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III. Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet, Incubator LifescapeE. Systems Cosmology: Fractal SpaceTimeMatter Weil, Melinda and Ralph Pudritz. Cosmological Evolution of Supergiant Star-Forming Clouds. The Astrophysical Journal. 556/164, 2001. Galaxies form into hierarchical clusters due to a “robust power-law mass spectrum.” Wen, Xiao-Gang. Zoo of Quantum-Topological Phases of Matter. arXiv:1610.03911. The MIT physicist and author has engaged this field for some years (check his publications page) and was interviewed by Natalie Wolchover for her 2018 Quanta report above which displays a “Periodic Table of Phases” that Wen conceived. This paper advances the 2010s turn in condensed matter physics from material and energetic aspects to realize that nature’s quantum realm is equally distinguished by innate geometric formations, which seem to arrange in an orderly way. We quote a full paragraph to convey its content. What are topological phases of matter? First, they are phases of matter at zero temperature. Second, they have a non-zero energy gap for the excitations above the ground state. Third, they are disordered liquids that seem have no feature. But those disordered liquids actually can have rich patterns of many-body entanglement representing new kinds of order. This paper will give a simple introduction and a brief survey of topological phases of matter. We will first discuss topological phases that have topological order (ie with long range entanglement). Then we will cover topological phases that have no topological order. (Abstract) Zhou, Yuan-Wu, et al. Multifractal and Complex Network Analyses of Protein Molecular Dynamics. arXiv:1403.4719. As the Abstract excerpts note, Xiangtan University, Hunan, and Queens University of Technology, Brisbane, researchers find nature’s universal self-similarity to be equally present in this vital class of intricate biomolecules. Based on protein molecular dynamics, we analyze fractal properties of energy, pressure and volume time series using the multifractal detrended fluctuations analysis (MF-DFA); and investigate the topological and multifractal properties of their visibility graph (complex network) representations. The energy terms of proteins we considered are bonded potential, angle potential, dihedral potential, improper potential, kinetic energy, Van der Waals potential, electrostatic potential, total energy and potential energy. Results of MF-DFA show that these time series are multifractal. Results of complex networks analysis based on visibility graph algorithm show that these visibility graphs are exponential. Our numerical results of multifractal analysis of the visibility graphs show that multifractality exists in these networks. (Abstract)
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