Publication | Open Access
Rate of convergence for particle approximation of PDEs in Wasserstein space
17
Citations
11
References
2022
Year
Numerical AnalysisLarge DeviationsEngineeringN -Particle ApproximationStochastic AnalysisStochastic PhenomenonStochastic Differential EquationsPde-constrained OptimizationApproximation TheoryConvergence AnalysisDirichlet FormPhysicsStochastic SystemWasserstein SpaceStochastic Dynamical SystemPathwise ErrorStochastic Differential EquationNatural SciencesCommon NoiseStochastic CalculusParticle ApproximationWasserstein Distance
Abstract We prove a rate of convergence for the N -particle approximation of a second-order partial differential equation in the space of probability measures, such as the master equation or Bellman equation of the mean-field control problem under common noise. The rate is of order $1/N$ for the pathwise error on the solution v and of order $1/\sqrt{N}$ for the $L^2$ -error on its L -derivative $\partial_\mu v$ . The proof relies on backward stochastic differential equation techniques.
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