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arXiv 0907.3262math.PR
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大面随机平面映射的尺度极限

Scaling limits of random planar maps with large faces

Jean-François Le Gall, Grégory Miermont

摘要:

在假设一个典型面的度的分布在一个指数为$α\in(1,2)$的稳定分布的吸引区域中的条件下,讨论了大型随机平面映射的渐近性.当映射的顶点数$n$趋于无穷大时,到一个特殊顶点的距离的渐近行为由一个称为连续距离过程的随机过程来描述,该过程可以由一个没有负跳和指标$α$的中心稳定过程来构造.特别地,由因子$n^{-1/2α}$重新缩放的地图中的距离的轮廓收敛到根据距离过程定义的随机测量。在相同的距离重标度下,被视为度量空间的顶点集在分布上收敛为$n\to\infty$,至少沿着适当的连续性,收敛到豪斯多夫维数等于$2α$的有限随机紧度量空间。

英文摘要:

We discuss asymptotics for large random planar maps under the assumption that the distribution of the degree of a typical face is in the domain of attraction of a stable distribution with index $α\in(1,2)$. When the number $n$ of vertices of the map tends to infinity, the asymptotic behavior of distances from a distinguished vertex is described by a random process called the continuous distance process, which can be constructed from a centered stable process with no negative jumps and index $α$. In particular, the profile of distances in the map, rescaled by the factor $n^{-1/2α}$, converges to a random measure defined in terms of the distance process. With the same rescaling of distances, the vertex set viewed as a metric space converges in distribution as $n\to\infty$, at least along suitable subsequences, toward a limiting random compact metric space whose Hausdorff dimension is equal to $2α$.

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