In linear algebra, the Schmidt decomposition (named after its originator Erhard Schmidt) refers to a particular way of expressing a vector in the tensor product of two inner product spaces. It has numerous applications in quantum information theory, for example in entanglement characterization and in state purification, and plasticity.
Let [math]\displaystyle{ H_1 }[/math] and [math]\displaystyle{ H_2 }[/math] be Hilbert spaces of dimensions n and m respectively. Assume [math]\displaystyle{ n \geq m }[/math]. For any vector [math]\displaystyle{ w }[/math] in the tensor product [math]\displaystyle{ H_1 \otimes H_2 }[/math], there exist orthonormal sets [math]\displaystyle{ \{ u_1, \ldots, u_m \} \subset H_1 }[/math] and [math]\displaystyle{ \{ v_1, \ldots, v_m \} \subset H_2 }[/math] such that [math]\displaystyle{ w= \sum_{i =1} ^m \alpha _i u_i \otimes v_i }[/math], where the scalars [math]\displaystyle{ \alpha_i }[/math] are real, non-negative, and unique up to re-ordering.
The Schmidt decomposition is essentially a restatement of the singular value decomposition in a different context. Fix orthonormal bases [math]\displaystyle{ \{ e_1, \ldots, e_n \} \subset H_1 }[/math] and [math]\displaystyle{ \{ f_1, \ldots, f_m \} \subset H_2 }[/math]. We can identify an elementary tensor [math]\displaystyle{ e_i \otimes f_j }[/math] with the matrix [math]\displaystyle{ e_i f_j ^\mathsf{T} }[/math], where [math]\displaystyle{ f_j ^\mathsf{T} }[/math] is the transpose of [math]\displaystyle{ f_j }[/math]. A general element of the tensor product
can then be viewed as the n × m matrix
By the singular value decomposition, there exist an n × n unitary U, m × m unitary V, and a positive semidefinite diagonal m × m matrix Σ such that
Write [math]\displaystyle{ U =\begin{bmatrix} U_1 & U_2 \end{bmatrix} }[/math] where [math]\displaystyle{ U_1 }[/math] is n × m and we have
Let [math]\displaystyle{ \{ u_1, \ldots, u_m \} }[/math] be the m column vectors of [math]\displaystyle{ U_1 }[/math], [math]\displaystyle{ \{ v_1, \ldots, v_m \} }[/math] the column vectors of [math]\displaystyle{ \overline{V} }[/math], and [math]\displaystyle{ \alpha_1, \ldots, \alpha_m }[/math] the diagonal elements of Σ. The previous expression is then
Then
which proves the claim.
Some properties of the Schmidt decomposition are of physical interest.
Consider a vector [math]\displaystyle{ w }[/math] of the tensor product
in the form of Schmidt decomposition
Form the rank 1 matrix [math]\displaystyle{ \rho = w w^* }[/math]. Then the partial trace of [math]\displaystyle{ \rho }[/math], with respect to either system A or B, is a diagonal matrix whose non-zero diagonal elements are [math]\displaystyle{ | \alpha_i|^2 }[/math]. In other words, the Schmidt decomposition shows that the reduced states of [math]\displaystyle{ \rho }[/math] on either subsystem have the same spectrum.
The strictly positive values [math]\displaystyle{ \alpha_i }[/math] in the Schmidt decomposition of [math]\displaystyle{ w }[/math] are its Schmidt coefficients, or Schmidt numbers. The total number of Schmidt coefficients of [math]\displaystyle{ w }[/math], counted with multiplicity, is called its Schmidt rank.
If [math]\displaystyle{ w }[/math] can be expressed as a product
then [math]\displaystyle{ w }[/math] is called a separable state. Otherwise, [math]\displaystyle{ w }[/math] is said to be an entangled state. From the Schmidt decomposition, we can see that [math]\displaystyle{ w }[/math] is entangled if and only if [math]\displaystyle{ w }[/math] has Schmidt rank strictly greater than 1. Therefore, two subsystems that partition a pure state are entangled if and only if their reduced states are mixed states.
A consequence of the above comments is that, for pure states, the von Neumann entropy of the reduced states is a well-defined measure of entanglement. For the von Neumann entropy of both reduced states of [math]\displaystyle{ \rho }[/math] is [math]\displaystyle{ -\sum_i |\alpha_i|^2 \log\left(|\alpha_i|^2\right) }[/math], and this is zero if and only if [math]\displaystyle{ \rho }[/math] is a product state (not entangled).
The Schmidt rank is defined for bipartite systems, namely quantum states
[math]\displaystyle{ |\psi\rangle \in H_A \otimes H_B }[/math]
The concept of Schmidt rank can be extended to quantum systems made up of more than two subsystems.[1]
Consider the tripartite quantum system:
[math]\displaystyle{ |\psi\rangle \in H_A \otimes H_B \otimes H_C }[/math]
There are three ways to reduce this to a bipartite system by performing the partial trace with respect to [math]\displaystyle{ H_A, H_B }[/math] or [math]\displaystyle{ H_C }[/math]
[math]\displaystyle{ \begin{cases} \hat{\rho}_A = Tr_A(|\psi\rangle\langle\psi|)\\ \hat{\rho}_B = Tr_B(|\psi\rangle\langle\psi|)\\ \hat{\rho}_C = Tr_C(|\psi\rangle\langle\psi|) \end{cases} }[/math]
Each of the systems obtained is a bipartite system and therefore can be characterized by one number (its Schmidt rank), respectively [math]\displaystyle{ r_A, r_B }[/math] and [math]\displaystyle{ r_C }[/math]. These numbers capture the "amount of entanglement" in the bipartite system when respectively A, B or C are discarded. For these reasons the tripartite system can be described by a vector, namely the Schmidt-rank vector
[math]\displaystyle{ \vec{r} = (r_A, r_B, r_C) }[/math]
The concept of Schmidt-rank vector can be likewise extended to systems made up of more than three subsystems through the use of tensors.
Take the tripartite quantum state [math]\displaystyle{ |\psi_{4, 2, 2}\rangle = \frac{1}{2}\big(|0, 0, 0\rangle + |1, 0, 1\rangle + |2, 1, 0\rangle + |3, 1, 1\rangle \big) }[/math]
This kind of system is made possible by encoding the value of a qudit into the orbital angular momentum (OAM) of a photon rather than its spin, since the latter can only take two values.
The Schmidt-rank vector for this quantum state is [math]\displaystyle{ (4, 2, 2) }[/math].
Original source: https://en.wikipedia.org/wiki/Schmidt decomposition.
Read more |