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Computational Physics with R provides a comprehensive introduction to computational methods in physics, designed for students and researchers who wish to use R as their primary programming environment. While computational physics is often taught with languages such as C++, Python, or Fortran, this book fills a unique gap by adopting R, a language widely known for statistical computing and data visualisation, and demonstrating its effectiveness in tackling core problems in physics. The book adopts a strongly pedagogical approach: it emphasizes step-by-step construction of algorithms, reproducible code, and guided exercises with fully worked solutions. The book is both a teaching resource and a reference for practical problem-solving in physics.
Key Features:
- First book on Computational Physics using the R programming language.
- The book can also be used as a thorough introduction to the R language for physicists.
- The book is accessible at an advanced undergraduate level.
- The book can be used both as introduction to fundamental Computational Physics and as reference to advanced Computational Physics.
- The book can be used as text book for a one- or two-semester courses on Computational Physics.
- Each section ends with a few recommended computing exercises and suggested computing projects. Solutions to both are included.
- Each chapter opens with learning objectives and closes with an end-of-chapter summary.
Preface
Author biography
Part I Introduction to computational physics and the R platform
1 Introduction to computational physics
2 Introduction to the R platform
Part II Core computational physics
3 Interpolation
4 Computation using matrices
5 Data fitting
6 Numerical solution of nonlinear equations
7 Differentiation and integration
8 Ordinary differential equations
Part III Computational physics with R
9 Monte Carlo methods
10 Differential equations with deSolve
11 An overview of machine learning
Part IV Appendices
Appendix A: Mathematical proofs
Appendix B: A short (and quick) introduction to matrices
Appendix C: Some statistical concepts and theory
Appendix D: The IEEE 754 standard for floating-point arithmetic
Appendix E: The IEEE standard to binary rounding
Appendix F: Legendre Polynomials
Appendix G: The eigenvalue problem in ordinary differential equations
Appendix H: List of functions in package comphy