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, spherical‐overdensity and phase‐space‐based algorithms. We further introduce a robust (and publicly available) suite of test scenarios that allow halo finder developers to compare the performance of their codes against those presented here. This set includes mock haloes containing various levels and distributions of substructure at a range of resolutions as well as a cosmological simulation of the large‐scale structure of the universe. All the halo‐finding codes tested could successfully recover the spatial location of our mock haloes. They further returned lists of particles (potentially) belonging to the object that led to coinciding values for the maximum of the circular velocity profile and the radius where it is reached. All the finders based in configuration space struggled to recover substructure that was located close to the centre of the host halo, and the radial dependence of the mass recovered varies from finder to finder. Those finders based in phase space could resolve central substructure although they found difficulties in accurately recovering its properties. Through a resolution study we found that most of the finders could not reliably recover substructure containing fewer than 30–40 particles. However, also here the phase‐space finders excelled by resolving substructure down to 10–20 particles. By comparing the halo finders using a high‐resolution cosmological volume, we found that they agree remarkably well on fundamental properties of astrophysical significance (e.g. mass, position, velocity and peak of the rotation curve). We further suggest to utilize the peak of the rotation curve, vmax, as a proxy for mass, given the arbitrariness in defining a proper halo edge.

Using a series of high-resolution N-body hydrodynamical numerical simulations, we investigate several scenarios for the evolution of the baryon budget in galactic halos. We derive individual halo star formation history (SFH), as well as the global star formation rate in the universe. We develop a simple analytical model that allows us to compute surprisingly accurate predictions, when compared to our simulations, but also to other simulations presented in Springel & Hernquist (2003b, MNRAS, 339, 312). The model depends on two main parameters: the star formation time scale t * and the wind efficiency η w . We also compute, for halos of a given mass, the baryon fraction in each of the following phases: cold disc gas, hot halo gas, and stars. Here again, our analytical model predictions are in good agreement with simulation results, if one correctly takes finite resolution effect into account. We compare predictions of our analytical model to several observational constraints and conclude that a very narrow range of the model parameters is allowed. The important role played by galactic winds is outlined, as well as a possible "superwind" scenario in groups and clusters. The "anti-hierarchical" behavior of observed SFH is reproduced well by our best model with t * = 3 Gyr and η w = 1.5. We obtain in this case a present-day cosmic baryon budget of Ω * 0.004, Ω cold 0.0004, Ω hot 0.01 and Ω back 0.02 (diffuse background).

The ever increasing size and complexity of data coming from simulations of cosmic structure formation demands equally sophisticated tools for their analysis. During the past decade, the art of object finding in these simulations has hence developed into an important discipline itself. A multitude of codes based upon a huge variety of methods and techniques have been spawned yet the question remained as to whether or not they will provide the same (physical) information about the structures of interest. Here we summarize and extent previous work of the "halo finder comparison project": we investigate in detail the (possible) origin of any deviations across finders. To this extent we decipher and discuss differences in halo finding methods, clearly separating them from the disparity in definitions of halo properties. We observe that different codes not only find different numbers of objects leading to a scatter of up to 20 per cent in the halo mass and V max function, but also that the particulars of those objects that are identified by all finders differ. The strength of the variation, however, depends on the property studied, e.g. the scatter in position, bulk velocity, mass, and the peak value of the rotation curve is practically below a few per cent, whereas derived quantities such as spin and shape show larger deviations. Our study indicates that the prime contribution to differences in halo properties across codes stems from the distinct particle collection methods and -to a minor extent -the particular aspects of how the procedure for removing unbound particles is implemented. We close with a discussion of the relevance and implications of the scatter across different codes for other fields such as semi-analytical galaxy formation models, gravitational lensing, and observables in general.