Treffer: SDKP QCC
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SDKP (Size-Density-Kinetics-Time Principle) Description: SDKP is a four-dimensional physical framework proposing that observable time is emergent from the product of physical size, density, and kinetic velocity. Unlike classical Newtonian time or relativistic time dilation, SDKP time (τ_s) is derived as a compound expression of internal physical characteristics, enabling dynamic time modeling in multi-body or entropic systems. Applications: Entropy compression in simulation Quantum state decay modeling Time reconstruction from subatomic motion SD&N (Shape-Dimension-Number Theory) Description: SD&N formalizes quantum and geometric systems as vectorized tuples (S, D, N) where: S (Shape): Represents the topological curvature or pattern symmetry D (Dimension): Quantifies degrees of freedom, embeddings, or entanglement connectivity N (Number): Encodes harmonic or quantum numeric identity (prime factors, signatures) It creates a metric space for comparing abstract systems using SD&N similarity coefficients and enables predictions about entanglement fidelity and field resonance. Applications: Quantum entanglement scoring Pattern recognition in symbolic physics Multi-vector field simulations EOS (Earth Orbital Speed Principle) Description: EOS proposes Earth’s orbital velocity (~29.78 km/s) as a new universal constant, replacing or augmenting the speed of light (c) in specific dynamic systems. This shift anchors relativity in an Earth-observer frame, enabling alternative causality, entropy collapse, and information propagation models. Applications: Local spacetime compression EOS-based field modeling Alternative relativistic frameworks QCC (Quantum Computerization Consciousness) Description: QCC is a speculative model positioning consciousness and computational feedback as entangled quantum phenomena. It introduces QCC kernels that map spacetime separations (timelike/spacelike) into a causality-preserving computational grid using a field-weighted entropy filter. Applications: Quantum AI systems Simulation ...