arXiv Analytics

Sign in

arXiv:1207.2719 [math.PR]AbstractReferencesReviewsResources

Minimising the expected commute time

Saul Jacka, Ma. Elena Hernandez-Hernandez

Published 2012-07-11, updated 2018-12-18Version 3

Motivated in part by a problem in simulated tempering (a form of Markov chain Monte Carlo) we seek to minimise, in a suitable sense, the time it takes a (regular) diffusion with instantaneous reflection at 0 and 1 to travel from the origin to $1$ and then return (the so-called commute time from 0 to 1). We consider the static and dynamic versions of this problem where the control mechanism is related to the diffusion\rq{}s drift via the corresponding scale function. In the static version the diffusion's drift can be chosen at each point in [0,1], whereas in the dynamic version, we are only able to choose the drift at each point at the time of first visiting that point. The dynamic version leads to a novel type of stochastic control problem.

Comments: 21 pages; significant revision; title change; additional author
Categories: math.PR, math.OC
Subjects: 60J25, 60J27, 60J60, 93E20
Related articles: Most relevant | Search more
arXiv:2403.06715 [math.PR] (Published 2024-03-11)
Dynamic minimisation of the commute time for a one-dimensional diffusion
arXiv:math/0701390 [math.PR] (Published 2007-01-14)
The birthday problem and Markov chain Monte Carlo
arXiv:math/0407120 [math.PR] (Published 2004-07-08)
A mixture representation of πwith applications in Markov chain Monte Carlo and perfect sampling