- 11/20 - The Heat Equation and the Wave Equation
- 11/17 - Fourier Series
- 11/8 - Linear Differential Equations
- 11/3 - our annotated copy of Bretscher §4.1
- 11/3 - Linear Spaces
- 11/3 - Modeling Springs with Differential Equations
- 10/30 - Linearization from
*Differential Equations*by Blanchard, Devaney, and Hall - 10/30 - Bretscher "9.4"
- 10/25 - A Brief Introduction to the Matrix Exponential
- 10/25 - Modeling via Differential Equations from
*Differential Equations*by Blanchard, Devaney, and Hall - 10/23 - Modeling with Systems of Differential Equations
- 10/20 - Orthogonal Matrices, Symmetric Matrices and the Spectral Theorem
- 10/13 - Bretscher 4th edition §7.1
- 10/13 - Complex Numbers and solutions to practice problems
- 10/2 - Computing Determinants Using Minors
- 9/20 - Coordinates
- 9/11 - Linear Combinations and Linear Transformations
- 9/8 - Introduction to Linear Transformations
- 9/6 - "A mathematical rating system" by Roland Minton
- 8/30 - The Method of Elimination
- 8/30 - Basics of Vectors and Matrices
- 8/30 - Slides from introductory meeting
- 8/30 - Syllabus

- 11/1 - Here's a paper on using nonlinear dynamical systems to model zombification. (Although the paper is obviously just for fun, many of the models described are used to model actual epidemics!)
- 9/19 - Markov chains, which are introduced in Problem Set 6, #6,
have a huge range of applications. For example, they are used in
chemistry to model reactions, in economics to model asset pricing, and
in biology to model population processes. A less serious (but fun!)
application is to use this math to figure out which squares in the
game Monopoly are landed on most frequently.
Here are a couple of
*Scientific American*articles which explain more: "How Fair Is Monopoly?" and "Monopoly Revisited". You should see that the math here is basically the same as that in Problem Set 6, #6.The articles mention that "eigenvectors" are a fast way to do some of the computations; we'll be talking about those in a few weeks!

- 9/6 - Here's a nice intro to how Google uses linear systems, written by Jameel Al-Aidroos. If you're interested in learning more about Google PageRank, take a look at this article. It features a lot of ideas we'll be studying later in the semester.