AntihermitianMatrixQ
Details and Options
- AntihermitianMatrixQ is also known as skew-Hermitian.
- A matrix m is antihermitian if m-ConjugateTranspose[m].
- AntihermitianMatrixQ 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 .
Examples
open allclose allBasic Examples (2)
Scope (10)
Basic Uses (6)
Test if a real machine-precision matrix is antihermitian:
A real antihermitian matrix is also antisymmetric:
Test if a complex matrix is antihermitian:
A complex antihermitian matrix has antisymmetric real part and symmetric imaginary part:
Test if an exact matrix is antihermitian:
Make the matrix antihermitian:
Use AntihermitianMatrixQ with an arbitrary-precision matrix:
A random matrix is typically not antihermitian:
Use AntihermitianMatrixQ with a symbolic matrix:
The matrix becomes antihermitian when c=-b and the real part of a and d is zero:
AntihermitianMatrixQ works efficiently with large numerical matrices:
Special Matrices (4)
Use AntihermitianMatrixQ with sparse matrices:
Use AntihermitianMatrixQ with structured matrices:
Use with a QuantityArray structured matrix:
The identity matrix is not antihermitian:
Make it antihermitian by multiplying with :
HilbertMatrix is not antihermitian:
Options (2)
SameTest (1)
This matrix is antihermitian for a positive real , but AntihermitianMatrixQ gives False:
Use the option SameTest to get the correct answer:
Tolerance (1)
A complex-valued antihermitian matrix with some random perturbation of order :
Adjust the option Tolerance to accept this matrix as antihermitian:
The norm of the difference between the matrix and its conjugate transpose with minus sign:
Applications (6)
Any matrix generated from an antihermitian function is antihermitian:
The function is antihermitian:
Using Table generates an antihermitian matrix:
SymmetrizedArray can generate matrices (and general arrays) with symmetries:
Convert back to an ordinary matrix using Normal:
Consider the family of rotation matrices corresponding to rotation by in the plane:
The logarithmic derivative is antihermitian:
This will be true of any 1-parameter family of rotations:
Stone's theorem says that any 1-parameter family of unitary matrices has an antihermitian logarithmic derivative. Verify the theorem for the following family of matrices:
First, confirm the matrices are unitary under the assumption that is real:
Compute the logarithmic derivative:
Verify the result is antihermitian:
In quantum mechanics, time evolution is represented by a 1-parameter family of unitary matrices . times the logarithmic derivative of is a Hermitian matrix called the Hamiltonian or energy operator . Its eigenvalues represent the possible energies of the system. For the following time evolution, compute the Hamiltonian and possible energies:
First, verify the matrices are, in fact, unitary:
Compute the logarithmic derivative:
Verify that the matrix is Hermitian:
Its real eigenvalues represent the possible energies:
The exponential MatrixExp[v] of an antihermitian matrix is unitary. Define a matrix function through its differential equation with initial value , and show that the solution is unitary:
Solve and check that the resulting matrix is unitary at each time:
With default settings, you get approximately unitary matrices:
Properties & Relations (15)
AntihermitianMatrixQ[x] trivially returns False for any x that is not a matrix:
A matrix is antihermitian if m==-ConjugateTranspose[m]:
An antihermitian matrix must have pure imaginary diagonal elements:
Use Diagonal to pick out the diagonal elements:
A real-valued antisymmetric matrix is antihermitian:
But a complex-valued symmetric matrix may not be:
Use Symmetrize with the symmetry Antihermitian to compute the antihermitian part of a matrix:
This equals the normalized difference between m and ConjugateTranspose[m]:
Any matrix can be represented as the sum of its Hermitian and antihermitian parts:
Use HermitianMatrixQ to test whether a matrix is Hermitian:
If is a Hermitian matrix, then is antihermitian:
MatrixExp[m] for antihermitian m is unitary:
An antihermitian matrix is always a normal matrix:
Use NormalMatrixQ to test whether the matrix is normal:
Antihermitian matrices have eigenvalues on the imaginary axis:
Use Eigenvalues to find eigenvalues:
CharacteristicPolynomial[m,x] for antihermitian m alternates real and imaginary coefficients:
Antihermitian matrices have a complete set of eigenvectors:
As a consequence, they must be diagonalizable:
Use Eigenvectors to find eigenvectors:
Det[m] for antisymmetric m of odd dimensions is imaginary:
If m has even dimensions, its determinant is real:
The inverse of an antihermitian matrix is antihermitian:
Text
Wolfram Research (2014), AntihermitianMatrixQ, Wolfram Language function, https://reference.wolfram.com/language/ref/AntihermitianMatrixQ.html.
CMS
Wolfram Language. 2014. "AntihermitianMatrixQ." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/AntihermitianMatrixQ.html.
APA
Wolfram Language. (2014). AntihermitianMatrixQ. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/AntihermitianMatrixQ.html