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Large Deviations for Marked Sparse Random Graphs with Applications to Interacting Diffusions

  • Rangel Baldasso
  • , Roberto Oliveira
  • , Alan Pereira
  • , Guilherme Reis

Research output: Contribution to journalArticlepeer-review

Abstract

We consider the empirical neighborhood distribution of marked sparse Erdős-Rényi random graphs, obtained by decorating edges and vertices of a sparse Erdős-Rényi random graph with i.i.d. random elements taking values on Polish spaces. We prove that the empirical neighborhood distribution of this model satisfies a large deviation principle in the framework of local weak convergence. We rely on the concept of BC-entropy introduced by Delgosha and Anantharam (2019) which is inspired on the previous work by Bordenave and Caputo (2015). Our main technical contribution is an approximation result that allows one to pass from graph with marks in discrete spaces to marks in general Polish spaces. As an application of the results developed here, we prove a large deviation principle for interacting diffusions driven by gradient evolution and defined on top of sparse Erdős-Rényi random graphs. In particular, our results apply for the stochastic Kuramoto model. We obtain analogous results for the sparse uniform random graph with given number of edges.

Original languageEnglish
Article number25
JournalJournal of Statistical Physics
Volume193
Issue number2
DOIs
StatePublished - Feb 2026
Externally publishedYes

Bibliographical note

Publisher Copyright:
© The Author(s) 2026.

Keywords

  • Interacting diffusions
  • Local topology
  • Sparse random graphs
  • Stochastic Kuramoto model
  • large deviations

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