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Numerical methods for nonlinear stochastic differential equations driven by subdiffusion
arXiv cs.NA0 views
arXiv:2610.41550v1 Announce Type: new Abstract: Stochastic differential equations (SDEs) driven by subdiffusion see great applications in anomalous transport and asset price dynamics. Trusted numerical methods are essential for their application in practice. In this paper, for SDEs driven by subdiffusion with superlinear coefficients, we propose a brand-new explicit numerical method. The sharp convergence rate is proved with new techniques. The potential application of the proposed method in numerically solving a generalized Fokker-Planck equation is also illustrated. Numerical simulations are provided to demonstrate the theoretical results.
Source：https://arxiv.org/abs/2610.41550PreviousA well-balanced path-conservative discontinuous Galerkin method with generalized hydrostatic reconstruction for non-conservative balance lawsNextAn Efficient Randomized Hierarchical Tucker Decomposition
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