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arXiv 2610.15664quant-ph
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通过重排实现的纠缠可分性判据与下界

Separability criteria and lower bounds of entanglement via realignment

School of Mathematics and Statistics, Henan University(河南大学数学与统计学院);School of Mathematics Sciences, Capital Normal University(首都师范大学数学科学学院)

Yuhang Xie, Yanjun Chu, Shao-Ming Fei

AI总结:

该研究针对量子信息科学中纠缠检测与量化的核心问题,基于密度矩阵重排和约化密度矩阵向量化构造增强型可分性判据,推导并发度等的更紧下界,通过示例验证了结果优势。

摘要:

量子纠缠的检测与量化是量子信息科学的核心问题。基于密度矩阵的重排和约化密度矩阵的向量化,我们构造了适用于 bipartite 和 multipartite 量子系统的一系列增强型可分性判据。我们的判据将先前提出的基于重排的判据作为特例包含在内,且能检测到比早期判据更多的纠缠。此外,我们推导了并发度、凸包扩展负性的更紧下界,以及真正三体纠缠的判据,还有真正多体纠缠并发度的下界。通过详细示例展示了我们结果的优势。

英文摘要:

The detection and quantification of quantum entanglement are central problems in quantum information science. Based on the realignment of density matrices and the vectorization of reduced density matrices, we construct a family of enhanced separability criteria for bipartite and multipartite quantum systems. Our criteria recover the previously proposed realignment-based criteria as special cases and detect more entanglement than the earlier ones. Moreover, we derive tighter lower bounds for the concurrence and the convex-roof extended negativity, criteria for detecting the genuine tripartite entanglement, and lower bounds on genuine-multipartite-entanglement concurrence. The advantages of our results are demonstrated with detailed examples.

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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