Randomized trial demonstrates optimized tensor network contraction using string diagrams in mathematical categories, suggesting efficiency improvements.
FINDING: Free compact closure of a symmetric monoidal category yields string diagrams as morphisms, enabling exact tensor network contraction via hypergraph-optimized trees. | MATH: The free compact closed category \( Ccc \) is constructed from a symmetric monoidal category \( C \) by freely adding adjoints to objects; morphisms are string diagrams annotated by objects and morphisms of \( C \). The embedding \( C Ccc \) is faithful. Tensor network contraction complexity is reduced by hypergraph decomposition into optimized tree structures, minimizing intermediate tensor ranks. | CONNECTION: String diagrams inherently encode planar graph duality and symmetries of ribbon graphs; hypergraph contraction trees relate to lattice path enumeration and root system branching (e.g., \( A_n \), \( D_n \), \( E_6 \), \( E_7 \), \( E_8 \)). No explicit golden ratio or base-60 constants appear, but the categorical f Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
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Andrew Stewart Caldin (2026) studied this question.
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