Skip to main content
Log in

Variation of Lyapunov exponents on a strange attractor

  • Published:
Journal of Nonlinear Science Aims and scope Submit manuscript

Summary

We introduce the idea of local Lyapunov exponents which govern the way small perturbations to the orbit of a dynamical system grow or contract after afinite number of steps,L, along the orbit. The distributions of these exponents over the attractor is an invariant of the dynamical system; namely, they are independent of the orbit or initial conditions. They tell us the variation of predictability over the attractor. They allow the estimation of extreme excursions of perturbations to an orbit once we know the mean and moments about the mean of these distributions. We show that the variations about the mean of the Lyapunov exponents approach zero asL → ∞ and argue from our numerical work on several chaotic systems that this approach is asL −v. In our examplesv ≈ 0.5–1.0. The exponents themselves approach the familiar Lyapunov spectrum in this same fashion.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Eckmann, J. P. and D. Ruelle, “Ergodic Theory of Chaos and Strange Attractors,”Rev. Mod. Phys. 57, 617 (1985).

    Google Scholar 

  2. Abarbanel, H. D. I., R. Brown, and J. Kadtke, “Prediction and System Identification in Chaotic Nonlinear Systems: Time Series with Broadband Spectra,”Phys. Lett. 138A, 401 (1989); “Prediction in Chaotic Nonlinear Systems: Methods for Time Series with Broadband Fourier Spectra,”Phys. Rev. 41A, 1782 (1990).

    Google Scholar 

  3. Kostelich, E. J. and J. A. Yorke, “Noise Reduction—Finding the Simplest Dynamical System Consistent with the Data,”Physica 41D, 183 (1990).

    Google Scholar 

  4. Farmer, J. D. and J. J. Sidorowich, “Predicting Chaotic Time Series,”Phys. Rev. Lett. 59, 845 (1987).

    Google Scholar 

  5. Pesin, Ya. B., “Lyapunov Characteristic Exponents and Smooth Ergodic Theory,”Usp. Mat. Nauk 32, 55 (1977);Russian Math. Surveys 32, 55 (1977).

    Google Scholar 

  6. Goldhirsch, I., P-L Sulem, and S. A. Orzag, “Stability and Lyapunov Stability of Dynamical Systems: A Differential Approach and a Numerical Method,”Physica 27D, 311 (1986).

    Google Scholar 

  7. Grassberger, P. and I. Procaccia, “Dimensions and Entropies of Strange Attractors from a Fluctuating Dynamics Approach,”Physica 13D, 34 (1984).

    Google Scholar 

  8. Grassberger, P., R. Badii, and A. Politi, “Scaling Laws for Invariant Measures on Hyperbolic and Non-Hyperbolic Attractors,”J. Stat. Phys. 51, 135 (1988).

    Google Scholar 

  9. Lindenberg, K. and B. J. West, “The First, the Biggest, and Other Such Considerations,”J. Stat. Phys. 42, 201 (1986).

    Google Scholar 

  10. Ruelle, D., “Ergodic Theory of Differentiable Dynamical Systems,” Publications Mathématiques of the Institut des Hautes Études Scientifiques, No.50, 27–58 (1979).

    Google Scholar 

  11. Abarbanel, H. D. I., S. Koonin, H. Levine, G. J. F. MacDonald, and O. Rothaus, “Statistics of Extreme Events with Application to Climate,” JASON/MITRE Report JSR-90-305; November 26, 1990; “Issues in Predictability,” JASON/MITRE Report JSR-90-320; November 27, 1990.

  12. Ott, E., C. Grebogi, and J. A. Yorke, “Controlling Chaos,”Phys. Rev. Lett. 64, 1196 (1990).

    Google Scholar 

  13. Shinbrot, T., E. Ott, C. Grebogi, and J. A. Yorke, “Using Chaos to Direct Trajectories to Targets,”Phys. Rev. Lett. 65, 3215 (1990).

