Day 1
- Functions.
- Matplotlib
- Flow Control
- Arrays
- Loops
Day 2
- Accuracy and precision
- Approximating Reality
- Root Finding
- Optimizing multi-dimensional functions
Day 3
- Differentiation and Integration
- Integration methods, scipy and numpy
- np.meshgrid
- Discretization
- Grids, Numerical accuracy of integrators
Day 4
- Discretization pt. 2
- Eulers Method
- Other ODE solvers (RK4)
- Boundary Value Problems
- SciPy Functions
- Euler Solvers, Pendulums,
Day 5
- Matrix approach to BVP
- Partial Differential Equations
- Parabolic Equations
- Elliptic Equations
- Temperature problems, Heat Diffusion, Potential over a grid, Laplace equation
Day 6
- Wave Equations
- Two dimensions, surface plots
- Complex Numbers
- Time-Dependent Schrodinger Eq.
- Jacobi Method, Gauss-Seidel Method, Simple Overrelaxation method
Day 7
- Interactions Between Particles
- Small particles
- Verlet integration scheme
- Simulation Cells
- Lennard-Jones potential
- Inverse Quadratic interactions
- Coarse Graining
- Periodic boundary conditions
Day 8
- Psuedo-random generation
- Probability Distributions
- Central Limit Theorem
- Transformation Method
- Rejection Method
- Monte-Carlo method
- Monte-Carlo simulations
- np.where
Day
- Interpolation
- Fourier Transforms
- np.fft.fft / ifft