Prof. Gilbert Strang, Massachusetts Institute of Technology
- Wednesday 4/22/2009 at 9AM
- DCL, Room 2240
I would like to discuss (together with the audience!) how we can go forward with teaching computational science and engineering. It is a fascinating and creative subject that combines applied mathematics with scientific computing. How can we present both of those essential parts? The need to move beyond older courses in engineering mathematics is widely recognized. But a pure software course misses the foundations for understanding new problems. Combining analysis with computational science and engineering is truly powerful.
I will describe a course we have developed at MIT to address these issues. My goal in this course is for each lecture to discuss a model problem and a code to solve it. This course is popular with engineering students and their departments, who want exposure to ideas and also to software.
The main sections of the course are applied linear algebra (notice this beginning!), differential equations, finite differences and finite elements, Fourier methods, analytical methods, large sparse systems, and optimization. The starting point is to understand the second difference matrices (entries −1, 2, −1) that appear everywhere in scientific computing and simulation.