Defective matrix

In linear algebra, a defective matrix is a square matrix that does not have a complete basis of eigenvectors, and is therefore not diagonalizable. In particular, for an $n\times n$ matrix, the matrix is defective if and only if it does not have n linearly independent eigenvectors. A complete basis is formed by augmenting the eigenvectors with generalized eigenvectors, which are necessary for solving defective systems of ordinary differential equations and other problems.

A defective matrix always has fewer than n distinct eigenvalues, since distinct eigenvalues always have linearly independent eigenvectors. In particular, a defective matrix has one or more eigenvalues λ with algebraic multiplicity $m>1$ (that is, they are multiple roots of the characteristic polynomial), but fewer than m linearly independent eigenvectors associated with λ. However, every eigenvalue with multiplicity m always has m linearly independent generalized eigenvectors.

A Hermitian matrix (or the special case of a real symmetric matrix) or a unitary matrix is never defective; more generally, a normal matrix (which includes Hermitian and unitary as special cases) is never defective.

Example

A simple example of a defective matrix is:

${\begin{bmatrix}1&1\\0&1\end{bmatrix}}$

which has a double eigenvalue of 1 but only one distinct eigenvector

${\begin{bmatrix}1\\0\end{bmatrix}}$

(and constant multiples thereof).

Another example of a defective matrix (with eigenvalues of 3,3) is:

${\begin{bmatrix}3&1\\0&3\end{bmatrix}}$

See also

• Jordan normal form
• Generalized eigenvector

References

• Gilbert Strang, Linear Algebra and Its Applications, 3rd ed. (Harcourt: San Diego, 1988).