Math 575A-- Numerical Analysis
Fall 2008 University of Arizona




Classroom: MATH 501, Tuesday and Thursday 11AM-12:15PM

Instructor:

Robert Indik
email: indik@math.arizona.edu (most reliable contact method)
telephone: 621-4599, office location: Math East 249A
Office Hours (subject to change): Monday at 10AM and Friday at 3PM in Math east 249a, Thursday 2PM in math 202 (U.D. tutoring)

Listserv and D2L:

Please subscribe to the MATH575 mailing list/list server.  This should be a convenient forum for questions on material and homework.  The name of the list is "MATH575"  follow this link to get instructions for subscribing. Solutions and grades will be posted using the university of Arizona D2L server.

Texts:

You may want to buy these directly from SIAM, if you accept the  free student membership in SIAM (Society for Industrial and Applied Mathematics) that you can get as a student at an affiliated University, the discount for the books is significant.  It is also a great organization.
Click on the links below to go to the publisher's website.

Numerical Linear Algebra by Trefethen and Bau, SIAM Press
  We will be using this text for the first 8-9 weeks of the semester.  The first 5 lectures in the book are available online at http://www.comlab.ox.ac.uk/nick.trefethen/text.html

We have used
Computer Methods for Ordinary Differential Equations and Differential-Algebraic Equations by Uri M. Ascher and Linda R. Petzold, SIAM Press
in the past, and most likely will this year as well starting near the end of this semester and for 575b-- a definite decision will be made shortly. 

We will also make some use of the online notes that Prof. Restrepo created.

Grading:

We will have a midterm and a final, and (mostly) weekly homework assignments.  In the second half of the semester we will be using MATLAB quite heavily, and those homework assignments can be completed either as printed output, or as posted web pages.  Homework will be assigned each class, and will be due before 4PM the Tuesday following the class during which it is assigned. I will try to keep this web page up to date with homework assignments.   Homework counts as 50% of the grade, the midterm as 20% and the final as 30%.

You will need to have access to a computer where you can run MATLAB.  Students in the Math department can access MATLAB on the departmental Linux machines.  All university students are entitled to accounts on the u.arizona.edu cluster, and can run MATLAB remotely on that cluster.  In addition, the MS Windows machines in the Info commons also have a limited number of MATLAB licenses which should be accessible from all of the stations.  If you have your own computer, you can take advantage of the Matlab site license, and install the software. Please see the instructions at https://sitelicense.arizona.edu/matlab/index.php .

Students entering this class are expected to have a solid background in Linear Algebra, in Calculus and Ordinary Differential Equations.  It is quite helpful to have some computer programming experience, especially in MATLAB.

Exams  Note changed date for midterm

We will have a single midterm exam and a final exam.  Our final is scheduled for Tuesday December 16th 11-1 in Math 501.  Our midterm is  scheduled for Tuesday October 28th during the regular class meeting.

Homework (subject to change)

HW1, Due Tuesday September 2: 
  Lecture 1:  1.1, 1.3, 1.4
  Lecture 2:  2.1, 2.3, 2.4, 2.6
HW2, Due Tuesday September 9:
  Lecture 3: 3.2 3.4 3.5
  Lecture 4:  4.1  4.4 4.5
  Matlab introduction: Do part I only of the homework assignment found by following this link
HW3 Due Tuesday September 16:
  Lecture 5: 5.2, 5.3, 5.4
  Lecture 6: 6.1, 6.2, 6.3
HW4 Due Tuesday September 23:
  Lecture 7: 7.1 7.3 7.5
  Lecture 8: 8.2, 8.3 + implement and test the CGS algorithm (Alg. 7.1) and compare its results to those of Alg. 8.1
           Matlab work must include listings of your functions, as well as some evidence of your tests of the programs and discussion of the errors.
HW5 Due Tuesday September 30:
   Lecture 9: 9.1, 9.2
     and use your programs for  Algorithm 7.1 and Algorithm 8.1 to duplicate experiments 2 and 3 from Lecture 9.  Produce a plot Like figure 9.1 and discuss the meaning of the results you compute.
   Lecture 10: 10.1, 10.2, 10.4
HW6 Due Tuesday October 7:
    Lecture 11: 11.1 11.2 11.3
    Lecture 12: 12.1 12.2 12.3
HW7 Due Thursday October 16:
    Lecture 13: 13.1 13.2 13.3
    Lecture 14:  14.1 14.2
HW8 Due Thursday October 23: 
    Lecture 15: 15.1 abcd only 15.2 ab (not c)
    Lecture 16: 16.1, 16.2     
HW9 Due Thursday October 30: 
    Implement and test Algorithm 17.1 (use random triangular matrices to test and verify that the algorithm is producing results that are as accurate as the theorems predict.)
HW10 Due Tuesday Nov 4
    Lecture 18: 18.1, 18.2
HW11 Due Thursday Nov 13
    Lecture 19: 19.1, 19.2
    Lecture 20: 20.1, 20.2
    Lecture 21: 21.2, 21.6
HW12 Due Thursday Nov 20
    Lecture 22: 22.1, 22.3
    Lecture 24: 24.3, 24.4
    Lecture 25: 25.1
HW13 Due Tuesday Dec 2
   Click here for the assignment
HW14 Due Tuesday  Dec 9
   Problems from Ascher+Petzold book
   Chapter 2: 2.3, 2.4
   Chapter 3: 3.2, 3.4
 

Syllabus

Below is a syllabus for the first semester.

Part I: Numerical Linear Algebra (following Trefethen and Bau):
Review of Linear Algebra
Fundamentals:

 Matrix Vector Multiplication
Orthogonal Vectors and Matrices
Norms
The Singular Value Decomposition

QR Factorization and Least Squares

Projectors
QR Factorization
Gram-Schmidt Orthogonalization
Householder Triangularization
Least Squares Problems

Conditioning and Stability

Conditioning and Condition Numbers
Floating Point Arithmetic
Stability
Stability of Householder Triangularization
Stability of Back Substitution
Conditioning of Least Squares Problems
Stability of Least Squares Algorithms

Systems of Equations

Gaussian Elimination
Pivoting

Eigenvalues

Eigenvalue problems
Overview of Eigenvalue Algorithms

Iterative Methods

Overview of Iterative Methods


Part II: Computer Methods for Ordinary Differential Equations (following Ascher and Petzold)
Background in ODEs
Initial Value Problems

Problem stability

Basic Methods and Stiffness

Forward Euler
Convergence, Accuracy, Consistency and 0-Stability
Absolute stability
Stiffness and Backward Euler
A-stability
Trapezoid method