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Creators/Authors contains: "Earle, Gabriel"

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  1. ; (, Multiscale Modeling & Simulation)
    We give a new proof of local convergence of a multigrid method called iterative aggregation/disaggregation (IAD) for computing steady states of Markov chains. Our proof leads naturally to precise and interpretable estimates of the asymptotic rate of convergence. We study IAD as a model of more complex methods from statistical physics for computing nonequilibrium steady states, such as the nonequilibrium umbrella sampling method of Warmflash, Bhimalapuram, and Dinner [J. Chem. Phys., 127 (2007), 154112]. We explain why it may be possible to use methods like IAD to efficiently calculate steady states of processes in statistical physics and how to choose parameters to optimize efficiency. 
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