4.7 Article

Orbital parameters of infalling satellite haloes in the hierarchical ΛCDM model

Journal

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Volume 448, Issue 2, Pages 1674-1686

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/mnras/stv053

Keywords

methods: numerical; galaxies: haloes; cosmology: theory; dark matter

Funding

  1. Science and Technology Facilities [ST/L00075X/1]
  2. Durham Doctoral Studentship
  3. CSF an ERC [GA 267291]
  4. BIS National E-infrastructure capital grant [ST/K00042X/1]
  5. STFC [ST/H008519/1]
  6. STFC DiRAC [ST/K003267/1]
  7. Durham University
  8. Science and Technology Facilities Council [ST/M007006/1, ST/K00042X/1, ST/L00075X/1, ST/H008519/1, ST/I00162X/1] Funding Source: researchfish
  9. STFC [ST/L00075X/1, ST/K00042X/1, ST/M007006/1, ST/I00162X/1, ST/H008519/1] Funding Source: UKRI

Ask authors/readers for more resources

We present distributions of orbital parameters of infalling satellites of Lambda cold dark matter (Lambda CDM) haloes in the mass range 10(12)-10(14) M-circle dot, which represent the initial conditions for the subsequent evolution of substructures within the host halo. We use merger trees constructed in a high-resolution cosmological N-body simulation to trace satellite haloes, and identify the time of infall. We find significant trends in the distribution of orbital parameters with both the host halo mass and the ratio of satellite-to-host halo masses. For all host halo masses, satellites whose infall mass is a larger fraction of the host halo mass have more eccentric, radially biased orbits. At fixed satellite-to-host halo mass ratio, high-mass haloes are biased towards accreting satellites on slightly more radial orbits. To characterize the orbital distributions fully requires fitting the correlated bivariate distribution of two chosen orbital parameters (e.g. radial and tangential velocity or energy and angular momentum). We provide simple fits to one choice of the bivariate distributions, which when transformed faithfully, captures the behaviour of any of the projected one-dimensional distributions.

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