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Table of contents

  1. Front Matter
    Pages i-xvii
  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 17-28
    3. Benjamin A. Stickler, Ewald Schachinger
      Pages 29-50
    4. Benjamin A. Stickler, Ewald Schachinger
      Pages 51-59
    5. Benjamin A. Stickler, Ewald Schachinger
      Pages 61-79
    6. Benjamin A. Stickler, Ewald Schachinger
      Pages 81-96
    7. Benjamin A. Stickler, Ewald Schachinger
      Pages 97-109
    8. Benjamin A. Stickler, Ewald Schachinger
      Pages 111-122
    9. Benjamin A. Stickler, Ewald Schachinger
      Pages 123-129
    10. Benjamin A. Stickler, Ewald Schachinger
      Pages 131-146
    11. Benjamin A. Stickler, Ewald Schachinger
      Pages 147-168
  4. Stochastic Methods

    1. Front Matter
      Pages 169-169
    2. Benjamin A. Stickler, Ewald Schachinger
      Pages 171-183
    3. Benjamin A. Stickler, Ewald Schachinger
      Pages 185-195
    4. Benjamin A. Stickler, Ewald Schachinger
      Pages 197-208
    5. Benjamin A. Stickler, Ewald Schachinger
      Pages 209-228
    6. Benjamin A. Stickler, Ewald Schachinger
      Pages 229-250
    7. Benjamin A. Stickler, Ewald Schachinger
      Pages 251-273
    8. Benjamin A. Stickler, Ewald Schachinger
      Pages 275-286
    9. Benjamin A. Stickler, Ewald Schachinger
      Pages 287-297
    10. Benjamin A. Stickler, Ewald Schachinger
      Pages 299-314
  5. Back Matter
    Pages 315-377

About this book

Introduction

With the development of ever more powerful computers a new branch of physics and engineering evolved over the last few decades: Computer Simulation or Computational Physics. It serves two main purposes:
- Solution of complex mathematical problems such as, differential equations, minimization/optimization, or high-dimensional sums/integrals.
- Direct simulation of physical processes, as for instance, molecular dynamics or Monte-Carlo simulation of physical/chemical/technical processes.
Consequently, the book is divided into two main parts: Deterministic methods and stochastic methods. Based on concrete problems, the first part discusses numerical differentiation and integration, and the treatment of ordinary differential equations. This is augmented by notes on the numerics of partial differential equations. The second part discusses the generation of random numbers, summarizes the basics of stochastics which is then followed by the introduction of various Monte-Carlo (MC) methods. Specific emphasis is on MARKOV chain MC algorithms. All this is again augmented by numerous applications from physics. The final two chapters on Data Analysis and Stochastic Optimization share the two main topics as a common denominator. The book offers a number of appendices to provide the reader with more detailed information on various topics discussed in the main part. Nevertheless, the reader should be familiar with the most important concepts of statistics and probability theory albeit two appendices have been dedicated to provide a rudimentary discussion.

Keywords

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

Authors and affiliations

  • Benjamin A. Stickler
    • 1
  • Ewald Schachinger
    • 2
  1. 1.Faculty of PhysicsUniversity of Duisburg-EssenDuisburgGermany
  2. 2.Institut für Theoretische und Computational PhysikGraz University of TechnologyGrazAustria

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-02435-6
  • Copyright Information Springer International Publishing Switzerland 2014
  • Publisher Name Springer, Cham
  • eBook Packages Physics and Astronomy
  • Print ISBN 978-3-319-02434-9
  • Online ISBN 978-3-319-02435-6
  • Buy this book on publisher's site