Georg Stadler

Courant Institute of Mathematical Sciences

New York University

Fall 18: MATH-UA 0252-001: Numerical Analysis

Instructor:

Georg Stadler, Warner Weaver Hall Office #1111

Lectures: Tuesday and Thursday 11:00-12:15pm, class starts on September 6

Location: Warren Weaver Hall #312

Office Hours: Wed. 10-11:30am or by appointment-please email.

Recitation: Friday 11:00-12:15pm, WWH #201, TA: Karina Koval

If you email me about the class, please start your subject line with [NA], or use this link.

We will use Piazza for communication and organization. If you are registered for this class you will receive an invitation to join the course on Piazza at the beginning of the semester. Otherwise please email me and I will add you.

Content:

We will cover classical topics in Numerical Analysis: The solution of linear and nonlinear equations, conditioning, least squares, numerical computation of eigenvalues, interpolation, quadrature, and numerical methods for ODEs. The course will have a focus on the analysis of numerical methods, but also require you to use numerical software (Matlab, Python, or Julia). If you are not familiar with any of these tools, the recitation will give an introduction to Matlab during the first weeks. Additionally, I recommend to work through one of the books listed below before the course starts or in the first weeks of the semester.

Grading policy:

30% Homework, 10% Quizzes, 25% Midterm, 35% Final.

Literature:

Endre Suli and David Mayers (2003): An Introduction to Numerical Analysis. Cambridge University Press, 2003. PDF available from campus

Further reading:

Ridgeway Scott (2011): Numerical Analysis, Princeton University Press.

Gander, W., Gander, M.J., & Kwok, F. (2014). Scientific Computing - An Introduction Using Maple and MATLAB. Texts in Computation Science and Engineering [Series, Vol. 11]. New York, NY: Springer-Verlag.

Moler, C: (2004) Numerical Computing with Matlab, SIAM.

Classes and Material:

Date Topics Book Sections Slides and notes Code Examples
9/6 fixed point iteration 1.1, 1.2 Slides (PDF), Notes (PDF)
9/11 fixed point convergence 1.2, 1.3 Notes (PDF) fixed point example (.m)
9/13 stability of fixed points, Newton method 1.4 Notes (PDF) Newton method example (.m)
9/18 Newton convergence proof, secant, bisection, global behavior of Newton 1.5-1.7 Notes (PDF) Newton ex1 (.m), Newton ex2 (.m), Newton ex3 (.m), global Newton behavior plot (.png)
9/20 Gaussian elimination 2.1,2.2 Notes (PDF) timings of LA operations (.m)
9/25 LU factorization, pivoting 2.3,2.4
9/27 computational work, conditioning 2.6,2.7

Homework assignments:

*) Assignment 1: [ PDF, TEX and figure for TEX file], due Sep 25.


© G.St.