Predictability of Chaotic Dynamics : A Finite-time Lyapunov Exponents Approach / by Juan C. Vallejo, Miguel A. F. Sanjuan.

Format:

Book

Author/Creator:

Vallejo, Juan C., author.

Sanjuán, Miguel A. F. (Miguel Angel Fernández), author.

Contributor:

SpringerLink (Online service)

Series:

Physics and Astronomy (Springer-11651)

Springer series in synergetics 0172-7389

Springer Series in Synergetics, 0172-7389

Language:

English

Subjects (All):

Statistical physics.

Physics.

Space sciences.

Mathematical physics.

Applications of Nonlinear Dynamics and Chaos Theory.

Numerical and Computational Physics, Simulation.

Space Sciences (including Extraterrestrial Physics, Space Exploration and Astronautics).

Mathematical Applications in the Physical Sciences.

Local Subjects:

Applications of Nonlinear Dynamics and Chaos Theory.

Numerical and Computational Physics, Simulation.

Space Sciences (including Extraterrestrial Physics, Space Exploration and Astronautics).

Mathematical Applications in the Physical Sciences.

Physical Description:

1 online resource (XIX, 196 pages) : 76 illustrations, 48 illustrations in color.

Edition:

Second edition 2019.

Contained In:

Springer eBooks

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2019.

System Details:

text file PDF

Summary:

This book is primarily concerned with the computational aspects of predictability of dynamical systems - in particular those where observations, modeling and computation are strongly interdependent. Unlike with physical systems under control in laboratories, in astronomy it is uncommon to have the possibility of altering the key parameters of the studied objects. Therefore, the numerical simulations offer an essential tool for analysing these systems, and their reliability is of ever-increasing interest and importance. In this interdisciplinary scenario, the underlying physics provide the simulated models, nonlinear dynamics provides their chaoticity and instability properties, and the computer sciences provide the actual numerical implementation. This book introduces and explores precisely this link between the models and their predictability characterization based on concepts derived from the field of nonlinear dynamics, with a focus on the strong sensitivity to initial conditions and the use of Lyapunov exponents to characterize this sensitivity. This method is illustrated using several well-known continuous dynamical systems, such as the Contopoulos, Hénon-Heiles and Rössler systems. This second edition revises and significantly enlarges the material of the first edition by providing new entry points for discussing new predictability issues on a variety of areas such as machine decision-making, partial differential equations or the analysis of attractors and basins. Finally, the parts of the book devoted to the application of these ideas to astronomy have been greatly enlarged, by first presenting some basics aspects of predictability in astronomy and then by expanding these ideas to a detailed analysis of a galactic potential.

Contents:

Preface

Forecasting and chaos

Lyapunov exponents

Dynamical regimes and timescales

Predictability

Chaos, predictability and astronomy

A detailed example: galactic dynamics

Appendix. .

Other Format:

Printed edition:

ISBN:

978-3-030-28630-9

9783030286309

Access Restriction:

Restricted for use by site license.