SSR × RIC: A Structural Framework for Resonance-Based Intelligence
Abstract Recent advances in artificial intelligence and quantum-inspired AI architectures are often framed in terms of scaling laws, data efficiency, or computational power. However, a growing class of failures cannot be adequately explained by these factors alone. This paper argues that many contemporary AI systems implicitly operate within structurally illegitimate state spaces—spaces that are mathematically expressible but physically, institutionally, or operationally non-existent. To address this foundational mismatch, we propose a unified theoretical framework that integrates Superselection Rules (SSR) with a novel architectural principle termed the Resonance Intelligence Core (RIC). SSR, originating from quantum theory, formalize the idea that not all theoretically definable states are mutually operable or coherent; certain structural boundaries prohibit interference across distinct sectors. We extend this concept beyond physics to cognitive, institutional, and artificial intell...