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The Solver's Paradox in Formal Problem Spaces

Published: November 18, 2025 | arXiv ID: 2511.14665v1

By: Milan Rosko

Potential Business Impact:

Proves math problems are harder than computers can solve.

Business Areas:
Quantum Computing Science and Engineering

This paper investigates how global decision problems over arithmetically represented domains acquire reflective structure through class-quantification. Arithmetization forces diagonal fixed points whose verification requires reflection beyond finitary means, producing Feferman-style obstructions independent of computational technique. We use this mechanism to analyze uniform complexity statements, including $\mathsf{P}$ vs. $\mathsf{NP}$, showing that their difficulty stems from structural impredicativity rather than methodological limitations. The focus is not on deriving separations but on clarifying the logical status of such arithmetized assertions.

Page Count
19 pages

Category
Computer Science:
Computational Complexity