Although computational models of all sorts have advanced considerably in recent years, chaotic systems remain stubbornly hard to capture. A recent study offers a modeling advance that could prove useful for understanding unstable systems.

Although computational models of all sorts have advanced considerably in recent years, chaotic systems remain stubbornly hard to capture. A recent study offers a modeling advance that could prove useful for understanding unstable systems.