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Bayesian Inference of Primordial Magnetic Field Parameters from CMB with Spherical Graph Neural Networks
Juan Alejandro Pinto Castro, Héctor J. Hortúa, Jorge Enrique García-Farieta +1
Deep learning has emerged as a transformative methodology in modern cosmology, providing powerful tools to extract meaningful physical information from complex astronomical dataset…
Parameter sensitivity of cosmic pairwise velocities in the non-linear regime of structure formation
Jorge Enrique García-Farieta, Héctor J. Hortúa
The peculiar velocities of dark matter tracers drive the growth of cosmic structures, providing a sensitive test of cosmological models and strengthening constraints on the nature…
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…
Individual halo bias in models of gravity
Jorge Enrique García-Farieta, Antonio D. Montero-Dorta, Andrés Balaguera-Antolínez
Halo bias links the statistical properties of the spatial distribution of dark matter halos to those of the underlying dark matter field, providing insights into clustering propert…