Geometry of the minimal spanning tree in the heavy-tailed regime: new universality classes

Bhamidi, S and Sen, S (2024) Geometry of the minimal spanning tree in the heavy-tailed regime: new universality classes. In: Probability Theory and Related Fields, 188 (3-4). pp. 729-804.

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Abstract

A well-known open problem on the behavior of optimal paths in random graphs in the strong disorder regime, formulated by statistical physicists, and supported by a large amount of numerical evidence over the last decade (Braunstein et al. in Phys Rev Lett 91(16):168701, 2003; Braunstein et al. in Int J Bifurc Chaos 17(07):2215�2255, 2007; Chen et al. in Phys Rev Lett 96(6):068702, 2006; Wu et al. in Phys Rev Lett 96(14):148702, 2006) is as follows: for a large class of random graph models with degree exponent ��(3,4), distances in the minimal spanning tree (MST) on the giant component in the supercritical regime scale like n(�-3)/(�-1). The aim of this paper is to make progress towards a proof of this conjecture. We consider a supercritical inhomogeneous random graph model with degree exponent ��(3,4) that is closely related to Aldous�s multiplicative coalescent, and show that the MST constructed by assigning i.i.d. continuous weights to the edges in its giant component, endowed with the tree distance scaled by n-(�-3)/(�-1), converges in distribution with respect to the Gromov�Hausdorff topology to a random compact real tree. Further, almost surely, every point in this limiting space either has degree one (leaf), or two, or infinity (hub), both the set of leaves and the set of hubs are dense in this space, and the Minkowski dimension of this space equals (�-1)/(�-3). The multiplicative coalescent, in an asymptotic sense, describes the evolution of the component sizes of various near-critical random graph processes. We expect the limiting spaces in this paper to be the candidates for the scaling limit of the MST constructed for a wide array of other heavy-tailed random graph models. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

Item Type:	Journal Article
Publication:	Probability Theory and Related Fields
Publisher:	Springer Science and Business Media Deutschland GmbH
Additional Information:	The copyright for this article belongs to Springer Science and Business Media Deutschland GmbH.
Department/Centre:	Division of Physical & Mathematical Sciences > Mathematics
Date Deposited:	15 May 2024 04:38
Last Modified:	15 May 2024 04:38
URI:	https://eprints.iisc.ac.in/id/eprint/84490

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