Análise da Função de Correlação de dois Pontos em Distribuições Sintéticas

Abstract

The two-point correlation function is one of the main statistical methods used within cosmology. This function compares sample distributions with a uniform and homogeneous distribution, identifying scales of sample distribution homogeneity. We test different synthetic distributions in order to identify the completeness of information obtained about such distributions. The results showed that the Two-Point Correlation Function is able to identify characteristic scales in which distributions can be considered homogeneous, concentrated or present empty. For Gaussian distributions, the resolution of oscillations representing characteristic scales is limited: if the distances between distributions are less than four times the standard deviation of the distributions, the oscillations are superimposed. We also show that different distributions can generate Correlation Functions of two similar points, confirming results found in the literature.