Isodensity Statistics on Clustering of High - z Objects in Cosmological Redshift - spaces

We discuss the systematic effects arising from the cosmological redshift-space (geometric) distortion on the statistical analysis of isodensity contour using high-redshift catalogs. Especially, we present a simple theoretical model for isodensity statistics in cosmological redshift-space, as a generalization of the work by Matsubara (1996). The statistical quantities considered here are the twoand three-dimensional genus of isodensity contour, the area of surface, the length of contour intersecting with a plane and the number of the crossing points of isodensity contour on a line. We give useful analytic formulae for the isodensity statistics, which take into account the corrections from the geometric distortion, the nonlinear clustering and the nonlinear velocity distortion phenomenologically. We then demonstrate how the geometric distortion and the nonlinear corrections alter shapes of the statistical quantities on the basis of plausible cosmological models. Our results show that the nonlinear correction can be sensitive to a choice of the redshift-space coordinate as increasing the redshift. The low-dimensional quantities such as two-dimensional genus systematically yield anisotropy due to the geometric and velocity distortions and their angle-dependence shows the 10 ∼ 20% difference of amplitude. Sensitivity for typical high-redshift samples are estimated in an analytic manner, and the influence of the light-cone effect for the isodensity statistics is also discussed. A simple estimation suggests that the systematic effects of geometric and redshift-space distortions can become comparable or could be dominant to the statistical error of deep cluster samples and future high-redshift galaxy surveys. These systematic effects might be a useful tool in probing the cosmological model of our universe. Subject headings: cosmology: theory dark matter large-scale structure of universe galaxies : distances and redshifts methods: statistical