Emergent Mechanics from Self-generating Topological Information Network
Tommy Wood
This article further develops the Space Element Reduction Duplication (SERD) model, a dynamic self generating topological information transmission network model for a background independent discrete space-time. Evidence is provided for the satisfaction of Newtons Laws under a specific extrinsic curvature reducing embedding algorithm applied to the background independent observed states evolution of the model at large scales. From this a specific definition of inertial rest mass is strengthened. Details relating to the specific update operations corresponding to matter flows are presented, leading to a resulting hypothesis regarding the internal structure of particles as local massive stable equilibrium states resulting from the update operations. The SERD model provides an emergent biologically analogous discrete space-time topology with a construct for an observer, transmission of topological information along space filaments and a capacity to define a fundamental unit of observer, and thereby begin to define the idea of observer complexity from first principles. Due to the specificity of the rules at play appropriate methods can be utilised to test physical analogies and to align emergent properties and behaviours of the model with observed physical systems.
Keywords: Discrete space-time, dynamic self generating topological information transmission network, biological morphology, emergence, unconventional computation, Newtonian mechanics, computational universe
Key: PP – Point Particle (hyperedge), SE – Space Element (edge), IG Information Gap (node), TS – Time Step, TI – Topological Information, TISM algorithm – Time Iterated Strain Minimization algorithm, CPPN – Connected Point Particle Network, PSB -Properagating Structural Bifurcations, PIP – Propagating Information Packet
DOI: 10.32908/ijuc.v19.200724