Broadcasting on trees and the Ising model
成果类型:
Article
署名作者:
Evans, W; Kenyon, C; Peres, Y; Schulman, LJ
署名单位:
University of Arizona; Universite Paris Saclay; University of California System; University of California Berkeley; Hebrew University of Jerusalem; University System of Georgia; Georgia Institute of Technology
刊物名称:
ANNALS OF APPLIED PROBABILITY
ISSN/ISSBN:
1050-5164
发表日期:
2000
页码:
410-433
关键词:
bethe lattice
random-walks
percolation
formulas
state
摘要:
Consider a process in which information is transmitted from a given root node on a noisy tree network T. We start with an unbiased random bit R at the root of the tree and send it down the edges of T. On every edge the bit can be reversed with probability epsilon, and these errors occur independently. The goal is to reconstruct R from the values which arrive at the nth level of the tree. This model has been studied in information theory, genetics and statistical mechanics. We bound the reconstruction probability from above, using the maximum flow on T viewed as a capacitated network, and from below using the electrical conductance of T. For general infinite trees, we establish a sharp threshold: the probability of correct reconstruction tends to 1/2 as n --> infinity if (1- 2 epsilon)(2) < p(c)(T), but the reconstruction probability stays bounded away from 1/2 if the opposite inequality holds. Here p(c)(T) is the critical probability for percolation on T; in particular p(c)(T) = 1/b for the b + 1-regular tree. The asymptotic reconstruction problem is equivalent to purity of the free boundary Gibbs state for the Ising model on a tree. The special case of regular trees was solved in 1995 by Bleher, Ruiz and Zagrebnov; our extension to general trees depends on a coupling argument and on a reconstruction algorithm that weights the input bits by the electrical current flow from the root to the leaves.