Math 170A (Introduction to Numerical Analysis: Linear Algebra)

Course Topics: Introduction to Numerical Analysis: Linear Algebra
Instructor: Prof. Michael Holst (5161 AP&M, mholst@ucsd.edu; Regular Office Hours: TBA)
Term: Fall 2021
Lecture: 2:00p-2:50p MWF (See Canvas for Room, Zoom Links, other info)
TA: See the Canvas Page
Discussion: See the Canvas Page

Main Class webpage: http://ccom.ucsd.edu/~mholst/teaching/ucsd/170a_f21/index.html

Canvas/Zoom:
    In 2021-2022 the course 170ABC will be based around the use of Canvas, which will be the place to find all materials for the course, information about lectures and office hours, including Zoom links, as well as any recorded lectures or materials that might be provided as part of the course. Note that this means that this webpage I created on my UCSD website for the course will not be updated after the first day of class; please use your Canvas account for the class going forward.

    Also note that there are two different sections of 170A in Fall 2021 taught by two different instructors. Although 170ABC is not a "coordinated" course like some of the lower division courses, the two sections of 170A in Fall 2021 will use the same book, cover roughly the same material, go at roughly the same pace, and have the same general types of assessments throughout the quarter. Therefore, the student experience in each section of 170A should be fairly similar.
Textbook(s):
    In order to use the best available resources for the course, we will be using different books for each of the three quarters of 170ABC. For 170A in Fall 2021, we will be using the following book:

  • Fundamentals of Matrix Computations.
    D. S. Watkins,
    Second Edition, John-Wiley & Sons, Inc., New York, 620 pages, 2002.

    This second edition of the book is open access, and a PDF file for each individual chapter of the book can be downloaded from the Wiley website [ here ]. The full book as a single PDF file can be downloaded for free by UCSD faculty and students; just log in from UCSD or through a UCSD VPN and the Wiley page will have an extra link to a downloadable single PDF file for the entire book.

    There are two other editions of this book: a 1993 first edition and a 2012 third edition. The first edition is also available electronically, but it is substantially different from the second edition and has more typographic errors, so we will stay away from that first edition. The third edition is not available electronically, but will be available at the bookstore if you want to have a physical copy. It has only minor differences from the second edition, and since the second edition is freely available, I will be using only the second edition listed above for my lecture notes and any homeworks that I assign from the book.
Printable Syllabus: A printable version of this webpage can be found [ here ].


CATALOG DESCRIPTION: 170A. INTRODUCTION TO NUMERICAL ANALYSIS: LINEAR ALGEBRA (4)
Analysis of numerical methods for linear algebraic systems and least squares problems. Orthogonalization methods. Ill conditioned problems. Eigenvalue and singular value computations. Knowledge of programming recommended.
Prerequisites: MATH 18 or MATH 20F or MATH 31AH, and MATH 20C or MATH 31BH. Students who have not completed the listed prerequisites may enroll with consent of instructor.


COURSE INFORMATION: Many of the advances of modern science have been made possible only through the sophisticated use of computer modeling. The mathematical foundation of the computer modeling techniques now used in all areas of mathematics, engineering, and science is known as numerical analysis. The Math 170ABC series at UCSD provides an introduction to the exciting field of numerical analysis, which is also sometimes referred to as computational mathematics or scientific computing. Professor Holst has a passion for this particular area of mathematics, and much of his published research is in this area. Math 170A deals primarily with the development and analysis of algorithms (or, numerical methods) for solving problems arising in linear algebra.


OTHER COURSE INFORMATION: Please see the Canvas page for other information about this course.