Timár G, da Costa R A, Dorogovtsev S N, Mendes J F F
Departamento de Física da Universidade de Aveiro & I3N, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal.
A. F. Ioffe Physico-Technical Institute, 194021 St. Petersburg, Russia.
Phys Rev E. 2017 Apr;95(4-1):042322. doi: 10.1103/PhysRevE.95.042322. Epub 2017 Apr 27.
Message passing equations yield a sharp percolation transition in finite graphs, as an artifact of the locally treelike approximation. For an arbitrary finite, connected, undirected graph we construct an infinite tree having the same local structural properties as this finite graph, when observed by a nonbacktracking walker. Formally excluding the boundary, this infinite tree is a generalization of the Bethe lattice. We indicate an infinite, locally treelike, random network whose local structure is exactly given by this infinite tree. Message passing equations for various cooperative models on this construction are the same as for the original finite graph, but here they provide the exact solutions of the corresponding cooperative problems. These solutions are good approximations to observables for the models on the original graph when it is sufficiently large and not strongly correlated. We show how to express these solutions in the critical region in terms of the principal eigenvector components of the nonbacktracking matrix. As representative examples we formulate the problems of the random and optimal destruction of a connected graph in terms of our construction, the nonbacktracking expansion. We analyze the limitations and the accuracy of the message passing algorithms for different classes of networks and compare the complexity of the message passing calculations to that of direct numerical simulations. Notably, in a range of important cases, simulations turn out to be more efficient computationally than the message passing.
作为局部树状近似的一种表现,消息传递方程在有限图中产生了尖锐的渗流转变。对于任意有限、连通、无向图,我们构造了一棵无限树,当由非回溯行走者观察时,它具有与该有限图相同的局部结构特性。形式上排除边界后,这棵无限树是贝塞晶格的一种推广。我们指出了一个无限的、局部树状的随机网络,其局部结构恰好由这棵无限树给出。在此构造上的各种合作模型的消息传递方程与原始有限图的相同,但在这里它们提供了相应合作问题的精确解。当原始图足够大且相关性不强时,这些解是原始图上模型可观测量的良好近似。我们展示了如何在临界区域根据非回溯矩阵的主特征向量分量来表达这些解。作为代表性例子,我们根据我们的构造,即非回溯展开,阐述了连通图的随机和最优破坏问题。我们分析了不同类网络的消息传递算法的局限性和准确性,并将消息传递计算的复杂度与直接数值模拟的复杂度进行了比较。值得注意的是,在一系列重要情况下,模拟在计算上比消息传递更有效。