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.
Home page url
Download or read it online for free here:
(multiple PDF files)
by T. H. Pulliam - NASA
Implicit finite difference schemes for solving two dimensional and three dimensional Euler and Navier-Stokes equations will be addressed. The methods are demonstrated in fully vectorized codes for a CRAY type architecture.
by Richard Fitzpatrick
The purpose of the text is to demonstrate how computers can help deepen our understanding of physics and increase the range of calculations which we can perform. These lecture notes are writen for an undergraduate course on computational physics.
by Matthias Troyer - ETH Zurich
Contents: Introduction; The Classical Few-Body Problem; Partial Differential Equations;The classical N-body problem; Integration methods; Percolation; Magnetic systems; The quantum one-body problem; The quantum N body problem; and more.
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.