AI 中文总结
研究在固定重放接口下四个量子软件栈中解码器行为，通过特定电路请求流经多种方法重放并比较，实现行级完整性，家族内排序稳定，BP减少干预量，比较具有栈感知且避免跨家族阈值等效性声明。
AI 中文摘要
我们在固定的重放接口下，对四个综合征生成栈（PennyLane、Qiskit、Cirq和一个LiDMaS+参考栈）的解码器行为进行了保留契约、家族感知的比较。来自重复轮表面码和数字化GKP电路的请求流通过具有匹配控制的BP、MWPM和UF进行重放。统一矩阵跨越24个单元并实现了行级完整性。家族内排序稳定，不同方法有不同的翻转计数，BP相对于MWPM在表面码和GKP中减少了平均干预量。源与参考的效应因家族而异，比较是栈感知、契约验证的，避免了原始的跨家族阈值等效性声明。
英文摘要
We present a contract-preserving, family-aware comparison of decoder behavior across four syndrome-generation stacks (PennyLane, Qiskit, Cirq, and a LiDMaS+ reference) under a fixed replay interface. Request streams from repeated-round surface-code and digitized-GKP circuits are replayed through BP, MWPM, and UF with matched controls. The unified matrix spans 24 cells and achieves line-level integrity: $24\,000$ request lines, $24\,000$ response lines, response ratio $=1.0$ in every cell, zero parse failures, and zero decoder-name mismatches. Fifteen warning-no-syndrome events occur only in GKP-Cirq rows. Within-family ordering is stable in both families ($\mathrm{BP}<\mathrm{MWPM}<\mathrm{UF}$); source-averaged flip counts are 2.435, 4.768, and 5.870 for surface and 1.595, 2.908, and 3.681 for GKP. Relative to MWPM, BP reduces mean intervention volume by $48.9\%$ in surface and $45.1\%$ in GKP. Source-vs-reference effects are family dependent, with larger coherent shifts in GKP. Source-bootstrap ranks remain unchanged, and hidden-truth sidecars add an outer-code logical-parity error-rate check in which UF has the largest source-mean rate in both families. The comparison is stack-aware, contract-verified, and avoids raw cross-family threshold-equivalence claims.
