In mathematics, a Hermitian matrix (or self-adjoint matrix) is a complex square matrix that is equal to its own conjugate transpose—that is, the element in the i-th row and j-th column is equal to the complex conjugate of the element in the j-th row and i-th column, for all indices i and j: A is Hermitian ⟺ a i j = a j i ¯ {\displaystyle A{\text{ is Hermitian}}\quad \iff \quad a_{ij}={\overline {a_{ji}}}}
or in matrix form: A is Hermitian ⟺ A = A T ¯ . {\displaystyle A{\text{ is Hermitian}}\quad \iff \quad A={\overline {A^{\mathsf {T}}}}.}
Hermitian matrices can be understood as the complex extension of real symmetric matrices.
If the conjugate transpose of a matrix A {\displaystyle A} is denoted by A H , {\displaystyle A^{\mathsf {H}},} then the Hermitian property can be written concisely as
A is Hermitian ⟺ A = A H {\displaystyle A{\text{ is Hermitian}}\quad \iff \quad A=A^{\mathsf {H}}}
Hermitian matrices are named after Charles Hermite, who demonstrated in 1855 that matrices of this form share a property with real symmetric matrices of always having real eigenvalues. Other, equivalent notations in common use are A H = A † = A ∗ , {\displaystyle A^{\mathsf {H}}=A^{\dagger }=A^{\ast },} although in quantum mechanics, A ∗ {\displaystyle A^{\ast }} typically means the complex conjugate only, and not the conjugate transpose.