{"title":"具有有限平滑特性的亚扩散方程的高阶分裂有限元方法","authors":"Buyang Li, Zongze Yang, Zhi Zhou","doi":"10.1090/mcom/3944","DOIUrl":null,"url":null,"abstract":"<p>In contrast with the diffusion equation which smoothens the initial data to <inline-formula content-type=\"math/mathml\"> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" alttext=\"upper C Superscript normal infinity\"> <mml:semantics> <mml:msup> <mml:mi>C</mml:mi> <mml:mi mathvariant=\"normal\">∞<!-- ∞ --></mml:mi> </mml:msup> <mml:annotation encoding=\"application/x-tex\">C^\\infty</mml:annotation> </mml:semantics> </mml:math> </inline-formula> for <inline-formula content-type=\"math/mathml\"> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" alttext=\"t greater-than 0\"> <mml:semantics> <mml:mrow> <mml:mi>t</mml:mi> <mml:mo>></mml:mo> <mml:mn>0</mml:mn> </mml:mrow> <mml:annotation encoding=\"application/x-tex\">t>0</mml:annotation> </mml:semantics> </mml:math> </inline-formula> (away from the corners/edges of the domain), the subdiffusion equation only exhibits limited spatial regularity. As a result, one generally cannot expect high-order accuracy in space in solving the subdiffusion equation with nonsmooth initial data. In this paper, a new splitting of the solution is constructed for high-order finite element approximations to the subdiffusion equation with nonsmooth initial data. The method is constructed by splitting the solution into two parts, i.e., a time-dependent smooth part and a time-independent nonsmooth part, and then approximating the two parts via different strategies. The time-dependent smooth part is approximated by using high-order finite element method in space and convolution quadrature in time, while the steady nonsmooth part could be approximated by using smaller mesh size or other methods that could yield high-order accuracy. Several examples are presented to show how to accurately approximate the steady nonsmooth part, including piecewise smooth initial data, Dirac–Delta point initial data, and Dirac measure concentrated on an interface. The argument could be directly extended to subdiffusion equations with nonsmooth source data. Extensive numerical experiments are presented to support the theoretical analysis and to illustrate the performance of the proposed high-order splitting finite element methods.</p>","PeriodicalId":18456,"journal":{"name":"Mathematics of Computation","volume":"23 1","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"High-order splitting finite element methods for the subdiffusion equation with limited smoothing property\",\"authors\":\"Buyang Li, Zongze Yang, Zhi Zhou\",\"doi\":\"10.1090/mcom/3944\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In contrast with the diffusion equation which smoothens the initial data to <inline-formula content-type=\\\"math/mathml\\\"> <mml:math xmlns:mml=\\\"http://www.w3.org/1998/Math/MathML\\\" alttext=\\\"upper C Superscript normal infinity\\\"> <mml:semantics> <mml:msup> <mml:mi>C</mml:mi> <mml:mi mathvariant=\\\"normal\\\">∞<!-- ∞ --></mml:mi> </mml:msup> <mml:annotation encoding=\\\"application/x-tex\\\">C^\\\\infty</mml:annotation> </mml:semantics> </mml:math> </inline-formula> for <inline-formula content-type=\\\"math/mathml\\\"> <mml:math xmlns:mml=\\\"http://www.w3.org/1998/Math/MathML\\\" alttext=\\\"t greater-than 0\\\"> <mml:semantics> <mml:mrow> <mml:mi>t</mml:mi> <mml:mo>></mml:mo> <mml:mn>0</mml:mn> </mml:mrow> <mml:annotation encoding=\\\"application/x-tex\\\">t>0</mml:annotation> </mml:semantics> </mml:math> </inline-formula> (away from the corners/edges of the domain), the subdiffusion equation only exhibits limited spatial regularity. As a result, one generally cannot expect high-order accuracy in space in solving the subdiffusion equation with nonsmooth initial data. In this paper, a new splitting of the solution is constructed for high-order finite element approximations to the subdiffusion equation with nonsmooth initial data. The method is constructed by splitting the solution into two parts, i.e., a time-dependent smooth part and a time-independent nonsmooth part, and then approximating the two parts via different strategies. The time-dependent smooth part is approximated by using high-order finite element method in space and convolution quadrature in time, while the steady nonsmooth part could be approximated by using smaller mesh size or other methods that could yield high-order accuracy. Several examples are presented to show how to accurately approximate the steady nonsmooth part, including piecewise smooth initial data, Dirac–Delta point initial data, and Dirac measure concentrated on an interface. The argument could be directly extended to subdiffusion equations with nonsmooth source data. Extensive numerical experiments are presented to support the theoretical analysis and to illustrate the performance of the proposed high-order splitting finite element methods.</p>\",\"PeriodicalId\":18456,\"journal\":{\"name\":\"Mathematics of Computation\",\"volume\":\"23 1\",\"pages\":\"\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-02-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mathematics of Computation\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1090/mcom/3944\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematics of Computation","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1090/mcom/3944","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
摘要
扩散方程在 t > 0 t>0 时(远离域的角落/边缘)将初始数据平滑为 C ∞ C^\infty,而亚扩散方程只表现出有限的空间规则性。因此,在用非光滑初始数据求解亚扩散方程时,一般不能期望空间上的高阶精度。本文为非光滑初始数据的亚扩散方程的高阶有限元近似求解构建了一种新的求解分割方法。该方法通过将解拆分为两部分,即与时间相关的平稳部分和与时间无关的非平稳部分,然后通过不同的策略对两部分进行逼近。与时间相关的平滑部分采用空间高阶有限元法和时间卷积正交法进行逼近,而稳定的非平滑部分可采用较小的网格尺寸或其他可获得高阶精度的方法进行逼近。本文举了几个例子来说明如何精确逼近稳定非光滑部分,包括片状光滑初始数据、Dirac-Delta 点初始数据和集中在界面上的 Dirac 量。该论证可直接扩展到具有非光滑源数据的子扩散方程。为了支持理论分析并说明所提出的高阶分裂有限元方法的性能,我们进行了大量的数值实验。
High-order splitting finite element methods for the subdiffusion equation with limited smoothing property
In contrast with the diffusion equation which smoothens the initial data to C∞C^\infty for t>0t>0 (away from the corners/edges of the domain), the subdiffusion equation only exhibits limited spatial regularity. As a result, one generally cannot expect high-order accuracy in space in solving the subdiffusion equation with nonsmooth initial data. In this paper, a new splitting of the solution is constructed for high-order finite element approximations to the subdiffusion equation with nonsmooth initial data. The method is constructed by splitting the solution into two parts, i.e., a time-dependent smooth part and a time-independent nonsmooth part, and then approximating the two parts via different strategies. The time-dependent smooth part is approximated by using high-order finite element method in space and convolution quadrature in time, while the steady nonsmooth part could be approximated by using smaller mesh size or other methods that could yield high-order accuracy. Several examples are presented to show how to accurately approximate the steady nonsmooth part, including piecewise smooth initial data, Dirac–Delta point initial data, and Dirac measure concentrated on an interface. The argument could be directly extended to subdiffusion equations with nonsmooth source data. Extensive numerical experiments are presented to support the theoretical analysis and to illustrate the performance of the proposed high-order splitting finite element methods.
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