Linear Response Theory for Jump-Driven Stochastic Systems: Transient Statistics and Escape Dynamics

Abstract

In this paper, we develop a linear response theory for a class of stochastic differential equations driven by jump processes. We investigate the response of the system to small time-dependent perturbations from three complementary perspectives: probability density functions, mean exit times, and escape probabilities. By performing perturbation analyses of the corresponding forward and backward Kolmogorov equations, we derive the first-order response equations governing these statistical quantities and establish explicit linear response formulas, which characterize the sensitivity of the evolution of the probability distribution and the escape behavior of the system to variations in its coefficients.

arXiv commentThe numerical experiments have not yet been completed, and some parts of the manuscript contain errors, for example, the definition of the stopping time \(τ_D^{t,x}\) in Theorem 5.3 is incorrect. We will resubmit the manuscript after making the necessary corrections and improvements