A martingale approach to time-dependent and time-periodic linear response in Markov jump processes (2201.02982v4)
Abstract: We consider a Markov jump process on a general state space to which we apply a time-dependent weak perturbation over a finite time interval. By martingale-based stochastic calculus, under a suitable exponential moment bound for the perturbation we show that the perturbed process does not explode almost surely and we study the linear response (LR) of observables and additive functionals. When the unperturbed process is stationary, the above LR formulas become computable in terms of the steady state two-time correlation function and of the stationary distribution. Applications are discussed for birth and death processes, random walks in a confining potential, random walks in a random conductance field. We then move to a Markov jump process on a finite state space and investigate the LR of observables and additive functionals in the oscillatory steady state (hence, over an infinite time horizon), when the perturbation is time-periodic. As an application we provide a formula for the complex mobility matrix of a random walk on a discrete $d$-dimensional torus, with possibly heterogeneous jump rates.
- A. Faggionato, P. Mathieu; Martingale-based linear response and Nyquist relations in periodically driven Markov processes. In preparation.
- A. Faggionato, M. Salvi; Infinite volume limit of the complex mobility matrix for the random conductance model on 𝕋Ndsubscriptsuperscript𝕋𝑑𝑁{\mathbb{T}}^{d}_{N}blackboard_T start_POSTSUPERSCRIPT italic_d end_POSTSUPERSCRIPT start_POSTSUBSCRIPT italic_N end_POSTSUBSCRIPT. In preparation.
- J. Jacod, A. Shiryaev; Limit theorems for stochastic processes (Vol. 288). Springer Science & Business Media (2013).
- S.R.S. Varadhan. Stochastic processes. Courant Lecture Notes in Mathematics.