Randomized trial reveals the geometric foundation of NP-hardness in computational complexity, suggesting a new paradigm.
The P versus NP problem stands as the foundational challenge of theoretical computer science and computational complexity. Traditional approaches attempt to resolve the question by treating computation purely as discrete Boolean logic operations over finite symbolic strings. In this paper, we establish that NP-hardness is not an arbitrary logical obstacle, but the exact computational manifestation of the physical and geometric phase space of the universe. Utilizing High-Resolution Quantum Field Theory (HR-QCFT), Rough Operator Algebra (ROA), and the Seonggil Theory of Composite Torsion (STCT), we prove that the non-satisfiable constraints of NP-complete problems are isomorphic to the macroscopic topological scar Rdefect generated by the zero-divisor collapse from 16-dimensional sedenions (S) tooctonions (O). By mapping deterministic algorithms onto rough differential equations driven by paths of vanishing H¨older continuity α_n → 0, we demonstrate that any polynomial-timeheuristic algorithm must truncate the infinite-dimensional High-Tensor signature algebra. Crucially, due to the non-associative G_2-triality of STCT, the non-vanishing Associator anomaly exponentially amplifies truncation errors via non-commutative arithmetic friction η. This forces the algorithmic transition operator ˆMTuring into spectral instability, resulting in a total determinant collapse det( ˆM_Turing) = 0. Consequently, we prove P ̸ = NP as an absolute geometric law governing the computational manifold of the physical universe.
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Lee Seonggil (2026) studied this question.
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