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Open AccessArticle

Comparing Information Metrics for a Coupled Ornstein–Uhlenbeck Process

School of Mathematics and Statistics, University of Sheffield, Sheffield S3 7RH, UK
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Entropy 2019, 21(8), 775; https://doi.org/10.3390/e21080775
Received: 9 July 2019 / Revised: 30 July 2019 / Accepted: 6 August 2019 / Published: 8 August 2019
(This article belongs to the Special Issue Statistical Mechanics and Mathematical Physics)
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Abstract

It is often the case when studying complex dynamical systems that a statistical formulation can provide the greatest insight into the underlying dynamics. When discussing the behavior of such a system which is evolving in time, it is useful to have the notion of a metric between two given states. A popular measure of information change in a system under perturbation has been the relative entropy of the states, as this notion allows us to quantify the difference between states of a system at different times. In this paper, we investigate the relaxation problem given by a single and coupled Ornstein–Uhlenbeck (O-U) process and compare the information length with entropy-based metrics (relative entropy, Jensen divergence) as well as others. By measuring the total information length in the long time limit, we show that it is only the information length that preserves the linear geometry of the O-U process. In the coupled O-U process, the information length is shown to be capable of detecting changes in both components of the system even when other metrics would detect almost nothing in one of the components. We show in detail that the information length is sensitive to the evolution of subsystems. View Full-Text
Keywords: stochastic processes; Langevin equation; Fokker–Planck equation; information length; Fisher information; metrics; O-U process; probability density function stochastic processes; Langevin equation; Fokker–Planck equation; information length; Fisher information; metrics; O-U process; probability density function
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Heseltine, J.; Kim, E.-J. Comparing Information Metrics for a Coupled Ornstein–Uhlenbeck Process. Entropy 2019, 21, 775.

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