by Michael P. Brenner
Publisher: Harvard University 2010
Number of pages: 250
The goal of this course is to give a modern introduction to mathematical methods for solving hard mathematics problems that arise in the sciences -- physical, biological and social. Our aim therefore is to teach, within a broad suite of examples, how computer simulations and analytical calculations can be effectively combined. In this course, we will begin with problems that are simple polynomial equations and first order differential equations -- and slowly march our way towards the study nonlinear partial differential equations.
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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 Volker Springel - arXiv
These are lecture notes about high performance computing and numerical modelling in 43rd Saas Fee Advanced Course winter school, specifically covering the basics of numerically treating gravity and hydrodynamics in the context of galaxy evolution.
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 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.