A global descriptor of spatial pattern interaction in the galaxy distribution

Abstract

We present the function J as a morphological descriptor for point patterns formed by the distribution of galaxies in the Universe. This function was recently introduced in the field of spatial statistics, and is based on the nearest neighbor distribution and the void probability function. The J descriptor allows to distinguish clustered (i.e. correlated) from ``regular'' (i.e. anti-correlated) point distributions. We outline the theoretical foundations of the method, perform tests with a Matern cluster process as an idealised model of galaxy clustering, and apply the descriptor to galaxies and loose groups in the Perseus-Pisces Survey. A comparison with mock-samples extracted from a mixed dark matter simulation shows that the J descriptor can be profitably used to constrain (in this case reject) viable models of cosmic structure formation.

Significantly enhanced version, 14 pages, LaTeX using epsf, aaspp4, 7 eps-figures, accepted for publication in the Astrophysical Journal

References in corpus (2)

• Beyond genus statistics: a unifying approach to the morphology of cosmic structure
• Loose Groups of Galaxies in the Perseus-Pisces Survey

Cited by in corpus (15)

• Nearest Neighbor distributions: new statistical measures for cosmological clustering
• Luminosity- and morphology-dependent clustering of galaxies
• Topology and Geometry of Gaussian random fields I: on Betti Numbers, Euler characteristic and Minkowski functionals
• Comparing estimators of the galaxy correlation function
• Direct Minkowski Functional analysis of large redshift surveys: a new high--speed code tested on the luminous red galaxy Sloan Digital Sky Survey-DR7 catalogue
• Constructing, characterizing, and simulating Gaussian and higher-order point distributions
• Analysis of the Spatial Distribution of Galaxies by Multiscale Methods
• Estimating the J function without edge correction
• Annealed invariance principle for random walks on random graphs generated by point processes in ${\mathbb{R}}^d$
• Detection of nonrandom patterns in cosmological gravitational clustering
• Morpho-statistical characterisation of the spatial galaxy distribution through Gibbs point processes
• Nearest neighbour analysis as a new probe for fuzzy dark matter
• Recurrence or transience of random walks on random graphs generated by point processes in ${\mathbb{R}}^d$
• Nearest neighbor vector analysis of sdss dr5 galaxy distribution
• Structure of cosmic web in non-linear regime: the nearest neighbour and spherical contact distributions