29 citations · 92 across the 6 of their papers we have counts for
4 papers · 1 filter
On the degeneracy between tension and its Gaussian process forecasting
Mauricio Reyes, Celia Escamilla-Rivera
In this paper we reconstruct the growth and evolution of the cosmic structure of the Universe using Markov Chain Monte Carlo algorithms for Gaussian processes [1]. We estimate the…
NECOLA: Towards a Universal Field-level Cosmological Emulator
Neerav Kaushal, Francisco Villaescusa-Navarro, Elena Giusarma +3
We train convolutional neural networks to correct the output of fast and approximate N-body simulations at the field level. Our model, Neural Enhanced COLA --NECOLA--, takes as inp…
Improving data-driven model-independent reconstructions and updated constraints on dark energy models from Horndeski cosmology
Mauricio Reyes, Celia Escamilla-Rivera
In light of the statistical performance of cosmological observations, in this work we present an improvement on the Gaussian reconstruction of the Hubble parameter data from…
Learning neutrino effects in Cosmology with Convolutional Neural Networks
Elena Giusarma, Mauricio Reyes Hurtado, Francisco Villaescusa-Navarro +3
Measuring the sum of the three active neutrino masses, , is one of the most important challenges in modern cosmology. Massive neutrinos imprint characteristic signatures on se…