Optimal rate of convergence for stochastic Burgers-type equations
File(s)
Published version
Author(s)
Hairer, M
Matetski, K
Type
Journal Article
Abstract
Recently, a solution theory for one-dimensional stochastic PDEs of Burgers type driven by space-time white noise was developed. In particular, it was shown that natural numerical approximations of these equations converge and that their convergence rate in the uniform topology is arbitrarily close to 1616. In the present article we improve this result in the case of additive noise by proving that the optimal rate of convergence is arbitrarily close to 1212.
Date Issued
2015-12-21
Date Acceptance
2015-04-20
Citation
Stochastics and Partial Differential Equations: Analysis and Computations, 2015, 4 (2), pp.402-437
ISSN
2194-0401
Publisher
Springer
Start Page
402
End Page
437
Journal / Book Title
Stochastics and Partial Differential Equations: Analysis and Computations
Volume
4
Issue
2
Copyright Statement
© The Author(s) 2015. This article is published with open access at Springerlink.com
License URL
Subjects
Science & Technology
Physical Sciences
Statistics & Probability
Mathematics
Burgers equation
Approximations
Rough paths
PARTIAL-DIFFERENTIAL EQUATIONS
LATTICE APPROXIMATIONS
DRIVEN
NOISE
Publication Status
Published