The Relational Stabilizer: Plastic Stability in Noisy Complex Systems

This project presents the Relational Stabilizer, a simulation-based framework for understanding resilience in complex systems operating under environmental noise. Using networks of coupled Kuramoto oscillators, the study examines how coherence is preserved—and how it fails—when systems are exposed to increasing coordination stress. The results reveal a consistent hierarchy of failure, in which informational richness degrades first, structural coupling fails second, and temporal persistence lingers briefly after fragmentation. Rather than collapsing uniformly, healthy systems shed capacity strategically to protect core coherence. A key finding is the identification of a “Lean Core” (Leader–Follower) topology that maximizes resilience while preserving informational diversity. By concentrating structural coupling within a small fraction of the system (approximately 5–6% acting as anchors), the network achieves a state of plastic stability—robust enough to survive high noise, flexible enough to adapt, and efficient enough to avoid the brittleness of heavy centralized control. The accompanying PDF provides an executive summary of the framework and findings, while the associated CSV files contain the underlying simulation results. Together, these artifacts offer a reusable model for analyzing resilience across biological, cognitive, organizational, and artificial systems.