## 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 in 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 large-scale linear algebra.

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

.