Computational Methods for Physical Science

732
Basic numerical methods: linear algebra, interpolation and extrapolation, integration, root finding, extremization and differential equations. Introduction to Monte Carlo techniques used to stimulate processes that occur in nature and methods to simulate experiments that measure these processes including random number generators, sampling techniques, and multidimensional simulation. Methods for extracting information from experiments such as experimental measurements and uncertainties, confidence intervals, parameter estimation, likelihood methods, least squares method, hypothesis tests, and goodness of fit tests. Chaotic dynamics and other special topics as time permits.

Credits: 

3

Level: 

Graduate

Availability: 

Fall