Forward Propagation of Low Discrepancy Through McKean-Vlasov Dynamics: From QMC to MLQMC
<|reference_start|>Forward Propagation of Low Discrepancy Through McKean-Vlasov Dynamics: From QMC to MLQMC: This work develops a particle system addressing the approximation of McKean-Vlasov stochastic differential equations (SDEs). The novelty of the approach lies in involving low discrepancy sequences nontrivially in the construction of a particle system with coupled noise and initial conditions. Weak convergence for SDEs with additive noise is proven. A numerical study demonstrates that the novel approach presented here doubles the respective convergence rates for weak and strong approximation of the mean-field limit, compared with the standard particle system. These rates are proven in the simplified setting of a mean-field ordinary differential equation in terms of appropriate bounds involving the star discrepancy for low discrepancy sequences with a group structure, such as Rank-1 lattice points. This construction nontrivially provides an antithetic multilevel quasi-Monte Carlo estimator. An asymptotic error analysis reveals that the proposed approach outperforms methods based on the classic particle system with independent initial conditions and noise.<|reference_end|>
@article{rached2024forward,
    title={Forward Propagation of Low Discrepancy Through McKean-Vlasov Dynamics:
  From QMC to MLQMC},
    author={Nadhir Ben Rached, Abdul-Lateef Haji-Ali, Ra'ul Tempone, Leon Wilkosz},
    journal={arXiv preprint arXiv:2409.09821},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.09821},
    primaryClass={math.NA cs.NA}
}