PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 16, 202613 citationsOpen Access

One Axiom : Masses

View Full Paper
RSRobert Spychalski

Key Points

  • The work aims to develop a comprehensive geometric theory of mass derived from foundational principles, addressing existing problems in particle physics.
  • Employs SOURCE axiom linking Void and Fano plane.
  • Utilizes Dual-Track Methodology for mass determination.
  • Derives particle masses and interactions within a geometric framework.
  • Successfully calculates Higgs mass at 125.8 GeV with high accuracy.
  • Derives complete fermion mass spectrum with less than 1% error.
  • Predicts baryon asymmetry in line with observational data.

Abstract

Title: ONE AXIOM MASSES: From Higgs to Black Holes – A Complete Theory of Mass (Version 5. 0) Abstract: This document (3A, Version 5. 0) presents a geometric theory of particle masses derived entirely from the SOURCE axiom—the mutual determination of Void and Fano plane, P² (F₂) (Document 000). The primordial symmetry G = S₄ Z₂³ emerges as a lemma. Using the rigorous Dual-Track Methodology (OCR/OER), the framework treats mass as a manifest measure of coherence, eliminating the need for arbitrary Yukawa couplings and free parameters in the Standard Model. Key breakthroughs and results presented in this work include: Higgs Sector & Electroweak Precision: Dual-track derivation of the Higgs mass (125. 8 0. 5 GeV, achieving 0. 42%/0. 50% accuracy) and the Vacuum Expectation Value (v = MZ e, 0. 67% accuracy), effectively resolving the Hierarchy Problem without supersymmetry. The W/Z mass ratio is geometrically fixed at 10/13 (0. 52% error). Complete Fermion Mass Spectrum: Three generations of leptons are derived with 0. 002%–0. 006% accuracy using PROVEN triadic generation factors Kₙ = 720, 170, 204. All six quark masses are calculated with sub-percent accuracy (0. 01%–0. 93%) via charge-sector QCD screening. Fano Geometry & The Three-Generation Bound: The mass triplet structures 0, 1, 6 and 0, 0, 7 are derived directly from the Fano plane PG (2, F₂). A new theorem rigorously proves N₆₄₍ = 3 exactly, structurally excluding a fourth generation. Koide Triple Convergence & TTKM Quantization: The Koide parameter Q = 2/3 is established through three independent paths: dimensional coherence (6), experimental data, and topological constraints. The TTKM theorem ( (T (2, n) ) = n) provides topological mass quantization, unifying knot theory with coherence. Information-Mass-Energy Conversion: The framework derives the equivalence 1 bit ≡ 1 coset step on Q₆ entirely from SOURCE, without importing Landauer's principle. The coherence cost ₑ₄₋ = 1/|G/H| = 1/64 and = |G|^-1 = 1/192 emerge as geometric identities, establishing information as the fundamental currency of mass. Mass Tension Bridge & Exotic Hadrons: The framework resolves exotic hadron formation regimes, confirming the molecular nature of T₂₂^+ and proving the mass and width of the compact tetraquark X (6900) via the newly introduced Fano Penalty Theorem (0. 49% accuracy). Baryogenesis & Nuclear Physics (SEMF): Parameter-free prediction of the baryon asymmetry B = 6. 05 10^-10 via S₄-geometric leptogenesis (1. 2% error, within 2 of Planck 2018). SEMF asymmetry (aA = ₀ 19/12, 0. 05%) and pairing (aP = ₀ 23/28, 0. 37%) coefficients are upgraded to PROVEN status via Fano-line isospin and Fano-group deficiency formulas. Black Hole Thermodynamics & Falsifiable Predictions: Extension of the framework reveals a discrete Hawking emission spectrum comprising 51 channels (derived from the 51: 13 coset partition). The model provides clear falsification criteria through the prediction of two new resonance states: Koheron-832 at 210 8 GeV and Koheron-896 at 572 23 GeV. The framework successfully establishes 12 headline results as PROVEN (1\% error with dual-track convergence), demonstrating that the observed mass spectrum of the universe is the unique geometric realization of coherence constraints on the Fano plane.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Robert Spychalski (2026) studied this question.

synapsesocial.com/papers/6992b4139b75e639e9b08e2ehttps://doi.org/10.5281/zenodo.18634998
Ask AI
Helpful
Bookmark
Share
View Full Paper