The birth of the strong components

IF 0.9 3区 数学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING Random Structures & Algorithms Pub Date : 2023-08-07 DOI:10.1002/rsa.21176
S. Dovgal, Élie de Panafieu, D. Ralaivaosaona, Vonjy Rasendrahasina, S. Wagner
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Abstract

It is known that random directed graphs undergo a phase transition around the point . Earlier, Łuczak and Seierstad have established that as when , the asymptotic probability that the strongly connected components of a random directed graph are only cycles and single vertices decreases from 1 to 0 as goes from to . By using techniques from analytic combinatorics, we establish the exact limiting value of this probability as a function of and provide more statistical insights into the structure of a random digraph around, below and above its transition point. We obtain the limiting probability that a random digraph is acyclic and the probability that it has one strongly connected complex component with a given difference between the number of edges and vertices (called excess). Our result can be extended to the case of several complex components with given excesses as well in the whole range of sparse digraphs. Our study is based on a general symbolic method which can deal with a great variety of possible digraph families, and a version of the saddle point method which can be systematically applied to the complex contour integrals appearing from the symbolic method. While the technically easiest model is the model of random multidigraphs, in which multiple edges are allowed, and where edge multiplicities are sampled independently according to a Poisson distribution with a fixed parameter , we also show how to systematically approach the family of simple digraphs, where multiple edges are forbidden, and where 2‐cycles are either allowed or not. Our theoretical predictions are supported by numerical simulations when the number of vertices is finite, and we provide tables of numerical values for the integrals of Airy functions that appear in this study.
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诞生了强大的组件
已知随机有向图在该点周围发生相变。先前Łuczak和Seierstad已经建立了当,随机有向图的强连通分量仅为环和单个顶点的渐近概率随着从到从1到0减小。通过使用分析组合学的技术,我们建立了这个概率的精确极限值,作为一个函数,并提供了更多的统计见解,以了解随机有向图在其过渡点周围,下方和上方的结构。我们得到了一个随机有向图是无环的极限概率,以及它有一个强连通复分量的概率,其边和顶点的数量之间有给定的差(称为过剩)。我们的结果可以推广到具有给定过裕量的几个复杂分量的情况,也可以推广到整个稀疏有向图的范围。我们的研究是基于一种可以处理多种可能的有向图族的一般符号方法,以及一种可以系统地应用于由符号方法产生的复杂轮廓积分的鞍点方法。虽然技术上最简单的模型是随机多有向图的模型,其中允许多条边,并且根据固定参数的泊松分布独立采样边的多重性,但我们也展示了如何系统地接近简单有向图的家庭,其中多条边是禁止的,并且允许或不允许2环。当顶点数量有限时,我们的理论预测得到了数值模拟的支持,并且我们为本研究中出现的Airy函数的积分提供了数值表。
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来源期刊
Random Structures & Algorithms
Random Structures & Algorithms 数学-计算机:软件工程
CiteScore
2.50
自引率
10.00%
发文量
56
审稿时长
>12 weeks
期刊介绍: It is the aim of this journal to meet two main objectives: to cover the latest research on discrete random structures, and to present applications of such research to problems in combinatorics and computer science. The goal is to provide a natural home for a significant body of current research, and a useful forum for ideas on future studies in randomness. Results concerning random graphs, hypergraphs, matroids, trees, mappings, permutations, matrices, sets and orders, as well as stochastic graph processes and networks are presented with particular emphasis on the use of probabilistic methods in combinatorics as developed by Paul Erdõs. The journal focuses on probabilistic algorithms, average case analysis of deterministic algorithms, and applications of probabilistic methods to cryptography, data structures, searching and sorting. The journal also devotes space to such areas of probability theory as percolation, random walks and combinatorial aspects of probability.
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