Computational Physics: Problem Solving with Computers
by Rubin H Landau, Manuel J Paez, Cristian Bordeianu
Publisher: Wiley-VCH 2012
Number of pages: 526
This upper-division text surveys many of the topics of modern computational physics from a computational science point of view. Its emphasis on learning by doing (assisted by many model programs), as with 2nd Edition, but with new materials as well as with Python.
Download or read it online for free here:
by Mark Newman - University of Michigan
The Python programming language is an excellent choice for learning, teaching, or doing computational physics. This page contains a selection of resources the author developed for teachers and students interested in computational physics and Python.
by Allen B. Downey - Green Tea Press
An introduction to physical modeling using a computational approach. Taking a computational approach makes it possible to work with more realistic models than what you typically see in a first-year physics class, such as friction and drag.
by K. P. N. Murthy - arXiv
An introduction to the basics of Monte Carlo is given. The topics covered include sample space, events, probabilities, random variables, mean, variance, covariance, characteristic function, chebyshev inequality, law of large numbers, etc.
by Eric Ayars - California State University, Chico
Contents: Useful Introductory Python; Python Basics; Basic Numerical Tools; Numpy, Scipy, and MatPlotLib; Ordinary Differential Equations; Chaos; Monte Carlo Techniques; Stochastic Methods; Partial Differential Equations; Linux; Visual Python; etc.