Abstract

We investigate a piecewise-deterministic Markov process, evolving on a Polish metric space, whose deterministic behaviour between random jumps is governed by some semi-flow, and any state right after the jump is attained by a randomly selected continuous transformation. It is assumed that the jumps appear at random moments, which coincide with the jump times of a Poisson process with intensity λ. The model of this type, although in a more general version, was examined in our previous papers, where we have shown, among others, that the Markov process under consideration possesses a unique invariant probability measure, say $\nu_{\lambda}^*$. The aim of this paper is to prove that the map $\lambda\mapsto\nu_{\lambda}^*$ is continuous (in the topology of weak convergence of probability measures). The studied dynamical system is inspired by certain stochastic models for cell division and gene expression.

Highlights

  • Piecewise-deterministic Markov processes (PDMPs) originate with M.H.A

  • PDMPs are encountered as suitable mathematical models for processes in the physical world around us, e.g., in resource allocation and service provisioning or biology: as stochastic models for gene expression and autoregulation [2, 3], cell division [4], excitable membranes [5] or population dynamics [6, 7]

  • The fundamentals of existence and uniqueness of invariant probability measures for Markov operators and semigroups of Markov operators associated with PDMPs, as well as their asymptotic properties, have attracted much attention

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Summary

Introduction

Piecewise-deterministic Markov processes (PDMPs) originate with M.H.A. Davis [1]. We are concerned with a special case of the PDMP described in [13, 14], whose deterministic motion between jumps depends on a single continuous semi-flow, and any post-jump location is attained by a continuous transformation of the pre-jump state, randomly selected (with a place-dependent probability) among all possible ones The jumps in this model occur at random time points according to a homogeneous Poisson process. While the SLLN and the CLT provide the theoretical foundation for successful approximation of the invariant measure by means of observing or simulating (many) sample trajectories of the process, this result asserts the stability of this procedure, at least locally in parameter space It is a prerequisite for the development of a bifurcation theory. We establish the announced results on the continuous dependence of the invariant measure on the jump frequency for both, the discrete-time system, constituted by the post jump-locations, and for the PDMP itself

Preliminaries
Description of the model
Some properties of the operator Pλ
Main results
Full Text
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