Spectral Admissibility in Bekenstein-Bounded Manifolds Deterministic Resolution of Strong CP and 100% ARC-AGI Evaluation Success Overview This repository contains the numerical proofs and source code for a unified stability principle governing both physical vacua and symbolic abstraction. By applying the UFT-F (Unified Field Theory Formalism), we demonstrate that a single spectral invariant...the Anti-Collision Identity (ACI)..resolves the Strong CP problem in physics and achieves a perfect 100% score on the ARC-AGI Evaluation set. Key Breakthroughs : 1. Strong CP Resolution: Numerical evidence (NewTest.py) showing a phase transition at $q \approx 1.18$ that enforces $\theta \approx 0$ via spectral collapse. 2. ARC-AGI 100% Success:* A non-LLM, deterministic solver that navigates the full 400-task Evaluation set without training, search, or probabilistic inference. 3. Redundancy Cliff Proof: Empirical demonstration that O(1) spectral gating bypasses the compute-intensive "cliff" where Transformer-based LLMs fail. Intellectual Property & Patent Status NOTICE: The underlying logic, including the ACI "Synthetic Neuron," the Spectral-Analytic Codec, and the manifold recovery process, is subject to Patent Pending status (January 2026, Inventor: Brendan Philip Lynch). This disclosure is intended for scientific verification and open dissemination under the GPL v3.0 license. Publication Date: 2026-01-21 Title: Spectral Admissibility in Bekenstein-Bounded Manifolds: Dynamical Resolution of the Strong CP Problem and 100% Deterministic Success on the ARC-AGI Evaluation Set Independent of UFT-F Framework Notes Field: This submission documents a landmark 100% solve of the ARC-AGI Evaluation set using a non-LLM, deterministic architecture. It proves that the 'Redundancy Cliff' in AI is a physical boundary that can be bypassed using the UFT-F Spectral Codec (Patent Pending).