AlchemQ：带逐结果等价证书的证明携带式量子电路优化
AlchemQ: Proof-Carrying Quantum Circuit Optimization with Per-Result Equivalence Certificates
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中文总结 AI 辅助
AlchemQ将不受信任的束搜索优化器与可机器检查的逐结果证书相结合，通过ZX演算和数值回退证明等价性，确保每个优化电路可验证且无回归，在100电路基准上全部通过认证并检测所有突变。
中文摘要 AI 辅助
我们提出AlchemQ v0.5，一个概念验证系统，它将不受信任的束搜索优化器与机器可检查的逐结果认证层以及版本化证书协议（0.2.0）相结合，使得每个优化后的电路都附带可验证的工件而非空泛的声明。认证器通过ZX演算全归约证明等价性直至全局相位，并基于最优Hilbert-Schmidt重叠提供数值张量回退方案。证书是自包含且防篡改的：包含规范门canon-v1哈希、实测残差、三态判定（已认证/已拒绝/不确定）以及用于跨平台可复现性的版本化相位注释模式。该智能体聚合三个模糊t-范数，不能返回未认证的电路，并且自v0.4起保证相对于原始电路无逐分量回归。在100个电路的基准测试中，所有400次优化均无错误终止，每个返回的电路均被认证，每次突变均被检测到，并且一个包含2998个测试的测试套件在两个平台上通过。PyZX基线很强（在82个电路上平均T计数减少21.4%），而该智能体在9/100个电路上严格更优；三个t-范数在所有100个标准实例上返回相同电路，仅在一个对抗性套件的4/38个实例上产生分歧。两个案例研究是新的：一个假阴性案例被根因定位为PyZX的compare_tensors中的枢轴归一化错误（枢轴残差4.7e-9；最优重叠残差为7.4e-11），以及八个证书在macOS上因phase_note中依赖BLAS的浮点数而被拒绝。两者均已修复；所有工件集在两个平台上均验证通过400/400。在IBM Heron r2上的试点运行给出了一个深度减少78%、双量子比特门减少65%的已认证电路；输出质量在所有三个指标上均偏向该电路，但在1024次采样下不显著。我们发布了证书规范和独立参考验证器（Apache-2.0）及数据和脚本；引擎是专有的。
英文摘要
We present AlchemQ v0.5, a proof-of-concept system that couples an untrusted beam-search optimizer with a machine-checkable per-result certification layer and a versioned certificate protocol (0.2.0), so that every optimized circuit ships with a verifiable artifact rather than a bare claim. The certifier proves equivalence up to global phase by ZX-calculus full reduction, with a numeric-tensor fallback based on the optimal Hilbert-Schmidt overlap. Certificates are self-contained and tamper-evident: canonical gate-canon-v1 hashes, measured residuals, tri-state verdicts (certified/rejected/inconclusive), and versioned phase-note schemas for cross-platform reproducibility. The agent aggregates three fuzzy t-norms, cannot return an uncertified circuit, and since v0.4 guarantees no componentwise regression against the original. On a benchmark of 100 circuits, all 400 optimizations terminate without error, every returned circuit is certified, every mutation is detected, and a 2998-test suite passes on two platforms. The PyZX baseline is strong (21.4% mean T-count reduction over 82 circuits) and the agent is strictly better on 9/100; the three t-norms return identical circuits on all 100 standard instances, diverging only on 4/38 of an adversarial suite. Two case studies are new: a false negative root-caused to a pivot-normalization bug in PyZX's compare_tensors (pivot 4.7e-9; the optimal-overlap residual is 7.4e-11), and eight certificates rejected on macOS due to BLAS-dependent floats in phase_note. Both were fixed; all artifact sets validate 400/400 on both platforms. A pilot run on IBM Heron r2 gives a certified circuit 78% shallower with 65% fewer two-qubit gates; output quality favors it on all three metrics but is not significant at 1024 shots. We release the certificate specification and a standalone reference verifier (Apache-2.0) with data and scripts; the engine is proprietary.
发表机构
- TriStiX S.L.
机构由 AI 辅助整理，请以论文原文为准。
