Computational Methods of Physical Chemistry

3.0 credits · Graduate

This course will introduce students to analytical and computational methods useful for graduate-level research in both experimental and theoretical physical chemistry. These methods will be used to explore interesting topics in quantum mechanics and statistical mechanics. The goal of this course is to bridge the gap between the analytical techniques taught in introductory courses and the computational (and visualization) methods required for modern research problems. Topics explored will include: scientific programming and visualization, numerical solution of the Schrodinger equation, linear and nonlinear optimization techniques, stochastic/Monte Carlo methods, and Machine Learning.