提出量子-经典混合搜索框架，高效发现稀有参数下的科学阈值突破点。
QC-PHAST Search: Classical--Quantum Query Benchmarks for Finite-Pool Rare-Regime Discovery
- 基于证据门控与查询计数的决策协议，动态评估搜索策略有效性。
- 在有限候选池中实现可验证的首次命中，避免虚假阳性与校准成本浪费。
- 适用于需高可信度发现的科学计算场景，如物理系统临界态探测。
在参数化动力系统中，稀有情形发现是一个主动搜索问题：需在候选稀少、非凸或碎片化的条件下，找到一个经验证的参数使科学定义的定性阈值被跨越。我们提出量子-经典相空间与稳定性阈值搜索（QC-PHAST），一种针对有限候选库的证据门控决策协议与查询计数框架。每个候选生成动力学对象、模拟器推导的临界性评分及已验证首次命中谓词。利用科学元数据与带费试点证据，判断方程感知搜索、标量评分主动搜索、仅谓词搜索或仅查询模型比较是否可行。量子部分沿用格罗弗/博耶-布拉萨德-霍耶-塔普（BBHT）未知-M标记集查询基准，非新量子搜索定理、电路实现或硬件加速声明。最终生成区域图。直接边界构造、几何控制、在线模拟循环和学习标签计账进一步识别何时经典结构、假阳性、校准成本或状态制备会侵蚀查询模型优势。因此，QC-PHAST是可审计的协议，用于判断有限池标记集参考是否具信息量，以及何时应由经典或资源敏感型搜索主导。
原文摘要 · Abstract (English)
Rare-regime discovery in parameterized dynamical systems is an active-search problem: find one verified parameter at which a scientifically defined qualitative threshold is crossed, even when acceptable candidates are rare, nonconvex, or fragmented. We introduce Quantum-Classical Phase-space and Stability-Threshold Search (QC-PHAST), an evidence-gated decision protocol and query-accounting framework for finite candidate libraries. A candidate induces a dynamical object, simulator-derived criticality score, and verified first-hit predicate. Scientific metadata and charged pilot evidence are used to assess whether equation-aware search, scalar-score active search, predicate-only search, or only a query-model comparison is admissible. The quantum row is the inherited Grover/Boyer--Brassard--Hoyer--Tapp (BBHT) unknown-$M$ marked-set query reference; it is not a new quantum-search theorem, materialized circuit, or hardware-speedup claim. The result is a regime map. Direct boundary constructions, geometry controls, online simulator loops, and learned-label accounting further identify when classical structure, false positives, calibration cost, or state preparation erases the query-model margin. QC-PHAST is therefore an auditable protocol for deciding when a finite-pool marked-set reference is informative and when classical or resource-aware search should dominate.
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