Structure finding in cosmological simulations: the state of affairs

Abstract

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.

Physical drivers of galaxies’ cold-gas content: exploring environmental and evolutionary effects with Dark Sage

“…Some difference in these values is expected, due to the nature of group finding versus subhalo finding for the observed galaxies and simulated data, respectively. In principle, subhalo finding for simulations is a more precise means of identifying satellites (although there is certainly some variation amongst codes -see Onions et al 2012;Knebe et al 2013;Behroozi et al 2015). Projection effects make it possible for true centrals to be observationally classified as satellites with a group finder, but the converse is unlikely (see, e.g., Campbell et al 2015).…”

The Vainshtein mechanism in the cosmic web

“…Here we look at the morphology and model dependence of the halo shapes of the matched AHF halos. The halo shapes are quantified by the ratios b/a and c/a, where a is the largest axis of the halo's moment of inertia tensor, b is the second largest, and c the smallest; thus c/a < b/a, and a spherical halo would have a = b = c. The values of the axis ratios are affected both by the particular method of calculation and by the presence of substructure [72], so here we only concern ourselves with the differences between axial ratios of halos in different gravity models or with different morphologies. Figure 14 shows the mean axial ratios for the set of matched AHF halos, separated according to their ORIGAMI morphology, for each gravity model.…”

The mass function of unprocessed dark matter haloes and merger tree branching rates

“…Of course, the problem of how to define a halo remains-as illustrated in Fig. 4 the choice of halo finder can affect the mass function at the level of a few percent (see also Knebe et al 2013).…”