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arXiv 2609.10698quant-ph

超越线性光学极限的逻辑贝尔态测量的演示

Demonstration of a logical Bell-state measurement beyond the linear-optical limit

Shreya Kumar, Simon D. Reiß, Peter van Loock, Stefanie Barz

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中文总结 AI 辅助

本研究利用线性光学和两量子比特重复码实现逻辑贝尔态测量,成功概率达70.8%,超越线性光学50%的极限,为容错光子量子技术提供关键进展。

中文摘要 AI 辅助

容错对于可扩展量子技术至关重要,并通过量子纠错码实现。贝尔态测量(BSM)是现代量子技术(如基于测量的量子计算、基于融合的量子计算以及量子网络)的基本构建模块。因此,对纠错后的量子比特执行BSM是在这些应用中实现容错的必要步骤。在本工作中,我们利用线性光学,基于两量子比特重复码(一种量子奇偶校验码,能够检测比特翻转错误)实现了逻辑BSM,并实验获得了(70.8±0.4)%的平均成功概率。虽然标准线性光学BSM在根本上受限于最大50%的成功概率,但这一提高的成功概率能够在量子通信中实现更高的安全密钥率,并有助于生成用于量子计算的大型图态。由于容错方案无论如何都需要纠错码,这一改进不会带来额外的资源开销。我们的结果表明,纠错码可用于超越BSM的线性光学极限,这是迈向实用、容错和可扩展的光子量子技术的重要一步。

英文摘要

Fault tolerance is essential for scalable quantum technologies and is enabled by quantum error-correction codes. Bell-state measurements (BSMs) are a fundamental building block for modern quantum technologies such as measurement-based quantum computation and fusion-based quantum computation, as well as quantum networks. Therefore, performing BSMs on error-corrected qubits is a necessary step for achieving fault tolerance in these applications. In this work, we realise a logical BSM using linear optics, based on a two-qubit repetition code, an instance of a quantum parity code that allows detection of bit-flip errors, and experimentally achieve a mean success probability of (70.8 +/- 0.4)%. While standard linear-optical BSMs are fundamentally limited to a maximum success probability of 50%, this increased success probability enables higher secure key rates in quantum communication and facilitates the generation of large graph states for quantum computation. Since fault-tolerant schemes require error-correction codes regardless, this improvement comes at no additional resource overhead. Our results demonstrate that error-correction codes can be used to surpass the linear-optics limit of BSMs, which is an important step towards practical, fault-tolerant, and scalable photonic quantum technologies.

发表机构

  • University of Stuttgart(斯图加特大学)
  • Johannes-Gutenberg University of Mainz(约翰内斯·古腾堡美因茨大学)

机构由 AI 辅助整理,请以论文原文为准。

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