Covers the theory of Markov Chain Monte Carlo (MCMC) sampling and discusses convergence conditions, transition matrix choice, and target distribution evolution.
Explores challenges in identifying useful metastable materials and discusses concepts like structure predictions, ensemble probabilities, and mapping algorithms.