Toward Accurate Measurement of Property-dependent Galaxy Clustering. II. Tests of the Smoothed Density-corrected V max Method

Abstract

We present a smoothed density-corrected V _max technique for building a random catalog for property-dependent galaxy clustering estimation. This approach is essentially based on the density-corrected V _max method of Cole, with three improvements to the original method. To validate the improved method, we generate two sets of flux-limited samples from two independent mock catalogs with different k + e corrections. By comparing the two-point correlation functions, our results demonstrate that the random catalog created by the smoothed density-corrected V _max approach provides a more accurate and precise measurement for both sets of mock samples than the commonly used V _max and redshift shuffled methods. For the flux-limited samples and color-dependent subsamples, the accuracy of the projected correlation function is well constrained within 1% on the scale of 0.07–30 h ^−1 Mpc. The accuracy of the redshift-space correlation function is less than 2% as well. Currently, it is the only approach that holds promise for achieving the goal of high-accuracy clustering measures for next-generation surveys.

Keywords

• Galaxies
• Galaxy evolution
• Large-scale structure of the universe
• Two-point correlation function