Probability-graphons: Limits of large dense weighted graphs

Fuente: arXiv
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Main Authors: Abraham, Romain, Delmas, Jean-François, Weibel, Julien
Format: Preprint
Published: 2023
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author Abraham, Romain
Delmas, Jean-François
Weibel, Julien
author_facet Abraham, Romain
Delmas, Jean-François
Weibel, Julien
contents We introduce probability-graphons which are probability kernels that generalize graphons to the case of weighted graphs. Probability-graphons appear as the limit objects to study sequences of large weighted graphs whose distribution of subgraph sampling converge. The edge-weights are taken from a general Polish space, which also covers the case of decorated graphs. Here, graphs can be either directed or undirected. Starting from a distance $d_m$ inducing the weak topology on measures, we define a cut distance on probability-graphons, making it a Polish space, and study the properties of this cut distance. In particular, we exhibit a tightness criterion for probability-graphons related to relative compactness in the cut distance. We also prove that under some conditions on the distance $d_m$, which are satisfied for some well-know distances like the Prohorov distance, and the Fortet-Mourier and Kantorovitch-Rubinstein norms, the topology induced by the cut distance on the spaceof probability-graphons is independent from the choice of $d_m$. Eventually, we prove that this topology coincides with the topology induced by the convergence in distribution of the sampled subgraphs.
format Preprint
id arxiv_https___arxiv_org_abs_2312_15935
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Probability-graphons: Limits of large dense weighted graphs
Abraham, Romain
Delmas, Jean-François
Weibel, Julien
Discrete Mathematics
Probability
We introduce probability-graphons which are probability kernels that generalize graphons to the case of weighted graphs. Probability-graphons appear as the limit objects to study sequences of large weighted graphs whose distribution of subgraph sampling converge. The edge-weights are taken from a general Polish space, which also covers the case of decorated graphs. Here, graphs can be either directed or undirected. Starting from a distance $d_m$ inducing the weak topology on measures, we define a cut distance on probability-graphons, making it a Polish space, and study the properties of this cut distance. In particular, we exhibit a tightness criterion for probability-graphons related to relative compactness in the cut distance. We also prove that under some conditions on the distance $d_m$, which are satisfied for some well-know distances like the Prohorov distance, and the Fortet-Mourier and Kantorovitch-Rubinstein norms, the topology induced by the cut distance on the spaceof probability-graphons is independent from the choice of $d_m$. Eventually, we prove that this topology coincides with the topology induced by the convergence in distribution of the sampled subgraphs.
title Probability-graphons: Limits of large dense weighted graphs
topic Discrete Mathematics
Probability
url https://arxiv.org/abs/2312.15935