Journal Article

The assembly bias of dark matter haloes to higher orders

R. E. Angulo, C. M. Baugh and C. G. Lacey

in Monthly Notices of the Royal Astronomical Society

Published on behalf of The Royal Astronomical Society

Volume 387, issue 2, pages 921-932
Published in print June 2008 | ISSN: 0035-8711
Published online May 2008 | e-ISSN: 1365-2966 | DOI:
The assembly bias of dark matter haloes to higher orders

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We use an extremely large volume (2.4 h−3Gpc3), high-resolution N-body simulation to measure the higher order clustering of dark matter haloes as a function of mass and internal structure. As a result of the large simulation volume and the use of a novel ‘cross-moment’ counts-in-cells technique which suppresses discreteness noise, we are able to measure the clustering of haloes corresponding to rarer peaks than was possible in previous studies; the rarest haloes for which we measure the variance are 100 times more clustered than the dark matter. We are able to extract, for the first time, halo bias parameters from linear up to fourth order. For all orders measured, we find that the bias parameters are a strong function of mass for haloes more massive than the characteristic mass M*. Currently, no theoretical model is able to reproduce this mass dependence closely. We find that the bias parameters also depend on the internal structure of the halo up to fourth order. For haloes more massive than M*, we find that the more concentrated haloes are more weakly clustered than the less concentrated ones. We see no dependence of clustering on concentration for haloes with masses M < M*; this is contrary to the trend reported in the literature when segregating haloes by their formation time. Our results are insensitive to whether haloes are labelled by the total mass returned by the friends-of-friends group finder or by the mass of the most massive substructure. This implies that our conclusions are not an artefact of the particular choice of group finding algorithm. Our results will provide important input to theoretical models of galaxy clustering.

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

Journal Article.  8266 words.  Illustrated.

Subjects: Astronomy and Astrophysics

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