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arXiv 2408.12554quant-ph
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用单一演化算符刻画非高斯连续变量态的多体纠缠结构

Characterizing the Multipartite Entanglement Structure of Non-Gaussian Continuous-Variable States with a Single Evolution Operator

Mingsheng Tian, Xiaoting Gao, Boxuan Jing, Feng-Xiao Sun, Matteo Fadel, Manuel Gessner, Qiongyi He

AI总结:

本文提出一种基于量子Fisher信息的高效方法,通过识别最优编码算符检测连续变量多模非高斯态的多体纠缠结构,在超$10^5$随机态上成功率极高,且扩展算符集可增强抗损耗鲁棒性,为实验应用提供通用框架。

摘要:

多体纠缠是量子信息任务的重要资源,但刻画连续变量系统中的纠缠结构仍具挑战性,特别是在多模非高斯场景中。本文提出了一种有效检测连续变量态多体纠缠结构的方法。基于量子Fisher信息,我们提出一种系统性方法来识别最优编码算符,该算符能捕捉多模非高斯态中的量子关联。我们在超过$10^5$个随机生成的多模纠缠量子态上验证了方法的有效性,在纠缠检测中取得了极高的成功率。此外,通过扩展可访问算符集合,该方法对损耗的鲁棒性可得到显著增强。本工作为刻画多样连续变量系统中的纠缠结构提供了通用框架,支持多项实验相关应用。

英文摘要:

Multipartite entanglement is an essential resource for quantum information tasks, but characterizing entanglement structures in continuous variable systems remains challenging, especially in multimode non-Gaussian scenarios. In this work, we introduce an efficient method for detecting multipartite entanglement structures in continuous-variable states. Based on the quantum Fisher information, we propose a systematic approach to identify an optimal encoding operator that can capture the quantum correlations in multimode non-Gaussian states. We demonstrate the effectiveness of our method on over $10^5$ randomly generated multimode-entangled quantum states, achieving a very high success rate in entanglement detection. Additionally, the robustness of our method can be considerably enhanced against losses by expanding the set of accessible operators. This work provides a general framework for characterizing entanglement structures in diverse continuous variable systems, enabling a number of experimentally relevant applications.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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