The richness-dependent cluster correlation function: Early Sloan Digital Sky Survey data

Neta A. Bahcall, Feng Dong, Lei Hao, Paul Bode, Jim Annis, James E. Gunn, Donald P. Schneider

Research output: Contribution to journalReview articlepeer-review

62 Scopus citations

Abstract

The cluster correlation function and its richness dependence are determined from 1108 clusters of galaxies - the largest sample of clusters studied so far - found in 379 deg2 of Sloan Digital Sky Survey early data. The results are compared with previous samples of optically and X-ray-selected clusters. The richness-dependent correlation function increases monotonically from an average correlation scale of ∼12 h-1 Mpc for poor clusters to ∼25 h-1 Mpc for the richer, more massive clusters with a mean separation of ∼90 h-1 Mpc. X-ray-selected clusters suggest slightly stronger correlations than optically selected clusters (∼2 σ). The results are compared with large-scale cosmological simulations. The observed richness-dependent cluster correlation function is well represented by the standard flat Λ-dominated cold dark matter (LCDM) model (Ωm ≃ 0.3., h ≃ 0.7) and is inconsistent with the considerably weaker correlations predicted by Ω m = 1 models. An analytic relation for the correlation scale versus cluster mean separation, r0-d, that best describes the observations and the LCDM prediction is r0 ≃ 2.6√d (for d ≃ 20-90 h-1 Mpc). Data from the complete Sloan Digital Sky Survey, when available, will greatly enhance the accuracy of the results and allow a more precise determination of cosmological parameters.

Original languageEnglish (US)
Pages (from-to)814-819
Number of pages6
JournalAstrophysical Journal
Volume599
Issue number2 I
DOIs
StatePublished - Dec 20 2003

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science

Keywords

  • Cosmological parameters
  • Cosmology: observations
  • Cosmology: theory
  • Dark matter
  • Galaxies: clusters: general
  • Large-scale structure of universe

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