Two Approaches to Teaching Computational Physics
Computing in Science and Engineering
Antipredictable Sequences: Harder to Predict Than Random Sequences
Neural Computation
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From the Publisher:This course, intended for upper-division undergraduate or graduate students, was designed by W. Kinzel and G. Reents as a textbook in computational physics but may also serve as a supplement to courses in theoretical physics. It is an introduction to the solution of physical models by computer. The programs developed in this book are based on the modern computer languages Mathematica and C and are written for PCs as well as for workstations. 28 examples from different fields of physics are worked out, including chaos, fractals, the Hofstadter butterfly, phase transitions, Monte-Carlo simulations, percolation, polymers, combinatorial optimization, neural networks, and game theory. Detailed explanation of the algorithms and computer programs together with source files and graphics routines help the student gain thorough experience right from the start.