Evidence of the Great Attractor and Great Repeller from Artificial Neural Network Imputation of Sloan Digital Sky Survey
Evidence of the Great Attractor and Great Repeller from Artificial Neural Network Imputation of Sloan Digital Sky Survey作者机构：School of Computing Ulster University Belfast UK Data Analysis CCT Dublin Ireland
出 版 物：《Journal of High Energy Physics, Gravitation and Cosmology》 (高能物理（英文）)
年 卷 期：2024年第10卷第3期
页 面：1178-1194页
学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学]
主 题：Artificial Neural Networks Convolutional Neural Networks SDSS Anisotropies Great Attractor
摘 要：The Sloane Digital Sky Survey (SDSS) has been in the process of creating a 3D digital map of the Universe, since 2000AD. However, it has not been able to map that portion of the sky which is occluded by the dust gas and stars of our own Milkyway Galaxy. This research builds on work from a previous paper that sought to impute this missing galactic information using Inpainting, polar transforms and Linear Regression ANNs. In that paper, the author only attempted to impute the data in the Northern hemisphere using the ANN model, which subsequently confirmed the existence of the Great Attractor and the homogeneity of the Universe. In this paper, the author has imputed the Southern Hemisphere and discovered a region that is mostly devoid of stars. Since this area appears to be the counterpart to the Great Attractor, the author refers to it as the Great Repeller and postulates that it is an area of physical repulsion, inline with the work of GerdPommerenke and others. Finally, the paper investigates large scale structures in the imputed galaxies.
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