Pith. sign in

REVIEW 1 cited by

Entanglement distillation by extendible maps

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1109.1779 v3 pith:LOBHO4XE submitted 2011-09-08 quant-ph

Entanglement distillation by extendible maps

classification quant-ph
keywords operationsstatesclassentangledk-extendibleloccmapsstate
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

It is known that from entangled states that have positive partial transpose it is not possible to distill maximally entangled states by local operations and classical communication (LOCC). A long-standing open question is whether maximally entangled states can be distilled from every state with a non-positive partial transpose. In this paper we study a possible approach to the question consisting of enlarging the class of operations allowed. Namely, instead of LOCC operations we consider k-extendible operations, defined as maps whose Choi-Jamiolkowski state is k-extendible. We find that this class is unexpectedly powerful - e.g. it is capable of distilling EPR pairs even from product states. We also perform numerical studies of distillation of Werner states by those maps, which show that if we raise the extension index k simultaneously with the number of copies of the state, then the class of k-extendible operations is not that powerful anymore and provide a better approximation to the set of LOCC operations.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Semidefinite optimization of the quantum relative entropy of channels

    quant-ph 2024-10 unverdicted novelty 6.0

    Semidefinite optimization yields arbitrarily tight upper and lower bounds on the quantum relative entropy of channels via discretized linearization of an integral representation.