Data Assimilation (DA) is the backbone of modern weather forecasting. It integrates observational data into computer simulations to synchronize the model with nature. The Duality Principle posits that chaos control is mathematically the "twin" (dual) of DA.

Data Assimilation: Uses observations to synchronize the Model to Nature.

Chaos Control: Uses interventions to synchronize Nature to a desired Model ("target trajectory").

"The butterfly effect has long been a symbol of unpredictability," says Dr. Miyoshi. "But I asked a simple question: If a butterfly's wings can change the future, does that not imply that with the right, tiny push, we could choose a better future?"
Instead of suppressing the chaotic system with massive force, this method acts like mathematical judo-leveraging the system's inherent instability. By applying minute, calculated "interventions" (analogous to the butterfly's flap), the system can be guided toward a "target trajectory"-for instance, shifting real-world conditions just enough to align with a model-simulated scenario where a typhoon causes no damage. Once synchronized, control becomes much easier to maintain. This study establishes the theoretical foundation for "Control Simulation Experiments" (CSE), a framework previously proposed by Miyoshi's team. It provides a roadmap for future disaster prevention research, moving beyond passive prediction to active mitigation. Beyond meteorology, this general framework is expected to serve as a universal tool for studying interventions in various chaotic systems, from ecosystems to economics.