Instructor: Dr. Manil Suri
- Dr. Manil Suri, Math/Psych 419, (410) 455-2311, firstname.lastname@example.org,
office hours: MW 3:30-4:30 or by appointment
- Lectures: MW 1-2:15, Math/Psych 401
- Text: An Introduction to Numerical Analysis by K. Atkinson (2nd edition)
- Syllabus: Chapters 1, 2 (2.1-2.3, 2.5, 2.10-2.11), 3 (3.1-3.2, 3.5, 3.6-3.8 briefly), 4 (4.1, 4.3-4.5), 5 (5.1-5.3, 5.7), 6 (6.1-6.5, time permitting). Parts of Chapters 7 and 8 may be covered as needed.
- Useful Reference Text: Numerical Analysis: Mathematics of Scientific Computing by Kincaid and Cheney.
- Prerequisites: CMSC 201, MATH 225, MATH 251, MATH 301 with a grade of C or better. You will need to have familiarity with a programming language (such as MATLAB) to be able to write your own code.
Overview and Goals
Problems encountered in mathematics courses such as Calculus generally can be solved by paper and pencil, and yield nice, “closed form” answers in the form of numerical values, functions or formulas. In real world applications, however, problems are seldom so well behaved. For instance, integrals may be difficult or impossible to compute exactly, differential equations may have solutions that can only be expressed as infinite series, and systems of nonlinear equations may not have any solutions that can be found by hand. Consequently, a large proportion of problems that mathematicians, engineers, scientists and other professionals “solve” are only done numerically, using computer power. Math 441 introduces you to various types of such computational methods that can be used to tackle an array of mathematical problems (several of which you will have encountered before in other courses). It therefore provides an introduction to the field of “scientific computing.”
A common characteristic of the methods mentioned above is that they are based on approximations of some sort: a numerical value may be replaced by a decimal expansion close to it, a function by a polynomial expansion, a problem by a “nearby” problem that is easier to solve. One of the key issues that we will learn in this course is how to analyze and control the resulting error in our computed answers. Our primary emphasis will be to gain an understanding of these methods through theoretical analysis.
We will also perform computer experiments in our quest to gain familiarity with these methods. Theoretical results are often “asymptotic” in nature – our goal will be to see whether these results are observed in practice. It is only through performing experiments that one can develop a “computational sixth sense” to decide when computer solutions are to be trusted and when not.
Although you are free to use other languages to write programs for assignments, you should at least have basic familiarity with MATLAB. (Note: You may wish to look into downloading the free software package “Octave” which is for the most part Matlab-compatible. However, you can access Matlab remotely on your home computer, using these directions.)
To summarize, the main goals of the course are:
- Learning computational methods that will solve problems (integration, differential equations, non-linear equations, etc) approximately
- Understanding, analyzing and assessing the errors in approximate solutions obtained through these methods
- Gaining experience in performing numerical computations
- Writing and using your own computational programs.
Tests and Homework
- HOMEWORK is an essential part of the course. It will consist of both computer and paper and pencil problems. There will also be one or two projects. Homework for sections completed in any given week (M-W) will be due the next Wednesday (unless otherwise noted). Homework assignments will be posted on Blackboard. NOTE: First hw will be due on Sep 12.
- TESTS will be given twice in the semester. The dates will be announced at least 2 weeks in advance.
- FINAL This will be cumulative. The final will be held on Wed, Dec 19 from 1-3 pm in our regular classroom.
- MAKE-UPS for tests will only be allowed under special circumstances with written documentation and prior approval if possible. If you miss something, contact me immediately (i.e. on that day) via e-mail (or phone).
- Homework: 25%, Project(s): 10%, Tests: 40%, Final: 25%
- Cut-offs: A: 90%, B: 80%, C: 65%, D: 55%
You are welcome to discuss problems with other students. However, work turned in has to be written up by you alone (no copying answers from one another). Similarly, any computer programs turned in must not be a copy from someone else. I will be enforcing these rules by asking some of you to demonstrate how you got your solutions (paper and pencil as well as computer problems).
Standard UMBC policy statement: By enrolling in this course, each student assumes the responsibilities of an active participant in UMBC’s scholarly community in which everyone’s academic work and behavior are held to the highest standards of honesty. Cheating, fabrication, plagiarism, and helping others to commit these acts are all forms of academic dishonesty, and they are wrong. Academic misconduct could result in disciplinary action that may include, but is not limited to, suspension or dismissal. To read the full Student Academic Conduct Policy, consult the UMBC Student Handbook, the Faculty Handbook, or the UMBC Policies section of the UMBC Directory.