Overview

Instructor

Holden Lee

Email

holee at math dot duke dot edu

Office Hours Location

Gross 352

Office Hours

Mon. 4:30-5:30pm Fri. 2-3pm (starting 1/24) See Piazza for adjustments.

Lectures

MW 3:05-4:20 (Physics 227)

Syllabus

Available here.

Website

Shortlink: tiny.cc/math361s20.

Piazza page

Math 361S

Textbook

Uri Ascher & Chen Greif, A First Couse in Numerical Methods Excerpts from Cleve Moler’s book Numerical Methods in MATLAB (free online).

Announcements regarding distance learning

• The syllabus has been updated with changes in the class format and policies.
• Lecture videos will be recorded and made available on Sakai. You are asked to watch the videos before class time, and are encouraged to ask questions and discuss the lecture on the Piazza page. Class time will be devoted to discussion and to working out examples. We will experiment with the format, but the general plan is to (a) first devote some time to QA on the relevant material, (b) work out practice problems, and (c) show demos involving code.
• All homework is to be submitted on Sakai. I will not check my mailbox.
• Access virtual class meetings and office hours through Sakai using Zoom. To access the meeting, log on to Sakai and click on "Zoom Meetings" on the left, then click "Join" beside the meeting. Feel free to email me to schedule meetings at other times; these will also be conducted using Zoom. (Let me know if you have any issues with using it.)
• Exam II has been postponed to April 13. It will likely be structured as a take-home exam.
• Let me know ASAP about any situation I should be aware of as I plan the remainder of the semester. This includes but is not limited to:
  • Not being available at the regular class time (e.g. because of time zone differences)
  • Lack of textbook access
  • Lack of internet/microphone/webcam

Description

Development of numerical techniques for accurate, efficient solution of problems in science, engineering, and mathematics through the use of computers. Linear systems, nonlinear equations, optimization, interpolation, numerical integration, differential equations, error analysis.

Prerequisites

Solid understanding of fundamental concepts from linear algebra is essential, including linearity, solving linear systems, eigenvalues and eigenvectors. A course in multi-variable calculus (e.g. Math 212) is also required. Experience with ordinary differential equations is recommended, but not necessary.

Grading

Grades will be assigned based on an assessment of your performance on homework, midterm exams, and a final project. The components will be weighted (roughly) as follows:

• Weekly homework (30%)
• Two midterm exams (20% each)
• Final project (30%)
• Participation (Up to 10% extra may be given for participation.)
• There is no final exam for this course.

Homework

• Homework will be assigned (roughly) weekly and will typically be due the following Wednesday. Consult the schedule for due dates.
• No late homework will be accepted, barring exceptional circumstances as per Duke policy.
• Working and studying in groups is encouraged (you will get much more out of doing homework if you discuss it with others!). However, you should write your own solutions to each problem in your own words.
• Solutions should be complete arguments; the process by which you arrive at the solution is far more important than a correct answer. Assertions should be supported by computed data and code when it is needed.
• Homework pages must be stapled together with clearly readable work. Solutions should be in the same order as in the list of assigned problems.

Computational work

• Some homework problems will require writing and running code. The official programming language for this course is Matlab, but you may write your code in Matlab, Python, or Julia.
• Collaboration is encouraged but the code you submit should be your own, which includes not copy-pasting code from other sources. Avoid looking up code online because it is difficult to un-see it when writing your own.

Ethics

Students are expected to follow the Duke Community Standard. If a student is found responsible for academic dishonesty through the Office of Student Conduct, the student will receive a score of zero for that assignment. If a student’s admitted academic dishonesty is resolved directly through a faculty-student resolution agreement approved by the Office of Student Conduct, the terms of that agreement will dictate the grading response to the assignment at issue.