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Theoretical study demonstrates algorithmic field regularization across quantum and cosmological scales, suggesting dark matter and dark energy emerge from computational load balancing.
This work operationalizes the core mechanism of the SAA—the Resolution-Bound Localic Accumulator (RBLA)—into a Turing-computable algebraic structure. By restricting physical evolution to polynomial-time complexity (P ≠ NP) within a discrete Pointless Locale, we demonstrate how discrete gauge theory over finite bitmask structures naturally derives the canonical basis of the Spacetime Algebra C(3,1) as optimal computational eigen-structures. We adapt Tensor Network theory using lazy evaluation to model multi-loop quantum entanglement while preserving O(N log N) execution bounds. Furthermore, the framework models Quantum Chromodynamics (QCD) topologically, interpreting Color Confinement as a deterministic Type-Theoretic Halting Fault and Hadronization as algorithmic garbage collection. Translating these principles to a hardware-compatible data-oriented design (leveraging AVX-512 SIMD operations) yields a scalable simulation architecture that natively regularizes ultraviolet (UV) divergences. Macroscopically, the SAA postulates that observed phenomena associated with Dark Energy and Dark Matter may emerge from dynamic algorithmic load balancing within the spatial computer, offering a resolution to the Hubble Tension and providing a strict, falsifiable prediction regarding the absence of peripheral kinematic plateaus in high-redshift ($z > 2.5$) galaxies.
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Huynh Hai Dang Vo (2026) studied this question.