Accelerating convergence in stochastic particle dispersion simulation codes
Recent work in adaptive importance sampling is applied to Markov chain models for Monte Carlo simulations. When this technique is incorporated into the simulation of physical processes, it can give orders-of-magnitude improvement in convergence times relative to standard approaches. We review the related methodology and illustrate its application.
importance sampling markov chains exponential convergence monte carlo methods