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arxiv: 1501.07258 · v2 · pith:ELOMV4TTnew · submitted 2015-01-28 · 🧮 math.PR · cond-mat.stat-mech· math.AP

The divisible sandpile at critical density

classification 🧮 math.PR cond-mat.stat-mechmath.AP
keywords almostmassessurelycriticaldivisiblefinitegraphmass
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The divisible sandpile starts with i.i.d. random variables ("masses") at the vertices of an infinite, vertex-transitive graph, and redistributes mass by a local toppling rule in an attempt to make all masses at most 1. The process stabilizes almost surely if m<1 and it almost surely does not stabilize if m>1, where $m$ is the mean mass per vertex. The main result of this paper is that in the critical case m=1, if the initial masses have finite variance, then the process almost surely does not stabilize. To give quantitative estimates on a finite graph, we relate the number of topplings to a discrete biLaplacian Gaussian field.

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