Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/184623
Title: Graph connectivity with fixed endpoints in the random-connection model
Authors: Liu, Qingwei
Privault, Nicolas
Keywords: Mathematical Sciences
Issue Date: 2025
Source: Liu, Q. & Privault, N. (2025). Graph connectivity with fixed endpoints in the random-connection model. Probability in the Engineering and Informational Sciences, 1-27. https://dx.doi.org/10.1017/S0269964824000160
Project: MOE-T2EP20120-0005 
Journal: Probability in the Engineering and Informational Sciences 
Abstract: We consider the count of subgraphs with an arbitrary configuration of endpoints in the random-connection model based on a Poisson point process on Rd. We present combinatorial expressions for the computation of the cumulants and moments of all orders of such subgraph counts, which allow us to estimate the growth of cumulants as the intensity of the underlying Poisson point process goes to infinity. As a consequence, we obtain a central limit theorem with explicit convergence rates under the Kolmogorov distance, and connectivity bounds. Numerical examples are presented using a computer code in SageMath for the closed-form computation of cumulants of any order, for any type of connected subgraph and for any configuration of endpoints in any dimension d>=1. In particular, graph connectivity estimates, Gram-Charlier expansions for density estimation, and correlation estimates for joint subgraph counting are obtained.
URI: https://hdl.handle.net/10356/184623
ISSN: 0269-9648
DOI: 10.1017/S0269964824000160
Schools: School of Physical and Mathematical Sciences 
Rights: © 2025 The Author(s). Published by Cambridge University Press. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Journal Articles

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