Monte Carlo methods are widely used for approximating complicated, multidimensional integrals Bayesian inference. Population (PMC) is an important class of methods, which adapts a population proposals to generate weighted samples that approximate the target distribution. When distribution expensive evaluate, PMC may encounter computational limitations since it requires many evaluations To addre...

In this lecture, we cover the other major method for generating atomic trajectories: the Monte Carlo (MC) approach. Unlike MD, Monte Carlo methods are stochastic in nature—the time progression of the atomic positions proceeds randomly and is not predictable given a set of initial conditions. The dynamic principles by which we evolve the atomic positions incorporate random moves or perturbations...