Universal Metric Mismatch (UMM) v6.0: 256-Node Topological Rigidity and the 1.024 Resonance Invariant as a Geometric Alternative to Dark Matter

This repository contains the formal derivation and computational verification of the Universal Metric Mismatch (UMM) theory v6.0. The work provides a definitive non-local geometric resolution to the "missing mass" problem in galactic dynamics. By shifting the focus from hypothetical non-baryonic particles to the discrete architecture of spacetime, the author demonstrates that dark matter is an emergent effect of a 256-node topological resonance on an S3 manifold. Key highlights of this version: The 1.024 Invariant: A fundamental, scale-invariant constant (zeta = 1.024) derived from information-theoretic density, eliminating the need for empirical fine-tuning. Gaia DR3 Validation: A rigorous explanation of the rotation curve decline in the Milky Way's outer disk as a topological phase transition. Large-Scale Audit: Statistical analysis of 30+ galaxies from the SPARC database, achieving an unprecedented fit of chi-squared approx 1.00. [ ! ] DEPRECATED VERSION — LICENSE UPDATED NOTICE: This version is now obsolete and contains technical and licensing errors. The license for this record has been corrected to PolyForm Noncommercial License 1.0.0 to reflect the author's proprietary rights and intended usage. DO NOT USE THIS VERSION. Please refer to the latest release (v6.5.2) for the final implementation of the UMM algorithm and current legal terms: doi.org Notice: Any licensing terms printed inside the PDF files of this version are superseded by the PolyForm Noncommercial License 1.0.0 stipulated in the current metadata.»(Примечание: любые лицензионные условия, напечатанные внутри PDF-файлов этой версии, заменяются лицензией PolyForm, указанной в текущих метаданных) This research aligns cosmological theory with the consistent null results of dark matter detection experiments and offers a unified geometric framework for astrophysics, from the Planck scale to galactic clusters. Author: Efim S. MarkovORCID: 0009-0005-2235-5464