Class webpage: http://www.math.umd.edu/~dlevy/classes/amsc661/index.html All course information and announcements (including assignments) will be posted on the course webpage. You should check it before each class.
Instructor: Prof. Doron Levy
Contact Information:
Email: dlevy@math.umd.edu.
My office is on the first floor of the Math Building, room 1105.
Phone: 301-405-5140. (from any campus phone dial 55140).
Webpage: http://www.math.umd.edu/~dlevy
Office Hours: TTh 1:30-2 and by appointment.
Grader: Ming Zhong
Email: mzhong1@umd.edu
Lecture Classroom: MATH 0105
Lecture: TTh 2-3:15pm
Prerequisites: Knowledge of numerical analysis and partial differential equations. Programming assignments will be in Matlab.
Textbook: Larsson & Thomee, Partial differential equations with numerical methods, Springer text in applied mathematics series. An Amazon link (a paperback for $46).
Grading Policy: Homework 70%, project 30%
HW Policy: Homework will be assigned on the web. Homework is due in class (before class starts) on the day noted. Homework should not be left in my mailbox or under my door. Late homework will not be graded.
Project: Your task will be to write a summary of an article, implement the algorithm it discusses, and compare it with techniques discussed in class. Topics for the project will be posted online in Mid March. The project will be due by the end of April.
Exams: There will be no exams
Academic Integrity: All work that you submit must be your own. You are welcomed to discuss the material with each other in a general way, but you may not consult any one else's written work, program drafts, computer files, etc. Any marked similarity in form or notation between submissions with different authors will be regarded as evidence of academic dishonesty so protect your work. You must cite any reference you use and clearly mark any quotation or close paraphrase that you include. Such citation will not lower your grade, although extensive quotation might. Homework should be done individually.
Additional Resources:
There is a detailed bibliography in the textbook that I recommend you look at. In addition, a partial list of good resources includes:
- Morton & Mayers, Numerical solution of PDEs
- Van Loan, Introduction to scientific computing
- Quarteroni & Saleri, Scientific computing with Matlab
- O'leary, Scientific computing with case studies
- Atkinson, an introduction to numerical analysis
- Suli & Mayers, an introduction to numerical analysis
- Isaacson & Keller, analysis of numerical methods
- Hesthaven, Gottlieb, & Gottlieb, spectral methods for time-dependent problems
- Gottlieb & Orszag, numerical analysis of spectral methods