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Quantum annealing has emerged in the last few years as a promising quantumcomputing approach to solving large-scale combinatorial optimization problems.In this paper, we formulate the problem of correctly placing pressure sensorson a Water Distribution Network (WDN) as a combinatorial optimization problemin the form of a Quadratic Unconstrained Binary Optimization (QUBO) or Isingmodel. Optimal sensor placement is indeed key to detect and isolate faultevents. We outline the QUBO and Ising formulations for the sensor placementproblem starting from the network topology and few other features. We present adetailed procedure to solve the problem by minimizing its Hamiltonian usingPyQUBO, an open-source Python Library. We then apply our methods to the case ofa real Water Distribution Network. Both simulated annealing and a hybridquantum-classical approach on a D-Wave machine are employed.

Solving Sensor Placement Problems In Real Water Distribution Networks Using Adiabatic Quantum Computation