Well-posedness of a class of stochastic partial differential equations with fully monotone coefficients perturbed by L\'evy noise
Abstract
In this article, we consider the following class of stochastic partial differential equations (SPDE): equation* \alignedd X(t)&=A(t,X(t))d t+B(t,X(t))dW(t)+∫Zγ(t,X(t-),z)π(d t,d z),\; t∈[0,T],\\ X(0)&=x ∈ H,aligned .equation* with fully locally monotone coefficients in a Gelfand triplet V⊂ H⊂V*, where the mappings align* A:[0,T]× V*, B:[0,T]× V2(U,H), γ:[0,T]×V×Z, align* are measurable, L2(U,H) is the space of all Hilbert-Schmidt operators from U, W is a U-cylindrical Wiener process and π is a compensated time homogeneous Poisson random measure. Such kind of SPDE cover a large class of quasilinear SPDE and a good number of fluid dynamic models. Under certain generic assumptions of A,B and γ, using the classical Faedo-Galekin technique, a compactness method and a version of Skorokhod's representation theorem, we prove the existence of a probabilistic weak solution as well as pathwise uniqueness of solution. We use the classical Yamada-Watanabe theorem to obtain the existence of a unique probabilistic strong solution. Finally, we allow both diffusion coefficient B(t,·) and jump noise coefficient γ(t,·,z) to depend on both H-norm and V-norm, which implies that both the coefficients could also depend on the gradient of solution. We establish the global solvability results.
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