01 / Reading Guide
Reading Guide
Who this book is for
For undergraduates beginning computational physics after foundational mathematical and physical science courses. The book is designed for active use alongside a computer and can support an extended sequence with laboratory practice. It is particularly helpful when a student understands an analytical equation but has not yet learned how discretization, numerical error and data analysis determine the meaning of a computed answer.
Prerequisites
Calculus, basic differential equations and university mechanics. Some programming experience is useful, but practical computing tools are introduced through examples; expect to learn at a terminal as well as on paper.
What it covers
Computing fundamentals lead into kinematics, nonlinear maps, particle motion, electrostatics, diffusion, oscillators, the Schrödinger equation, random walks and Monte Carlo methods. The later statistical physics examples connect numerical experimentation with finite-size behaviour. C++ and Fortran presentations belong to the same work and should be selected according to the reader’s programming environment.
How to use it
Run a small supplied program and reproduce one figure before changing the model. Vary the time step, spatial resolution or sample size independently and record how the answer changes. Check conservation laws and compare with an analytically solvable limit. Separate implementation errors from approximation errors, keep simulation parameters with every output and explain whether a plotted feature persists under a convergence test.
Edition and sources
The author’s university site supplies complete books and code in several formats. This guide follows the 2016 second C++ edition under the stated CC BY-SA 4.0 book licence; software has its own GPL terms. Language variants and print volumes are counted as one work, without mixing their ISBNs.
