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Clustering of galaxy clusters in cold dark matter...
Journal article

Clustering of galaxy clusters in cold dark matter universes

Abstract

We use very large cosmological N-body simulations to obtain accurate predictions for the two-point correlations and power spectra of mass-limited samples of galaxy clusters. We consider two currently popular cold dark matter (CDM) cosmogonies, a critical density model (τCDM) and a flat low density model with a cosmological constant (ΛCDM). Our simulations each use 109 particles to follow the mass distribution within cubes of side 2 h−1 Gpc (τCDM) and 3 h−1 Gpc (ΛCDM) with a force resolution better than 10−4 of the cube side. We investigate how the predicted cluster correlations increase for samples of increasing mass and decreasing abundance. Very similar behaviour is found in the two cases. The correlation length increases from for samples with mean separation to for samples with The lower value here corresponds to τCDM and the upper to ΛCDM. The power spectra of these cluster samples are accurately parallel to those of the mass over more than a decade in scale. Both correlation lengths and power spectrum biases can be predicted to better than 10 per cent using the simple model of Sheth, Mo & Tormen. This prediction requires only the linear mass power spectrum and has no adjustable parameters. We compare our predictions with published results for the automated plate measurement (APM) cluster sample. The observed variation of correlation length with richness agrees well with the models, particularly for ΛCDM. The observed power spectrum (for a cluster sample of mean separation ) lies significantly above the predictions of both models.

Authors

Colberg JM; White SDM; Yoshida N; MacFarland TJ; Jenkins A; Frenk CS; Pearce FR; Evrard AE; Couchman HMP; Efstathiou G

Journal

Monthly Notices of the Royal Astronomical Society, Vol. 319, No. 1, pp. 209–214

Publisher

Oxford University Press (OUP)

Publication Date

November 21, 2000

DOI

10.1046/j.1365-8711.2000.03832.x

ISSN

0035-8711

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