Introduction to Computational Physics and Monte Carlo Simulations of Matrix Field Theory
by Badis Ydri
Publisher: arXiv 2015
Number of pages: 350
This book is divided into two parts. In the first part we give an elementary introduction to computational physics consisting of 21 simulations which originated from a formal course of lectures and laboratory simulations. The second part is much more advanced and deals with the problem of how to set up working Monte Carlo simulations of matrix field theories which involve finite dimensional matrix regularizations of noncommutative and fuzzy field theories, fuzzy spaces and matrix geometry.
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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.
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 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 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.