Analytical solutions to some generalized and polynomial eigenvalue problems

IF 0.8 Q2 MATHEMATICS Special Matrices Pub Date : 2020-07-16 DOI:10.1515/spma-2020-0135
Quanling Deng
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引用次数: 5

Abstract

Abstract It is well-known that the finite difference discretization of the Laplacian eigenvalue problem −Δu = λu leads to a matrix eigenvalue problem (EVP) Ax =λx where the matrix A is Toeplitz-plus-Hankel. Analytical solutions to tridiagonal matrices with various boundary conditions are given in a recent work of Strang and MacNamara. We generalize the results and develop analytical solutions to certain generalized matrix eigenvalue problems (GEVPs) Ax = λBx which arise from the finite element method (FEM) and isogeometric analysis (IGA). The FEM matrices are corner-overlapped block-diagonal while the IGA matrices are almost Toeplitz-plus-Hankel. In fact, IGA with a correction that results in Toeplitz-plus-Hankel matrices gives a better numerical method. In this paper, we focus on finding the analytical eigenpairs to the GEVPs while developing better numerical methods is our motivation. Analytical solutions are also obtained for some polynomial eigenvalue problems (PEVPs). Lastly, we generalize the eigenvector-eigenvalue identity (rediscovered and coined recently for EVPs) for GEVPs and derive some trigonometric identities.
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若干广义和多项式特征值问题的解析解
摘要众所周知,拉普拉斯特征值问题-Δu=λu的有限差分离散化导致了矩阵特征值问题(EVP)Ax=λx,其中矩阵a是Toeplitz加Hankel。Strang和MacNamara最近的工作给出了具有各种边界条件的三对角矩阵的解析解。我们推广了有限元法(FEM)和等几何分析(IGA)产生的某些广义矩阵特征值问题(GEVPs)Ax=λBx的结果,并给出了它们的解析解。FEM矩阵是角重叠块对角矩阵,而IGA矩阵几乎是Toeplitz加Hankel矩阵。事实上,经过Toeplitz加Hankel矩阵校正的IGA给出了一种更好的数值方法。在本文中,我们专注于寻找GEVP的分析本征对,而开发更好的数值方法是我们的动机。还得到了一些多项式特征值问题的解析解。最后,我们推广了GEVP的特征向量特征值恒等式(最近为EVP重新发现和创造),并推导了一些三角恒等式。
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来源期刊
Special Matrices
Special Matrices MATHEMATICS-
CiteScore
1.10
自引率
20.00%
发文量
14
审稿时长
8 weeks
期刊介绍: Special Matrices publishes original articles of wide significance and originality in all areas of research involving structured matrices present in various branches of pure and applied mathematics and their noteworthy applications in physics, engineering, and other sciences. Special Matrices provides a hub for all researchers working across structured matrices to present their discoveries, and to be a forum for the discussion of the important issues in this vibrant area of matrix theory. Special Matrices brings together in one place major contributions to structured matrices and their applications. All the manuscripts are considered by originality, scientific importance and interest to a general mathematical audience. The journal also provides secure archiving by De Gruyter and the independent archiving service Portico.
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