Analysis of Measurement-based Quantum Network Coding over Repeater Networks under Noisy Conditions

TL;DR

This paper proposes a measurement-based quantum network coding scheme for repeater networks, demonstrating reduced circuit depth and improved fidelity under noisy conditions through simulation analysis.

Contribution

Introduces a novel measurement-based quantum network coding protocol that reduces circuit depth and enhances error tolerance in quantum repeater networks.

Findings

Circuit depth reduced by 56.5% compared to previous schemes

Entangled pairs' fidelity drops below 50% if local operation accuracy is under 98.9%

MQNC outperforms previous quantum network coding schemes in error tolerance

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.