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In mathematics, the conjugate transpose or adjoint of an m-by-n matrix A with complex entries is the n-by-m matrix A* obtained from A by taking the transpose and then taking the complex conjugate of each entry. Formally
for 1 ≤ i ≤ n and 1 ≤ j ≤ m. This is a particular case of the Hermitian conjugate (sometimes called Hermitian adjoint or just adjoint) linear operator.
For example, if
2-2i&i\end{bmatrix}<math> then
2&-i\end{bmatrix}<math>
If the entries of A are real, then A* coincides with the transpose AT of A. It is often useful to think of square complex matrices as "generalized complex numbers", and of the conjugate transpose as a generalization of complex conjugation.
The square matrix A is called hermitian or self-adjoint if A = A*. It is called normal if A*A = AA*.
Even if A is not square, the two matrices A*A and AA* are both hermitian and in fact positive semi-definite.
The adjoint matrix A* should not be confused with the adjugate adj(A) (which in older texts is also sometimes called "adjoint").
The final property given above shows that if one views A as a linear operator from the Euclidean Hilbert space Cn to Cm, then the matrix A* corresponds to the adjoint operator.
In fact it can be used to define what is meant by that. Assuming now we are in a Hilbert space H, the relation
<Ax,y> = <x, A*y>
can be used to define the adjoint operator A*, by means of the Riesz representation theorem.
When working in Hilbert space, especially with the bra-ket notation, the adjoint operator - called the Hermitian Conjugate, denoted as <math>A^{\dagger}<math>, is defined by the relation
The term Hermitian conjugate transpose is used since if <math> A = A^{\dagger} <math> than A is called an Hermitian operator.
It has also been stated in which way the above can be related to the notion of a pair of adjoint functors in category theory. An explanation is given by John Baez in of his famous series. See also the previous weeks for a gentle introduction to category theory.