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arXiv 2405.09613quant-phcond-mat.stat-mechmath-phmath.MP

正部分转置操作下的可计算纠缠成本

Computable entanglement cost under positive partial transpose operations

Ludovico Lami, Francesco Anna Mele, Bartosz Regula

AI总结:

本文针对PPT操作下制备含噪量子态的渐近纠缠成本计算问题,构造半定规划层级绕开正则化难题,并证明其指数收敛,首次实现无闭式公式的渐近纠缠度量的高效可计算性。

摘要:

量子信息理论长期受到正则化问题的困扰,这类问题需要对难以处理的渐近量进行求值。这使得精确量化关键操作任务(如纠缠操控)的最终效率在计算上变得不可行。本文考虑在正部分转置(PPT)量子操作下制备含噪量子态的渐近纠缠成本的计算问题。通过一个解析例子,我们证明先前针对该问题所声称的一个解是不正确的。基于先前用正则化公式对PPT纠缠成本所作的刻画,我们转而构造了一个半定规划层级,该层级完全绕开了正则化问题,并收敛到纠缠成本的真实渐近值。我们的主要结果证明这种收敛以指数速度发生,从而得到一个高效算法,可在时间$\mathrm{poly}(D,\\,\log(1/\varepsilon))$内以加性误差$\varepsilon$近似该成本,其中$D$是底层希尔伯特空间的维度。据我们所知,这是首次证明一个渐近纠缠度量在没有闭式公式的情况下仍可被高效计算。

英文摘要:

Quantum information theory is plagued by the problem of regularisations, which require the evaluation of formidable asymptotic quantities. This makes it computationally intractable to gain a precise quantitative understanding of the ultimate efficiency of key operational tasks such as entanglement manipulation. Here we consider the problem of computing the asymptotic entanglement cost of preparing noisy quantum states under quantum operations with positive partial transpose (PPT). By means of an analytical example, a previously claimed solution to this problem is shown to be incorrect. Building on a previous characterisation of the PPT entanglement cost in terms of a regularised formula, we construct instead a hierarchy of semi-definite programs that bypasses the issue of regularisation altogether, and converges to the true asymptotic value of the entanglement cost. Our main result establishes that this convergence happens exponentially fast, thus yielding an efficient algorithm that approximates the cost up to an additive error $\varepsilon$ in time $\mathrm{poly}(D,\,\log(1/\varepsilon))$, where $D$ is the underlying Hilbert space dimension. To our knowledge, this is the first time that an asymptotic entanglement measure is shown to be efficiently computable despite no closed-form formula being available.

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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