Optimal Path-Finding using Quantum Alternating Operator Ansatz with Grover’s Search for Multi-hop Wireless Sensor Networks

With the development of wireless sensor networks to combat the problem of reaching places otherwise unreachable for humans, there is a need to keep these remote renewable devices charged. Optimizing the network to utilize the minimum amount of energy becomes paramount. With the advent of powerful Quantum Variational Algorithms suited for the current Noisy Intermediate Scale Quantum (NISQ) era of quantum computers, we can exploit the power of these quantum processors to solve classically hard problems. In this paper, we use the Quantum Alternating Operator Ansatz (QAOA) followed by Grover Searching, which amplifies the possible paths to find the optimal path in a multi-hop network. We perform experiments using quantum simulators to obtain useful insights into the algorithm’s performance with respect to various parameters of interest. Our approach involving QAOA and Grover Searching is a useful benchmark for more general and complex optimization problems in remote renewable wireless networks.