This course will give students an operative knowledge of computational simulation and optimization techniques based on stochastic methods.
Course syllabus:
(1) Monte-Carlo Integration. Sampling techniques and variance reduction.
(2) Stochastic optimization: simulated annealing and genetic algorithms.
(3) Dynamic Monte Carlo: random walks and the diffusion equation.
(4) Classical Monte Carlo simulations: from simple to molecular systems and biomolecules.
(5) Application of Monte Carlo methods to quantum systems.