Schmidt decomposition

Summary

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.

Theorem

edit

Let   and   be Hilbert spaces of dimensions n and m respectively. Assume  . For any vector   in the tensor product  , there exist orthonormal sets   and   such that  , where the scalars   are real, non-negative, and unique up to re-ordering.

Proof

edit

The Schmidt decomposition is essentially a restatement of the singular value decomposition in a different context. Fix orthonormal bases   and  . We can identify an elementary tensor   with the matrix  , where   is the transpose of  . 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   where   is n × m and we have

 

Let   be the m column vectors of  ,   the column vectors of  , and   the diagonal elements of Σ. The previous expression is then

 

Then

 

which proves the claim.

Some observations

edit

Some properties of the Schmidt decomposition are of physical interest.

Spectrum of reduced states

edit

Consider a vector   of the tensor product

 

in the form of Schmidt decomposition

 

Form the rank 1 matrix  . Then the partial trace of  , with respect to either system A or B, is a diagonal matrix whose non-zero diagonal elements are  . In other words, the Schmidt decomposition shows that the reduced states of   on either subsystem have the same spectrum.

Schmidt rank and entanglement

edit

The strictly positive values   in the Schmidt decomposition of   are its Schmidt coefficients, or Schmidt numbers. The total number of Schmidt coefficients of  , counted with multiplicity, is called its Schmidt rank.

If   can be expressed as a product

 

then   is called a separable state. Otherwise,   is said to be an entangled state. From the Schmidt decomposition, we can see that   is entangled if and only if   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.

Von Neumann entropy

edit

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   is  , and this is zero if and only if   is a product state (not entangled).

Schmidt-rank vector

edit

The Schmidt rank is defined for bipartite systems, namely quantum states

 

The concept of Schmidt rank can be extended to quantum systems made up of more than two subsystems.[1]

Consider the tripartite quantum system:

 

There are three ways to reduce this to a bipartite system by performing the partial trace with respect to   or  

 

Each of the systems obtained is a bipartite system and therefore can be characterized by one number (its Schmidt rank), respectively   and  . 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

 

The concept of Schmidt-rank vector can be likewise extended to systems made up of more than three subsystems through the use of tensors.

Example [2]

edit

Take the tripartite quantum state  

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  .

See also

edit

References

edit
  1. ^ Huber, Marcus; de Vicente, Julio I. (January 14, 2013). "Structure of Multidimensional Entanglement in Multipartite Systems". Physical Review Letters. 110 (3): 030501. arXiv:1210.6876. Bibcode:2013PhRvL.110c0501H. doi:10.1103/PhysRevLett.110.030501. ISSN 0031-9007. PMID 23373906. S2CID 44848143.
  2. ^ Krenn, Mario; Malik, Mehul; Fickler, Robert; Lapkiewicz, Radek; Zeilinger, Anton (March 4, 2016). "Automated Search for new Quantum Experiments". Physical Review Letters. 116 (9): 090405. arXiv:1509.02749. Bibcode:2016PhRvL.116i0405K. doi:10.1103/PhysRevLett.116.090405. ISSN 0031-9007. PMID 26991161. S2CID 20182586.

Further reading

edit
  • Pathak, Anirban (2013). Elements of Quantum Computation and Quantum Communication. London: Taylor & Francis. pp. 92–98. ISBN 978-1-4665-1791-2.