| Abstract: |
| This work investigates the asymptotic behavior of multiscale McKean-Vlasov stochastic differential equations. The system consists of a slow component perturbed by a small fractional Brownian motion with Hurst index $H \in (1/2, 1)$ and a fast component driven by an independent standard Brownian motion. We establish the large deviation principle to characterize the probability of deviations from the averaged process. The main results are established via a weak convergence approach combined with the occupation measure method. The main challenge lies in addressing the inherent interplay between the distribution-dependent coefficients and the memory effects inherent in the fractional noise. |
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