Optimal rate of convergence for approximations of SPDEs with non-regular drift
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2021
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| _version_ | 1866910617602883584 |
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| author | Butkovsky, Oleg Dareiotis, Konstantinos Gerencsér, Máté |
| author_facet | Butkovsky, Oleg Dareiotis, Konstantinos Gerencsér, Máté |
| contents | A fully discrete finite difference scheme for stochastic reaction-diffusion equations driven by a $1+1$-dimensional white noise is studied. The optimal strong rate of convergence is proved without posing any regularity assumption on the non-linear reaction term. The proof relies on stochastic sewing techniques. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2110_06148 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | Optimal rate of convergence for approximations of SPDEs with non-regular drift Butkovsky, Oleg Dareiotis, Konstantinos Gerencsér, Máté Probability Numerical Analysis Analysis of PDEs 60H15, 60H50, 60H35 A fully discrete finite difference scheme for stochastic reaction-diffusion equations driven by a $1+1$-dimensional white noise is studied. The optimal strong rate of convergence is proved without posing any regularity assumption on the non-linear reaction term. The proof relies on stochastic sewing techniques. |
| title | Optimal rate of convergence for approximations of SPDEs with non-regular drift |
| topic | Probability Numerical Analysis Analysis of PDEs 60H15, 60H50, 60H35 |
| url | https://arxiv.org/abs/2110.06148 |