Hermittian Operators
Definition
The conjugate transpose of a matrix M M=∑n∑kmnk|en⟩⟨ek| is defined as M†=∑n∑km∗kn|en⟩⟨ek|. If the conjugate transpose of a matrix is equal to itself, M†=M, then the matrix is said to be Hermittian.
Properties of Hermittian Operators
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For any kets |ψ1⟩ and |ψ2⟩ ⟨ψ1|M|ψ2⟩=⟨ψ1|M†|ψ1⟩=⟨ψ2|M|ψ1⟩∗, by the definition of Hermittian operator.
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All eigenvalues of a Hermittian operator are real M \left| n \right> &= \lambda_n \left| n \right> Then, ⟨n|M|n⟩=λn M|n⟩=λn|n⟩⟨n|M†=λ∗n⟨n|⟨n|M=λ∗n⟨n|. Then, ⟨n|M|n⟩=λ∗)n. So, λn=λ∗n, i.e. it is real.
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Eigenvectors of Hermittian operators with distinct eigenvalues are orthogonal to each other. Let M|n⟩=λn|n⟩ and M|k⟩=λk|k⟩, where λn≠λk. Then, ⟨k|M|n⟩=λn⟨k|n⟩ and ⟨n|M|k⟩=λk⟨n|k⟩⟨k|M|n⟩=λ∗k⟨k|n⟩. So, 0=(λn−λk)⟨k|n⟩. Since λn≠λk, we have ⟨k|n⟩=0
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If the eigenvectors of the Hermittian operator have same eigenvalue, one can always construct a new set of eigenvectors in terms of linear combination of the original eigenvector set to achieve orthogonality
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