Quantum estimation, control and learning: Opportunities and challenges
Daoyi Dong, Ian R. Petersen
Abstract
The development of estimation and control theories for quantum systems is a fundamental task for practical quantum technology. This vision article presents a brief introduction to challenging problems and potential opportunities in the emerging areas of quantum estimation, control and learning. The topics cover quantum state estimation, quantum parameter identification, quantum filtering, quantum open-loop control, quantum feedback control, machine learning for estimation and control of quantum systems, and quantum machine learning.
Topics & Concepts
Quantum technologyQuantum sensorQuantum phase estimation algorithmQuantum stateComputer scienceOpen quantum systemQuantumQuantum algorithmQuantum networkQuantum computerQuantum error correctionArtificial intelligencePhysicsQuantum mechanicsQuantum Information and CryptographyQuantum Computing Algorithms and ArchitectureQuantum Mechanics and Applications