The birth of the infinite cluster: Finite-size scaling in percolation

被引:60
作者
Borgs, C
Chayes, JT
Kesten, H
Spencer, J
机构
[1] Microsoft Corp, Res, Redmond, WA 98052 USA
[2] Cornell Univ, Dept Math, Ithaca, NY 14853 USA
[3] NYU, Courant Inst Math Sci, New York, NY 10012 USA
关键词
D O I
10.1007/s002200100521
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
We address the question of finite-size scaling in percolation by studying bond percolation in a finite box of side length n, both in two and in higher dimensions. In dimension d = 2, we obtain a complete characterization of finite-size scaling. In dimensions d > 2, we establish the same results under a set of hypotheses related to so-called scaling and hyperscaling postulates which are widely believed to hold up to d = 6. As a function of the size of the box, we determine the scaling window in which the system behaves critically. We characterize criticality in terms of the scaling of the sizes of the largest clusters in the box: incipient infinite clusters which give rise to the infinite cluster. Within the scaling window, we show that the size of the largest cluster behaves like n(d)pi (n), where pi (n) is the probability at criticality that the origin is connected to the boundary of a box of radius n. We also show that, inside the window, there are typically many clusters of scale n(d)pi (n) and hence that "the" incipient infinite cluster is not unique. Below the window, we show that the size of the largest cluster scales like xi (d)pi (xi) log(n/xi), where is the correlation length, and again, there are many clusters of this scale. Above the window, we show that the size of the largest cluster scales like n(d) P-infinity, where P-infinity is the infinite cluster density, and that there is only one cluster of this scale. Our results are finite-dimensional analogues of results on the dominant component of the Erdos-Renyi mean-field random graph model.
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页码:153 / 204
页数:52
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