Leseprobe
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Natural Complexity
Paul Charbonneau
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Naturwissenschaften, Medizin, Informatik, Technik / Naturwissenschaften allgemein
Beschreibung
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.
Kundenbewertungen
Local variable, Thermodynamic equilibrium, Discrete mathematics, Elastic collision, Quantity, Simulation, Percolation threshold, Probability, Free parameter, A New Kind of Science, Normal distribution, Random number generation, Python (programming language), Accuracy and precision, Irregular matrix, Emergence, Iteration, For All Practical Purposes, Variable (computer science), Log–log plot, Percolation, Langton's ant, Bifurcation diagram, Counterexample, Monte Carlo algorithm, Pseudorandomness, Calculation, Nonlinear system, Big O notation, Length scale, Statistical physics, Cluster labeling, Pattern formation, Parameter (computer programming), Symmetry breaking, Random sequence, Time series, Power law, Dimension, Order and disorder (physics), SIMPLE algorithm, Self-similarity, Backtracking, Periodic boundary conditions, NumPy, Random walk, Small-world network, Equation, Scale invariance, Sierpinski triangle, Scale-free network, Fractal dimension, Forest-fire model, Pseudorandom number generator, K-index, Pairwise, Correlation and dependence, Logistic map, Stochastic, Spontaneous symmetry breaking, Expected value, Magnetosphere, Idealization, Initial condition, Box counting, Computational physics, Histogram, Line segment, Critical phenomena, Complexity