纯化在顺序量子信道鉴别中带来优势
Purification enables an unbounded query separation in sequential quantum channel discrimination
- Sorbonne Université, CNRS, LIP6（索邦大学，法国国家科学研究中心，LIP6）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文证明在顺序量子信道鉴别中，利用纯化资源（即使环境参考系未知）能严格提升成功概率，优于裸访问和平行策略，并给出具体信道实例验证该优势。
AI中文摘要：
纯化常被用作构建量子信息处理任务协议时量子态和信道的便捷数学表示。尽管这种视角很强大，但它可能暗示纯化自由度及其与环境的关联仅仅是一种有用的表示变换。在这里，我们展示了即使在环境参考系未知或被平均化的情况下，这些自由度如何被利用为顺序量子信道鉴别中的操作性资源。与态鉴别和平行信道鉴别（其中裸访问和平均纯化访问是等价的）不同，对纯化资源的顺序访问在成功概率上展现出严格优势。我们通过两个主要结果证明了这种严格分离。首先，我们构造了两族量子比特-量子比特信道，在两次查询情况下具有严格分离；其次，我们展示了一对量子比特-量子比特信道的例子，其纯化在三次查询下可完美区分，而任何有限次数的裸（非纯化）查询都不足以实现完美区分。这些分离意味着顺序策略在信道鉴别中优于平行策略，并确立了通过允许查询间任意干预的变换将裸信道查询转换为平均纯化查询的不可能性，从而加强了先前的结果。
英文摘要：
Purifications are often used as a convenient mathematical representation of quantum states and channels when constructing protocols for quantum information processing tasks. Although powerful, this perspective can suggest that the purifying degrees of freedom and its correlations with an environment are just a useful change of representation. Here we show how they can instead be exploited as an operational resource in sequential quantum channel discrimination, even when the environmental reference frame is unknown or averaged. In contrast to state discrimination and parallel channel discrimination, for which bare and averaged-purification access are equivalent, sequential access to purified resources exhibits a strict advantage in probability of success. We prove this strict separation via two main results. In the first, we construct a pair of families of qubit-qubit channels with a strict separation in the two-query case, and in the second, we show an example of a pair of qubit-qubit channels whose purifications are perfectly distinguishable with three queries while no finite number of bare (non-purified) queries suffices for perfect discrimination. These separations imply an advantage of sequential over parallel strategies for channel discrimination and establish the impossibility of converting bare channel queries into averaged-purification queries via transformations that allow arbitrary interventions between queries, strengthening previous results.
