Large Deviations for Marked Sparse Random Graphs with Applications to Interacting Diffusions
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.
Authors
- Rangel Baldasso (ORCID: https://orcid.org/0000-0001-8872-9442)
- Roberto I. Oliveira (ORCID: https://orcid.org/0000-0002-1064-3398)
- Guilherme Reis
- Alan Pereira
Institutions
- Instituto Nacional de Matemática Pura e Aplicada (BR)
- Pontifícia Universidade Católica do Rio de Janeiro (BR)
- Brazilian Society of Computational and Applied Mathematics (BR)
- Universidade Federal de Alagoas (BR)
Publication Details
- Journal
- Journal of Statistical Physics
- Published
- 2026-02-04
- DOI
- https://doi.org/10.1007/s10955-025-03565-z
- Primary Topic
- Stochastic processes and statistical mechanics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- European Commission
- Universiteit Leiden
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Fundação de Amparo à Pesquisa do Estado de Alagoas
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro
- HORIZON EUROPE Excellent Science
- H2020 Marie Skłodowska-Curie Actions