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Semidefinite programming lower bounds on the squashed entanglement
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Semidefinite programming lower bounds on the squashed entanglement
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The squashed entanglement is a widely used entanglement measure that has many desirable properties. However, as it is based on an optimization over extensions of arbitrary dimension, one drawback of this measure is the lack of good algorithms to compute it. Here, we introduce a hierarchy of semidefinite programming lower bounds on the squashed entanglement.
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Cited by 1 Pith paper
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Semidefinite optimization of the quantum relative entropy of channels
Semidefinite optimization yields arbitrarily tight upper and lower bounds on the quantum relative entropy of channels via discretized linearization of an integral representation.
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