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PreprintarXiv licencearXiv

Numerical methods for nonlinear stochastic differential equations driven by subdiffusion

  • Qian Guo
  • Wei Liu
  • Ruchun Zuo
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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.

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Cite

BibTeXRIS
BibTeX
@misc{guo2026numerical,
  title = {{Numerical methods for nonlinear stochastic differential equations driven by subdiffusion}},
  author = {Qian Guo and Wei Liu and Ruchun Zuo},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.41550},
  eprint = {2610.41550},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.41550},
}
RIS
TY  - UNPB
TI  - Numerical methods for nonlinear stochastic differential equations driven by subdiffusion
AU  - Qian Guo
AU  - Wei Liu
AU  - Ruchun Zuo
PY  - 2026
DA  - 2026/10/30
PB  - arXiv
DO  - 10.48550/arxiv.2610.41550
UR  - https://arxiv.org/abs/2610.41550
AB  - 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.
ER  -