Conference of Computational Interdisciplinary Science

The Large-Scale Structure of the Universe is a homogeneous network of galaxies separated in dense complexes, the Superclusters of Galaxies, and almost empty Voids. The superclusters are young structures that did not have time to evolve into dynamically relaxed systems through the age of the Universe. Internally, they are very irregular, with dense cores, filaments and peripheral systems of galaxies. We propose a methodology to map the internal structure of superclusters using pattern recognition techniques. Our approach allows to: i) identify groups and clusters in the LSS distribution of galaxies; ii) correct for the “fingers of God” projection effect, caused by the partial knowledge of the third space coordinate; iii) detect filaments of galaxies. In this paper, we present the algorithms, discuss the optimization of the free parameters and evaluate its application. With this methodology, we have mapped the internal structure of 42 superclusters in the nearby Universe (z < 0.15).