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A General Framework for Solving Singular SPDEs with Applications to Fluid Models Driven by Pseudo-differential Noise

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arxiv 2208.08312 v3 pith:SOHPTGN6 submitted 2022-08-17 math.AP math.PR

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keywords spdesstochasticnoiseapplicationsdrivenequationequationsfluid
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In this paper we focus on nonlinear SPDEs with singularities included in both drift and noise coefficients, for which the Gelfand-triple argument developed for (local) monotone SPDEs turns out to be invalid. We propose a general framework of \emph{proper regularization} to solve such singular SPDEs. As applications, the (local and global) existence is presented for a broad class of fluid models driven by pseudo-differential noise of arbitrary order, which include the stochastic magnetohydrodynamics (hence Navier-Stokes/Euler) equations, stochastic Camassa-Holm type equations, stochastic aggregation-diffusion equation and stochastic surface quasi-geostrophic equation. Thus, some recent results derived in the literature are considerably extended in a unified way.

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  1. Closed Estimates of Leray Projected Transport Noise and Strong Solutions of the Stochastic Euler Equations

    math.AP 2025-07 conditional novelty 8.0 of 10

    Closed Sobolev estimates for Leray-projected transport noise yield unique local strong solutions of the 3D stochastic Euler equations, with blow-up characterized by L1([0,T]; W^{1,∞}).

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