Computational Physics with Python
by Mark Newman
Publisher: University of Michigan 2012
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.
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(multiple PDF files)
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.
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.
by Adrian Feiguin - University of Wyoming
The purpose of this course is to introduce students to a series of paradigmatic physical problems in condensed matter, using the computer to solve them. The course will feel like a natural extension of introductory condensed matter.
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.