Optimal rate of convergence for stochastic Burgers-type equations
作者： Martin Hairer , Kanstantsin Matetski
DOI: 10.1007/S40072-015-0067-5
关键词: Partial differential equation 、 Approximations of π 、 Type (model theory) 、 Rate of convergence 、 White noise 、 Noise (electronics) 、 Burgers' equation 、 Numerical analysis 、 Applied mathematics 、 Mathematics
摘要: Recently, a solution theory for one-dimensional stochastic PDEs of Burgers type driven by space-time white noise was developed. In particular, it shown that natural numerical approximations these equations converge and their convergence rate in the uniform topology is arbitrarily close to \(\frac{1}{6}\). present article we improve this result case additive proving optimal \(\frac{1}{2}\).
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