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 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 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 Werner Krauth - CNRS-Laboratoire de Physique Statistique
The author discusses the fundamental principles of thermodynamic and dynamic Monte Carlo methods in a simple light-weight fashion. The keywords are Markov chains, Sampling, Detailed Balance, A Priori Probabilities, Rejections, Ergodicity, etc.
by Johan Hoffman, Claes Johnson - Springer
In this book we address mathematical modeling of turbulent fluid flow, and its many mysteries that have haunted scientist over the centuries. We approach these mysteries using a synthesis of computational and analytical mathematics.