AM-Applied Mathematics

AM 209 Foundations of Scientific Computing

Covers the fundamental aspects of scientific computing for research. Introduces algorithmic development; programming (including the use of compilers, libraries, debugging, optimization, and code publication); computational infrastructure; and data-analysis tools. Students gain hands-on experience through practical assignments. Basic programming experience will be assumed. May be taught in conjunction with AM 129 some quarters. (Formerly AMS 209.)

Credits

5

Requirements

Enrollment is restricted to graduate students; undergraduates may enroll by permission of the instructor.

AM 213 Numerical Solutions of Differential Equations

Teaches basic numerical methods for numerical linear algebra and, thus, the solution of ordinary differential equations (ODEs) and partial differential equations (PDEs). Covers LU, Cholesky, and QR decompositions; eigenvalue search methods (QR algorithm); singular value decomposition; conjugate gradient method; Runge-Kutta methods; error estimation and error control; finite differences for PDEs; stability, consistency, and convergence. Basic knowledge of computer programming is needed. (Formerly AMS 213.)

Credits

5

Instructor

Hongyun Wang, Pascale Garaud, Nicholas Brummell, Qi Gong

Requirements

Enrollment is restricted to graduate students or permission of instructor.

AM 290A Topics in Mathematical and Computational Biology

Focuses on applications of mathematical and computational methods with particular emphasis on advanced methods applying to organismal biology or resource management. Students read current literature, prepare critiques, and conduct projects.

Credits

2

Requirements

Enrollment is restricted to graduate students.

Repeatable for credit

Yes