用绝热量子计算求解实际给水管网中的传感器配置问题
Solving Sensor Placement Problems In Real Water Distribution Networks Using Adiabatic Quantum Computation
摘要：
量子退火是近年来出现的一种解决大规模组合最优化问题的量子计算方法。在本文中，我们制定的问题正确放置压力传感器的供水管网（WDN）作为一个组合最优化问题的形式，二次无约束二进制优化（QUBO）或伊辛模型。最佳传感器位置确实是检测和隔离故障事件的关键。我们概述了QUBO和伊辛公式的传感器布局问题从网络拓扑结构和一些其他功能。我们提出了一个详细的过程来解决这个问题，通过使用PyQUBO，一个开源的Python库最小化其哈密顿量。然后，我们将我们的方法应用到一个真正的配水网络的情况下。模拟退火和混合量子经典的方法上的D波机。
英文摘要：
Quantum annealing has emerged in the last few years as a promising quantum computing approach to solving large-scale combinatorial optimization problems. In this paper, we formulate the problem of correctly placing pressure sensors on a Water Distribution Network (WDN) as a combinatorial optimization problem in the form of a Quadratic Unconstrained Binary Optimization (QUBO) or Ising model. Optimal sensor placement is indeed key to detect and isolate fault events. We outline the QUBO and Ising formulations for the sensor placement problem starting from the network topology and few other features. We present a detailed procedure to solve the problem by minimizing its Hamiltonian using PyQUBO, an open-source Python Library. We then apply our methods to the case of a real Water Distribution Network. Both simulated annealing and a hybrid quantum-classical approach on a D-Wave machine are employed.
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