论文标题

通过自适应学习增强量子接收器

Quantum Receiver Enhanced by Adaptive Learning

论文作者

Cui, Chaohan, Horrocks, William, Hao, Shuhong, Guha, Saikat, Peyghambarian, N., Zhuang, Quntao, Zhang, Zheshen

论文摘要

量子接收器旨在有效地导航庞大的量子状态空间,以赋予经典接收器无与伦比的量子信息处理功能。迄今为止,仅构建了少数量子接收器来解决歧视连贯状态的问题。但是,通过分析方法设计的量子接收器无法有效适应各种环境条件,从而随着操作复杂性的增加而迅速降低了性能。在这里,我们提出了一种通用体系结构,称为通过自适应学习(QREAL)增强的量子接收器,以使量子接收器结构适应各种操作条件。 QREAL是在具有创纪录效率的硬件平台中实验实现的。结合QREAL架构和实验进步,在两个相干态编码方案中,错误率在标准量子限制上降低了40%。

Quantum receivers aim to effectively navigate the vast quantum-state space to endow quantum information processing capabilities unmatched by classical receivers. To date, only a handful of quantum receivers have been constructed to tackle the problem of discriminating coherent states. Quantum receivers designed by analytical approaches, however, are incapable of effectively adapting to diverse environment conditions, resulting in their quickly diminishing performance as the operational complexities increase. Here, we present a general architecture, dubbed the quantum receiver enhanced by adaptive learning (QREAL), to adapt quantum receiver structures to diverse operational conditions. QREAL is experimentally implemented in a hardware platform with record-high efficiency. Combining the QREAL architecture and the experimental advances, the error rate is reduced up to 40% over the standard quantum limit in two coherent-state encoding schemes.

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