Scientific Computing
G22.2112-001/G63.2043
Graduate Division
Computer Science/Mathematics
Spring 2001

Instructor. Prof. Yu Chen, Warren Weaver Hall (Ciww), Room 1126. Tel: 998-3285, yuchen@cims.nyu.edu

Class Mailing List. g22_2112_001_sp01@cs.nyu.edu subscribe to mailing list
There is also an email-based interface; you can get info about using it by sending a message with just the word `help' as subject or in the body, to: g22_2112_001_sp01-request@cs.nyu.edu

Basic Course Information
Homework and project schedule

Class Time.
Lecture: 7:10 p.m.-9:00 p.m., Thur., room 101, Warren Weaver Hall (Ciww)
First meeting: Thursday, January 18.
Last day of class: Thursday, April 26.
Spring break: March 12--17; no class on March 15.
Number of lectures: 14

Office Hours. 4:00 p.m. - 6:00 p.m. Thursday, and by appointment.
Prerequisite. multivariate calculus, linear algebra, and programming with Matlab.
Required Text. Numerical Methods Using Matlab, by G. Lindfield and J. Penny, Prentice Hall, 2nd Edition, 1999; available at the university bookstore.

Syllabus. The course will cover basic principles and useful algorithms essential for numerical applications in the physical and biological sciences, engineering and finance. It is intended for students familiar with a particular application area but not necessarily with numerical computing. Students learn techniques for problem solving by implementing Matlab programs. We will consider the following topics:

  1. General concepts in numerical calculations - stability, accuracy
  2. Numerical linear algebra
  3. Solution of nonlinear equations
  4. Numerical differentiation and integration
  5. Initial and boundary value problems for differential equations
  6. Data fitting and optimization.
  7. Monte Carlo Methods.
Assignments and Grading. There will be a number of homework assignments, most involving the computer programming in Matlab. The grade will be based on the following two aspects of your homework:
  1. The writeup, in English, discussing the results and answering the questions.
  2. Output and/or graphics, carefully chosen to be illustrative without taking too much paper.

Reference Texts.

  1. Scientific computing, an introductory survey, Michael T. Heath
  2. A survey of numerical mathematics, David M. Young
  3. An introduction to Numerical analysis, G. Strang, G. J. Fix
  4. Analysis of numerical methods, E. Isaacson, H. Keller
  5. Numerical methods, G. Dahlquist, A. Bjorck

yuchen@cims.nyu.edu (Yu Chen)
Last modified: January 16, 2001