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August 29, 20260 citationsOpen Access

The Phantom Metric: Resolving Dark Matter Anomalies in Galactic Kinematics, Strong Lensing, and Galaxy Clusters via Discrete Topological Constraints (Parameter-Free)

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THTomer Haimovich

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Abstract

We present a unified, parameter-free discrete geometric framework eliminating the need for hypothetical Dark Matter halos. By modeling galactic spacetime as a discrete spatial lattice and enforcing an information-theoretic geometric saturation boundary governed by a Topological Scaling Constant (φ ≈ 1. 618), observed anomalies in light bending and stellar velocities emerge deterministically as topological information latency. This framework undergoes a rigorous, three-pronged empirical audit with zero free parameters: Gravitational Lensing: Tested against 100 strong gravitational lenses from the NASA/HST SLACS dataset, the model predicts the information-theoretic bounding box radius (RBB, Einstein Ring Radius) with a consolidated global accuracy of 99. 17% (R² = 0. 9917). Galactic Kinematics: Tested against 100% of the SPARC database spanning 3, 391 spatiotemporal measurement points across all 175 Late-Type Galaxies (LTGs), and locking the universal stellar mass-to-light ratio (Υ* = 0. 46), the model delivers an unfiltered global goodness-of-fit of 91. 5% (R² = 0. 9150) with zero localized curve-fitting. Macroscopic Cluster Lensing: Tested against massive galaxy clusters from the HST CLASH survey. Operating strictly on the observable baryonic mass fraction (~13%) with zero dark matter, the model predicts Einstein Ring radii with an exceptional 97. 1% structural parity (R²₁: 1 = 0. 9710) across all morphologically relaxed clusters. This demonstrates that geometric conservation scales flawlessly to the largest bound structures in the universe, provided the system maintains a unified spherical geometry. These results prove that cosmic rotation flattening and strong lensing anomalies are fundamental geometric conservation properties of the spacetime manifold, rendering invisible dark matter mathematically redundant.

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Tomer Haimovich (2026) studied this question.

synapsesocial.com/papers/6a9299338e5d7d1fc0c110f1https://doi.org/10.5281/zenodo.22122808
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