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* The vectorial pure state <math>| \psi \rangle</math> is in the form specified by the ]. | * The vectorial pure state <math>| \psi \rangle</math> is in the form specified by the ]. | ||
* Since square root decompositions of a positive semidefinite matrix |
* Since square root decompositions of a positive semidefinite matrix are not unique, neither are purifications. | ||
== An application: Stinespring's theorem == | == An application: Stinespring's theorem == |
Revision as of 16:19, 16 June 2006
In quantum mechanics, especially quantum information, purification refers to the fact that every mixed state acting on finite dimensional Hilbert spaces can be viewed as the reduced state of some pure state.
Statement
Let ρ be a density matrix acting on a Hilbert space of finite dimension n, then there exist a Hilbert space and a pure state such that the partial trace of with respect to
Proof
A density matrix is by definition positive semidefinite. So ρ has square root factorization . Let be another copy of the n-dimensional Hilbert space with any orthonormal basis . Define by
Direct calculation gives
This proves the claim.
Note
- The vectorial pure state is in the form specified by the Schmidt decomposition.
- Since square root decompositions of a positive semidefinite matrix are not unique, neither are purifications.
An application: Stinespring's theorem
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By combining Choi's theorem on completely positive maps and purification of a mixed state, we can recover the Stinespring dilation theorem for the finite dimensional case.
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