用于投资组合优化的基于全局上下文注入的混合量子-经典协调架构
A Hybrid Quantum-Classical Coordination Architecture for Portfolio Optimization via Global Context Injection
- Origin Quantum Computing Technology (Hefei) Co., Ltd.（本源量子计算技术（合肥）有限公司）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
提出CAF混合量子-经典协调架构，通过全局上下文注入改进投资组合优化，在经典大规模测试中提升目标函数，并验证了跨后端兼容性与真实量子硬件可执行性。
AI中文摘要：
近期量子与量子启发式求解器在投资组合优化中，受限于严格规模约束，依赖局部子问题执行，但这种局部性可能遗漏对全局风险协调至关重要的跨聚类协方差。我们提出上下文感知折叠（CAF），一种轻量级混合量子-经典协调层，介于一次性静态分解与全矩阵优化之间。CAF通过状态相关的线性偏置将压缩的全局风险状态注入每个局部子问题，将局部候选生成与全局承诺解耦，并保留具有单调非发散保证的序贯接受规则。在2016年罗素3000子集（N=484）上，使用模拟退火（SA），CAF相较于静态基线将标量化均值-方差目标改进6.59%（20/20胜出），并在额外的2018年面板（N=1397，17/20胜出）上改进0.2579%。我们进一步报告了与量子近似优化算法（QAOA）和模拟量子退火（SQA）作为局部求解器的匹配折叠N=40兼容性研究，以及在Origin Quantum的Wukong 180（\ exttt{WK\_C180}）上对n=5的一个热启动QAOA子问题进行的冻结硬件在环运行。这些结果支持CAF作为一种协调架构，具有强大的经典大规模证据、跨后端兼容性，以及在嘈杂中等规模量子（NISQ）时代在真实量子硬件上的局部可执行性。
英文摘要：
Near-term quantum and quantum-inspired solvers for portfolio optimization rely on local subproblem execution under severe size constraints, but this locality can omit cross-cluster covariance essential for global risk coordination. We propose Context-Aware Folding (CAF), a lightweight hybrid quantum-classical coordination layer between one-shot static decomposition and full-matrix optimization. CAF injects a compressed global risk state into each local subproblem via a state-dependent linear bias, decouples local candidate generation from global commitment, and retains a sequential acceptance rule with a monotonic non-divergence guarantee. On a 2016 Russell 3000 subset (N=484) with Simulated Annealing (SA), CAF improves the scalarized mean-variance objective by 6.59\% over a static baseline (20/20 wins), and by 0.2579\% on an additional 2018 panel (N=1397, 17/20 wins). We further report matched folded N=40 compatibility studies with the Quantum Approximate Optimization Algorithm (QAOA) and simulated quantum annealing (SQA) as local solvers, together with a frozen hardware-in-the-loop run on Origin Quantum's Wukong 180 (\texttt{WK\_C180}) for one warm-started QAOA subproblem at n=5. These results support CAF as a coordination architecture with strong classical large-scale evidence, cross-backend compatibility, and local executability on real quantum hardware in the noisy intermediate-scale quantum (NISQ) era.
