Related papers: AVISM: Algorithm for Void Identification in coSMol…
Galaxies and their dark matter halos populate a complicated filamentary network around large, nearly empty regions known as cosmic voids. Cosmic voids are usually identified in spectroscopic galaxy surveys, where 3D information about the…
We present VIDE, the Void IDentification and Examination toolkit, an open-source Python/C++ code for finding cosmic voids in galaxy redshift surveys and N-body simulations, characterizing their properties, and providing a platform for more…
Cosmic voids are the major volume component in the matter distribution of the Universe. They posses great potential for constraining dark energy as well as for testing theories of gravity. Nevertheless, in spite of their growing popularity…
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…
We discuss various applications of VIDE, the Void IDentification and Examination toolkit, an open-source Python/C++ code for finding cosmic voids in galaxy redshift surveys and N-body simulations. Based on a substantially enhanced version…
Voids are the most prominent feature of the LSS of the universe. Still, they have been generally ignored in quantitative analysis of it, essentially due to the lack of an objective tool to identify and quantify the voids. To overcome this,…
Cosmic voids are large underdense regions that, together with galaxy clusters, filaments and walls, build up the large-scale structure of the Universe. The void size function provides a powerful probe to test the cosmological framework.…
Voids are the most prominent feature of the large-scale structure of the universe. Still, they have been generally ignored in quantitative analysis of it, essentially due to the lack of an objective tool to identify the voids and to…
Cosmic voids contain higher-order cosmological information and are of interest for astroparticle physics. Finding genuine matter underdensities in sparse galaxy surveys is, however, an underconstrained problem. Traditional void finding…
We study how well void-finding algorithms identify cosmic void regions and whether we can quantitatively and qualitatively compare the voids they find with dynamical information from the underlying matter distribution. Using the ORIGAMI…
Cosmic voids are large, nearly empty regions that lie between the web of galaxies, filaments and walls, and are recognized for their extensive applications in the field of cosmology and astrophysics. Despite their significance, a universal…
Cosmic voids are the largest and most underdense structures in the Universe. Their properties have been shown to encode precious information about the laws and constituents of the Universe. We show that machine learning techniques can…
We present a public catalogue of voids in the Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 11 LOWZ and CMASS galaxy surveys. This catalogue contains information on the location, sizes, densities, shapes and bounding surfaces…
While cosmic voids are now recognized as a valuable cosmological probe, identifying them in a galaxy catalog is challenging for multiple reasons: observational effects such as holes in the mask or magnitude selection hinder the detection…
The aim of this study is to distinguish genuine cosmic voids, found in a galaxy catalog by the void finder ZOBOV-VIDE, from under-dense regions in a Poisson distribution of objects. For this purpose, we perform two multivariate analyses…
Cosmic voids, the large underdense regions of our Universe, have emerged over the past decade as powerful cosmological laboratories: their simple dynamics, sensitivity to local gravitational effects and cosmic expansion, and ability to span…
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…
Cosmic voids are promising cosmological laboratories for studying the dark energy phenomenon and alternative gravity theories. They are receiving special attention nowadays in view of the new generation of galaxy spectroscopic surveys,…
Understanding galaxy properties may be the key to unlocking some of the most intriguing mysteries of modern cosmology. Recent work relied on machine learning to extract cosmological constraints on $\Omega_\mathrm{m}$ using only one galaxy.…
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…