Analysis of measurement-based quantum network coding over repeater networks under noisy conditions

Takaaki Matsuo, Takahiko Satoh, Shota Nagayama, Rodney D Van Meter

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Quantum network coding is an effective solution for alleviating bottlenecks in quantum networks. We introduce a measurement-based quantum network coding scheme for quantum repeater networks (MQNC), and analyze its behavior based on results acquired from Monte Carlo simulation that includes various error sources over a butterfly network. By exploiting measurement-based quantum computing, operation on qubits for completing network coding proceeds in parallel. We show that such an approach offers advantages over other schemes in terms of the quantum circuit depth and therefore improves the communication fidelity without disturbing the aggregate throughput. The circuit depth of our protocol has been reduced by 56.5% compared to the quantum network coding scheme (QNC) introduced in 2012 by Satoh et al. For MQNC, we have found that the resulting entangled pairs' joint fidelity drops below 50% when the accuracy of local operations is lower than 98.9%, assuming that all initial Bell pairs across quantum repeaters have a fixed fidelity of 98%. Overall, MQNC showed substantially higher error tolerance compared to QNC and slightly better than buffer space multiplexing using step-by-step entanglement swapping, but not quite as strong as simultaneous entanglement swapping operations.

Original languageEnglish
Article number062328
JournalPhysical Review A
Volume97
Issue number6
DOIs
Publication statusPublished - 2018 Jun 20

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repeaters
coding
quantum computation
multiplexing
bells
buffers
communication

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

Cite this

Analysis of measurement-based quantum network coding over repeater networks under noisy conditions. / Matsuo, Takaaki; Satoh, Takahiko; Nagayama, Shota; Van Meter, Rodney D.

In: Physical Review A, Vol. 97, No. 6, 062328, 20.06.2018.

Research output: Contribution to journalArticle

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