Geometric Ergodicity and Strong Error Estimates for Tamed Schemes of Super-linear SODEs
Abstract We construct a family of explicit tamed Euler–Maruyama (TEM) schemes, which can preserve the same Lyapunov function for super-linear stochastic ordinary differential equations (SODEs) driven by multiplicative noise. These TEM schemes are shown to inherit the geometric ergodicity of the considered SODEs and converge with optimal strong convergence orders. Numerical experiments verify our theoretical results.
Authors
- Zhihui Liu (ORCID: https://orcid.org/0000-0003-0890-623X)
- Xiao-Ming Wu (ORCID: https://orcid.org/0000-0002-3130-0554)
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Southern University of Science and Technology (CN)
Publication Details
- Journal
- BIT Numerical Mathematics
- Published
- 2026-07-27
- DOI
- https://doi.org/10.1007/s10543-026-01147-3
- Primary Topic
- Numerical methods for differential equations
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Basic and Applied Basic Research Foundation of Guangdong Province