Power flow calculation plays an important role in planning, operation, and control of the power system. The quantum HHL algorithm can achieve theoretical exponential speedup over classical algorithms on DC power flow calculation. Since the qubit resources in the Noisy Intermediate-scale Quantum (NISQ) era are limited, it is important to discuss the performance considering this limitation. The coefficient matrix of the linear systems of equations in DC power flow problems cannot be represented perfectly by finite binary number strings, which leads to imperfect phase estimation. This work is carried out under the assumption of imperfect phase estimation. The performance of the HHL algorithm is systematically investigated with different accuracy and redundant qubits. In order to further reduce the required qubit resources, a hybrid quantum-classical algorithm is proposed. By comparing errors of the HHL and hybrid algorithms in the DC power flow calculation of the IEEE 5-bus test system, it is found that the hybrid algorithm can achieve comparable precision with fewer qubits than HHL by increasing the number of phase estimation modules, which may make the hybrid algorithm a feasible route in the NISQ era.
Distributed quantum-classical hybrid algorithm for solving K-SAT problem
School of Computer Science and Engineering, Sun Yat-sen University（中山大学计算机学院）；The Guangdong Key Laboratory of Information Security Technology, Sun Yat-sen University（中山大学广东省信息安全技术重点实验室）；Shenzhen Research Institute of Sun Yat-Sen University（中山大学深圳研究院）；School of Physics and Astronomy, Sun Yat-sen University（中山大学物理与天文学院）；Departamento de Matemática, Instituto Superior Técnico, Instituto de Telecomunicações（里斯本高等理工学院数学系，电信研究所）
Solving Constrained Optimization Problems Using Hybrid Qubit-Qumode Quantum Devices
Yale University（耶鲁大学）；Massachusetts Institute of Technology（麻省理工学院）；University of Connecticut（康涅狄格大学）；RTX Technology Research Center（RTX技术研究中心）；University of Massachusetts-Amherst（马萨诸塞大学阿默斯特分校）
Quantum-Classical Hybrid Algorithm for Solving the Learning-With-Errors Problem on NISQ Devices
Beijing Academy of Quantum Information Sciences（北京量子信息科学研究院）；State Key Laboratory of Low-Dimensional Quantum Physics and Department of Physics, Tsinghua University（清华大学物理系低维量子物理国家重点实验室）；State Key Laboratory of Mathematical Engineering and Advanced Computing（数学工程与先进计算国家重点实验室）；Division of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University（南洋理工大学物理与数学科学学院物理与应用物理系）
Solving Drone Routing Problems with Quantum Computing: A Hybrid Approach Combining Quantum Annealing and Gate-Based Paradigms
TECNALIA（泰克纳利亚技术研究中心）；Basque Research and Technology Alliance (BRTA)（巴斯克研究与技术联盟）；National Centre for Scientific Research “Demokritos”（德谟克利特国家科学研究中心）；Fraunhofer Institute for Open Communication Systems (FOKUS)（弗劳恩霍夫开放通信系统研究所）
