Course information¶
Instructor¶
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Office: Lewis 328
netid for email: rjl (but please ask questions on the discussion board)
Office hours:
In Lewis 328: W, Th 12:00 - 1:00
On GoToMeeting: M, W 7:00 - 8:00pm (Pacific). See the Canvas page for link and access code
Or usually available to talk after class, or make an appointment.
TA: Kenan Li
Office hours:
Both on GoToMeeting and in Lewis 129: T, W 4:00-5:00pm (Pacific). See the Canvas page for link and access code
Class meeting times¶
MWF 2:30 - 3:20 pm in LOW 216.
Videos and online students¶
This course will be streamed and available as Panopto videos on the class Canvas page. On-campus students may also watch the videos and this may be useful to review material or if you have to be out of town one day. However, on-campus students are generally expected to attend class and participate in discussions to improve the experience for everyone.
Online students, please see the additional Information for online students.
Canvas page¶
Registered students can view grades and other materials on the Canvas page
Grading¶
Homework: 60%, midterm: 15%, final exam: 25%
See Homework for more information and due dates.
Late homework: Homework will generally be due Thursday evenings at 11:00pm to a Canvas dropbox. You may turn in an assignment up to 24 hours late with a reduction of 10% for tardiness. After that homework will not be accepted unless you have made arrangements in advance due to special circumstances.
There will be 6 homework assignments plus in-class midterm and final exams.
The midterm will be Wednesday Februry 12, in class.
The Final Exam will be Tuesday March 17, 2020 from 2:30 - 4:20pm, also in the usual classroom.
NOTE: Due to the coronavirus, the in-class final exam has been replaced by a Take-home final exam.
Online students must arrange proctors in advance, or else take the exams in the classroom.
Recommended Background¶
Prerequisite: Either AMath 584, AMath 581, or permission of instructor. Some past experience in numerical linear algebra will be assumed, along with basic understanding of ordinary and partial differential equations.
Programming experience is also expected, e.g. in Matlab. Python and Jupyter notebooks will be used for many demonstrations and sample codes. See Python and Jupyter for some links to tutorials and documentation and Matlab vs. Python for comments on what to use for homework.
Textbook¶
R. J. LeVeque Finite Difference Methods for Ordinary and Partial Differential Equations, Steady State and Time Dependent Problems, SIAM, 2007.
The book webpage contains links to a tar file of matlab scripts and latex files.
The book webpage also lists some errata. Please look this over since there are some typos in the book.
Note: You can get a 30% discount if you buy the book direct from SIAM and you are a member. Student membership is free for UW students!
This text is also available online as an ebook. You should be able to access this link from a UW computer. Or if you are off-campus, you can gain access by using the UW library off-campus proxy.