Computational physics Mark Newman, University of Michigan

Includes an index

Contents: Introduction -- Python programming for physicists -- Graphics and visualization -- Accuracy and speed -- Integrals and derivatives -- Solution of linear and nonlinear equations -- Fourier transforms -- Ordinary differential equations -- Partial differential equations -- Random processes and Monte Carlo methods -- Using what you have learned -- Appendices -- Index..

This book explains the fundamentals of computational physics and describes the techniques that every physicist should know, such as finite difference methods, numerical quadrature, and the fast Fourier transform. The book offers a complete introduction to the topic at the undergraduate level, and is also suitable for the advanced student or researcher. The book begins with an introduction to Python, then moves on to a step-by-step description of the techniques of computational physics, with examples ranging from simple mechanics problems to complex calculations in quantum mechanics, electromagnetism, statistical mechanics, and more