Quantum-Error-Mitigated Detectable Byzantine Agreement with Dynamical Decoupling for Distributed Quantum Computing
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Abstract (arXiv)
In the burgeoning domain of distributed quantum computing, achieving consensus amidst adversarial settings remains a pivotal challenge. We introduce an enhancement to the Quantum Byzantine Agreement (QBA) protocol, uniquely incorporating advanced error mitigation techniques: Twirled Readout Error Extinction (T-REx) and dynamical decoupling (DD). Central to this refined approach is the utilization of a Noisy Intermediate Scale Quantum (NISQ) source device for heightened performance. Extensive tests on both simulated and real-world quantum devices, notably IBM's quantum computer, provide compelling evidence of the effectiveness of our T-REx and DD adaptations in mitigating prevalent quantum channel errors. Subsequent to the entanglement distribution, our protocol adopts a verification method reminiscent of Quantum Key Distribution (QKD) schemes. The Commander then issues orders encoded in specific quantum states, like Retreat or Attack. In situations where received orders diverge, lieutenants engage in structured games to reconcile discrepancies. Notably, the frequency of these games is contingent upon the Commander's strategies and the overall network size. Our empirical findings underscore the enhanced resilience and effectiveness of the protocol in diverse scenarios. Nonetheless, scalability emerges as a concern with the growth of the network size. To sum up, our research illuminates the considerable potential of fortified quantum consensus systems in the NISQ era, highlighting the imperative for sustained research in bolstering quantum ecosystems.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Nov 2023.
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Citing papers per year: 2023: 1; 2024: 2.
3 papers.
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- 2024Consensus-based Distributed Quantum Kernel Learning for Speech Recognition9 Sep 2024
- 2024Multi-GPU-Enabled Hybrid Quantum-Classical Workflow in Quantum-HPC Middleware: Applications in Quantum Simulations9 Mar 2024
- 2023Quantum-Enhanced Support Vector Machine for Large-Scale Stellar Classification with GPU Acceleration21 Nov 2023