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