# An Introduction to Computational Physics

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## An Introduction to Computational Physics

Thoroughly revised for its second edition, this advanced textbook provides an introduction to the basic methods of computational physics, and an overview of progress in several areas of scientific computing by relying on free software available from CERN. The book begins by dealing with basic computational tools and routines, covering approximating functions, differential equations, spectral analysis, and matrix operations. Important concepts are illustrated by relevant examples at each stage.

The author also discusses more advanced topics, such as molecular dynamics, modeling continuous systems, Monte Carlo methods, genetic algorithm and programming, and numerical renormalization. It includes many more exercises. This can be used as a textbook for either undergraduate or first-year graduate courses on computational physics or scientific computation.

It will also be a useful reference for anyone involved in computational research. The first half of the book deals with basic computational tools and routines, covering differential equations, spectral analysis and matrix operations.

- An Introduction to Computational Physics.
- An Introduction to Computational Physics, 2nd Edition.
- Submission history!
- Das Ladendesign als Erfolgskomponente der Ladengestaltung (German Edition).
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- Tao Pang-An Introduction to Computational Physics-Cambridge University Press (2006);
- Introduction to Computational Physics for Undergraduates - Books - IOPscience.

Important concepts are illustrated by relevant examples at each stage. The author also discusses more advanced topics, such as Monte Carlo simulations, lattice gas methods, molecular dynamics and symbolic computing. The book includes many exercises, and it can be used as a textbook for senior undergraduate or first-year graduate courses on scientific computation. It will also be a useful reference for anyone involved in computational physics or related disciplines.

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Numerical methods for matrices.