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 Michael P. Brenner - Harvard University
This is an introduction to mathematical methods for solving hard mathematics problems that arise in the sciences -- physical, biological and social. Our aim therefore is to teach how computer simulations and analytical calculations can be combined.
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 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 Badis Ydri - arXiv
We give an elementary introduction to computational physics. We deal with the problem of how to set up working Monte Carlo simulations of matrix field theories which involve finite dimensional matrix regularizations of noncommutative field theories.