Math 466/666

Fall 2020 University of Nevada Reno

466/666 NUMERICAL METHODS I (3+0) 3 credits

Instructor  Course                             Time            Room
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Eric Olson  Math 466/666 Numerical Methods I   TR 3:00-4:15pm  Remote

Course Information

Instructor:
Eric Olson
email:
ejolson at unr dot edu
Office:
Through Zoom and by appointment.
Homepage:
http://fractal.math.unr.edu/~ejolson/466/

Required Texts:

Anthony Ralston and Philip Rabinowitz, A First Course in Numerical Analysis, Second Edition, Dover, 1978.

Supplemental Texts on Numerical Methods:

Justin Solomon, Numerical Algorithms: Methods for Computer Vision, Machine Learning and Graphics, CRC Press, 2015.

David Kincaid and Ward Cheney, Numerical Analysis: Mathematics of Scientific Computing, 3rd Revised Edition, Pure and Applied Undergraduate Texts, American Mathematical Society, 2002.

R.W. Hamming, Numerical Methods for Scientists and Engineers, Second Edition (online).

Classic Texts on Numerical Methods:

Kendall Atkinson, An Introduction to Numerical Analysis, Second Edition, Wiley, 1989.

Eugene Isaacson, Analysis of Numerical Methods, Revised Edition, Dover Books on Mathematics, 1993.

Supplemental Texts on Computer Programming:

JTC1/SC22/WG14, C99 Programming Standard, ISO/IEC, 2007.

Simon Long, Learn to Code with C, MagPi, 2017.

Richard Smedley, Conquer the Command Line, MagPi, 2016.

Williamt Shots, The Linux Command Line, Creative Commons, 2019.

Classic Texts on Computer Programming:

Brian Kernighan, Dennis Ritchie, C Programming Language, 2nd Edition, Prentice Hall, 1988.

Brian Kernighan, Rob Pike, Unix Programming Environment, Prentice-Hall Software Series, 1984.

Information about Other Software:

Thomas Williams, Colin Kelley, Gnuplot 5.2: An Interactive Plotting Program, official documentation.

The Julia Project, The Julia 1.2 Language, official documentation.

Student Learning Outcomes

Upon completion of this course
  1. Students will be able to implement a numerical method to solve a nonlinear equation using the bisection method and Newton's method.

  2. Students will be able to solve linear systems using direct and iterative methods.

  3. Students will be able to construct interpolating functions.

Announcements

[09-Dec-2020] Prep Day

This is the study day after the last day of class and before the final exam.

[25-Aug-2020] First Day of Class

Details to be announced.

[02-Aug-2020] Julia

Julia is a free open-source software designed at MIT for performing matrix and vector computations similar to Matlab. This language is quickly becoming popular in science, technology, engineering and mathematics because it is easy to use and generally performs faster than Matlab. Click and install versions can be downloaded for Windows, macOS and Linux from the official Julia language website. If you try to download it over summer and encounter difficulties, please let me know.

[31-Jul-2020] Alternative Remote

This course was originally scheduled to be delivered in-person, but has moved to entirely online due to social distancing and capacity limitations. We will be using a combination of Zoom, WebCampus and other Internet resources which will be announced later. Luckly, this course will not include the additional $34 per credit online fee; however, please make sure you have a computer, suitable web camera and the Internet connection needed for online learning.

[16-Jul-2020] HPC and COVID-19

Here is an interview with Dr Kathy Yelick (the link plays only the part of the show that contains the interview) discussing computational techniques, problems and priorities in the analysis of the coronavirus epidemic.

[25-Jun-2020] Inspirational Video

Here is an inspirational video from the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory discussing the roles scientific computing and numerical methods are likely to play in the future as computers become more powerful.

Grading

     COVID-19 Training Quiz     5 points
     Written Quiz              30 points
     Computer Quiz             30 points
     Midterm                   50 points
     2 Homework Assignments    20 points each
     2 Programming Projects    30 points each
     In-class Lab Work         20 points
     Final Exam                70 points
    ------------------------------------------
                              305 points total
Exams and quizzes will be interpreted according to the following grading scale:
    Grade        Minimum Percentage
      A                 90 %
      B                 80 %
      C                 70 %
      D                 60 %
The instructor reserves the right to give plus or minus grades and higher grades than shown on the scale if he believes they are warranted.

Final Exam

The final exam is scheduled for Wednesday, December 16 from 2:30-4:30pm through alternative remote. Please make sure you have a web camera available for the final exam.

Equal Opportunity Statement

The Mathematics Department is committed to equal opportunity in education for all students, including those with documented physical disabilities or documented learning disabilities. University policy states that it is the responsibility of students with documented disabilities to contact instructors during the first week of each semester to discuss appropriate accommodations to ensure equity in grading, classroom experiences and outside assignments.

Academic Conduct

Bring your student identification to all exams. Work independently on all exams and quizzes. Behaviors inappropriate to test taking may disturb other students and will be considered cheating. Don't talk or pass notes with other students during an exam. Don't read notes or books while taking exams given in the classroom. You may work on the programming assignments in groups of two if desired. Homework may be discussed freely. If you are unclear as to what constitutes cheating, please consult with me.
Last Updated: Sun Aug 2 20:59:53 PDT 2020