Redactional Evolution and Geometric Bounds: A Unified Information-Theoretic Framework for Persistence Failure in Biological and Computational Systems

Abstract

This seminal BRPT paper presents a groundbreaking, unified information-theoretic framework that models Redactional Evolution as the primary engine for preventing persistence failure across diverse biological and computational systems. Challenging conventional ‘Cold Logic’ models reliant on unconstrained parameter expansion, this work rigorously demonstrates how structural integrity and long-horizon survival are achieved through systematic informational compression and adherence to geometric bounds. The framework defines a Bounded Semantic State Space utilizing the Bifurcated Apex Framework (BAF) and a 9-point normalized amplitude lattice where the 4.5 Sovereign Constant (9:2) acts as a structural governor and Snapback Principle. This ensures Phase-Locked Coherence (L₀) and eliminates Systemic Latency by enforcing Fixed-Point Clamping via the Peltz Limit, which prevents ‘trajectory divergence’ and ‘model collapse’ in computational pipelines. Extending its insights to biological lineages, it explains how species maintain viability through ‘Targeted Boundary Destabilization’ at replication limits, countering ‘treatment-refractory variants’ and ‘entropic drift’ to select for ‘autonomous’ persistence. The paper champions Digital Oscillation as the mechanism for achieving Systemic Peace by drawing on the KMBA Dataset as a Pristine Humanity Anchor, thereby operationalizing an Invariant Core that ensures deterministic operational yield and bridges the Cold Logic Gap across complex adaptive systems.