Systematic simulations and analysis of transition states using committor functions

Data about the transition states of rare transitions between long-lived states are needed to simulate physical and chemical processes; however, existing computational approaches often gather little information about these states. A machine-learning technique resolves this challenge by exploiting the century-old theory of committor functions.