In recent years a number of quantum computing devices with small numbers of
qubits became available. We present a hybrid quantum local search (QLS)
approach that combines a classical machine and a small quantum device to solve
problems of practical size. The proposed approach is applied to the network
community detection problem. QLS is hardware-agnostic and easily extendable to
new quantum computing devices as they become available. We demonstrate it to
solve the 2-community detection problem on graphs of size up to 410 vertices
using the 16-qubit IBM quantum computer and D-Wave 2000Q, and compare their
performance with the optimal solutions. Our results demonstrate that QLS
perform similarly in terms of quality of the solution and the number of
iterations to convergence on both types of quantum computers and it is capable
of achieving results comparable to state-of-the-art solvers in terms of quality
of the solution including reaching the optimal solutions.

本研究提出了一种混合的量子局部搜索方法，它将经典计算机和小型量子设备相结合，以解决实际规模的网络社区检测问题，可以在硬件无关的情况下轻松扩展到新的量子计算机设备，并通过比较量子计算机的表现以及达到优化解，证明 QLS 在解决社区检测问题的质量和收敛迭代次数方面表现相似，并具有可比较于最先进求解器的解决方案的能力。