Fall 2021: CX4640 Numerical Analysis 1
Course Description
Introduction to fundamental algorithms and analysis of numerical methods commonly used by scientists, mathematicians, and engineers.
Prerequisites
- Linear and Discrete Mathematics (MATH 2602)
- Differential Equations (MATH 2403/2413)
- Intermediate-level expertise of Python, Matlab, Julia, Mathematica, C/C++, Fortran, or similar
Topics
- Finite precision computation, sources of error, stability, conditioning
- Linear systems of equations
- Linear least squares
- Eigenvalue problems
- Solution of nonlinear equations
- Optimization
- Interpolation and approximation
- Numerical differentiation and integration
- Numerical solution of ordinary differential equations
- Numerical solution of partial differential equations
Grading
Breakdown
- 5% Participation
- 10% Homework
- 25% Midterm 1 (take-home)
- 25% Midterm 2 (take-home)
- 35% Final project (take-home)
Letters
Your final grade will be assigned as a letter grade according to the following scale.
- A: 90-100%
- B: 80-89%
- C: 70-79%
- D: 60-69%
- F: 0-59%
Submission requirements of homework, midterms, and projects
- All documents must be submitted in PDF format.
- Submission must be fully typeset (Tex, Word, or whatever you prefer). No handwritten submissions are allowed.
- Submission must show all of your work.
- If a question asks “why?” or “what do you expect?” you must fully, clearly, and concisely justify your answer or reasoning. Stray justifications or comments that do not answer the question, or answer it incorrectly, will receive negative marks.
- All plots must be fully labeled (axes labels, legend labels, titles, and more as appropriate) and cast using appropriate scaling (i.e., log or linear plots) to make the solution as clear as possible.
- Solutions to any problems that require writing code should include a listing of that code.
Screenshots or images of your code are not appropriate.
Instead, copy the code into the document directly.
If the code is long, you can include it at the end of the document in an appropriately labeled appendix.
The program itself does not have to be submitted unless stated otherwise.
- All code submissions must have comments describing the purpose of each line.
Textbook
Michael Heath, Scientific Computing: An Introductory Survey (Revised Second Edition)
Course expectations and guidelines
University policy
Georgia Tech aims to cultivate a community based on trust, academic integrity, and honor.
Students are expected to act according to the highest ethical standards.
Any student suspected of cheating or plagiarizing on a quiz, exam, or assignment will be reported to the Office of Student Integrity, which will investigate the incident and identify the appropriate penalty for violations.
Collaboration policy
- Homework and midterms: These are to be completed on your own.
No collaboration is acceptable.
- Final project: Intellectual collaboration is acceptable, though all “hands on” work is to be your own.
This includes your code and your report.
Late assignments
Assignments submitted late are subject to a 20% penalty per day late.
Accommodations
If you are a student with learning needs that require special accommodation, contact the Office of Disability Services at (404) 894-2563 or their website, as soon as possible, to discuss your needs and to obtain an accommodations letter. Then, make an appointment with me as soon as possible to discuss your learning needs.
Supporting video resources
- Floating point numbers
- Linear algebra refresher
- Eigenvalues
- Least squares
- Numerical time integration
- Numerical integration and quadrature
- Differential equations refresher