Decomposing a density matrix of a mixed ensemble

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Discussion Overview

The discussion revolves around the decomposition of a density matrix for a mixed ensemble, specifically addressing how to determine if a given matrix can be classified as a density matrix and how to express it as a sum of pure states. The participants explore the conditions for mixed ensembles and the implications of the trace of the density matrix.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant identifies the matrix as a mixed ensemble density matrix due to the condition $Tr(\rho^2)<1$, but expresses uncertainty about how to decompose it into pure states without knowing the number of states involved.
  • Another participant suggests looking for an orthonormal basis such that the density matrix can be expressed as a sum of projectors, indicating that the coefficients must sum to 1.
  • A later reply mentions that any sum of pure states will suffice for the decomposition, referencing the HJW theorem regarding purifications in a larger Hilbert space.
  • There is a question raised about the assumption of orthogonality among the states forming the density matrix, which leads to a clarification that while orthogonal states are one possible solution, non-orthogonal states may also exist.

Areas of Agreement / Disagreement

Participants generally agree on the classification of the matrix as a mixed ensemble density matrix and the need for decomposition, but there is disagreement regarding the necessity of orthogonality among the states in the decomposition.

Contextual Notes

The discussion highlights the complexity of decomposing density matrices, including the implications of orthogonality and the potential for multiple valid decompositions. The reference to the HJW theorem suggests a broader context for understanding the relationships between different states.

Gabriel Maia
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I'm trying to solve a problem where I am given a few matrices and asked to determine if they could be density matrices or not and if they are if they represent pure or mixed ensembles. In the case of mixed ensembles, I should find a decomposition in terms of a sum of pure ensembles. The matrix I'm having trouble with is this one

\rho = \left[\begin{array}{ccc}\frac{1}{2} &amp; 0 &amp; \frac{1}{4} \\ 0 &amp; \frac{1}{4} &amp; 0 \\ \frac{1}{4} &amp; 0 &amp; \frac{1}{4}\end{array}\right]

I know it's a mixed ensemble density matrix because $Tr(\rho^2)<1$, but how can I decompose if I don't even know how big is this sum? I mean, any number of pure states may compose a mixed ensemble since they do not need to be orthogonal. How can I approach this?Thank you very much.
 
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Gabriel Maia said:
I'm trying to solve a problem where I am given a few matrices and asked to determine if they could be density matrices or not and if they are if they represent pure or mixed ensembles. In the case of mixed ensembles, I should find a decomposition in terms of a sum of pure ensembles. The matrix I'm having trouble with is this one

\rho = \left[\begin{array}{ccc}\frac{1}{2} &amp; 0 &amp; \frac{1}{4} \\ 0 &amp; \frac{1}{4} &amp; 0 \\ \frac{1}{4} &amp; 0 &amp; \frac{1}{4}\end{array}\right]

I know it's a mixed ensemble density matrix because $Tr(\rho^2)<1$, but how can I decompose if I don't even know how big is this sum? I mean, any number of pure states may compose a mixed ensemble since they do not need to be orthogonal. How can I approach this?Thank you very much.

Is this homework? If so, it should be in the homework forum.

What you're looking for is an orthonormal basis |\psi_j\rangle such that \rho = \sum_j p_j |\psi_j\rangle \langle \psi_j|, where the p_j are all real, and add up to 1. Now consider the product:

\rho |\psi_k\rangle = \sum_j p_j |\psi_j\rangle \langle \psi_j | \psi_k \rangle = p_k |\psi_k\rangle

where for the last equality, we used that the kets |\psi_j\rangle are orthonormal, meaning that \langle \psi_j | \psi_k \rangle = \delta_{jk}

So what that means is that the basis vector |\psi_k\rangle and the coefficient p_k are solvable as an eigenvalue problem:

\rho |\psi_k\rangle = p_k |\psi_k\rangle

Do you know how to find the eigenvalues and corresponding eigenvectors of a square matrix?
 
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Gabriel Maia said:
I know it's a mixed ensemble density matrix because $Tr(\rho^2)<1$, but how can I decompose if I don't even know how big is this sum? I mean, any number of pure states may compose a mixed ensemble since they do not need to be orthogonal. How can I approach this?

The problem only asks you to find a sum, so any sum will do. Their purifications to a larger Hilbert space with fixed dimension will all be related by unitary matrices via the HJW theorem: https://arxiv.org/abs/quant-ph/0305068
 
stevendaryl said:
Is this homework? If so, it should be in the homework forum.

What you're looking for is an orthonormal basis |\psi_j\rangle such that \rho = \sum_j p_j |\psi_j\rangle \langle \psi_j|, where the p_j are all real, and add up to 1. Now consider the product:

\rho |\psi_k\rangle = \sum_j p_j |\psi_j\rangle \langle \psi_j | \psi_k \rangle = p_k |\psi_k\rangle

where for the last equality, we used that the kets |\psi_j\rangle are orthonormal, meaning that \langle \psi_j | \psi_k \rangle = \delta_{jk}

So what that means is that the basis vector |\psi_k\rangle and the coefficient p_k are solvable as an eigenvalue problem:

\rho |\psi_k\rangle = p_k |\psi_k\rangle

Do you know how to find the eigenvalues and corresponding eigenvectors of a square matrix?

By considering that \langle \psi_j|\psi_{k} \rangle = \delta_{j\,k} aren't we assuming that all the states that form the density matrix are orthogonal?
 
Gabriel Maia said:
By considering that \langle \psi_j|\psi_{k} \rangle = \delta_{j\,k} aren't we assuming that all the states that form the density matrix are orthogonal?

Well, yes. But if there is any solution, there is a solution of that form.
 

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