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 allowed by the analysed simulations. The code has been especially designed for the adaptive mesh refinement cosmological codes, although it can be used as a stand-alone halo finder for N-body codes. It has been optimised for the purpose of building the merger tree of the haloes. In order to verify the viability of this new tool, we have developed a set of bed tests that allows us to estimate the performance of the finder. Finally, we apply the halo finder to a cosmological simulation and compare the resul...
We use a set of large cosmological N-body simulations to study the internal structure of dark matter...
Publisher's Version/PDFWe describe a new algorithm for finding substructures within dark matter halo...
We present a parallel implementation of the friends-of-friends algorithm and an innovative technique...
We present and test a new halo finder based on the spherical overdensity (SO) method. This new adapt...
Context. New-generation cosmological simulations are providing huge amounts of data, whose analysis ...
We present a detailed comparison of fundamental dark matter halo properties retrieved by a substanti...
We describe our new `MLAPM halo finder' (MHF), which is based on the adaptive grid structure of the ...
Modern N-body cosmological simulations contain billions (109) of dark mat-ter particles. These simul...
The ever increasing size and complexity of data coming from simulations of cosmic structure formatio...
We present a detailed comparison of the substructure properties of a single Milky Way sized dark mat...
Context. The stellar halo holds some of the best preserved fossils of Galactic formation history tha...
Cosmological simulations predict dark matter to form bound structures (i.e. main halos), hosting gal...
We describe an algorithm for identifying ellipsoidal haloes in numerical simulations, and quantify h...
We present a new algorithm for identifying dark matter halos, substructure, and tidal features. The ...
© ESO, 2017. Context. The stellar halo holds some of the best preserved fossils of Galactic formatio...
We use a set of large cosmological N-body simulations to study the internal structure of dark matter...
Publisher's Version/PDFWe describe a new algorithm for finding substructures within dark matter halo...
We present a parallel implementation of the friends-of-friends algorithm and an innovative technique...
We present and test a new halo finder based on the spherical overdensity (SO) method. This new adapt...
Context. New-generation cosmological simulations are providing huge amounts of data, whose analysis ...
We present a detailed comparison of fundamental dark matter halo properties retrieved by a substanti...
We describe our new `MLAPM halo finder' (MHF), which is based on the adaptive grid structure of the ...
Modern N-body cosmological simulations contain billions (109) of dark mat-ter particles. These simul...
The ever increasing size and complexity of data coming from simulations of cosmic structure formatio...
We present a detailed comparison of the substructure properties of a single Milky Way sized dark mat...
Context. The stellar halo holds some of the best preserved fossils of Galactic formation history tha...
Cosmological simulations predict dark matter to form bound structures (i.e. main halos), hosting gal...
We describe an algorithm for identifying ellipsoidal haloes in numerical simulations, and quantify h...
We present a new algorithm for identifying dark matter halos, substructure, and tidal features. The ...
© ESO, 2017. Context. The stellar halo holds some of the best preserved fossils of Galactic formatio...
We use a set of large cosmological N-body simulations to study the internal structure of dark matter...
Publisher's Version/PDFWe describe a new algorithm for finding substructures within dark matter halo...
We present a parallel implementation of the friends-of-friends algorithm and an innovative technique...