The findings come from Professors Michelle Girvan and Edward Ott along with two other UMD collaborators. "They employed a machine-learning algorithm called reservoir computing to “learn” the dynamics of an archetypal chaotic system called the Kuramoto-Sivashinsky equation. The evolving solution to this equation behaves like a flame front, flickering as it advances through a combustible medium."

Read the story in Quanta magazine.