Renormalization of stochastic continuity equations on Riemannian manifolds

TL;DR

This paper proves that weak solutions to stochastic continuity equations on Riemannian manifolds are renormalized, extending Euclidean results and revealing structural effects of noise on solution dynamics.

Contribution

It establishes the renormalization property for stochastic continuity equations on manifolds, using regularization techniques and geometric analysis, which was previously known only in Euclidean spaces.

Findings

Weak solutions are renormalized solutions on manifolds.

Regularization and commutator analysis are effective in this geometric setting.

Noise influences the structure and dynamics of solutions.

Abstract

We consider the initial-value problem for stochastic continuity equations of the form $$ \partial_t \rho + \text{div}_h \left[\rho \left(u(t,x) + \sum_{i=1}^N a_i(x)\circ \frac{dW^i}{dt}\right)\right] = 0, $$ defined on a smooth closed Riemanian manifold $M$ with metric $h$, where the Sobolev regular velocity field $u$ is perturbed by Gaussian noise terms $\dot{W}_i(t)$ driven by smooth spatially dependent vector fields $a_i(x)$ on $M$. Our main result is that weak ($L^2$) solutions are renormalized solutions, that is, if $\rho$ is a weak solution, then the nonlinear composition $S(\rho)$ is a weak solution as well, for any "reasonable" function $S:\mathbb{R}\to\mathbb{R}$. The proof consists of a systematic procedure for regularizing tensor fields on a manifold, a convenient choice of atlas to simplify technical computations linked to the Christoffel symbols, and several DiPerna-Lions type commutators $\mathcal{C}_\varepsilon (\rho,D)$ between (first/second order) geometric differential operators $D$ and the regularization device ($\varepsilon$ is the scaling parameter). This work, which is related to the "Euclidean" result in Punshon-Smith (2017), reveals some structural effects that noise and nonlinear domains have on the dynamics of weak solutions.