Introduction to Monte Carlo Methods
by Stefan Weinzierl
Publisher: arXiv 2000
Number of pages: 47
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 together with variance-reducing techniques is introduced. A short description on the generation of pseudo-random numbers and quasi-random numbers is given.
Home page url
Download or read it online for free here:
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 Mark Newman - University of Michigan
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.
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.
by Angus MacKinnon - Imperial College London
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.