- Skew-Hermitian matrix
In
linear algebra , asquare matrix (or more generally, a linear transformation from a complexvector space with asesquilinear norm to itself) "A" is said to be skew-Hermitian or antihermitian if itsconjugate transpose "A"* is also its negative. That is, if it satisfies the relation::"A"* = −"A"or in component form, if "A" = ("a""i,j")::for all "i" and "j".Examples
For example, the following matrix is skew-Hermitian::
Properties
* The eigenvalues of a skew-Hermitian matrix are all purely imaginary. Furthermore, skew-Hermitian matrices are normal. Hence they are diagonalizable and their eigenvectors for distinct eigenvalues must be orthogonal.
* All entries on themain diagonal of a skew-Hermitian matrix have to be pure imaginary, ie. on the imaginary axis. This definition includes the number "0i".
* If "A" is skew-Hermitian, then "iA" is Hermitian
* If "A, B" are skew-Hermitian, then "aA + bB" is skew-Hermitian for all real scalars "a, b".
* If "A" is skew-Hermitian, then "A""2k" is Hermitian for all positive integers "k".
* If "A" is skew-Hermitian, then "A" raised to an odd power is skew-Hermitian.
* If "A" is skew-Hermitian, then e"A" is unitary.
* The difference of a matrix and itsconjugate transpose () is skew-Hermitian.
* An arbitrary (square) matrix "C" can be written as the sum of a Hermitian matrix "A" and a skew-Hermitian matrix "B":::
* The space of skew-Hermitian matrices forms theLie algebra u("n") of theLie group U("n").ee also
*
skew-symmetric matrix
*Hermitian matrix
*normal matrix
*unitary matrix
Wikimedia Foundation. 2010.