Computing rough solutions of the KdV equation below ${\bf L^2}$
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866909662085906432 |
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| author | Cao, Jiachuan Li, Buyang Wu, Yifei Yao, Fangyan |
| author_facet | Cao, Jiachuan Li, Buyang Wu, Yifei Yao, Fangyan |
| contents | We establish a novel numerical and analytical framework for solving the Korteweg--de Vries (KdV) equation in the negative Sobolev spaces, where classical numerical methods fail due to their reliance on high regularity and inability to control nonlinear interactions at low regularities. Numerical analysis is established by combining a continuous reformulation of the numerical scheme, the Bourgain-space estimates for the continuous reformulation, and a rescaling strategy that reduces the reformulated problem to a small initial value problem, which allow us to bridge a critical gap between numerical analysis and theoretical well-posedness by designing the first numerical method capable of solving the KdV equation in the negative Sobolev spaces. The numerical scheme is proved to have nearly optimal-order convergence with respect to the spatial degrees of freedom in the $H^{-\frac{1}{2}}$ norm for initial data in $H^s$, with $-\frac{1}{2} < s \leq 0$, a result unattainable by existing numerical methods. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2506_21969 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Computing rough solutions of the KdV equation below ${\bf L^2}$ Cao, Jiachuan Li, Buyang Wu, Yifei Yao, Fangyan Numerical Analysis 65M12, 65M15, 65M70, 35Q53 We establish a novel numerical and analytical framework for solving the Korteweg--de Vries (KdV) equation in the negative Sobolev spaces, where classical numerical methods fail due to their reliance on high regularity and inability to control nonlinear interactions at low regularities. Numerical analysis is established by combining a continuous reformulation of the numerical scheme, the Bourgain-space estimates for the continuous reformulation, and a rescaling strategy that reduces the reformulated problem to a small initial value problem, which allow us to bridge a critical gap between numerical analysis and theoretical well-posedness by designing the first numerical method capable of solving the KdV equation in the negative Sobolev spaces. The numerical scheme is proved to have nearly optimal-order convergence with respect to the spatial degrees of freedom in the $H^{-\frac{1}{2}}$ norm for initial data in $H^s$, with $-\frac{1}{2} < s \leq 0$, a result unattainable by existing numerical methods. |
| title | Computing rough solutions of the KdV equation below ${\bf L^2}$ |
| topic | Numerical Analysis 65M12, 65M15, 65M70, 35Q53 |
| url | https://arxiv.org/abs/2506.21969 |