Spring 2018

Time: MWF 13:00 - 13:50

Room: B218

Instructor: Erin Kiley - [email protected] - github/bitbucket: emkiley - office: B105D, x5144, M 16:00-16:50, TR 13:00-13:50, W 15:00-15:50

Math Drop-In Help Center: Please see mcla.edu/mathcenter for opening times and schedules.

Topics of this course:

• tools and utilities for this course, such as
  • the PhysMa Linux virtual machine, installing software packages
  • Linux command line
• introduction to python notebooks and the Python programming language, plotting data and functions with python
• symbolic computing with Sympy
• numerical analysis
  • differentiating
  • integrating
  • differential equations
• Newton-Raphson method
• linear algebra and applications
• data acquisition, analysis and visualization
• statistical methods, such as
  • least-square fitting and higher-order moments
  • Monte-Carlo methods and related techniques
• basic time series analysis
• how can computational math & physics fail
• emphasis on programming for the purpose of exploring mathematical constructions and data
• examples and applications from physics

Grades:

• 2 individual assignments (15%)
• 2 group assignments (2-3 students, 10%)
• midterm exam (25%)
• final exam (50%)