Quafu-Qcover: Explore combinatorial optimization problems on cloud-based quantum computers

• Published in: Chinese physics B Vol. 33; no. 5; pp. 50302 - 116
• Main Authors: Xu, Hong-Ze, Zhuang, Wei-Feng, Wang, Zheng-An, Huang, Kai-Xuan, Shi, Yun-Hao, Ma, Wei-Guo, Li, Tian-Ming, Chen, Chi-Tong, Xu, Kai, Feng, Yu-Long, Liu, Pei, Chen, Mo, Li, Shang-Shu, Yang, Zhi-Peng, Qian, Chen, Jin, Yu-Xin, Ma, Yun-Heng, Xiao, Xiao, Qian, Peng, Gu, Yanwu, Chai, Xu-Dan, Pu, Ya-Nan, Zhang, Yi-Peng, Wei, Shi-Jie, Zeng, Jin-Feng, Li, Hang, Long, Gui-Lu, Jin, Yirong, Yu, Haifeng, Fan, Heng, Liu, Dong E., Hu, Meng-Jun
• Format: Journal Article
• Language: English
• Published: Chinese Physical Society and IOP Publishing Ltd 01.04.2024
• Subjects: combinatorial optimization problems; quantum cloud platform; quantum software; quantum cloud platform; combinatorial optimization problems; quantum software
• ISSN: 1674-1056; 2058-3834
• DOI: 10.1088/1674-1056/ad18ab

We introduce Quafu-Qcover, an open-source cloud-based software package developed for solving combinatorial optimization problems using quantum simulators and hardware backends. Quafu-Qcover provides a standardized and comprehensive workflow that utilizes the quantum approximate optimization algorithm (QAOA). It facilitates the automatic conversion of the original problem into a quadratic unconstrained binary optimization (QUBO) model and its corresponding Ising model, which can be subsequently transformed into a weight graph. The core of Qcover relies on a graph decomposition-based classical algorithm, which efficiently derives the optimal parameters for the shallow QAOA circuit. Quafu-Qcover incorporates a dedicated compiler capable of translating QAOA circuits into physical quantum circuits that can be executed on Quafu cloud quantum computers. Compared to a general-purpose compiler, our compiler demonstrates the ability to generate shorter circuit depths, while also exhibiting superior speed performance. Additionally, the Qcover compiler has the capability to dynamically create a library of qubits coupling substructures in real-time, utilizing the most recent calibration data from the superconducting quantum devices. This ensures that computational tasks can be assigned to connected physical qubits with the highest fidelity. The Quafu-Qcover allows us to retrieve quantum computing sampling results using a task ID at any time, enabling asynchronous processing. Moreover, it incorporates modules for results preprocessing and visualization, facilitating an intuitive display of solutions for combinatorial optimization problems. We hope that Quafu-Qcover can serve as an instructive illustration for how to explore application problems on the Quafu cloud quantum computers.