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Optimizing probability of barrier crossing with differentiable simulators
Martin Šípka · Johannes Dietschreit · Michal Pavelka · Lukáš Grajciar · Rafael Gomez-Bombarelli

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in Differentiable Almost Everything: Differentiable Relaxations, Algorithms, Operators, and Simulators »
Event URL: https://openreview.net/forum?id=mbJM1RNCJC »

Simulating events that involve some energy barrier often requires us to promote the barrier crossing in order to increase the probability of the event. One example of such a system can be a chemical reaction which we propose to explore using differentiable simulations. Transition path discovery and estimation of the reaction barrier are merged into a single end-to-end problem that is solved by path-integral optimization. We show how the probability of transition can be formulated in a differentiable way and increase it by introducing a trainable position dependent bias function. We also introduce improvements over standard methods making DiffSim training stable and efficient.

Author Information

Martin Šípka (Charles University | MIT)
Johannes Dietschreit (Massachusetts Institute of Technology)
Michal Pavelka (Faculty of Mathematics and Physics, Charles University Prague)
Lukáš Grajciar (Charles University Prague)
Rafael Gomez-Bombarelli (MIT)

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