Math 449

Numerical Applied Mathematics, Fall 2017

Basic Information

Instructor: Ari Stern
Email: stern@wustl.edu
Office: Cupples I, 211B
Office Hours: TuTh 2-3pm

Homework Assignments

Problem sets will be posted approximately biweekly, and will be collected at the beginning of class on the due date. You are encouraged to discuss the homework with your fellow students and to collaborate on problems, but your final write-up must be your own. Please make sure that your solutions are written clearly and legibly.

Changming Xu (c.xu@wustl.edu) is responsible for grading the homework assignments.

Lectures

Lectures will be held MWF 3-4pm, in Crow 206. The first class will be on Monday, August 28, and the last will be on Friday, December 8. Class will be canceled for Labor Day (Monday, September 4), Fall Break (Monday, October 16), and Thanksgiving Break (Wednesday, November 22, and Friday, November 24).

Exams

There will be one in-class midterm exam on Friday, October 13. The final exam will be held on Thursday, December 14, from 6-8pm.

Grading

Grades will be based on a weighted average of homework (40%, lowest score dropped), midterm exam (20%), and final exam (40%).

Textbook

The text for this course is An Introduction to Numerical Analysis, by Endre Süli and David Mayers, published by Cambridge University Press. (Note: The Amazon Kindle eBook version of this text is not recommended, since the Kindle software does not always display mathematical formulas properly.)

Software

The programming component of this class is based on the Python programming language with the SciPy collection of numerical and scientific computing tools. No previous experience with either is assumed (although experience with some programming language is a prerequisite). This software is free and open source, and can be installed on your own computer.

The Anaconda Python Distribution is officially recommended for this course, and is available for Linux, Mac, and Windows.

Catalog Description

Computer arithmetic, error propagation, condition number and stability; mathematical modeling, approximation and convergence; roots of functions; calculus of finite differences; implicit and explicit methods for initial and boundary value problems; numerical integration; numerical solution of linear systems, matrix equations, and eigensystems; Fourier transforms; optimization. Various software packages may be introduced and used. Prerequisites: CSE 131 or 200 (or other computer background with permission of the instructor); Math 217 and 309.

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