Comparing Information Metrics for a Coupled Ornstein–Uhlenbeck Process

James Heseltine, Eun-jin Kim

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)
44 Downloads (Pure)


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.
Original languageEnglish
Article number775
Number of pages16
Issue number8
Publication statusPublished - 8 Aug 2019
Externally publishedYes

Bibliographical note

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (


  • Fisher information
  • Fokker-Planck equation
  • Information length
  • Langevin equation
  • Metrics
  • O-U process
  • Probability density function
  • Stochastic processes

ASJC Scopus subject areas

  • Physics and Astronomy(all)


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