13. Eigensystems

This chapter describes functions for computing eigenvalues and eigenvectors of matrices. There are routines for real symmetric and complex hermitian matrices, and eigenvalues can be computed with or without eigenvectors. The algorithms used are symmetric bidiagonalization followed by QR reduction.

These routines are intended for "small" systems where simple algorithms are acceptable. Anyone interested finding eigenvalues and eigenvectors of large matrices will want to use the sophisticated routines found in LAPACK. The Fortran version of LAPACK is recommended as the standard package for linear algebra.

The functions described in this chapter are declared in the header file `gsl_eigen.h'.

13.1 Real Symmetric Matrices

13.2 Complex Hermitian Matrices

13.3 Sorting Eigenvalues and Eigenvectors

13.4 Examples

13.5 References and Further Reading

This document was generated by Michael Stenner on February, 14 2002 using texi2html

13.1 Real Symmetric Matrices
13.2 Complex Hermitian Matrices
13.3 Sorting Eigenvalues and Eigenvectors
13.4 Examples
13.5 References and Further Reading