SIMULATION OF LARGE-SCALE STRUCTURE OF UNIVERSE BY GAUSSIAN RANDOM FIELDS
Journal Title: Odessa Astronomical Publications - Year 2018, Vol 31, Issue
Abstract
Large-scale structure of Universe includes galaxy clusters connected by filaments. Voids occupy the rest of cosmic volume.The search of any dependencities in filament structure can give answer to more general questions about origin of structures in the Universe. This becomes possible because, according to current picture of Universe, one could simulate the evolution of Universe until its very beginning or vice versa. One of the theories which describe the shape of large-scale structures is adiabatic Zeldovich theory. This theory explain three-dimensional galaxy distribution as a set of thin pancakes which were formed from hot primordial gas under own gravitational pressure in the cosmological period of acоustic oscillations. According to cosmological hydrodynamical theories a number of computer simulations of LSS were performed to describe its properties . In this work we consider alternative variant of simulating the distribution of matter that is very similar to real. We simulated two-dimensional galaxy distribution on the sky using random distributions of clusters and single galaxies. The main assumption was that matter clusterised to initial density fluctuations with uniform distribution. According to Zeldovich theory, low dimensional anisotropies should increase, that corresponds to appearance of filaments in 2D case. Thus we generated a net of filaments between clusters with certain length limits . Real galaxy distribution was simulated by random changing galaxy positions in filaments and clusters. We generated radial distributions of galaxies in clusters taking into account the surrounding and add uniform distribution of isolated galaxies in voids. Our model has been coordinated with SDSS galaxy distribution with using two-point angular correlation function. Parameters of random distributions were found for the case of equality of correlation function slope for the model and for observational data.
Authors and Affiliations
V. V. Voitsekhovskiy, A. V. Tugay
Keywords
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- EP ID EP603598
- DOI 10.18524/1810-4215.2018.31.144752
- Views 88
- Downloads 0
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