Almost Sure Diffusion Approximation in Averaging: Direct Proofs with Rough Paths Flavors

Abstract: We consider again the fast-slow motions setups in the continuous time $\frac {dX_N(t)}{dt}=N^{1/2} \sig(X_N(t))(\xi(tN))+b(X_N(t)),\, t\in [0,T]$ and the discrete time $X_N((n+1)/N)=X_N(n/N)+N^{-1/2}\sig(X_N(n/N))\xi(n)+N^{-1}b(X_N(n/N)),\, n=0,1,...,[TN]$ where $\sig$ and $b$ are smooth matrix and vector functions, respectively, $\xi$ is a centered vector stationary stochastic process with weak dependence in time and $N$ is a big parameter. We obtain estimates for the almost sure approximations of the process $X_N$ by certain diffusion process $\Sig$. In \cite{FK} and in other papers concerning similar setups the results were obtained relying fully on the rough paths theory. Here we derive our probabilistic results as corollaries of quite general deterministic estimates which are obtained with all details provided following somewhat ideology of the rough paths theory but not relying on this theory per se which should allow a more general readership to follow complete arguments.