Modeling and Simulation in Python
by Allen B. Downey
Publisher: Green Tea Press 2017
Number of pages: 206
Modeling and Simulation in Python is an introduction to physical modeling using a computational approach. Taking a computational approach makes it possible to work with more realistic models than what you typically see in a first-year physics class, with the option to include features like friction and drag.
Home page url
Download or read it online for free here:
by T. H. Pulliam - NASA
Implicit finite difference schemes for solving two dimensional and three dimensional Euler and Navier-Stokes equations will be addressed. The methods are demonstrated in fully vectorized codes for a CRAY type architecture.
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 Jeffrey R. Chasnov - Harvey Mudd College
This course consists of both numerical methods and computational physics. MATLAB is used to solve various computational math problems. The course is primarily for Math majors and supposes no previous knowledge of numerical analysis or methods.
by Adrian Feiguin - University of Wyoming
The purpose of this course is to introduce students to a series of paradigmatic physical problems in condensed matter, using the computer to solve them. The course will feel like a natural extension of introductory condensed matter.