Metrology-assisted entanglement distribution in noisy quantum networks
- URL: http://arxiv.org/abs/2110.15627v2
- Date: Mon, 23 May 2022 15:09:01 GMT
- Title: Metrology-assisted entanglement distribution in noisy quantum networks
- Authors: Simon Morelli, David Sauerwein, Michalis Skotiniotis, Nicolai Friis
- Abstract summary: We consider the distribution of high-dimensional entangled states to multiple parties via noisy channels and the subsequent probabilistic conversion of these states to desired target states.
We show that such state-conversion protocols can be enhanced by embedded channel-estimation routines at no additional cost in terms of the number of copies of the distributed states.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We consider the distribution of high-dimensional entangled states to multiple
parties via noisy channels and the subsequent probabilistic conversion of these
states to desired target states using stochastic local operations and classical
communication. We show that such state-conversion protocols can be enhanced by
embedded channel-estimation routines at no additional cost in terms of the
number of copies of the distributed states. The defining characteristic of our
strategy is the use of those copies for which the conversion was unsuccessful
for the estimation of the noise, thus allowing one to counteract its
detrimental effect on the successfully converted copies. Although this idea
generalizes to various more complex situations, we focus on the realistic
scenario, where only finitely many copies are distributed and where the parties
are not required to process multiple copies simultaneously. In particular, we
investigate the performance of so-called one-successful-branch protocols,
applied sequentially to single copies and an adaptive Bayesian estimation
strategy. Finally, we compare our strategy to more general but less easily
practically implementable strategies involving distillation and the use of
quantum memories to process multiple copies simultaneously.
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