Pathwise large deviations for white noise chaos expansions

We consider a family of continuous processes {X?}?>0 which are measurable with respect to white noise measure, take values in the space functions C([0,1]d:R), and have Wiener chaos expansion X?= ?n=0??nIn(fn?). provide sufficient conditions for large deviations principle hold thereby refreshing problem left open by Pérez–Abreu (1993) Brownian motion case. The proof is based on weak convergence approach deviations: it involves demonstrating distribution certain perturbations original process, thus main difficulties lie analysing controlling perturbed multiple stochastic integrals. Moreover, adopting this representation offers new perspective pathwise induces variety applications thereof.