Description

Book Synopsis
This advanced textbook, revised for its second edition, provides an introduction to the methods and tools of computational physics, and offers an overview of progress in scientific computing. Important concepts are illustrated with relevant step-by-step examples with exercises.

Trade Review
Review of the hardback: 'This is an excellent textbook for course on computational physics and scientific computation.' Zentralblatt MATH

Table of Contents
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.

An Introduction to Computational Physics

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    A Paperback by Tao Pang

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      View other formats and editions of An Introduction to Computational Physics by Tao Pang

      Publisher: Cambridge University Press
      Publication Date: 6/10/2010 12:00:00 AM
      ISBN13: 9780521532761, 978-0521532761
      ISBN10: 0521532760

      Description

      Book Synopsis
      This advanced textbook, revised for its second edition, provides an introduction to the methods and tools of computational physics, and offers an overview of progress in scientific computing. Important concepts are illustrated with relevant step-by-step examples with exercises.

      Trade Review
      Review of the hardback: 'This is an excellent textbook for course on computational physics and scientific computation.' Zentralblatt MATH

      Table of Contents
      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.

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