by Angus MacKinnon
Publisher: Imperial College London 2002
Number of pages: 48
This course aims to give the student a thorough grounding in the main computational techniques used in modern physics. This is not a text in computing science, nor in programming. It focuses specifically on methods for solving physics problems.
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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 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 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 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.