In mathematics, especially functional analysis, a normal operator on a complex Hilbert space H {\displaystyle H} is a continuous linear operator N : H → H {\displaystyle N\colon H\rightarrow H} that commutes with its Hermitian adjoint N ∗ {\displaystyle N^{\ast }} , that is: N ∗ N = N N ∗ {\displaystyle N^{\ast }N=NN^{\ast }} . Normal operators are important because the spectral theorem holds for them. The class of normal operators is well understood. Examples of normal operators are
unitary operators: U ∗ = U − 1 {\displaystyle U^{\ast }=U^{-1}}
Hermitian operators (i.e., self-adjoint operators): N ∗ = N {\displaystyle N^{\ast }=N}
skew-Hermitian operators: N ∗ = − N {\displaystyle N^{\ast }=-N}
positive operators: N = M ∗ M {\displaystyle N=M^{\ast }M} for some M {\displaystyle M} (so N is self-adjoint). A normal matrix is the matrix expression of a normal operator on the Hilbert space C n {\displaystyle \mathbb {C} ^{n}} .
Properties Normal operators are characterized by the spectral theorem. A compact normal operator (in particular, a normal operator on a finite-dimensional inner product space) is unitarily diagonalizable. Let T {\displaystyle T} be a bounded operator. The following are equivalent.
T {\displaystyle T} is normal.
T ∗ {\displaystyle T^{\ast }} is normal.
‖ T x ‖ = ‖ T ∗ x ‖ {\displaystyle \|Tx\|=\|T^{\ast }x\|} for all x {\displaystyle x} (use ‖ T x ‖ 2 = ⟨ T ∗ T x , x ⟩ = ⟨ T T ∗ x , x ⟩ = ‖ T ∗ x ‖ 2 {\displaystyle \|Tx\|^{2}=\langle T^{\ast }Tx,x\rangle =\langle TT^{*}x,x\rangle =\|T^{\ast }x\|^{2}} ). The self-adjoint and anti–self adjoint parts of T {\displaystyle T} commute. That is, if T {\displaystyle T} is written as T = T 1 + i T 2 {\displaystyle T=T_{1}+iT_{2}} with T 1 := T + T ∗ 2 {\displaystyle T_{1}:={\frac {T+T^{*}}{2}}} and i T 2 := T − T ∗ 2 , {\displaystyle i\,T_{2}:={\frac {T-T^{*}}{2}},} then T 1 T 2 = T 2 T 1 . {\displaystyle T_{1}T_{2}=T_{2}T_{1}.}
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