Deterministic Resolution of Malignant Neoplasms via Resonance Scanning and Entropy Collapse: A Non-Constructive Proof of Polynomial-Time Eradication

Current oncological paradigms rely predominantly on probabilistic interventions, including recently publicized personalized mRNA vaccines, which seek to reduce the risk of recurrence through stochastic immune training. While these represent the zenith of heuristic medicine, they fail to address the structural complexity of the tumor as a mathematical object. This paper presents a non-constructive proof that the eradication of malignant neoplasms is a polynomial-time problem. By modeling the tumor as a constrained resonance graph and applying the Robinson–Ely (R-E) Principle, we demonstrate that the state of malignancy is a high-entropy configuration that can be deterministically collapsed into a benign state via the identification of a maximum resonance node. We prove that the complexity of this resolution is O(nᵏ), effectively shifting cancer eradication from a probabilistic hope to a deterministic certainty.