Numerical analysis for subdiffusion problem with non-positive memory
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866908353683259392 |
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| author | Qiu, Wenlin Zheng, Xiangcheng |
| author_facet | Qiu, Wenlin Zheng, Xiangcheng |
| contents | This work considers the subdiffusion problem with non-positive memory, which not only arises from physical laws with memory, but could be transformed from sophisticated models such as subdiffusion or subdiffusive Fokker-Planck equation with variable exponent. We apply the non-uniform L1 formula and interpolation quadrature to discretize the fractional derivative and the memory term, respectively, and then adopt the complementary discrete convolution kernel approach to prove the stability and first-order temporal accuracy of the scheme. The main difficulty in numerical analysis lies in the non-positivity of the kernel and its coupling with the complementary discrete convolution kernel (such that different model exponents are also coupled), and the results extend those in [Chen, Thomée and Wahlbin, Math. Comp. 1992] to the subdiffusive case. Numerical experiments are performed to substantiate the theoretical results. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2505_04924 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Numerical analysis for subdiffusion problem with non-positive memory Qiu, Wenlin Zheng, Xiangcheng Numerical Analysis 45K05, 65M12, 65M60 This work considers the subdiffusion problem with non-positive memory, which not only arises from physical laws with memory, but could be transformed from sophisticated models such as subdiffusion or subdiffusive Fokker-Planck equation with variable exponent. We apply the non-uniform L1 formula and interpolation quadrature to discretize the fractional derivative and the memory term, respectively, and then adopt the complementary discrete convolution kernel approach to prove the stability and first-order temporal accuracy of the scheme. The main difficulty in numerical analysis lies in the non-positivity of the kernel and its coupling with the complementary discrete convolution kernel (such that different model exponents are also coupled), and the results extend those in [Chen, Thomée and Wahlbin, Math. Comp. 1992] to the subdiffusive case. Numerical experiments are performed to substantiate the theoretical results. |
| title | Numerical analysis for subdiffusion problem with non-positive memory |
| topic | Numerical Analysis 45K05, 65M12, 65M60 |
| url | https://arxiv.org/abs/2505.04924 |