Maximal inequalities for stochastic convolutions and pathwise uniform convergence of time discretisation schemes

We prove a new Burkholder-Rosenthal type inequality for discrete-time processes taking values in a 2-smooth Banach space. As a first application we prove that if $(S(t,s){)}_{0\le s\le T}$ is a $C_0$-evolution family of contractions on a $2$-smooth Banach space $X$ and $(W_t{)}_{t\in [0,T]}$ is a cylindrical Brownian motion on a probability space $(\mathrm{\Omega },P)$, then for every $0<p<\mathrm{\infty }$ there exists a constant $C_{p,X}$ such that for all progressively measurable processes $g:[0,T]\times \mathrm{\Omega }\to X$ the process $(\int_0^t S(t,s)g_sdW_s){t\in [0,T]}$hasacontinuousmodificationand$$E\sup{t\in [0,T]}\Big| \int_0^t S(t,s)g_sdW_s \Big|^p\leq C_{p,X}^p $\mathbb{E}$ \Bigl(\int_0^T | g_t|^2_{\gamma(H,X)}dt\Bigr)^{p/2}.Moreover, for $2\leq p<\infty$ one may take $C_{p,X} = 10 D \sqrt{p},$ where $D$ is the constant in the definition of $2$-smoothness for $X$. Our result improves and unifies several existing maximal estimates and is even new in case $X$ is a Hilbert space. Similar results are obtained if the driving martingale $g_tdW_t$ is replaced by more general $X$-valued martingales $dM_t$. Moreover, our methods allow for random evolution systems, a setting which appears to be completely new as far as maximal inequalities are concerned. As a second application, for a large class of time discretisation schemes we obtain stability and pathwise uniform convergence of time discretisation schemes for solutions of linear SPDEs du_t = A(t)u_tdt + g_tdW_t, \quad u_0 = 0,$$Underspatialsmoothnessassumptionsontheinhomogeneity$g$, contractivity is not needed and explicit decay rates are obtained. In the parabolic setting this sharpens several know estimates in the literature; beyond the parabolic setting this seems to provide the first systematic approach to pathwise uniform convergence to time discretisation schemes.