Syllabus

 

The class presents and ties together important notions of computational mathematics for scientists and engineers. It sheds a second light on linear algebra and differential equations. The focus is not on any particular application -- many will be covered from mechanical to electrical systems, graphs, networks, etc. -- but rather on the common mathematical framework that underlies most of them. Both modeling and computation will be covered. The class is suitable for master students, advanced undergraduates, or anyone interested in building a foundation in CSE.


Topics:



Reference material

The class will closely follow the first four chapters of the book Computational Science and Engineering by Gil Strang. The book should be available at the Coop.

Chapters 5 through 8 of the book are normally covered in 18.086 (which is taught this term as well).

Prerequisites: Calculus, including derivatives, integrals, linear differential equations, complex numbers, and familiarity with the noble functions of mathematics (sin, cos, exp, log, etc.). Vectors and matrices, including elementary operations (mat-vec, mat-mat multiply, etc.), row reduction, linear (in)dependence of vectors, linear systems of equations. It helps, but is not necessary, to have taken a linear algebra class such as 18.06. The homework assignments will involve basic computer programming in the language of your choice (MATLAB recommended).

Who, when, and where

Date and Time: Tu-Th, 2:30-4:00, room 4-163.
Instructor: Alex Townsend Office hours: W 9:00-11:00, room E18-475.
Teaching assistants: Rik Sengupta and Vinoth Nandakumar Office hours: TBA

Quiz dates: Thursday 19th March, Tuesday 14th April, and Tuesday 12th May.
These will take place in 50-340!


Evaluation

40% homework, 60% three in-class quizzes.

The homework problem sets will consist of both theoretical questions (without going into too much proof!) and numerical questions. No late copy will be allowed, but the lowest score will be dropped. Due on Thursdays. Please use MATLAB or Julia notation to describe algorithms. Use of MATLAB or Julia for tedious calculations is encouraged, however you need to know how to do the basic algorithms taught in the course by hand (at least for small matrices) for the quizzes.

Turn in the homework during the class on the day it is due. (Dates below are subject to change.)

Turn in the homework during the class on the day it is due. (Dates below are subject to change.)



Previous year's websites