The fluctuation process of the stochastic point vortex model with common noise converges in distribution to the unique strong solution of a linear fluctuation SPDE with multiplicative transport noise and a conditionally Gaussian additive noise.
Quasi-continuity method for mean-field diffusions: large deviations and central limit theorem
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abstract
A pathwise large deviation principle in the Wasserstein topology and a pathwise central limit theorem are proved for the empirical measure of a mean-field system of interacting diffusions. The coefficients are path-dependent. The framework allows for degenerate diffusion matrices, which may depend on the empirical measure, including mean-field kinetic processes. The main tool is an extension of Tanaka's pathwise construction to non-constant diffusion matrices. This can be seen as a mean-field analogous of Azencott's quasi-continuity method for the Freidlin-Wentzell theory. As a by-product, uniform-in-time-step fluctuation and large deviation estimates are proved for a discrete-time version of the meanfield system. Uniform-in-time-step convergence is also proved for the value function of some mean-field control problems with quadratic cost.
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The fluctuation behaviour of the stochastic point vortex model with common noise
The fluctuation process of the stochastic point vortex model with common noise converges in distribution to the unique strong solution of a linear fluctuation SPDE with multiplicative transport noise and a conditionally Gaussian additive noise.