An Introduction to Computational Physics
eBook - PDF

An Introduction to Computational Physics

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

An Introduction to Computational Physics

Book details
Table of contents
Citations

About This Book

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.

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Yes, you can access An Introduction to Computational Physics by Tao Pang in PDF and/or ePUB format, as well as other popular books in Physical Sciences & Mathematical & Computational Physics. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Cambridge University Press
Year
2006
ISBN
9780511137945
Edition
2
Topic
Physical Sciences
Subtopic
Mathematical & Computational Physics

Table of contents

  1. Cover
  2. Half-title
  3. Title
  4. Copyright
  5. Dedication
  6. Contents
  7. Preface to first edition
  8. Preface
  9. Acknowledgments
  10. Chapter 1 Introduction
  11. Chapter 2 Approximation of a function
  12. Chapter 3 Numerical calculus
  13. Chapter 4 Ordinary differential equations
  14. Chapter 5 Numerical methods for matrices
  15. Chapter 6 Spectral analysis
  16. Chapter 7 Partial differential equations
  17. Chapter 8 Molecular dynamics simulations
  18. Chapter 9 Modeling continuous systems
  19. Chapter 10 Monte Carlo simulations
  20. Chapter 11 Genetic algorithm and programming
  21. Chapter 12 Numerical renormalization
  22. References
  23. Index