Characterizing Cosmic Voids in Large Scale Simulations

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Scientific paper

The scale of cosmic voids was first realized in the early 1980's with the advent of large galaxy redshift surveys. The voids and the galaxies they host can provide insight into the evolution of galaxies individually and the Universe as a whole. Analyzing these voids and their contents is, however, complicated by the difficulty of defining exactly what a void is. This was partially remedied by a recent comparison of thirteen different void finders on a region of the Millennium Simulation.
Here we present a computer vision algorithm that has been modified to identify and extract structures in large-scale simulations (clusters, filaments, voids). Comparing our results in the same region of the Millennium Simulation, we can identify and characterize the same large void region as the other algorithms do. We also catalog and characterize the void density, distribution, and evolution as calculated from the galaxy, dark matter, and baryonic distributions of a separate large scale hydrodynamical simulation

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