Lecture
This lecture covers the concept of correlated sampling, focusing on the correct description of the weight function and the introduction of Markovian chains. It explains the abandonment of statistical independence for calculating integrals and the method for generating random variables according to a given weight function. The theorem associated with a Markovian chain and the conditions of ergodicity are discussed, along with the notion of walkers and the scope in correlated sampling.