The Neighborhood Function and Its Application to Identifying Large-Scale Structure in the Comoving Universe Frame

Details The Neighborhood Function and Its Application to Identifying Large-Scale Structure in the Comoving Universe Frame The Neighborhood Function and Its Application to Identifying Large-Scale Structure in the Comoving Universe Frame

2007-03-11

arxiv.org/abs/astro-ph/0703249v2

Astrophys.J. 669 (2007) 692-713

Astronomy and Astrophysics

Astrophysics

68 pages, 26 figures and 2 tables, accepted for publication in ApJ

Scientific paper

10.1086/521812

In this paper a relative number density parameter, called the neighborhood function, is introduced so that the crowded nature of the neighborhood of individual sources can be described. With this parameter one can determine the probability of forming a cluster by chance. A method is proposed to identify large-scale structure in the cosmological comoving frame. The scale used to sort out clustered sources is determined by the mean local number density, and the sample adopted is required to have regular borders. The method is applied to a sample drawn from the Two Degree Field survey. We find from the analysis that the probability of forming the resulting large-scale structures by chance is very small, and the phenomenon of clustering is dominant in the local universe. Within a 3\sigma confidence level, a coherent cluster with a scale as large as 357h^{-1}Mpc is identified from the sample. There exist some galaxies which are not affected by the gravitation of clusters, and hence are suspected to be at rest in the comoving frame of the universe. Voids are likely volumes within which very crowded sources are not present, and they are likely formed in embryo by fluctuations in the very early epochs of the universe. In addition, we find that large-scale structures are coral-like and are likely made up of smaller structures; sources with large values of the neighborhood function are mainly distributed within the structure of prominent clusters, and they form the framework of the large-scale structure.

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