Theory of Computational Irreversibility in Self-Parameterized Function Chains
Abstract
Comprehensive theory of computational irreversibility in self-parameterized function chains. This paper introduces three distinct mechanisms for irreversibility:- Computational — exponential search complexity Ω(mⁿ)- Probabilistic — recovery probability approaching zero- Absolute — mathematical impossibility through information destruction We present the concept of Tunable Complexity — a framework where inversion difficulty can be precisely controlled through system parameters (permutation complexity π, dependency depth δ, information loss λ). VERSION HISTORY:- v3 (24 January 2026): Reformatted to LaTeX, added reference to experimental validation work- v2 (04 January 2026): Initial public release RELATED WORK:The theoretical concepts introduced here are developed into a rigorous experimental framework with statistical validation in: "Nonna Functions: An Experimental Study of Information Loss and Inversion Complexity" (24 January 2026)DOI: https://doi.org/10.5281/zenodo.18361874 STATUS: Theoretical framework. Does not claim to resolve P vs NP.
Fields of Study & Subjects
Computability
Logic
AI Algorithms
Cellular Automata and Applications
Quantum Computing Algorithms and Architecture
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 4 January 2026
- Language
- EN
- Document type
- Preprint