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利用交叉克尔相互作用的双模二项式猫态概率生成

Probabilistic generation of two-mode binomial cat states using cross-Kerr interactions

S. Zhao, A. Metelmann, S. Qvarfort

arXiv 2608.29173首次发表:更新:

发表机构

Institute for Quantum Materials and Technology, Karlsruhe Institute of Technology; Institute for Theory of Condensed Matter, Karlsruhe Institute of Technology; Institut de Science et d’Ingénierie Supramoléculaires (ISIS, UMR7006), University of Strasbourg and CNRS; Nordita, KTH Royal Institute of Technology and Stockholm University; Department of Physics, Stockholm University(卡尔斯鲁厄理工学院量子材料与技术研究所; 卡尔斯鲁厄理工学院凝聚态理论研究所; 斯特拉斯堡大学与法国国家科学研究中心超分子科学与工程学院; 斯德哥尔摩皇家理工学院与斯德哥尔摩大学诺迪塔中心; 斯德哥尔摩大学物理系)

机构由 AI 辅助整理,请以论文原文为准。

AI 中文总结

该研究提出一种利用交叉克尔相互作用、结合高斯初始态与预报外差测量的方案,可在超导电路架构中概率生成双模二项式猫态,且对耗散具有鲁棒性,克服了现有制备方案需非高斯初始资源的关键局限。

AI 中文摘要

宏观上可区分的相干态叠加,即猫态,是量子技术的关键资源。特别是,双模二项式猫态可在连续变量量子计算中实现精确量子纠错。然而,它们的制备通常需要非高斯初始态,例如福克(Fock)态或NOON态,这些态在实验中难以实现。在此,我们提出一种生成双模二项式猫态的方案,该方案仅需高斯初始态结合预报外差测量。我们的方法利用了玻色模式之间的交叉克尔相互作用,这在超导电路架构中通常可实现。我们表明,通过调整输入态参数,该方案在实际实验条件下对耗散仍具有鲁棒性。我们的工作为在当前实验平台上实现多项式猫态提供了一条实用途径,无需非高斯初始资源,克服了现有制备方案的关键局限。

英文摘要

Superpositions of macroscopically distinct coherent states, or cat states, are a key resource for quantum technologies. In particular, two-mode binomial cat states can give rise to exact quantum error correction in continuous-variable quantum computing. However, their preparation typically requires non-Gaussian initial states, such as Fock or NOON states, which are challenging to realize experimentally. Here, we propose a protocol to generate two-mode binomial cat states where the only requirements are Gaussian initial states in combination with heralded heterodyne measurements. Our approach utilizes cross-Kerr interactions between bosonic modes commonly realizable in superconducting circuit architectures. We show that by adjusting the input state parameters, our protocol remains robust to dissipation under realistic experimental conditions. Our work provides a practical route to realizing multinomial cat states in current experimental platforms without requiring non-Gaussian initial resources, overcoming a key limitation of existing preparation schemes.

Comments12 pages with appendix and references, 2 figures

论文原文

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