Abstract
Abstract We use a large N-body simulation to study the relation of the structural properties of dark matter halos to their assembly history and environment. The complexity of individual halo assembly histories can be well described by a small number of principal components (PCs), which, compared to formation times, provide a more complete description of halo assembly histories and have a stronger correlation with halo structural properties. Using decision trees built with the random ensemble method, we find that about 60%, 10%, and 20% of the variances in halo concentration, axis ratio, and spin, respectively, can be explained by combining four dominating predictors: the first PC of the assembly history, halo mass, and two environment parameters. Halo concentration is dominated by halo assembly. The local environment is found to be important for the axis ratio and spin but is degenerate with halo assembly. The small percentages of the variance in the axis ratio and spin that are explained by known assembly and environmental factors suggest that the variance is produced by many nuanced factors and should be modeled as such. The relations between halo intrinsic properties and environment are weak compared to their variances, with the anisotropy of the local tidal field having the strongest correlation with halo properties. Our method of dimension reduction and regression can help simplify the characterization of the halo population and clarify the degeneracy among halo properties.
Highlights
In the concordant Λ cold dark matter (ΛCDM) cosmology, dark matter halos, the dense clumps formed through gravitational collapse of the initial density perturbations, are the basic building blocks of the cosmic web
Using decision trees built with the random ensemble method, we find that about 60%, 10%, and 20% of the variances in halo concentration, axis ratio, and spin, respectively, can be explained by combining four dominating predictors: the first principal components (PCs) of the assembly history, halo mass, and two environment parameters
We have tried to combine halo formation times and PCs of the mass assembly history (MAH) as predictors, and we found that the overall performance changes little, indicating that the MAH PCs dominate the information content about halo concentration
Summary
Dark matter halos are diverse in their structure, mass assembly history (MAH), and interaction with the largescale environment. In addition to assembly history, halo bias has been analyzed in its dependencies on other halo properties, such as halo concentration (Wechsler et al 2006; Jing et al 2007), substructure occupation (Wechsler et al 2006; Gao & White 2007), halo spin (Bett et al 2007; Gao & White 2007; Hahn et al 2007; Wang et al 2011), and halo shape (Hahn et al 2007; Faltenbacher & White 2010; Wang et al 2011) These dependencies are collectively referred to as the “secondary bias”, and sometimes as the “assembly bias”, presumably because these intrinsic properties may be related to halo formation. We use both the PCA and the RF regressor to investigate the dependence of halo structural properties on halo assembly history and environment.
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