Related papers: Machine-learning cosmology from void properties
We investigate the possibility of learning the representations of cosmological multifield dataset from the CAMELS project. We train a very deep variational encoder on images which comprise three channels, namely gas density (Mgas), neutral…
The large-scale structure of the universe can only be observed via luminous tracers of the dark matter. However, the clustering statistics of tracers are biased and depend on various properties, such as their host-halo mass and assembly…
Our goal is to see how density waves of different scale combine to form voids between galaxy systems of various scale. We perform numerical simulations of structure formation in cubes of size 100 and 256 Mpc/h, with resolutions 256^3 and…
Cosmic voids identified in the spatial distribution of galaxies provide complementary information to two-point statistics. In particular, constraints on the neutrino mass sum, $\sum m_\nu$, promise to benefit from the inclusion of void…
Exclusion zones in the cross-correlations between critical points (peak-void, peak-wall, filament-wall, filament-void) of the density field define quasi-standard rulers that can be used to constrain dark matter and dark energy cosmological…
In this work we analyse the properties of cosmic voids in standard and coupled dark energy cosmologies. Using large numerical simulations, we investigate the effects produced by the dark energy coupling on three statistics: the filling…
We perform a statistical study focused on void environments. We examine galaxy density profiles around voids in the SDSS, finding a correlation between void--centric distance to the shell of maximum density and void radius when a maximum in…
We present a comparison of the properties of galaxies in the most underdense regions of the Universe, where the galaxy number density is less than 10% of the mean density, with galaxies from more typical regions. We have compiled a sample…
Despite a history that dates back at least a quarter of a century studies of voids in the large--scale structure of the Universe are bedevilled by a major problem: there exist a large number of quite different void--finding algorithms, a…
We report here the first systematic study of the supercluster-void network in the LCDM concordance cosmology in which voids and superclusters are treated on an equal footing. Superclusters are defined as individual members of an over-dense…
Voids are parts of the cosmic web least affected by non-linearities and baryonic feedback. We thus calculate the sensitivity of voids to the nature of dark matter (DM), using ultra-light axions as a concrete model and the ongoing Dark…
We use the machine learning techniques, for the first time, to study the background evolution of the universe in light of 30 cosmic chronometers. From 7 machine learning algorithms, using the principle of mean squared error minimization on…
We analyze the structure and connectivity of the distinct morphologies that define the Cosmic Web. With the help of our Multiscale Morphology Filter (MMF), we dissect the matter distribution of a cosmological $\Lambda$CDM N-body computer…
We identify cosmic voids from galaxy density fields under the theory of void-cluster correspondence. We extend the previous novel void-identification method developed for the matter density field to the galaxy density field for practical…
We investigate the properties of voids and void galaxies in the \texttt{TNG300} simulation. Using a luminous galaxy catalog and a spherical void finding algorithm, we identify 5,078 voids at redshift $z = 0$. Within the voids, mass does not…
Convolutional Neural Networks (CNN) have recently been demonstrated on synthetic data to improve upon the precision of cosmological inference. In particular they have the potential to yield more precise cosmological constraints from weak…
Starting from the geometrical concept of a 4-dimensional de-Sitter configuration of spheres in Euclidean 3-space and modelling voids in the Universe as spheres, we show that a uniform distribution over this configuration space implies a…
This article reviews recent advances in the application of machine learning to weak-lensing cosmology. Weak gravitational lensing provides a unique and powerful probe of the total matter distribution in the Universe, independent of its…
Current explanation of the overabundance of dark matter subhalos in the Local Group (LG) indicates that there maybe a limit on mass of a halo, which can host a galaxy. This idea can be tested using voids in the distribution of galaxies: at…
A simple inhomogeneous cosmological model with a local void is constrained with the latest Union supernova compilation. To fit the supernova data, a large local void on the scales of 1 Gpc is found, contrary to the small scales of 200 Mpc…