Computational Methods for Physics

Presenting mathematical techniques for physical problems, this textbook is invaluable for undergraduate students in physics.

Joel Franklin (Author)

9781107034303, Cambridge University Press

Hardback, published 23 May 2013

420 pages, 107 b/w illus. 264 exercises
24.9 x 17.3 x 2.3 cm, 0.98 kg

'Joel Franklin's approach in this text is very much that of the physicist, in that he takes great pains to demonstrate the range of physical problems to which each computational technique might be applied before introducing the numerical method itself. … This book takes an original approach to teaching numerical methods to undergraduate physicists, and broadly succeeds in its task. There is a good range of material, and it is clearly presented at an appropriate level. It has great potential as a course text.' A. H. Harker, Contemporary Physics

There is an increasing need for undergraduate students in physics to have a core set of computational tools. Most problems in physics benefit from numerical methods, and many of them resist analytical solution altogether. This textbook presents numerical techniques for solving familiar physical problems where a complete solution is inaccessible using traditional mathematical methods. The numerical techniques for solving the problems are clearly laid out, with a focus on the logic and applicability of the method. The same problems are revisited multiple times using different numerical techniques, so readers can easily compare the methods. The book features over 250 end-of-chapter exercises. A website hosted by the author features a complete set of programs used to generate the examples and figures, which can be used as a starting point for further investigation. A link to this can be found at www.cambridge.org/9781107034303.

1. Programming overview
2. Ordinary differential equations
3. Root-finding
4. Partial differential equations
5. Time dependent problems
6. Integration
7. Fourier transform
8. Harmonic oscillators
9. Matrix inversion
10. The eigenvalue problem
11. Iterative methods
12. Minimization
13. Chaos
14. Neural networks
15. Galerkin methods
References
Index.

Subject Areas: Physics [PH], Mathematics & science [P]