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Existence, uniqueness, and numerical approximations for stochastic Burgers equations
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In this paper we propose an all-in-one statement which includes existence, uniqueness, regularity, and numerical approximations of mild solutions for a class of stochastic partial differential equations (SPDEs) with non-globally monotone nonlinearities. The proof of this result exploits the properties of an existent fully explicit space-time discrete approximation scheme and, in particular, the fact that it satisfies suitable a priori estimates. As a byproduct we obtain almost sure and strong convergence of the approximation scheme to the mild solutions of the considered SPDEs. We conclude by applying the main result of the paper to the stochastic Burgers equations with space-time white noise.
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Spatial Sobolev regularity for stochastic Burgers equations with additive trace class noise
Stochastic Burgers solutions with additive trace class noise are shown to exist uniquely in Sobolev spaces H^gamma for all gamma < min{1, 1/2+beta}.
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