Volume 21, Issue 5
An Inverse Eigenvalue Problem for Jacobi Matrices
DOI:

J. Comp. Math., 21 (2003), pp. 569-584

Published online: 2003-10

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• Abstract

Let $T_{1,n}$ be an $n\times n$ unreduced symmetric tridiagonal matrix with eigenvalues $$\lambda_1<\lambda_2<\cdots<\lambda_n.$$ and $$W_k=\left(\begin{array}{cc} T_{1,k-1} & 0 \ 0 & T_{k+1,n} \end{array}\right)$$ is an $(n-1)\times(n-1)$ submatrix by deleting the $k^{th}$ row and $k^{th}$ column, $k=1,2,\ldots,n$ from $T_n$.\let $$\mu_1\leq\mu_2\leq\cdots\leq\mu_{k-1}$$ be the eigenvalues of $T_{1,k-1}$ and $$\mu_k\leq\mu_{k+1}\leq\cdots\leq\mu_{n-1}$$ be the eigenvalues of $T_{k+1,n}$.\\A new inverse eigenvalues problem has put forward as follows: How do we construct an unreduced symmetric tridiagonal matrix $T_{1,n}$, if we only know the spectral data: the eigenvalues of $T_{1,n}$, the eigenvalues of $T_{1,k-1}$ and the eigenvalues of $T_{k+1,n}$?\\Namely if we only know the data:$\lambda_1,\lambda_2,\cdots,\lambda_n,\mu_1,\mu_2,\cdots,\mu_{k-1}$ and $\mu_k,\mu_{k+1},\cdots,\mu_{n-1}$ how do we find the matrix $T_{1,n}$? Anecessary and sufficient condition and an algorithm of solving such problem, are given in this paper.

• Keywords

Symmetric tridiagonal matrix Jacobi matrix Eigenvalue problem Inverse eigenvalue problem

@Article{JCM-21-569, author = {}, title = {An Inverse Eigenvalue Problem for Jacobi Matrices}, journal = {Journal of Computational Mathematics}, year = {2003}, volume = {21}, number = {5}, pages = {569--584}, abstract = { Let $T_{1,n}$ be an $n\times n$ unreduced symmetric tridiagonal matrix with eigenvalues $$\lambda_1<\lambda_2<\cdots<\lambda_n.$$ and $$W_k=\left(\begin{array}{cc} T_{1,k-1} & 0 \ 0 & T_{k+1,n} \end{array}\right)$$ is an $(n-1)\times(n-1)$ submatrix by deleting the $k^{th}$ row and $k^{th}$ column, $k=1,2,\ldots,n$ from $T_n$.\let $$\mu_1\leq\mu_2\leq\cdots\leq\mu_{k-1}$$ be the eigenvalues of $T_{1,k-1}$ and $$\mu_k\leq\mu_{k+1}\leq\cdots\leq\mu_{n-1}$$ be the eigenvalues of $T_{k+1,n}$.\\A new inverse eigenvalues problem has put forward as follows: How do we construct an unreduced symmetric tridiagonal matrix $T_{1,n}$, if we only know the spectral data: the eigenvalues of $T_{1,n}$, the eigenvalues of $T_{1,k-1}$ and the eigenvalues of $T_{k+1,n}$?\\Namely if we only know the data:$\lambda_1,\lambda_2,\cdots,\lambda_n,\mu_1,\mu_2,\cdots,\mu_{k-1}$ and $\mu_k,\mu_{k+1},\cdots,\mu_{n-1}$ how do we find the matrix $T_{1,n}$? Anecessary and sufficient condition and an algorithm of solving such problem, are given in this paper. }, issn = {1991-7139}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jcm/8888.html} }
TY - JOUR T1 - An Inverse Eigenvalue Problem for Jacobi Matrices JO - Journal of Computational Mathematics VL - 5 SP - 569 EP - 584 PY - 2003 DA - 2003/10 SN - 21 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jcm/8888.html KW - Symmetric tridiagonal matrix KW - Jacobi matrix KW - Eigenvalue problem KW - Inverse eigenvalue problem AB - Let $T_{1,n}$ be an $n\times n$ unreduced symmetric tridiagonal matrix with eigenvalues $$\lambda_1<\lambda_2<\cdots<\lambda_n.$$ and $$W_k=\left(\begin{array}{cc} T_{1,k-1} & 0 \ 0 & T_{k+1,n} \end{array}\right)$$ is an $(n-1)\times(n-1)$ submatrix by deleting the $k^{th}$ row and $k^{th}$ column, $k=1,2,\ldots,n$ from $T_n$.\let $$\mu_1\leq\mu_2\leq\cdots\leq\mu_{k-1}$$ be the eigenvalues of $T_{1,k-1}$ and $$\mu_k\leq\mu_{k+1}\leq\cdots\leq\mu_{n-1}$$ be the eigenvalues of $T_{k+1,n}$.\\A new inverse eigenvalues problem has put forward as follows: How do we construct an unreduced symmetric tridiagonal matrix $T_{1,n}$, if we only know the spectral data: the eigenvalues of $T_{1,n}$, the eigenvalues of $T_{1,k-1}$ and the eigenvalues of $T_{k+1,n}$?\\Namely if we only know the data:$\lambda_1,\lambda_2,\cdots,\lambda_n,\mu_1,\mu_2,\cdots,\mu_{k-1}$ and $\mu_k,\mu_{k+1},\cdots,\mu_{n-1}$ how do we find the matrix $T_{1,n}$? Anecessary and sufficient condition and an algorithm of solving such problem, are given in this paper.