Lars Ruthotto

MATH 516 - Numerical Analysis II

Instructor:
Prof. Lars Ruthotto
Syllabus:
The syllabus can be downloaded from here.
Material:
Additional course material will be made available using Blackboard.
Times:
TueTh 10:00 AM - 11:15 AM, Math & Science Center, Room W302
First day of classes: January 13, 2015
Last day of classes: April 23, 2015
Recess: March 9-13 (Spring break)
Prerequisites:
Math 515 - I will not review this material. You are expected to know it.
Topics:
Finding roots: Given some function f, find x such that f(x) = 0.
Optimization: For example, given an objective function f, solve min_x f(x)
Interpolation, splines best approximation, integration: For example, given some measurements y_1, y_2, ...,y_n at locations x_1,x_2,...,x_n, find a function p such that p(x_i) = y_i for all i.
Integration: Given some function f, approximate \int_a^b f(x) dx.
Ordinary differential equations (ODEs)
Literature:
No specific book is required for this course. Two excellent books you can use as references are:
A First Course in Numerical Methods, U. Asher and C. Greif, SIAM 2011
Scientific Computing with Case Studies, D.P. O'Leary, SIAM, 2009
Grades:
There will be several homework assignments / projects and a final project.
The final grade will be determined as:
50% homework, 25% midterm exam, 25% final exam
Homework:
Homework will be a combination of computing and analysis. Computing will be done using Julia or Matlab.
Solutions, results, and analysis should be submitted as a single, readable document. This document can either be sent to me electronically (as a pdf file), or you can give me a printed copy.
All codes used to generate results for the assignments have to be submitted electronically as a single .zip, .tar, or .tgz archive.
Important dates:
Midterm: to be scheduled
Final Exam: to be scheduled
Attendance:
Attendance is not required, but strongly encouraged.
If you miss a class, then you should get a copy of the notes from one of your classmates.
If you come to class, please do not disturb your fellow students and avoid using phones, computers, or leaving in the middle of a lecture.
Conduct:
All students must adhere to the provisions of the Graduate Student Conduct Code. For more information, see page 29 of the graduate student handbook.