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arXiv · 2006.10979

Estimating the Most Probable Transition Time for Stochastic Dynamical Systems

Yuanfei Huang·Ying Chao·Wei Wei·Jinqiao Duan
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Abstract

This work is devoted to the investigation of the most probable transition time between metastable states for stochastic dynamical systems. Such a system is modeled by a stochastic differential equation with non-vanishing Brownian noise, and is restricted in a domain with absorbing boundary. Instead of minimizing the Onsager-Machlup action functional, we examine the maximum probability that the solution process of the system stays in a neighborhood (or a tube) of a transition path, in order to characterize the most probable transition path. We first establish the exponential decay lower bound and a power law decay upper bound for the maximum of this probability. Based on these estimates, we further derive the lower and upper bounds for the most probable transition time, under suitable conditions. Finally, we illustrate our results in simple stochastic dynamical systems, and highlight the relation with some relevant works.

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Yuanfei Huang, Ying Chao, Wei Wei, Jinqiao Duan. 2020-06-19. Estimating the Most Probable Transition Time for Stochastic Dynamical Systems. https://doi.org/10.1088/1361-6544/abf33d

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