An Introduction to Computational Physics pdf pdb 阿里云 极速 mobi caj kindle 下载

　　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.

Preface to first edition

Preface

Acknowledgements

1. Introduction

2. Approximation of a function

3. Numerical calculus

4. Ordinary differential equations

5. Numerical methods for matrices

6. Spectral analysis

7. Partial differential equations

8. Molecular dynamics simulations

9. Modeling continuous systems

10. Monte Carlo simulations

11. Genetic algorithm and programming

12. Numerical renormalization

References

Index

暂无相关内容，正在全力查找中

暂无出版社相关信息，正在全力查找中！

暂无相关书籍摘录，正在全力查找中！

在线阅读地址：An Introduction to Computational Physics在线阅读

在线听书地址：An Introduction to Computational Physics在线收听

在线购买地址：An Introduction to Computational Physics在线购买

暂无原文赏析，正在全力查找中！

书籍介绍

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.