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 Matthias Bolten - John von Neumann Institute for Computing
This work is focused on the application of multigrid methods to particle simulation methods. Particle simulation is important for a broad range of scientific fields, like biophysics, astrophysics or plasma physics, to name a few.
by Rubin H Landau, Manuel J Paez, Cristian Bordeianu - Wiley-VCH
This 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.
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.