In this paper, we present a unified approach to decomposing a special class of block tridiagonal matrices <i>K</i> (<i>α</i> ,<i>β</i> ) into block diagonal matrices using similar...In this paper, we present a unified approach to decomposing a special class of block tridiagonal matrices <i>K</i> (<i>α</i> ,<i>β</i> ) into block diagonal matrices using similarity transformations. The matrices <i>K</i> (<i>α</i> ,<i>β</i> )∈ <i>R</i><sup><i>pq</i>× <i>pq</i></sup> are of the form <i>K</i> (<i>α</i> ,<i>β</i> = block-tridiag[<i>β B</i>,<i>A</i>,<i>α B</i>] for three special pairs of (<i>α</i> ,<i>β</i> ): <i>K</i> (1,1), <i>K</i> (1,2) and <i>K</i> (2,2) , where the matrices <i>A</i> and <i>B</i>, <i>A</i>, <i>B</i>∈ <i>R</i><sup><i>p</i>× <i>q</i></sup> , are general square matrices. The decomposed block diagonal matrices <img src="Edit_00717830-3b3b-4856-8ecd-a9db983fef19.png" width="15" height="15" alt="" />(<i>α</i> ,<i>β</i> ) for the three cases are all of the form: <img src="Edit_71ffcd27-6acc-4922-b5e2-f4be15b9b8dc.png" width="15" height="15" alt="" />(<i>α</i> ,<i>β</i> ) = <i>D</i><sub>1</sub> (<i>α</i> ,<i>β</i> ) ⊕ <i>D</i><sub>2</sub> (<i>α</i> ,<i>β</i> ) ⊕---⊕ <i>D</i><sub>q</sub> (<i>α</i> ,<i>β</i> ) , where <i>D<sub>k</sub></i> (<i>α</i> ,<i>β</i> ) = <i>A</i>+ 2cos ( <i>θ<sub>k</sub></i> (<i>α</i> ,<i>β</i> )) <i>B</i>, in which <i>θ<sub>k</sub></i> (<i>α</i> ,<i>β</i> ) , k = 1,2, --- q , depend on the values of <i>α</i> and <i>β</i>. Our decomposition method is closely related to the classical fast Poisson solver using Fourier analysis. Unlike the fast Poisson solver, our approach decomposes <i>K</i> (<i>α</i> ,<i>β</i> ) into <i>q</i> diagonal blocks, instead of <i>p</i> blocks. Furthermore, our proposed approach does not require matrices <i>A</i> and <i>B</i> to be symmetric and commute, and employs only the eigenvectors of the tridiagonal matrix <i>T</i> (<i>α</i> ,<i>β</i> ) = tridiag[<i>β b</i>, <i>a</i>,<i>αb</i>] in a block form, where <i>a</i> and <i>b</i> are scalars. The transformation matrices, their inverses, and the explicit form of the decomposed block diagonal matrices are derived in this paper. Numerical examples and experiments are also presented to demonstrate the validity and usefulness of the approach. Due to the decoupled nature of the decomposed matrices, this approach lends itself to parallel and distributed computations for solving both linear systems and eigenvalue problems using multiprocessors.展开更多
In CAD/CAM, mesh rather than smooth surface is only needed sometimes. A mesh-generating method from permanence principle of Coons patch is developed. A new mesh point is defined through local small subpatch and all me...In CAD/CAM, mesh rather than smooth surface is only needed sometimes. A mesh-generating method from permanence principle of Coons patch is developed. A new mesh point is defined through local small subpatch and all mesh points are computed by a linear system with special symmetric block tridiagonal coefficient matrix. By simplification, the determinant of coefficient matrix is determined by determinants of submatrices. Condition of existence of solution is given. Whether coefficient matrix is singular can be judged by a simple polynomial function with the eigenvalue of submatrix as variable. Numerical examples demonstrate the effects of shape parameters.展开更多
In this paper,we consider using Schur complements to design preconditioners for twofold and block tridiagonal saddle point problems.One type of the preconditioners are based on the nested(or recursive)Schur complement...In this paper,we consider using Schur complements to design preconditioners for twofold and block tridiagonal saddle point problems.One type of the preconditioners are based on the nested(or recursive)Schur complement,the other is based on an additive type Schur complement after permuting the original saddle point systems.We analyze different preconditioners incorporating the exact Schur complements.We show that some of them will lead to positively stable preconditioned systems if proper signs are selected in front of the Schur complements.These positive-stable preconditioners outperform other preconditioners if the Schur complements are further approximated inexactly.Numerical experiments for a 3-field formulation of the Biot model are provided to verify our predictions.展开更多
