Eli Shlizerman, Guggenheim 418D
Email: shlizee [at] .uw.edu
Eli Shlizerman, Guggenheim 418D
Email: shlizee [at] .uw.edu
Edwin Ding, Guggenheim 407
Email: ding [at] amath.washington.edu
| Mikala Johnson, Harkirat Sohi, Chris Queitzsch, Genia Vogman, Aaron White and Marcus Ohlheiser- Guggenheim 407
Office Hours (Starting on the week of Oct. 12):
ICL room B027: M 3:30-8:00pm, W 11:30-1:30, 5:30-8:00pm, Th 9:30-10:30am, 2:30-3:30pm, F 2:30-4:30pm, room B022: T 2:00-6:00pm
GUG room 416 (Laptops): T 3:30-7:00pm, W 5:00-8:00pm
MGH room 030 (Terminal Server): T 10:00-12:00pm, W 4:30-8:00pm
|12/03||Sample questions for midterm 2 are available for download.|
|12/03||Homework 5 is available for download. Please start doing it as early as possible.|
|11/23||Question 3 in Homework 4 was changed to Questions 3,4. Please download the new version of the homework.|
|11/18||Homework 4 is available for download. Please start doing it as early as possible.|
|11/08||Homework 3 is available for download. Please start doing it as early as possible.|
|10/30||Sample questions for midterm are available for download.|
|10/15||Homework set 2 is now available online for you to download. You will be able to submit it to scorelator from the beginning of next week.|
|10/12||TA office hours start this week. You are more than welcome to come and ask questions. Please check the times of the office hours before you come, as these might change frequently.|
|10/11||Scorelator login details were sent.|
|10/9||You will receive login details for the Scorelator submissions by 10/11 (or before) once the course mailing list is finalized. Please check that a valid email address is listed in the course records.|
|10/7||Examples of Matlab codes are available online. See links at the appropriate syllabus sections.|
Schedule and HomeworkCourse Notes: amath301
|First day of classes||Wednesday, September 30|
|Homework#1||due Thursday, October 15 at 3 a.m.||Homework #1|
|Homework#2||due Thursday, October 29 at 3 a.m.||Homework #2|
|Midterm 1||Friday, November 6||Sample|
|Veteran's Day||Wednesday, November 11||no classes|
|Homework#3||due Thursday, November 19 at 3 a.m.||Homework #3|
|Thanksgiving Break||Friday, November 27||no classes|
|Homework#4||due Thursday, December 3 at 3 a.m.||Homework #4|
|Homework#5||due Thursday, December 10 at 3 a.m.||Homework #5|
|Midterm 2||Friday, December 11||Sample|
|Last day of classes||Friday, December 11|
Homework Submission and GradingHomework will be submitted and graded on-line. You have up to five (5) attempts per homework to get everything correct. If everything is correct the first time a homework is submitted, you will receive a 100% for that homework. If something is not correct, then you must fix it and re-submit the homework. Your highest submitted homework grade will be your final grade for that particular homework.
Remember that the submission checks your answers and compares (anti-cheat) against the MATLAB codes of others in this class and those of past years.
LATE HOMEWORK WILL NOT BE ACCEPTED.
Your course grade will be calculated by weighing the Homework, Midterm 1, and Midterm 2 in the proportions 60%, 20%, and 20%, respectively. Homework problem sets will be assigned roughly bi-weekly. Four highest graded homework will constitute 60% of your final grade. There will also be two one-hour-long midterms for 20% and 20% or your grade respectively.
The test schedule is as follows:
Midterm 1: Friday, November 6, 2009 (20% - 1 hour)
Description and ObjectivesThis course is intended to provide an introduction to the use of computers to solve scientific and engineering problems. Various computational approaches to solve mathematical problems, such as solution of a set of linear equations, curve fitting, solution of differential equations and more (see syllabus) will be presented. The approaches will be covered along with a discussion of their limitations, eventually providing a mathematical judgment in selecting tools to solve scientific problems. MATLAB will be used as the primary environment for numerical computation. Overview of MATLAB's syntax, code structure and algorithms will be given.
Although the subject matter of Scientific Computing has many aspects that can be made rather difficult, the material in this course is an introduction to the field and will be presented in a simple as possible way. Theoretical aspects will be mentioned throught the course, but more complicated issues such as proofs of relevant theorems/schemes will not be presented. Applications will be emphasized.
PrerequisitesMATH 125 or MATH 135
MATLAB on campusThere is MATLAB access at the ICL lab on campus. You can access this also remotely by following the links to "terminal server".
Textbook and NotesThere is no text required for this course. Lecture notes written by Prof. Kutz (pdf) are available online and are the suggested text for the course.
We will also refer to parts of Numerical Computing with MATLAB, by Cleve Moler available online. There are a variety of MATLAB help books available at the library. For further reading, books on Scientific Computing and Numerical Analysis are listed in the referrences section in the lecture notes.
A student version of MATLAB (available at the UW bookstore) is recommended if you do not have access to ICL or have a personal Laptop and would like to run MATLAB on it.
- (1) MATLAB Introduction: Program Algorithms, Architecture and Visualization
- Introduction to MATLAB: Matrices and Vectors
- MATLAB Logic, Loops and Iterations (examples)
- Plotting and Saving Data (examples)
- Algorithm Development and Code Architecture (examples)
- Subroutines and Function Calls (examples)
- Visualization: Advanced 2D Plotting, Advanced 3D Plotting, Movies and Animation (examples)
- (2) Linear Systems:
- Solving Linear Systems and LU Decomposition
- Iterative Methods for Linear Systems (examples)
- Eigenvalue Problems
- (3) Curve Fitting, Interpolation, Splines:
- Least Square Fits (examples)
- Polynomial Fits and Splines (examples)
- Implementation of Curve Fits (examples)
- Statistical Description of Data
- (4) Numerical Differentiation and Integration:
- Numerical Differentiation (examples)
- Numerical Integration (examples)
- Implementation of Differentiation and Integration
- (5) Differential Equations, Ordinary Differential Equations (ODEs):
- Initial Value Problems: Basic Time-Stepping Schemes (examples)
- Error Analysis for Time-Stepping
- The Dynamical Systems Approach to ODEs
- Two Point Boundary Value Problems: Shooting Method (extra notes)
- Implementing Shooting (examples)
- Two Point Boundary Value Problems: Direct Method
- Implementing the Direct Solve
- (6) Transforms and Spectral Analysis:
- The Fourier Transform
- Spectral Analysis and Applications of FFT
- (7) Differential Equations, Partial Differential Equations (PDEs):
- Basic Time and Space-Stepping Schemes
- Implementing Time and Space-Stepping Schemes
- Basic Methods Using Spectral Methods