Analysing Cosmic Large Scale Structure using Surrogate Data

摘要

Methods derived from nonlinear time series analyses are applied to three-dimensional point distributions as they are typical in the analysis of the cosmic large scale structure. Using the technique of constrained randomisation we generate for a given data set surrogate data sets which have the same linear properties (power spectrum) as well as the same density amplitude distribution but different morphological features. It is shown that the original data set can be discriminated from the surrogates by analysing the local scaling properties of the point sets as measured by weighted scaling indices.