Skip to main content

Dynamical Regimes and Time Scales

  • Chapter
  • First Online:
Predictability of Chaotic Dynamics

Abstract

The key factor to build the finite-time distributions is finding the most adequate interval length, to be large enough to ensure a satisfactory reduction of the local fluctuations, but small enough to reveal slow trends. This length is different for every orbit. There are different time scales to take into account in every model, including transient behaviours that could be of interest. By a proper selection of the total integration time, we can characterise the dynamics using small finite-time interval lengths. But increasing those lengths, we see how the distributions stop tracing the flow at local scales and begin to describe the flow at global scales, that is, the global regime.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 69.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 89.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Abraham, R., Smale, S.: Non-genericity of Ω-stability. Proc. Symp. Pure Math. 14, 5 (1970)

    Article  Google Scholar 

  2. Aguirre, J., Vallejo, J.C., Sanjuán, M.A.F.: Wada basins and chaotic invariant sets in the Hénon-Heiles system. Phys. Rev. E 64, 66208 (2001)

    Article  ADS  Google Scholar 

  3. Alligood, K.T., Sauer, T.D., Yorke, J.A.: Chaos. An Introduction to Dynamical Systems, p. 383. Springer, New York (1996)

    Google Scholar 

  4. Alligood, K.T., Sander, E., Yorke, J.A.: Three-dimensional crisis: crossing bifurcations and unstable dimension variability. Phys. Rev. Lett. 96, 244103 (2006)

    Article  ADS  Google Scholar 

  5. Barreto, E., So, P.: Mechanisms for the development of unstable dimension variability and the breakdown of shadowing in coupled chaotic systems. Phys. Rev. Lett. 85, 2490 (2000)

    Article  ADS  Google Scholar 

  6. Benzi, R., Parisi, G., Vulpiani, A.: Characterisation of intermittency in chaotic systems. J. Phys. A 18, 2157 (1985)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  7. Binney, J., Tremaine, S.: Galactic Dynamics. Princenton University Press, Princenton (1987)

    MATH  Google Scholar 

  8. Branicki, M., Wiggings, S.: Finite-time Lagrangian transport analysis: stable and unstable manifolds of hyperbolic trajectories and finite-time exponents. Nonlinear Proc. Geophys. 17, 1–36 (2010)

    Article  ADS  Google Scholar 

  9. Contopoulos, G.: Orbits in highly perturbed dynamical systems. I. Periodic orbits. Astron. J. 75, 96 (1970)

    ADS  MathSciNet  Google Scholar 

  10. Contopoulos, G., Grousousakou, E., Voglis, N.: Invariant spectra in Hamiltonian systems. Astron. Astrophys. 304, 374 (1995)

    ADS  Google Scholar 

  11. Davidchack, R.L., Lai, Y.C.: Characterization of transition to chaos with multiple positive Lyapunov exponents by unstable periodic orbits. Phys. Lett. A 270, 308 (2000)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  12. Grassberger, P.: Generalizations of the Hausdorff dimension of fractal measures. Phys. Lett. A 107, 101 (1985)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  13. Grassberger, P., Badii, R., Politi, A.: Scaling laws for invariant measures on hyperbolic and non-hyperbolic attractors. J. Stat. Phys. 51, 135 (1988)

    Article  ADS  MATH  Google Scholar 

  14. Grebogi, C., Ott, E., Yorke, J.A.: Crises, sudden changes in chaotic attractors, and transient chaos. Physica D 7, 181 (1983)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  15. Jacobs, J., Ott, E., Hunt, R.: Scaling of the durations of chaotic transients in windows of attracting periodicity. Phys. Rev. E 56, 6508 (1997)

    Article  ADS  MathSciNet  Google Scholar 

  16. Kantz, H., Grebogi, C., Prasad, A., Lai, Y.C., Sinde, E.: Unexpected robustness-against-noise of a class of nonhyperbolic chaotic attractors. Phys. Rev. E 65, 026209 (2002)

    Article  ADS  MathSciNet  Google Scholar 

  17. Kottos, T., Politi, A., Izrailev, F.M., Ruffo, S.: Scaling properties of Lyapunov Spectra for the band random matrix model. Phys. Rev. E 53, 6 (1996)

