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Convergence in Wasserstein distance for empirical measures of semilinear SPDEs

Feng‐Yu Wang

2023The Annals of Applied Probability12 citationsDOIOpen Access PDF

Abstract

The convergence rate in Wasserstein distance is estimated for the empirical measures of symmetric semilinear SPDEs. Unlike in the finite-dimensional case that the convergence is of algebraic order in time, in the present situation the convergence is of log order with a power given by eigenvalues of the underlying linear operator.

Topics & Concepts

MathematicsConvergence (economics)Eigenvalues and eigenvectorsRate of convergenceApplied mathematicsEmpirical measureModes of convergence (annotated index)Operator (biology)Algebraic numberOrder (exchange)Normal convergenceCompact convergenceMathematical analysisPure mathematicsStatisticsComputer scienceTopological vector spaceEconomicsIsolated pointChannel (broadcasting)GeneTopological spaceTranscription factorComputer networkEconomic growthChemistryFinanceBiochemistryQuantum mechanicsPhysicsRepressorGeometric Analysis and Curvature FlowsPoint processes and geometric inequalitiesNonlinear Partial Differential Equations
Convergence in Wasserstein distance for empirical measures of semilinear SPDEs | Litcius