Eigenvalues of a reduced density matrix

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Discussion Overview

The discussion revolves around the properties of density matrices, particularly in relation to pure states and their eigenvalues. Participants explore the conditions under which a density matrix has a specific eigenvalue structure, including the implications of diagonalization and basis choice.

Discussion Character

  • Conceptual clarification
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant asserts that a density matrix describing a pure state must contain only one non-zero eigenvalue equal to one, referencing a statement from their lecturer.
  • Another participant suggests that the density matrix can be expressed in terms of a pure state vector, leading to eigenvalues that are Kronecker deltas, indicating a potential misunderstanding of the conditions under which this holds.
  • A third participant questions whether the vectors used in the density matrix representation need to be orthogonal, expressing uncertainty about the lecturer's claim regarding eigenvalues in different bases.
  • Another participant proposes that the basis of the eigenvectors may be relevant, suggesting that a pure state can be represented as one of the basis vectors, while expressing uncertainty about generalization to higher dimensions.

Areas of Agreement / Disagreement

Participants express differing interpretations of the lecturer's statement regarding eigenvalues of density matrices for pure states, indicating that multiple competing views remain on the topic.

Contextual Notes

There is uncertainty regarding the orthogonality of state vectors in the context of density matrices and the implications of basis choice on eigenvalue structure. The discussion does not resolve these ambiguities.

Who May Find This Useful

Students and researchers interested in quantum mechanics, particularly those studying the properties of density matrices and pure states.

barnflakes
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My lecturer keeps telling me that if a density matrix describes a pure state then it must contain only one non-zero eigenvalue which is equal to one. However I can't see how this is true, particularly as I have seen a matrix [tex]\rho_A = \begin{pmatrix} 1/2 & - 1/2 \\ -1/2 & 1/2 \\ \end{pmatrix}[/tex] for which this is not true. He then clarified that if it was in "the diagonal basis" this was true. Can someone clarify this for me or show me a proof please?
 
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I guess he means that you can write a density matrix as
[tex]\rho = | \psi_i \rangle \langle \psi_i |[/tex]
Which has eigenvalues [itex]\delta_{ij}[/itex] since
[tex]\rho |\psi_j \rangle = \delta_{ij} |\psi_i \rangle[/tex].
The example you gave can be written as [itex]\rho = | - \rangle \langle - |[/itex], where [tex]| - \rangle = \frac{1}{\sqrt{2}} \begin{pmatrix}1 \\ -1\end{pmatrix}[/tex] which has [itex]| - \rangle[/itex] as an eigenvector, with eigenvalue 1.
 
Is that true? I thought $\psi_i \rangle$ and $\psi_j \rangle$ weren't necessarily orthogonal. He also definitely said that when it's pure it only has one non-zero eigenvalue. Maybe he means only in the basis of its eigenvectors, I don't know? That's what I'm trying to find out.
 
Yeah I think it is the basis of its eigenvectors. I think you can always take a pure state as one possible basis vector. E.g. if you have [itex]|\psi_a \rangle = \alpha |0 \rangle + \beta |1 \rangle[/itex] then the other one is [itex]|\psi_b \rangle = \alpha |0 \rangle - \beta |1 \rangle[/itex]. I can't remember if/how this generalizes to higher dimensions though. :blushing: Maybe Gram-Schmidt?
 

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