原子损失的位置至关重要：中性原子量子纠错中的解码器感知风险沉积
Where Atom Loss Lands Matters: Decoder-Aware Risk Deposition in Neutral-Atom QEC
AI总结：
该研究针对中性原子量子纠错中原子损失位置影响逻辑错误率的问题，提出编译器侧优化方法CAST，通过优化损失沉积模式降低逻辑错误率，在多数物理规模设置中性能优于传统方法。
AI中文摘要：
中性原子阵列正成为可扩展量子纠错（QEC）的领先平台。量子比特在阵列中被路由和复用，同时检测到的损失作为擦除信息被报告给解码器。现有的中性原子编译器对这种移动（包括路由、穿梭和复用）进行优化，且通常通过标量暴露成本来建模损失。然而，总暴露量对于经擦除纠错的QEC而言是不完整的统计量：它仅捕获损失发生的数量，却未捕获其在量子纠错码上的位置，我们将此称为损失沉积。在相同的预期原子损失预算下，同一码块上不同的沉积模式会导致显著不同的逻辑错误率（LER）。我们将此形式化为解码器感知风险沉积，并提出CAST，一种编译器侧优化过程，该过程在角色索引的暴露台账上叠加码拓扑灵敏度图，在可比暴露约束下最小化解码器加权危害目标，仅使用局部路由、角色和接缝冷却操作。在表面码存储、物理规模架构模型、格手术和解码器失配检查中，CAST相较于拓扑盲暴露最小化降低了LER，在48个物理规模设置中的35个上表现更优，在暴露异质且路由有松弛的情况下提升幅度高达5.3倍。最大增益出现在高暴露与高解码器灵敏度初始未对齐时，此时CAST有空间将风险重定向至低影响的码角色。CAST表明，解码器感知原子损失风险沉积可作为中性原子QEC中的编译器侧优化过程进行优化。
英文摘要：
Neutral-atom arrays are emerging as a leading platform for scalable quantum error correction (QEC). Qubits are routed and reused across the array, while detected loss is reported to the decoder as erasure information. Existing neutral-atom compilers optimize this movement, including routing, shuttling, and reuse, and often model loss through scalar exposure costs. Yet total exposure is an incomplete statistic for erasure-corrected QEC. It captures how much loss occurs, but not where it lands on the code, which we call its deposition. Under the same expected atom-loss budget, different deposition patterns over a code patch induce substantially different logical error rates (LER). We formalize this as decoder-aware risk deposition and present CAST, a compiler-side optimization pass that overlays a code-topology sensitivity map on a role-indexed exposure ledger and minimizes a decoder-weighted harm objective under a comparable-exposure constraint, using only local route, role, and seam-cooling actions. Across surface-code memory, physical-scale architecture models, lattice surgery, and decoder-mismatch checks, CAST lowers LER relative to topology-blind exposure minimization, improving on it in 35 of 48 physical-scale settings and by as much as 5.3x where exposure is heterogeneous and routing has slack. The largest gains occur when high exposure and high decoder sensitivity are initially misaligned, giving CAST room to redirect risk toward lower-impact code roles. CAST shows that decoder-aware atom-loss risk deposition can be optimized as a compiler-side pass in neutral-atom QEC.
