Multi-Level Feature in the Large Scale Distribution of Galaxies

Abstract

Discoveries of the super-large scale structures in the distribution of galaxies (e.g. the giant void in Bootes, the ‘Great Wall’ of galaxies and so-called ‘great attractor’ etc.) have raised the problem of how to determine the characteristic of distributions on very large scale. Two-point correlation function can not meet this requirement. To calculate two point correlation function from a flux-limited sample we need to weight each pair count by a selection function which depends on the two-point correlation function itself. Besides, it has too large error bars for a volume-limited sample sorted out from flux-limited sample. These restrict the maximum scale of the analysis. Usually, two-point correlation function can only give us the characteristics of a distribution on scales about 10 h -1Mpc.