Informational Filtrations, Global Dependencies, and the Structural Boundary of Deterministic Polynomial-Time Computation
Abstract
This paper develops a structural characterization of deterministic polynomial-time computation based on informational filtrations induced by execution. Building on earlier work showing that polynomial-time algorithms cannot eliminate global inconsistency at an exponential informational cost, it defines compatibility complexes and associates to each computation a monotone filtration reflecting progressive refinement of compatible inputs. The Informational/Filtrational Principle is proved, showing that such filtrations admit only locally certified changes and cannot create higher-dimensional global dependencies. Using this framework, the paper formalizes Global Non-Local Irreducible Dependencies and proves that they are incompatible with polynomial-time computation and preserved under standard reductions. As a consequence, the P versus NP problem is reduced to the question of whether NP-complete problems necessarily contain such dependencies.
Fields of Study & Subjects
Complexity and Algorithms in Graphs
Computability
Logic
AI Algorithms
Advanced Graph Theory Research
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 4 February 2026
- Language
- EN
- Document type
- Preprint