Details and Options
- HermitianMatrixQ is also known as a self-adjoint.
- A matrix m is Hermitian if m==ConjugateTranspose[m].
- HermitianMatrixQ works for symbolic as well as numerical matrices.
- The following options can be given:
SameTest Automatic function to test equality of expressions Tolerance Automatic tolerance for approximate numbers
- For exact and symbolic matrices, the option SameTest->f indicates that two entries mij and mkl are taken to be equal if f[mij,mkl] gives True.
- For approximate matrices, the option Tolerance->t can be used to indicate that all entries Abs[mij]≤t are taken to be zero.
- For matrix entries Abs[mij]>t, equality comparison is done except for the last bits, where is $MachineEpsilon for MachinePrecision matrices and for matrices of Precision .
Examplesopen allclose all
Basic Examples (1)
For a real matrix, SymmetricMatrixQ gives the same result:
Approximate MachinePrecision matrix:
Adjust the option Tolerance to accept this matrix as Hermitian:
By using Table, it generates a Hermitian matrix:
Several statistical measures of complex data are Hermitian matrices, including Covariance:
Check that a matrix drawn from GaussianUnitaryMatrixDistribution is Hermitian:
Check that a matrix drawn from GaussianSymplecticMatrixDistribution is Hermitian:
Properties & Relations (10)
A matrix is Hermitian if m==ConjugateTranspose[m]:
Use Diagonal to pick out the diagonal elements:
Use AntihermitianMatrixQ to test whether a matrix is antihermitian:
Use NormalMatrixQ to test whether a matrix is normal:
Use Eigenvalues to find eigenvalues:
This also means that their CharacteristicPolynomial has real coefficients:
Use Eigenvectors to find eigenvectors:
A Hermitian matrix is always diagonalizable as tested with DiagonalizableMatrixQ: