MCSC (Massively Coherent Systems Computing) is an analog coherent system that controls chaos during errors and shocks in large networks. Unlike classical models (Ising, Kuramoto) that collapse sharply to low activity, MCSC exhibits a sharp surge to near-100% coherence, long-term holding at high levels (90–99% for hundreds of steps), and slow, controlled decline (to 30–60%) – never sudden zero failure. This behavior is demonstrated across multiple domains: random circuit sampling (RCS-like Hamming weight ~49–50%), power grid synchronization (recovery after shock to 87–95%), swarm robotics (100% coordination with partial recovery), brain-inspired oscillations (surge to 100% sync), Max-Cut optimization (best cut 80% of maximum), and risk propagation (rapid spread followed by slow decline to ~50%). All simulations run on commodity hardware – specifically a 2014 HP EliteBook G2 laptop with HDD storage and 8 GB DDR3 RAM – without any GPU or cloud requirements, showing strong scale stability: larger N enhances coherence and resilience even on low-end machines. MCSC offers a new approach for critical systems where reaction time prevents total collapse: energy grids, autonomous transport, financial networks, and biological modeling. Results-videos and graphics: https://github.com/Vasman84/-MCSC-Massively-Coherent-Systems-Computing
Vasil Manchev (Wed,) studied this question.