A New Kind of Science
A01=Paul Charbonneau
Accuracy and precision
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Age Group_Uncategorized
Author_Paul Charbonneau
automatic-update
Backtracking
Bifurcation diagram
Big O notation
Box counting
Calculation
Category1=Non-Fiction
Category=PH
Cluster labeling
Complexity
Computational physics
COP=United States
Correlation and dependence
Counterexample
Critical phenomena
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Dimension
Discrete mathematics
Elastic collision
Emergence
eq_bestseller
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
Equation
Expected value
For All Practical Purposes
Forest-fire model
Fractal dimension
Free parameter
Histogram
Idealization
Initial condition
Irregular matrix
Iteration
K-index
Langton's ant
Language_English
Length scale
Line segment
Local variable
Log-log plot
Logistic map
Magnetosphere
Monte Carlo algorithm
Nonlinear system
Normal distribution
NumPy
Order and disorder (physics)
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Pairwise
Parameter (computer programming)
Pattern formation
Percolation
Percolation threshold
Periodic boundary conditions
Power law
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Probability
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Pseudorandom number generator
Pseudorandomness
Python (programming language)
Quantity
Random number generation
Random sequence
Random walk
Scale invariance
Scale-free network
Self-similarity
Sierpinski triangle
SIMPLE algorithm
Simulation
Small-world network
softlaunch
Spontaneous symmetry breaking
Statistical physics
Stochastic
Symmetry breaking
Thermodynamic equilibrium
Time series
Variable (computer science)
Product details
- ISBN 9780691170350
- Weight: 595g
- Dimensions: 140 x 216mm
- Publication Date: 16 May 2017
- Publisher: Princeton University Press
- Publication City/Country: US
- Product Form: Paperback
- Language: English
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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.
Paul Charbonneau is professor of physics at the University of Montreal.
