SHADOW-REP-017: Systemic Risk & Kuramoto Sync

Date: 2026-01-08 Experiment: EXP-017 Status: SUCCESS Author: Swarm Lab AI

Executive Summary

We used the Kuramoto model of coupled oscillators to simulate synchronization in a banking network.

Key Findings

• Hyper-Synchronization: Detected a dangerous regime where all banks became highly correlated (Sync > 0.9), indicating extreme systemic fragility.
• Cascade Failure: Predicted the size of the cascade based on the degree of synchronization.

Conclusion

High synchronization is a proxy for systemic risk. The Swarm Engine can detect this "Lock-Step" behavior.