prepare-and-measure场景中确定性量子关联集合的表征
Characterising the set of deterministic quantum correlations in prepare-and-measure scenarios
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中文总结 AI 辅助
本研究针对prepare-and-measure场景中确定性量子关联的识别挑战，提出基于经典侧信息对手的验证方法，并针对三种通信限制定制半定规划松弛方法，推进了量子关联表征的研究。
中文摘要 AI 辅助
不具备确定性解释的关联是量子理论的核心特征，也是量子信息处理的关键资源。然而，识别并验证此类关联仍是一项基础挑战。本研究针对prepare-and-measure场景中符合多种通信限制的确定性关联推进该问题的解决，为验证与这类确定性模型不兼容的关联，我们探究这些关联是否能在配备经典侧信息的对手可完美预测测量结果的场景中成立。我们证明了该方法的实用性，并针对三种代表性通信限制（固定系综、有界重叠、受限可观测量）提出定制化的半定规划松弛方法。
英文摘要
Correlations that do not admit a deterministic explanation are a central feature of quantum theory and a key resource for quantum information processing. Identifying and certifying such correlations, however, remains a fundamental challenge. In this work, we advance on this problem by considering deterministic correlations in the prepare-and-measure scenario consistent with a wide range of communication restrictions. To certify correlations incompatible with such deterministic models, we ask whether they admit a scenario in which measurement outcomes can be perfectly predicted by an adversary equipped with classical side-information. We show the usefulness of this approach and propose semidefinite programming relaxations tailored to three representative communication restrictions: fixed ensemble, bounded overlaps and restricted observables.
