中性原子量子处理器的交互感知嵌入优化
Interaction-Aware Embedding Optimization for Neutral-Atom Quantum Processors
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中文总结 AI 辅助
针对中性原子量子处理器，提出一种面向交互的力导向嵌入优化方法，显著提升嵌入可行性与解质量，且在大规模实例上保持可靠。
中文摘要 AI 辅助
基于中性原子的量子计算机能够在实验运行之间动态重塑量子比特寄存器几何结构。这一能力使得不同类型的问题可以直接映射到硬件上，显著提高了解决复杂优化和机器学习用例的效率。然而，这种灵活性需要找到原子位置以实现目标成对交互，从而引发为搭建量子机器而进行困难非凸优化的需求。在本工作中，我们引入了一种新的力导向方法，该方法针对交互作用以将输入问题编码到量子计算机上。数值结果表明，我们的新方法可以将嵌入可行性和解质量提高数量级，并且在大规模实例上保持可靠性。
英文摘要
Neutral atom-based quantum computers have the ability to dynamically reshape the qubit register geometry between experimental runs. This capability enables different types of problems to be mapped directly onto the hardware, significantly enhancing the efficiency of solving, for instance, complex optimization and machine learning use-cases. However, this flexibility requires finding atom positions to implement target pairwise interactions, inducing a difficult nonconvex optimization for setting up the quantum machine. In this work, we introduce a new force-directed method that targets interactions to encode the input problem on the quantum computer. Numerical results show that our new method can improve embedding feasibility and solution quality by orders of magnitude, and remains reliable on the largest instances.
发表机构
- Pasqal（帕斯卡尔）
机构由 AI 辅助整理，请以论文原文为准。
