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2012 Limit theorems for infinite-dimensional piecewise deterministic Markov processes. Applications to stochastic excitable membrane models
Martin Riedler, Michèle Thieullen, Gilles Wainrib
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Electron. J. Probab. 17: 1-48 (2012). DOI: 10.1214/EJP.v17-1946

Abstract

We present limit theorems for a sequence of Piecewise Deterministic Markov Processes (PDMPs) taking values in a separable Hilbert space. This class of processes provides a rigorous framework for stochastic spatial models in which discrete random events are globally coupled with continuous space dependent variables solving partial differential equations, e.g., stochastic hybrid models of excitable membranes. We derive a law of large numbers which establishes a connection to deterministic macroscopic models and a martingale central limit theorem which connects the stochastic fluctuations to diffusion processes. As a prerequisite we carry out a thorough discussion of Hilbert space valued martingales associated to the PDMPs. Furthermore, these limit theorems provide the basis for a general Langevin approximation to PDMPs, i.e., stochastic partial differential equations that are expected to be similar in their dynamics to PDMPs. We apply these results to compartmental-type models of spatially extended excitable membranes. Ultimately this yields a system of stochastic partial differential equations which models the internal noise of a biological excitable membrane based on a theoretical derivation from exact stochastic hybrid models.

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Martin Riedler. Michèle Thieullen. Gilles Wainrib. "Limit theorems for infinite-dimensional piecewise deterministic Markov processes. Applications to stochastic excitable membrane models." Electron. J. Probab. 17 1 - 48, 2012. https://doi.org/10.1214/EJP.v17-1946

Information

Accepted: 18 July 2012; Published: 2012
First available in Project Euclid: 4 June 2016

zbMATH: 1255.60126
MathSciNet: MR2955047
Digital Object Identifier: 10.1214/EJP.v17-1946

Subjects:
Primary: 60J25
Secondary: 60B12, 60F05, 92C20

JOURNAL ARTICLE
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