Mean field analysis of interacting network model with jumps
Fuente:
arXiv
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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866929256631631872 |
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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 |