Ay190 2013/14 Syllabus

Important Prerequisites:

In order to take this class you will need:

  • A laptop running Linux, MacOS X, or Windows, since we will be doing in class exercises.
  • If Windows: You will need a virtual machine that runs a flavor of Linux. We will prepare detailed instructions.
  • If Mac: You will need to install either MacPorts or HomeBrew and get the relevant python packages. Alternatively, you may also install linux a virtual machine.

Rules of Engagement

  • All work will be in Python (there will be an introduction to Python). Exceptions can be made for exceptionally computationally demanding problems and term projects.
  • All work must be submitted via git. You will learn how git works.
  • Your work must be document in the form of source code and a LaTeX writeup.
  • Each class will consist of about 30-45 minutes lecture and 45-60 minutes of work on the work sheets
  • You will work in teams of two, but everybody must hand in their own work.
  • You must come to class. Work sheets will not be made available online. If you really can't make it because of travel or sickness, we can email you the work sheet upon request.
  • No exams, but homework (completion of work sheets) and a term project
  • Passing grade: at least 50\% of the work sheets + a serious attempt on the term project.
  • You can't get away without the term project. If the grade on the the term project is better than the homework grade, then your homework letter grade will be bumped up. If it is worse, your letter grade will be bumped down.


  1. Introduction: Getting setup, using Python, using version control
  2. Basic Numerical Analysis
    • Computer and Numbers
    • Finite Differences
    • Convergence
    • Interpolation
    • Integration
  3. Ordinary Differential Equations I
  4. Root Finding
  5. Linear Systems of Equations
  6. Ordinary Differential Equations II: Boundary Value Problems
  7. Applications in Astrophysics
    • Nuclear Reaction Networks
    • N-Body Methods
    • Hydrodynamics I: Basics
    • Smoothed Particle Hydrodynamics (SPH)
    • Grid Based Hydrodynamics
    • Radiation Transport
  8. Monte Carlo Methods
  9. Data Analysis