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arXiv 2007.07246quant-phcond-mat.stat-mech
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使用广义量子测量量化信息提取

Quantifying Information Extraction using Generalized Quantum Measurements

Dominik Šafránek, Juzar Thingna

AI总结:

本文将观测熵的解释从理想投影测量推广到广义量子测量,建立量化测量序列信息提取能力的框架,并分析间接测量、von Neumann 方案及量子态推断应用。

摘要:

观测熵被解释为进行测量的观察者与一个系统相关联的不确定性。到目前为止,使这种解释成为可能的性质依赖于理想投影测量的假设。我们证明,即使考虑广义测量,同样的性质仍然成立。因此,该解释依然成立:观测熵是一个定义良好的量化器,用于确定给定测量序列在信息提取中的影响程度。这一广义框架使得研究间接测量方案的性能成为可能,间接测量方案即那些使用探针的方案。利用该框架,我们首先分析了有限维探针的局限性。随后,我们研究了 von Neumann 测量方案的若干情形,在这些情形中探针是由其位置表征的经典粒子。最后,我们讨论了观测熵作为量子态推断工具的作用。进一步发展后,该框架可在量子信息处理中获得应用。例如,它可以帮助确定从量子存储器中读取信息的最佳程序,并提供可替代量子态层析的自适应测量策略。

英文摘要:

Observational entropy is interpreted as the uncertainty an observer making measurements associates with a system. So far, properties that make such an interpretation possible rely on the assumption of ideal projective measurements. We show that the same properties hold even when considering generalized measurements. Thus, the interpretation still holds: Observational entropy is a well-defined quantifier determining how influential a given series of measurements is in information extraction. This generalized framework allows for the study of the performance of indirect measurement schemes, which are those using a probe. Using this framework, we first analyze the limitations of a finite-dimensional probe. Then we study several scenarios of the von Neumann measurement scheme, in which the probe is a classical particle characterized by its position. Finally, we discuss observational entropy as a tool for quantum state inference. Further developed, this framework could find applications in quantum information processing. For example, it could help in determining the best read-out procedures from quantum memories and to provide adaptive measurement strategies alternative to quantum state tomography.

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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