Lower and upper bounds for strong approximation errors for numerical approximations of stochastic heat equations

@article{Becker2018LowerAU,
  title={Lower and upper bounds for strong approximation errors for numerical approximations of stochastic heat equations},
  author={Sebastian Becker and Benjamin Gess and Arnulf Jentzen and Peter E. Kloeden},
  journal={BIT Numerical Mathematics},
  year={2018},
  pages={1-17}
}
  • Sebastian Becker, Benjamin Gess, +1 author Peter E. Kloeden
  • Published 2018
  • Mathematics, Computer Science
  • BIT Numerical Mathematics
  • This article establishes optimal upper and lower error estimates for strong full-discrete numerical approximations of the stochastic heat equation driven by space-time white noise. Thereby, this work proves the optimality of the strong convergence rates for certain full-discrete approximations of stochastic Allen–Cahn equations with space-time white noise which have been obtained in a recent previous work of the authors of this article. 

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