Related papers: Phase-space structures II: Hierarchical Structure …
Context. New-generation cosmological simulations are providing huge amounts of data, whose analysis becomes itself a cutting-edge computational problem. In particular, the identification of gravitationally bound structures, known as halo…
Most of the mass content of dark matter haloes is expected to be in the form of tidal debris. The density of debris is not constant, but rather can grow due to formation of caustics at the apocenters and pericenters of the orbit, or decay…
[abridged] We present a detailed comparison of fundamental dark matter halo properties retrieved by a substantial number of different halo finders. These codes span a wide range of techniques including friends-of-friends (FOF),…
We present a method for computing the 6-dimensional coarse-grained phase-space density $f(x,v)$ in an N-body system, and derive its distribution function $v(f)$. The method is based on Delaunay tessellation, where $v(f)$ is obtained with an…
We describe a new algorithm for finding substructures within dark matter haloes from N-body simulations. The algorithm relies upon the fact that dynamically distinct substructures in a halo will have a {\em local} velocity distribution that…
We present a new algorithm which groups the subhaloes found in cosmological N- body simulations by structure finders such as SUBFIND into dark matter haloes whose formation histories are strictly hierarchical. One advantage of these…
We have developed a new halo finding method, Physically Self-Bound (PSB) group finding algorithm, which can efficiently identify halos located even at crowded regions. This method combines two physical criteria such as the tidal radius of a…
We present a method to numerically estimate the densities of a discretely sampled data based on binary space partitioning tree. We start with a root node containing all the particles and then recursively divide each node into two nodes each…
We present a new and completely general technique for calculating the fine-grained phase-space structure of dark matter throughout the Galactic halo. Our goal is to understand this structure on the scales relevant for direct and indirect…
We present a new algorithm for identifying dark matter halos, substructure, and tidal features. The approach is based on adaptive hierarchical refinement of friends-of-friends groups in six phase-space dimensions and one time dimension,…
We present and test a new halo finder based on the spherical overdensity (SO) method. This new adaptive spherical overdensity halo finder (ASOHF) is able to identify dark matter haloes and their substructures (subhaloes) down to the scales…
We present a deep-learning-based approach for identifying dark matter haloes in cosmological N-body simulations. Our framework consists of a volumetric Convolutional Neural Network to classify individual simulation particles as either halo…
The phase-space structure of primordial dark matter halos is revisited using cosmological simulations with three sine waves and Cold Dark Matter (CDM) initial conditions. The simulations are performed with the tessellation based Vlasov…
We develop a theoretical framework for describing the hierarchical structure of the phase space of cold dark matter haloes, due to gravitationally bound substructures. Because it includes the full hierarchy of the cold dark matter initial…
A method is presented for computing the 6-D phase-space density f(x,v) and its PDF v(f) in an N-body system. It is based on Delaunay tessellation, yielding v(f) with a fixed smoothing window over a wide f range, independent of the sampling…
Dark matter haloes in cosmological filaments and walls have their spin vector aligned (in average) with their host structure. While haloes in walls are aligned with the plane of the wall independently of their mass, haloes in filaments…
The structural and dynamic properties of the dark matter halos, though an important ingredient in understanding large-scale structure formation, require more conservative particle resolution than those required by halo mass alone in a…
We present an algorithm which is designed to allow the efficient identification and preliminary dynamical analysis of thousands of structures and substructures in large N-body simulations. First we utilise a refined density gradient system…
We describe a new method (\textsc{CompaSO}) for identifying groups of particles in cosmological $N$-body simulations. \textsc{CompaSO} builds upon existing spherical overdensity (SO) algorithms by taking into consideration the tidal radius…
Structure identification in cosmological simulations plays an important role in analysing simulation outputs. The definition of these structures directly impacts the inferred properties derived from these simulations. This paper proposes a…