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Rafael Engel

Publications and source records attributed to Rafael Engel.

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High-degree vertices in uniform recursive directed acyclic graphs with freezing

We study uniform recursive directed acyclic graphs with freezing. Here, a graph is built by adding vertices one-by-one and connecting a new vertex to $m\in\mathbb N$ uniformly selected vertices already present. At certain steps vertices can also be frozen, and arriving vertices are not allowed to connect to frozen vertices. This model generalises the uniform attachment tree with freezing, introduced by Bellin et. al (which corresponds to the case $m=1$) as well as the uniform recursive directed acyclic graph model (where no vertices are frozen). Under mild assumptions on when vertices are frozen, we study the empirical degree distribution, large degrees in the graph, and other properties of large-degree vertices such as their label and distance to the first vertex in the graph. Our work improves and/or extends various results from the literature on uniform attachment trees (with freezing) and uniform recursive directed acyclic graphs without freezing. In particular, our results show that statistics that are determined `locally' (e.g. the empirical degree distribution and maximum degree) are essentially unaffected by the freezing of vertices, whereas statistics that are determined `globally' (e.g. the length of paths between vertices) are highly affected by introducing freezing. The analysis relies on adapting the Kingman coalescent construction for uniform attachment trees to the non-tree setting.

math.PR

Large degree vertices in random directed acyclic graphs

This Master's thesis examines the properties of large degree vertices in random recursive directed acyclic graphs (RRDAGs), a generalization of the well-studied random recursive tree (RRT) model. Using a novel adaptation of Kingman's coalescent, we extend results from RRTs to RRDAGs, focusing on different vertex properties. For large degrees, we establish the asymptotic joint distribution of the degree of multiple uniform vertices, proving that they follow a multivariate geometric distribution, and obtain results on maximal and near-maximal degree vertices. In addition, we consider a version of vertex depth that we call ungreedy depth and describe its asymptotic behavior, along with the labels, of single uniform vertices with a given large degree. Finally, we extend this analysis to multiple uniform vertices by deriving the asymptotic behavior of their labels conditional on large degrees.

math.PR