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Natural complexity : a modeling handbook /
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 explorati...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Princeton, NJ :
Princeton University Press,
[2017]
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| Colección: | Primers in complex systems.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Part 1. What Is complexity?: Complexity Is not simple
- Randomness Is not complexity
- Chaos Is not complexity
- Open dissipative systems
- Natural complexity
- About the computer programs listed in this book
- Part 2. Iterated growth: Cellular automata in one spatial dimension
- Cellular automata in two spatial dimensions
- A zoo of 2-D structures from simple rules
- Agents, ants, and highways
- Emergent structures and behaviors
- Part 3. Aggregation: Diffusion-limited aggregation
- Numerical implementation
- A representative simulation
- A zoo of aggregates
- Fractal geometry
- Self-similarity and scale invariance
- Part 4. Percolation: Percolation in one dimension
- Percolation in two dimensions
- Cluster sizes
- Fractal clusters
- Is it really a power law?
- Criticality
- Part 5. Sandpiles: Model definition
- Numerical implementation
- A representative simulation
- Measuring avalanches
- Self-organized criticality
- Part 6. Forest fires: Model definition
- Numerical implementation
- A representative simulation
- Model behavior
- Back to criticality
- The pros and cons of wildfire management
- Part 7. Traffic jams: Model definition
- Numerical implementation
- A representative simulation
- Model behavior
- Traffic jams as avalanches
- Car traffic as a SOC system?
- Part 8. Earthquakes: The Burridge-Knopoff model
- Numerical implementation
- A representative simulation
- Model behavior
- Predicting real earthquakes
- Part 9. Epidemics: Model definition
- Numerical implementation
- A representative simulation
- Model behavior
- Epidemic self-organization
- Small-world networks
- Part 10. Flocking
- Model definition
- Numerical implementation
- A behavioral zoo
- Segregation of active and passive flockers
- Why you should never panic
- Part 11. Pattern formation: Excitable systems
- The hodgepodge machine
- Numerical implementation
- Waves, spirals, spaghettis, and cells
- Spiraling out
- Spontaneous pattern formation
- Part 12. Epilogue: A hike on slickrock
- Johannes Kepler and the unity of nature
- From lichens to solar flares
- Emergence and natural order
- Into the abyss: your turn
- Part A. Basic elements of the Python programming language: Code structure
- Variables and arrays
- Operators
- Loop constructs
- Conditional constructs
- Input/output and graphics
- Part B. Probability density functions: A simple example
- Continuous PDFs
- Some mathematical properties of power-law PDFs
- Cumulative PDFs
- PDFs with logarithmic bin sizes
- Better fits to power-law PDFs
- Part C. Random Numbers and walks: Random deviates
- The classical random walk
- Random walk and diffusion
- Part D. Lattice computation: Nearest-neighbor templates
- Periodic boundary conditions
- Random walks on lattices.