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NATURAL COMPLEXITY. A MODELING HANDBOOK
Título:
NATURAL COMPLEXITY. A MODELING HANDBOOK
Subtítulo:
Autor:
CHARBONNEAU, P
Editorial:
PRINCETON UNIVERSITY PRESS
Año de edición:
2017
ISBN:
978-0-691-17035-0
Páginas:
376
51,50 € -10,0% 46,35 €

 

Sinopsis

This book provides a short, hands-on introduction to the science of complexity using simple computational models of natural complex systems-with models and exercises drawn from physics, chemistry, geology, and biology. By working through the models and engaging in additional computational explorations suggested at the end of each chapter, readers very quickly develop an understanding of how complex structures and behaviors can emerge in natural phenomena as diverse as avalanches, forest fires, earthquakes, chemical reactions, animal flocks, and epidemic diseases.

Natural Complexity provides the necessary topical background, complete source codes in Python, and detailed explanations for all computational models. Ideal for undergraduates, beginning graduate students, and researchers in the physical and natural sciences, this unique handbook requires no advanced mathematical knowledge or programming skills and is suitable for self-learners with a working knowledge of precalculus and high-school physics.

Self-contained and accessible, Natural Complexity enables readers to identify and quantify common underlying structural and dynamical patterns shared by the various systems and phenomena it examines, so that they can form their own answers to the questions of what natural complexity is and how it arises.

First published in 2017.

Paul Charbonneau is professor of physics at the University of Montreal.



Table of Contents
Preface xiii
1. Introduction: What Is Complexity? 1
1.1 Complexity Is Not Simple 1
1.2 Randomness Is Not Complexity 4
1.3 Chaos Is Not Complexity 10
1.4 Open Dissipative Systems 13
1.5 Natural Complexity 16
1.6 About the Computer Programs Listed in This Book 18
1.7 Suggested Further Reading 20
2 Iterated Growth 23
2.1 Cellular Automata in One Spatial Dimension 23
2.2 Cellular Automata in Two Spatial Dimensions 31
2.3 A Zoo of 2-D Structures from Simple Rules 38
2.4 Agents, Ants, and Highways 41
2.5 Emergent Structures and Behaviors 46
2.6 Exercises and Further Computational Explorations 47
2.7 Further Reading 50
3 Aggregation 53
3.1 Diffusion-Limited Aggregation 53
3.2 Numerical Implementation 54
3.3 A Representative Simulation 58
3.4 A Zoo of Aggregates 60
3.5 Fractal Geometry 63
3.6 Self-Similarity and Scale Invariance 73
3.7 Exercises and Further Computational Explorations 76
3.8 Further Reading 78
4 Percolation 80
4.1 Percolation in One Dimension 80
4.2 Percolation in Two Dimensions 83
4.3 Cluster Sizes 85
4.4 Fractal Clusters 98
4.5 Is It Really a Power Law? 98
4.6 Criticality 100
4.7 Exercises and Further Computational Explorations 102
4.8 Further Reading 104
5 Sandpiles 106
5.1 Model Definition 106
5.2 Numerical Implementation 110
5.3 A Representative Simulation 112
5.4 Measuring Avalanches 119
5.5 Self-Organized Criticality 123
5.6 Exercises and Further Computational Explorations 127
5.7 Further Reading 129
6 Forest Fires 130
6.1 Model Definition 130
6.2 Numerical Implementation 131
6.3 A Representative Simulation 134
6.4 Model Behavior 137
6.5 Back to Criticality 147
6.6 The Pros and Cons of Wildfire Management 148
6.7 Exercises and Further Computational Explorations 149
6.8 Further Reading 152
7 Traffic Jams 154
7.1 Model Definition 154
7.2 Numerical Implementation 157
7.3 A Representative Simulation 157
7.4 Model Behavior 161
7.5 Traffic Jams as Avalanches 164
7.6 Car Traffic as a SOC System? 168
7.7 Exercises and Further Computational Explorations 170
7.8 Further Reading 172
8 Earthquakes 174
8.1 The Burridge-Knopoff Model 175
8.2 Numerical Implementation 182
8.3 A Representative Simulation 184
8.4 Model Behavior 189
8.5 Predicting Real Earthquakes 193
8.6 Exercises and Further Computational Explorations 194
8.7 Further Reading 196
9 Epidemics 198
9.1 Model Definition 198
9.2 Numerical Implementation 199
9.3 A Representative Simulation 202
9.4 Model Behavior 205
9.5 Epidemic Self-Organization 213
9.6 Small-World Networks 215
9.7 Exercises and Further Computational Explorations 220
9.8 Further Reading 222
10 Flocking 224
10.1 Model Definition 225
10.2 Numerical Implementation 228
10.3 A Behavioral Zoo 235
10.4 Segregation of Active and Passive Flockers 240
10.5 Why You Should Never Panic 242
10.6 Exercises and Further Computational Explorations 245
10.7 Further Reading 247
11 Pattern Formation 249
11.1 Excitable Systems 249
11.2 The Hodgepodge Machine 253
11.3 Numerical Implementation 260
11.4 Waves, Spirals, Spaghettis, and Cells 262
11.5 Spiraling Out 266
11.6 Spontaneous Pattern Formation 270
11.7 Exercises and Further Computational Explorations 272
11.8 Further Reading 273
12 Epilogue 275
12.1 A Hike on Slickrock 275
12.2 Johannes Kepler and the Unity of Nature 279
12.3 From Lichens to Solar Flares 285
12.4 Emergence and Natural Order 288
12.5 Into the Abyss: Your Turn 290
12.6 Further Reading 291
A. Basic Elem