A New O(n2) Algorithm for the Symmetric Tridiagonal Eigenvalue/Eigenvector Problem

Abstract

Computing the eigenvalues and orthogonal eigenvectors of an n x n symmetric tridiagonal matrix is an important task that arises while solving any symmetric eigenproblem. All practical software requires O(n3) time to compute all the eigenvectors and ensure their orthogonality when eigenvalues are close. In the first part of this thesis we review earlier work and show how some existing implementations of inverse iteration can fail in surprising ways. The main contribution of this thesis is a new O(n^2), easily parallelizable algorithm for solving the tridiagonal eigenproblem. Three main advances lead to our new algorithm. A tridiagonal matrix is traditionally represented by its diagonal and off-diagonal elements. Our most important advance is in recognizing that its bidiagonal factors are "better" for computational purposes. The use of bidiagonals enables us to invoke a relative criterion to judge when eigenvalues are "close". The second advance comes by using multiple bidiagonal factorizations in order to compute different eigenvectors independently of each other. Thirdly, we use carefully chose dqds-like transformations as inner loops to compute eigenpairs that are highly accurate and "faithful" to the various bidiagonal representations. Orthogonality of the eigenvectors is a consequence of this accuracy. Only O(n) work per eigenpair is needed by our new algorithm. An interesting aspect of our work is that increased accuracy in the eigenvalues and eigenvectors obviates the need for explicit orthogonalization and leads to greater speed. We present timing and accuracy results comparing a computer implementation of our new algorithm with four existing EISPACK and LAPACK software routines. Our test-bed contains a variety of tridiagonal matrices, some coming from quantum chemistry applications. The numerical results demonstrate the superiority of our new algorithm.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1997
Accession Number
ADA637073

Entities

People

  • Inderjit S. Dhillon

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Algebra
  • Algorithms
  • Arithmetic Units
  • Biphenyl
  • Case Studies
  • Chemistry
  • Computers
  • Eigenvalues
  • Equations
  • Error Analysis
  • Iterations
  • Linear Algebra
  • Orthogonality
  • Perturbation Theory
  • Quantum Chemistry
  • Test Beds

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Graph Algorithms and Convex Optimization.
  • Marine Ecological Systems Migration

Technology Areas

  • Quantum Computing