    Article  Google Scholar 

  18. Lai, Y.C., Grebogi, C., Kurths, J.: Modeling of deterministic chaotic systems. Phys. Rev. E 59, 2907 (1999)

    Article  ADS  Google Scholar 

  19. Mancho, A.M., Wiggins, S., Curbelo, J., Mendoza, C.: Lagrangian descriptors: a method for revealing phase space structures of general time dependent dynamical systems. Commun. Nonlinear Sci. 18, 3530 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  20. Meiss, J.D.: Transient measures for the standard map. Physica D 74, 254 (1994)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  21. Oyarzabal, R.S., Szezech, J.D., Batista, A.M., de Souza, S.L.T., Caldas, I.L., Viana, R.L., Sanjuán, M.A.F.: Transient chaotic transport in dissipative drift motion. Phys. Lett. A 380, 1621 (2016)

    Article  ADS  MathSciNet  Google Scholar 

  22. Parisi, G., Vulpiani, A.: Scaling law for the maximal Lyapunov characteristic exponent of infinite product of random matrices. J. Phys. A 19, L45 (1986)

    Article  Google Scholar 

  23. Prasad, A., Ramaswany, R.: Characteristic distributions of finite-time Lyapunov exponents. Phys. Rev. E 60, 2761 (1999)

    Article  ADS  Google Scholar 

  24. Sauer, T.: Shadowing breakdown and large errors in dynamical simulations of physical systems. Phys. Rev. E 65, 036220 (2002)

    Article  ADS  MathSciNet  Google Scholar 

  25. Sauer, T.: Chaotic itinerancy based on attractors of one-dimensional maps. Chaos 13, 947 (2003)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  26. Sauer, T., Grebogi, C., Yorke, J.A.: How long do numerical chaotic solutions remain valid? Phys. Lett. A 79, 59 (1997)

    Article  Google Scholar 

  27. Skokos, Ch., Bountis, T.C., Antonopoulos, Ch.: Geometrical properties of local dynamics in Hamiltonian systems: the Generalized Alignment Index (GALI) method. Physica D 231, 30 (2007)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  28. Smith, L.A., Spiegel, E.A.: Strange accumulators. In: Buchler, J.R., Eichhorn, H. (eds.) Chaotic Phenomena in Astrophysics. New York Academy of Sciences, New York (1987)

    Google Scholar 

  29. Stefanski, K., Buszko, K., Piecsyk, K.: Transient chaos measurements using finite-time Lyapunov exponents. Chaos 20, 033117 (2010)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  30. Szezech Jr., J.D., Lopes, S.R., Viana, R.L.: Finite time Lyapunov spectrum for chaotic orbits of non integrable Hamiltonian systems. Phys. Lett. A 335, 394 (2005)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  31. Vallejo, J.C., Aguirre, J., Sanjuan, M.A.F.: Characterization of the local instability in the Henon-Heiles Hamiltonian. Phys. Lett. A 311, 26 (2003)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  32. Vallejo, J.C., Viana, R., Sanjuan, M.A.F.: Local predictability and non hyperbolicity through finite Lyapunov Exponents distributions in two-degrees-of-freedom Hamiltonian systems. Phys. Rev. E 78, 066204 (2008)

    Article  ADS  MathSciNet  Google Scholar 

  33. Viana, R.L., Grebogi, C.: Unstable dimension variability and synchronization of chaotic systems. Phys. Rev. E 62, 462 (2000)

    Article  ADS  Google Scholar 

  34. Viana, R.L., Pinto, S.E., Barbosa, J.R., Grebogi, C.: Pseudo-deterministic chaotic systems. Int. J. Bifurcation Chaos Appl. Sci. Eng. 11, 1 (2003)

    Google Scholar 

  35. Viana, R.L., Barbosa, J.R., Grebogi, C., Batista, C.M.: Simulating a chaotic process. Braz. J. Phys. 35, 1 (2005)

    Article  ADS  Google Scholar 

  36. Yanchuk, S., Kapitaniak, T.: Symmetry increasing bifurcation as a predictor of chaos-hyperchaos transition in coupled systems. Phys. Rev. E 64, 056235 (2001)

    Article  ADS  Google Scholar 

  37. Ziehmann, C., Smith, L.A., Kurths, J.: Localized Lyapunov exponents and the prediction of predictability. Phys. Lett. A 271, 237 (2000)

    Article  ADS  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

Vallejo, J.C., Sanjuan, M.A.F. (2017). Dynamical Regimes and Time Scales. In: Predictability of Chaotic Dynamics . Springer Series in Synergetics. Springer, Cham. https://doi.org/10.1007/978-3-319-51893-0_3

Download citation

Publish with us

Policies and ethics