Related papers: The Accuracy of Subhalo Detection
[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 detailed comparison of the substructure properties of a single Milky Way sized dark matter halo from the Aquarius suite at five different resolutions, as identified by a variety of different (sub-)halo finders for simulations…
A major question in $\Lambda$CDM is what this theory actually predicts for the properties of subhalo populations. Subhalos are difficult to simulate and to find within simulations, and this propagates into uncertainty in theoretical…
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…
Dark matter subhaloes are key for the predictions of simulations of structure formation, but their existence frequently ends prematurely due to two technical issues, namely numerical disruption in N-body simulations and halo finders failing…
With advances in cosmology and computer science, cosmological simulations now resolve structures in increasingly fine detail. As key tracers of hierarchical structure formation, subhalos are among the most important objects within these…
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 use cosmological LCDM numerical simulations to model the evolution of the substructure population in sixteen dark matter haloes with resolutions of up to seven million particles within the virial radius. The combined substructure…
Cosmological simulations are essential for inferring cosmological and galaxy population properties based on forward-modelling, but this typically requires finding the population of (sub)haloes and galaxies that they contain. The properties…
We present a study of the substructure finder dependence of subhalo clustering in the Aquarius Simulation. We run 11 different subhalo finders on the haloes of the Aquarius Simulation and we study their differences in the density profile,…
We use group size haloes identified with a ``friends of friends'' (FOF) algorithm in a concordance $\Lambda \rm{CDM}$ GADGET2 (dark matter only) simulation to investigate the dependence of halo properties on the environment at $z=0$. The…
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…
Subhalos play a crucial role in accurately modeling galaxy formation and galaxy-based cosmological probes within the highly nonlinear, virialized regime. However, numerical convergence of subhalo evolution is difficult to achieve,…
When a dark matter halo falls into a more massive object and becomes a subhalo, it typically loses much of its mass through tidal stripping. The reverse process is also possible in principle. The subhalo may gravitationally capture material…
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,…
Multiresolution analysis is applied to the problem of halo identification in cosmological N-body simulations. The procedure makes use of a discrete wavelet transform known as the algorithme a trous and segmentation analysis. It has the…
Accurate predictions of the abundance and clustering of dark matter haloes play a key role in testing the standard cosmological model. Here, we investigate the accuracy of one of the leading methods of connecting the simulated dark matter…
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…
The evolution of a dark matter halo in a dark matter only simulation is governed purely byNewtonian gravity, making a clean testbed to determine what halo properties drive its fate.Using machine learning, we predict the survival, mass loss,…
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…