This framework develops principles linking polynomial-time computation and NP-completeness, suggesting implications for algorithm design.
This paper develops a structural framework for polynomial-time computation based on bounded exposure and effective incompatibility witnesses. Building on earlier results that ruled out non-adaptive algorithms and linked NP-hardness to global irreducible dependencies, it proves that every deterministic polynomial-time computation admits a bounded exposure normal form and introduces the Strong Bounded Exposure with Effective Witnesses principle. This principle asserts that rejection must be accompanied by a finite, local, and extractable certificate. Through systematic attempts to refute this hypothesis across combinatorial, algebraic, spectral, and statistical paradigms, the paper finds no counterexamples. The framework reduces the P versus NP problem to whether NP-complete problems admit globally irreducible dependencies that evade all effective witnesses.
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Michael Arias (2026) studied this question.
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