340 citations · 1k across the 12 of their papers we have counts for
5 papers · 1 filter
From Dark Matter to Galaxies with Convolutional Neural Networks
Jacky H. T. Yip, Xinyue Zhang, Yanfang Wang +7
Cosmological simulations play an important role in the interpretation of astronomical data, in particular in comparing observed data to our theoretical expectations. However, to co…
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…
The Quijote simulations
Francisco Villaescusa-Navarro, ChangHoon Hahn, Elena Massara +26
The Quijote simulations are a set of 44,100 full N-body simulations spanning more than 7,000 cosmological models in the hyperplane.…
HIGAN: Cosmic Neutral Hydrogen with Generative Adversarial Networks
Juan Zamudio-Fernandez, Atakan Okan, Francisco Villaescusa-Navarro +5
One of the most promising ways to observe the Universe is by detecting the 21cm emission from cosmic neutral hydrogen (HI) through radio-telescopes. Those observations can shed lig…
From Dark Matter to Galaxies with Convolutional Networks
Xinyue Zhang, Yanfang Wang, Wei Zhang +5
Cosmological surveys aim at answering fundamental questions about our Universe, including the nature of dark matter or the reason of unexpected accelerated expansion of the Univers…