With new problems and codes, as well as from CP texts (Taylor & Francis, 2018)
2020: Appendix on General Relativity
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Chap 3: Classical & Nonlinear Dynamics  Full Table of Contents 

Physics courses too often include computation to illustrate physics, with little discussion of the underlying applied math and its commensurate level of precision and reliability. Yet a scientist should not believe a simulation's result if the computation behind it is not understood and reliable. The authors have spent over two decades thinking up computational problems and demonstrations for their Computational Physics texts and for conference tutorials and institutional talks. This book extends those problems and demos with the aim of having computation supplement a variety of existing courses.
The first two chapters review background materials used throughout the book, with other chapters organized by subject. Most problems are at an upperdivision undergraduate level, with a separate chapter aimed at entrylevel courses. The problems can be solved with whatever software the instructor prefers, with simple pseudocodes presented within the chapters. Full Python code listings are given at the end of each chapter, and are available online. The Python language is probably the easiest compiled language for students to use and with its family of packages comprises a veritable ecosystem for computing at all levels.