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arXiv 2305.03384math.NAcs.NA
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带奇异源项次扩散模型的高阶BDF卷积求积

High-order BDF convolution quadrature for subdiffusion models with a singular source term

Jiankang Shi, Minghua Chen

AI总结:

针对带弱奇异源项次扩散方程中高阶BDF方法阶数降低的问题,提出ID$m$-BDF$k$平滑方法,通过正则化奇异项并离散化方程,在源项弱奇异且初始数据不兼容时恢复$k$阶收敛性。

摘要:

反常扩散通常用次扩散方程来建模,该方程可能包含弱奇异源项。对于这种情况,许多主流的时间步进方法,包括高阶BDF格式的修正[{\sc Jin, Li, and Zhou}, SIAM J. Sci. Comput., 39 (2017), A3129--A3152],都可能会遭受严重的阶数降低。为了填补这一空白,我们提出了一种用于时间步进格式的平滑方法,其中奇异项通过使用$m$重积分微分微积分进行正则化,方程由$k$步BDF卷积求积进行离散化,称为ID$m$-BDF$k$方法。我们证明,即使源项是弱奇异的且初始数据不兼容,也能恢复所需的$k$阶收敛性。数值实验验证了理论结果。

英文摘要:

Anomalous diffusion is often modelled in terms of the subdiffusion equation, which can involve a weakly singular source term. For this case, many predominant time stepping methods, including the correction of high-order BDF schemes [{\sc Jin, Li, and Zhou}, SIAM J. Sci. Comput., 39 (2017), A3129--A3152], may suffer from a severe order reduction. To fill in this gap, we propose a smoothing method for time stepping schemes, where the singular term is regularized by using a $m$-fold integral-differential calculus and the equation is discretized by the $k$-step BDF convolution quadrature, called ID$m$-BDF$k$ method. We prove that the desired $k$th-order convergence can be recovered even if the source term is a weakly singular and the initial data is not compatible. Numerical experiments illustrate the theoretical results.

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