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About this paper
Boya Hou, Shane Wang, Siddharth Ambekar, Maxim Raginsky, Olgica Milenkovic
The authors construct a controller for rare molecular transitions using leading Koopman eigenfunctions to identify metastable basins and estimate the committor. They solve for the bias through kernel-based optimization without repeated controlled rollouts for training. On Müller–Brown, it reaches the target in 99.0% of paths versus 100% for TPS-DPS, while following the reported lower-energy route.
Summary by alphaXiv.
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