Natural extension of fast-slow decomposition for dynamical systems

J. E. Rubin, B. Krauskopf, and H. M. Osinga
Phys. Rev. E 97, 012215 – Published 23 January 2018

Abstract

Modeling and parameter estimation to capture the dynamics of physical systems are often challenging because many parameters can range over orders of magnitude and are difficult to measure experimentally. Moreover, selecting a suitable model complexity requires a sufficient understanding of the model's potential use, such as highlighting essential mechanisms underlying qualitative behavior or precisely quantifying realistic dynamics. We present an approach that can guide model development and tuning to achieve desired qualitative and quantitative solution properties. It relies on the presence of disparate time scales and employs techniques of separating the dynamics of fast and slow variables, which are well known in the analysis of qualitative solution features. We build on these methods to show how it is also possible to obtain quantitative solution features by imposing designed dynamics for the slow variables in the form of specified two-dimensional paths in a bifurcation-parameter landscape.

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  • Received 19 January 2017
  • Revised 26 October 2017

DOI:https://doi.org/10.1103/PhysRevE.97.012215

©2018 American Physical Society

Physics Subject Headings (PhySH)

Nonlinear DynamicsPhysics of Living Systems

Authors & Affiliations

J. E. Rubin

  • Department of Mathematics, University of Pittsburgh, 301 Thackeray Hall, Pittsburgh, Pennsylvania 15260, USA

B. Krauskopf and H. M. Osinga

  • Department of Mathematics, University of Auckland, Private Bag 92019 Auckland 1142, New Zealand

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Issue

Vol. 97, Iss. 1 — January 2018

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