Limits of multiplicative inhomogeneous random graphs and Lévy trees: The continuum graphs - ENS de Lyon - École normale supérieure de Lyon
Article Dans Une Revue The Annals of Applied Probability Année : 2022

Limits of multiplicative inhomogeneous random graphs and Lévy trees: The continuum graphs

Résumé

Motivated by limits of critical inhomogeneous random graphs, we construct a family of sequences of measured metric spaces that we call continuous multiplicative graphs, that are expected to be the universal limit of graphs related to the multiplicative coalescent (the Erdős--Rényi random graph, more generally the so-called rank-one inhomogeneous random graphs of various types, and the configuration model). At the discrete level, the construction relies on a new point of view on (discrete) inhomogeneous random graphs that involves an embedding into a Galton--Watson forest. The new representation allows us to demonstrate that a processus that was already present in the pionnering work of Aldous [Ann. Probab., vol.~25, pp.~812--854, 1997] and Aldous and Limic [Electron. J. Probab., vol.~3, pp.~1--59, 1998] about the multiplicative coalescent actually also (essentially) encodes the limiting metric: The discrete embedding of random graphs into a Galton--Watson forest is paralleled by an embedding of the encoding process into a Lévy process which is crucial in proving the very existence of the local time functionals on which the metric is based; it also yields a transparent approach to compactness and fractal dimensions of the continuous objects. In a companion paper, we show that the continuous Lévy graphs are indeed the scaling limit of inhomogeneous random graphs.

Dates et versions

ensl-01773432 , version 1 (21-04-2018)

Identifiants

Citer

Nicolas Broutin, Thomas Duquesne, Minmin Wang. Limits of multiplicative inhomogeneous random graphs and Lévy trees: The continuum graphs. The Annals of Applied Probability, 2022, 32 (4), pp.2448-2503. ⟨10.1214/21-AAP1737⟩. ⟨ensl-01773432⟩
267 Consultations
0 Téléchargements

Altmetric

Partager

More