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arXiv quant-ph/0407135quant-phcond-mat.othermath.OC
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纠缠理论中有效逼近的完备族

Complete hierarchies of efficient approximations to problems in entanglement theory

J. Eisert, P. Hyllus, O. Guehne, M. Curty

摘要:

本文从凸优化的角度研究了纠缠理论中的几个问题。这一系列问题包括:(A)判定一个状态是否是多方纠缠的,(B)纠缠见证者相对于纯乘积态的期望值的最小化,(C)量化纯多方纠缠的纠缠几何度量的密切相关的评估,(D)基于二阶矩和线性熵准则的证据检验状态是否多方纠缠,以及(E)评估量子信道的最大输出纯度的实例。我们证明这些问题可以被表述为某些优化问题:采用三次或更少次多项式的多项式约束问题。然后,我们将最近建立的半定松弛理论中的已知方法应用于所表述的优化问题。通过这种结构,我们到达一个层次的有效可解的近似的解决方案,近似的精确解,如所需的,在一种方式,是渐近完成。例如,这导致了一个新的层次结构,有效地判定多粒子纠缠的充分标准,使得每个纠缠态都必须在层次结构的某个步骤中被检测到。最后,我们提出了数值例子来证明这种方法的实际可达性。

英文摘要:

We investigate several problems in entanglement theory from the perspective of convex optimization. This list of problems comprises (A) the decision whether a state is multi-party entangled, (B) the minimization of expectation values of entanglement witnesses with respect to pure product states, (C) the closely related evaluation of the geometric measure of entanglement to quantify pure multi-party entanglement, (D) the test whether states are multi-party entangled on the basis of witnesses based on second moments and on the basis of linear entropic criteria, and (E) the evaluation of instances of maximal output purities of quantum channels. We show that these problems can be formulated as certain optimization problems: as polynomially constrained problems employing polynomials of degree three or less. We then apply very recently established known methods from the theory of semi-definite relaxations to the formulated optimization problems. By this construction we arrive at a hierarchy of efficiently solvable approximations to the solution, approximating the exact solution as closely as desired, in a way that is asymptotically complete. For example, this results in a hierarchy of novel, efficiently decidable sufficient criteria for multi-particle entanglement, such that every entangled state will necessarily be detected in some step of the hierarchy. Finally, we present numerical examples to demonstrate the practical accessibility of this approach.

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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