XIRAC-Q: a near-real-time quantum operating system scheduling structure based on Shannon information theorem

In the race for quantum computing supremacy, the key factor lies in maximizing the number of stable qubits by far, as each additional qubit doubles the computing power. Namely, it makes sense various ecosystems of organizations and developers gravitate toward these extraordinarily expensive supercomputers. Concurrently, the drive to democratize quantum computing has given rise to cloud-based operating systems built upon classical models. However, a growing demand forecast underscores the need for executing an infinite stream of near-real-time quantum tasks accessible via the cloud. This vacancy represents a potential boundary between quantum and classical operating systems. To address this, a refinement method called XIRAC-Q is introduced, which harnesses the principles of information theory for optimization. By maximizing the entropy toleration of the system, our approach enhances overall performance, particularly as the number of processes and tasks approaches infinity. Unlike the limited literature that has explored information theory principles solely for task priority alignment in classical computers, yielding limited advantage, our work integrates information theory and entropy in the design cycle of quantum operating system infrastructure. This paper highlights the novel advantages offered by the proposed paradigm, encompassing improved performance, scalability, and adaptability, which are thoroughly explained and explored.