不可靠门布尔网络Pippenger概率失效模型中的相变和随机控制
A Phase Transition and Stochastic Domination in Pippenger's Probabilistic Failure Model for Boolean Networks with Unreliable Gates
摘要：
研究了具有不可靠门的布尔网络的Pippenger模型。在这个模型中，给定网络中在它之前的任何门子集的故障状态，特定门故障的条件概率由某个$ε$从上限定。我们证明了，如果我们根据随机无圈有向图的Barak-Erdibs模型随机选取一个具有$n$门的布尔网络，使得期望的边密度为$c n^{-1}\log n$，并且如果$ε$等于顶点的最大自反传递闭包的大小的某个函数（相对于随机有向图的特定实现），则Pippenger模型在$c=1$处表现出相变。也就是说，当概率$1-o(1)$为$n\to\infty$时，我们有以下结果：对于$0 \le c \le 1$，在与Pippenger模型一致的所有门失效概率分布中，没有门失效的概率的最小值等于$o(1)$，而对于$c >1$，它等于$\exp(-\frac{c}{e(c-1)}) + o(1)$。我们还指出如何更精细的分析Pippenger的模型，例如，为了估计单调事件的概率，可以使用随机控制机制来进行。
英文摘要：
We study Pippenger's model of Boolean networks with unreliable gates. In this model, the conditional probability that a particular gate fails, given the failure status of any subset of gates preceding it in the network, is bounded from above by some $ε$. We show that if we pick a Boolean network with $n$ gates at random according to the Barak-Erdős model of a random acyclic digraph, such that the expected edge density is $c n^{-1}\log n$, and if $ε$ is equal to a certain function of the size of the largest reflexive, transitive closure of a vertex (with respect to a particular realization of the random digraph), then Pippenger's model exhibits a phase transition at $c=1$. Namely, with probability $1-o(1)$ as $n\to\infty$, we have the following: for $0 \le c \le 1$, the minimum of the probability that no gate has failed, taken over all probability distributions of gate failures consistent with Pippenger's model, is equal to $o(1)$, whereas for $c >1$ it is equal to $\exp(-\frac{c}{e(c-1)}) + o(1)$. We also indicate how a more refined analysis of Pippenger's model, e.g., for the purpose of estimating probabilities of monotone events, can be carried out using the machinery of stochastic domination.
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