A random-walk model for dark matter halo spins

Jan 24, 2020
10 pages
Published in:
  • Mon.Not.Roy.Astron.Soc. 496 (2020) 3, 3371-3380
  • Published: Aug 11, 2020
e-Print:
DOI:

Citations per year

202020212022202320246123
Abstract: (Oxford University Press)
We extend the random-walk model of Vitvitska et al. for predicting the spins of dark matter haloes from their merger histories. Using updated merger rates, orbital parameter distributions, and N-body constraints, we show that this model can accurately reproduce the distribution of spin parameters measured in N-body simulations when we include a weak correlation between the spins of haloes and the angular momenta of infalling subhaloes. We further show that this model is in approximate agreement with the correlation of the spin magnitude over time as determined from N-body simulations, while it slightly underpredicts the correlation in the direction of the spin vector measured from the same simulations. This model is useful for predicting spins from merger histories derived from non-N-body sources, thereby circumventing the need for very high resolution simulations to permit accurate measurements of spins. It may be particularly relevant to modelling systems that accumulate angular momentum from haloes over time (such as galactic discs) – we show that this model makes small but significant changes in the distribution of galactic disc sizes computed using the galacticus semi-analytic galaxy formation model.
Note:
  • 11 pages, MNRAS accepted, comments welcome
  • dark matter
  • large-scale structure of Universe
  • cosmology: theory