This course integrates the use of mathematics and computers for modeling various phenomena drawn from the natural and social sciences. Scientific topics, organized as case studies, will span a wide range of systems at all scales, with special emphasis on the life sciences. Mathematical tools include data analysis, discrete and continuous dynamical systems, and discrete geometry. The course will provide training through programming in Mathematica.
Prerequisites: MTH 112 or MTH 114; Recommended: CSC. 111
| Number | Topic |
|---|---|
| 1 | Introduction to Modeling and Simulation in Mathematica |
| 2 | Fibonacci Numbers, the Golden Ratio, Phyllotaxis |
| 3 | Symmetry in Nature: Crystallography |
| 4 | Motion Simulation |
| 5 | Introduction to Dynamical Systems |
| 6 | Predator Prey Models |
| 7 | Data Driven Models |
| 8 | Geometry and Shape |
| 9 | Modeling bio-molecules: DNA, RNA, Proteins |
| 10 | Monte Carlo Simulations, Random Walk |
| 11 | Cellular Automata: Spread of Disease; Spread of Fire |