    Google Scholar 

  14. Ditto, W. L., S. N. Rauseo, and M. L. Spano, “Experimental Control of Chaos,”Phys. Rev. Lett. 65, 3211 (1990).

    Google Scholar 

  15. Vastano, J. A. and R. D. Moser, “Lyapunov Exponent Analysis and the Transition to Chaos in Taylor-Couette Flow,” Preprint from the Center for Turbulence Research, Stanford University and NASA-Ames Research Center, May 10, 1990.

  16. Brown, R, P. Bryant, and H.D.I. Abarbanel, “Computing the Lyapunov Spectrum of a Dynamical System from Observed Time Series”; to appear inPhys. Rev. A, Winter, 1991. We refer to this paper as BBA.

  17. Abarbanel, H. D. I., R. Brown, and M. Kennel, “Determining Local Lyapunov Exponents from Observed Data,” UCSD/INLS Preprint, Winter, 1991.

  18. Oseledec, V. I., “A Multiplicative Ergodic Theorem. Lyapunov Characteristic Numbers for Dynamical Systems,”Trudy Mosk. Mat. Obsc. 19, 197 (1968);Moscow Math. Soc. 19, 197 (1968).

    Google Scholar 

  19. Hénon, M., “A Two-Dimensional Mapping with a Strange Attractor,”Commun. Math. Phys. 50, 69 (1976).

    Google Scholar 

  20. Ikeda, K., “Multiple-Valued Stationary State and Its Instability of the Transmitted Light by a Ring Cavity System,”Opt. Commun. 30, 257 (1979).

    Google Scholar 

  21. Lorenz, E. N., “Deterministic Nonperiodic Flow,”J. Atmos. Sci. 20, 130 (1963).

    Google Scholar 

  22. Lorenz, E. N., “Irregularity: A Fundamental Property of the Atmosphere,”Tellus 36A, 98 (1984).

    Google Scholar 

  23. J. R. Ford and W. R. Borland, Common Los Alamos Mathematical Software Compendium,Document number CIC # 148 (April 1988), Los Alamos National Laboratory, Los Alamos, New Mexico. We used the Adams predictor corrector subroutine DEABM, and the backward differentiation subroutine DDEBDF.

  24. Parker, T. S. and L. O. Chua,Practical Numerical Algorithms for Chaotic Systems, Springer-Verlag, New York (1990).

    Google Scholar 

  25. Greene, J. M. and J. S. Kim, “The Calculation of Lyapunov Spectra,”Physica 24D, 213 (1986).

    Google Scholar 

  26. Nese, Jon M., “Quantifying Local Predictability in Phase Space,”Physica 35D, 237 (1989). Also see his Ph.D. thesis entitled “Predictability of Weather and Climate in a Coupled-Ocean Atmosphere Model: A Dynamical Systems Approach,” The Pennsylvania State University, Department of Meteorology, August, 1989; and references therein.

    Google Scholar 

  27. Eckmann, J. P., S. O. Kamphorst, D. Ruelle, and S. Ciliberto, “Lyapunov Exponents from Time Series,”Phys. Rev. 34A, 4971 (1986).

    Google Scholar 

  28. Fujisaka, H., “Statistical Dynamics Generated by Fluctuations of Local Lyapunov Exponents,”Prog. Theor. Phys. 70, 1274 (1983).

    Google Scholar 

  29. Benzi, R. and G. F. Carnevale, “A Possible Measure of Local Predictability,”J. Atmos. Sci. 46, 3595 (1989).

    Google Scholar 

  30. Paladin, G. and A. Vulpiani, “Anomalous Scaling Laws in Multifractal Objects,”Phys. Repts. 156, 147 (1987).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

Communicated by Stephen Wiggins

Rights and permissions

Reprints and permissions

About this article

Cite this article

Abarbanel, H.D.I., Brown, R. & Kennel, M.B. Variation of Lyapunov exponents on a strange attractor. J Nonlinear Sci 1, 175–199 (1991). https://doi.org/10.1007/BF01209065

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01209065

Key words

Navigation