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.
Home page url
Download or read it online for free here:
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.
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.
by Stefan Weinzierl - arXiv
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 and variance-reducing techniques is introduced.
by Michael P. Brenner - Harvard University
This is an introduction to mathematical methods for solving hard mathematics problems that arise in the sciences -- physical, biological and social. Our aim therefore is to teach how computer simulations and analytical calculations can be combined.