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Preface | p. vii |
The phenomenology of complex systems | p. 1 |
Complexity, a new paradigm | p. 1 |
Signatures of complexity | p. 3 |
Onset of complexity | p. 5 |
Four case studies | p. 8 |
Rayleigh-Benard convection | p. 8 |
Atmospheric and climatic variability | p. 11 |
Collective problem solving: food recruitment in ants | p. 15 |
Human systems | p. 19 |
Summing up | p. 23 |
Deterministic view | p. 25 |
Dynamical systems, phase space, stability | p. 25 |
Conservative systems | p. 27 |
Dissipative systems | p. 27 |
Levels of description | p. 34 |
The microscopic level | p. 34 |
The macroscopic level | p. 36 |
Thermodynamic formulation | p. 38 |
Bifurcations, normal forms, emergence | p. 41 |
Universality, structural stability | p. 46 |
Deterministic chaos | p. 49 |
Aspects of coupling-induced complexity | p. 53 |
Modeling complexity beyond physical science | p. 59 |
The probabilistic dimension of complex systems | p. 64 |
Need for a probabilistic approach | p. 64 |
Probability distributions and their evolution laws | p. 65 |
The retrieval of universality | p. 72 |
The transition to complexity in probability space | p. 77 |
The limits of validity of the macroscopic description | p. 82 |
Closing the moment equations in the mesoscopic description | p. 82 |
Transitions between states | p. 84 |
Average values versus fluctuations in deterministic chaos | p. 88 |
Simulating complex systems | p. 90 |
Monte Carlo simulation | p. 91 |
Microscopic simulations | p. 92 |
Cellular automata | p. 94 |
Agents, players and games | p. 95 |
Disorder-generated complexity | p. 96 |
Information, entropy and selection | p. 101 |
Complexity and information | p. 101 |
The information entropy of a history | p. 104 |
Scaling rules and selection | p. 106 |
Time-dependent properties of information. Information entropy and thermodynamic entropy | p. 115 |
Dynamical and statistical properties of time histories. Large deviations, fluctuation theorems | p. 117 |
Further information measures. Dimensions and Lyapunov exponents revisited | p. 120 |
Physical complexity, algorithmic complexity, and computation | p. 124 |
Summing up: towards a thermodynamics of complex systems | p. 128 |
Communicating with a complex system: monitoring, analysis and prediction | p. 131 |
Nature of the problem | p. 131 |
Classical approaches and their limitations | p. 131 |
Exploratory data analysis | p. 132 |
Time series analysis and statistical forecasting | p. 135 |
Sampling in time and in space | p. 138 |
Nonlinear data analysis | p. 139 |
Dynamical reconstruction | p. 139 |
Symbolic dynamics from time series | p. 143 |
Nonlinear prediction | p. 148 |
The monitoring of complex fields | p. 151 |
Optimizing an observational network | p. 153 |
Data assimilation | p. 157 |
The predictability horizon and the limits of modeling | p. 159 |
The dynamics of growth of initial errors | p. 160 |
The dynamics of model errors | p. 164 |
Can prediction errors be controlled? | p. 170 |
Recurrence as a predictor | p. 171 |
Formulation | p. 172 |
Recurrence time statistics and dynamical complexity | p. 176 |
Extreme events | p. 180 |
Formulation | p. 180 |
Statistical theory of extremes | p. 182 |
Signatures of a deterministic dynamics in extreme events | p. 185 |
Statistical and dynamical aspects of the Hurst phenomenon | p. 191 |
Selected topics | p. 195 |
The arrow of time | p. 195 |
The Maxwell-Boltzmann revolution, kinetic theory, Boltzmann's equation | p. 196 |
First resolution of the paradoxes: Markov processes, master equation | p. 200 |
Generalized kinetic theories | p. 202 |
Microscopic chaos and nonequilibrium statistical mechanics | p. 204 |
Thriving on fluctuations: the challenge of being small | p. 208 |
Fluctuation dynamics in nonequilibrium steady states revisited | p. 210 |
The peculiar energetics of irreversible paths joining equilibrium states | p. 211 |
Transport in a fluctuating environment far from equilibrium | p. 214 |
Atmospheric dynamics | p. 217 |
Low order models | p. 218 |
More detailed models | p. 222 |
Data analysis | p. 223 |
Modeling and predicting with probabilities | p. 224 |
Climate dynamics | p. 226 |
Low order climate models | p. 227 |
Predictability of meteorological versus climatic fields | p. 230 |
Climatic change | p. 233 |
Networks | p. 235 |
Geometric and statistical properties of networks | p. 236 |
Dynamical origin of networks | p. 239 |
Dynamics on networks | p. 244 |
Perspectives on biological complexity | p. 247 |
Nonlinear dynamics and self-organization at the biochemical, cellular and organismic level | p. 249 |
Biological superstructures | p. 251 |
Biological networks | p. 253 |
Complexity and the genome organization | p. 260 |
Molecular evolution | p. 263 |
Equilibrium versus nonequilibrium in complexity and self-organization | p. 267 |
Nucleation | p. 268 |
Stabilization of nanoscale patterns | p. 272 |
Supramolecular chemistry | p. 274 |
Epistemological insights from complex systems | p. 276 |
Complexity, causality and chance | p. 277 |
Complexity and historicity | p. 279 |
Complexity and reductionism | p. 283 |
Facts, analogies and metaphors | p. 285 |
Color plates | p. 287 |
Suggestions for further reading | p. 291 |
Index | p. 321 |
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