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The Milky Way system in Λ cold dark matter cosmological simulations.

Guo, Q. and Cooper, A. P. and Frenk, C. and Helly, J. and Hellwing, W. A. (2015) 'The Milky Way system in Λ cold dark matter cosmological simulations.', Monthly notices of the Royal Astronomical Society., 454 (1). pp. 550-559.


We apply a semi-analytic galaxy formation model to two high-resolution cosmological N-body simulations to investigate analogues of the Milky Way system. We select these according to observed properties of the Milky Way rather than by halo mass as in most previous work. For disc-dominated central galaxies with stellar mass (5–7) × 1010 M⊙, the median host halo mass is 1.4 × 1012 M⊙, with 32–68 per cent percentile spread in the range [0.86, 3.1] × 1012 M⊙, consistent with dynamical measurements of the Milky Way halo mass. For any given halo mass, the probability of hosting a Milky Way system is low, with a maximum of ∼20 per cent in haloes of mass ∼1012 M⊙. The model reproduces the V-band luminosity function and radial profile of the bright (MV < −9) Milky Way satellites (r < 280 kpc). Galaxy formation in low-mass haloes is found to be highly stochastic, resulting in an extremely large scatter in the relation between MV (or stellar mass) for satellites and the depth of the subhalo potential well in which they live, as measured by the maximum of the rotation curve, Vmax. Following Sawala et al., we account for baryonic effects on the growth of dark halo potentials by rescaling Vmax. This adjustment alleviates the ‘too big to fail’ problem – we find that, in 35 per cent of Milky Way-like systems, three or fewer of the top 12 satellites (in order of Vmax) have Vmax > 30 km s−1. Our model predicts that around half of the dark matter subhaloes with Vmax > 20 km s−1 host satellites fainter than MV = −9 and so may be missing from existing surveys.

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Publisher statement:© The Authors 2015 Published by Oxford University Press on behalf of The Royal Astronomical Society. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Date accepted:18 August 2015
Date deposited:24 March 2016
Date of first online publication:22 September 2015
Date first made open access:No date available

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