论文标题
计算统计物理稳态的聚合方法
Aggregation Methods for Computing Steady-States in Statistical Physics
论文作者
论文摘要
我们提供了一种用于计算马尔可夫链的稳态的多机方法的局部收敛的新证明。我们的证明自然会导致对收敛速率的精确且可解释的估计。我们将IAD研究为统计物理学更复杂的方法的模型，用于计算非平衡稳态，例如Warmflash等人的非平衡伞采样方法。我们解释为什么可以使用IAD等方法有效地计算统计物理中模型的稳态以及如何选择参数以优化效率。
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 a precise and interpretable estimate 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, et al. We explain why it may be possible to use methods like IAD to efficiently calculate steady-states of models in statistical physics and how to choose parameters to optimize efficiency.
