On Computing Eigenvectors of Symmetric Tridiagonal Matrices

DOI10.1007/978-3-030-04088-8_9OpenAlexW2938099053MaRDI QIDQ3294691

Paul Van Dooren, Harold Taeter, Nicola Mastronardi

Publication date: 29 June 2020

Published in: Structured Matrices in Numerical Linear Algebra (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-030-04088-8_9

zbMATH Keywords

QR methodtridiagonal matriceseigenvalue computation

Mathematics Subject Classification ID

Numerical linear algebra (65Fxx) Numerical analysis (65-XX) Computer science (68-XX) Computer aspects of numerical algorithms (65Yxx) Linear and multilinear algebra; matrix theory (15-XX)

Related Items (3)

Computing Gaussian quadrature rules with high relative accuracy ⋮ Unnamed Item ⋮ Computing the eigenvectors of nonsymmetric tridiagonal matrices

Uses Software

• LAPACK

Cites Work

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• A Divide and Conquer method for the symmetric tridiagonal eigenproblem
• Multiple representations to compute orthogonal eigenvectors of symmetric tridiagonal matrices
• Inner deflation for symmetric tridiagonal matrices
• Improved Accuracy and Parallelism for MRRR-Based Eigensolvers---A Mixed Precision Approach
• Twisted Factorizations and qd-Type Transformations for the $\mbox{MR}^{3}$ Algorithm---New Representations and Analysis
• LAPACK Users' Guide
• Forward Instability of Tridiagonal QR
• A Divide-and-Conquer Algorithm for the Symmetric Tridiagonal Eigenproblem
• The $QR$ Steps with Perfect Shifts
• A Framework for the $MR^3$ Algorithm: Theory and Implementation
• Computing the Jordan Structure of an Eigenvalue

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