Computational Physics With Python
by Eric Ayars
Publisher: California State University, Chico 2013
Number of pages: 194
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; Least-Squares Fitting.
Download or read it online for free here:
by Angus MacKinnon - Imperial College London
This course aims to give the student a thorough grounding in the main computational techniques used in modern physics. This is not a text in computing science, nor in programming. It focuses specifically on methods for solving physics problems.
by Johan Hoffman, Claes Johnson
Computational foundation of thermodynamics based on deterministic finite precision computation without resort to statistics. A new 2nd Law without the concept of entropy is proved to be a consequence of the 1st Law and finite precision computation.
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 Franz J. Vesely - University of Vienna
The essential point in computational physics is the systematic application of numerical techniques in place of, and in addition to, analytical methods, in order to render accessible to computation as large a part of physical reality as possible.