Q-MAP：用于相干受控孤岛的多平台分布式量子计算基准测试

中文摘要 AI 辅助

分布式能源资源接入电网的速度正在加快。由此产生的波动性收窄了运行裕度，因此一次扰动可能级联成大范围停电。受控孤岛通过将受损电网分割成自维持的孤岛来阻止这种传播，这些孤岛保持相干发电机在一起。随着母线数量和孤岛数量的增加，精确的经典求解变得难以处理。基于门的量子优化为穿越这个组合空间提供了另一条途径，尽管当单个电路承载所有母线分配时，其能力受到限制，因为量子比特数和深度随后跟随电网规模。在本研究中，开发了一个轮同步分布式量子计算框架，用于在固定的每电路量子比特预算下进行相干受控孤岛。每一轮从一个冻结的电网范围快照中推导出所有区域子问题，同时将它们分派给独立的量子后端，并将返回的候选解经典地合并为一个全局评估的更新。因此，并行执行的电路在电网增长时保持恒定大小，一轮的成本取决于最慢的区域而不是所有区域的总和。基准测试涵盖从9到300母线的IEEE系统，在模拟和不同架构的量子处理器上进行。该框架在噪声下于每个平台上都实现了最优且可操作的分区，即使编译成本相差近一个数量级。以这种方式限制宽度，使超出单片电路范围的电网落入当前设备的可及范围，并为大规模电力系统优化中的量子计算建立了多后端基线。

英文摘要

The integration of distributed energy resources into power networks is accelerating. The resulting variability narrows operating margins, so a disturbance can cascade into a wide-area blackout. Controlled islanding arrests that propagation by splitting a compromised grid into self-sustaining islands that keep coherent generators together. Exact classical solutions become intractable as the bus count and island number grow. Gate-based quantum optimization provides a different route through this combinatorial space, although its reach is limited when one circuit carries every bus assignment, since qubit count and depth then follow grid size. In this study, a round-synchronous distributed quantum computing framework is developed for coherent controlled islanding under a fixed per-circuit qubit budget. Every round derives all regional subproblems from one frozen grid-wide snapshot, dispatches them to independent quantum backends at the same time, and merges the returned candidates classically into one globally evaluated update. Circuits executed in parallel therefore keep a constant size as the grid grows, and a round costs the slowest region rather than the sum of all of them. Benchmarking spans IEEE systems from 9 to 300 buses on simulation and on quantum processors of different architectures. The framework attains optimal and operationally feasible partitions on every platform under noise, even where compilation cost differs by nearly an order of magnitude. Bounding width in this way places grids beyond the reach of monolithic circuits within range of present devices and establishes a multi-backend baseline for quantum computing in large-scale power-system optimization.

发表机构

• The Pennsylvania State University（宾夕法尼亚州立大学）
• Rensselaer Polytechnic Institute（伦斯勒理工学院）
• Kent State University（肯特州立大学）
• Clemson University（克莱姆森大学）
• University of Pretoria（比勒陀利亚大学）

机构由 AI 辅助整理，请以论文原文为准。