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This work presents some outcomes of a theoretical investigation of incompressible high-order networks defined by a generalized graph represen tation. We study some of their network topological properties and how these may be related to real world complex networks. We show that these networks have very short diameter, high k-connectivity, degrees of the order of half of the network size within a strong-asymptotically dominated standard deviation, and rigidity with respect to automorphisms. In addition, we demonstrate that incompressible dynamic (or dynamic multilayered) networks have transtemporal (or crosslayer) edges and, thus, a snapshot-like representation of dynamic networks is inaccurate for capturing the presence of such edges that compose underlying structures of some real-world networks.
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Computer Science - Logic in Computer Science, time-varying graphs, Discrete Mathematics (cs.DM), algorithmic complexity, Computer Science - Information Theory, Information Theory (cs.IT), General Topology (math.GN), Computer Science - Social and Information Networks, Logic in Computer Science (cs.LO), algorithmic randomness, FOS: Mathematics, generalized graphs, multiaspect graphs, Computer Science - Discrete Mathematics, Mathematics - General Topology
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Computer Science - Logic in Computer Science, time-varying graphs, Discrete Mathematics (cs.DM), algorithmic complexity, Computer Science - Information Theory, Information Theory (cs.IT), General Topology (math.GN), Computer Science - Social and Information Networks, Logic in Computer Science (cs.LO), algorithmic randomness, FOS: Mathematics, generalized graphs, multiaspect graphs, Computer Science - Discrete Mathematics, Mathematics - General Topology
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