The Effects of Varying Cosmological Parameters on Halo Substructure

Abstract

We investigate how different cosmological parameters, such as those delivered by the WMAP and Planck missions, affect the nature and evolution of dark matter halo substructure. We use a series of flat Λ cold dark matter (ΛCDM) cosmological N -body simulations of structure formation, each with a different power spectrum but the same initial white noise field. Our fiducial simulation is based on parameters from the WMAP 7th year cosmology. We then systematically vary the spectral index, n s , matter density, Ω M , and normalization of the power spectrum, σ 8 , for 7 unique simulations. Across these, we study variations in the subhalo mass function, mass fraction, maximum circular velocity function, spatial distribution, concentration, formation times, accretion times, and peak mass. We eliminate dependence of subhalo properties on host halo mass and average over many hosts to reduce variance. While the "same" subhalos from identical initial overdensity peaks in higher σ 8 , n s , and Ω m simulations accrete earlier and end up less massive and closer to the halo center at z = 0, the process of continuous subhalo accretion and destruction leads to a steady state distribution of these properties across all subhalos in a given host. This steady state mechanism eliminates cosmological dependence on all properties listed above except subhalo concentration and V max , which remain greater for higher σ 8 , n s and Ω m simulations, and subhalo formation time, which remains earlier. We also find that the numerical technique for computing scale radius and the halo finder used can significantly affect the concentration-mass relationship computed for a simulation.

Exploring the liminality: properties of haloes and subhaloes in borderlinef(R) gravity

“…It is well known from early studies that the halo concentration in CDM simulations is given by a power-law function of mass (e.g. Bullock et al 2001;Zhao et al 2003;Neto et al 2007;Duffy et al 2008;Maccio', Dutton & Bosch 2008;Giocoli et al 2010;Dooley et al 2014), and our CDM simulation shows the same result as illustrated by the red curves in Fig. 4 (neglecting the scatter at large halo masses, which is due to the small numbers of haloes there).…”

An Accurate Physical Model for Halo Concentrations

“…Both their fitting functions include a very strong upturn at high redshift and no upturn at z = 0, leading to 20% disagreements with our model (see also Klypin et al 2011;Prada et al 2012;Ludlow et al 2012;Meneghetti & Rasia 2013). Klypin et al (2016) used the Bound Density Maxima halo finder (BDM; Klypin & Holtzman 1997) rather than Rockstar as well as a different algorithm to determine concentrations, which may explain an overall offset in the normalization of the concentrations (e.g., Dooley et al 2014). However, the differences also show a strong dependence on halo mass and redshift, indicating that other systematic effects are at play (as discussed in detail in Section 4.3).…”

Chemical Abundances in the Ultra-faint Dwarf Galaxies Grus I and Triangulum II: Neutron-capture Elements as a Defining Feature of the Faintest Dwarfs*

“…Second, one must assume that z = 0 halo masses are highly correlated with halo masses at the time of star formation. This is true on average in ΛCDM, but it breaks down in specific cases due to scatter in halo growth histories (e.g., Torrey et al 2015) and tidal stripping from different subhalo infall times (e.g., Dooley et al 2014). Together, these two assumptions would imply that neutron-capture element behavior is uncorrelated with halo mass, disfavoring explanation (2).…”