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© 2016

Basic Concepts in Computational Physics

Benefits

  • Now with ready to use C++ program code available online

  • Contains heavily expanded chapters on molecular dynamics, PDEs, random generators, Monte Carlo applications, data analysis and data optimization

  • Presents deterministic methods are presented on a par with stochastic methods

  • Mathematically precise, but driven by the needs of physicists

  • Extensive appendices deepen the knowledge and present the mathematical basis

Textbook

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Benjamin A. Stickler, Ewald Schachinger
    Pages 1-13
  3. Deterministic Methods

    1. Front Matter
      Pages 15-15
    2. Benjamin A. Stickler, Ewald Schachinger
      Pages 17-30
    3. Benjamin A. Stickler, Ewald Schachinger
      Pages 31-52
    4. Benjamin A. Stickler, Ewald Schachinger
      Pages 53-61
    5. Benjamin A. Stickler, Ewald Schachinger
      Pages 63-83
    6. Benjamin A. Stickler, Ewald Schachinger
      Pages 85-101
    7. Benjamin A. Stickler, Ewald Schachinger
      Pages 103-116
    8. Benjamin A. Stickler, Ewald Schachinger
      Pages 117-129
    9. Benjamin A. Stickler, Ewald Schachinger
      Pages 131-138
    10. Benjamin A. Stickler, Ewald Schachinger
      Pages 139-156
    11. Benjamin A. Stickler, Ewald Schachinger
      Pages 157-180
  4. Stochastic Methods

    1. Front Matter
      Pages 181-181
    2. Benjamin A. Stickler, Ewald Schachinger
      Pages 183-195
    3. Benjamin A. Stickler, Ewald Schachinger
      Pages 197-209
    4. Benjamin A. Stickler, Ewald Schachinger
      Pages 211-223
    5. Benjamin A. Stickler, Ewald Schachinger
      Pages 225-246
    6. Benjamin A. Stickler, Ewald Schachinger
      Pages 247-270
    7. Benjamin A. Stickler, Ewald Schachinger
      Pages 271-295

About this book

Introduction

This new edition is a concise introduction to the basic methods of computational physics. Readers will discover the benefits of numerical methods for solving complex mathematical problems and for the direct simulation of physical processes.


The book is divided into two main parts: Deterministic methods and stochastic methods in computational physics. Based on concrete problems, the first part discusses numerical differentiation and integration, as well as the treatment of ordinary differential equations. This is extended by a brief introduction to the numerics of partial differential equations. The second part deals with the generation of random numbers, summarizes the basics of stochastics, and subsequently introduces Monte-Carlo (MC) methods. Specific emphasis is on MARKOV chain MC algorithms. The final two chapters discuss data analysis and stochastic optimization. All this is again motivated and augmented by applications from physics. In addition, the book offers a number of appendices to provide the reader with information on topics not discussed in the main text.


Numerous problems with worked-out solutions, chapter introductions and summaries, together with a clear and application-oriented style support the reader. Ready to use C++ codes are provided online.

Keywords

Textbook Computational Physics Textbook Numerical Physics Calculation Deterministic Methods Calculation Stochastic Methods Monte Carlo Method Data Analysis Experiment Numerical Solution Equation

Authors and affiliations

  1. 1.Faculty of PhysicsUniversity of Duisburg-EssenDuisburgGermany
  2. 2.Graz University of TechnologyInstitute of Theoretical and Computational PhysicsGrazAustria

About the authors

Ewald Schachinger is a Professor in the Institute for Theoretical and Computational Physics in Graz University of Technology, Austria. 

Benjamin A. Stickler is a Professor in the Institute of Theoretical Physics at the University of Duisburg-Essen, Germany. 

Bibliographic information

Industry Sectors
Energy, Utilities & Environment