Qbit pure vs mixed state space

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Discussion Overview

The discussion revolves around the distinction between pure and mixed states in the context of quantum mechanics, specifically focusing on qubits and their representation in Hilbert space. Participants explore the definitions, implications, and mathematical representations of these states, as well as the role of density matrices.

Discussion Character

  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • Some participants assert that a quantum pure qubit state is represented by a ray in the Hilbert space ##\mathbb H_2##, while mixed states are described by density matrices.
  • There is a suggestion that all non-null vectors in ##\mathbb H_2## that lie on the same ray represent the same pure state.
  • One participant questions whether the statement about rays representing pure states is generalizable to any quantum system described by a separable Hilbert space.
  • Some participants discuss the implications of measurements on pure states and how they relate to density operators.
  • There is a clarification that while a pure state can be represented by a density operator, it is fundamentally a normalized vector in Hilbert space.
  • Participants note that mixed states are statistical ensembles of pure states and can be described by density operators.
  • There is a debate regarding the definition of pure states as density operators versus state vectors, with references to the rank of density operators.

Areas of Agreement / Disagreement

Participants express differing views on the definitions and implications of pure and mixed states, particularly regarding their representations and the role of density matrices. No consensus is reached on some of the finer points of these definitions.

Contextual Notes

Some participants highlight the need for clarity regarding the mathematical definitions and properties of density operators, particularly in relation to their rank and the distinction between pure and mixed states.

  • #31
cianfa72 said:
I'm still confused about the meaning of a writing like this: $$\ket{0}$$
Is it an actual vector in qbit's 2-dimensional Hilbert space
Yes, it is.

cianfa72 said:
or is it the "column vector" of the coordinates/components in a given Hilbert space basis ?
If you want a density matrix, then it is easiest to see it as a column vector in a specific basis.

Otherwise, you should imagine a density operator. This is not difficult either, it is just a different picture. In that case, you "imagine" how it applies/operates on a given vector. For example, if you apply the operator ##\ket{\psi}\bra{\psi}## to the vector ##\ket{x}##, you get ##\ket{\psi}\bra{\psi}\ \ket{x}=\ket{\psi}\ (\langle\psi|x\rangle)=(\langle\psi|x\rangle)\ \ket{\psi}##.
 
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  • #32
gentzen said:
For example, if you apply the operator ##\ket{\psi}\bra{\psi}## to the vector ##\ket{x}##, you get ##\ket{\psi}\bra{\psi}\ \ket{x}=\ket{\psi}\ (\langle\psi|x\rangle)=(\langle\psi|x\rangle)\ \ket{\psi}##.
Ah yes, as I said before in this thread ##\ket{\psi}\bra{\psi}## should be actually a dyadic tensor product.
 
  • #33
cianfa72 said:
Sorry, then ##\ket{\psi}\bra{\psi}## should be actually the (dyadic) product tensor of the ket ##\ket{\psi}## times the dual-vector (bra) ##\bra{\psi}## ?

Edit: it is a dyad according to Wikipedia (tensor of order two and rank 1).
If the "dyad picture" works nice for you, then you can think like that. However, the typical contexts where the "dyad picture" arises is in formulas from classical electrodynamics that are written with explicit scalar products (and vector products). In this context, the "dyad picture" is a convenient way to generalize the behavior of scalar products, such that a "tensor like" value can be put into a scalar product, and you get out a vector, instead of a scalar.
 
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  • #34
cianfa72 said:
Is it an actual vector in qbit's 2-dimensional Hilbert space or is it the "column vector" of the coordinates/components in a given Hilbert space basis ?
You seem to be confused about what the thing you are calling a "column vector" actually is. It is a representation of the vector itself in a particular basis. The vector itself is an element of a vector space, which is an abstract space that exists and has certain properties independent of any particular choice of representation/basis. If you choose a basis, then you can write the vector as a column vector in that basis.

A ket like ##\ket{0}## can represent either the abstract vector itself, or the column vector in a specific basis. It depends on how you want to view the label ##0## that you put on the ket. Is that label referring to the particular abstract vector that you have in mind? Or is it referring to the column vector that represents that abstract vector in the particular basis in which that vector is an eigenvector whose eigenvalue corresponds to the label ##0##? It could be either; the only person who knows which is the person who wrote down the ket, which in this case is you.
 
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  • #35
PeterDonis said:
Or is it referring to the column vector that represents that abstract vector in the particular basis in which that vector is an eigenvector whose eigenvalue corresponds to the label ##0##?
A vector is an eigenvector for an operator regardless of the picked basis. Therefore I believe what you meant is that if ##0## was understood as the label for an eigenvalue, then ket ##\ket{0}## would be the "column vector" representing the associated eigenvector in the basis in which an element is that eigenvector. That means it could be for example in the form $$\ket{0}=\begin{bmatrix} 1 \\ 0 \end{bmatrix}$$
 
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  • #36
cianfa72 said:
A vector is an eigenvector for an operator regardless of the picked basis.
Yes, but it is one of the basis vectors in only one basis.

cianfa72 said:
it could be for example in the form $$\ket{0}=\begin{bmatrix} 1 \\ 0 \end{bmatrix}$$
Yes, it would be a basis vector in this basis, but not in any other basis.
 

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