Localization errors in solving stochastic partial differential equations in the whole space
Gerencser M, Gyöngy I. 2017. Localization errors in solving stochastic partial differential equations in the whole space. Mathematics of Computation. 86(307), 2373–2397.
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Author
Gerencser, MateISTA;
Gyöngy, István
Department
Abstract
Cauchy problems with SPDEs on the whole space are localized to Cauchy problems on a ball of radius R. This localization reduces various kinds of spatial approximation schemes to finite dimensional problems. The error is shown to be exponentially small. As an application, a numerical scheme is presented which combines the localization and the space and time discretization, and thus is fully implementable.
Publishing Year
Date Published
2017-01-01
Journal Title
Mathematics of Computation
Volume
86
Issue
307
Page
2373 - 2397
ISSN
IST-REx-ID
Cite this
Gerencser M, Gyöngy I. Localization errors in solving stochastic partial differential equations in the whole space. Mathematics of Computation. 2017;86(307):2373-2397. doi:10.1090/mcom/3201
Gerencser, M., & Gyöngy, I. (2017). Localization errors in solving stochastic partial differential equations in the whole space. Mathematics of Computation. American Mathematical Society. https://doi.org/10.1090/mcom/3201
Gerencser, Mate, and István Gyöngy. “Localization Errors in Solving Stochastic Partial Differential Equations in the Whole Space.” Mathematics of Computation. American Mathematical Society, 2017. https://doi.org/10.1090/mcom/3201.
M. Gerencser and I. Gyöngy, “Localization errors in solving stochastic partial differential equations in the whole space,” Mathematics of Computation, vol. 86, no. 307. American Mathematical Society, pp. 2373–2397, 2017.
Gerencser M, Gyöngy I. 2017. Localization errors in solving stochastic partial differential equations in the whole space. Mathematics of Computation. 86(307), 2373–2397.
Gerencser, Mate, and István Gyöngy. “Localization Errors in Solving Stochastic Partial Differential Equations in the Whole Space.” Mathematics of Computation, vol. 86, no. 307, American Mathematical Society, 2017, pp. 2373–97, doi:10.1090/mcom/3201.
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