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Explores sampling the canonical ensemble, temperature fluctuations, extended Lagrangian, and Maxwell-Boltzmann distribution in molecular dynamics simulations.
Covers the theory of Markov Chain Monte Carlo (MCMC) sampling and discusses convergence conditions, transition matrix choice, and target distribution evolution.
Explores Monte Carlo techniques for sampling and simulation, covering integration, importance sampling, ergodicity, equilibration, and Metropolis acceptance.
