Data assimilation with the 2D Navier–Stokes equations: Optimal Gaussian asymptotics for the posterior measure
二维 Navier–Stokes 方程的数据同化:后验测度的最优高斯渐近性质
A functional Bernstein–von Mises theorem is proved for posterior measures arising in a data assimilation problem with the two-dimensional Navier–Stokes equation where a Gaussian process prior is assigned to the initial condition of the system. The posterior measure, which provides the update in the space of all trajectories arising from a discrete sample of the (deterministic) dynamics, is shown to be approximated by a Gaussian random vector field obtained as the solution to…