Quantifying the pattern of galaxy clustering

Details Quantifying the pattern of galaxy clustering Quantifying the pattern of galaxy clustering

Feb 1993

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1993pasj...45....7u&link_type=abstract

PASJ: Publications of the Astronomical Society of Japan (ISSN 0004-6264), vol. 45, no. 1, p. 7-23.

Statistics

Computation

4

Cosmology, Galactic Clusters, Many Body Problem, Astronomical Models, Computational Astrophysics, Red Shift, Statistical Correlation, Universe

Scientific paper

The various statistical measures used to quantify the distribution of galaxies are explored using particle data from large N-body simulations. In particular, the counts-in-cells analysis and multifractal approach are examined in detail, and compared with the conventional correlation statistics. Although all of them have been successful to some extent in quantitatively describing the pattern of galaxy clustering, none seems to be particularly superior to the two-point correlation function in distinguishing the underlying structure. Due to the discrete nature of galaxy distribution, multi-fractal measures are defined only in a somewhat ambiguous manner, and previous claims concerning the usefulness of multi-fractal measures should be interpreted with caution. A measure similar to the percolation test provides a useful guide for quantifying the pattern, at least in a complementary manner to the correlation function. We found, however, that it also sensitively depends on the sampling method of galaxies from the entire universe (the selection function, the shape of the sample, etc.). In this sense, the correlation function is less sensitive to such observational complexities. In contrast to earlier claims by different authors, therefore, the above-mentioned measures are not very powerful in unambiguously characterizing galaxy clustering as is the two-point correlation function.

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