Toward accurate measurement of property-dependent galaxy clustering: II. Tests of the smoothed density-corrected $V_{\rm max}$ method

Abstract

We present a smoothed density-corrected V max technique for building a random catalog for propertydependent galaxy clustering estimation. This approach is essentially based on the density-corrected V max method of Cole (2011), 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 method and redshift shuffled method. For flux-limited samples and color-dependent subsamples, the accuracy for the projected correlation function is well constrained within 1% on the scale 0.07h −1 Mpc to 30h −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 high-accuracy goal of clustering measures for nextgeneration surveys.