Related papers: Machine-learning cosmology from void properties
Eulerian cosmological codes are especially suited to properly describe the low density regions. This property makes this class of codes excellent tools to study the formation and evolution of cosmic voids. Following such ideas, we present…
Cosmic voids are effective cosmological probes to discriminate among competing world models. Their identification is generally based on density or geometry criteria that, because of their very nature, are prone to shot noise. We propose two…
Euclid is poised to survey galaxies across a cosmological volume of unprecedented size, providing observations of more than a billion objects distributed over a third of the full sky. Approximately 20 million of these galaxies will have…
Galaxy clusters and cosmic voids, the most extreme objects of our Universe in terms of mass and size, trace two opposite sides of the large-scale matter density field. By studying their abundance as a function of their mass and radius,…
We develop a method to identify cosmic voids from the matter density field by adopting a physically-motivated concept that voids are the counterpart of massive clusters. To prove the concept we use a pair of $\Lambda$CDM simulations, a…
Context: We present the first Cosmological Parameter inferences from eROSITA X-ray observations of galaxy clusters using a Machine Learning algorithm. Methods: We train a Random Forest using mock catalogs of clusters from Magneticum…
We present the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) Multifield Dataset, CMD, a collection of hundreds of thousands of 2D maps and 3D grids containing many different properties of cosmic gas, dark matter, and…
Astrophysical processes such as feedback from supernovae and active galactic nuclei modify the properties and spatial distribution of dark matter, gas, and galaxies in a poorly understood way. This uncertainty is one of the main theoretical…
Cosmic voids refer to the large empty regions in the universe with a very low number density of galaxies. Voids are likely to be severely disturbed by the tidal effect from the surrounding dark matter. We derive a completely analytic model…
Cosmic voids have been shown to be an effective probe of cosmology, complementary to galaxy clusters. In this work, we present a simple theoretical framework for predicting of the size of the largest voids expected within a given redshift…
Cosmic voids as typical under-density regions in the large scale Universe are known for their hyperbolic properties as an ability to deviate the photon beams. The under-density then is acting as the negative curvature in the hyperbolic…
In this work, we present a study of the void lensing signal or the excess surface mass density (ESMD) around cosmic voids. First, we propose a new void-finder algorithm that is designed to capture the ESMD around voids. We compare our…
This paper presents a systematic literature review focusing on the application of machine learning techniques for deriving observational constraints in cosmology. The goal is to evaluate and synthesize existing research to identify…
A spherical Lagrangian hydrodynamical code has been written to study the formation of cosmological structures in the early Universe. In this code we take into account the presence of collisionless non-baryonic cold dark matter (CDM), the…
Voids form a prominent aspect of the Megaparsec distribution of galaxies and matter. Not only do they represent a key constituent of the Cosmic Web, they also are one of the cleanest probes and measures of global cosmological parameters.…
We present the most distant detection of cosmic voids ($z \sim 2.3$) and the first detection of three-dimensional voids in the Lyman-$\alpha$ forest. We used a 3D tomographic map of the absorption with effective comoving spatial resolution…
We present DeepVoid, an application of deep learning trained on a physical definition of cosmic voids to detect voids in density fields and galaxy distributions. By semantically segmenting the IllustrisTNG simulation volume using the tidal…
Cosmic voids are underdense regions filling up most of the volume in the Universe. They are expected to emerge in regions comprising negative initial density fluctuations, and subsequently expand as the matter around them collapses and…
The formation of large voids in the Cosmic Web from the initial adiabatic cosmological perturbations of space-time metric, density and velocity of matter is investigated in cosmological model with the dynamical dark energy accelerating…
The suggestion that we occupy a privileged position near the centre of a large, nonlinear, and nearly spherical void has recently attracted much attention as an alternative to dark energy. Putting aside the philosophical problems with this…