Accelerating convergence in stochastic particle dispersion simulation codes

Abstract 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.