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SPDEs with $α$-stable Lévy noise: a random field approach

This article is dedicated to the study of an SPDE of the form $$Lu(t,x)=σ(u(t,x))\dot{Z}(t,x) \quad t>0, x \in \cO$$ with zero initial conditions and Dirichlet boundary conditions, where $σ$ is a Lipschitz function, $L$ is a second-order pseudo-differential operator, $\cO$ is a bounded domain in $\bR^d$, and $\dot{Z}$ is an $α$-stable Lévy noise with $α\in (0,2)$, $α\not=1$ and possibly non-symmetric tails. To give a meaning to the concept of solution, we develop a theory of stochastic integration with respect to $Z$, by generalizing the method of Giné and Marcus (1983) to higher dimensions and non-symmetric tails. The idea is to first solve the equation with &#34;truncated&#34; noise $\dot{Z}_{K}$ (obtained by removing from $Z$ the jumps which exceed a fixed value $K$), yielding a solution $u_{K}$, and then show that the solutions $u_L,L>K$ coincide on the event $t \leq τ_{K}$, for some stopping times $τ_K \uparrow \infty$ a.s. A similar idea was used in Peszat and Zabczyk (2007) in the setting of Hilbert-space valued processes. A major step is to show that the stochastic integral with respect to $Z_{K}$ satisfies a $p$-th moment inequality, for $p \in (α,1)$ if $α<1$, and $p \in (α,2)$ if $α>1$. This inequality plays the same role as the Burkholder-Davis-Gundy inequality in the theory of integration with respect to continuous martingales.