Demonstrates convergence to invariant measures in McKean-Vlasov equations, implying a novel numerical approach for complex systems.
To approximate the invariant measure of McKean-Vlasov stochastic differential equation (MVSDE) with highly nonlinear drift and diffusion coefficients, this paper constructs the backward Euler scheme for the corresponding self-interacting stochastic differential equation (SDE), which depends on both current and historical information. Then the empirical measure of the numerical solution for self-interacting SDE is proved to converge to the invariant measure of the original MVSDE under the Wasserstein distance. The numerical simulations are provided to support this finding.
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Liu et al. (2026) studied this question.
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