THE SCALING ANALYSIS AS A TOOL TO COMPARE N-BODY SIMULATIONS WITH OBSERVATIONS - APPLICATION TO A LOW-BIAS COLD DARK MATTER MODEL

We show that the scaling or multifractal analysis is specially suited to quantify the clustering properties of galaxy distributions, The information provided by this method of volume-limited samples is not masked by the boundary corrections made. Consequently, the formalism could be a useful tool to compare the outputs of N-body simulations and galaxy catalogs. The multifractal statistical analysis has been applied to the output of a highly evolved, low bias (b(t) congruent-to 0.8), OMEGA = 1 cold dark matter simulation with 128(3) particles in a 100 h-1 Mpc cubic volume. The identification of galaxy tracers in this simulation is carried out by means of an algorithm that mimics the formation and merging of galaxies. The same statistical analysis has been performed in several samples of the 14.5 CfA galaxy catalog. From the comparison of both analyses we conclude that there exists a very good agreement in the overall clustering properties of the observational samples and the simulation, as described by the statistical method.