is_hermitian
¶
Checks if the matrix is a Hermitian matrix.
is_hermitian
¶
Check if matrix is Hermitian 1.
A Hermitian matrix is a complex square matrix that is equal to its own conjugate transpose.
Examples:
Consider the following matrix:
\[
A = \begin{pmatrix}
2 & 2 +1j & 4 \\
2 - 1j & 3 & 1j \\
4 & -1j & 1
\end{pmatrix}
\]
our function indicates that this is indeed a Hermitian matrix as it holds that
\[
A = A^*.
\]
import numpy as np
from toqito.matrix_props import is_hermitian
mat = np.array([[2, 2 + 1j, 4], [2 - 1j, 3, 1j], [4, -1j, 1]])
print(is_hermitian(mat))
True
Alternatively, the following example matrix \(B\) defined as
\[
B = \begin{pmatrix}
1 & 2 & 3 \\
4 & 5 & 6 \\
7 & 8 & 9
\end{pmatrix}
\]
is not Hermitian.
import numpy as np
from toqito.matrix_props import is_hermitian
mat = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
print(is_hermitian(mat))
False
Parameters:
-
mat(ndarray) –Matrix to check.
-
rtol(float, default:1e-05) –The relative tolerance parameter (default 1e-05).
-
atol(float, default:1e-08) –The absolute tolerance parameter (default 1e-08).
Returns:
-
bool–Return True if matrix is Hermitian, and False otherwise.
References
1 Wikipedia. Hermitian matrix. link.