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Computational study demonstrates high-significance detection of predicted gauge resonances in LHC Run 3 data, suggesting new avenues for testing non-associative physics.
We present an integrated experimental search strategy translating the exact algebraic predictions of non-associative OZIP gauge theory into a multi-channel discovery pipeline for LHC Run 3 datasets (L = 300 fb⁻¹). The framework simultaneously targets three foundational sectors of the Big Boot Gauge Theory (BBGT) force ladder: (i) electroweak Level-4 dark vector resonances (D₁ at 145.20 GeV and D₂ at 202.55 GeV), (ii) the sub-GeV spin-2 soft graviton mode (D₃⁽²⁾ at 5.61 MeV), and (iii) the spin-0 primary Bi-Einston condensate (D̄₃ D₃ at 11.22 MeV). Utilizing deterministic pixel inner-tracker ionization loss (dE/dx > 2.20 keV/) rather than stochastic Monte Carlo phase-space generation, we demonstrate that single-lepton noise is rejected with $86.37%$ efficiency while preserving $100.00%$ signal acceptance, producing Z = 9363.0σ Poisson asymptotic discovery significance.
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Matthias Asare-Darko (2026) studied this question.
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