Related papers: The persistent cosmic web and its filamentary stru…
A dynamical classification of the cosmic web is proposed. The large scale environment is classified into four web types: voids, sheets, filaments and knots. The classification is based on the evaluation of the deformation tensor, i.e. the…
We present a novel parameter-free cosmological void finder (\textsc{dive}, Delaunay TrIangulation Void findEr) based on Delaunay Triangulation (DT), which efficiently computes the empty spheres constrained by a discrete set of tracers. We…
We have carried out a search for filamentary structures in the Taurus molecular cloud using $\rm^{13}CO$ line emission data from the FCRAO survey of $\rm \sim100 \, deg^2$. We have used the topological analysis tool, DisPerSe, and…
We develop an analysis pipeline for characterizing the topology of large scale structure and extracting cosmological constraints based on persistent homology. Persistent homology is a technique from topological data analysis that quantifies…
The discovery of the large-scale structure has transformed our view of galaxy formation and evolution. Filaments of the cosmic web provide key environments that channel the growth of structures. Guided by predictions from cosmological…
The cosmic web is the largest scale manifestation of the anisotropic gravitational collapse of matter. It represents the transitional stage between linear and non-linear structures and contains easily accessible information about the early…
We study the topology of cosmic large-scale structure through the genus statistics, using galaxy catalogues generated from the Millennium Simulation and observational data from the latest Sloan Digital Sky Survey Data Release (SDSS DR7). We…
We construct a catalogue for filaments using a novel approach called SCMS (subspace constrained mean shift; Ozertem & Erdogmus 2011; Chen et al. 2015). SCMS is a gradient-based method that detects filaments through density ridges (smooth…
Large-scale structure of Universe includes galaxy clusters connected by filaments. Voids occupy the rest of cosmic volume. The search of any dependencities in filament structure can give answer to more general questions about origin of…
The density fields constructed by traditional mass assignment methods are susceptible to irritating discreteness, which hinders morphological measurements of cosmic large-scale structure (LSS) through Minkowski functionals (MFs). For…
On large cosmological scales, anisotropic gravitational collapse is manifest in the dark cosmic web. Its statistical properties are little known for alternative dark matter models such as fuzzy dark matter (FDM). In this work, we assess for…
(abridged) We present the Significant Cosmic Holes in Universe (SCHU) method for identifying cosmic voids and loops of filaments in cosmological datasets and assigning their statistical significance using techniques from topological data…
Thread-like structures are pervasive across scales, from polymeric proteins to root systems to galaxy filaments, and their characteristics can be readily investigated in the network formalism. Yet, network links usually represent only parts…
Filaments are ubiquitous in the universe. Recent observations have revealed that stars and star clusters form preferentially along dense filaments. Understanding the formation and properties of filaments is therefore a crucial step in…
In this paper we explore the use of spatial clustering algorithms as a new computational approach for modeling the cosmic web. We demonstrate that such algorithms are efficient in terms of computing time needed. We explore three distinct…
One of the important unknowns of current cosmology concerns the effects of the large scale distribution of matter on the formation and evolution of dark matter haloes and galaxies. One main difficulty in answering this question lies in the…
We investigate the ability of three reconstruction techniques to analyze and investigate weblike features and geometries in a discrete distribution of objects. The three methods are the linear Delaunay Tessellation Field Estimator (DTFE),…
It is possible to visualize the Cosmic Web as an interconnected network of one-dimensional filaments, two-dimensional sheets and three-dimensional volume-filling structures which we refer to as clusters. We have used the Local Dimension D,…
A diffusion process on complex networks is introduced in order to uncover their large scale topological structures. This is achieved by focusing on the slowest decaying diffusive modes of the network. The proposed procedure is applied to…
We explore the capability of deep learning to classify cosmic structures. In cosmological simulations, cosmic volumes are segmented into voids, sheets, filaments and knots, according to the distribution and kinematics of dark matter (DM),…