Rare events arising in nonlinear atmospheric dynamics remain hard to predict and attribute.
We address the problem of forecasting rare events in a prototypical example, sudden …

We propose a novel approach for computing committor functions, which describe transitions
of a stochastic process between metastable states. The committor function satisfies a …

We present a time-dependent variational method to learn the mechanisms of equilibrium
reactive processes and efficiently evaluate their rates within a transition path ensemble. This …

Estimating the likelihood, timing, and nature of events is a major goal of modeling stochastic
dynamical systems. When the event is rare in comparison with the timescales of simulation …

Inferring a diffusion equation from discretely observed measurements is a statistical
challenge of significant importance in a variety of fields, from single-molecule tracking in …

Understanding dynamics in complex systems is challenging because there are many
degrees of freedom, and those that are most important for describing events of interest are …

As an optimal one-dimensional reaction coordinate, the committor function not only
describes the probability of a trajectory initiated at a phase space point first reaching the …

The probability that a configuration of a physical system reacts, or transitions from one
metastable state to another, is quantified by the committor function. This function contains …

A central object in the computational studies of rare events is the committor function. Though
costly to compute, the committor function encodes complete mechanistic information of the …

In the field of computational physics and material science, the efficient sampling of rare
events occurring at atomic scale is crucial. It aids in understanding mechanisms behind a …