Poster - Functional Stable Limit in Random Connection Hypergraphs
Aug 4, 2025
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0 min read
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.
Date
Aug 4, 2025 4:00 PM — 5:15 PM
Event
Location
Aarhus University - Aarhus Institute of Advanced Studies
6B Hoegh-Guldbergs Gade, Aarhus C, 8000
Authors
Quantitative Researcher
Quantitative researcher with a PhD in Mathematics, combining expertise in stochastic modeling, statistical inference, and machine learning with industrial experience in developing predictive systems.
Experienced in large-scale time-series analysis, uncertainty quantification, and rigorous model validation, with strong Python/C++ skills and a proven track record of translating research into production software.
Currently developing intraday electricity-price models and stochastic-control methods for optimal liquidation at Aarhus University, in collaboration with an energy trading firm.