output
20052025
most citedConstraining cosmological parameters from N-body simulations with Variational Bayesian Neural Networks

9 citations

9 papers

quant-ph2025★ 5 cited

The Kossakowski Matrix and Strict Positivity of Markovian Quantum Dynamics

Julián Agredo, Franco Fagnola, Damiano Poletti

We investigate the relationship between strict positivity of the Kossakowski matrix, irreducibility and positivity improvement properties of Markovian Quantum Dynamics. We show tha…

astro-ph.CO2024★ 1 cited

The imprint of cosmic voids from the DESI Legacy Survey DR9 LRGs in the Planck 2018 lensing map through spectroscopically calibrated mocks

S. Sartori, P. Vielzeuf, S. Escoffier +31

The cross-correlation of cosmic voids with the lensing convergence () map of the Cosmic Microwave Background (CMB) fluctuations provides a powerful tool to refine our understand…

physics.ed-ph2024

A comprehensive modelling and experimental approach for damped oscillations in U-tubes via Easy JavaScript Simulations

Fredy A Orjuela, Jorge Enrique García-Farieta, Héctor J Hortúa +1

In recent years, science simulations have become popular among educators due to their educational usefulness, availability, and potential for increasing the students' knowledge on…

astro-ph.CO2023★ 7 cited

Bayesian deep learning for cosmic volumes with modified gravity

Jorge Enrique García-Farieta, Héctor J Hortúa, Francisco-Shu Kitaura

The new generation of galaxy surveys will provide unprecedented data allowing us to test gravity at cosmological scales. A robust cosmological analysis of the large-scale structure…

gr-qc2023

About Jordan and Einstein frames: a study in inflationary magnetogenesis

Joel Velásquez, Héctor J. Hortua, Leonardo Castañeda

There has been considerable interest in the community to understand if the Einstein and Jordan frames are either physically equivalent to each other or if there exists a preference…

astro-ph.IM2023★ 9 cited

Constraining cosmological parameters from N-body simulations with Variational Bayesian Neural Networks

Héctor J. Hortúa, Luz Ángela García, Leonardo Castañeda C

Methods based on Deep Learning have recently been applied on astrophysical parameter recovery thanks to their ability to capture information from complex data. One of these methods…