Poster - Functional Stable Limit in Random Connection Hypergraphs

Abstract

We investigate a dynamic random connection hypergraph model based on a bipartite connection structure, in which nodes and hyperedges are modeled by two independent marked Poisson point processes. Nodes are equipped with birth-death dynamics, while hyperedges are temporally localized. Then, edges are formed under spatial and temporal constraints influenced by the vertex marks. In this system, we focus on the edge count process as a function of time within a growing spatial observation window. Under suitable assumptions, we show a functional stable limit theorem the properly rescaled and centered edge count process converges in distribution to a non-Gaussian, heavy-tailed limit in the Skorokhod space.

Péter Juhász

PhD Candidate