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Partition function of the Ising model via factor graph duality

机译:通过因子图对偶性的Ising模型的分区函数

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The partition function of a factor graph and the partition function of the dual factor graph are related to each other by the normal factor graph duality theorem. We apply this result to the classical problem of computing the partition function of the Ising model. In the one-dimensional case, we thus obtain an alternative derivation of the (well-known) analytical solution. In the two-dimensional case, we find that Monte Carlo methods are much more efficient on the dual graph than on the original graph, especially at low temperature.
机译:因子图的分配函数和对偶因子图的分配函数通过正态因子图对偶定理相互关联。我们将此结果应用于计算Ising模型的分区函数的经典问题。因此,在一维情况下,我们获得了(众所周知的)分析解决方案的另一种推导。在二维情况下,我们发现对偶图上的蒙特卡洛方法比原始图上的效率要高得多,尤其是在低温下。

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