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Chaos Detection and Predictability

Distinguishing chaoticity from regularity in deterministic dynamical systems and specifying the subspace of the phase space in which instabilities are expected to occur is of utmost importance in as disparate areas as astronomy, particle physics and climate dynamics. To address these issues there ex...

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Corporate Author: SpringerLink (Online service)
Other Authors: Skokos, Charalampos (Haris). (Editor, http://id.loc.gov/vocabulary/relators/edt), Gottwald, Georg A. (Editor, http://id.loc.gov/vocabulary/relators/edt), Laskar, Jacques. (Editor, http://id.loc.gov/vocabulary/relators/edt)
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2016.
Edition:1st ed. 2016.
Series:Lecture Notes in Physics, 915
Subjects:
Statistical physics.
Physics.
Mathematical physics.
Space sciences.
Physical geography.
Applications of Nonlinear Dynamics and Chaos Theory.
Mathematical Methods in Physics.
Mathematical Applications in the Physical Sciences.
Space Sciences (including Extraterrestrial Physics, Space Exploration and Astronautics).
Earth System Sciences.
Online Access:https://doi.org/10.1007/978-3-662-48410-4
Table of Contents:
  • Estimating Lyapunov exponents from time series
  • Theory and applications of the fast Lyapunov Indicator (FLI) method
  • Theory and applications of the Orthogonal Fast Lyapunov Indicator (OFLI and OFLI2) methods
  • Theory and applications of the Mean Exponential Growth factor of Nearby Orbits (MEGNO) method
  • The Smaller (SALI) and the Generalized (GALI) Alignment Indices: Efficient Methods of Chaos Detection
  • The Relative Lyapunov Indicators: Theory and Application to Dynamical Astronomy
  • The 0-1 Test for Chaos: A review.

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