Properties of dark matter haloes and their correlations: The lesson from principal component analysis

Ramin A. Skibba, Andrea Maccio

Research output: Contribution to journalArticle

Abstract

We study the correlations between the structural parameters of dark matter haloes using principal component analysis. We consider a set of eight parameters, six of which are commonly used to characterize dark matter halo properties: mass, concentration, spin, shape, overdensity and the angle (ΦL) between the major axis and the angular momentum vector. Two additional parameters (xoff and ρrms) are used to describe the degree of 'relaxedness' of the halo. We find that we can account for much of the variance of these properties with halo mass and concentration, on the one hand, and halo relaxedness on the other. None the less, three principal components are usually required to account for most of the variance. We argue that halo mass is not as dominant as expected, which is a challenge for halo occupation models and semi-analytic models that assume that mass determines other halo (and galaxy) properties. In addition, we find that the angle ΦL is not significantly correlated with other halo parameters, which may present a difficulty for models in which galaxy discs are oriented in haloes in a particular way. Finally, at fixed mass, we find that a halo's environment (quantified by the large-scale overdensity) is relatively unimportant.

Original languageEnglish (US)
Pages (from-to)2388-2400
Number of pages13
JournalMonthly Notices of the Royal Astronomical Society
Volume416
Issue number3
DOIs
StatePublished - Sep 1 2011

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principal components analysis
halos
dark matter
principal component analysis
angular momentum
occupation
parameter
disk galaxies
galaxies

Keywords

  • Cosmology: theory
  • Dark matter
  • Galaxies: haloes
  • Gravitation
  • Methods: numerical
  • Methods: statistical

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science

Cite this

Properties of dark matter haloes and their correlations : The lesson from principal component analysis. / Skibba, Ramin A.; Maccio, Andrea.

In: Monthly Notices of the Royal Astronomical Society, Vol. 416, No. 3, 01.09.2011, p. 2388-2400.

Research output: Contribution to journalArticle

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