论文标题
资源有效量子网络的量子语义通信
Quantum Semantic Communications for Resource-Efficient Quantum Networking
论文作者
论文摘要
量子通信网络（QCN）利用量子力学来进行安全信息传输，但是依赖脆弱且昂贵的光子量子资源使QCN资源优化挑战QCN。与先前的QCN作品不同，依赖于盲目压缩经典数据的直接量子嵌入，这封信提出了一种新型的量子语义通信（QSC）框架，利用量子机器学习中的进步和量子语义表示的进步到提取物中的进步，并仅将相关信息从经典数据中的相关信息嵌入到最小量子状态的量子量中，以使量子频道准确地通道和量子频道准确。仿真结果表明，与语义无关QCN方案相比，所提出的框架可在所需的量子通信资源中减少约50-75％，同时实现更高的量子语义忠诚度。
Quantum communication networks (QCNs) utilize quantum mechanics for secure information transmission, but the reliance on fragile and expensive photonic quantum resources renders QCN resource optimization challenging. Unlike prior QCN works that relied on blindly compressing direct quantum embeddings of classical data, this letter proposes a novel quantum semantic communications (QSC) framework exploiting advancements in quantum machine learning and quantum semantic representations to extracts and embed only the relevant information from classical data into minimal high-dimensional quantum states that are accurately communicated over quantum channels with quantum communication and semantic fidelity measures. Simulation results indicate that, compared to semantic-agnostic QCN schemes, the proposed framework achieves approximately 50-75% reduction in quantum communication resources needed, while achieving a higher quantum semantic fidelity.
