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Main Author: Li, Zeqian
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2402.16295
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author Li, Zeqian
author_facet Li, Zeqian
contents This paper considers an $n$-particle jump-diffusion system with mean filed interaction, where the coefficients are locally Lipschitz continuous. We address the convergence as $n\to\infty$ of the empirical measure of the jump-diffusions to the solution of a deterministic McKean-Vlasov equation. The strong well-posedness of the associated McKean-Vlasov equation and a corresponding propagation of chaos result are proven. In particular, we provide also precise estimates of the convergence speed with respect to a Wasserstein-like metric.
format Preprint
id arxiv_https___arxiv_org_abs_2402_16295
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Mean field analysis of interacting network model with jumps
Li, Zeqian
Probability
This paper considers an $n$-particle jump-diffusion system with mean filed interaction, where the coefficients are locally Lipschitz continuous. We address the convergence as $n\to\infty$ of the empirical measure of the jump-diffusions to the solution of a deterministic McKean-Vlasov equation. The strong well-posedness of the associated McKean-Vlasov equation and a corresponding propagation of chaos result are proven. In particular, we provide also precise estimates of the convergence speed with respect to a Wasserstein-like metric.
title Mean field analysis of interacting network model with jumps
topic Probability
url https://arxiv.org/abs/2402.16295