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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.

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Fig. 1: Application of the method on a toy model.


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This is a summary of: Kang, P. et al. Computing the committor with the committor to study the transition state ensemble. Nat. Comput. Sci. (2024).

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Systematic simulations and analysis of transition states using committor functions. Nat Comput Sci 4, 396–397 (2024).

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