There will be between 10-14 units in this course. This will be adjusted as the course goes on.
Unit 1: N Ways To Generate PI
- A good introduction to python: here
- Setting up your owl account
- 0. PDF on Hardware (nothing to hand in)
- 1a. Python Preliminaries (nothing to hand in)
- 1b. N Ways to Compute PI
Unit 2: The Dynamics of Throwing Balls into the Air
Learning objectives: Remembering dynamics; Differential Equations as a route to understand scientific phenomena; Air Resistance; Programming Functions; Understanding abstraction of computational components; Validating code; Euler Integration and errors associated with them; Plotting on logarithmic scales;Unit 3: Improved Dynamics and Springs
Learning objectives: Programming and using classes; Midpoint formulas for differential equations and their associated errors; Learning how to modify small parts of a code to change the physics/more abstraction; Damped harmonic oscillators; Pendulums; Forcing functions;Unit 4: Orbital Dynamics
Learning objectives: Developing two-dimensional dynamics code; gravitational forces; central potentials; Kepler's laws; analyzing data; orbital dynamics;Unit 5: Mercury Perihelion
Learning objectives: General relativity; machine precision;Unit 6: Exoplanets
Learning objectives: Fourier transforms; analyzing real data; basic data I/O techniques & signal processing;Unit 7: Predator-Prey
Learning objectives: biophysics; differential equations for other systems; ecosystems; continuous time markov chains; stochastic methodsUnit 8: Random Walks
Learning objectives: Random walks; stochasticity;Unit 9: Fluid Dynamics
Learning objectives: Fluid dynamics; animation; turbulence; conventionUnit 10: Markov Chains
Learning objectives: Markov chains; Metropolis Algorithm; Boltzmann distribution;Unit 12: Particle Physics
Learning objectives: Particle Physics; simulation of a particle physics experimentUnit 10: Quantum Computing
Learning objectives: quantum computingFinal Exam
- The exam notebook