Analysis of Patterns in Galaxy Clustering

  • Peter Coles

Abstract

Systematic attempts to quantify the intrinsic pattern present in galaxy clustering data began with the determination of what has become known as the two-point correlation function of galaxies from their projected positions on the sky. This was later extended to three- and four-point (projected) correlations and, with the advent of large-scale galaxy redshift surveys, low-order correlation functions of galaxies in three-dimensional space. In this paper, I review the current state of play with regard to correlation function analysis, both in terms of computational and sampling problems and with regard to the fundamental limitations of such an approach in giving a complete statistical description of the pattern present. I explain the importance of cosmic “voids” (large-scale underdense regions) for the analysis of clustered patterns and show that the Void Probability Function is a good example of a statistical characteristic containing more information than the hierarchy of correlation functions. The existence of large voids also has important consequences for theories of galaxy formation.

Keywords

Foam Covariance Sponge Percolate 

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Copyright information

© Springer-Verlag New York, Inc. 1992

Authors and Affiliations

  • Peter Coles
    • 1
  1. 1.Astronomy Unit, School of Mathematical SciencesQueen Mary & Westfield CollegeLondonUK

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