吉林国家应用数学中心Colloquium:Double-parameter regularization for solving the backward diffusion problem with parallel-in-time algorithm
报 告 人: 刘继军教授
所在单位: Southeast University & Nanjing Center for Applied Mathematics
报告地点: 正新楼209
报告时间: 2024-08-06 10:00:00
报告简介:

We propose a double-parameter regularization scheme for dealing with the backward diffusion process. Considering the smoothing effect of Yosida approximation for PDE, we propose to regularize this ill-posed problem by modifying original governed system in terms of a pseudoparabolic equation together with a quasi-boundary condition simultaneously, which consequently contains two regularizing parameters. Theoretically, we establish the optimal error estimates between the regularizing solution and the exact one in terms of suitable choice strategy for the regularizing parameters, under a-priori regularity assumptions on the exact solution. The a-posteriori choice strategy for the regularizing parameters based on the discrepancy principle is also studied. To weaken the heavy computational cost for solving the discrete nonsymmetric linear regularizing system by finite difference scheme, especially in higher spatial dimensional cases, the block divide-and-conquer method together with the properties of the Schur complement is applied to decompose the linear system into two half-size linear systems, one of which can be solved by the diagonalization technique, and consequently an efficient parallel-in-time algorithm originally developed for direct problem is applicable. Our proposed method is of much lower complexity than the standard solver for the corresponding linear system. Finally, some numerical examples are presented to verify the efficiency of our proposed method.

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主讲人简介:
刘继军,博士。东南大学二级教授,博士研究生导师,享受国务院政府特殊津贴专家。2009年12月至2014年11月任东南大学数学系主任、东南大学理学部副主任。现任南京应用数学中心副主任。长期从事数学物理反问题、波场散射与逆散射、图像处理、大规模科学计算和介质成像的数学理论和方法的研究。主持完成国家自然科学基金重大研究计划、面上项目、国际合作项目、天元基金、教育部博士点基金、江苏省自然科学基金等项目的研究。已发表论文130余篇,在科学出版社信息与计算科学丛书出版学术专著2本。应邀担任多个国际学术会议的组委会委员、学术委员会委员、大会报告人。反问题研究学术刊物JIIP编委。获江苏省教学成果一等奖,教育部自然科学二等奖。