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Physics - Theoretical, Mathematical & Computational Physics | Foundations of Synergetics II - Complex Patterns

Foundations of Synergetics II

Complex Patterns

Mikhailov, Alexander, Loskutov, Alexander Yu.

Softcover reprint of the original 1st ed. 1991, VIII, 210 pp. 98 figs.

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  • About this textbook

This textbook is based on a lecture course in synergetics given at the University of Moscow. In this second of two volumes, we discuss the emergence and properties of complex chaotic patterns in distributed active systems. Such patterns can be produced autonomously by a system, or can result from selective amplification of fluctuations caused by external weak noise. Although the material in this book is often described by refined mathematical theories, we have tried to avoid a formal mathematical style. Instead of rigorous proofs, the reader will usually be offered only "demonstrations" (the term used by Prof. V. I. Arnold) to encourage intuitive understanding of a problem and to explain why a particular statement seems plausible. We also refrained from detailing concrete applications in physics or in other scientific fields, so that the book can be used by students of different disciplines. While preparing the lecture course and producing this book, we had intensive discussions with and asked the advice of Prof. V. I. Arnold, Prof. S. Grossmann, Prof. H. Haken, Prof. Yu. L. Klimontovich, Prof. R. L. Stratonovich and Prof. Ya.

Content Level » Research

Keywords » Reaction-Diffusion Systems - Reaction-Diiffusion Systems - Synergetik - Turbulence - Verteilte Verarbeitung - chaos - noise - pattern - random processes

Related subjects » Communication Networks - Image Processing - Life Sciences, Medicine & Health - Plant Sciences - Theoretical, Mathematical & Computational Physics

Table of contents 

1. Introduction.- 1.1 Chaotic Dynamics.- 1.2 Noise-Induced Complex Patterns.- 1.3 Chaos and Self-Organization.- 2. Unpredictable Dynamics.- 2.1 Hamiltonian Systems.- 2.2 Destruction of Tori.- 2.3 Ergodicity and Mixing.- 3. Strange Attractors.- 3.1 Dissipative Systems and Their Attractors.- 3.2 The Lorenz Model.- 3.3 Lyapunov Exponents.- 3.4 The Autocorrelation Function.- 4. Fractals.- 4.1 Self-Similar Patterns.- 4.2 Dimensions.- 4.3 Fractal Dimensions of Strange Attractors.- 5. Discrete Maps.- 5.1 Fixed Points and Cycles.- 5.2 Chaotic Maps.- 5.3 Feigenbaum Universality.- 6. Routes to Temporal Chaos.- 6.1 Bifurcations.- 6.2 The Ruelle-Takens Scenario.- 6.3 Period Doubling.- 6.4 Intermittency.- 7. Spatio-Temporal Chaos.- 7.1 Embedding Dimensions.- 7.2 Phase Turbulence.- 7.3 Coupled Chaotic Maps.- 8. Random Processes.- 8.1 Probabilistic Automata.- 8.2 Continuous Random Processes.- 8.3 The Fokker-Planck Equation.- 9. Active Systems with Noise.- 9.1 Generalized Brownian Motion.- 9.2 Internal Noise.- 9.3 Optimal Fluctuations.- 10. Population Explosions.- 10.1 Mean Ignition Time of Explosion.- 10.2 Intermittency of Growth.- 10.3 Breeding Centers.- 11. Extinction and Long-Time Relaxation.- 11.1 Random Traps.- 11.2 Irreversible Annihilation.- 11.3 Conserved Quantities and Long-Time Relaxation.- 11.4 Stochastic Segregation and the Sub-Poissonian Distribution.- 12. Catastrophes.- 12.1 Second-Order Phase Transitions.- 12.2 Sweeping Through the Critical Region.- 12.3 The Biased Transition.- 12.4 Population Settling-Down.- 12.5 Survival in the Fluctuating Environment.- References.

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