (HCGs) are dense gravitationally-bound collections of 4-10 galaxies ideal for studying gas and star formation quenching processes. Aims: We aim to u…

astro-ph.GA2025

Classification of HI Galaxy Profiles Using Unsupervised Learning and Convolutional Neural Networks: A Comparative Analysis and Methodological Cases of Studies

Gabriel Jaimes-Illanes, Manuel Parra-Royon, Laura Darriba-Pol +5

Hydrogen, the most abundant element in the universe, is crucial for understanding galaxy formation and evolution. The 21 cm neutral atomic hydrogen - HI spectral line maps the gas…