Dynamic Inhomogeneous Quantum Resource Scheduling with Reinforcement
Learning
Dynamic Inhomogeneous Quantum Resource Scheduling with Reinforcement
Learning
A central challenge in quantum information science and technology is achieving real-time estimation and feedforward control of quantum systems. This challenge is compounded by the inherent inhomogeneity of quantum resources, such as qubit properties and controls, and their intrinsically probabilistic nature. This leads to stochastic challenges in error detection and …