Abelian and stochastic sandpile models on complete bipartite graphs

Thomas Selig, Haoyue Zhu
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Abstract

In the sandpile model, vertices of a graph are allocated grains of sand. At each unit of time, a grain is added to a randomly chosen vertex. If that causes its number of grains to exceed its degree, that vertex is called unstable, and topples. In the Abelian sandpile model (ASM), topplings are deterministic, whereas in the stochastic sandpile model (SSM) they are random. We study the ASM and SSM on complete bipartite graphs. For the SSM, we provide a stochastic version of Dhar's burning algorithm to check if a given (stable) configuration is recurrent or not, with linear complexity. We also exhibit a bijection between sorted recurrent configurations and pairs of compatible Ferrers diagrams. We then provide a similar bijection for the ASM, and also interpret its recurrent configurations in terms of labelled Motzkin paths.
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完整双向图上的非线性和随机沙堆模型
在沙堆模型中,图形的顶点被分配为沙粒。在一个教学单位时间内,随机选择一个顶点添加一粒沙。如果沙粒的数量超过了顶点的度数,那么这个顶点就被称为不稳定顶点。在阿贝尔沙堆模型(ASM)中,顶点是确定的,而在随机沙堆模型(SSM)中,顶点是随机的。我们研究了完整双向图上的 ASM 和 SSM。对于 SSM,我们提供了 Dhar 燃烧算法的随机版本,以线性复杂度检查给定(稳定)配置是否是循环的。我们还展示了排序递归配置与兼容费勒斯图对之间的双射关系。然后,我们为 ASM 提供了类似的偏射,并用带标签的莫兹金路径来解释其递归配置。
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