Computational Problems for Physics Courses Throughout the Curriculum

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. 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. A
new book Computational Problems for Physics with Guided Solutions Using Python extends those problems and demos with
the aim of having computation supplement a variety of existing courses. The text
includes a large number of worked problems with fully guided solutions in
Python, with other languages (Java, C, Fortran, Maple, and Mathematica)
available on the Web.
Chapters: 1. Computational Basics for Physics; 2. Data Analytics for Physics; 3.
Classical & Nonlinear Dynamics; 4. Wave Equations & Fluid Dynamics; 5.
Electricity & Magnetism; 6. Quantum Mechanics; 7. Thermodynamics &
Statistical Physics; 8. Biological Models: Population Dynamics & Plant Growth; 9.
Additional Entry-Level Problems; Appendix: Python Codes