  Metropolis algorithm has been extensively employed for simulating a canonical
ensemble and estimating macroscopic properties of a closed system at any
desired temperature. A mechanical property, like energy can be calculated by
averaging over a large number of micro states of the stationary Markov chain
generated by the Metropolis algorithm. However thermal properties like entropy,
and free energies are not easily accessible. A method called umbrella sampling
was proposed some forty years ago for this purpose. Ever since, umbrella
sampling has undergone several metamorphoses and we have now multi canonical
Monte Carlo, entropic sampling, flat histogram methods, Wang-Landau algorithm
etc. In these talks I shall tell you of Metropolis algorithm for estimating
mechanical properties and of Wang-Landau algorithm for estimating both
mechanical and thermal properties of an equilibrium system. I shall make these
lectures as pedagogical and self-contained as possible.
