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Math 567 : Finite difference methods for differential equations

This course will introduce you to methods for solving partial differential equations (PDEs) using finite difference methods. The course content is roughly as follows :

The course will have roughly 6 homework projects and two midterms.

Send me an e-mail

Please send me an e-mail at so that I can compile an e-mail list for the class. At the very least, include a subject header that says "Math 567". You may leave the message area blank, if you wish, or send me a short note about what you hope to get out of this course.

Basic course information

Instructor Prof. Donna Calhoun
Office Mathematics 241A
Time Tuesday/Thursday 9:00-10:15
Place Math 124
Office Hours Thursday 1:15-2:45
Prerequesites Math 465 (Introduction to Numerical Methods) or equivalent course

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Required textbook and other resources

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We will stick the following schedule as much as possible.

Week #1 (Aug. 22)
Tuesday --  Introduction to finite difference approximations
Thursday --  Finite difference approximations; Computing truncation errors
Codes written or demonstrated in class :
Some useful or interesting links
Thomas Algorithm for solving tridiagonal systems (Thomas Algorithm)
Anaconda for scientific computing in Python (Anaconda Python)
Project Jupyter for Jupyter notebooks (Jupyter)

Week #2 (Aug. 28)
Tuesday --  Chapter 1 : Designing finite difference stencils
Codes written or demonstrated in class :
Thursday --  Boundary value problems (2.1-2.5)

Week #3 (Sept. 4)
Tuesday --  Stability, Consistency and Convergence (2.6-2.10)
Thursday --  Green's Functions and max-norm stability (2.11)

Week #4 (Sept. 11)
Tuesday --  Mathworks on-campus visit: River Front Hall, Rm. 101 (9:00-11:00)
Some useful or interesting links
More information and to register (Mathworks visit)
Thursday --  Work through details of Section 2.11 on stability of BVP problem

Week #5 (Sept. 18)
Tuesday --  Neumann boundary conditions (2.12-2.13)
Thursday --  Variable coefficient problems (2.15); Direct methods for 2d elliptic problems (3.1-3.3)
Codes written or demonstrated in class :

Week #6 (Sept. 25)
Tuesday --  Splitting methods : Jacobi and Gauss Seidel (4.1 - 4.2)
Lecture slides :
Iterative Methods - Splitting techniques  (pdf)
Thursday --  Steepest descent methods; Conjugate Gradient (4.3)
Codes written or demonstrated in class :

Week #7 (Oct. 2)
Tuesday --  Matrix-vector multiply in 2d
Codes written or demonstrated in class :
Thursday --  Chapter 5 : Initial Value Problems; Basic numerical methods; One step methods

Week #8 (Oct. 9)
Tuesday --  Terminology (one-step; multi-step, and so on); Truncation error
Thursday --  Runge-Kutta Methods

Week #9 (Oct. 16)
Tuesday --  Midterm #1
Thursday --  Multi-step methods; Chapter 6 : Absolute stability

Week #10 (Oct. 24)

Week #11 (Oct. 31)

Week #12 (Nov. 7)

Week #13 (Nov. 14)

Week #14 (Nov. 28)

Week #15 (Dec. 5)

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Homework assignments

Homework assignments are due Thursday, at the start of class.

Homework #1

Due Sept. 7

Assignment :
Other resources :
test_errors.m  -- Errors needed for problem 1
Updates to homework :
 --  (8/30/2017) Fixed bug in problems 2(b) and 2(c).

Homework #2

Due Sept. 22

Assignment :
Updates to homework :
 --  (9/11/2017) Re-ordered the problems; minor re-wording of question in problems 5 and 6
 --  (9/17/2017) Problem #6 : N=8*2^n, i.e N is increasing powers of 2

Homework #3

Due Oct. 5

Assignment :
Other resources :
Updates to homework :
 --  (9/27/2017) Changed problems 1 and 4 slightly; Fixed minor typos.
 --  (10/2/2017) Right hand side in Problem 3(c) should be 3x1 (not 4x1)

Homework #4

Due Nov. 3

Assignment :

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We will have two midterms and (possibly) a final exam

Midterm #1 Date: TBA

Midterm #2 Date: TBA

Final Date: TBA

You can find the Final Exam calendar here.

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Grading policy

Homework will count for 60% of your final grade, and the rest will be made up with exams and a possible final or final project.

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