发表机构
Shanghai Qi Zhi Institute（上海人工智能实验室）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对囚禁离子量子模拟器中任意相互作用图设计的核心挑战，提出残差引导优化协议设计多频全局驱动频谱，可实现近线性缩放的激光频数收敛至理论极限，能合成多种耦合拓扑并降低误差，提升了模拟器的可编程能力。
AI 中文摘要
囚禁离子量子模拟器是探索多体物理的强大平台，但任意相互作用图的工程设计仍是核心挑战。为利用本征运动模式的结构并提升可编程性，本文提出一种残差引导优化协议，用于系统设计多频全局驱动频谱。尽管可实现的相互作用保真度受限于可用运动模式，但该自适应策略使用与系统规模近线性缩放的激光频数，收敛至理论极限。该方法的通用性使其可合成长程耦合拓扑及传统上难以实现的短程耦合拓扑。此外，通过引入对残差运动激发的惩罚，该算法有效缓解了相空间轨迹未完全闭合带来的误差。总体而言，该可扩展框架显著扩展了囚禁离子架构的可编程能力，同时保持低计算开销，且具备很高的实验实现潜力。
英文摘要
Trapped-ion quantum simulators are powerful platforms for exploring many-body physics, yet engineering of arbitrary interaction graphs remains a central challenge. To leverage the intrinsic structure of native motional modes and thereby enhance programmability, a residual-guided optimization protocol is introduced for the systematic design of multi-tone global drive spectra. While the achievable interaction fidelity is fundamentally bounded by the available motional modes, this adaptive strategy converges on the theoretical limit using a number of laser tones that scales nearly linearly with system size. The versatility of this method enables the synthesis of both long-range and traditionally difficult short-range coupling topologies. Additionally, by incorporating a penalty for residual motional excitation, the algorithm effectively mitigates errors associated with incomplete closure of phase-space trajectories. Overall, this scalable framework significantly expands the programmable capabilities of trapped-ion architectures while maintaining low computational overhead and high potential for experimental implementation.
