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 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 Rubin H Landau, Manuel J Paez, Cristian Bordeianu - Wiley-VCH
This text surveys many of the topics of modern computational physics from a computational science point of view. Its emphasis on learning by doing (assisted by many model programs), as with 2nd Edition, but with new materials as well as with Python.
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 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.