Using the weak convergence approach, we prove the large deviation principle (LDP) for solutions to quasilinear stochastic evolution equations with small Gaussian noise in the critical variational setting, a recently developed general variational framework. No additional assumptions are made apart from those required for well-posedness. In particular, no monotonicity is required, nor a compact embedding in the Gelfand triple. Moreover, we allow for flexible growth of the diffusion coefficient, including gradient noise. This leads to numerous applications for which the LDP was not established yet, in particular equations on unbounded domains with gradient noise. Since our framework includes the 2D Navier–Stokes and Boussinesq equations with gradient noise and unbounded domains, our results resolve an open problem that has remained unsolved for over 15 years.

On spaces of finite signed Borel measures on a metric space one has introduced the Fortet-Mourier and Dudley norms, by embedding the measures into the dual space of the Banach space of bounded Lipschitz functions, equipped with different – but equivalent – norms: the FM-norm and the BL-norm, respectively. The norm of such a measure is then obtained by maximising the value of the measure when applied by integration to extremal functions of the unit ball. We introduce Lipschitz extension operators, essentially based on those defined by McShane, and investigate their properties. A remarkable one is that non-trivial extreme points are mapped to non-trivial extreme points of FM- and BL-norm unit balls. Using these extension operators, we define suitable ‘small’ subsets of extremal functions that are weak-star dense in the full set of extreme points of the unit ball, for any underlying metric space. For connected metric spaces, we additionally find a larger set of extremal functions for the BL-norm, similar to such a set that was defined previously by J. Johnson for the FM-norm. This set is then also weak-star dense in the extremal functions. These results may open an avenue to obtaining computational approaches for the Dudley norm on signed Borel measures.

Explicit expressions and computational approaches are given for the Fortet–Mourier distance between a positively weighted sum of Dirac measures on a metric space and a positive finite Borel measure. Explicit expressions are given for the distance to a single Dirac measure. For the case of a sum of several Dirac measures one needs to resort to a computational approach. In particular, two algorithms are given to compute the Fortet–Mourier norm of a molecular measure, i.e. a finite weighted sum of Dirac measures. It is discussed how one of these can be modified to allow computation of the dual bounded Lipschitz (or Dudley) norm of such measures.