Mean first passage times for piecewise deterministic Markov processes and the effects of critical points
File(s)resPDMP.pdf (319.93 KB)
Accepted version
Author(s)
Bressloff, Paul C
Lawley, Sean D
Type
Journal Article
Abstract
In this paper, we use probabilistic methods to determine the mean first passage time (MFPT) for a two-state piecewise deterministic Markov process (PDMP), also known as a dichotomous noise process, to escape from a finite interval. In particular, we consider the case where the set of functions generating the piecewise deterministic dynamics have one or more critical points. In order to solve this type of problem, we partition the domain into a set of subintervals that contain no critical points and impose conditions at the critical points separating these regions. Our analysis exploits the fact that a PDMP satisfies the strong Markov property. We prove that in the absence of common critical points, the MFPT is finite. Through specific examples, we also explore how the MFPT depends on the number of critical points and prove that the MFPT can be infinite if there are common critical points.
Date Issued
2017-06
Date Acceptance
2017-05-02
Citation
Journal of Statistical Mechanics: Theory and Experiment, 2017, 2017 (6)
ISSN
1742-5468
Publisher
IOP Publishing
Journal / Book Title
Journal of Statistical Mechanics: Theory and Experiment
Volume
2017
Issue
6
Copyright Statement
Copyright © 2017 IOP Publishing Ltd. This is an author-created, un-copyedited version of an article published in Journal of Statistical Mechanics: Theory and Experiment. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at 10.1088/1742-5468/aa71df
Identifier
http://dx.doi.org/10.1088/1742-5468/aa71df
Publication Status
Published
Article Number
063202
Date Publish Online
2017-06-02