Lecture site:	Remote. Videos are made available on Canvas.
Discussion sessions	175 A01 43577: Thursday 5:00pm-5:50pm, remote 275 A01 43668: Thursday 5:00pm-5:50pm, remote Meeting ID: 929 6367 9144
Final Exam time and place	Remotely, June 10th, 2021, 11:30am-2:29pm
Instructor	Martin Licht Email: mlicht AT ucsd DOT edu Office Hours: Monday, Wednesday, Friday, 5:00pm-5:50pm Office Hour Meeting ID: 929 6367 9144
Section(s)	43577, 43668
Credit Hours:	4 units
Course content	Mathematical background for working with partial differential equations. Survey of finite difference, finite element, and other numerical methods for the solution of elliptic, parabolic, and hyperbolic partial differential equations. (Formerly MATH 172; students may not receive credit for MATH 175/275 and MATH 172.) Graduate students will do an extra paper, project, or presentation, per instructor.
Formal prerequesite	MATH 174 or MATH 274, or consent of instructor.
Required textbook	The textbook is PDEs with Numerical Methods, by Stig Larsson and Vidar Thomee. (Springer Texts in Applied Mathematics, Volume 45, ISBN 978-3-540-01772-1, hardcover, and 978-3-540-88705-8, softcover) Electronic Version
Homework information	Homework is due Sunday 11:59pm and submitted to Gradescope. The entry code for Gradescope is: X3EV68
Final exam	Final exam: June 10 Details of the final exam to be announced.
Academic Integrity	Every student is expected to conduct themselves with academic integrity. Violations of academic integrity will be treated seriously. See http://www-senate.ucsd.edu/manual/Appendices/app2.htm for UCSD Policy on Integrity of Scholarship.
Resources	The textbook for this lecture is: Stig Larsson and Vidar Thomee: Partial Differential Equations with Numerical Methods. ISBN-13 978-3-540-01772-1 Electronic Version The following textbook is recommend to supplement the lecture in regard to background in real and functional analysis: Lawrence C. Evans, Partial Differential Equations. Publisher's website The following textbooks are recommended to supplement the lectures in regard to numerical analysis: Åke Björck, Numerical Methods in Matrix Computations. Publisher's website Robert Plato, Concise Numerical Mathematics. Publisher's website Gerard Meurant, Computer Solution of Large Linear Systems. Publisher's website Golub, Van Loan, Matrix Computations. Publisher's website Trefethen, Bau Linear Algebra. Publisher's website Some information about floating point arithmetics: D. Goldberg, What every computer scientist should know about Floating-Point arithmetics. [Link] Information about Floating-Point numbers. [Link] E. Wallace Floating-Point Toy. [Link] Your experience in numerical linear algebra will greatly benefit from a solid background in linear algebra. Your instructor recommends the following textbook as a helpful reference: Serge Lang, Linear Algebra. Publisher's website Assorted links to additional material: Lloyd N. Trefethen, The Definition of Numerical Analysis. [Link] J. R. Shewchuk, The Conjugate Gradient Method without the Agonizing Pain. [Link]
Helpful links	Important academic dates for this academic year