Optimizing Resource Allocation in a Distributed Quantum Computing Cloud: a Game-Theoretic Approach

Quantum cloud computing will play a vital role in achieving quantum supremacy by providing flexible allocation of resources for applications that demand extensive computational power. Such a platform allows various clients to run their quantum jobs (quantum circuits) without managing the quantum hardware and to pay based on resource usage. Therefore, defining optimal quantum resource allocation is essential to prevent overcharging clients and to help quantum cloud providers maximize resource utilization. Our approach involves examining the problem from a game theory perspective. We introduce a quantum circuit partitioning resource allocation game model (QC-PRAGM) designed to minimize client costs and inter-node communication. This is achieved by solving a convex optimization problem that finds the system's optimal cost while maximizing the number of local gates within a partition through the selection of the best qubit combinations. We demonstrate analytically that clients are charged fairly. Additionally, our simulations show that our solutions outperform traditional methods.