Astronomy and Astrophysics – Astrophysics
Scientific paper
1998-12-17
Astronomy and Astrophysics
Astrophysics
16 pages including 3 figures, MNRAS, submitted
Scientific paper
10.1046/j.1365-8711.1999.02589.x
The highly nonlinear regime of gravitational clustering is characterized by the presence of scale-invariant form of many-body correlation functions. Useful insights can be obtained by investigating the consequences of a generic scaling {\em ansatz}. Extending earlier studies by Bernardeau & Schaeffer (1992) we calculate the detailed consequences of such scaling. We generalise the two-point cumulant correlators to a hierarchy of multi-point cumulant correlators (MCC). We introduce the concept of reduced cumulant correlators (RCC) and their related generating functions. Using analytical and diagrammatic method we show that every new vertex of the tree representation of higher-order correlations has its own reduced cumulant correlator. In the limit of large separations, MCCs of arbitrary order can be expressed in terms of RCCs of the same and lower order. We relate the generating functions of RCCs with the statistics of {\em collapsed} objects. We develop the hierarchy for the correlation functions of overdense regions. In this vein, we compute the lower-order cumulants and cumulant correlators for overdense regions. Our study shows how they vary as a function of the initial power spectrum of primordial density fluctuations (abridged).
Coles Peter
Melott Adrian L.
Munshi Dipak
No associations
LandOfFree
From Snakes to Stars, the Statistics of Collapsed Objects - I. Lower--order Clustering Properties does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with From Snakes to Stars, the Statistics of Collapsed Objects - I. Lower--order Clustering Properties, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and From Snakes to Stars, the Statistics of Collapsed Objects - I. Lower--order Clustering Properties will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-347395