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Astrophysics, Cosmology and Extragalactic Astrophysics, astro-ph.CO
Abstract:
As deeper galaxy catalogues are soon to come, it becomes even more important
to measure large-scale fluctuations in the catalogues with robust statistics
that cover all moments of the galaxy distribution. In this paper we reinforce a
direct analysis of galaxy data by employing the Germ-Grain method to calculate
the family of Minkowski Functionals. We introduce a new code, suitable for the
analysis of large data sets without smoothing and without the construction of
excursion sets. We provide new tools to measure correlation properties, putting
emphasis on explicitly isolating non-Gaussian correlations with the help of
integral--geometric relations. As a first application we present the analysis
of large-scale fluctuations in the LRG sample of SDSS DR7 data. We find
significant (more than 2-sigma) deviations from the simulated mock catalogues
on samples as large as $500h^{-1}$Mpc and $700h^{-1}$Mpc, respectively, and we
investigate possible sources of these deviations.