文摘In this paper, we present a unified approach to decomposing a special class of block tridiagonal matrices <i>K</i> (<i>α</i> ,<i>β</i> ) into block diagonal matrices using similarity transformations. The matrices <i>K</i> (<i>α</i> ,<i>β</i> )∈ <i>R</i><sup><i>pq</i>× <i>pq</i></sup> are of the form <i>K</i> (<i>α</i> ,<i>β</i> = block-tridiag[<i>β B</i>,<i>A</i>,<i>α B</i>] for three special pairs of (<i>α</i> ,<i>β</i> ): <i>K</i> (1,1), <i>K</i> (1,2) and <i>K</i> (2,2) , where the matrices <i>A</i> and <i>B</i>, <i>A</i>, <i>B</i>∈ <i>R</i><sup><i>p</i>× <i>q</i></sup> , are general square matrices. The decomposed block diagonal matrices <img src="Edit_00717830-3b3b-4856-8ecd-a9db983fef19.png" width="15" height="15" alt="" />(<i>α</i> ,<i>β</i> ) for the three cases are all of the form: <img src="Edit_71ffcd27-6acc-4922-b5e2-f4be15b9b8dc.png" width="15" height="15" alt="" />(<i>α</i> ,<i>β</i> ) = <i>D</i><sub>1</sub> (<i>α</i> ,<i>β</i> ) ⊕ <i>D</i><sub>2</sub> (<i>α</i> ,<i>β</i> ) ⊕---⊕ <i>D</i><sub>q</sub> (<i>α</i> ,<i>β</i> ) , where <i>D<sub>k</sub></i> (<i>α</i> ,<i>β</i> ) = <i>A</i>+ 2cos ( <i>θ<sub>k</sub></i> (<i>α</i> ,<i>β</i> )) <i>B</i>, in which <i>θ<sub>k</sub></i> (<i>α</i> ,<i>β</i> ) , k = 1,2, --- q , depend on the values of <i>α</i> and <i>β</i>. Our decomposition method is closely related to the classical fast Poisson solver using Fourier analysis. Unlike the fast Poisson solver, our approach decomposes <i>K</i> (<i>α</i> ,<i>β</i> ) into <i>q</i> diagonal blocks, instead of <i>p</i> blocks. Furthermore, our proposed approach does not require matrices <i>A</i> and <i>B</i> to be symmetric and commute, and employs only the eigenvectors of the tridiagonal matrix <i>T</i> (<i>α</i> ,<i>β</i> ) = tridiag[<i>β b</i>, <i>a</i>,<i>αb</i>] in a block form, where <i>a</i> and <i>b</i> are scalars. The transformation matrices, their inverses, and the explicit form of the decomposed block diagonal matrices are derived in this paper. Numerical examples and experiments are also presented to demonstrate the validity and usefulness of the approach. Due to the decoupled nature of the decomposed matrices, this approach lends itself to parallel and distributed computations for solving both linear systems and eigenvalue problems using multiprocessors.
基金Supported by National Natural Science Foundation of China(No.60970097,No.11271376)
文摘In CAD/CAM, mesh rather than smooth surface is only needed sometimes. A mesh-generating method from permanence principle of Coons patch is developed. A new mesh point is defined through local small subpatch and all mesh points are computed by a linear system with special symmetric block tridiagonal coefficient matrix. By simplification, the determinant of coefficient matrix is determined by determinants of submatrices. Condition of existence of solution is given. Whether coefficient matrix is singular can be judged by a simple polynomial function with the eigenvalue of submatrix as variable. Numerical examples demonstrate the effects of shape parameters.
基金the NIH-RCMI(Grant No.347U54MD013376)the affliated project award from the Center for Equitable Artificial Intelligence and Machine Learning Systems at Morgan State University(Project ID 02232301)+3 种基金the National Science Foundation awards(Grant No.1831950).The work of G.Ju is supported in part by the National Key R&D Program of China(Grant No.2017YFB1001604)the National Natural Science Foundation of China(Grant No.11971221)the Shenzhen Sci-Tech Fund(Grant Nos.RCJC20200714114556020,JCYJ20170818153840322,JCYJ20190809150413261)the Guangdong Provincial Key Laboratory of Computational Science and Material Design(Grant No.2019B030301001).
文摘In this paper,we consider using Schur complements to design preconditioners for twofold and block tridiagonal saddle point problems.One type of the preconditioners are based on the nested(or recursive)Schur complement,the other is based on an additive type Schur complement after permuting the original saddle point systems.We analyze different preconditioners incorporating the exact Schur complements.We show that some of them will lead to positively stable preconditioned systems if proper signs are selected in front of the Schur complements.These positive-stable preconditioners outperform other preconditioners if the Schur complements are further approximated inexactly.Numerical experiments for a 3-field formulation of the Biot model are provided to verify our predictions.