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Analysis of Patterns in Galaxy Clustering

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Book cover Statistical Challenges in Modern Astronomy

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.

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Author information

Authors and Affiliations

  1. Astronomy Unit, School of Mathematical Sciences, Queen Mary & Westfield College, Mile End Road, London, E1 4NS, UK

    Peter Coles

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  1. Peter Coles
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Editors and Affiliations

  1. Department of Astronomy and Astrophysics, Pennsylvania State University, University Park, PA, 16802, USA

    Eric D. Feigelson

  2. Department of Statistics, Pennsylvania State University, University Park, PA, 16802, USA

    G. Jogesh Babu

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© 1992 Springer-Verlag New York, Inc.

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Coles, P. (1992). Analysis of Patterns in Galaxy Clustering. In: Feigelson, E.D., Babu, G.J. (eds) Statistical Challenges in Modern Astronomy. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-9290-3_5

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  • DOI: https://doi.org/10.1007/978-1-4613-9290-3_5

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4613-9292-7

  • Online ISBN: 978-1-4613-9290-3

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