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 Johannes Grotendorst, Stefan Bluegel, Dominik Marx - NIC
This volume focuses on the application of electronic structure calculations and dynamical simulation techniques covering aspects of solid state physics, surface and nanoscience, chemical reactions and dynamics, magnetism and electron transport, etc.
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 Stefan Weinzierl - arXiv
These lectures given to graduate students in high energy physics, provide an introduction to Monte Carlo methods. After an overview of classical numerical quadrature rules, Monte Carlo integration and variance-reducing techniques is introduced.
by Morten Hjorth-Jensen - University of Oslo
These notes should train you in an algorithmic approach to problems in the sciences, represented here by the unity of three disciplines, physics, mathematics and informatics. This trinity outlines the emerging field of computational physics.